From f1041f4ed8cb1d3715a58bb5962446a75122f77f Mon Sep 17 00:00:00 2001
From: fawda123 <mbafs2012@gmail.com>
Date: Sat, 12 Oct 2024 18:01:59 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20tbep-tec?=
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---
 articles/fib.html                        |   6 +-
 articles/intro.html                      | 192 +++++++++++------------
 articles/seagrasstransect.html           |   8 +-
 articles/tbbi.html                       |   8 +-
 articles/tbni.html                       |   6 +-
 articles/tidalcreeks.html                |   4 +-
 pkgdown.yml                              |   2 +-
 reference/show_annualassess.html         |   4 +-
 reference/show_matrixplotly.html         |   2 +-
 reference/show_ratab.html                |   2 +-
 reference/show_sedimentpelaveplotly.html |   2 +-
 reference/show_segplotly.html            |   2 +-
 reference/show_tbniscrplotly.html        |   2 +-
 reference/show_tdlcrkindic.html          |   2 +-
 reference/show_tdlcrkindiccdf.html       |   2 +-
 reference/show_transectsum.html          |   2 +-
 search.json                              |   2 +-
 17 files changed, 124 insertions(+), 124 deletions(-)

diff --git a/articles/fib.html b/articles/fib.html
index 4e44dbb8..0216bed3 100644
--- a/articles/fib.html
+++ b/articles/fib.html
@@ -437,7 +437,7 @@ <h4 id="show">Show<a class="anchor" aria-label="anchor" href="#show"></a>
 <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_fibmatrix.html">show_fibmatrix</a></span><span class="op">(</span><span class="va">fibdata</span>, plotly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
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","data:image/png;base64,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","data:image/png;base64,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","data:image/png;base64,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 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_fibmatrix.html">show_fibmatrix</a></span><span class="op">(</span><span class="va">mancofibdata</span>, plotly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
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index 9f9174fb..0111b8f9 100644
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+++ b/articles/intro.html
@@ -560,7 +560,7 @@ <h3 id="show">Show<a class="anchor" aria-label="anchor" href="#show"></a>
 <div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_matrix.html">show_matrix</a></span><span class="op">(</span><span class="va">epcdata</span>, plotly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
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Outcomes can be
 returned in tabular format with <code><a href="../reference/anlz_yrattain.html">anlz_yrattain()</a></code>. This table
 also shows segment averages for chlorophyll and light attenuation,
 including the associated targets.</p>
@@ -627,7 +627,7 @@ <h3 id="show">Show<a class="anchor" aria-label="anchor" href="#show"></a>
 <div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_segplotly.html">show_segplotly</a></span><span class="op">(</span><span class="va">epcdata</span>, width <span class="op">=</span> <span class="fl">1000</span>, height <span class="op">=</span> <span class="fl">600</span><span class="op">)</span></span></code></pre></div>
 <div id="htmlwidget-36aa3d2a04d42bbc2145" style="width:1000px;height:600px;" class="plotly html-widget"></div>
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Ann. Light Atten. 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Chl-a (ug/L)","font":{"color":"rgba(0,0,0,1)","family":"","size":14.611872146118724}},"hoverformat":".2f"},"annotations":[],"shapes":[{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":1,"y0":0.62,"y1":1},{"type":"rect","fillcolor":"transparent","line":{"color":"rgba(51,51,51,1)","width":0.66417600664176002,"linetype":"solid"},"yref":"paper","xref":"paper","x0":0,"x1":1,"y0":0.41999999999999993,"y1":0.57999999999999996},{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":1,"y0":0,"y1":0.37999999999999989}],"images":[],"margin":{"t":28.176560121765604,"r":7.3059360730593621,"b":26.752021793168243,"l":48.949771689497723},"plot_bgcolor":"rgba(236,236,236,1)","paper_bgcolor":"rgba(255,255,255,1)","font":{"color":"rgba(0,0,0,1)","family":"","size":14.611872146118724},"showlegend":true,"legend":{"bgcolor":"transparent","bordercolor":"transparent","borderwidth":1.8897637795275593,"font":{"color":"rgba(0,0,0,1)","family":"","size":11.68949771689498},"title":""},"hovermode":"closest","width":1000,"height":600,"barmode":"relative"},"attrs":{"22a86b5335df":{"x":{},"y":{},"colour":{},"type":"scatter"},"22a823c62ff3":{"x":{},"y":{},"colour":{}},"22a820faa01b":{"yintercept":{},"colour":{}},"22a86f0552c":{"yintercept":{},"colour":{}},"22a813f7e3c3":{"yintercept":{},"colour":{}},"22a868c6f7e7":{"x":{},"y":{},"fill":{},"type":"scatter"},"22a8ef1612e":{"x":{},"y":{},"colour":{},"type":"scatter"},"22a86594dddb":{"x":{},"y":{},"colour":{}},"22a814373803":{"yintercept":{},"colour":{}},"22a8eda51":{"yintercept":{},"colour":{}},"22a87d43fc31":{"yintercept":{},"colour":{}}},"source":"A","config":{"doubleClick":"reset","modeBarButtonsToAdd":["hoverclosest","hovercompare"],"showSendToCloud":false,"toImageButtonOptions":{"format":"svg","filename":"myplot"}},"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.20000000000000001,"selected":{"opacity":1},"debounce":0},"subplot":true,"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script><p>From these plots, we can quickly view a summary of the environmental
 history of water quality in Tampa Bay. Degraded conditions were common
 early in the period of record, particularly for Old Tampa Bay and
 Hillsborough Bay. Conditions began to improve by the late 1980s and
@@ -658,50 +658,50 @@ <h4 id="reasonable-assurance-reporting">Reasonable Assurance reporting<a class="
 <div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_annualassess.html">show_annualassess</a></span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span><span class="op">)</span></span></code></pre></div>
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-<table data-quarto-disable-processing="true" class="table cl-bdb63196">
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+<table data-quarto-disable-processing="true" class="table cl-c9ca6726">
 <thead>
 <tr style="overflow-wrap:break-word;">
-<th class="cl-bdb2e590"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92">Segment</span></p></th>
-<th colspan="2" class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">Chl-a (ug/L)</span></p></th>
-<th colspan="2" class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">Light Penetration (m</span><span class="cl-bdb04f9c">-1</span><span class="cl-bdb04f92">)</span></p></th>
+<th class="cl-c9c6fea6"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6">Segment</span></p></th>
+<th colspan="2" class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">Chl-a (ug/L)</span></p></th>
+<th colspan="2" class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">Light Penetration (m</span><span class="cl-c9c46100">-1</span><span class="cl-c9c460f6">)</span></p></th>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<th class="cl-bdb2e590"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92"></span></p></th>
-<th class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">2023</span></p></th>
-<th class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">target</span></p></th>
-<th class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">2023</span></p></th>
-<th class="cl-bdb2e59a"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">target</span></p></th>
+<th class="cl-c9c6fea6"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6"></span></p></th>
+<th class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">2023</span></p></th>
+<th class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">target</span></p></th>
+<th class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">2023</span></p></th>
+<th class="cl-c9c6feb0"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">target</span></p></th>
 </tr>
 </thead>
 <tbody>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdb2e59b"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92">OTB</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">6.2</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">8.5</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.73</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.83</span></p></td>
+<td class="cl-c9c6feba"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6">OTB</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">6.2</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">8.5</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.73</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.83</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdb2e59b"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92">HB</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">6.9</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">13.2</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.79</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">1.58</span></p></td>
+<td class="cl-c9c6feba"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6">HB</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">6.9</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">13.2</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.79</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">1.58</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdb2e59b"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92">MTB</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">3.7</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">7.4</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.47</span></p></td>
-<td class="cl-bdb2e5a4"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.83</span></p></td>
+<td class="cl-c9c6feba"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6">MTB</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">3.7</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">7.4</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.47</span></p></td>
+<td class="cl-c9c6febb"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.83</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdb2e5ae"><p class="cl-bdb2cb3c"><span class="cl-bdb04f92">LTB</span></p></td>
-<td class="cl-bdb2e5af"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">2.6</span></p></td>
-<td class="cl-bdb2e5af"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">4.6</span></p></td>
-<td class="cl-bdb2e5af"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.54</span></p></td>
-<td class="cl-bdb2e5af"><p class="cl-bdb2cb46"><span class="cl-bdb04f92">0.63</span></p></td>
+<td class="cl-c9c6fec4"><p class="cl-c9c6e3ee"><span class="cl-c9c460f6">LTB</span></p></td>
+<td class="cl-c9c6fec5"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">2.6</span></p></td>
+<td class="cl-c9c6fec5"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">4.6</span></p></td>
+<td class="cl-c9c6fec5"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.54</span></p></td>
+<td class="cl-c9c6fec5"><p class="cl-c9c6e3f8"><span class="cl-c9c460f6">0.63</span></p></td>
 </tr>
 </tbody>
 </table>
@@ -711,51 +711,51 @@ <h4 id="reasonable-assurance-reporting">Reasonable Assurance reporting<a class="
 <div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_annualassess.html">show_annualassess</a></span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span>, caption <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
 <div class="tabwid">
-<style>.cl-bdf28042{}.cl-bdec55be{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-bdec55c8{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-bdee93ba{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-bdee93c4{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-bdeeabca{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bdeeabd4{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bdeeabde{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bdeeabdf{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bdeeabe8{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bdeeabe9{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-bde8f59a{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}</style>
-<table data-quarto-disable-processing="true" class="table cl-bdf28042">
-<caption style="display:table-caption;margin:0pt;text-align:center;border-bottom: 0.00pt solid transparent;border-top: 0.00pt solid transparent;border-left: 0.00pt solid transparent;border-right: 0.00pt solid transparent;padding-top:3pt;padding-bottom:3pt;padding-left:3pt;padding-right:3pt;line-height: 1;background-color:transparent;"><span class="cl-bde8f59a">Water quality outcomes for 2023.</span></caption>
+<style>.cl-ca0783b8{}.cl-ca0128ec{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ca0128f6{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-ca036a26{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ca036a30{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ca0382ae{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ca0382b8{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ca0382b9{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ca0382c2{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ca0382cc{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ca0382d6{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c9fdc42c{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}</style>
+<table data-quarto-disable-processing="true" class="table cl-ca0783b8">
+<caption style="display:table-caption;margin:0pt;text-align:center;border-bottom: 0.00pt solid transparent;border-top: 0.00pt solid transparent;border-left: 0.00pt solid transparent;border-right: 0.00pt solid transparent;padding-top:3pt;padding-bottom:3pt;padding-left:3pt;padding-right:3pt;line-height: 1;background-color:transparent;"><span class="cl-c9fdc42c">Water quality outcomes for 2023.</span></caption>
 <thead>
 <tr style="overflow-wrap:break-word;">
-<th class="cl-bdeeabca"><p class="cl-bdee93ba"><span class="cl-bdec55be">Segment</span></p></th>
-<th colspan="2" class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">Chl-a (ug/L)</span></p></th>
-<th colspan="2" class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">Light Penetration (m</span><span class="cl-bdec55c8">-1</span><span class="cl-bdec55be">)</span></p></th>
+<th class="cl-ca0382ae"><p class="cl-ca036a26"><span class="cl-ca0128ec">Segment</span></p></th>
+<th colspan="2" class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">Chl-a (ug/L)</span></p></th>
+<th colspan="2" class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">Light Penetration (m</span><span class="cl-ca0128f6">-1</span><span class="cl-ca0128ec">)</span></p></th>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<th class="cl-bdeeabca"><p class="cl-bdee93ba"><span class="cl-bdec55be"></span></p></th>
-<th class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">2023</span></p></th>
-<th class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">target</span></p></th>
-<th class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">2023</span></p></th>
-<th class="cl-bdeeabd4"><p class="cl-bdee93c4"><span class="cl-bdec55be">target</span></p></th>
+<th class="cl-ca0382ae"><p class="cl-ca036a26"><span class="cl-ca0128ec"></span></p></th>
+<th class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">2023</span></p></th>
+<th class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">target</span></p></th>
+<th class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">2023</span></p></th>
+<th class="cl-ca0382b8"><p class="cl-ca036a30"><span class="cl-ca0128ec">target</span></p></th>
 </tr>
 </thead>
 <tbody>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdeeabde"><p class="cl-bdee93ba"><span class="cl-bdec55be">OTB</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">6.2</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">8.5</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.73</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.83</span></p></td>
+<td class="cl-ca0382b9"><p class="cl-ca036a26"><span class="cl-ca0128ec">OTB</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">6.2</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">8.5</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.73</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.83</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdeeabde"><p class="cl-bdee93ba"><span class="cl-bdec55be">HB</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">6.9</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">13.2</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.79</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">1.58</span></p></td>
+<td class="cl-ca0382b9"><p class="cl-ca036a26"><span class="cl-ca0128ec">HB</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">6.9</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">13.2</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.79</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">1.58</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdeeabde"><p class="cl-bdee93ba"><span class="cl-bdec55be">MTB</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">3.7</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">7.4</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.47</span></p></td>
-<td class="cl-bdeeabdf"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.83</span></p></td>
+<td class="cl-ca0382b9"><p class="cl-ca036a26"><span class="cl-ca0128ec">MTB</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">3.7</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">7.4</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.47</span></p></td>
+<td class="cl-ca0382c2"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.83</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-bdeeabe8"><p class="cl-bdee93ba"><span class="cl-bdec55be">LTB</span></p></td>
-<td class="cl-bdeeabe9"><p class="cl-bdee93c4"><span class="cl-bdec55be">2.6</span></p></td>
-<td class="cl-bdeeabe9"><p class="cl-bdee93c4"><span class="cl-bdec55be">4.6</span></p></td>
-<td class="cl-bdeeabe9"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.54</span></p></td>
-<td class="cl-bdeeabe9"><p class="cl-bdee93c4"><span class="cl-bdec55be">0.63</span></p></td>
+<td class="cl-ca0382cc"><p class="cl-ca036a26"><span class="cl-ca0128ec">LTB</span></p></td>
+<td class="cl-ca0382d6"><p class="cl-ca036a30"><span class="cl-ca0128ec">2.6</span></p></td>
+<td class="cl-ca0382d6"><p class="cl-ca036a30"><span class="cl-ca0128ec">4.6</span></p></td>
+<td class="cl-ca0382d6"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.54</span></p></td>
+<td class="cl-ca0382d6"><p class="cl-ca036a30"><span class="cl-ca0128ec">0.63</span></p></td>
 </tr>
 </tbody>
 </table>
@@ -770,50 +770,50 @@ <h4 id="reasonable-assurance-reporting">Reasonable Assurance reporting<a class="
 <div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_ratab.html">show_ratab</a></span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span>, bay_segment <span class="op">=</span> <span class="st">'OTB'</span><span class="op">)</span></span></code></pre></div>
 <div class="tabwid">
-<style>.cl-be91d0b6{}.cl-be8c63d8{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-be8c63e2{font-family:'Lato light';font-size:13pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-be8c63ec{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:italic;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-be8e9dba{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-be8e9dc4{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-be8eb750{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb75a{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb764{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb765{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb766{width:0.6in;background-color:rgba(144, 238, 144, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb767{width:0.6in;background-color:rgba(255, 255, 255, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb76e{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-be8eb76f{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style>
-<table data-quarto-disable-processing="true" class="table cl-be91d0b6"><tbody>
+<style>.cl-cae376ac{}.cl-caddb7b2{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-caddb7bc{font-family:'Lato light';font-size:13pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-caddb7bd{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:italic;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-cae0206a{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-cae02074{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-cae03bae{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bb8{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bb9{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bc2{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bcc{width:0.6in;background-color:rgba(144, 238, 144, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bcd{width:0.6in;background-color:rgba(255, 255, 255, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bce{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-cae03bd6{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style>
+<table data-quarto-disable-processing="true" class="table cl-cae376ac"><tbody>
 <tr style="overflow-wrap:break-word;">
-<td rowspan="2" class="cl-be8eb750"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Bay</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Segment</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Reasonable</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Assurance</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Assessment</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Steps</span></p></td>
-<td colspan="5" class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">DATA</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">USED</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">TO</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">ASSESS</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">ANNUAL</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">REASONABLE</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">ASSURANCE</span></p></td>
-<td rowspan="2" class="cl-be8eb764"><p class="cl-be8e9dba"><span class="cl-be8c63d8">OUTCOME</span></p></td>
+<td rowspan="2" class="cl-cae03bae"><p class="cl-cae0206a"><span class="cl-caddb7b2">Bay</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Segment</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Reasonable</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Assurance</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Assessment</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Steps</span></p></td>
+<td colspan="5" class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">DATA</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">USED</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">TO</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">ASSESS</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">ANNUAL</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">REASONABLE</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">ASSURANCE</span></p></td>
+<td rowspan="2" class="cl-cae03bb9"><p class="cl-cae0206a"><span class="cl-caddb7b2">OUTCOME</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Year</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">1</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(2022)</span></p></td>
-<td class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Year</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">2</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(2023)</span></p></td>
-<td class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Year</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">3</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(2024)</span></p></td>
-<td class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Year</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">4</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(2025)</span></p></td>
-<td class="cl-be8eb75a"><p class="cl-be8e9dba"><span class="cl-be8c63d8">Year</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">5</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(2026)</span></p></td>
+<td class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">Year</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">1</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(2022)</span></p></td>
+<td class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">Year</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">2</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(2023)</span></p></td>
+<td class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">Year</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">3</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(2024)</span></p></td>
+<td class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">Year</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">4</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(2025)</span></p></td>
+<td class="cl-cae03bb8"><p class="cl-cae0206a"><span class="cl-caddb7b2">Year</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">5</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(2026)</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-be8eb765"><p class="cl-be8e9dc4"><span class="cl-be8c63e2">NMC</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">Action</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">1:</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Determine</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">if</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">observed</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">chlorophyll-a</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">exceeds</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">FDEP</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">threshold</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">of</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">9.3</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">ug/L</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">No</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(7.1)</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">No</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">(6.2)</span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb76e"><p class="cl-be8e9dc4"><span class="cl-be8c63d8">All</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">years</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">below</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">threshold</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">so</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">far,</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">not</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">necessary</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">for</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">NMC</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Actions</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">2-5</span></p></td>
+<td class="cl-cae03bc2"><p class="cl-cae02074"><span class="cl-caddb7bc">NMC</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">Action</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">1:</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Determine</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">if</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">observed</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">chlorophyll-a</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">exceeds</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">FDEP</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">threshold</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">of</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">9.3</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">ug/L</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">No</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(7.1)</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">No</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">(6.2)</span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bce"><p class="cl-cae02074"><span class="cl-caddb7b2">All</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">years</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">below</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">threshold</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">so</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">far,</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">not</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">necessary</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">for</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">NMC</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Actions</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">2-5</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-be8eb765"><p class="cl-be8e9dc4"><span class="cl-be8c63e2">NMC</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">Action</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">2:</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Determine</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">if</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">any</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">observed</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">chlorophyll-</span><span class="cl-be8c63ec">a</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">exceedences</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">occurred</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">for</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">2</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">consecutive</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">years</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">No</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">No</span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb76e"><p class="cl-be8e9dc4"><span class="cl-be8c63d8">All</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">years</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">met</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">threshold,</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">not</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">necessary</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">for</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">NMC</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Actions</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">3-5</span></p></td>
+<td class="cl-cae03bc2"><p class="cl-cae02074"><span class="cl-caddb7bc">NMC</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">Action</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">2:</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Determine</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">if</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">any</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">observed</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">chlorophyll-</span><span class="cl-caddb7bd">a</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">exceedences</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">occurred</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">for</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">2</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">consecutive</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">years</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">No</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">No</span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bce"><p class="cl-cae02074"><span class="cl-caddb7b2">All</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">years</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">met</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">threshold,</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">not</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">necessary</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">for</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">NMC</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Actions</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">3-5</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td class="cl-be8eb765"><p class="cl-be8e9dc4"><span class="cl-be8c63e2">NMC</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">Action</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">3:</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Determine</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">if</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">observed</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">hydrologically-normalized</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">total</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">load</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">exceeds</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">federally-recognized</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">TMDL</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">of</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">486</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">tons/year</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">N/A</span></p></td>
-<td class="cl-be8eb766"><p class="cl-be8e9dba"><span class="cl-be8c63d8">N/A</span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb767"><p class="cl-be8e9dba"><span class="cl-be8c63d8"></span></p></td>
-<td class="cl-be8eb76e"><p class="cl-be8e9dc4"><span class="cl-be8c63d8">Not</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">necessary</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">due</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">to</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">observed</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">water</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">quality</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">and</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">seagrass</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">conditions</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">in</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">the</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">bay</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">segment</span></p></td>
+<td class="cl-cae03bc2"><p class="cl-cae02074"><span class="cl-caddb7bc">NMC</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">Action</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">3:</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Determine</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">if</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">observed</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">hydrologically-normalized</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">total</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">load</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">exceeds</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">federally-recognized</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">TMDL</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">of</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">486</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">tons/year</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">N/A</span></p></td>
+<td class="cl-cae03bcc"><p class="cl-cae0206a"><span class="cl-caddb7b2">N/A</span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bcd"><p class="cl-cae0206a"><span class="cl-caddb7b2"></span></p></td>
+<td class="cl-cae03bce"><p class="cl-cae02074"><span class="cl-caddb7b2">Not</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">necessary</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">due</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">to</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">observed</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">water</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">quality</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">and</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">seagrass</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">conditions</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">in</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">the</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">bay</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">segment</span></p></td>
 </tr>
 <tr style="overflow-wrap:break-word;">
-<td colspan="6" class="cl-be8eb765"><p class="cl-be8e9dc4"><span class="cl-be8c63e2">NMC</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">Actions</span><span class="cl-be8c63e2"> </span><span class="cl-be8c63e2">4-5:</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">Determine</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">if</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">any</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">entity/source/facility</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">specific</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">exceedences</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">of</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">5-yr</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">average</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">allocation</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">occurred</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">during</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">implementation</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">period</span></p></td>
-<td class="cl-be8eb76e"><p class="cl-be8e9dc4"><span class="cl-be8c63d8">Not</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">necessary</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">when</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">chlorophyll-</span><span class="cl-be8c63ec">a</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">threshold</span><span class="cl-be8c63d8"> </span><span class="cl-be8c63d8">met</span></p></td>
+<td colspan="6" class="cl-cae03bc2"><p class="cl-cae02074"><span class="cl-caddb7bc">NMC</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">Actions</span><span class="cl-caddb7bc"> </span><span class="cl-caddb7bc">4-5:</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">Determine</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">if</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">any</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">entity/source/facility</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">specific</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">exceedences</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">of</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">5-yr</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">average</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">allocation</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">occurred</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">during</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">implementation</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">period</span></p></td>
+<td class="cl-cae03bce"><p class="cl-cae02074"><span class="cl-caddb7b2">Not</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">necessary</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">when</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">chlorophyll-</span><span class="cl-caddb7bd">a</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">threshold</span><span class="cl-caddb7b2"> </span><span class="cl-caddb7b2">met</span></p></td>
 </tr>
 </tbody></table>
 </div>
diff --git a/articles/seagrasstransect.html b/articles/seagrasstransect.html
index 56b68f64..6489c0aa 100644
--- a/articles/seagrasstransect.html
+++ b/articles/seagrasstransect.html
@@ -409,7 +409,7 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_transect.html">show_transect</a></span><span class="op">(</span><span class="va">transect</span>, site <span class="op">=</span> <span class="st">'S3T10'</span>, species <span class="op">=</span> <span class="st">'Halodule'</span>, varplo <span class="op">=</span> <span class="st">'Abundance'</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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 100<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:  120<br />Year: 2022<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:   13<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  200<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2022<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2022<br />val: 0.1<br />name: Halodule","Site:   50<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2022<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   15<br />Year: 2020<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2020<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2020<br />val: 5.0<br />name: Halodule","Site:  200<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2020<br />val: 2.0<br />name: Halodule","Site: 1000<br />Year: 2021<br />val: 0.1<br />name: Halodule","Site:  150<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  175<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  200<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  225<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  250<br />Year: 2021<br />val: 3.0<br />name: Halodule","Site:  275<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  325<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  350<br />Year: 2021<br />val: 3.0<br />name: Halodule","Site:  400<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  425<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  450<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  475<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  500<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  525<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  550<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  625<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  650<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  675<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  700<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  725<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  765<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  770<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  825<br />Year: 2021<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  935<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:   10<br />Year: 2023<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  200<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2000<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2000<br />val: 4.0<br />name: Halodule","Site:  650<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:  850<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  910<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  920<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  940<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  950<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2001<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2001<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2001<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:  775<br />Year: 2001<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2001<br />val: 0.5<br />name: Halodule","Site:  875<br />Year: 2001<br />val: 1.0<br />name: Halodule","Site:  940<br />Year: 2001<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2002<br />val: 4.0<br />name: Halodule","Site:  175<br />Year: 2002<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:   50<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:   75<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  850<br />Year: 2002<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  910<br />Year: 2002<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2002<br />val: 2.0<br />name: Halodule","Site:   10<br />Year: 2003<br />val: 0.1<br />name: Halodule","Site:  100<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  200<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  225<br />Year: 2003<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:  275<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  350<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  525<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:  550<br />Year: 2003<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2004<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  175<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  225<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2004<br />val: 5.0<br />name: Halodule","Site:  270<br />Year: 2004<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2004<br />val: 5.0<br />name: Halodule","Site:  525<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  575<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  672<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  700<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2004<br />val: 3.0<br />name: Halodule","Site:  773<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  800<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  825<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  850<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  930<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site: 1000<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  125<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:   13<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  175<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:   25<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  250<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  323<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  655<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  696<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  724<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  748<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  799<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  825<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site:  850<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  925<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  950<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  998<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  110<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  120<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  130<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  160<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   20<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   30<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   40<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   60<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  670<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  690<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:   70<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  710<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  720<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  740<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  760<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  780<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  790<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:   80<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  800<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  810<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  820<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  830<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  840<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  860<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  880<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  890<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:   90<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  930<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  949<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  850<br />Year: 2007<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2007<br />val: 0.5<br />name: Halodule","Site:  930<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2007<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2008<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:   25<br />Year: 2008<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:  725<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:   75<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  750<br />Year: 2008<br />val: 4.0<br />name: Halodule","Site:  800<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  900<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  125<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2009<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2009<br />val: 3.0<br />name: Halodule","Site:  750<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  800<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  825<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  850<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  900<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:    0<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   10<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  150<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:   20<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  250<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   30<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  300<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   40<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  400<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:  450<br />Year: 2010<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  575<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   60<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   70<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  725<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2010<br />val: 4.0<br />name: Halodule","Site:   80<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  825<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:   90<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   -2<br />Year: 2011<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2011<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  300<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:  325<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   50<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2011<br />val: 3.0<br />name: Halodule","Site:  725<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  750<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  875<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2011<br />val: 3.0<br />name: Halodule","Site:  930<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  962<br />Year: 2011<br />val: 0.1<br />name: Halodule","Site:    0<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2012<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2012<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  300<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2012<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:    0<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2013<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2013<br />val: 1.0<br />name: Halodule","Site:  450<br />Year: 2013<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  580<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  950<br />Year: 2013<br />val: 1.0<br />name: Halodule","Site:  960<br />Year: 2013<br />val: 0.5<br />name: Halodule","Site:    0<br />Year: 2014<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2014<br />val: 1.0<br />name: Halodule","Site:  175<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  200<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  400<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:  550<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  625<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:  750<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2014<br />val: 0.5<br />name: Halodule","Site:  910<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  950<br />Year: 2014<br />val: 2.0<br />name: Halodule","Site:  960<br />Year: 2014<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2015<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2015<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2015<br />val: 4.0<br />name: Halodule","Site:  167<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  200<br />Year: 2015<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  542<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  550<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  645<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  650<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  670<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  675<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  725<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2016<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:  300<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  650<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2017<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2017<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2017<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:  550<br />Year: 2017<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:    0<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2018<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2018<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2018<br />val: 2.0<br />name: Halodule","Site:    0<br />Year: 2019<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2019<br />val: 3.0<br />name: Halodule","Site: 1000<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  125<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  175<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  193<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  200<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   25<br />Year: 2019<br />val: 1.0<br />name: Halodule","Site:  275<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  300<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:  425<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  450<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   50<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  500<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  575<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:  650<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   75<br />Year: 2019<br />val: 3.0<br />name: Halodule","Site:  880<br />Year: 2019<br />val: 0.1<br />name: 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 100<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:  120<br />Year: 2022<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:   13<br />Year: 2022<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  200<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2022<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2022<br />val: 0.1<br />name: Halodule","Site:   50<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2022<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2022<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   15<br />Year: 2020<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2020<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2020<br />val: 5.0<br />name: Halodule","Site:  200<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2020<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2020<br />val: 2.0<br />name: Halodule","Site: 1000<br />Year: 2021<br />val: 0.1<br />name: Halodule","Site:  150<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  175<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  200<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  225<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  250<br />Year: 2021<br />val: 3.0<br />name: Halodule","Site:  275<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  325<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  350<br />Year: 2021<br />val: 3.0<br />name: Halodule","Site:  400<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  425<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  450<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  475<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  500<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  525<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  550<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  625<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  650<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  675<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  700<br />Year: 2021<br />val: 5.0<br />name: Halodule","Site:  725<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  765<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  770<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  825<br />Year: 2021<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2021<br />val: 4.0<br />name: Halodule","Site:  935<br />Year: 2021<br />val: 2.0<br />name: Halodule","Site:   10<br />Year: 2023<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  200<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2023<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2000<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2000<br />val: 4.0<br />name: Halodule","Site:  650<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:  850<br />Year: 2000<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  910<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  920<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  940<br />Year: 2000<br />val: 5.0<br />name: Halodule","Site:  950<br />Year: 2000<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2001<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2001<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2001<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2001<br />val: 2.0<br />name: Halodule","Site:  775<br />Year: 2001<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2001<br />val: 0.5<br />name: Halodule","Site:  875<br />Year: 2001<br />val: 1.0<br />name: Halodule","Site:  940<br />Year: 2001<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2002<br />val: 4.0<br />name: Halodule","Site:  175<br />Year: 2002<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:   50<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:   75<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  850<br />Year: 2002<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2002<br />val: 5.0<br />name: Halodule","Site:  910<br />Year: 2002<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2002<br />val: 2.0<br />name: Halodule","Site:   10<br />Year: 2003<br />val: 0.1<br />name: Halodule","Site:  100<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  200<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  225<br />Year: 2003<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:  275<br />Year: 2003<br />val: 5.0<br />name: Halodule","Site:  350<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  525<br />Year: 2003<br />val: 2.0<br />name: Halodule","Site:  550<br />Year: 2003<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2003<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2004<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  175<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  225<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2004<br />val: 5.0<br />name: Halodule","Site:  270<br />Year: 2004<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2004<br />val: 5.0<br />name: Halodule","Site:  525<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  575<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  672<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  700<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2004<br />val: 3.0<br />name: Halodule","Site:  773<br />Year: 2004<br />val: 0.1<br />name: Halodule","Site:  800<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  825<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  850<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2004<br />val: 2.0<br />name: Halodule","Site:  930<br />Year: 2004<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site: 1000<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  125<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:   13<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  175<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:   25<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  250<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  323<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  655<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  696<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  724<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  748<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2005<br />val: 5.0<br />name: Halodule","Site:  799<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  825<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site:  850<br />Year: 2005<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2005<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  925<br />Year: 2005<br />val: 0.5<br />name: Halodule","Site:  950<br />Year: 2005<br />val: 0.1<br />name: Halodule","Site:  998<br />Year: 2005<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  110<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  120<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  130<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  160<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   20<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   30<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   40<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:   60<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  670<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  690<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:   70<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  710<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  720<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  740<br />Year: 2006<br />val: 5.0<br />name: Halodule","Site:  760<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  780<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  790<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:   80<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  800<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  810<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  820<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  830<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  840<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  850<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  860<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  880<br />Year: 2006<br />val: 4.0<br />name: Halodule","Site:  890<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:   90<br />Year: 2006<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  930<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2006<br />val: 1.0<br />name: Halodule","Site:  949<br />Year: 2006<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  850<br />Year: 2007<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2007<br />val: 3.0<br />name: Halodule","Site:  900<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2007<br />val: 0.5<br />name: Halodule","Site:  930<br />Year: 2007<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2007<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2008<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:   25<br />Year: 2008<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:  725<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:   75<br />Year: 2008<br />val: 5.0<br />name: Halodule","Site:  750<br />Year: 2008<br />val: 4.0<br />name: Halodule","Site:  800<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  900<br />Year: 2008<br />val: 2.0<br />name: Halodule","Site:  940<br />Year: 2008<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  125<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  150<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:   25<br />Year: 2009<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:   75<br />Year: 2009<br />val: 3.0<br />name: Halodule","Site:  750<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  800<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:  825<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  850<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  900<br />Year: 2009<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2009<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:    0<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   10<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  150<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:   20<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  250<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   30<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  300<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  325<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:  350<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   40<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  400<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:  450<br />Year: 2010<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  575<br />Year: 2010<br />val: 0.1<br />name: Halodule","Site:   60<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   70<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  725<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2010<br />val: 4.0<br />name: Halodule","Site:   80<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:  825<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:   90<br />Year: 2010<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2010<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2010<br />val: 3.0<br />name: Halodule","Site:   -2<br />Year: 2011<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2011<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  175<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  300<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:  325<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   50<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  675<br />Year: 2011<br />val: 3.0<br />name: Halodule","Site:  725<br />Year: 2011<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  750<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  825<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  875<br />Year: 2011<br />val: 5.0<br />name: Halodule","Site:  900<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  925<br />Year: 2011<br />val: 3.0<br />name: Halodule","Site:  930<br />Year: 2011<br />val: 2.0<br />name: Halodule","Site:  962<br />Year: 2011<br />val: 0.1<br />name: Halodule","Site:    0<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2012<br />val: 5.0<br />name: Halodule","Site:  150<br />Year: 2012<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  300<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2012<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  675<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2012<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2012<br />val: 3.0<br />name: Halodule","Site:    0<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  125<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  150<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2013<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2013<br />val: 1.0<br />name: Halodule","Site:  450<br />Year: 2013<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  580<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  725<br />Year: 2013<br />val: 2.0<br />name: Halodule","Site:  750<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2013<br />val: 3.0<br />name: Halodule","Site:  950<br />Year: 2013<br />val: 1.0<br />name: Halodule","Site:  960<br />Year: 2013<br />val: 0.5<br />name: Halodule","Site:    0<br />Year: 2014<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  125<br />Year: 2014<br />val: 1.0<br />name: Halodule","Site:  175<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  200<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:   25<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  300<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  400<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:  550<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  625<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2014<br />val: 3.0<br />name: Halodule","Site:  750<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  875<br />Year: 2014<br />val: 0.5<br />name: Halodule","Site:  910<br />Year: 2014<br />val: 4.0<br />name: Halodule","Site:  950<br />Year: 2014<br />val: 2.0<br />name: Halodule","Site:  960<br />Year: 2014<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2015<br />val: 0.5<br />name: Halodule","Site:  100<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2015<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2015<br />val: 4.0<br />name: Halodule","Site:  167<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  200<br />Year: 2015<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:   25<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  300<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  350<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:   50<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  542<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  550<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  645<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  650<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  670<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  675<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:  725<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2015<br />val: 3.0<br />name: Halodule","Site:  800<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  875<br />Year: 2015<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2015<br />val: 1.0<br />name: Halodule","Site:    0<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  125<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2016<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:  300<br />Year: 2016<br />val: 1.0<br />name: Halodule","Site:   50<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  650<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:   75<br />Year: 2016<br />val: 3.0<br />name: Halodule","Site:  875<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:  950<br />Year: 2016<br />val: 2.0<br />name: Halodule","Site:  100<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2017<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2017<br />val: 2.0<br />name: Halodule","Site:  175<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:   25<br />Year: 2017<br />val: 0.5<br />name: Halodule","Site:   50<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:  550<br />Year: 2017<br />val: 3.0<br />name: Halodule","Site:   75<br />Year: 2017<br />val: 5.0<br />name: Halodule","Site:    0<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:  100<br />Year: 2018<br />val: 5.0<br />name: Halodule","Site:  125<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:  175<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:   25<br />Year: 2018<br />val: 3.0<br />name: Halodule","Site:   50<br />Year: 2018<br />val: 4.0<br />name: Halodule","Site:   75<br />Year: 2018<br />val: 5.0<br />name: Halodule","Site:  800<br />Year: 2018<br />val: 2.0<br />name: Halodule","Site:    0<br />Year: 2019<br />val: 1.0<br />name: Halodule","Site:  100<br />Year: 2019<br />val: 3.0<br />name: Halodule","Site: 1000<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  125<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  150<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  175<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  193<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  200<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  225<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   25<br />Year: 2019<br />val: 1.0<br />name: Halodule","Site:  275<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  300<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:  425<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  450<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   50<br />Year: 2019<br />val: 4.0<br />name: Halodule","Site:  500<br />Year: 2019<br />val: 0.5<br />name: Halodule","Site:  575<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:  650<br />Year: 2019<br />val: 0.1<br />name: Halodule","Site:   75<br />Year: 2019<br />val: 3.0<br />name: Halodule","Site:  880<br />Year: 2019<br />val: 0.1<br />name: 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 multiple species. One to many species can be provided to the
 <code>species</code> argument.</p>
 <div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
@@ -431,7 +431,7 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_transectsum.html">show_transectsum</a></span><span class="op">(</span><span class="va">transectocc</span>, site <span class="op">=</span> <span class="st">'S3T10'</span><span class="op">)</span></span></code></pre></div>
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summary matrix of frequency occurrence estimates across all species
+<script type="application/json" data-for="htmlwidget-36aa3d2a04d42bbc2145">{"x":{"visdat":{"23034cfce325":["function () ","plotlyVisDat"]},"cur_data":"23034cfce325","attrs":{"23034cfce325":{"alpha_stroke":1,"sizes":[10,100],"spans":[1,20],"x":{},"y":{},"type":"scatter","mode":"markers","color":{},"colors":["#ED90A4","#CCA65A","#7EBA68","#00C1B2","#D400FF","#6FB1E7"],"stackgroup":"one","marker":{"opacity":0,"size":0},"inherit":true}},"layout":{"margin":{"b":40,"l":60,"t":25,"r":10},"yaxis":{"domain":[0,1],"automargin":true,"title":"Frequency 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summary matrix of frequency occurrence estimates across all species
 can be plotted with <code><a href="../reference/show_transectmatrix.html">show_transectmatrix()</a></code>. This uses
 results from the <code><a href="../reference/anlz_transectocc.html">anlz_transectocc()</a></code> and
 <code><a href="../reference/anlz_transectave.html">anlz_transectave()</a></code> functions to estimate annual averages by
@@ -452,7 +452,7 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_transectmatrix.html">show_transectmatrix</a></span><span class="op">(</span><span class="va">transectocc</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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Bay","OTB","HB","MTB","LTB","BCB"]}},"config":{"doubleClick":"reset","modeBarButtonsToAdd":["hoverclosest","hovercompare"],"showSendToCloud":false,"toImageButtonOptions":{"format":"svg","filename":"myplot"}},"source":"A","attrs":{"230313b9845d":{"x":{},"y":{},"fill":{},"type":"scatter"},"23035c99f9d0":{"xintercept":{}},"2303cf0cab4":{"x":{},"y":{},"fill":{},"label":{}},"230313b9845d.1":{"x":["Tampa Bay","OTB","HB","MTB","LTB","BCB"],"y":[1,2,3,4,5,6],"type":"bar","xaxis":"x2","showlegend":false,"inherit":false}},"cur_data":"230313b9845d","visdat":{"230313b9845d":["function (y) ","x"],"23035c99f9d0":["function (y) ","x"],"2303cf0cab4":["function (y) 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 estimates by each species can be shown with the
 <code><a href="../reference/show_transectavespp.html">show_transectavespp()</a></code> function. By default, all estimates
 are averaged across all bay segments for each species. The plot is a
@@ -472,7 +472,7 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_transectavespp.html">show_transectavespp</a></span><span class="op">(</span><span class="va">transectocc</span>, bay_segment <span class="op">=</span> <span class="st">'LTB'</span>, species <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">'Syringodium'</span>, <span class="st">'Thalassia'</span><span class="op">)</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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","x"],"236657d9d8d4":["function (y) ","x"]},"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.20000000000000001,"selected":{"opacity":1},"debounce":0},"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script><p>As an alternative to plotting the species averages over time with
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","x"],"23035e97c032":["function (y) ","x"]},"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.20000000000000001,"selected":{"opacity":1},"debounce":0},"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script><p>As an alternative to plotting the species averages over time with
 <code><a href="../reference/show_transectavespp.html">show_transectavespp()</a></code>, a table can be created by setting
 <code>asreact = TRUE</code>. Filtering options that apply to the plot
 also apply to the table, e.g., filtering by the four major bay segments
diff --git a/articles/tbbi.html b/articles/tbbi.html
index f01d77c3..70ea0b78 100644
--- a/articles/tbbi.html
+++ b/articles/tbbi.html
@@ -291,7 +291,7 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_tbbimatrix.html">show_tbbimatrix</a></span><span class="op">(</span><span class="va">tbbiscr</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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 <div class="section level3">
 <h3 id="additional-sediment-data">Additional sediment data<a class="anchor" aria-label="anchor" href="#additional-sediment-data"></a>
@@ -409,7 +409,7 @@ <h3 id="additional-sediment-data">Additional sediment data<a class="anchor" aria
 <div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
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(mg/kg)","font":{"color":"rgba(0,0,0,1)","family":null,"size":15.940224159402243}},"hoverformat":".2f"},"shapes":[{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":1,"y0":0,"y1":1}],"showlegend":true,"legend":{"bgcolor":"rgba(255,255,255,1)","bordercolor":"transparent","borderwidth":2.0615604867573372,"font":{"color":"rgba(0,0,0,1)","family":null,"size":12.7521793275218},"title":{"text":"","font":{"color":null,"family":null,"size":0}},"traceorder":"reversed","orientation":"h","xanchor":"center","x":0.5,"y":1.1000000000000001},"hovermode":"closest","barmode":"relative"},"config":{"doubleClick":"reset","modeBarButtonsToAdd":["hoverclosest","hovercompare"],"showSendToCloud":false,"toImageButtonOptions":{"format":"svg","filename":"myplot"}},"source":"A","attrs":{"235323014488":{"x":{},"y":{},"type":"scatter"},"235347fdfe03":{"x":{},"y":{},"ymin":{},"ymax":{}},"23533bea9aa0":{"yintercept":{},"colour":{},"linetype":{}},"2353323a9e04":{"yintercept":{},"colour":{},"linetype":{}},"2353413e72f8":{"yintercept":{},"colour":{},"linetype":{}}},"cur_data":"235323014488","visdat":{"235323014488":["function (y) ","x"],"235347fdfe03":["function (y) ","x"],"23533bea9aa0":["function (y) ","x"],"2353323a9e04":["function (y) ","x"],"2353413e72f8":["function (y) ","x"]},"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.20000000000000001,"selected":{"opacity":1},"debounce":0},"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script><p>The values used in the plot can be returned with
 <code><a href="../reference/anlz_sedimentave.html">anlz_sedimentave()</a></code>.</p>
 <div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/anlz_sedimentave.html">anlz_sedimentave</a></span><span class="op">(</span><span class="va">sedimentdata</span>, param <span class="op">=</span> <span class="st">'Arsenic'</span>, yrrng <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1993</span>, <span class="fl">2022</span><span class="op">)</span><span class="op">)</span></span>
@@ -451,7 +451,7 @@ <h3 id="additional-sediment-data">Additional sediment data<a class="anchor" aria
 <div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_sedimentpelave.html">show_sedimentpelave</a></span><span class="op">(</span><span class="va">sedimentdata</span>, yrrng <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1993</span>, <span class="fl">2022</span><span class="op">)</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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 <code><a href="../reference/anlz_sedimentpelave.html">anlz_sedimentpelave()</a></code>.</p>
 <div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/anlz_sedimentpelave.html">anlz_sedimentpelave</a></span><span class="op">(</span><span class="va">sedimentdata</span>, yrrng <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1993</span>, <span class="fl">2022</span><span class="op">)</span><span class="op">)</span></span>
@@ -481,7 +481,7 @@ <h3 id="additional-sediment-data">Additional sediment data<a class="anchor" aria
 <div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_sedimentalratio.html">show_sedimentalratio</a></span><span class="op">(</span><span class="va">sedimentdata</span>, param <span class="op">=</span> <span class="st">'Zinc'</span>, bay_segment <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">'HB'</span>, <span class="st">'LTB'</span><span class="op">)</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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32184.000<br />param:  127.389<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4262.000<br />param:   24.492<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13535.000<br />param:   63.291<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27978.000<br />param:  112.734<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5553.000<br />param:   17.699<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   229.000<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12697.000<br />param:  376.892<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1103.000<br />param:    3.740<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35573.000<br />param:  108.652<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2743.000<br />param:   17.699<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   415.000<br />param:    3.606<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   284.000<br />param:    3.784<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    9.852<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   811.000<br />param:    6.954<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 48714.000<br />param:  193.956<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18253.450<br />param:  521.996<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37142.860<br />param:  207.792<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5864.040<br />param:   36.326<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14369.230<br />param:   70.769<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    7.246<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.375<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15050.070<br />param:   62.947<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.246<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9896.680<br />param:   35.345<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3164.560<br />param:   20.138<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12800.710<br />param:   62.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.603<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1264.420<br />param:   15.528<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5978.370<br />param:   21.632<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.441<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   193.720<br />param:    6.457<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27477.140<br />param:   79.071<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    6.616<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    5.627<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2318.710<br />param:   11.366<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17376.000<br />param:  368.257<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12560.000<br />param:   21.198<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44366.000<br />param:  202.729<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14157.000<br />param:   15.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12911.000<br />param:   45.814<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    6.727<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 26929.000<br />param:  353.001<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   509.000<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8361.000<br />param:   63.345<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9700.000<br />param:   22.822<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11985.000<br />param:   29.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1505.000<br />param:   73.504<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11359.000<br />param:   58.339<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19174.000<br />param:  135.604<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    47.000<br />param:   28.477<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:   65.163<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1510.570<br />param:    8.056<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18190.640<br />param:   50.476<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2931.600<br />param:    8.143<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   796.650<br />param:   21.908<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2203.280<br />param:    4.157<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1897.960<br />param:   10.204<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   490.970<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3624.320<br />param:   11.691<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3451.720<br />param:  313.248<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5557.760<br />param:   25.804<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 40206.800<br />param:  109.366<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19555.370<br />param:  249.074<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 41396.100<br />param:   87.256<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   869.040<br />param:    2.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23973.990<br />param:   73.141<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2807.090<br />param:    5.973<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4982.140<br />param:   31.759<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24381.260<br />param:   85.907<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1012.110<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15855.930<br />param:   41.399<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6101.770<br />param:   10.781<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6540.170<br />param:   16.149<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3964.300<br />param:    8.302<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1514.000<br />param:    6.271<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1879.000<br />param:    6.891<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17250.000<br />param:   74.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2300.000<br />param:   11.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6513.000<br />param:   18.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5063.000<br />param:   20.460<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1257.000<br />param:    4.856<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1405.000<br />param:    7.101<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    15.400<br />param:   16.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1516.000<br />param:    5.244<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2672.000<br />param:    6.860<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2957.000<br />param:    7.604<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 31230.000<br />param:   78.910<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 21460.000<br />param:   42.110<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2126.000<br />param:    8.765<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35690.000<br />param:   89.830<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 42860.000<br />param:  388.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1249.000<br />param:    4.902<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10050.000<br />param:   26.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1337.000<br />param:    5.519<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7196.000<br />param:   18.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7563.000<br />param:   16.540<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 49005.832<br />param:  169.539<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13720.174<br />param:   54.024<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1242.758<br />param:    4.876<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 20147.874<br />param:   42.017<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1163.618<br />param:    5.589<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35691.180<br />param:   83.739<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1995.007<br />param:    6.917<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27663.273<br />param:   57.114<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   958.914<br />param:    7.756<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6226.436<br />param:   18.566<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39604.167<br />param:   70.385<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5074.345<br />param:   13.083<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3418.530<br />param:   10.937<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3282.839<br />param:   10.095<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10869.710<br />param:   28.684<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 33202.333<br />param:  108.963<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   852.194<br />param:    4.832<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    13.682<br />param:    9.186<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2669.586<br />param:   10.817<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4213.850<br />param:   10.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1982.243<br />param:   10.754<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   857.074<br />param:    5.252<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27642.276<br />param:   84.762<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10233.858<br />param:   32.660<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1740.733<br />param:    5.450<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37847.079<br />param:  112.392<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 34016.422<br />param:   96.228<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 46587.292<br />param:  128.620<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37463.050<br />param:   93.333<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 45243.122<br />param:  107.916<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44953.234<br />param:  105.119<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 36720.164<br />param:   76.911<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39187.544<br />param:   80.582<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 52442.580<br />param:  117.960<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44434.450<br />param:  208.968<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2939.076<br />param:   10.489<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1444.554<br />param:    3.338<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4010.643<br />param:    8.439<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 32181.951<br />param:  167.585<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2802.720<br />param:    9.182<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1987.046<br />param:    5.616<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1378.924<br />param:   15.269<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14380.579<br />param:   38.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7025.862<br />param:   21.667<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4679.724<br />param:   13.686<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12219.017<br />param:   36.607<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1391.532<br />param:   10.209<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4413.802<br />param:   18.907<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12876.191<br />param:  470.696<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10379.837<br />param:   34.908<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3281.956<br />param:   10.581<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15667.844<br />param:   57.753<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2877.037<br />param:   11.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12414.483<br />param:   47.703<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5944.163<br />param:   31.900<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:   15.802<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19814.984<br />param:   67.375<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24669.671<br />param:   79.497<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3236.928<br />param:   10.362<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3100.587<br />param:   11.208<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2818.775<br />param:   13.607<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1051.178<br />param:    6.171<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18948.944<br />param:  133.334<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1854.259<br />param:    6.422<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3605.617<br />param:   16.075<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16378.832<br />param:   88.027<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1272.795<br />param:    6.784<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1078.048<br />param:    6.337<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3862.314<br />param:   11.661<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12055.930<br />param:   39.857<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11855.800<br />param:   40.795<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   876.120<br />param:    3.947<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.165<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8101.529<br />param:   17.785<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2576.414<br />param:   12.453<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12837.925<br />param:   88.766<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2228.554<br />param:    5.029<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1896.303<br />param:    2.927<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1992.915<br />param:    3.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5839.321<br />param:   16.696<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16187.748<br />param:  164.123<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1438.131<br />param:    2.656<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17668.669<br />param:   71.239<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14744.157<br />param:   97.788<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1390.946<br />param:    4.158<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1492.379<br />param:    2.215<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1045.362<br />param:    2.879<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2630.018<br />param:    7.828<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14638.271<br />param:  184.134<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24556.268<br />param:   94.600<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   635.748<br />param:    1.521<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2063.092<br />param:    7.365<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   826.707<br />param:    2.496<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1050.806<br />param:    2.916<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1091.386<br />param:    5.124<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18771.346<br />param:   95.466<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2634.581<br />param:    6.654<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2483.576<br />param:    7.989<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1892.563<br />param:    4.596<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18567.346<br />param:   43.261<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35308.374<br />param:   83.549<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 21255.484<br />param:   64.177<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2084.699<br />param:    5.430<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4015.608<br />param:    8.194<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3482.766<br />param:   12.796<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10005.812<br />param:   30.531<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1983.986<br />param:    7.587<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39947.084<br />param:  385.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7301.650<br />param:   26.305<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 38606.705<br />param:  125.456<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 22988.650<br />param:   74.866<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 48317.759<br />param:  106.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23301.643<br />param:   87.778<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4829.056<br />param:    9.001<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1837.786<br />param:    7.398<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1116.333<br />param:    3.373<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2627.657<br />param:    9.175<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3313.481<br />param:   21.392<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4940.032<br />param:   14.768<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1055.110<br />param:    7.665<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5683.264<br />param:   15.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3102.896<br />param:    8.386<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 31104.223<br />param:   82.655<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1903.281<br />param:    5.389<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9542.662<br />param:   24.151<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1183.886<br />param:    4.143<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2529.418<br />param:   10.206<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16744.907<br />param:   45.668<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1033.457<br />param:    2.594<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1987.528<br />param:    5.635<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5080.363<br />param:   14.867<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4347.880<br />param:   11.910<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14960.965<br />param:   35.586<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1939.394<br />param:    7.713<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1055.329<br />param:    3.934<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15982.549<br />param:   43.477<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 38550.591<br />param:  196.740<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5435.273<br />param:   32.615<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 26372.522<br />param:   80.772<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19778.615<br />param:   61.940<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2568.130<br />param:    6.990<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2696.274<br />param:    7.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1997.376<br />param:    7.498<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   820.028<br />param:    2.883<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2944.010<br />param:    5.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25590.000<br />param:  101.960<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7772.280<br />param:   15.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23920.000<br />param:   27.210<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4022.320<br />param:    7.220<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1439.250<br />param:    5.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25231.350<br />param:   55.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8156.740<br />param:   12.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6905.380<br />param:  169.400<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9388.160<br />param:   22.340<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7109.340<br />param:   16.320<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6684.020<br />param:   36.970<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8057.890<br />param:   16.890<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6825.000<br />param:   12.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2709.270<br />param:    4.100<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2391.420<br />param:    2.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1154.750<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   692.300<br />param:    0.250<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9034.470<br />param:   36.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15400.080<br />param:   89.150<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   549.690<br />param:    9.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10908.460<br />param:   30.340<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3797.610<br />param:   14.110<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1544.300<br />param:    2.200<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2073.900<br />param:   12.090<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3152.230<br />param:   10.430<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2808.280<br />param:    8.590<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    22.325<br />param:   11.730<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8356.760<br />param:   34.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1695.280<br />param:   17.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   599.820<br />param:   10.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1871.680<br />param:   11.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2252.090<br />param:   13.820<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1420.100<br />param:   11.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4398.600<br />param:   17.030<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13871.300<br />param:   29.550<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6171.030<br />param:   23.380<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3990.310<br />param:   24.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2913.650<br />param:   14.590<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5632.510<br />param:   22.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16554.910<br />param:   31.450<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1796.740<br />param:   10.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4397.970<br />param:   26.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3530.330<br />param:   16.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3403.350<br />param:   13.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16285.040<br />param:   63.290<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18941.560<br />param:   71.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   392.440<br />param:    2.530<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14165.940<br />param:   52.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3466.580<br />param:    6.670<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    46.875<br />param: 1227.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1588.720<br />param:    3.090<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 20447.460<br />param:  114.190<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3276.100<br />param:    9.270<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2350.710<br />param:    7.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12699.930<br />param:   45.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8172.880<br />param:   28.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6687.320<br />param:   21.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4924.490<br />param:   11.710<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3234.290<br />param:    8.070<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5208.540<br />param:   14.640<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1563.510<br />param:    5.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4000.870<br />param:    7.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3284.770<br />param:   13.260<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2886.310<br />param:    9.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19482.960<br />param:   51.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1428.100<br />param:    4.480<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    42.500<br />param:   11.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3029.720<br />param:    7.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1336.970<br />param:    3.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1489.760<br />param:    5.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3278.080<br />param:    6.080<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24654.550<br />param:  104.440<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14376.210<br />param:   61.020<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25981.900<br />param:  119.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1384.410<br />param:    5.210<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10891.960<br />param:   41.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10711.560<br />param:   47.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1224.440<br />param:    8.310<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    32.600<br />param:   10.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4404.900<br />param:   10.500<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1018.690<br />param:    3.170<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   838.370<br />param:    3.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4534.800<br />param:   26.980<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1232.130<br />param:    1.660<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5023.810<br />param:   34.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16374.220<br />param:   80.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 43093.730<br />param:  229.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3739.930<br />param:    9.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11116.490<br />param:  201.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9559.510<br />param:   39.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1476.780<br />param:    8.730<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4506.180<br />param:   11.600<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2471.350<br />param:    2.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8737.050<br />param:   37.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   159.380<br />param:   54.530<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8179.610<br />param:   33.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   142.570<br />param:   57.880<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   125.450<br />param:   70.190<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   189.500<br />param:   51.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   117.170<br />param:   36.550<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   607.580<br />param:    3.410<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2740.800<br />param:   10.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   956.710<br />param:    5.790<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   691.160<br />param:  782.290<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   317.090<br />param:   12.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   588.850<br />param:   50.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7779.340<br />param:   38.080<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5149.080<br />param:   42.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1094.920<br />param:    4.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1314.420<br />param:    3.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   438.840<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   236.490<br />param:    7.650<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1251.510<br />param:   17.990<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6376.780<br />param:   50.220<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1951.550<br />param:    8.890<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10990.530<br />param:   45.260<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   507.730<br />param:    7.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1821.360<br />param:   14.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   295.270<br />param:    6.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3437.730<br />param:   19.180<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6132.060<br />param:   60.670<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9035.970<br />param:   97.640<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1074.580<br />param:   20.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5691.840<br />param:   56.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  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   0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2790.000<br />param:    2.007<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2474.000<br />param:    2.334<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2576.000<br />param:    4.727<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   678.540<br />param:   14.136<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.370<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.586<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:   11.413<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    8.251<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    6.911<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.894<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.006<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    8.651<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.269<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.714<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.736<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.901<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1486.450<br />param:    2.915<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    9.518<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.137<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:   12.542<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3162.000<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   909.630<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6576.330<br />param:    7.971<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1915.710<br />param:    4.033<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1639.990<br />param:    3.952<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1967.730<br />param:    3.935<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   217.180<br />param:    1.974<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4100.130<br />param:    4.316<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   881.230<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   708.500<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1380.000<br />param:    2.000<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1207.000<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2808.490<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1282.310<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   636.290<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1719.550<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   466.820<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   287.200<br />param:    3.452<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   187.400<br />param:    3.827<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   726.200<br />param:    4.753<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3275.000<br />param:    5.396<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   147.600<br />param:    2.903<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   131.900<br />param:    2.434<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4109.000<br />param:    3.147<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   155.500<br />param:    2.769<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3102.000<br />param:    6.810<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1646.000<br />param:    3.460<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1989.000<br />param:    6.330<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   856.000<br />param:    4.500<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   816.000<br />param:    3.290<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    42.600<br />param:    6.230<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   795.000<br />param:    4.090<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    18.000<br />param:    8.650<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   364.300<br />param:    2.582<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2612.809<br />param:    9.471<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1090.747<br />param:    6.330<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   593.576<br />param:    3.655<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    13.179<br />param:   11.656<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1172.002<br />param:    3.353<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   782.951<br />param:    4.882<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2944.066<br />param:    7.568<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   851.132<br />param:    3.626<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.000<br />param:    0.000<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   852.109<br />param:    2.783<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5263.700<br />param:    7.623<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   518.945<br />param:    3.113<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2929.158<br />param:    5.625<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3056.245<br />param:    9.843<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   683.683<br />param:    4.489<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1456.507<br />param:    3.592<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1038.283<br />param:    3.089<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6507.398<br />param:    5.233<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   602.688<br />param:    2.693<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   537.306<br />param:    2.870<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   689.070<br />param:    9.441<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   729.903<br />param:    4.817<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.904<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1833.140<br />param:    6.311<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2958.811<br />param:    6.905<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   602.242<br />param:    2.056<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1820.267<br />param:    6.530<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3740.938<br />param:    7.522<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.137<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3112.807<br />param:    5.691<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1065.343<br />param:    5.352<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1393.442<br />param:    4.099<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   932.070<br />param:    5.045<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    4.470<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   757.860<br />param:    6.763<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   354.368<br />param:    2.864<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.270<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   622.248<br />param:    1.234<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    1.878<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.465<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2470.551<br />param:    8.510<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3919.187<br />param:    3.755<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   885.409<br />param:    1.620<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3180.716<br />param:    4.366<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3210.491<br />param:    6.746<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3307.181<br />param:    3.486<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    6.172<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   868.557<br />param:    3.867<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2602.336<br />param:    3.875<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  8110.616<br />param:    4.807<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   932.243<br />param:    4.172<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2159.053<br />param:    4.410<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3892.890<br />param:   10.684<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   263.211<br />param:    1.404<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   717.431<br />param:    2.171<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4319.253<br />param:    4.064<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.265<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   210.447<br />param:    1.529<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1528.931<br />param:    3.355<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.581<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   117.842<br />param:    3.992<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1413.720<br />param:    1.861<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2313.950<br />param:    3.550<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2038.750<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    4.930<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   700.090<br />param:    8.790<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    15.650<br />param:    1.590<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   654.870<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:    4.150<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   976.090<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   474.810<br />param:    8.490<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   185.090<br />param:    8.170<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   922.730<br />param:    4.970<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:   13.790<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3181.660<br />param:    8.430<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   633.020<br />param:    7.370<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1284.840<br />param:   13.190<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    46.875<br />param:   18.780<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1380.670<br />param:   11.630<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   768.500<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1731.580<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   583.780<br />param:    1.535<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    42.500<br />param:    1.535<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1830.990<br />param:    3.810<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1566.950<br />param:    1.290<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4223.620<br />param:    3.690<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6217.790<br />param:    5.880<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1716.850<br />param:    1.050<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5212.570<br />param:    4.280<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5060.340<br />param:    5.450<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5128.640<br />param:    4.200<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1089.320<br />param:    2.540<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4017.990<br />param:    3.500<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5616.320<br />param:    2.780<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4519.660<br />param:    2.420<br />AreaAbbr: LTB<br 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15.400<br />fit:  1.30424361","Aluminum:    15.650<br />fit:  1.31171107","Aluminum:    18.000<br />fit:  1.37841168","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    32.600<br />fit:  1.70148818","Aluminum:    42.500<br />fit:  1.86922227","Aluminum:    42.500<br />fit:  1.86922227","Aluminum:    42.600<br />fit:  1.87078038","Aluminum:    46.875<br />fit:  1.93529489","Aluminum:    46.875<br />fit:  1.93529489","Aluminum:    47.000<br />fit:  1.93712298","Aluminum:    47.400<br />fit:  1.94295189","Aluminum:    53.000<br />fit:  2.02141745","Aluminum:    74.400<br />fit:  2.27969973","Aluminum:    97.810<br />fit:  2.51188528","Aluminum:   117.170<br />fit:  2.67797755","Aluminum:   117.842<br />fit:  2.68341273","Aluminum:   125.450<br />fit:  2.74359707","Aluminum:   131.900<br />fit:  2.79280088","Aluminum:   142.570<br />fit:  2.87089480","Aluminum:   147.600<br />fit:  2.90640349","Aluminum:   155.500<br />fit:  2.96062880","Aluminum:   159.380<br />fit:  2.98661111","Aluminum:   185.090<br />fit:  3.14923647","Aluminum:   187.400<br />fit:  3.16311521","Aluminum:   189.500<br />fit:  3.17563673","Aluminum:   191.200<br />fit:  3.18570776","Aluminum:   193.720<br />fit:  3.20053079","Aluminum:   210.447<br />fit:  3.29589937","Aluminum:   217.180<br />fit:  3.33290489","Aluminum:   221.700<br />fit:  3.35733380","Aluminum:   229.000<br />fit:  3.39611763","Aluminum:   236.490<br />fit:  3.43509011","Aluminum:   244.300<br />fit:  3.47488819","Aluminum:   247.300<br />fit:  3.48995710","Aluminum:   247.740<br />fit:  3.49215727","Aluminum:   263.211<br />fit:  3.56796683","Aluminum:   284.000<br />fit:  3.66543448","Aluminum:   285.630<br />fit:  3.67287920","Aluminum:   287.200<br />fit:  3.68002400","Aluminum:   291.780<br />fit:  3.70072382","Aluminum:   295.270<br />fit:  3.71635689","Aluminum:   310.900<br />fit:  3.78494387","Aluminum:   317.090<br />fit:  3.81149093","Aluminum:   344.600<br />fit:  3.92559170","Aluminum:   350.290<br />fit:  3.94845079","Aluminum:   354.368<br />fit:  3.96468675","Aluminum:   364.300<br />fit:  4.00373136","Aluminum:   367.700<br />fit:  4.01693938","Aluminum:   368.000<br />fit:  4.01810100","Aluminum:   384.500<br />fit:  4.08107124","Aluminum:   385.400<br />fit:  4.08445539","Aluminum:   392.440<br />fit:  4.11075256","Aluminum:   400.000<br />fit:  4.13865525","Aluminum:   402.290<br />fit:  4.14704001","Aluminum:   415.000<br />fit:  4.19302604","Aluminum:   435.400<br />fit:  4.26497155","Aluminum:   438.840<br />fit:  4.27688777","Aluminum:   458.000<br />fit:  4.34217901","Aluminum:   466.820<br />fit:  4.37164276","Aluminum:   474.810<br />fit:  4.39802521","Aluminum:   490.970<br />fit:  4.45052130","Aluminum:   491.110<br />fit:  4.45097118","Aluminum:   506.170<br />fit:  4.49889037","Aluminum:   507.730<br />fit:  4.50380124","Aluminum:   509.000<br />fit:  4.50779200","Aluminum:   516.000<br />fit:  4.52967381","Aluminum:   518.945<br />fit:  4.53882254","Aluminum:   537.306<br />fit:  4.59511912","Aluminum:   549.690<br />fit:  4.63239178","Aluminum:   583.780<br />fit:  4.73227214","Aluminum:   585.800<br />fit:  4.73807102","Aluminum:   588.850<br />fit:  4.74680234","Aluminum:   593.576<br />fit:  4.76027413","Aluminum:   599.820<br />fit:  4.77796733","Aluminum:   600.000<br />fit:  4.77847562","Aluminum:   602.242<br />fit:  4.78479839","Aluminum:   602.688<br />fit:  4.78605436","Aluminum:   607.580<br />fit:  4.79979142","Aluminum:   608.200<br />fit:  4.80152732","Aluminum:   622.248<br />fit:  4.84055700","Aluminum:   630.000<br />fit:  4.86185134","Aluminum:   633.020<br />fit:  4.87010134","Aluminum:   635.748<br />fit:  4.87753185","Aluminum:   636.290<br />fit:  4.87900569","Aluminum:   639.840<br />fit:  4.88863911","Aluminum:   654.870<br />fit:  4.92904727","Aluminum:   678.540<br />fit:  4.99148771","Aluminum:   683.683<br />fit:  5.00486808","Aluminum:   689.070<br />fit:  5.01881378","Aluminum:   690.000<br />fit:  5.02121420","Aluminum:   691.160<br />fit:  5.02420535","Aluminum:   692.300<br />fit:  5.02714178","Aluminum:   700.000<br />fit:  5.04689426","Aluminum:   700.090<br />fit:  5.04712430","Aluminum:   704.500<br />fit:  5.05837306","Aluminum:   708.500<br />fit:  5.06853676","Aluminum:   717.431<br />fit:  5.09109686","Aluminum:   724.300<br />fit:  5.10832523","Aluminum:   726.200<br />fit:  5.11307205","Aluminum:   729.903<br />fit:  5.12230036","Aluminum:   742.770<br />fit:  5.15413350","Aluminum:   756.970<br />fit:  5.18885401","Aluminum:   757.450<br />fit:  5.19002029","Aluminum:   757.860<br />fit:  5.19101611","Aluminum:   759.500<br />fit:  5.19499590","Aluminum:   768.500<br />fit:  5.21673808","Aluminum:   773.110<br />fit:  5.22781129","Aluminum:   775.800<br />fit:  5.23425299","Aluminum:   781.000<br />fit:  5.24666458","Aluminum:   782.951<br />fit:  5.25130756","Aluminum:   786.460<br />fit:  5.25963948","Aluminum:   791.690<br />fit:  5.27201342","Aluminum:   795.000<br />fit:  5.27981748","Aluminum:   796.650<br />fit:  5.28369989","Aluminum:   811.000<br />fit:  5.31724827","Aluminum:   816.000<br />fit:  5.32884753","Aluminum:   820.028<br />fit:  5.33815858","Aluminum:   826.707<br />fit:  5.35353278","Aluminum:   838.370<br />fit:  5.38018841","Aluminum:   851.132<br />fit:  5.40908295","Aluminum:   852.109<br />fit:  5.41128342","Aluminum:   852.194<br />fit:  5.41147479","Aluminum:   856.000<br />fit:  5.42003092","Aluminum:   857.074<br />fit:  5.42244090","Aluminum:   865.660<br />fit:  5.44163753","Aluminum:   868.557<br />fit:  5.44808692","Aluminum:   869.040<br />fit:  5.44916084","Aluminum:   873.000<br />fit:  5.45795114","Aluminum:   876.120<br />fit:  5.46485873","Aluminum:   881.230<br />fit:  5.47613789","Aluminum:   883.240<br />fit:  5.48056294","Aluminum:   885.409<br />fit:  5.48533075","Aluminum:   891.670<br />fit:  5.49905127","Aluminum:   900.000<br />fit:  5.51720978","Aluminum:   900.000<br />fit:  5.51720978","Aluminum:   909.630<br />fit:  5.53806747","Aluminum:   922.500<br />fit:  5.56572135","Aluminum:   922.730<br />fit:  5.56621328","Aluminum:   932.070<br />fit:  5.58612347","Aluminum:   932.243<br />fit:  5.58649103","Aluminum:   956.710<br />fit:  5.63803826","Aluminum:   958.914<br />fit:  5.64263970","Aluminum:   963.190<br />fit:  5.65154755","Aluminum:   965.100<br />fit:  5.65551825","Aluminum:   976.090<br />fit:  5.67826739","Aluminum:  1000.000<br />fit:  5.72719576","Aluminum:  1000.000<br />fit:  5.72719576","Aluminum:  1003.810<br />fit:  5.73492239","Aluminum:  1012.110<br />fit:  5.75168939","Aluminum:  1018.690<br />fit:  5.76491881","Aluminum:  1030.410<br />fit:  5.78834652","Aluminum:  1033.457<br />fit:  5.79440912","Aluminum:  1038.283<br />fit:  5.80398784","Aluminum:  1045.362<br />fit:  5.81798648","Aluminum:  1047.000<br />fit:  5.82121688","Aluminum:  1050.806<br />fit:  5.82871036","Aluminum:  1051.178<br />fit:  5.82944184","Aluminum:  1055.110<br />fit:  5.83716326","Aluminum:  1055.329<br />fit:  5.83759277","Aluminum:  1055.500<br />fit:  5.83792810","Aluminum:  1065.343<br />fit:  5.85717151","Aluminum:  1074.580<br />fit:  5.87512606","Aluminum:  1078.048<br />fit:  5.88184131","Aluminum:  1089.320<br />fit:  5.90357197","Aluminum:  1090.747<br />fit:  5.90631264","Aluminum:  1091.386<br />fit:  5.90753914","Aluminum:  1094.920<br />fit:  5.91431396","Aluminum:  1103.000<br />fit:  5.92975080","Aluminum:  1116.333<br />fit:  5.95506469","Aluminum:  1123.390<br />fit:  5.96838411","Aluminum:  1132.000<br />fit:  5.98456173","Aluminum:  1154.750<br />fit:  6.02692881","Aluminum:  1163.618<br />fit:  6.04329762","Aluminum:  1172.002<br />fit:  6.05869916","Aluminum:  1183.886<br />fit:  6.08040888","Aluminum:  1202.900<br />fit:  6.11485304","Aluminum:  1207.000<br />fit:  6.12223412","Aluminum:  1224.440<br />fit:  6.15345115","Aluminum:  1232.130<br />fit:  6.16712484","Aluminum:  1242.758<br />fit:  6.18593226","Aluminum:  1249.000<br />fit:  6.19692981","Aluminum:  1251.510<br />fit:  6.20134209","Aluminum:  1257.000<br />fit:  6.21097298","Aluminum:  1264.420<br />fit:  6.22394654","Aluminum:  1272.795<br />fit:  6.23853098","Aluminum:  1282.310<br />fit:  6.25502567","Aluminum:  1284.840<br />fit:  6.25939824","Aluminum:  1300.000<br />fit:  6.28548336","Aluminum:  1300.000<br />fit:  6.28548336","Aluminum:  1314.420<br />fit:  6.31011361","Aluminum:  1336.970<br />fit:  6.34828318","Aluminum:  1337.000<br />fit:  6.34833368","Aluminum:  1378.924<br />fit:  6.41820595","Aluminum:  1380.000<br />fit:  6.41998109","Aluminum:  1380.670<br />fit:  6.42108598","Aluminum:  1384.000<br />fit:  6.42657230","Aluminum:  1384.410<br />fit:  6.42724720","Aluminum:  1390.946<br />fit:  6.43798878","Aluminum:  1391.532<br />fit:  6.43895025","Aluminum:  1393.442<br />fit:  6.44208224","Aluminum:  1400.000<br />fit:  6.45281488","Aluminum:  1405.000<br />fit:  6.46097596","Aluminum:  1413.720<br />fit:  6.47516415","Aluminum:  1420.100<br />fit:  6.48550921","Aluminum:  1428.100<br />fit:  6.49843876","Aluminum:  1438.131<br />fit:  6.51458492","Aluminum:  1439.250<br />fit:  6.51638158","Aluminum:  1444.554<br />fit:  6.52488541","Aluminum:  1456.507<br />fit:  6.54397587","Aluminum:  1476.780<br />fit:  6.57612454","Aluminum:  1486.450<br />fit:  6.59135881","Aluminum:  1489.760<br />fit:  6.59655873","Aluminum:  1492.379<br />fit:  6.60066784","Aluminum:  1497.000<br />fit:  6.60790665","Aluminum:  1500.000<br />fit:  6.61259845","Aluminum:  1505.000<br />fit:  6.62040467","Aluminum:  1510.570<br />fit:  6.62908111","Aluminum:  1514.000<br />fit:  6.63441378","Aluminum:  1516.000<br />fit:  6.63751961","Aluminum:  1528.931<br />fit:  6.65753682","Aluminum:  1534.980<br />fit:  6.66686318","Aluminum:  1537.150<br />fit:  6.67020310","Aluminum:  1544.300<br />fit:  6.68118645","Aluminum:  1563.510<br />fit:  6.71053390","Aluminum:  1566.950<br />fit:  6.71576464","Aluminum:  1582.670<br />fit:  6.73957405","Aluminum:  1588.720<br />fit:  6.74869666","Aluminum:  1600.000<br />fit:  6.76564571","Aluminum:  1600.000<br />fit:  6.76564571","Aluminum:  1603.200<br />fit:  6.77043991","Aluminum:  1639.990<br />fit:  6.82511974","Aluminum:  1646.000<br />fit:  6.83397675","Aluminum:  1669.150<br />fit:  6.86789945","Aluminum:  1695.280<br />fit:  6.90582600","Aluminum:  1698.000<br />fit:  6.90975222","Aluminum:  1700.000<br />fit:  6.91263656","Aluminum:  1700.000<br />fit:  6.91263656","Aluminum:  1716.850<br />fit:  6.93685059","Aluminum:  1719.550<br />fit:  6.94071631","Aluminum:  1731.580<br />fit:  6.95789276","Aluminum:  1740.733<br />fit:  6.97090991","Aluminum:  1764.700<br />fit:  7.00478713","Aluminum:  1777.400<br />fit:  7.02261823","Aluminum:  1796.740<br />fit:  7.04961477","Aluminum:  1820.267<br />fit:  7.08220422","Aluminum:  1821.360<br />fit:  7.08371161","Aluminum:  1830.990<br />fit:  7.09696748","Aluminum:  1833.140<br />fit:  7.09992084","Aluminum:  1837.786<br />fit:  7.10629523","Aluminum:  1845.800<br />fit:  7.11726617","Aluminum:  1854.259<br />fit:  7.12881300","Aluminum:  1871.680<br />fit:  7.15248660","Aluminum:  1879.000<br />fit:  7.16239140","Aluminum:  1884.050<br />fit:  7.16921011","Aluminum:  1892.563<br />fit:  7.18067806","Aluminum:  1896.303<br />fit:  7.18570573","Aluminum:  1897.960<br />fit:  7.18793118","Aluminum:  1903.281<br />fit:  7.19506914","Aluminum:  1915.710<br />fit:  7.21169222","Aluminum:  1918.000<br />fit:  7.21474737","Aluminum:  1939.394<br />fit:  7.24317654","Aluminum:  1951.550<br />fit:  7.25923980","Aluminum:  1967.730<br />fit:  7.28052060","Aluminum:  1982.243<br />fit:  7.29951300","Aluminum:  1983.986<br />fit:  7.30178792","Aluminum:  1987.046<br />fit:  7.30577866","Aluminum:  1987.528<br />fit:  7.30640690","Aluminum:  1989.000<br />fit:  7.30832491","Aluminum:  1992.915<br />fit:  7.31342169","Aluminum:  1995.007<br />fit:  7.31614252","Aluminum:  1997.376<br />fit:  7.31922140","Aluminum:  2019.460<br />fit:  7.34781022","Aluminum:  2032.000<br />fit:  7.36395411","Aluminum:  2038.750<br />fit:  7.37261739","Aluminum:  2063.092<br />fit:  7.40370624","Aluminum:  2073.900<br />fit:  7.41743399","Aluminum:  2084.699<br />fit:  7.43110427","Aluminum:  2126.000<br />fit:  7.48296890","Aluminum:  2159.053<br />fit:  7.52400932","Aluminum:  2203.280<br />fit:  7.57829450","Aluminum:  2228.554<br />fit:  7.60900108","Aluminum:  2252.090<br />fit:  7.63739460","Aluminum:  2275.670<br />fit:  7.66564978","Aluminum:  2277.000<br />fit:  7.66723784","Aluminum:  2295.000<br />fit:  7.68867169","Aluminum:  2300.000<br />fit:  7.69460627","Aluminum:  2313.950<br />fit:  7.71111984","Aluminum:  2318.710<br />fit:  7.71673987","Aluminum:  2350.710<br />fit:  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2647.810<br />fit:  8.08852376","Aluminum:  2669.586<br />fit:  8.11204542","Aluminum:  2672.000<br />fit:  8.11464530","Aluminum:  2696.274<br />fit:  8.14070455","Aluminum:  2698.230<br />fit:  8.14279780","Aluminum:  2709.270<br />fit:  8.15459415","Aluminum:  2737.840<br />fit:  8.18497813","Aluminum:  2740.800<br />fit:  8.18811435","Aluminum:  2743.000<br />fit:  8.19044390","Aluminum:  2763.000<br />fit:  8.21156658","Aluminum:  2790.000<br />fit:  8.23992623","Aluminum:  2802.720<br />fit:  8.25322540","Aluminum:  2807.090<br />fit:  8.25778539","Aluminum:  2808.280<br />fit:  8.25902633","Aluminum:  2808.490<br />fit:  8.25924528","Aluminum:  2818.775<br />fit:  8.26995593","Aluminum:  2847.260<br />fit:  8.29948872","Aluminum:  2877.037<br />fit:  8.33015786","Aluminum:  2886.310<br />fit:  8.33966683","Aluminum:  2900.000<br />fit:  8.35366921","Aluminum:  2913.650<br />fit:  8.36758827","Aluminum:  2929.158<br />fit:  8.38335097","Aluminum:  2931.600<br />fit:  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15.400<br />upr:   98.827633","Aluminum:    15.650<br />upr:   99.391610","Aluminum:    18.000<br />upr:  104.429043","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    32.600<br />upr:  128.827153","Aluminum:    42.500<br />upr:  141.493734","Aluminum:    42.500<br />upr:  141.493734","Aluminum:    42.600<br />upr:  141.611397","Aluminum:    46.875<br />upr:  146.483290","Aluminum:    46.875<br />upr:  146.483290","Aluminum:    47.000<br />upr:  146.621341","Aluminum:    47.400<br />upr:  147.061519","Aluminum:    53.000<br />upr:  152.986999","Aluminum:    74.400<br />upr:  172.492313","Aluminum:    97.810<br />upr:  190.027981","Aluminum:   117.170<br />upr:  202.572845","Aluminum:   117.842<br />upr:  202.983374","Aluminum:   125.450<br />upr:  207.529270","Aluminum:   131.900<br />upr:  211.245857","Aluminum:   142.570<br />upr:  217.144798","Aluminum:   147.600<br />upr:  219.827063","Aluminum:   155.500<br />upr:  223.923229","Aluminum:   159.380<br />upr:  225.885959","Aluminum:   185.090<br />upr:  238.171362","Aluminum:   187.400<br />upr:  239.219862","Aluminum:   189.500<br />upr:  240.165834","Aluminum:   191.200<br />upr:  240.926680","Aluminum:   193.720<br />upr:  242.046538","Aluminum:   210.447<br />upr:  249.251675","Aluminum:   217.180<br />upr:  252.047544","Aluminum:   221.700<br />upr:  253.893243","Aluminum:   229.000<br />upr:  256.823556","Aluminum:   236.490<br />upr:  259.768178","Aluminum:   244.300<br />upr:  262.775235","Aluminum:   247.300<br />upr:  263.913825","Aluminum:   247.740<br />upr:  264.080068","Aluminum:   263.211<br />upr:  269.808285","Aluminum:   284.000<br />upr:  277.173315","Aluminum:   285.630<br />upr:  277.735881","Aluminum:   287.200<br />upr:  278.275786","Aluminum:   291.780<br />upr:  279.840001","Aluminum:   295.270<br />upr:  281.021349","Aluminum:   310.900<br />upr:  286.204390","Aluminum:   317.090<br />upr:  288.210569","Aluminum:   344.600<br />upr:  296.833547","Aluminum:   350.290<br />upr:  298.561145","Aluminum:   354.368<br />upr:  299.788206","Aluminum:   364.300<br />upr:  302.739111","Aluminum:   367.700<br />upr:  303.737357","Aluminum:   368.000<br />upr:  303.825152","Aluminum:   384.500<br />upr:  308.584462","Aluminum:   385.400<br />upr:  308.840241","Aluminum:   392.440<br />upr:  310.827838","Aluminum:   400.000<br />upr:  312.936813","Aluminum:   402.290<br />upr:  313.570566","Aluminum:   415.000<br />upr:  317.046419","Aluminum:   435.400<br />upr:  322.484584","Aluminum:   438.840<br />upr:  323.385318","Aluminum:   458.000<br />upr:  328.320710","Aluminum:   466.820<br />upr:  330.547941","Aluminum:   474.810<br />upr:  332.542279","Aluminum:   490.970<br />upr:  336.510715","Aluminum:   491.110<br />upr:  336.544725","Aluminum:   506.170<br />upr:  340.167266","Aluminum:   507.730<br />upr:  340.538517","Aluminum:   509.000<br />upr:  340.840212","Aluminum:   516.000<br />upr:  342.494445","Aluminum:   518.945<br />upr:  343.186082","Aluminum:   537.306<br />upr:  347.442132","Aluminum:   549.690<br />upr:  350.260032","Aluminum:   583.780<br />upr:  357.811488","Aluminum:   585.800<br />upr:  358.249925","Aluminum:   588.850<br />upr:  358.910077","Aluminum:   593.576<br />upr:  359.928650","Aluminum:   599.820<br />upr:  361.266405","Aluminum:   600.000<br />upr:  361.304836","Aluminum:   602.242<br />upr:  361.782894","Aluminum:   602.688<br />upr:  361.877857","Aluminum:   607.580<br />upr:  362.916507","Aluminum:   608.200<br />upr:  363.047758","Aluminum:   622.248<br />upr:  365.998811","Aluminum:   630.000<br />upr:  367.608911","Aluminum:   633.020<br />upr:  368.232712","Aluminum:   635.748<br />upr:  368.794552","Aluminum:   636.290<br />upr:  368.905993","Aluminum:   639.840<br />upr:  369.634404","Aluminum:   654.870<br />upr:  372.689824","Aluminum:   678.540<br />upr:  377.411317","Aluminum:   683.683<br />upr:  378.423107","Aluminum:   689.070<br />upr:  379.477652","Aluminum:   690.000<br />upr:  379.659168","Aluminum:   691.160<br />upr:  379.885354","Aluminum:   692.300<br />upr:  380.107402","Aluminum:   700.000<br />upr:  381.601064","Aluminum:   700.090<br />upr:  381.618460","Aluminum:   704.500<br />upr:  382.469086","Aluminum:   708.500<br />upr:  383.237666","Aluminum:   717.431<br />upr:  384.943675","Aluminum:   724.300<br />upr:  386.246509","Aluminum:   726.200<br />upr:  386.605472","Aluminum:   729.903<br />upr:  387.303337","Aluminum:   742.770<br />upr:  389.710652","Aluminum:   756.970<br />upr:  392.336365","Aluminum:   757.450<br />upr:  392.424565","Aluminum:   757.860<br />upr:  392.499873","Aluminum:   759.500<br />upr:  392.800845","Aluminum:   768.500<br />upr:  394.445110","Aluminum:   773.110<br />upr:  395.282536","Aluminum:   775.800<br />upr:  395.769699","Aluminum:   781.000<br />upr:  396.708350","Aluminum:   782.951<br />upr:  397.059486","Aluminum:   786.460<br />upr:  397.689609","Aluminum:   791.690<br />upr:  398.625424","Aluminum:   795.000<br />upr:  399.215632","Aluminum:   796.650<br />upr:  399.509253","Aluminum:   811.000<br />upr:  402.046494","Aluminum:   816.000<br />upr:  402.923749","Aluminum:   820.028<br />upr:  403.627949","Aluminum:   826.707<br />upr:  404.790716","Aluminum:   838.370<br />upr:  406.806732","Aluminum:   851.132<br />upr:  408.992112","Aluminum:   852.109<br />upr:  409.158542","Aluminum:   852.194<br />upr:  409.173016","Aluminum:   856.000<br />upr:  409.820148","Aluminum:   857.074<br />upr:  410.002425","Aluminum:   865.660<br />upr:  411.454351","Aluminum:   868.557<br />upr:  411.942151","Aluminum:   869.040<br />upr:  412.023377","Aluminum:   873.000<br />upr:  412.688234","Aluminum:   876.120<br />upr:  413.210693","Aluminum:   881.230<br />upr:  414.063803","Aluminum:   883.240<br />upr:  414.398498","Aluminum:   885.409<br />upr:  414.759117","Aluminum:   891.670<br />upr:  415.796894","Aluminum:   900.000<br />upr:  417.170357","Aluminum:   900.000<br />upr:  417.170357","Aluminum:   909.630<br />upr:  418.747994","Aluminum:   922.500<br />upr:  420.839710","Aluminum:   922.730<br />upr:  420.876919","Aluminum:   932.070<br />upr:  422.382927","Aluminum:   932.243<br />upr:  422.410730","Aluminum:   956.710<br />upr:  426.309838","Aluminum:   958.914<br />upr:  426.657903","Aluminum:   963.190<br />upr:  427.331717","Aluminum:   965.100<br />upr:  427.632074","Aluminum:   976.090<br />upr:  429.352901","Aluminum:  1000.000<br />upr:  433.054087","Aluminum:  1000.000<br />upr:  433.054087","Aluminum:  1003.810<br />upr:  433.638576","Aluminum:  1012.110<br />upr:  434.906942","Aluminum:  1018.690<br />upr:  435.907711","Aluminum:  1030.410<br />upr:  437.679966","Aluminum:  1033.457<br />upr:  438.138593","Aluminum:  1038.283<br />upr:  438.863210","Aluminum:  1045.362<br />upr:  439.922196","Aluminum:  1047.000<br />upr:  440.166575","Aluminum:  1050.806<br />upr:  440.733455","Aluminum:  1051.178<br />upr:  440.788791","Aluminum:  1055.110<br />upr:  441.372916","Aluminum:  1055.329<br />upr:  441.405409","Aluminum:  1055.500<br />upr:  441.430777","Aluminum:  1065.343<br />upr:  442.886553","Aluminum:  1074.580<br />upr:  444.244838","Aluminum:  1078.048<br />upr:  444.752859","Aluminum:  1089.320<br />upr:  446.396835","Aluminum:  1090.747<br />upr:  446.604174","Aluminum:  1091.386<br />upr:  446.696962","Aluminum:  1094.920<br />upr:  447.209498","Aluminum:  1103.000<br />upr:  448.377349","Aluminum:  1116.333<br />upr:  450.292453","Aluminum:  1123.390<br />upr:  451.300134","Aluminum:  1132.000<br />upr:  452.524061","Aluminum:  1154.750<br />upr:  455.729415","Aluminum:  1163.618<br />upr:  456.967844","Aluminum:  1172.002<br />upr:  458.133100","Aluminum:  1183.886<br />upr:  459.775640","Aluminum:  1202.900<br />upr:  462.381694","Aluminum:  1207.000<br />upr:  462.940154","Aluminum:  1224.440<br />upr:  465.302090","Aluminum:  1232.130<br />upr:  466.336678","Aluminum:  1242.758<br />upr:  467.759709","Aluminum:  1249.000<br />upr:  468.591826","Aluminum:  1251.510<br />upr:  468.925677","Aluminum:  1257.000<br />upr:  469.654393","Aluminum:  1264.420<br />upr:  470.636035","Aluminum:  1272.795<br />upr:  471.739572","Aluminum:  1282.310<br />upr:  472.987659","Aluminum:  1284.840<br />upr:  473.318515","Aluminum:  1300.000<br />upr:  475.292297","Aluminum:  1300.000<br />upr:  475.292297","Aluminum:  1314.420<br />upr:  477.156017","Aluminum:  1336.970<br />upr:  480.044274","Aluminum:  1337.000<br />upr:  480.048095","Aluminum:  1378.924<br />upr:  485.335412","Aluminum:  1380.000<br />upr:  485.469741","Aluminum:  1380.670<br />upr:  485.553351","Aluminum:  1384.000<br />upr:  485.968516","Aluminum:  1384.410<br />upr:  486.019588","Aluminum:  1390.946<br />upr:  486.832436","Aluminum:  1391.532<br />upr:  486.905193","Aluminum:  1393.442<br />upr:  487.142201","Aluminum:  1400.000<br />upr:  487.954379","Aluminum:  1405.000<br />upr:  488.571960","Aluminum:  1413.720<br />upr:  489.645642","Aluminum:  1420.100<br />upr:  490.428503","Aluminum:  1428.100<br />upr:  491.406951","Aluminum:  1438.131<br />upr:  492.628826","Aluminum:  1439.250<br />upr:  492.764790","Aluminum:  1444.554<br />upr:  493.408329","Aluminum:  1456.507<br />upr:  494.853036","Aluminum:  1476.780<br />upr:  497.285979","Aluminum:  1486.450<br />upr:  498.438890","Aluminum:  1489.760<br />upr:  498.832416","Aluminum:  1492.379<br />upr:  499.143390","Aluminum:  1497.000<br />upr:  499.691220","Aluminum:  1500.000<br />upr:  500.046294","Aluminum:  1505.000<br />upr:  500.637069","Aluminum:  1510.570<br />upr:  501.293705","Aluminum:  1514.000<br />upr:  501.697285","Aluminum:  1516.000<br />upr:  501.932337","Aluminum:  1528.931<br />upr:  503.447263","Aluminum:  1534.980<br />upr:  504.153097","Aluminum:  1537.150<br />upr:  504.405870","Aluminum:  1544.300<br />upr:  505.237113","Aluminum:  1563.510<br />upr:  507.458217","Aluminum:  1566.950<br />upr:  507.854099","Aluminum:  1582.670<br />upr:  509.656095","Aluminum:  1588.720<br />upr:  510.346537","Aluminum:  1600.000<br />upr:  511.629332","Aluminum:  1600.000<br />upr:  511.629332","Aluminum:  1603.200<br />upr:  511.992184","Aluminum:  1639.990<br />upr:  516.130727","Aluminum:  1646.000<br />upr:  516.801096","Aluminum:  1669.150<br />upr:  519.368666","Aluminum:  1695.280<br />upr:  522.239333","Aluminum:  1698.000<br />upr:  522.536512","Aluminum:  1700.000<br />upr:  522.754831","Aluminum:  1700.000<br />upr:  522.754831","Aluminum:  1716.850<br />upr:  524.587629","Aluminum:  1719.550<br />upr:  524.880233","Aluminum:  1731.580<br />upr:  526.180362","Aluminum:  1740.733<br />upr:  527.165670","Aluminum:  1764.700<br />upr:  529.729970","Aluminum:  1777.400<br />upr:  531.079693","Aluminum:  1796.740<br />upr:  533.123216","Aluminum:  1820.267<br />upr:  535.590134","Aluminum:  1821.360<br />upr:  535.704239","Aluminum:  1830.990<br />upr:  536.707679","Aluminum:  1833.140<br />upr:  536.931243","Aluminum:  1837.786<br />upr:  537.413773","Aluminum:  1845.800<br />upr:  538.244257","Aluminum:  1854.259<br />upr:  539.118340","Aluminum:  1871.680<br />upr:  540.910422","Aluminum:  1879.000<br />upr:  541.660217","Aluminum:  1884.050<br />upr:  542.176398","Aluminum:  1892.563<br />upr:  543.044531","Aluminum:  1896.303<br />upr:  543.425131","Aluminum:  1897.960<br />upr:  543.593601","Aluminum:  1903.281<br />upr:  544.133955","Aluminum:  1915.710<br />upr:  545.392355","Aluminum:  1918.000<br />upr:  545.623636","Aluminum:  1939.394<br />upr:  547.775806","Aluminum:  1951.550<br />upr:  548.991854","Aluminum:  1967.730<br />upr:  550.602904","Aluminum:  1982.243<br />upr:  552.040725","Aluminum:  1983.986<br />upr:  552.212950","Aluminum:  1987.046<br />upr:  552.515070","Aluminum:  1987.528<br />upr:  552.562632","Aluminum:  1989.000<br />upr:  552.707837","Aluminum:  1992.915<br />upr:  553.093692","Aluminum:  1995.007<br />upr:  553.299676","Aluminum:  1997.376<br />upr:  553.532767","Aluminum:  2019.460<br />upr:  555.697131","Aluminum:  2032.000<br />upr:  556.919346","Aluminum:  2038.750<br />upr:  557.575226","Aluminum:  2063.092<br />upr:  559.928922","Aluminum:  2073.900<br />upr:  560.968244","Aluminum:  2084.699<br />upr:  562.003222","Aluminum:  2126.000<br />upr:  565.929957","Aluminum:  2159.053<br />upr:  569.037248","Aluminum:  2203.280<br />upr:  573.147433","Aluminum:  2228.554<br />upr:  575.472419","Aluminum:  2252.090<br />upr:  577.622299","Aluminum:  2275.670<br />upr:  579.761734","Aluminum:  2277.000<br />upr:  579.881980","Aluminum:  2295.000<br />upr:  581.504936","Aluminum:  2300.000<br />upr:  581.954301","Aluminum:  2313.950<br />upr:  583.204711","Aluminum:  2318.710<br />upr:  583.630263","Aluminum:  2350.710<br />upr:  586.476612","Aluminum:  2361.100<br />upr:  587.395415","Aluminum:  2391.420<br />upr:  590.061856","Aluminum:  2442.500<br />upr:  594.505182","Aluminum:  2470.551<br />upr:  596.919849","Aluminum:  2471.350<br />upr:  596.988368","Aluminum:  2474.000<br />upr:  597.215522","Aluminum:  2483.576<br />upr:  598.035056","Aluminum:  2513.650<br />upr:  600.595693","Aluminum:  2529.418<br />upr:  601.930372","Aluminum:  2542.730<br />upr:  603.052997","Aluminum:  2568.130<br />upr:  605.184568","Aluminum:  2576.000<br />upr:  605.842262","Aluminum:  2576.414<br />upr:  605.876824","Aluminum:  2598.300<br />upr:  607.698866","Aluminum:  2602.336<br />upr:  608.033789","Aluminum:  2607.300<br />upr:  608.445261","Aluminum:  2612.809<br />upr:  608.901319","Aluminum:  2619.000<br />upr:  609.413098","Aluminum:  2627.657<br />upr:  610.127423","Aluminum:  2630.018<br />upr:  610.321976","Aluminum:  2630.450<br />upr:  610.357562","Aluminum:  2634.581<br />upr:  610.697661","Aluminum:  2647.810<br />upr:  611.784480","Aluminum:  2669.586<br />upr:  613.565879","Aluminum:  2672.000<br />upr:  613.762781","Aluminum:  2696.274<br />upr:  615.736389","Aluminum:  2698.230<br />upr:  615.894924","Aluminum:  2709.270<br />upr:  616.788334","Aluminum:  2737.840<br />upr:  619.089523","Aluminum:  2740.800<br />upr:  619.327052","Aluminum:  2743.000<br />upr:  619.503487","Aluminum:  2763.000<br />upr:  621.103276","Aluminum:  2790.000<br />upr:  623.251205","Aluminum:  2802.720<br />upr:  624.258479","Aluminum:  2807.090<br />upr:  624.603852","Aluminum:  2808.280<br />upr:  624.697841","Aluminum:  2808.490<br />upr:  624.714425","Aluminum:  2818.775<br />upr:  625.525652","Aluminum:  2847.260<br />upr:  627.762495","Aluminum:  2877.037<br />upr:  630.085438","Aluminum:  2886.310<br />upr:  630.805673","Aluminum:  2900.000<br />upr:  631.866258","Aluminum:  2913.650<br />upr:  632.920539","Aluminum:  2929.158<br />upr:  634.114471","Aluminum:  2931.600<br />upr:  634.302105","Aluminum:  2939.076<br />upr:  634.875907","Aluminum:  2944.010<br />upr:  635.254089","Aluminum:  2944.066<br />upr:  635.258379","Aluminum:  2954.000<br />upr:  636.018557","Aluminum:  2957.000<br />upr:  636.247801","Aluminum:  2958.811<br />upr:  636.386116","Aluminum:  2997.000<br />upr:  639.290183","Aluminum:  3008.560<br />upr:  640.164556","Aluminum:  3029.720<br />upr:  641.759462","Aluminum:  3056.245<br />upr:  643.748647","Aluminum:  3062.830<br />upr:  644.240751","Aluminum:  3076.000<br />upr:  645.222917","Aluminum:  3100.587<br />upr:  647.049295","Aluminum:  3102.000<br />upr:  647.153972","Aluminum:  3102.896<br />upr:  647.220333","Aluminum:  3105.600<br />upr:  647.420526","Aluminum:  3112.807<br />upr:  647.953555","Aluminum:  3152.230<br />upr:  650.855302","Aluminum:  3161.430<br />upr:  651.529104","Aluminum:  3162.000<br />upr:  651.570808","Aluminum:  3164.560<br />upr:  651.758055","Aluminum:  3180.716<br />upr:  652.937510","Aluminum:  3181.660<br />upr:  653.006306","Aluminum:  3210.491<br />upr:  655.101140","Aluminum:  3234.000<br />upr:  656.800332","Aluminum:  3234.290<br />upr:  656.821243","Aluminum:  3236.928<br />upr:  657.011406","Aluminum:  3273.700<br />upr:  659.651814","Aluminum:  3275.000<br />upr:  659.744810","Aluminum:  3276.100<br />upr:  659.823480","Aluminum:  3278.080<br />upr:  659.965044","Aluminum:  3281.956<br />upr:  660.242006","Aluminum:  3282.839<br />upr:  660.305072","Aluminum:  3284.770<br />upr:  660.442951","Aluminum:  3307.181<br />upr:  662.039349","Aluminum:  3313.481<br />upr:  662.486861","Aluminum:  3400.000<br />upr:  668.577933","Aluminum:  3403.350<br />upr:  668.811760","Aluminum:  3411.500<br />upr:  669.380005","Aluminum:  3418.530<br />upr:  669.869458","Aluminum:  3437.730<br />upr:  671.202934","Aluminum:  3451.720<br />upr:  672.171548","Aluminum:  3460.000<br />upr:  672.743632","Aluminum:  3466.580<br />upr:  673.197632","Aluminum:  3482.766<br />upr:  674.312058","Aluminum:  3530.330<br />upr:  677.567719","Aluminum:  3605.617<br />upr:  682.663710","Aluminum:  3624.320<br />upr:  683.919023","Aluminum:  3706.800<br />upr:  689.405726","Aluminum:  3739.930<br />upr:  691.587449","Aluminum:  3740.938<br />upr:  691.653634","Aluminum:  3746.920<br />upr:  692.046173","Aluminum:  3770.700<br />upr:  693.602638","Aluminum:  3797.610<br />upr:  695.356365","Aluminum:  3817.000<br />upr:  696.615058","Aluminum:  3862.314<br />upr:  699.540624","Aluminum:  3892.890<br />upr:  701.502206","Aluminum:  3919.187<br />upr:  703.181350","Aluminum:  3964.300<br />upr:  706.045134","Aluminum:  3990.310<br />upr:  707.686725","Aluminum:  4000.870<br />upr:  708.351241","Aluminum:  4010.643<br />upr:  708.965227","Aluminum:  4015.608<br />upr:  709.276783","Aluminum:  4017.990<br />upr:  709.426166","Aluminum:  4022.320<br />upr:  709.697569","Aluminum:  4100.130<br />upr:  714.542937","Aluminum:  4109.000<br />upr:  715.091516","Aluminum:  4213.850<br />upr:  721.519108","Aluminum:  4223.620<br />upr:  722.112767","Aluminum:  4262.000<br />upr:  724.436346","Aluminum:  4319.253<br />upr:  727.877612","Aluminum:  4347.880<br />upr:  729.587267","Aluminum:  4397.970<br />upr:  732.561374","Aluminum:  4398.600<br />upr:  732.598641","Aluminum:  4404.900<br />upr:  732.971124","Aluminum:  4413.802<br />upr:  733.496864","Aluminum:  4431.470<br />upr:  734.538292","Aluminum:  4466.000<br />upr:  736.565947","Aluminum:  4506.180<br />upr:  738.912710","Aluminum:  4519.660<br />upr:  739.697006","Aluminum:  4534.800<br />upr:  740.576091","Aluminum:  4578.000<br />upr:  743.074101","Aluminum:  4679.724<br />upr:  748.896859","Aluminum:  4721.000<br />upr:  751.236280","Aluminum:  4775.320<br />upr:  754.295016","Aluminum:  4829.056<br />upr:  757.298902","Aluminum:  4852.940<br />upr:  758.627128","Aluminum:  4924.490<br />upr:  762.581116","Aluminum:  4940.032<br />upr:  763.435098","Aluminum:  4982.140<br />upr:  765.740136","Aluminum:  5000.000<br />upr:  766.714023","Aluminum:  5023.810<br />upr:  768.008881","Aluminum:  5060.340<br />upr:  769.987828","Aluminum:  5063.000<br />upr:  770.131569","Aluminum:  5074.345<br />upr:  770.744085","Aluminum:  5080.363<br />upr:  771.068638","Aluminum:  5128.640<br />upr:  773.663323","Aluminum:  5149.080<br />upr:  774.757147","Aluminum:  5208.540<br />upr:  777.923275","Aluminum:  5212.570<br />upr:  778.137021","Aluminum:  5263.700<br />upr:  780.839693","Aluminum:  5308.000<br />upr:  783.167704","Aluminum:  5435.273<br />upr:  789.787201","Aluminum:  5553.000<br />upr:  795.821924","Aluminum:  5557.760<br />upr:  796.064183","Aluminum:  5616.320<br />upr:  799.033705","Aluminum:  5632.510<br />upr:  799.851165","Aluminum:  5683.264<br />upr:  802.404052","Aluminum:  5691.840<br />upr:  802.833966","Aluminum:  5839.321<br />upr:  810.162817","Aluminum:  5864.040<br />upr:  811.379489","Aluminum:  5944.163<br />upr:  815.300600","Aluminum:  5978.370<br />upr:  816.964280","Aluminum:  6101.770<br />upr:  822.915486","Aluminum:  6132.060<br />upr:  824.364413","Aluminum:  6143.000<br />upr:  824.886596","Aluminum:  6171.030<br />upr:  826.221787","Aluminum:  6217.790<br />upr:  828.440504","Aluminum:  6226.436<br />upr:  828.849571","Aluminum:  6376.780<br />upr:  835.905040","Aluminum:  6399.000<br />upr:  836.938683","Aluminum:  6507.398<br />upr:  841.948348","Aluminum:  6513.000<br />upr:  842.205783","Aluminum:  6540.170<br />upr:  843.452334","Aluminum:  6560.000<br />upr:  844.360025","Aluminum:  6576.330<br />upr:  845.106183","Aluminum:  6684.020<br />upr:  849.997181","Aluminum:  6687.320<br />upr:  850.146255","Aluminum:  6825.000<br />upr:  856.324037","Aluminum:  6893.810<br />upr:  859.381539","Aluminum:  6905.380<br />upr:  859.893708","Aluminum:  6942.000<br />upr:  861.511132","Aluminum:  7025.862<br />upr:  865.194548","Aluminum:  7109.340<br />upr:  868.833092","Aluminum:  7126.600<br />upr:  869.581965","Aluminum:  7196.000<br />upr:  872.581347","Aluminum:  7301.650<br />upr:  877.111861","Aluminum:  7563.000<br />upr:  888.140714","Aluminum:  7772.280<br />upr:  896.796592","Aluminum:  7779.340<br />upr:  897.085965","Aluminum:  7806.600<br />upr:  898.201703","Aluminum:  8057.890<br />upr:  908.370694","Aluminum:  8101.529<br />upr:  910.115748","Aluminum:  8110.616<br />upr:  910.478361","Aluminum:  8156.740<br />upr:  912.314899","Aluminum:  8172.880<br />upr:  912.955972","Aluminum:  8179.610<br />upr:  913.223044","Aluminum:  8318.290<br />upr:  918.695182","Aluminum:  8356.760<br />upr:  920.202740","Aluminum:  8361.000<br />upr:  920.368624","Aluminum:  8600.000<br />upr:  929.632892","Aluminum:  8737.050<br />upr:  934.870716","Aluminum:  9034.470<br />upr:  946.058367","Aluminum:  9035.970<br />upr:  946.114185","Aluminum:  9388.160<br />upr:  959.058226","Aluminum:  9542.662<br />upr:  964.638036","Aluminum:  9559.510<br />upr:  965.242973","Aluminum:  9700.000<br />upr:  970.260820","Aluminum:  9896.680<br />upr:  977.207608","Aluminum: 10005.812<br />upr:  981.023901","Aluminum: 10050.000<br />upr:  982.561512","Aluminum: 10233.858<br />upr:  988.912920","Aluminum: 10343.200<br />upr:  992.655390","Aluminum: 10379.837<br />upr:  993.903674","Aluminum: 10711.560<br />upr: 1005.079048","Aluminum: 10869.710<br />upr: 1010.328600","Aluminum: 10891.960<br />upr: 1011.063202","Aluminum: 10908.460<br />upr: 1011.607339","Aluminum: 10990.470<br />upr: 1014.304036","Aluminum: 10990.530<br />upr: 1014.306005","Aluminum: 11116.490<br />upr: 1018.422766","Aluminum: 11359.000<br />upr: 1026.264971","Aluminum: 11526.000<br />upr: 1031.602900","Aluminum: 11711.000<br />upr: 1037.458372","Aluminum: 11803.000<br />upr: 1040.348133","Aluminum: 11855.800<br />upr: 1042.000060","Aluminum: 11985.000<br />upr: 1046.022406","Aluminum: 12055.930<br />upr: 1048.218791","Aluminum: 12219.017<br />upr: 1053.237509","Aluminum: 12247.000<br />upr: 1054.094296","Aluminum: 12414.483<br />upr: 1059.196155","Aluminum: 12430.700<br />upr: 1059.687798","Aluminum: 12560.000<br />upr: 1063.593039","Aluminum: 12600.000<br />upr: 1064.795914","Aluminum: 12641.000<br />upr: 1066.026312","Aluminum: 12697.000<br />upr: 1067.702712","Aluminum: 12699.930<br />upr: 1067.790293","Aluminum: 12800.710<br />upr: 1070.794823","Aluminum: 12837.925<br />upr: 1071.900455","Aluminum: 12876.191<br />upr: 1073.035162","Aluminum: 12911.000<br />upr: 1074.065475","Aluminum: 13313.000<br />upr: 1085.836829","Aluminum: 13535.000<br />upr: 1092.239591","Aluminum: 13578.400<br />upr: 1093.483388","Aluminum: 13714.000<br />upr: 1097.353129","Aluminum: 13720.174<br />upr: 1097.528735","Aluminum: 13775.000<br />upr: 1099.085913","Aluminum: 13871.300<br />upr: 1101.811415","Aluminum: 13983.000<br />upr: 1104.957558","Aluminum: 14157.000<br />upr: 1109.826382","Aluminum: 14165.940<br />upr: 1110.075496","Aluminum: 14369.230<br />upr: 1115.713092","Aluminum: 14376.210<br />upr: 1115.905745","Aluminum: 14380.579<br />upr: 1116.026303","Aluminum: 14638.271<br />upr: 1123.095710","Aluminum: 14744.157<br />upr: 1125.977321","Aluminum: 14960.965<br />upr: 1131.836305","Aluminum: 15050.070<br />upr: 1134.228420","Aluminum: 15400.080<br />upr: 1143.537567","Aluminum: 15580.000<br />upr: 1148.269940","Aluminum: 15667.844<br />upr: 1150.567699","Aluminum: 15747.000<br />upr: 1152.631112","Aluminum: 15855.930<br />upr: 1155.459780","Aluminum: 15982.549<br />upr: 1158.732119","Aluminum: 16187.748<br />upr: 1164.000033","Aluminum: 16285.040<br />upr: 1166.482723","Aluminum: 16374.220<br />upr: 1168.750040","Aluminum: 16378.832<br />upr: 1168.867079","Aluminum: 16554.910<br />upr: 1173.319667","Aluminum: 16744.907<br />upr: 1178.090178","Aluminum: 16986.000<br />upr: 1184.093743","Aluminum: 17250.000<br />upr: 1190.605155","Aluminum: 17376.000<br />upr: 1193.690279","Aluminum: 17668.669<br />upr: 1200.801171","Aluminum: 18190.640<br />upr: 1213.297496","Aluminum: 18253.450<br />upr: 1214.785581","Aluminum: 18567.346<br />upr: 1222.173401","Aluminum: 18721.000<br />upr: 1225.760503","Aluminum: 18771.346<br />upr: 1226.931724","Aluminum: 18915.000<br />upr: 1230.262537","Aluminum: 18941.560<br />upr: 1230.876582","Aluminum: 18948.944<br />upr: 1231.047195","Aluminum: 19043.000<br />upr: 1233.216703","Aluminum: 19174.000<br />upr: 1236.226907","Aluminum: 19482.960<br />upr: 1243.274357","Aluminum: 19494.000<br />upr: 1243.524846","Aluminum: 19555.370<br />upr: 1244.915627","Aluminum: 19741.000<br />upr: 1249.105395","Aluminum: 19770.000<br />upr: 1249.757648","Aluminum: 19778.615<br />upr: 1249.951293","Aluminum: 19814.984<br />upr: 1250.768187","Aluminum: 20147.874<br />upr: 1258.200878","Aluminum: 20447.460<br />upr: 1264.822699","Aluminum: 21255.484<br />upr: 1282.376945","Aluminum: 21460.000<br />upr: 1286.751704","Aluminum: 22988.650<br />upr: 1318.631036","Aluminum: 23301.643<br />upr: 1324.988792","Aluminum: 23502.000<br />upr: 1329.029801","Aluminum: 23767.000<br />upr: 1334.340693","Aluminum: 23920.000<br />upr: 1337.389649","Aluminum: 23973.990<br />upr: 1338.462556","Aluminum: 24381.260<br />upr: 1346.506300","Aluminum: 24556.268<br />upr: 1349.936224","Aluminum: 24654.550<br />upr: 1351.855528","Aluminum: 24669.671<br />upr: 1352.150381","Aluminum: 25231.350<br />upr: 1363.021530","Aluminum: 25590.000<br />upr: 1369.881869","Aluminum: 25981.900<br />upr: 1377.307854","Aluminum: 26372.522<br />upr: 1384.638249","Aluminum: 26929.000<br />upr: 1394.961419","Aluminum: 27052.400<br />upr: 1397.231968","Aluminum: 27375.200<br />upr: 1403.140115","Aluminum: 27477.140<br />upr: 1404.996585","Aluminum: 27642.276<br />upr: 1407.994561","Aluminum: 27663.273<br />upr: 1408.374927","Aluminum: 27760.700<br />upr: 1410.137413","Aluminum: 27978.000<br />upr: 1414.054154","Aluminum: 31104.223<br />upr: 1468.356833","Aluminum: 31230.000<br />upr: 1470.466518","Aluminum: 31722.000<br />upr: 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15.400<br />lwr: 0.017212305","Aluminum:    15.650<br />lwr: 0.017311179","Aluminum:    18.000<br />lwr: 0.018194352","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    32.600<br />lwr: 0.022472452","Aluminum:    42.500<br />lwr: 0.024693616","Aluminum:    42.500<br />lwr: 0.024693616","Aluminum:    42.600<br />lwr: 0.024714248","Aluminum:    46.875<br />lwr: 0.025568557","Aluminum:    46.875<br />lwr: 0.025568557","Aluminum:    47.000<br />lwr: 0.025592765","Aluminum:    47.400<br />lwr: 0.025669951","Aluminum:    53.000<br />lwr: 0.026708992","Aluminum:    74.400<br />lwr: 0.030129058","Aluminum:    97.810<br />lwr: 0.033203361","Aluminum:   117.170<br />lwr: 0.035402394","Aluminum:   117.842<br />lwr: 0.035474353","Aluminum:   125.450<br />lwr: 0.036271148","Aluminum:   131.900<br />lwr: 0.036922555","Aluminum:   142.570<br />lwr: 0.037956410","Aluminum:   147.600<br />lwr: 0.038426485","Aluminum:   155.500<br />lwr: 0.039144322","Aluminum:   159.380<br />lwr: 0.039488271","Aluminum:   185.090<br />lwr: 0.041640986","Aluminum:   187.400<br />lwr: 0.041824695","Aluminum:   189.500<br />lwr: 0.041990438","Aluminum:   191.200<br />lwr: 0.042123745","Aluminum:   193.720<br />lwr: 0.042319950","Aluminum:   210.447<br />lwr: 0.043582266","Aluminum:   217.180<br />lwr: 0.044072062","Aluminum:   221.700<br />lwr: 0.044395393","Aluminum:   229.000<br />lwr: 0.044908711","Aluminum:   236.490<br />lwr: 0.045424517","Aluminum:   244.300<br />lwr: 0.045951240","Aluminum:   247.300<br />lwr: 0.046150673","Aluminum:   247.740<br />lwr: 0.046179791","Aluminum:   263.211<br />lwr: 0.047183085","Aluminum:   284.000<br />lwr: 0.048472956","Aluminum:   285.630<br />lwr: 0.048571476","Aluminum:   287.200<br />lwr: 0.048666026","Aluminum:   291.780<br />lwr: 0.048939954","Aluminum:   295.270<br />lwr: 0.049146830","Aluminum:   310.900<br />lwr: 0.050054439","Aluminum:   317.090<br />lwr: 0.050405727","Aluminum:   344.600<br />lwr: 0.051915528","Aluminum:   350.290<br />lwr: 0.052217993","Aluminum:   354.368<br />lwr: 0.052432820","Aluminum:   364.300<br />lwr: 0.052949435","Aluminum:   367.700<br />lwr: 0.053124193","Aluminum:   368.000<br />lwr: 0.053139563","Aluminum:   384.500<br />lwr: 0.053972719","Aluminum:   385.400<br />lwr: 0.054017494","Aluminum:   392.440<br />lwr: 0.054365422","Aluminum:   400.000<br />lwr: 0.054734587","Aluminum:   402.290<br />lwr: 0.054845520","Aluminum:   415.000<br />lwr: 0.055453922","Aluminum:   435.400<br />lwr: 0.056405742","Aluminum:   438.840<br />lwr: 0.056563387","Aluminum:   458.000<br />lwr: 0.057427138","Aluminum:   466.820<br />lwr: 0.057816910","Aluminum:   474.810<br />lwr: 0.058165914","Aluminum:   490.970<br />lwr: 0.058860354","Aluminum:   491.110<br />lwr: 0.058866305","Aluminum:   506.170<br />lwr: 0.059500183","Aluminum:   507.730<br />lwr: 0.059565143","Aluminum:   509.000<br />lwr: 0.059617933","Aluminum:   516.000<br />lwr: 0.059907380","Aluminum:   518.945<br />lwr: 0.060028396","Aluminum:   537.306<br />lwr: 0.060773055","Aluminum:   549.690<br />lwr: 0.061266064","Aluminum:   583.780<br />lwr: 0.062587145","Aluminum:   585.800<br />lwr: 0.062663843","Aluminum:   588.850<br />lwr: 0.062779325","Aluminum:   593.576<br />lwr: 0.062957505","Aluminum:   599.820<br />lwr: 0.063191516","Aluminum:   600.000<br />lwr: 0.063198239","Aluminum:   602.242<br />lwr: 0.063281863","Aluminum:   602.688<br />lwr: 0.063298475","Aluminum:   607.580<br />lwr: 0.063480159","Aluminum:   608.200<br />lwr: 0.063503118","Aluminum:   622.248<br />lwr: 0.064019312","Aluminum:   630.000<br />lwr: 0.064300940","Aluminum:   633.020<br />lwr: 0.064410049","Aluminum:   635.748<br />lwr: 0.064508320","Aluminum:   636.290<br />lwr: 0.064527812","Aluminum:   639.840<br />lwr: 0.064655216","Aluminum:   654.870<br />lwr: 0.065189617","Aluminum:   678.540<br />lwr: 0.066015375","Aluminum:   683.683<br />lwr: 0.066192323","Aluminum:   689.070<br />lwr: 0.066376746","Aluminum:   690.000<br />lwr: 0.066408490","Aluminum:   691.160<br />lwr: 0.066448046","Aluminum:   692.300<br />lwr: 0.066486878","Aluminum:   700.000<br />lwr: 0.066748089","Aluminum:   700.090<br />lwr: 0.066751131","Aluminum:   704.500<br />lwr: 0.066899885","Aluminum:   708.500<br />lwr: 0.067034290","Aluminum:   717.431<br />lwr: 0.067332623","Aluminum:   724.300<br />lwr: 0.067560447","Aluminum:   726.200<br />lwr: 0.067623217","Aluminum:   729.903<br />lwr: 0.067745249","Aluminum:   742.770<br />lwr: 0.068166195","Aluminum:   756.970<br />lwr: 0.068625313","Aluminum:   757.450<br />lwr: 0.068640735","Aluminum:   757.860<br />lwr: 0.068653903","Aluminum:   759.500<br />lwr: 0.068706528","Aluminum:   768.500<br />lwr: 0.068994026","Aluminum:   773.110<br />lwr: 0.069140446","Aluminum:   775.800<br />lwr: 0.069225624","Aluminum:   781.000<br />lwr: 0.069389740","Aluminum:   782.951<br />lwr: 0.069451133","Aluminum:   786.460<br />lwr: 0.069561303","Aluminum:   791.690<br />lwr: 0.069724919","Aluminum:   795.000<br />lwr: 0.069828109","Aluminum:   796.650<br />lwr: 0.069879444","Aluminum:   811.000<br />lwr: 0.070323034","Aluminum:   816.000<br />lwr: 0.070476402","Aluminum:   820.028<br />lwr: 0.070599514","Aluminum:   826.707<br />lwr: 0.070802793","Aluminum:   838.370<br />lwr: 0.071155232","Aluminum:   851.132<br />lwr: 0.071537268","Aluminum:   852.109<br />lwr: 0.071566362","Aluminum:   852.194<br />lwr: 0.071568892","Aluminum:   856.000<br />lwr: 0.071682018","Aluminum:   857.074<br />lwr: 0.071713881","Aluminum:   865.660<br />lwr: 0.071967690","Aluminum:   868.557<br />lwr: 0.072052960","Aluminum:   869.040<br />lwr: 0.072067158","Aluminum:   873.000<br />lwr: 0.072183378","Aluminum:   876.120<br />lwr: 0.072274705","Aluminum:   881.230<br />lwr: 0.072423829","Aluminum:   883.240<br />lwr: 0.072482334","Aluminum:   885.409<br />lwr: 0.072545369","Aluminum:   891.670<br />lwr: 0.072726770","Aluminum:   900.000<br />lwr: 0.072966843","Aluminum:   900.000<br />lwr: 0.072966843","Aluminum:   909.630<br />lwr: 0.073242599","Aluminum:   922.500<br />lwr: 0.073608202","Aluminum:   922.730<br />lwr: 0.073614705","Aluminum:   932.070<br />lwr: 0.073877928","Aluminum:   932.243<br />lwr: 0.073882787","Aluminum:   956.710<br />lwr: 0.074564255","Aluminum:   958.914<br />lwr: 0.074625086","Aluminum:   963.190<br />lwr: 0.074742848","Aluminum:   965.100<br />lwr: 0.074795341","Aluminum:   976.090<br />lwr: 0.075096082","Aluminum:  1000.000<br />lwr: 0.075742897","Aluminum:  1000.000<br />lwr: 0.075742897","Aluminum:  1003.810<br />lwr: 0.075845039","Aluminum:  1012.110<br />lwr: 0.076066688","Aluminum:  1018.690<br />lwr: 0.076241572","Aluminum:  1030.410<br />lwr: 0.076551266","Aluminum:  1033.457<br />lwr: 0.076631408","Aluminum:  1038.283<br />lwr: 0.076758029","Aluminum:  1045.362<br />lwr: 0.076943075","Aluminum:  1047.000<br />lwr: 0.076985778","Aluminum:  1050.806<br />lwr: 0.077084832","Aluminum:  1051.178<br />lwr: 0.077094502","Aluminum:  1055.110<br />lwr: 0.077196569","Aluminum:  1055.329<br />lwr: 0.077202247","Aluminum:  1055.500<br />lwr: 0.077206679","Aluminum:  1065.343<br />lwr: 0.077461052","Aluminum:  1074.580<br />lwr: 0.077698384","Aluminum:  1078.048<br />lwr: 0.077787150","Aluminum:  1089.320<br />lwr: 0.078074393","Aluminum:  1090.747<br />lwr: 0.078110620","Aluminum:  1091.386<br />lwr: 0.078126832","Aluminum:  1094.920<br />lwr: 0.078216384","Aluminum:  1103.000<br />lwr: 0.078420430","Aluminum:  1116.333<br />lwr: 0.078755030","Aluminum:  1123.390<br />lwr: 0.078931084","Aluminum:  1132.000<br />lwr: 0.079144917","Aluminum:  1154.750<br />lwr: 0.079704908","Aluminum:  1163.618<br />lwr: 0.079921261","Aluminum:  1172.002<br />lwr: 0.080124827","Aluminum:  1183.886<br />lwr: 0.080411768","Aluminum:  1202.900<br />lwr: 0.080867016","Aluminum:  1207.000<br />lwr: 0.080964570","Aluminum:  1224.440<br />lwr: 0.081377156","Aluminum:  1232.130<br />lwr: 0.081557876","Aluminum:  1242.758<br />lwr: 0.081806443","Aluminum:  1249.000<br />lwr: 0.081951790","Aluminum:  1251.510<br />lwr: 0.082010104","Aluminum:  1257.000<br />lwr: 0.082137388","Aluminum:  1264.420<br />lwr: 0.082308849","Aluminum:  1272.795<br />lwr: 0.082501598","Aluminum:  1282.310<br />lwr: 0.082719592","Aluminum:  1284.840<br />lwr: 0.082777379","Aluminum:  1300.000<br />lwr: 0.083122115","Aluminum:  1300.000<br />lwr: 0.083122115","Aluminum:  1314.420<br />lwr: 0.083447620","Aluminum:  1336.970<br />lwr: 0.083952047","Aluminum:  1337.000<br />lwr: 0.083952714","Aluminum:  1378.924<br />lwr: 0.084876081","Aluminum:  1380.000<br />lwr: 0.084899539","Aluminum:  1380.670<br />lwr: 0.084914140","Aluminum:  1384.000<br />lwr: 0.084986640","Aluminum:  1384.410<br />lwr: 0.084995559","Aluminum:  1390.946<br />lwr: 0.085137506","Aluminum:  1391.532<br />lwr: 0.085150212","Aluminum:  1393.442<br />lwr: 0.085191600","Aluminum:  1400.000<br />lwr: 0.085333428","Aluminum:  1405.000<br />lwr: 0.085441273","Aluminum:  1413.720<br />lwr: 0.085628763","Aluminum:  1420.100<br />lwr: 0.085765467","Aluminum:  1428.100<br />lwr: 0.085936323","Aluminum:  1438.131<br />lwr: 0.086149682","Aluminum:  1439.250<br />lwr: 0.086173423","Aluminum:  1444.554<br />lwr: 0.086285794","Aluminum:  1456.507<br />lwr: 0.086538057","Aluminum:  1476.780<br />lwr: 0.086962866","Aluminum:  1486.450<br />lwr: 0.087164168","Aluminum:  1489.760<br />lwr: 0.087232878","Aluminum:  1492.379<br />lwr: 0.087287174","Aluminum:  1497.000<br />lwr: 0.087382825","Aluminum:  1500.000<br />lwr: 0.087444820","Aluminum:  1505.000<br />lwr: 0.087547968","Aluminum:  1510.570<br />lwr: 0.087662614","Aluminum:  1514.000<br />lwr: 0.087733076","Aluminum:  1516.000<br />lwr: 0.087774115","Aluminum:  1528.931<br />lwr: 0.088038609","Aluminum:  1534.980<br />lwr: 0.088161840","Aluminum:  1537.150<br />lwr: 0.088205971","Aluminum:  1544.300<br />lwr: 0.088351095","Aluminum:  1563.510<br />lwr: 0.088738863","Aluminum:  1566.950<br />lwr: 0.088807976","Aluminum:  1582.670<br />lwr: 0.089122565","Aluminum:  1588.720<br />lwr: 0.089243099","Aluminum:  1600.000<br />lwr: 0.089467040","Aluminum:  1600.000<br />lwr: 0.089467040","Aluminum:  1603.200<br />lwr: 0.089530383","Aluminum:  1639.990<br />lwr: 0.090252831","Aluminum:  1646.000<br />lwr: 0.090369851","Aluminum:  1669.150<br />lwr: 0.090818037","Aluminum:  1695.280<br />lwr: 0.091319113","Aluminum:  1698.000<br />lwr: 0.091370985","Aluminum:  1700.000<br />lwr: 0.091409092","Aluminum:  1700.000<br />lwr: 0.091409092","Aluminum:  1716.850<br />lwr: 0.091728995","Aluminum:  1719.550<br />lwr: 0.091780067","Aluminum:  1731.580<br />lwr: 0.092006991","Aluminum:  1740.733<br />lwr: 0.092178963","Aluminum:  1764.700<br />lwr: 0.092626518","Aluminum:  1777.400<br />lwr: 0.092862084","Aluminum:  1796.740<br />lwr: 0.093218729","Aluminum:  1820.267<br />lwr: 0.093649254","Aluminum:  1821.360<br />lwr: 0.093669168","Aluminum:  1830.990<br />lwr: 0.093844283","Aluminum:  1833.140<br />lwr: 0.093883298","Aluminum:  1837.786<br />lwr: 0.093967506","Aluminum:  1845.800<br />lwr: 0.094112435","Aluminum:  1854.259<br />lwr: 0.094264971","Aluminum:  1871.680<br />lwr: 0.094577702","Aluminum:  1879.000<br />lwr: 0.094708544","Aluminum:  1884.050<br />lwr: 0.094798619","Aluminum:  1892.563<br />lwr: 0.094950109","Aluminum:  1896.303<br />lwr: 0.095016524","Aluminum:  1897.960<br />lwr: 0.095045921","Aluminum:  1903.281<br />lwr: 0.095140212","Aluminum:  1915.710<br />lwr: 0.095359798","Aluminum:  1918.000<br />lwr: 0.095400155","Aluminum:  1939.394<br />lwr: 0.095775691","Aluminum:  1951.550<br />lwr: 0.095987877","Aluminum:  1967.730<br />lwr: 0.096268981","Aluminum:  1982.243<br />lwr: 0.096519854","Aluminum:  1983.986<br />lwr: 0.096549903","Aluminum:  1987.046<br />lwr: 0.096602617","Aluminum:  1987.528<br />lwr: 0.096610916","Aluminum:  1989.000<br />lwr: 0.096636251","Aluminum:  1992.915<br />lwr: 0.096703574","Aluminum:  1995.007<br />lwr: 0.096739513","Aluminum:  1997.376<br />lwr: 0.096780182","Aluminum:  2019.460<br />lwr: 0.097157808","Aluminum:  2032.000<br />lwr: 0.097371048","Aluminum:  2038.750<br />lwr: 0.097485478","Aluminum:  2063.092<br />lwr: 0.097896115","Aluminum:  2073.900<br />lwr: 0.098077436","Aluminum:  2084.699<br />lwr: 0.098257997","Aluminum:  2126.000<br />lwr: 0.098943028","Aluminum:  2159.053<br />lwr: 0.099485080","Aluminum:  2203.280<br />lwr: 0.100202050","Aluminum:  2228.554<br />lwr: 0.100607597","Aluminum:  2252.090<br />lwr: 0.100982591","Aluminum:  2275.670<br />lwr: 0.101355752","Aluminum:  2277.000<br />lwr: 0.101376725","Aluminum:  2295.000<br />lwr: 0.101659795","Aluminum:  2300.000<br />lwr: 0.101738170","Aluminum:  2313.950<br />lwr: 0.101956257","Aluminum:  2318.710<br />lwr: 0.102030477","Aluminum:  2350.710<br />lwr: 0.102526899","Aluminum:  2361.100<br />lwr: 0.102687140","Aluminum:  2391.420<br />lwr: 0.103152163","Aluminum:  2442.500<br />lwr: 0.103927037","Aluminum:  2470.551<br />lwr: 0.104348114","Aluminum:  2471.350<br />lwr: 0.104360063","Aluminum:  2474.000<br />lwr: 0.104399674","Aluminum:  2483.576<br />lwr: 0.104542583","Aluminum:  2513.650<br />lwr: 0.104989095","Aluminum:  2529.418<br />lwr: 0.105221824","Aluminum:  2542.730<br />lwr: 0.105417574","Aluminum:  2568.130<br />lwr: 0.105789245","Aluminum:  2576.000<br />lwr: 0.105903922","Aluminum:  2576.414<br />lwr: 0.105909948","Aluminum:  2598.300<br />lwr: 0.106227637","Aluminum:  2602.336<br />lwr: 0.106286033","Aluminum:  2607.300<br />lwr: 0.106357776","Aluminum:  2612.809<br />lwr: 0.106437292","Aluminum:  2619.000<br />lwr: 0.106526523","Aluminum:  2627.657<br />lwr: 0.106651067","Aluminum:  2630.018<br />lwr: 0.106684987","Aluminum:  2630.450<br />lwr: 0.106691192","Aluminum:  2634.581<br />lwr: 0.106750488","Aluminum:  2647.810<br />lwr: 0.106939974","Aluminum:  2669.586<br />lwr: 0.107250555","Aluminum:  2672.000<br />lwr: 0.107284883","Aluminum:  2696.274<br />lwr: 0.107628966","Aluminum:  2698.230<br />lwr: 0.107656604","Aluminum:  2709.270<br />lwr: 0.107812360","Aluminum:  2737.840<br />lwr: 0.108213537","Aluminum:  2740.800<br />lwr: 0.108254946","Aluminum:  2743.000<br />lwr: 0.108285704","Aluminum:  2763.000<br />lwr: 0.108564595","Aluminum:  2790.000<br />lwr: 0.108939034","Aluminum:  2802.720<br />lwr: 0.109114624","Aluminum:  2807.090<br />lwr: 0.109174830","Aluminum:  2808.280<br />lwr: 0.109191214","Aluminum:  2808.490<br />lwr: 0.109194105","Aluminum:  2818.775<br />lwr: 0.109335518","Aluminum:  2847.260<br />lwr: 0.109725435","Aluminum:  2877.037<br />lwr: 0.110130350","Aluminum:  2886.310<br />lwr: 0.110255893","Aluminum:  2900.000<br />lwr: 0.110440759","Aluminum:  2913.650<br />lwr: 0.110624524","Aluminum:  2929.158<br />lwr: 0.110832628","Aluminum:  2931.600<br />lwr: 0.110865333","Aluminum:  2939.076<br />lwr: 0.110965346","Aluminum:  2944.010<br />lwr: 0.111031262","Aluminum:  2944.066<br />lwr: 0.111032010","Aluminum:  2954.000<br />lwr: 0.111164506","Aluminum:  2957.000<br />lwr: 0.111204463","Aluminum:  2958.811<br />lwr: 0.111228570","Aluminum:  2997.000<br />lwr: 0.111734726","Aluminum:  3008.560<br />lwr: 0.111887119","Aluminum:  3029.720<br />lwr: 0.112165088","Aluminum:  3056.245<br />lwr: 0.112511766","Aluminum:  3062.830<br />lwr: 0.112597529","Aluminum:  3076.000<br />lwr: 0.112768699","Aluminum:  3100.587<br />lwr: 0.113086990","Aluminum:  3102.000<br />lwr: 0.113105232","Aluminum:  3102.896<br />lwr: 0.113116797","Aluminum:  3105.600<br />lwr: 0.113151685","Aluminum:  3112.807<br />lwr: 0.113244577","Aluminum:  3152.230<br />lwr: 0.113750256","Aluminum:  3161.430<br />lwr: 0.113867676","Aluminum:  3162.000<br />lwr: 0.113874943","Aluminum:  3164.560<br />lwr: 0.113907573","Aluminum:  3180.716<br />lwr: 0.114113107","Aluminum:  3181.660<br />lwr: 0.114125095","Aluminum:  3210.491<br />lwr: 0.114490136","Aluminum:  3234.000<br />lwr: 0.114786226","Aluminum:  3234.290<br />lwr: 0.114789870","Aluminum:  3236.928<br />lwr: 0.114823006","Aluminum:  3273.700<br />lwr: 0.115283094","Aluminum:  3275.000<br />lwr: 0.115299298","Aluminum:  3276.100<br />lwr: 0.115313006","Aluminum:  3278.080<br />lwr: 0.115337672","Aluminum:  3281.956<br />lwr: 0.115385932","Aluminum:  3282.839<br />lwr: 0.115396921","Aluminum:  3284.770<br />lwr: 0.115420945","Aluminum:  3307.181<br />lwr: 0.115699106","Aluminum:  3313.481<br />lwr: 0.115777080","Aluminum:  3400.000<br />lwr: 0.116838349","Aluminum:  3403.350<br />lwr: 0.116879087","Aluminum:  3411.500<br />lwr: 0.116978090","Aluminum:  3418.530<br />lwr: 0.117063365","Aluminum:  3437.730<br />lwr: 0.117295687","Aluminum:  3451.720<br />lwr: 0.117464440","Aluminum:  3460.000<br />lwr: 0.117564108","Aluminum:  3466.580<br />lwr: 0.117643203","Aluminum:  3482.766<br />lwr: 0.117837354","Aluminum:  3530.330<br />lwr: 0.118404528","Aluminum:  3605.617<br />lwr: 0.119292264","Aluminum:  3624.320<br />lwr: 0.119510935","Aluminum:  3706.800<br />lwr: 0.120466660","Aluminum:  3739.930<br />lwr: 0.120846676","Aluminum:  3740.938<br />lwr: 0.120858204","Aluminum:  3746.920<br />lwr: 0.120926576","Aluminum:  3770.700<br />lwr: 0.121197675","Aluminum:  3797.610<br />lwr: 0.121503128","Aluminum:  3817.000<br />lwr: 0.121722354","Aluminum:  3862.314<br />lwr: 0.122231888","Aluminum:  3892.890<br />lwr: 0.122573518","Aluminum:  3919.187<br />lwr: 0.122865953","Aluminum:  3964.300<br />lwr: 0.123364687","Aluminum:  3990.310<br />lwr: 0.123650566","Aluminum:  4000.870<br />lwr: 0.123766289","Aluminum:  4010.643<br />lwr: 0.123873211","Aluminum:  4015.608<br />lwr: 0.123927466","Aluminum:  4017.990<br />lwr: 0.123953480","Aluminum:  4022.320<br />lwr: 0.124000743","Aluminum:  4100.130<br />lwr: 0.124844500","Aluminum:  4109.000<br />lwr: 0.124940025","Aluminum:  4213.850<br />lwr: 0.126059224","Aluminum:  4223.620<br />lwr: 0.126162591","Aluminum:  4262.000<br />lwr: 0.126567159","Aluminum:  4319.253<br />lwr: 0.127166312","Aluminum:  4347.880<br />lwr: 0.127463968","Aluminum:  4397.970<br />lwr: 0.127981755","Aluminum:  4398.600<br />lwr: 0.127988243","Aluminum:  4404.900<br />lwr: 0.128053090","Aluminum:  4413.802<br />lwr: 0.128144619","Aluminum:  4431.470<br />lwr: 0.128325923","Aluminum:  4466.000<br />lwr: 0.128678916","Aluminum:  4506.180<br />lwr: 0.129087452","Aluminum:  4519.660<br />lwr: 0.129223984","Aluminum:  4534.800<br />lwr: 0.129377015","Aluminum:  4578.000<br />lwr: 0.129811861","Aluminum:  4679.724<br />lwr: 0.130825418","Aluminum:  4721.000<br />lwr: 0.131232618","Aluminum:  4775.320<br />lwr: 0.131765006","Aluminum:  4829.056<br />lwr: 0.132287828","Aluminum:  4852.940<br />lwr: 0.132518999","Aluminum:  4924.490<br />lwr: 0.133207148","Aluminum:  4940.032<br />lwr: 0.133355770","Aluminum:  4982.140<br />lwr: 0.133756918","Aluminum:  5000.000<br />lwr: 0.133926402","Aluminum:  5023.810<br />lwr: 0.134151741","Aluminum:  5060.340<br />lwr: 0.134496122","Aluminum:  5063.000<br />lwr: 0.134521136","Aluminum:  5074.345<br />lwr: 0.134627726","Aluminum:  5080.363<br />lwr: 0.134684204","Aluminum:  5128.640<br />lwr: 0.135135720","Aluminum:  5149.080<br />lwr: 0.135326059","Aluminum:  5208.540<br />lwr: 0.135876991","Aluminum:  5212.570<br />lwr: 0.135914183","Aluminum:  5263.700<br />lwr: 0.136384453","Aluminum:  5308.000<br />lwr: 0.136789520","Aluminum:  5435.273<br />lwr: 0.137941234","Aluminum:  5553.000<br />lwr: 0.138991129","Aluminum:  5557.760<br />lwr: 0.139033275","Aluminum:  5616.320<br />lwr: 0.139549872","Aluminum:  5632.510<br />lwr: 0.139692080","Aluminum:  5683.264<br />lwr: 0.140136179","Aluminum:  5691.840<br />lwr: 0.140210965","Aluminum:  5839.321<br />lwr: 0.141485812","Aluminum:  5864.040<br />lwr: 0.141697441","Aluminum:  5944.163<br />lwr: 0.142379463","Aluminum:  5978.370<br />lwr: 0.142668828","Aluminum:  6101.770<br />lwr: 0.143703881","Aluminum:  6132.060<br />lwr: 0.143955872","Aluminum:  6143.000<br />lwr: 0.144046687","Aluminum:  6171.030<br />lwr: 0.144278893","Aluminum:  6217.790<br />lwr: 0.144664748","Aluminum:  6226.436<br />lwr: 0.144735888","Aluminum:  6376.780<br />lwr: 0.145962829","Aluminum:  6399.000<br />lwr: 0.146142571","Aluminum:  6507.398<br />lwr: 0.147013681","Aluminum:  6513.000<br />lwr: 0.147058444","Aluminum:  6540.170<br />lwr: 0.147275194","Aluminum:  6560.000<br />lwr: 0.147433021","Aluminum:  6576.330<br />lwr: 0.147562760","Aluminum:  6684.020<br />lwr: 0.148413160","Aluminum:  6687.320<br />lwr: 0.148439079","Aluminum:  6825.000<br />lwr: 0.149513147","Aluminum:  6893.810<br />lwr: 0.150044697","Aluminum:  6905.380<br />lwr: 0.150133736","Aluminum:  6942.000<br />lwr: 0.150414918","Aluminum:  7025.862<br />lwr: 0.151055246","Aluminum:  7109.340<br />lwr: 0.151687748","Aluminum:  7126.600<br />lwr: 0.151817925","Aluminum:  7196.000<br />lwr: 0.152339296","Aluminum:  7301.650<br />lwr: 0.153126787","Aluminum:  7563.000<br />lwr: 0.155043654","Aluminum:  7772.280<br />lwr: 0.156547929","Aluminum:  7779.340<br />lwr: 0.156598216","Aluminum:  7806.600<br />lwr: 0.156792105","Aluminum:  8057.890<br />lwr: 0.158559137","Aluminum:  8101.529<br />lwr: 0.158862350","Aluminum:  8110.616<br />lwr: 0.158925355","Aluminum:  8156.740<br />lwr: 0.159244457","Aluminum:  8172.880<br />lwr: 0.159355843","Aluminum:  8179.610<br />lwr: 0.159402247","Aluminum:  8318.290<br />lwr: 0.160352995","Aluminum:  8356.760<br />lwr: 0.160614914","Aluminum:  8361.000<br />lwr: 0.160643733","Aluminum:  8600.000<br />lwr: 0.162253187","Aluminum:  8737.050<br />lwr: 0.163163070","Aluminum:  9034.470<br />lwr: 0.165106354","Aluminum:  9035.970<br />lwr: 0.165116049","Aluminum:  9388.160<br />lwr: 0.167364136","Aluminum:  9542.662<br />lwr: 0.168333130","Aluminum:  9559.510<br />lwr: 0.168438180","Aluminum:  9700.000<br />lwr: 0.169309531","Aluminum:  9896.680<br />lwr: 0.170515769","Aluminum: 10005.812<br />lwr: 0.171178393","Aluminum: 10050.000<br />lwr: 0.171445362","Aluminum: 10233.858<br />lwr: 0.172548084","Aluminum: 10343.200<br />lwr: 0.173197813","Aluminum: 10379.837<br />lwr: 0.173414522","Aluminum: 10711.560<br />lwr: 0.175354505","Aluminum: 10869.710<br />lwr: 0.176265724","Aluminum: 10891.960<br />lwr: 0.176393232","Aluminum: 10908.460<br />lwr: 0.176487680","Aluminum: 10990.470<br />lwr: 0.176955749","Aluminum: 10990.530<br />lwr: 0.176956090","Aluminum: 11116.490<br />lwr: 0.177670617","Aluminum: 11359.000<br />lwr: 0.179031670","Aluminum: 11526.000<br />lwr: 0.179958032","Aluminum: 11711.000<br />lwr: 0.180974155","Aluminum: 11803.000<br />lwr: 0.181475605","Aluminum: 11855.800<br />lwr: 0.181762252","Aluminum: 11985.000<br />lwr: 0.182460200","Aluminum: 12055.930<br />lwr: 0.182841300","Aluminum: 12219.017<br />lwr: 0.183712079","Aluminum: 12247.000<br />lwr: 0.183860733","Aluminum: 12414.483<br />lwr: 0.184745886","Aluminum: 12430.700<br />lwr: 0.184831182","Aluminum: 12560.000<br />lwr: 0.185508693","Aluminum: 12600.000<br />lwr: 0.185717372","Aluminum: 12641.000<br />lwr: 0.185930823","Aluminum: 12697.000<br />lwr: 0.186221643","Aluminum: 12699.930<br />lwr: 0.186236837","Aluminum: 12800.710<br />lwr: 0.186758047","Aluminum: 12837.925<br />lwr: 0.186949842","Aluminum: 12876.191<br />lwr: 0.187146680","Aluminum: 12911.000<br />lwr: 0.187325406","Aluminum: 13313.000<br />lwr: 0.189367229","Aluminum: 13535.000<br />lwr: 0.190477735","Aluminum: 13578.400<br />lwr: 0.190693454","Aluminum: 13714.000<br />lwr: 0.191364587","Aluminum: 13720.174<br />lwr: 0.191395042","Aluminum: 13775.000<br />lwr: 0.191665098","Aluminum: 13871.300<br />lwr: 0.192137762","Aluminum: 13983.000<br />lwr: 0.192683360","Aluminum: 14157.000<br />lwr: 0.193527669","Aluminum: 14165.940<br />lwr: 0.193570867","Aluminum: 14369.230<br />lwr: 0.194548438","Aluminum: 14376.210<br />lwr: 0.194581844","Aluminum: 14380.579<br />lwr: 0.194602748","Aluminum: 14638.271<br />lwr: 0.195828522","Aluminum: 14744.157<br />lwr: 0.196328144","Aluminum: 14960.965<br />lwr: 0.197343951","Aluminum: 15050.070<br />lwr: 0.197758670","Aluminum: 15400.080<br />lwr: 0.199372501","Aluminum: 15580.000<br />lwr: 0.200192849","Aluminum: 15667.844<br />lwr: 0.200591149","Aluminum: 15747.000<br />lwr: 0.200948819","Aluminum: 15855.930<br />lwr: 0.201439126","Aluminum: 15982.549<br />lwr: 0.202006321","Aluminum: 16187.748<br />lwr: 0.202919373","Aluminum: 16285.040<br />lwr: 0.203349665","Aluminum: 16374.220<br />lwr: 0.203742621","Aluminum: 16378.832<br />lwr: 0.203762906","Aluminum: 16554.910<br />lwr: 0.204534573","Aluminum: 16744.907<br />lwr: 0.205361304","Aluminum: 16986.000<br />lwr: 0.206401671","Aluminum: 17250.000<br />lwr: 0.207529980","Aluminum: 17376.000<br />lwr: 0.208064552","Aluminum: 17668.669<br />lwr: 0.209296627","Aluminum: 18190.640<br />lwr: 0.211461622","Aluminum: 18253.450<br />lwr: 0.211719417","Aluminum: 18567.346<br />lwr: 0.212999228","Aluminum: 18721.000<br />lwr: 0.213620600","Aluminum: 18771.346<br />lwr: 0.213823479","Aluminum: 18915.000<br />lwr: 0.214400431","Aluminum: 18941.560<br />lwr: 0.214506792","Aluminum: 18948.944<br />lwr: 0.214536345","Aluminum: 19043.000<br />lwr: 0.214912128","Aluminum: 19174.000<br />lwr: 0.215433516","Aluminum: 19482.960<br />lwr: 0.216654130","Aluminum: 19494.000<br />lwr: 0.216697513","Aluminum: 19555.370<br />lwr: 0.216938386","Aluminum: 19741.000<br />lwr: 0.217664004","Aluminum: 19770.000<br />lwr: 0.217776964","Aluminum: 19778.615<br />lwr: 0.217810500","Aluminum: 19814.984<br />lwr: 0.217951972","Aluminum: 20147.874<br />lwr: 0.219239140","Aluminum: 20447.460<br />lwr: 0.220385812","Aluminum: 21255.484<br />lwr: 0.223425281","Aluminum: 21460.000<br />lwr: 0.224182685","Aluminum: 22988.650<br />lwr: 0.229701094","Aluminum: 23301.643<br />lwr: 0.230801458","Aluminum: 23502.000<br />lwr: 0.231500821","Aluminum: 23767.000<br />lwr: 0.232419922","Aluminum: 23920.000<br />lwr: 0.232947554","Aluminum: 23973.990<br />lwr: 0.233133220","Aluminum: 24381.260<br />lwr: 0.234525138","Aluminum: 24556.268<br />lwr: 0.235118634","Aluminum: 24654.550<br />lwr: 0.235450734","Aluminum: 24669.671<br />lwr: 0.235501752","Aluminum: 25231.350<br />lwr: 0.237382690","Aluminum: 25590.000<br />lwr: 0.238569585","Aluminum: 25981.900<br />lwr: 0.239854263","Aluminum: 26372.522<br />lwr: 0.241122325","Aluminum: 26929.000<br />lwr: 0.242907965","Aluminum: 27052.400<br />lwr: 0.243300690","Aluminum: 27375.200<br />lwr: 0.244322557","Aluminum: 27477.140<br />lwr: 0.244643639","Aluminum: 27642.276<br />lwr: 0.245162139","Aluminum: 27663.273<br />lwr: 0.245227922","Aluminum: 27760.700<br />lwr: 0.245532737","Aluminum: 27978.000<br />lwr: 0.246210105","Aluminum: 31104.223<br />lwr: 0.255599047","Aluminum: 31230.000<br />lwr: 0.255963728","Aluminum: 31722.000<br />lwr: 0.257381176","Aluminum: 31774.000<br />lwr: 0.257530154","Aluminum: 32181.951<br />lwr: 0.258693472","Aluminum: 32184.000<br />lwr: 0.258699291","Aluminum: 32745.600<br />lwr: 0.260285174","Aluminum: 33202.333<br />lwr: 0.261561987","Aluminum: 34016.422<br />lwr: 0.263809882","Aluminum: 35308.374<br />lwr: 0.267306830","Aluminum: 35573.000<br />lwr: 0.268012829","Aluminum: 35690.000<br />lwr: 0.268323891","Aluminum: 35691.180<br />lwr: 0.268327024","Aluminum: 36720.164<br />lwr: 0.271034647","Aluminum: 37142.860<br />lwr: 0.272132671","Aluminum: 37463.050<br />lwr: 0.272959042","Aluminum: 37847.079<br />lwr: 0.273944163","Aluminum: 38526.000<br />lwr: 0.275670028","Aluminum: 38550.591<br />lwr: 0.275732169","Aluminum: 38606.705<br />lwr: 0.275873872","Aluminum: 39044.600<br />lwr: 0.276975120","Aluminum: 39187.544<br />lwr: 0.277332873","Aluminum: 39434.000<br />lwr: 0.277947710","Aluminum: 39579.000<br />lwr: 0.278308281","Aluminum: 39604.167<br />lwr: 0.278370777","Aluminum: 39947.084<br />lwr: 0.279219769","Aluminum: 40206.800<br />lwr: 0.279859637","Aluminum: 41396.100<br />lwr: 0.282756038","Aluminum: 42860.000<br />lwr: 0.286248129","Aluminum: 42931.000<br />lwr: 0.286415520","Aluminum: 43093.730<br />lwr: 0.286798499","Aluminum: 43385.000<br />lwr: 0.287481661","Aluminum: 43939.000<br />lwr: 0.288772890","Aluminum: 44366.000<br />lwr: 0.289760938","Aluminum: 44434.450<br />lwr: 0.289918753","Aluminum: 44953.234<br />lwr: 0.291109746","Aluminum: 45243.122<br />lwr: 0.291771380","Aluminum: 46587.292<br />lwr: 0.294803924","Aluminum: 48317.759<br />lwr: 0.298625663","Aluminum: 48714.000<br />lwr: 0.299488241","Aluminum: 49005.832<br />lwr: 0.300120629","Aluminum: 52442.580<br />lwr: 0.307390931","Aluminum: 55798.500<br />lwr: 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32184.000<br />param:  127.389<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4262.000<br />param:   24.492<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13535.000<br />param:   63.291<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27978.000<br />param:  112.734<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5553.000<br />param:   17.699<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   229.000<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12697.000<br />param:  376.892<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1103.000<br />param:    3.740<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35573.000<br />param:  108.652<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2743.000<br />param:   17.699<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   415.000<br />param:    3.606<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   284.000<br />param:    3.784<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    9.852<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   811.000<br />param:    6.954<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 48714.000<br />param:  193.956<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18253.450<br />param:  521.996<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37142.860<br />param:  207.792<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5864.040<br />param:   36.326<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14369.230<br />param:   70.769<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    7.246<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.375<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15050.070<br />param:   62.947<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.246<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9896.680<br />param:   35.345<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3164.560<br />param:   20.138<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12800.710<br />param:   62.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.603<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1264.420<br />param:   15.528<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5978.370<br />param:   21.632<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.441<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   193.720<br />param:    6.457<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27477.140<br />param:   79.071<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    6.616<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    5.627<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2318.710<br />param:   11.366<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17376.000<br />param:  368.257<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12560.000<br />param:   21.198<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44366.000<br />param:  202.729<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14157.000<br />param:   15.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12911.000<br />param:   45.814<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    6.727<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 26929.000<br />param:  353.001<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   509.000<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8361.000<br />param:   63.345<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9700.000<br />param:   22.822<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11985.000<br />param:   29.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1505.000<br />param:   73.504<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11359.000<br />param:   58.339<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19174.000<br />param:  135.604<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    47.000<br />param:   28.477<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:   65.163<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1510.570<br />param:    8.056<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18190.640<br />param:   50.476<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2931.600<br />param:    8.143<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   796.650<br />param:   21.908<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2203.280<br />param:    4.157<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1897.960<br />param:   10.204<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   490.970<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3624.320<br />param:   11.691<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3451.720<br />param:  313.248<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5557.760<br />param:   25.804<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 40206.800<br />param:  109.366<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19555.370<br />param:  249.074<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 41396.100<br />param:   87.256<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   869.040<br />param:    2.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23973.990<br />param:   73.141<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2807.090<br />param:    5.973<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4982.140<br />param:   31.759<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24381.260<br />param:   85.907<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1012.110<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15855.930<br />param:   41.399<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6101.770<br />param:   10.781<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6540.170<br />param:   16.149<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3964.300<br />param:    8.302<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1514.000<br />param:    6.271<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1879.000<br />param:    6.891<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17250.000<br />param:   74.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2300.000<br />param:   11.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6513.000<br />param:   18.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5063.000<br />param:   20.460<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1257.000<br />param:    4.856<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1405.000<br />param:    7.101<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    15.400<br />param:   16.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1516.000<br />param:    5.244<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2672.000<br />param:    6.860<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2957.000<br />param:    7.604<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 31230.000<br />param:   78.910<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 21460.000<br />param:   42.110<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2126.000<br />param:    8.765<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35690.000<br />param:   89.830<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 42860.000<br />param:  388.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1249.000<br />param:    4.902<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10050.000<br />param:   26.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1337.000<br />param:    5.519<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7196.000<br />param:   18.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7563.000<br />param:   16.540<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 49005.832<br />param:  169.539<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13720.174<br />param:   54.024<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1242.758<br />param:    4.876<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 20147.874<br />param:   42.017<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1163.618<br />param:    5.589<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35691.180<br />param:   83.739<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1995.007<br />param:    6.917<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27663.273<br />param:   57.114<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   958.914<br />param:    7.756<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6226.436<br />param:   18.566<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39604.167<br />param:   70.385<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5074.345<br />param:   13.083<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3418.530<br />param:   10.937<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3282.839<br />param:   10.095<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10869.710<br />param:   28.684<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 33202.333<br />param:  108.963<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   852.194<br />param:    4.832<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    13.682<br />param:    9.186<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2669.586<br />param:   10.817<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4213.850<br />param:   10.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1982.243<br />param:   10.754<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   857.074<br />param:    5.252<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 27642.276<br />param:   84.762<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10233.858<br />param:   32.660<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1740.733<br />param:    5.450<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37847.079<br />param:  112.392<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 34016.422<br />param:   96.228<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 46587.292<br />param:  128.620<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 37463.050<br />param:   93.333<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 45243.122<br />param:  107.916<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44953.234<br />param:  105.119<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 36720.164<br />param:   76.911<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39187.544<br />param:   80.582<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 52442.580<br />param:  117.960<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 44434.450<br />param:  208.968<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2939.076<br />param:   10.489<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1444.554<br />param:    3.338<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4010.643<br />param:    8.439<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 32181.951<br />param:  167.585<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2802.720<br />param:    9.182<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1987.046<br />param:    5.616<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1378.924<br />param:   15.269<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14380.579<br />param:   38.021<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7025.862<br />param:   21.667<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4679.724<br />param:   13.686<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12219.017<br />param:   36.607<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1391.532<br />param:   10.209<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4413.802<br />param:   18.907<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12876.191<br />param:  470.696<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10379.837<br />param:   34.908<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3281.956<br />param:   10.581<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15667.844<br />param:   57.753<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2877.037<br />param:   11.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12414.483<br />param:   47.703<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5944.163<br />param:   31.900<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:   15.802<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19814.984<br />param:   67.375<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24669.671<br />param:   79.497<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3236.928<br />param:   10.362<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3100.587<br />param:   11.208<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2818.775<br />param:   13.607<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1051.178<br />param:    6.171<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18948.944<br />param:  133.334<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1854.259<br />param:    6.422<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3605.617<br />param:   16.075<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16378.832<br />param:   88.027<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1272.795<br />param:    6.784<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1078.048<br />param:    6.337<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3862.314<br />param:   11.661<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12055.930<br />param:   39.857<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11855.800<br />param:   40.795<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   876.120<br />param:    3.947<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.165<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8101.529<br />param:   17.785<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2576.414<br />param:   12.453<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12837.925<br />param:   88.766<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:     0.010<br />param:    2.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2228.554<br />param:    5.029<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1896.303<br />param:    2.927<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1992.915<br />param:    3.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5839.321<br />param:   16.696<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16187.748<br />param:  164.123<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1438.131<br />param:    2.656<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 17668.669<br />param:   71.239<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14744.157<br />param:   97.788<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1390.946<br />param:    4.158<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1492.379<br />param:    2.215<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1045.362<br />param:    2.879<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2630.018<br />param:    7.828<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14638.271<br />param:  184.134<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24556.268<br />param:   94.600<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   635.748<br />param:    1.521<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2063.092<br />param:    7.365<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   826.707<br />param:    2.496<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1050.806<br />param:    2.916<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1091.386<br />param:    5.124<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18771.346<br />param:   95.466<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2634.581<br />param:    6.654<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2483.576<br />param:    7.989<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1892.563<br />param:    4.596<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18567.346<br />param:   43.261<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 35308.374<br />param:   83.549<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 21255.484<br />param:   64.177<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2084.699<br />param:    5.430<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4015.608<br />param:    8.194<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3482.766<br />param:   12.796<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10005.812<br />param:   30.531<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1983.986<br />param:    7.587<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 39947.084<br />param:  385.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7301.650<br />param:   26.305<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 38606.705<br />param:  125.456<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 22988.650<br />param:   74.866<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 48317.759<br />param:  106.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23301.643<br />param:   87.778<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4829.056<br />param:    9.001<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1837.786<br />param:    7.398<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1116.333<br />param:    3.373<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2627.657<br />param:    9.175<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3313.481<br />param:   21.392<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4940.032<br />param:   14.768<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1055.110<br />param:    7.665<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5683.264<br />param:   15.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3102.896<br />param:    8.386<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 31104.223<br />param:   82.655<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1903.281<br />param:    5.389<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9542.662<br />param:   24.151<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1183.886<br />param:    4.143<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2529.418<br />param:   10.206<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16744.907<br />param:   45.668<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1033.457<br />param:    2.594<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1987.528<br />param:    5.635<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5080.363<br />param:   14.867<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4347.880<br />param:   11.910<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14960.965<br />param:   35.586<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1939.394<br />param:    7.713<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1055.329<br />param:    3.934<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15982.549<br />param:   43.477<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 38550.591<br />param:  196.740<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5435.273<br />param:   32.615<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 26372.522<br />param:   80.772<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19778.615<br />param:   61.940<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2568.130<br />param:    6.990<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2696.274<br />param:    7.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1997.376<br />param:    7.498<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   820.028<br />param:    2.883<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2944.010<br />param:    5.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25590.000<br />param:  101.960<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7772.280<br />param:   15.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 23920.000<br />param:   27.210<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4022.320<br />param:    7.220<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1439.250<br />param:    5.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25231.350<br />param:   55.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8156.740<br />param:   12.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6905.380<br />param:  169.400<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9388.160<br />param:   22.340<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7109.340<br />param:   16.320<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6684.020<br />param:   36.970<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8057.890<br />param:   16.890<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6825.000<br />param:   12.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2709.270<br />param:    4.100<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2391.420<br />param:    2.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1154.750<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   692.300<br />param:    0.250<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9034.470<br />param:   36.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 15400.080<br />param:   89.150<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   549.690<br />param:    9.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10908.460<br />param:   30.340<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3797.610<br />param:   14.110<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1544.300<br />param:    2.200<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2073.900<br />param:   12.090<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3152.230<br />param:   10.430<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2808.280<br />param:    8.590<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    22.325<br />param:   11.730<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8356.760<br />param:   34.370<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1695.280<br />param:   17.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   599.820<br />param:   10.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1871.680<br />param:   11.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2252.090<br />param:   13.820<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1420.100<br />param:   11.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4398.600<br />param:   17.030<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 13871.300<br />param:   29.550<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6171.030<br />param:   23.380<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3990.310<br />param:   24.700<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2913.650<br />param:   14.590<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5632.510<br />param:   22.780<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16554.910<br />param:   31.450<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1796.740<br />param:   10.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4397.970<br />param:   26.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3530.330<br />param:   16.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3403.350<br />param:   13.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16285.040<br />param:   63.290<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 18941.560<br />param:   71.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   392.440<br />param:    2.530<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14165.940<br />param:   52.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3466.580<br />param:    6.670<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    46.875<br />param: 1227.420<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1588.720<br />param:    3.090<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 20447.460<br />param:  114.190<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3276.100<br />param:    9.270<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2350.710<br />param:    7.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 12699.930<br />param:   45.490<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8172.880<br />param:   28.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6687.320<br />param:   21.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4924.490<br />param:   11.710<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3234.290<br />param:    8.070<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5208.540<br />param:   14.640<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1563.510<br />param:    5.510<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4000.870<br />param:    7.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3284.770<br />param:   13.260<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2886.310<br />param:    9.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 19482.960<br />param:   51.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1428.100<br />param:    4.480<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    42.500<br />param:   11.130<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3029.720<br />param:    7.330<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1336.970<br />param:    3.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1489.760<br />param:    5.580<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3278.080<br />param:    6.080<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 24654.550<br />param:  104.440<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 14376.210<br />param:   61.020<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 25981.900<br />param:  119.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1384.410<br />param:    5.210<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10891.960<br />param:   41.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10711.560<br />param:   47.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1224.440<br />param:    8.310<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:    32.600<br />param:   10.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4404.900<br />param:   10.500<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1018.690<br />param:    3.170<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   838.370<br />param:    3.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4534.800<br />param:   26.980<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1232.130<br />param:    1.660<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5023.810<br />param:   34.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 16374.220<br />param:   80.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 43093.730<br />param:  229.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3739.930<br />param:    9.680<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 11116.490<br />param:  201.050<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9559.510<br />param:   39.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1476.780<br />param:    8.730<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  4506.180<br />param:   11.600<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2471.350<br />param:    2.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8737.050<br />param:   37.690<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   159.380<br />param:   54.530<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  8179.610<br />param:   33.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   142.570<br />param:   57.880<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   125.450<br />param:   70.190<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   189.500<br />param:   51.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   117.170<br />param:   36.550<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   607.580<br />param:    3.410<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  2740.800<br />param:   10.060<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   956.710<br />param:    5.790<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   691.160<br />param:  782.290<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   317.090<br />param:   12.350<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   588.850<br />param:   50.470<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  7779.340<br />param:   38.080<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5149.080<br />param:   42.240<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1094.920<br />param:    4.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1314.420<br />param:    3.720<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   438.840<br />param:    0.010<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   236.490<br />param:    7.650<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1251.510<br />param:   17.990<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6376.780<br />param:   50.220<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1951.550<br />param:    8.890<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum: 10990.530<br />param:   45.260<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   507.730<br />param:    7.140<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1821.360<br />param:   14.560<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:   295.270<br />param:    6.000<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  3437.730<br />param:   19.180<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  6132.060<br />param:   60.670<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  9035.970<br />param:   97.640<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  1074.580<br />param:   20.230<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  5691.840<br />param:   56.160<br />AreaAbbr: HB<br />AreaAbbr: HB","Aluminum:  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   0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2790.000<br />param:    2.007<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2474.000<br />param:    2.334<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2576.000<br />param:    4.727<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   678.540<br />param:   14.136<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.370<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.586<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:   11.413<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    8.251<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    6.911<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.894<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.006<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    8.651<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.269<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.714<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.736<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.901<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1486.450<br />param:    2.915<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    9.518<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.137<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:   12.542<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3162.000<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   909.630<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6576.330<br />param:    7.971<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1915.710<br />param:    4.033<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1639.990<br />param:    3.952<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1967.730<br />param:    3.935<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   217.180<br />param:    1.974<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4100.130<br />param:    4.316<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   881.230<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   708.500<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1380.000<br />param:    2.000<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1207.000<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2808.490<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1282.310<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   636.290<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1719.550<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   466.820<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   287.200<br />param:    3.452<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   187.400<br />param:    3.827<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   726.200<br />param:    4.753<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3275.000<br />param:    5.396<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   147.600<br />param:    2.903<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   131.900<br />param:    2.434<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4109.000<br />param:    3.147<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   155.500<br />param:    2.769<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3102.000<br />param:    6.810<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1646.000<br />param:    3.460<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1989.000<br />param:    6.330<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   856.000<br />param:    4.500<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   816.000<br />param:    3.290<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    42.600<br />param:    6.230<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   795.000<br />param:    4.090<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    18.000<br />param:    8.650<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   364.300<br />param:    2.582<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2612.809<br />param:    9.471<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1090.747<br />param:    6.330<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   593.576<br />param:    3.655<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    13.179<br />param:   11.656<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1172.002<br />param:    3.353<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   782.951<br />param:    4.882<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2944.066<br />param:    7.568<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   851.132<br />param:    3.626<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.000<br />param:    0.000<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   852.109<br />param:    2.783<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5263.700<br />param:    7.623<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   518.945<br />param:    3.113<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2929.158<br />param:    5.625<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3056.245<br />param:    9.843<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   683.683<br />param:    4.489<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1456.507<br />param:    3.592<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1038.283<br />param:    3.089<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6507.398<br />param:    5.233<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   602.688<br />param:    2.693<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   537.306<br />param:    2.870<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   689.070<br />param:    9.441<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   729.903<br />param:    4.817<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.904<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1833.140<br />param:    6.311<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2958.811<br />param:    6.905<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   602.242<br />param:    2.056<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1820.267<br />param:    6.530<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3740.938<br />param:    7.522<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    3.137<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3112.807<br />param:    5.691<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1065.343<br />param:    5.352<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1393.442<br />param:    4.099<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   932.070<br />param:    5.045<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    4.470<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   757.860<br />param:    6.763<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   354.368<br />param:    2.864<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.270<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   622.248<br />param:    1.234<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    1.878<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    2.465<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2470.551<br />param:    8.510<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3919.187<br />param:    3.755<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   885.409<br />param:    1.620<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3180.716<br />param:    4.366<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3210.491<br />param:    6.746<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3307.181<br />param:    3.486<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    6.172<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   868.557<br />param:    3.867<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2602.336<br />param:    3.875<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  8110.616<br />param:    4.807<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   932.243<br />param:    4.172<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2159.053<br />param:    4.410<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3892.890<br />param:   10.684<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   263.211<br />param:    1.404<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   717.431<br />param:    2.171<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4319.253<br />param:    4.064<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.265<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   210.447<br />param:    1.529<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1528.931<br />param:    3.355<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    5.581<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   117.842<br />param:    3.992<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1413.720<br />param:    1.861<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2313.950<br />param:    3.550<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  2038.750<br />param:    0.010<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:     0.010<br />param:    4.930<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   700.090<br />param:    8.790<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    15.650<br />param:    1.590<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   654.870<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:    4.150<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   976.090<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   474.810<br />param:    8.490<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   185.090<br />param:    8.170<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   922.730<br />param:    4.970<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:   13.790<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  3181.660<br />param:    8.430<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   633.020<br />param:    7.370<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1284.840<br />param:   13.190<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    46.875<br />param:   18.780<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1380.670<br />param:   11.630<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   768.500<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    22.325<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1731.580<br />param:    0.715<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:   583.780<br />param:    1.535<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:    42.500<br />param:    1.535<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1830.990<br />param:    3.810<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1566.950<br />param:    1.290<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4223.620<br />param:    3.690<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  6217.790<br />param:    5.880<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1716.850<br />param:    1.050<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5212.570<br />param:    4.280<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5060.340<br />param:    5.450<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5128.640<br />param:    4.200<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  1089.320<br />param:    2.540<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4017.990<br />param:    3.500<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  5616.320<br />param:    2.780<br />AreaAbbr: LTB<br />AreaAbbr: LTB","Aluminum:  4519.660<br />param:    2.420<br />AreaAbbr: LTB<br 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15.400<br />fit:  1.30424361","Aluminum:    15.650<br />fit:  1.31171107","Aluminum:    18.000<br />fit:  1.37841168","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    22.325<br />fit:  1.48776549","Aluminum:    32.600<br />fit:  1.70148818","Aluminum:    42.500<br />fit:  1.86922227","Aluminum:    42.500<br />fit:  1.86922227","Aluminum:    42.600<br />fit:  1.87078038","Aluminum:    46.875<br />fit:  1.93529489","Aluminum:    46.875<br />fit:  1.93529489","Aluminum:    47.000<br />fit:  1.93712298","Aluminum:    47.400<br />fit:  1.94295189","Aluminum:    53.000<br />fit:  2.02141745","Aluminum:    74.400<br />fit:  2.27969973","Aluminum:    97.810<br />fit:  2.51188528","Aluminum:   117.170<br />fit:  2.67797755","Aluminum:   117.842<br />fit:  2.68341273","Aluminum:   125.450<br />fit:  2.74359707","Aluminum:   131.900<br />fit:  2.79280088","Aluminum:   142.570<br />fit:  2.87089480","Aluminum:   147.600<br />fit:  2.90640349","Aluminum:   155.500<br />fit:  2.96062880","Aluminum:   159.380<br />fit:  2.98661111","Aluminum:   185.090<br />fit:  3.14923647","Aluminum:   187.400<br />fit:  3.16311521","Aluminum:   189.500<br />fit:  3.17563673","Aluminum:   191.200<br />fit:  3.18570776","Aluminum:   193.720<br />fit:  3.20053079","Aluminum:   210.447<br />fit:  3.29589937","Aluminum:   217.180<br />fit:  3.33290489","Aluminum:   221.700<br />fit:  3.35733380","Aluminum:   229.000<br />fit:  3.39611763","Aluminum:   236.490<br />fit:  3.43509011","Aluminum:   244.300<br />fit:  3.47488819","Aluminum:   247.300<br />fit:  3.48995710","Aluminum:   247.740<br />fit:  3.49215727","Aluminum:   263.211<br />fit:  3.56796683","Aluminum:   284.000<br />fit:  3.66543448","Aluminum:   285.630<br />fit:  3.67287920","Aluminum:   287.200<br />fit:  3.68002400","Aluminum:   291.780<br />fit:  3.70072382","Aluminum:   295.270<br />fit:  3.71635689","Aluminum:   310.900<br />fit:  3.78494387","Aluminum:   317.090<br />fit:  3.81149093","Aluminum:   344.600<br />fit:  3.92559170","Aluminum:   350.290<br />fit:  3.94845079","Aluminum:   354.368<br />fit:  3.96468675","Aluminum:   364.300<br />fit:  4.00373136","Aluminum:   367.700<br />fit:  4.01693938","Aluminum:   368.000<br />fit:  4.01810100","Aluminum:   384.500<br />fit:  4.08107124","Aluminum:   385.400<br />fit:  4.08445539","Aluminum:   392.440<br />fit:  4.11075256","Aluminum:   400.000<br />fit:  4.13865525","Aluminum:   402.290<br />fit:  4.14704001","Aluminum:   415.000<br />fit:  4.19302604","Aluminum:   435.400<br />fit:  4.26497155","Aluminum:   438.840<br />fit:  4.27688777","Aluminum:   458.000<br />fit:  4.34217901","Aluminum:   466.820<br />fit:  4.37164276","Aluminum:   474.810<br />fit:  4.39802521","Aluminum:   490.970<br />fit:  4.45052130","Aluminum:   491.110<br />fit:  4.45097118","Aluminum:   506.170<br />fit:  4.49889037","Aluminum:   507.730<br />fit:  4.50380124","Aluminum:   509.000<br />fit:  4.50779200","Aluminum:   516.000<br />fit:  4.52967381","Aluminum:   518.945<br />fit:  4.53882254","Aluminum:   537.306<br />fit:  4.59511912","Aluminum:   549.690<br />fit:  4.63239178","Aluminum:   583.780<br />fit:  4.73227214","Aluminum:   585.800<br />fit:  4.73807102","Aluminum:   588.850<br />fit:  4.74680234","Aluminum:   593.576<br />fit:  4.76027413","Aluminum:   599.820<br />fit:  4.77796733","Aluminum:   600.000<br />fit:  4.77847562","Aluminum:   602.242<br />fit:  4.78479839","Aluminum:   602.688<br />fit:  4.78605436","Aluminum:   607.580<br />fit:  4.79979142","Aluminum:   608.200<br />fit:  4.80152732","Aluminum:   622.248<br />fit:  4.84055700","Aluminum:   630.000<br />fit:  4.86185134","Aluminum:   633.020<br />fit:  4.87010134","Aluminum:   635.748<br />fit:  4.87753185","Aluminum:   636.290<br />fit:  4.87900569","Aluminum:   639.840<br />fit:  4.88863911","Aluminum:   654.870<br />fit:  4.92904727","Aluminum:   678.540<br />fit:  4.99148771","Aluminum:   683.683<br />fit:  5.00486808","Aluminum:   689.070<br />fit:  5.01881378","Aluminum:   690.000<br />fit:  5.02121420","Aluminum:   691.160<br />fit:  5.02420535","Aluminum:   692.300<br />fit:  5.02714178","Aluminum:   700.000<br />fit:  5.04689426","Aluminum:   700.090<br />fit:  5.04712430","Aluminum:   704.500<br />fit:  5.05837306","Aluminum:   708.500<br />fit:  5.06853676","Aluminum:   717.431<br />fit:  5.09109686","Aluminum:   724.300<br />fit:  5.10832523","Aluminum:   726.200<br />fit:  5.11307205","Aluminum:   729.903<br />fit:  5.12230036","Aluminum:   742.770<br />fit:  5.15413350","Aluminum:   756.970<br />fit:  5.18885401","Aluminum:   757.450<br />fit:  5.19002029","Aluminum:   757.860<br />fit:  5.19101611","Aluminum:   759.500<br />fit:  5.19499590","Aluminum:   768.500<br />fit:  5.21673808","Aluminum:   773.110<br />fit:  5.22781129","Aluminum:   775.800<br />fit:  5.23425299","Aluminum:   781.000<br />fit:  5.24666458","Aluminum:   782.951<br />fit:  5.25130756","Aluminum:   786.460<br />fit:  5.25963948","Aluminum:   791.690<br />fit:  5.27201342","Aluminum:   795.000<br />fit:  5.27981748","Aluminum:   796.650<br />fit:  5.28369989","Aluminum:   811.000<br />fit:  5.31724827","Aluminum:   816.000<br />fit:  5.32884753","Aluminum:   820.028<br />fit:  5.33815858","Aluminum:   826.707<br />fit:  5.35353278","Aluminum:   838.370<br />fit:  5.38018841","Aluminum:   851.132<br />fit:  5.40908295","Aluminum:   852.109<br />fit:  5.41128342","Aluminum:   852.194<br />fit:  5.41147479","Aluminum:   856.000<br />fit:  5.42003092","Aluminum:   857.074<br />fit:  5.42244090","Aluminum:   865.660<br />fit:  5.44163753","Aluminum:   868.557<br />fit:  5.44808692","Aluminum:   869.040<br />fit:  5.44916084","Aluminum:   873.000<br />fit:  5.45795114","Aluminum:   876.120<br />fit:  5.46485873","Aluminum:   881.230<br />fit:  5.47613789","Aluminum:   883.240<br />fit:  5.48056294","Aluminum:   885.409<br />fit:  5.48533075","Aluminum:   891.670<br />fit:  5.49905127","Aluminum:   900.000<br />fit:  5.51720978","Aluminum:   900.000<br />fit:  5.51720978","Aluminum:   909.630<br />fit:  5.53806747","Aluminum:   922.500<br />fit:  5.56572135","Aluminum:   922.730<br />fit:  5.56621328","Aluminum:   932.070<br />fit:  5.58612347","Aluminum:   932.243<br />fit:  5.58649103","Aluminum:   956.710<br />fit:  5.63803826","Aluminum:   958.914<br />fit:  5.64263970","Aluminum:   963.190<br />fit:  5.65154755","Aluminum:   965.100<br />fit:  5.65551825","Aluminum:   976.090<br />fit:  5.67826739","Aluminum:  1000.000<br />fit:  5.72719576","Aluminum:  1000.000<br />fit:  5.72719576","Aluminum:  1003.810<br />fit:  5.73492239","Aluminum:  1012.110<br />fit:  5.75168939","Aluminum:  1018.690<br />fit:  5.76491881","Aluminum:  1030.410<br />fit:  5.78834652","Aluminum:  1033.457<br />fit:  5.79440912","Aluminum:  1038.283<br />fit:  5.80398784","Aluminum:  1045.362<br />fit:  5.81798648","Aluminum:  1047.000<br />fit:  5.82121688","Aluminum:  1050.806<br />fit:  5.82871036","Aluminum:  1051.178<br />fit:  5.82944184","Aluminum:  1055.110<br />fit:  5.83716326","Aluminum:  1055.329<br />fit:  5.83759277","Aluminum:  1055.500<br />fit:  5.83792810","Aluminum:  1065.343<br />fit:  5.85717151","Aluminum:  1074.580<br />fit:  5.87512606","Aluminum:  1078.048<br />fit:  5.88184131","Aluminum:  1089.320<br />fit:  5.90357197","Aluminum:  1090.747<br />fit:  5.90631264","Aluminum:  1091.386<br />fit:  5.90753914","Aluminum:  1094.920<br />fit:  5.91431396","Aluminum:  1103.000<br />fit:  5.92975080","Aluminum:  1116.333<br />fit:  5.95506469","Aluminum:  1123.390<br />fit:  5.96838411","Aluminum:  1132.000<br />fit:  5.98456173","Aluminum:  1154.750<br />fit:  6.02692881","Aluminum:  1163.618<br />fit:  6.04329762","Aluminum:  1172.002<br />fit:  6.05869916","Aluminum:  1183.886<br />fit:  6.08040888","Aluminum:  1202.900<br />fit:  6.11485304","Aluminum:  1207.000<br />fit:  6.12223412","Aluminum:  1224.440<br />fit:  6.15345115","Aluminum:  1232.130<br />fit:  6.16712484","Aluminum:  1242.758<br />fit:  6.18593226","Aluminum:  1249.000<br />fit:  6.19692981","Aluminum:  1251.510<br />fit:  6.20134209","Aluminum:  1257.000<br />fit:  6.21097298","Aluminum:  1264.420<br />fit:  6.22394654","Aluminum:  1272.795<br />fit:  6.23853098","Aluminum:  1282.310<br />fit:  6.25502567","Aluminum:  1284.840<br />fit:  6.25939824","Aluminum:  1300.000<br />fit:  6.28548336","Aluminum:  1300.000<br />fit:  6.28548336","Aluminum:  1314.420<br />fit:  6.31011361","Aluminum:  1336.970<br />fit:  6.34828318","Aluminum:  1337.000<br />fit:  6.34833368","Aluminum:  1378.924<br />fit:  6.41820595","Aluminum:  1380.000<br />fit:  6.41998109","Aluminum:  1380.670<br />fit:  6.42108598","Aluminum:  1384.000<br />fit:  6.42657230","Aluminum:  1384.410<br />fit:  6.42724720","Aluminum:  1390.946<br />fit:  6.43798878","Aluminum:  1391.532<br />fit:  6.43895025","Aluminum:  1393.442<br />fit:  6.44208224","Aluminum:  1400.000<br />fit:  6.45281488","Aluminum:  1405.000<br />fit:  6.46097596","Aluminum:  1413.720<br />fit:  6.47516415","Aluminum:  1420.100<br />fit:  6.48550921","Aluminum:  1428.100<br />fit:  6.49843876","Aluminum:  1438.131<br />fit:  6.51458492","Aluminum:  1439.250<br />fit:  6.51638158","Aluminum:  1444.554<br />fit:  6.52488541","Aluminum:  1456.507<br />fit:  6.54397587","Aluminum:  1476.780<br />fit:  6.57612454","Aluminum:  1486.450<br />fit:  6.59135881","Aluminum:  1489.760<br />fit:  6.59655873","Aluminum:  1492.379<br />fit:  6.60066784","Aluminum:  1497.000<br />fit:  6.60790665","Aluminum:  1500.000<br />fit:  6.61259845","Aluminum:  1505.000<br />fit:  6.62040467","Aluminum:  1510.570<br />fit:  6.62908111","Aluminum:  1514.000<br />fit:  6.63441378","Aluminum:  1516.000<br />fit:  6.63751961","Aluminum:  1528.931<br />fit:  6.65753682","Aluminum:  1534.980<br />fit:  6.66686318","Aluminum:  1537.150<br />fit:  6.67020310","Aluminum:  1544.300<br />fit:  6.68118645","Aluminum:  1563.510<br />fit:  6.71053390","Aluminum:  1566.950<br />fit:  6.71576464","Aluminum:  1582.670<br />fit:  6.73957405","Aluminum:  1588.720<br />fit:  6.74869666","Aluminum:  1600.000<br />fit:  6.76564571","Aluminum:  1600.000<br />fit:  6.76564571","Aluminum:  1603.200<br />fit:  6.77043991","Aluminum:  1639.990<br />fit:  6.82511974","Aluminum:  1646.000<br />fit:  6.83397675","Aluminum:  1669.150<br />fit:  6.86789945","Aluminum:  1695.280<br />fit:  6.90582600","Aluminum:  1698.000<br />fit:  6.90975222","Aluminum:  1700.000<br />fit:  6.91263656","Aluminum:  1700.000<br />fit:  6.91263656","Aluminum:  1716.850<br />fit:  6.93685059","Aluminum:  1719.550<br />fit:  6.94071631","Aluminum:  1731.580<br />fit:  6.95789276","Aluminum:  1740.733<br />fit:  6.97090991","Aluminum:  1764.700<br />fit:  7.00478713","Aluminum:  1777.400<br />fit:  7.02261823","Aluminum:  1796.740<br />fit:  7.04961477","Aluminum:  1820.267<br />fit:  7.08220422","Aluminum:  1821.360<br />fit:  7.08371161","Aluminum:  1830.990<br />fit:  7.09696748","Aluminum:  1833.140<br />fit:  7.09992084","Aluminum:  1837.786<br />fit:  7.10629523","Aluminum:  1845.800<br />fit:  7.11726617","Aluminum:  1854.259<br />fit:  7.12881300","Aluminum:  1871.680<br />fit:  7.15248660","Aluminum:  1879.000<br />fit:  7.16239140","Aluminum:  1884.050<br />fit:  7.16921011","Aluminum:  1892.563<br />fit:  7.18067806","Aluminum:  1896.303<br />fit:  7.18570573","Aluminum:  1897.960<br />fit:  7.18793118","Aluminum:  1903.281<br />fit:  7.19506914","Aluminum:  1915.710<br />fit:  7.21169222","Aluminum:  1918.000<br />fit:  7.21474737","Aluminum:  1939.394<br />fit:  7.24317654","Aluminum:  1951.550<br />fit:  7.25923980","Aluminum:  1967.730<br />fit:  7.28052060","Aluminum:  1982.243<br />fit:  7.29951300","Aluminum:  1983.986<br />fit:  7.30178792","Aluminum:  1987.046<br />fit:  7.30577866","Aluminum:  1987.528<br />fit:  7.30640690","Aluminum:  1989.000<br />fit:  7.30832491","Aluminum:  1992.915<br />fit:  7.31342169","Aluminum:  1995.007<br />fit:  7.31614252","Aluminum:  1997.376<br />fit:  7.31922140","Aluminum:  2019.460<br />fit:  7.34781022","Aluminum:  2032.000<br />fit:  7.36395411","Aluminum:  2038.750<br />fit:  7.37261739","Aluminum:  2063.092<br />fit:  7.40370624","Aluminum:  2073.900<br />fit:  7.41743399","Aluminum:  2084.699<br />fit:  7.43110427","Aluminum:  2126.000<br />fit:  7.48296890","Aluminum:  2159.053<br />fit:  7.52400932","Aluminum:  2203.280<br />fit:  7.57829450","Aluminum:  2228.554<br />fit:  7.60900108","Aluminum:  2252.090<br />fit:  7.63739460","Aluminum:  2275.670<br />fit:  7.66564978","Aluminum:  2277.000<br />fit:  7.66723784","Aluminum:  2295.000<br />fit:  7.68867169","Aluminum:  2300.000<br />fit:  7.69460627","Aluminum:  2313.950<br />fit:  7.71111984","Aluminum:  2318.710<br />fit:  7.71673987","Aluminum:  2350.710<br />fit:  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2647.810<br />fit:  8.08852376","Aluminum:  2669.586<br />fit:  8.11204542","Aluminum:  2672.000<br />fit:  8.11464530","Aluminum:  2696.274<br />fit:  8.14070455","Aluminum:  2698.230<br />fit:  8.14279780","Aluminum:  2709.270<br />fit:  8.15459415","Aluminum:  2737.840<br />fit:  8.18497813","Aluminum:  2740.800<br />fit:  8.18811435","Aluminum:  2743.000<br />fit:  8.19044390","Aluminum:  2763.000<br />fit:  8.21156658","Aluminum:  2790.000<br />fit:  8.23992623","Aluminum:  2802.720<br />fit:  8.25322540","Aluminum:  2807.090<br />fit:  8.25778539","Aluminum:  2808.280<br />fit:  8.25902633","Aluminum:  2808.490<br />fit:  8.25924528","Aluminum:  2818.775<br />fit:  8.26995593","Aluminum:  2847.260<br />fit:  8.29948872","Aluminum:  2877.037<br />fit:  8.33015786","Aluminum:  2886.310<br />fit:  8.33966683","Aluminum:  2900.000<br />fit:  8.35366921","Aluminum:  2913.650<br />fit:  8.36758827","Aluminum:  2929.158<br />fit:  8.38335097","Aluminum:  2931.600<br />fit:  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15.400<br />upr:   98.827633","Aluminum:    15.650<br />upr:   99.391610","Aluminum:    18.000<br />upr:  104.429043","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    22.325<br />upr:  112.687458","Aluminum:    32.600<br />upr:  128.827153","Aluminum:    42.500<br />upr:  141.493734","Aluminum:    42.500<br />upr:  141.493734","Aluminum:    42.600<br />upr:  141.611397","Aluminum:    46.875<br />upr:  146.483290","Aluminum:    46.875<br />upr:  146.483290","Aluminum:    47.000<br />upr:  146.621341","Aluminum:    47.400<br />upr:  147.061519","Aluminum:    53.000<br />upr:  152.986999","Aluminum:    74.400<br />upr:  172.492313","Aluminum:    97.810<br />upr:  190.027981","Aluminum:   117.170<br />upr:  202.572845","Aluminum:   117.842<br />upr:  202.983374","Aluminum:   125.450<br />upr:  207.529270","Aluminum:   131.900<br />upr:  211.245857","Aluminum:   142.570<br />upr:  217.144798","Aluminum:   147.600<br />upr:  219.827063","Aluminum:   155.500<br />upr:  223.923229","Aluminum:   159.380<br />upr:  225.885959","Aluminum:   185.090<br />upr:  238.171362","Aluminum:   187.400<br />upr:  239.219862","Aluminum:   189.500<br />upr:  240.165834","Aluminum:   191.200<br />upr:  240.926680","Aluminum:   193.720<br />upr:  242.046538","Aluminum:   210.447<br />upr:  249.251675","Aluminum:   217.180<br />upr:  252.047544","Aluminum:   221.700<br />upr:  253.893243","Aluminum:   229.000<br />upr:  256.823556","Aluminum:   236.490<br />upr:  259.768178","Aluminum:   244.300<br />upr:  262.775235","Aluminum:   247.300<br />upr:  263.913825","Aluminum:   247.740<br />upr:  264.080068","Aluminum:   263.211<br />upr:  269.808285","Aluminum:   284.000<br />upr:  277.173315","Aluminum:   285.630<br />upr:  277.735881","Aluminum:   287.200<br />upr:  278.275786","Aluminum:   291.780<br />upr:  279.840001","Aluminum:   295.270<br />upr:  281.021349","Aluminum:   310.900<br />upr:  286.204390","Aluminum:   317.090<br />upr:  288.210569","Aluminum:   344.600<br />upr:  296.833547","Aluminum:   350.290<br />upr:  298.561145","Aluminum:   354.368<br />upr:  299.788206","Aluminum:   364.300<br />upr:  302.739111","Aluminum:   367.700<br />upr:  303.737357","Aluminum:   368.000<br />upr:  303.825152","Aluminum:   384.500<br />upr:  308.584462","Aluminum:   385.400<br />upr:  308.840241","Aluminum:   392.440<br />upr:  310.827838","Aluminum:   400.000<br />upr:  312.936813","Aluminum:   402.290<br />upr:  313.570566","Aluminum:   415.000<br />upr:  317.046419","Aluminum:   435.400<br />upr:  322.484584","Aluminum:   438.840<br />upr:  323.385318","Aluminum:   458.000<br />upr:  328.320710","Aluminum:   466.820<br />upr:  330.547941","Aluminum:   474.810<br />upr:  332.542279","Aluminum:   490.970<br />upr:  336.510715","Aluminum:   491.110<br />upr:  336.544725","Aluminum:   506.170<br />upr:  340.167266","Aluminum:   507.730<br />upr:  340.538517","Aluminum:   509.000<br />upr:  340.840212","Aluminum:   516.000<br />upr:  342.494445","Aluminum:   518.945<br />upr:  343.186082","Aluminum:   537.306<br />upr:  347.442132","Aluminum:   549.690<br />upr:  350.260032","Aluminum:   583.780<br />upr:  357.811488","Aluminum:   585.800<br />upr:  358.249925","Aluminum:   588.850<br />upr:  358.910077","Aluminum:   593.576<br />upr:  359.928650","Aluminum:   599.820<br />upr:  361.266405","Aluminum:   600.000<br />upr:  361.304836","Aluminum:   602.242<br />upr:  361.782894","Aluminum:   602.688<br />upr:  361.877857","Aluminum:   607.580<br />upr:  362.916507","Aluminum:   608.200<br />upr:  363.047758","Aluminum:   622.248<br />upr:  365.998811","Aluminum:   630.000<br />upr:  367.608911","Aluminum:   633.020<br />upr:  368.232712","Aluminum:   635.748<br />upr:  368.794552","Aluminum:   636.290<br />upr:  368.905993","Aluminum:   639.840<br />upr:  369.634404","Aluminum:   654.870<br />upr:  372.689824","Aluminum:   678.540<br />upr:  377.411317","Aluminum:   683.683<br />upr:  378.423107","Aluminum:   689.070<br />upr:  379.477652","Aluminum:   690.000<br />upr:  379.659168","Aluminum:   691.160<br />upr:  379.885354","Aluminum:   692.300<br />upr:  380.107402","Aluminum:   700.000<br />upr:  381.601064","Aluminum:   700.090<br />upr:  381.618460","Aluminum:   704.500<br />upr:  382.469086","Aluminum:   708.500<br />upr:  383.237666","Aluminum:   717.431<br />upr:  384.943675","Aluminum:   724.300<br />upr:  386.246509","Aluminum:   726.200<br />upr:  386.605472","Aluminum:   729.903<br />upr:  387.303337","Aluminum:   742.770<br />upr:  389.710652","Aluminum:   756.970<br />upr:  392.336365","Aluminum:   757.450<br />upr:  392.424565","Aluminum:   757.860<br />upr:  392.499873","Aluminum:   759.500<br />upr:  392.800845","Aluminum:   768.500<br />upr:  394.445110","Aluminum:   773.110<br />upr:  395.282536","Aluminum:   775.800<br />upr:  395.769699","Aluminum:   781.000<br />upr:  396.708350","Aluminum:   782.951<br />upr:  397.059486","Aluminum:   786.460<br />upr:  397.689609","Aluminum:   791.690<br />upr:  398.625424","Aluminum:   795.000<br />upr:  399.215632","Aluminum:   796.650<br />upr:  399.509253","Aluminum:   811.000<br />upr:  402.046494","Aluminum:   816.000<br />upr:  402.923749","Aluminum:   820.028<br />upr:  403.627949","Aluminum:   826.707<br />upr:  404.790716","Aluminum:   838.370<br />upr:  406.806732","Aluminum:   851.132<br />upr:  408.992112","Aluminum:   852.109<br />upr:  409.158542","Aluminum:   852.194<br />upr:  409.173016","Aluminum:   856.000<br />upr:  409.820148","Aluminum:   857.074<br />upr:  410.002425","Aluminum:   865.660<br />upr:  411.454351","Aluminum:   868.557<br />upr:  411.942151","Aluminum:   869.040<br />upr:  412.023377","Aluminum:   873.000<br />upr:  412.688234","Aluminum:   876.120<br />upr:  413.210693","Aluminum:   881.230<br />upr:  414.063803","Aluminum:   883.240<br />upr:  414.398498","Aluminum:   885.409<br />upr:  414.759117","Aluminum:   891.670<br />upr:  415.796894","Aluminum:   900.000<br />upr:  417.170357","Aluminum:   900.000<br />upr:  417.170357","Aluminum:   909.630<br />upr:  418.747994","Aluminum:   922.500<br />upr:  420.839710","Aluminum:   922.730<br />upr:  420.876919","Aluminum:   932.070<br />upr:  422.382927","Aluminum:   932.243<br />upr:  422.410730","Aluminum:   956.710<br />upr:  426.309838","Aluminum:   958.914<br />upr:  426.657903","Aluminum:   963.190<br />upr:  427.331717","Aluminum:   965.100<br />upr:  427.632074","Aluminum:   976.090<br />upr:  429.352901","Aluminum:  1000.000<br />upr:  433.054087","Aluminum:  1000.000<br />upr:  433.054087","Aluminum:  1003.810<br />upr:  433.638576","Aluminum:  1012.110<br />upr:  434.906942","Aluminum:  1018.690<br />upr:  435.907711","Aluminum:  1030.410<br />upr:  437.679966","Aluminum:  1033.457<br />upr:  438.138593","Aluminum:  1038.283<br />upr:  438.863210","Aluminum:  1045.362<br />upr:  439.922196","Aluminum:  1047.000<br />upr:  440.166575","Aluminum:  1050.806<br />upr:  440.733455","Aluminum:  1051.178<br />upr:  440.788791","Aluminum:  1055.110<br />upr:  441.372916","Aluminum:  1055.329<br />upr:  441.405409","Aluminum:  1055.500<br />upr:  441.430777","Aluminum:  1065.343<br />upr:  442.886553","Aluminum:  1074.580<br />upr:  444.244838","Aluminum:  1078.048<br />upr:  444.752859","Aluminum:  1089.320<br />upr:  446.396835","Aluminum:  1090.747<br />upr:  446.604174","Aluminum:  1091.386<br />upr:  446.696962","Aluminum:  1094.920<br />upr:  447.209498","Aluminum:  1103.000<br />upr:  448.377349","Aluminum:  1116.333<br />upr:  450.292453","Aluminum:  1123.390<br />upr:  451.300134","Aluminum:  1132.000<br />upr:  452.524061","Aluminum:  1154.750<br />upr:  455.729415","Aluminum:  1163.618<br />upr:  456.967844","Aluminum:  1172.002<br />upr:  458.133100","Aluminum:  1183.886<br />upr:  459.775640","Aluminum:  1202.900<br />upr:  462.381694","Aluminum:  1207.000<br />upr:  462.940154","Aluminum:  1224.440<br />upr:  465.302090","Aluminum:  1232.130<br />upr:  466.336678","Aluminum:  1242.758<br />upr:  467.759709","Aluminum:  1249.000<br />upr:  468.591826","Aluminum:  1251.510<br />upr:  468.925677","Aluminum:  1257.000<br />upr:  469.654393","Aluminum:  1264.420<br />upr:  470.636035","Aluminum:  1272.795<br />upr:  471.739572","Aluminum:  1282.310<br />upr:  472.987659","Aluminum:  1284.840<br />upr:  473.318515","Aluminum:  1300.000<br />upr:  475.292297","Aluminum:  1300.000<br />upr:  475.292297","Aluminum:  1314.420<br />upr:  477.156017","Aluminum:  1336.970<br />upr:  480.044274","Aluminum:  1337.000<br />upr:  480.048095","Aluminum:  1378.924<br />upr:  485.335412","Aluminum:  1380.000<br />upr:  485.469741","Aluminum:  1380.670<br />upr:  485.553351","Aluminum:  1384.000<br />upr:  485.968516","Aluminum:  1384.410<br />upr:  486.019588","Aluminum:  1390.946<br />upr:  486.832436","Aluminum:  1391.532<br />upr:  486.905193","Aluminum:  1393.442<br />upr:  487.142201","Aluminum:  1400.000<br />upr:  487.954379","Aluminum:  1405.000<br />upr:  488.571960","Aluminum:  1413.720<br />upr:  489.645642","Aluminum:  1420.100<br />upr:  490.428503","Aluminum:  1428.100<br />upr:  491.406951","Aluminum:  1438.131<br />upr:  492.628826","Aluminum:  1439.250<br />upr:  492.764790","Aluminum:  1444.554<br />upr:  493.408329","Aluminum:  1456.507<br />upr:  494.853036","Aluminum:  1476.780<br />upr:  497.285979","Aluminum:  1486.450<br />upr:  498.438890","Aluminum:  1489.760<br />upr:  498.832416","Aluminum:  1492.379<br />upr:  499.143390","Aluminum:  1497.000<br />upr:  499.691220","Aluminum:  1500.000<br />upr:  500.046294","Aluminum:  1505.000<br />upr:  500.637069","Aluminum:  1510.570<br />upr:  501.293705","Aluminum:  1514.000<br />upr:  501.697285","Aluminum:  1516.000<br />upr:  501.932337","Aluminum:  1528.931<br />upr:  503.447263","Aluminum:  1534.980<br />upr:  504.153097","Aluminum:  1537.150<br />upr:  504.405870","Aluminum:  1544.300<br />upr:  505.237113","Aluminum:  1563.510<br />upr:  507.458217","Aluminum:  1566.950<br />upr:  507.854099","Aluminum:  1582.670<br />upr:  509.656095","Aluminum:  1588.720<br />upr:  510.346537","Aluminum:  1600.000<br />upr:  511.629332","Aluminum:  1600.000<br />upr:  511.629332","Aluminum:  1603.200<br />upr:  511.992184","Aluminum:  1639.990<br />upr:  516.130727","Aluminum:  1646.000<br />upr:  516.801096","Aluminum:  1669.150<br />upr:  519.368666","Aluminum:  1695.280<br />upr:  522.239333","Aluminum:  1698.000<br />upr:  522.536512","Aluminum:  1700.000<br />upr:  522.754831","Aluminum:  1700.000<br />upr:  522.754831","Aluminum:  1716.850<br />upr:  524.587629","Aluminum:  1719.550<br />upr:  524.880233","Aluminum:  1731.580<br />upr:  526.180362","Aluminum:  1740.733<br />upr:  527.165670","Aluminum:  1764.700<br />upr:  529.729970","Aluminum:  1777.400<br />upr:  531.079693","Aluminum:  1796.740<br />upr:  533.123216","Aluminum:  1820.267<br />upr:  535.590134","Aluminum:  1821.360<br />upr:  535.704239","Aluminum:  1830.990<br />upr:  536.707679","Aluminum:  1833.140<br />upr:  536.931243","Aluminum:  1837.786<br />upr:  537.413773","Aluminum:  1845.800<br />upr:  538.244257","Aluminum:  1854.259<br />upr:  539.118340","Aluminum:  1871.680<br />upr:  540.910422","Aluminum:  1879.000<br />upr:  541.660217","Aluminum:  1884.050<br />upr:  542.176398","Aluminum:  1892.563<br />upr:  543.044531","Aluminum:  1896.303<br />upr:  543.425131","Aluminum:  1897.960<br />upr:  543.593601","Aluminum:  1903.281<br />upr:  544.133955","Aluminum:  1915.710<br />upr:  545.392355","Aluminum:  1918.000<br />upr:  545.623636","Aluminum:  1939.394<br />upr:  547.775806","Aluminum:  1951.550<br />upr:  548.991854","Aluminum:  1967.730<br />upr:  550.602904","Aluminum:  1982.243<br />upr:  552.040725","Aluminum:  1983.986<br />upr:  552.212950","Aluminum:  1987.046<br />upr:  552.515070","Aluminum:  1987.528<br />upr:  552.562632","Aluminum:  1989.000<br />upr:  552.707837","Aluminum:  1992.915<br />upr:  553.093692","Aluminum:  1995.007<br />upr:  553.299676","Aluminum:  1997.376<br />upr:  553.532767","Aluminum:  2019.460<br />upr:  555.697131","Aluminum:  2032.000<br />upr:  556.919346","Aluminum:  2038.750<br />upr:  557.575226","Aluminum:  2063.092<br />upr:  559.928922","Aluminum:  2073.900<br />upr:  560.968244","Aluminum:  2084.699<br />upr:  562.003222","Aluminum:  2126.000<br />upr:  565.929957","Aluminum:  2159.053<br />upr:  569.037248","Aluminum:  2203.280<br />upr:  573.147433","Aluminum:  2228.554<br />upr:  575.472419","Aluminum:  2252.090<br />upr:  577.622299","Aluminum:  2275.670<br />upr:  579.761734","Aluminum:  2277.000<br />upr:  579.881980","Aluminum:  2295.000<br />upr:  581.504936","Aluminum:  2300.000<br />upr:  581.954301","Aluminum:  2313.950<br />upr:  583.204711","Aluminum:  2318.710<br />upr:  583.630263","Aluminum:  2350.710<br />upr:  586.476612","Aluminum:  2361.100<br />upr:  587.395415","Aluminum:  2391.420<br />upr:  590.061856","Aluminum:  2442.500<br />upr:  594.505182","Aluminum:  2470.551<br />upr:  596.919849","Aluminum:  2471.350<br />upr:  596.988368","Aluminum:  2474.000<br />upr:  597.215522","Aluminum:  2483.576<br />upr:  598.035056","Aluminum:  2513.650<br />upr:  600.595693","Aluminum:  2529.418<br />upr:  601.930372","Aluminum:  2542.730<br />upr:  603.052997","Aluminum:  2568.130<br />upr:  605.184568","Aluminum:  2576.000<br />upr:  605.842262","Aluminum:  2576.414<br />upr:  605.876824","Aluminum:  2598.300<br />upr:  607.698866","Aluminum:  2602.336<br />upr:  608.033789","Aluminum:  2607.300<br />upr:  608.445261","Aluminum:  2612.809<br />upr:  608.901319","Aluminum:  2619.000<br />upr:  609.413098","Aluminum:  2627.657<br />upr:  610.127423","Aluminum:  2630.018<br />upr:  610.321976","Aluminum:  2630.450<br />upr:  610.357562","Aluminum:  2634.581<br />upr:  610.697661","Aluminum:  2647.810<br />upr:  611.784480","Aluminum:  2669.586<br />upr:  613.565879","Aluminum:  2672.000<br />upr:  613.762781","Aluminum:  2696.274<br />upr:  615.736389","Aluminum:  2698.230<br />upr:  615.894924","Aluminum:  2709.270<br />upr:  616.788334","Aluminum:  2737.840<br />upr:  619.089523","Aluminum:  2740.800<br />upr:  619.327052","Aluminum:  2743.000<br />upr:  619.503487","Aluminum:  2763.000<br />upr:  621.103276","Aluminum:  2790.000<br />upr:  623.251205","Aluminum:  2802.720<br />upr:  624.258479","Aluminum:  2807.090<br />upr:  624.603852","Aluminum:  2808.280<br />upr:  624.697841","Aluminum:  2808.490<br />upr:  624.714425","Aluminum:  2818.775<br />upr:  625.525652","Aluminum:  2847.260<br />upr:  627.762495","Aluminum:  2877.037<br />upr:  630.085438","Aluminum:  2886.310<br />upr:  630.805673","Aluminum:  2900.000<br />upr:  631.866258","Aluminum:  2913.650<br />upr:  632.920539","Aluminum:  2929.158<br />upr:  634.114471","Aluminum:  2931.600<br />upr:  634.302105","Aluminum:  2939.076<br />upr:  634.875907","Aluminum:  2944.010<br />upr:  635.254089","Aluminum:  2944.066<br />upr:  635.258379","Aluminum:  2954.000<br />upr:  636.018557","Aluminum:  2957.000<br />upr:  636.247801","Aluminum:  2958.811<br />upr:  636.386116","Aluminum:  2997.000<br />upr:  639.290183","Aluminum:  3008.560<br />upr:  640.164556","Aluminum:  3029.720<br />upr:  641.759462","Aluminum:  3056.245<br />upr:  643.748647","Aluminum:  3062.830<br />upr:  644.240751","Aluminum:  3076.000<br />upr:  645.222917","Aluminum:  3100.587<br />upr:  647.049295","Aluminum:  3102.000<br />upr:  647.153972","Aluminum:  3102.896<br />upr:  647.220333","Aluminum:  3105.600<br />upr:  647.420526","Aluminum:  3112.807<br />upr:  647.953555","Aluminum:  3152.230<br />upr:  650.855302","Aluminum:  3161.430<br />upr:  651.529104","Aluminum:  3162.000<br />upr:  651.570808","Aluminum:  3164.560<br />upr:  651.758055","Aluminum:  3180.716<br />upr:  652.937510","Aluminum:  3181.660<br />upr:  653.006306","Aluminum:  3210.491<br />upr:  655.101140","Aluminum:  3234.000<br />upr:  656.800332","Aluminum:  3234.290<br />upr:  656.821243","Aluminum:  3236.928<br />upr:  657.011406","Aluminum:  3273.700<br />upr:  659.651814","Aluminum:  3275.000<br />upr:  659.744810","Aluminum:  3276.100<br />upr:  659.823480","Aluminum:  3278.080<br />upr:  659.965044","Aluminum:  3281.956<br />upr:  660.242006","Aluminum:  3282.839<br />upr:  660.305072","Aluminum:  3284.770<br />upr:  660.442951","Aluminum:  3307.181<br />upr:  662.039349","Aluminum:  3313.481<br />upr:  662.486861","Aluminum:  3400.000<br />upr:  668.577933","Aluminum:  3403.350<br />upr:  668.811760","Aluminum:  3411.500<br />upr:  669.380005","Aluminum:  3418.530<br />upr:  669.869458","Aluminum:  3437.730<br />upr:  671.202934","Aluminum:  3451.720<br />upr:  672.171548","Aluminum:  3460.000<br />upr:  672.743632","Aluminum:  3466.580<br />upr:  673.197632","Aluminum:  3482.766<br />upr:  674.312058","Aluminum:  3530.330<br />upr:  677.567719","Aluminum:  3605.617<br />upr:  682.663710","Aluminum:  3624.320<br />upr:  683.919023","Aluminum:  3706.800<br />upr:  689.405726","Aluminum:  3739.930<br />upr:  691.587449","Aluminum:  3740.938<br />upr:  691.653634","Aluminum:  3746.920<br />upr:  692.046173","Aluminum:  3770.700<br />upr:  693.602638","Aluminum:  3797.610<br />upr:  695.356365","Aluminum:  3817.000<br />upr:  696.615058","Aluminum:  3862.314<br />upr:  699.540624","Aluminum:  3892.890<br />upr:  701.502206","Aluminum:  3919.187<br />upr:  703.181350","Aluminum:  3964.300<br />upr:  706.045134","Aluminum:  3990.310<br />upr:  707.686725","Aluminum:  4000.870<br />upr:  708.351241","Aluminum:  4010.643<br />upr:  708.965227","Aluminum:  4015.608<br />upr:  709.276783","Aluminum:  4017.990<br />upr:  709.426166","Aluminum:  4022.320<br />upr:  709.697569","Aluminum:  4100.130<br />upr:  714.542937","Aluminum:  4109.000<br />upr:  715.091516","Aluminum:  4213.850<br />upr:  721.519108","Aluminum:  4223.620<br />upr:  722.112767","Aluminum:  4262.000<br />upr:  724.436346","Aluminum:  4319.253<br />upr:  727.877612","Aluminum:  4347.880<br />upr:  729.587267","Aluminum:  4397.970<br />upr:  732.561374","Aluminum:  4398.600<br />upr:  732.598641","Aluminum:  4404.900<br />upr:  732.971124","Aluminum:  4413.802<br />upr:  733.496864","Aluminum:  4431.470<br />upr:  734.538292","Aluminum:  4466.000<br />upr:  736.565947","Aluminum:  4506.180<br />upr:  738.912710","Aluminum:  4519.660<br />upr:  739.697006","Aluminum:  4534.800<br />upr:  740.576091","Aluminum:  4578.000<br />upr:  743.074101","Aluminum:  4679.724<br />upr:  748.896859","Aluminum:  4721.000<br />upr:  751.236280","Aluminum:  4775.320<br />upr:  754.295016","Aluminum:  4829.056<br />upr:  757.298902","Aluminum:  4852.940<br />upr:  758.627128","Aluminum:  4924.490<br />upr:  762.581116","Aluminum:  4940.032<br />upr:  763.435098","Aluminum:  4982.140<br />upr:  765.740136","Aluminum:  5000.000<br />upr:  766.714023","Aluminum:  5023.810<br />upr:  768.008881","Aluminum:  5060.340<br />upr:  769.987828","Aluminum:  5063.000<br />upr:  770.131569","Aluminum:  5074.345<br />upr:  770.744085","Aluminum:  5080.363<br />upr:  771.068638","Aluminum:  5128.640<br />upr:  773.663323","Aluminum:  5149.080<br />upr:  774.757147","Aluminum:  5208.540<br />upr:  777.923275","Aluminum:  5212.570<br />upr:  778.137021","Aluminum:  5263.700<br />upr:  780.839693","Aluminum:  5308.000<br />upr:  783.167704","Aluminum:  5435.273<br />upr:  789.787201","Aluminum:  5553.000<br />upr:  795.821924","Aluminum:  5557.760<br />upr:  796.064183","Aluminum:  5616.320<br />upr:  799.033705","Aluminum:  5632.510<br />upr:  799.851165","Aluminum:  5683.264<br />upr:  802.404052","Aluminum:  5691.840<br />upr:  802.833966","Aluminum:  5839.321<br />upr:  810.162817","Aluminum:  5864.040<br />upr:  811.379489","Aluminum:  5944.163<br />upr:  815.300600","Aluminum:  5978.370<br />upr:  816.964280","Aluminum:  6101.770<br />upr:  822.915486","Aluminum:  6132.060<br />upr:  824.364413","Aluminum:  6143.000<br />upr:  824.886596","Aluminum:  6171.030<br />upr:  826.221787","Aluminum:  6217.790<br />upr:  828.440504","Aluminum:  6226.436<br />upr:  828.849571","Aluminum:  6376.780<br />upr:  835.905040","Aluminum:  6399.000<br />upr:  836.938683","Aluminum:  6507.398<br />upr:  841.948348","Aluminum:  6513.000<br />upr:  842.205783","Aluminum:  6540.170<br />upr:  843.452334","Aluminum:  6560.000<br />upr:  844.360025","Aluminum:  6576.330<br />upr:  845.106183","Aluminum:  6684.020<br />upr:  849.997181","Aluminum:  6687.320<br />upr:  850.146255","Aluminum:  6825.000<br />upr:  856.324037","Aluminum:  6893.810<br />upr:  859.381539","Aluminum:  6905.380<br />upr:  859.893708","Aluminum:  6942.000<br />upr:  861.511132","Aluminum:  7025.862<br />upr:  865.194548","Aluminum:  7109.340<br />upr:  868.833092","Aluminum:  7126.600<br />upr:  869.581965","Aluminum:  7196.000<br />upr:  872.581347","Aluminum:  7301.650<br />upr:  877.111861","Aluminum:  7563.000<br />upr:  888.140714","Aluminum:  7772.280<br />upr:  896.796592","Aluminum:  7779.340<br />upr:  897.085965","Aluminum:  7806.600<br />upr:  898.201703","Aluminum:  8057.890<br />upr:  908.370694","Aluminum:  8101.529<br />upr:  910.115748","Aluminum:  8110.616<br />upr:  910.478361","Aluminum:  8156.740<br />upr:  912.314899","Aluminum:  8172.880<br />upr:  912.955972","Aluminum:  8179.610<br />upr:  913.223044","Aluminum:  8318.290<br />upr:  918.695182","Aluminum:  8356.760<br />upr:  920.202740","Aluminum:  8361.000<br />upr:  920.368624","Aluminum:  8600.000<br />upr:  929.632892","Aluminum:  8737.050<br />upr:  934.870716","Aluminum:  9034.470<br />upr:  946.058367","Aluminum:  9035.970<br />upr:  946.114185","Aluminum:  9388.160<br />upr:  959.058226","Aluminum:  9542.662<br />upr:  964.638036","Aluminum:  9559.510<br />upr:  965.242973","Aluminum:  9700.000<br />upr:  970.260820","Aluminum:  9896.680<br />upr:  977.207608","Aluminum: 10005.812<br />upr:  981.023901","Aluminum: 10050.000<br />upr:  982.561512","Aluminum: 10233.858<br />upr:  988.912920","Aluminum: 10343.200<br />upr:  992.655390","Aluminum: 10379.837<br />upr:  993.903674","Aluminum: 10711.560<br />upr: 1005.079048","Aluminum: 10869.710<br />upr: 1010.328600","Aluminum: 10891.960<br />upr: 1011.063202","Aluminum: 10908.460<br />upr: 1011.607339","Aluminum: 10990.470<br />upr: 1014.304036","Aluminum: 10990.530<br />upr: 1014.306005","Aluminum: 11116.490<br />upr: 1018.422766","Aluminum: 11359.000<br />upr: 1026.264971","Aluminum: 11526.000<br />upr: 1031.602900","Aluminum: 11711.000<br />upr: 1037.458372","Aluminum: 11803.000<br />upr: 1040.348133","Aluminum: 11855.800<br />upr: 1042.000060","Aluminum: 11985.000<br />upr: 1046.022406","Aluminum: 12055.930<br />upr: 1048.218791","Aluminum: 12219.017<br />upr: 1053.237509","Aluminum: 12247.000<br />upr: 1054.094296","Aluminum: 12414.483<br />upr: 1059.196155","Aluminum: 12430.700<br />upr: 1059.687798","Aluminum: 12560.000<br />upr: 1063.593039","Aluminum: 12600.000<br />upr: 1064.795914","Aluminum: 12641.000<br />upr: 1066.026312","Aluminum: 12697.000<br />upr: 1067.702712","Aluminum: 12699.930<br />upr: 1067.790293","Aluminum: 12800.710<br />upr: 1070.794823","Aluminum: 12837.925<br />upr: 1071.900455","Aluminum: 12876.191<br />upr: 1073.035162","Aluminum: 12911.000<br />upr: 1074.065475","Aluminum: 13313.000<br />upr: 1085.836829","Aluminum: 13535.000<br />upr: 1092.239591","Aluminum: 13578.400<br />upr: 1093.483388","Aluminum: 13714.000<br />upr: 1097.353129","Aluminum: 13720.174<br />upr: 1097.528735","Aluminum: 13775.000<br />upr: 1099.085913","Aluminum: 13871.300<br />upr: 1101.811415","Aluminum: 13983.000<br />upr: 1104.957558","Aluminum: 14157.000<br />upr: 1109.826382","Aluminum: 14165.940<br />upr: 1110.075496","Aluminum: 14369.230<br />upr: 1115.713092","Aluminum: 14376.210<br />upr: 1115.905745","Aluminum: 14380.579<br />upr: 1116.026303","Aluminum: 14638.271<br />upr: 1123.095710","Aluminum: 14744.157<br />upr: 1125.977321","Aluminum: 14960.965<br />upr: 1131.836305","Aluminum: 15050.070<br />upr: 1134.228420","Aluminum: 15400.080<br />upr: 1143.537567","Aluminum: 15580.000<br />upr: 1148.269940","Aluminum: 15667.844<br />upr: 1150.567699","Aluminum: 15747.000<br />upr: 1152.631112","Aluminum: 15855.930<br />upr: 1155.459780","Aluminum: 15982.549<br />upr: 1158.732119","Aluminum: 16187.748<br />upr: 1164.000033","Aluminum: 16285.040<br />upr: 1166.482723","Aluminum: 16374.220<br />upr: 1168.750040","Aluminum: 16378.832<br />upr: 1168.867079","Aluminum: 16554.910<br />upr: 1173.319667","Aluminum: 16744.907<br />upr: 1178.090178","Aluminum: 16986.000<br />upr: 1184.093743","Aluminum: 17250.000<br />upr: 1190.605155","Aluminum: 17376.000<br />upr: 1193.690279","Aluminum: 17668.669<br />upr: 1200.801171","Aluminum: 18190.640<br />upr: 1213.297496","Aluminum: 18253.450<br />upr: 1214.785581","Aluminum: 18567.346<br />upr: 1222.173401","Aluminum: 18721.000<br />upr: 1225.760503","Aluminum: 18771.346<br />upr: 1226.931724","Aluminum: 18915.000<br />upr: 1230.262537","Aluminum: 18941.560<br />upr: 1230.876582","Aluminum: 18948.944<br />upr: 1231.047195","Aluminum: 19043.000<br />upr: 1233.216703","Aluminum: 19174.000<br />upr: 1236.226907","Aluminum: 19482.960<br />upr: 1243.274357","Aluminum: 19494.000<br />upr: 1243.524846","Aluminum: 19555.370<br />upr: 1244.915627","Aluminum: 19741.000<br />upr: 1249.105395","Aluminum: 19770.000<br />upr: 1249.757648","Aluminum: 19778.615<br />upr: 1249.951293","Aluminum: 19814.984<br />upr: 1250.768187","Aluminum: 20147.874<br />upr: 1258.200878","Aluminum: 20447.460<br />upr: 1264.822699","Aluminum: 21255.484<br />upr: 1282.376945","Aluminum: 21460.000<br />upr: 1286.751704","Aluminum: 22988.650<br />upr: 1318.631036","Aluminum: 23301.643<br />upr: 1324.988792","Aluminum: 23502.000<br />upr: 1329.029801","Aluminum: 23767.000<br />upr: 1334.340693","Aluminum: 23920.000<br />upr: 1337.389649","Aluminum: 23973.990<br />upr: 1338.462556","Aluminum: 24381.260<br />upr: 1346.506300","Aluminum: 24556.268<br />upr: 1349.936224","Aluminum: 24654.550<br />upr: 1351.855528","Aluminum: 24669.671<br />upr: 1352.150381","Aluminum: 25231.350<br />upr: 1363.021530","Aluminum: 25590.000<br />upr: 1369.881869","Aluminum: 25981.900<br />upr: 1377.307854","Aluminum: 26372.522<br />upr: 1384.638249","Aluminum: 26929.000<br />upr: 1394.961419","Aluminum: 27052.400<br />upr: 1397.231968","Aluminum: 27375.200<br />upr: 1403.140115","Aluminum: 27477.140<br />upr: 1404.996585","Aluminum: 27642.276<br />upr: 1407.994561","Aluminum: 27663.273<br />upr: 1408.374927","Aluminum: 27760.700<br />upr: 1410.137413","Aluminum: 27978.000<br />upr: 1414.054154","Aluminum: 31104.223<br />upr: 1468.356833","Aluminum: 31230.000<br />upr: 1470.466518","Aluminum: 31722.000<br />upr: 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15.400<br />lwr: 0.017212305","Aluminum:    15.650<br />lwr: 0.017311179","Aluminum:    18.000<br />lwr: 0.018194352","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    22.325<br />lwr: 0.019642347","Aluminum:    32.600<br />lwr: 0.022472452","Aluminum:    42.500<br />lwr: 0.024693616","Aluminum:    42.500<br />lwr: 0.024693616","Aluminum:    42.600<br />lwr: 0.024714248","Aluminum:    46.875<br />lwr: 0.025568557","Aluminum:    46.875<br />lwr: 0.025568557","Aluminum:    47.000<br />lwr: 0.025592765","Aluminum:    47.400<br />lwr: 0.025669951","Aluminum:    53.000<br />lwr: 0.026708992","Aluminum:    74.400<br />lwr: 0.030129058","Aluminum:    97.810<br />lwr: 0.033203361","Aluminum:   117.170<br />lwr: 0.035402394","Aluminum:   117.842<br />lwr: 0.035474353","Aluminum:   125.450<br />lwr: 0.036271148","Aluminum:   131.900<br />lwr: 0.036922555","Aluminum:   142.570<br />lwr: 0.037956410","Aluminum:   147.600<br />lwr: 0.038426485","Aluminum:   155.500<br />lwr: 0.039144322","Aluminum:   159.380<br />lwr: 0.039488271","Aluminum:   185.090<br />lwr: 0.041640986","Aluminum:   187.400<br />lwr: 0.041824695","Aluminum:   189.500<br />lwr: 0.041990438","Aluminum:   191.200<br />lwr: 0.042123745","Aluminum:   193.720<br />lwr: 0.042319950","Aluminum:   210.447<br />lwr: 0.043582266","Aluminum:   217.180<br />lwr: 0.044072062","Aluminum:   221.700<br />lwr: 0.044395393","Aluminum:   229.000<br />lwr: 0.044908711","Aluminum:   236.490<br />lwr: 0.045424517","Aluminum:   244.300<br />lwr: 0.045951240","Aluminum:   247.300<br />lwr: 0.046150673","Aluminum:   247.740<br />lwr: 0.046179791","Aluminum:   263.211<br />lwr: 0.047183085","Aluminum:   284.000<br />lwr: 0.048472956","Aluminum:   285.630<br />lwr: 0.048571476","Aluminum:   287.200<br />lwr: 0.048666026","Aluminum:   291.780<br />lwr: 0.048939954","Aluminum:   295.270<br />lwr: 0.049146830","Aluminum:   310.900<br />lwr: 0.050054439","Aluminum:   317.090<br />lwr: 0.050405727","Aluminum:   344.600<br />lwr: 0.051915528","Aluminum:   350.290<br />lwr: 0.052217993","Aluminum:   354.368<br />lwr: 0.052432820","Aluminum:   364.300<br />lwr: 0.052949435","Aluminum:   367.700<br />lwr: 0.053124193","Aluminum:   368.000<br />lwr: 0.053139563","Aluminum:   384.500<br />lwr: 0.053972719","Aluminum:   385.400<br />lwr: 0.054017494","Aluminum:   392.440<br />lwr: 0.054365422","Aluminum:   400.000<br />lwr: 0.054734587","Aluminum:   402.290<br />lwr: 0.054845520","Aluminum:   415.000<br />lwr: 0.055453922","Aluminum:   435.400<br />lwr: 0.056405742","Aluminum:   438.840<br />lwr: 0.056563387","Aluminum:   458.000<br />lwr: 0.057427138","Aluminum:   466.820<br />lwr: 0.057816910","Aluminum:   474.810<br />lwr: 0.058165914","Aluminum:   490.970<br />lwr: 0.058860354","Aluminum:   491.110<br />lwr: 0.058866305","Aluminum:   506.170<br />lwr: 0.059500183","Aluminum:   507.730<br />lwr: 0.059565143","Aluminum:   509.000<br />lwr: 0.059617933","Aluminum:   516.000<br />lwr: 0.059907380","Aluminum:   518.945<br />lwr: 0.060028396","Aluminum:   537.306<br />lwr: 0.060773055","Aluminum:   549.690<br />lwr: 0.061266064","Aluminum:   583.780<br />lwr: 0.062587145","Aluminum:   585.800<br />lwr: 0.062663843","Aluminum:   588.850<br />lwr: 0.062779325","Aluminum:   593.576<br />lwr: 0.062957505","Aluminum:   599.820<br />lwr: 0.063191516","Aluminum:   600.000<br />lwr: 0.063198239","Aluminum:   602.242<br />lwr: 0.063281863","Aluminum:   602.688<br />lwr: 0.063298475","Aluminum:   607.580<br />lwr: 0.063480159","Aluminum:   608.200<br />lwr: 0.063503118","Aluminum:   622.248<br />lwr: 0.064019312","Aluminum:   630.000<br />lwr: 0.064300940","Aluminum:   633.020<br />lwr: 0.064410049","Aluminum:   635.748<br />lwr: 0.064508320","Aluminum:   636.290<br />lwr: 0.064527812","Aluminum:   639.840<br />lwr: 0.064655216","Aluminum:   654.870<br />lwr: 0.065189617","Aluminum:   678.540<br />lwr: 0.066015375","Aluminum:   683.683<br />lwr: 0.066192323","Aluminum:   689.070<br />lwr: 0.066376746","Aluminum:   690.000<br />lwr: 0.066408490","Aluminum:   691.160<br />lwr: 0.066448046","Aluminum:   692.300<br />lwr: 0.066486878","Aluminum:   700.000<br />lwr: 0.066748089","Aluminum:   700.090<br />lwr: 0.066751131","Aluminum:   704.500<br />lwr: 0.066899885","Aluminum:   708.500<br />lwr: 0.067034290","Aluminum:   717.431<br />lwr: 0.067332623","Aluminum:   724.300<br />lwr: 0.067560447","Aluminum:   726.200<br />lwr: 0.067623217","Aluminum:   729.903<br />lwr: 0.067745249","Aluminum:   742.770<br />lwr: 0.068166195","Aluminum:   756.970<br />lwr: 0.068625313","Aluminum:   757.450<br />lwr: 0.068640735","Aluminum:   757.860<br />lwr: 0.068653903","Aluminum:   759.500<br />lwr: 0.068706528","Aluminum:   768.500<br />lwr: 0.068994026","Aluminum:   773.110<br />lwr: 0.069140446","Aluminum:   775.800<br />lwr: 0.069225624","Aluminum:   781.000<br />lwr: 0.069389740","Aluminum:   782.951<br />lwr: 0.069451133","Aluminum:   786.460<br />lwr: 0.069561303","Aluminum:   791.690<br />lwr: 0.069724919","Aluminum:   795.000<br />lwr: 0.069828109","Aluminum:   796.650<br />lwr: 0.069879444","Aluminum:   811.000<br />lwr: 0.070323034","Aluminum:   816.000<br />lwr: 0.070476402","Aluminum:   820.028<br />lwr: 0.070599514","Aluminum:   826.707<br />lwr: 0.070802793","Aluminum:   838.370<br />lwr: 0.071155232","Aluminum:   851.132<br />lwr: 0.071537268","Aluminum:   852.109<br />lwr: 0.071566362","Aluminum:   852.194<br />lwr: 0.071568892","Aluminum:   856.000<br />lwr: 0.071682018","Aluminum:   857.074<br />lwr: 0.071713881","Aluminum:   865.660<br />lwr: 0.071967690","Aluminum:   868.557<br />lwr: 0.072052960","Aluminum:   869.040<br />lwr: 0.072067158","Aluminum:   873.000<br />lwr: 0.072183378","Aluminum:   876.120<br />lwr: 0.072274705","Aluminum:   881.230<br />lwr: 0.072423829","Aluminum:   883.240<br />lwr: 0.072482334","Aluminum:   885.409<br />lwr: 0.072545369","Aluminum:   891.670<br />lwr: 0.072726770","Aluminum:   900.000<br />lwr: 0.072966843","Aluminum:   900.000<br />lwr: 0.072966843","Aluminum:   909.630<br />lwr: 0.073242599","Aluminum:   922.500<br />lwr: 0.073608202","Aluminum:   922.730<br />lwr: 0.073614705","Aluminum:   932.070<br />lwr: 0.073877928","Aluminum:   932.243<br />lwr: 0.073882787","Aluminum:   956.710<br />lwr: 0.074564255","Aluminum:   958.914<br />lwr: 0.074625086","Aluminum:   963.190<br />lwr: 0.074742848","Aluminum:   965.100<br />lwr: 0.074795341","Aluminum:   976.090<br />lwr: 0.075096082","Aluminum:  1000.000<br />lwr: 0.075742897","Aluminum:  1000.000<br />lwr: 0.075742897","Aluminum:  1003.810<br />lwr: 0.075845039","Aluminum:  1012.110<br />lwr: 0.076066688","Aluminum:  1018.690<br />lwr: 0.076241572","Aluminum:  1030.410<br />lwr: 0.076551266","Aluminum:  1033.457<br />lwr: 0.076631408","Aluminum:  1038.283<br />lwr: 0.076758029","Aluminum:  1045.362<br />lwr: 0.076943075","Aluminum:  1047.000<br />lwr: 0.076985778","Aluminum:  1050.806<br />lwr: 0.077084832","Aluminum:  1051.178<br />lwr: 0.077094502","Aluminum:  1055.110<br />lwr: 0.077196569","Aluminum:  1055.329<br />lwr: 0.077202247","Aluminum:  1055.500<br />lwr: 0.077206679","Aluminum:  1065.343<br />lwr: 0.077461052","Aluminum:  1074.580<br />lwr: 0.077698384","Aluminum:  1078.048<br />lwr: 0.077787150","Aluminum:  1089.320<br />lwr: 0.078074393","Aluminum:  1090.747<br />lwr: 0.078110620","Aluminum:  1091.386<br />lwr: 0.078126832","Aluminum:  1094.920<br />lwr: 0.078216384","Aluminum:  1103.000<br />lwr: 0.078420430","Aluminum:  1116.333<br />lwr: 0.078755030","Aluminum:  1123.390<br />lwr: 0.078931084","Aluminum:  1132.000<br />lwr: 0.079144917","Aluminum:  1154.750<br />lwr: 0.079704908","Aluminum:  1163.618<br />lwr: 0.079921261","Aluminum:  1172.002<br />lwr: 0.080124827","Aluminum:  1183.886<br />lwr: 0.080411768","Aluminum:  1202.900<br />lwr: 0.080867016","Aluminum:  1207.000<br />lwr: 0.080964570","Aluminum:  1224.440<br />lwr: 0.081377156","Aluminum:  1232.130<br />lwr: 0.081557876","Aluminum:  1242.758<br />lwr: 0.081806443","Aluminum:  1249.000<br />lwr: 0.081951790","Aluminum:  1251.510<br />lwr: 0.082010104","Aluminum:  1257.000<br />lwr: 0.082137388","Aluminum:  1264.420<br />lwr: 0.082308849","Aluminum:  1272.795<br />lwr: 0.082501598","Aluminum:  1282.310<br />lwr: 0.082719592","Aluminum:  1284.840<br />lwr: 0.082777379","Aluminum:  1300.000<br />lwr: 0.083122115","Aluminum:  1300.000<br />lwr: 0.083122115","Aluminum:  1314.420<br />lwr: 0.083447620","Aluminum:  1336.970<br />lwr: 0.083952047","Aluminum:  1337.000<br />lwr: 0.083952714","Aluminum:  1378.924<br />lwr: 0.084876081","Aluminum:  1380.000<br />lwr: 0.084899539","Aluminum:  1380.670<br />lwr: 0.084914140","Aluminum:  1384.000<br />lwr: 0.084986640","Aluminum:  1384.410<br />lwr: 0.084995559","Aluminum:  1390.946<br />lwr: 0.085137506","Aluminum:  1391.532<br />lwr: 0.085150212","Aluminum:  1393.442<br />lwr: 0.085191600","Aluminum:  1400.000<br />lwr: 0.085333428","Aluminum:  1405.000<br />lwr: 0.085441273","Aluminum:  1413.720<br />lwr: 0.085628763","Aluminum:  1420.100<br />lwr: 0.085765467","Aluminum:  1428.100<br />lwr: 0.085936323","Aluminum:  1438.131<br />lwr: 0.086149682","Aluminum:  1439.250<br />lwr: 0.086173423","Aluminum:  1444.554<br />lwr: 0.086285794","Aluminum:  1456.507<br />lwr: 0.086538057","Aluminum:  1476.780<br />lwr: 0.086962866","Aluminum:  1486.450<br />lwr: 0.087164168","Aluminum:  1489.760<br />lwr: 0.087232878","Aluminum:  1492.379<br />lwr: 0.087287174","Aluminum:  1497.000<br />lwr: 0.087382825","Aluminum:  1500.000<br />lwr: 0.087444820","Aluminum:  1505.000<br />lwr: 0.087547968","Aluminum:  1510.570<br />lwr: 0.087662614","Aluminum:  1514.000<br />lwr: 0.087733076","Aluminum:  1516.000<br />lwr: 0.087774115","Aluminum:  1528.931<br />lwr: 0.088038609","Aluminum:  1534.980<br />lwr: 0.088161840","Aluminum:  1537.150<br />lwr: 0.088205971","Aluminum:  1544.300<br />lwr: 0.088351095","Aluminum:  1563.510<br />lwr: 0.088738863","Aluminum:  1566.950<br />lwr: 0.088807976","Aluminum:  1582.670<br />lwr: 0.089122565","Aluminum:  1588.720<br />lwr: 0.089243099","Aluminum:  1600.000<br />lwr: 0.089467040","Aluminum:  1600.000<br />lwr: 0.089467040","Aluminum:  1603.200<br />lwr: 0.089530383","Aluminum:  1639.990<br />lwr: 0.090252831","Aluminum:  1646.000<br />lwr: 0.090369851","Aluminum:  1669.150<br />lwr: 0.090818037","Aluminum:  1695.280<br />lwr: 0.091319113","Aluminum:  1698.000<br />lwr: 0.091370985","Aluminum:  1700.000<br />lwr: 0.091409092","Aluminum:  1700.000<br />lwr: 0.091409092","Aluminum:  1716.850<br />lwr: 0.091728995","Aluminum:  1719.550<br />lwr: 0.091780067","Aluminum:  1731.580<br />lwr: 0.092006991","Aluminum:  1740.733<br />lwr: 0.092178963","Aluminum:  1764.700<br />lwr: 0.092626518","Aluminum:  1777.400<br />lwr: 0.092862084","Aluminum:  1796.740<br />lwr: 0.093218729","Aluminum:  1820.267<br />lwr: 0.093649254","Aluminum:  1821.360<br />lwr: 0.093669168","Aluminum:  1830.990<br />lwr: 0.093844283","Aluminum:  1833.140<br />lwr: 0.093883298","Aluminum:  1837.786<br />lwr: 0.093967506","Aluminum:  1845.800<br />lwr: 0.094112435","Aluminum:  1854.259<br />lwr: 0.094264971","Aluminum:  1871.680<br />lwr: 0.094577702","Aluminum:  1879.000<br />lwr: 0.094708544","Aluminum:  1884.050<br />lwr: 0.094798619","Aluminum:  1892.563<br />lwr: 0.094950109","Aluminum:  1896.303<br />lwr: 0.095016524","Aluminum:  1897.960<br />lwr: 0.095045921","Aluminum:  1903.281<br />lwr: 0.095140212","Aluminum:  1915.710<br />lwr: 0.095359798","Aluminum:  1918.000<br />lwr: 0.095400155","Aluminum:  1939.394<br />lwr: 0.095775691","Aluminum:  1951.550<br />lwr: 0.095987877","Aluminum:  1967.730<br />lwr: 0.096268981","Aluminum:  1982.243<br />lwr: 0.096519854","Aluminum:  1983.986<br />lwr: 0.096549903","Aluminum:  1987.046<br />lwr: 0.096602617","Aluminum:  1987.528<br />lwr: 0.096610916","Aluminum:  1989.000<br />lwr: 0.096636251","Aluminum:  1992.915<br />lwr: 0.096703574","Aluminum:  1995.007<br />lwr: 0.096739513","Aluminum:  1997.376<br />lwr: 0.096780182","Aluminum:  2019.460<br />lwr: 0.097157808","Aluminum:  2032.000<br />lwr: 0.097371048","Aluminum:  2038.750<br />lwr: 0.097485478","Aluminum:  2063.092<br />lwr: 0.097896115","Aluminum:  2073.900<br />lwr: 0.098077436","Aluminum:  2084.699<br />lwr: 0.098257997","Aluminum:  2126.000<br />lwr: 0.098943028","Aluminum:  2159.053<br />lwr: 0.099485080","Aluminum:  2203.280<br />lwr: 0.100202050","Aluminum:  2228.554<br />lwr: 0.100607597","Aluminum:  2252.090<br />lwr: 0.100982591","Aluminum:  2275.670<br />lwr: 0.101355752","Aluminum:  2277.000<br />lwr: 0.101376725","Aluminum:  2295.000<br />lwr: 0.101659795","Aluminum:  2300.000<br />lwr: 0.101738170","Aluminum:  2313.950<br />lwr: 0.101956257","Aluminum:  2318.710<br />lwr: 0.102030477","Aluminum:  2350.710<br />lwr: 0.102526899","Aluminum:  2361.100<br />lwr: 0.102687140","Aluminum:  2391.420<br />lwr: 0.103152163","Aluminum:  2442.500<br />lwr: 0.103927037","Aluminum:  2470.551<br />lwr: 0.104348114","Aluminum:  2471.350<br />lwr: 0.104360063","Aluminum:  2474.000<br />lwr: 0.104399674","Aluminum:  2483.576<br />lwr: 0.104542583","Aluminum:  2513.650<br />lwr: 0.104989095","Aluminum:  2529.418<br />lwr: 0.105221824","Aluminum:  2542.730<br />lwr: 0.105417574","Aluminum:  2568.130<br />lwr: 0.105789245","Aluminum:  2576.000<br />lwr: 0.105903922","Aluminum:  2576.414<br />lwr: 0.105909948","Aluminum:  2598.300<br />lwr: 0.106227637","Aluminum:  2602.336<br />lwr: 0.106286033","Aluminum:  2607.300<br />lwr: 0.106357776","Aluminum:  2612.809<br />lwr: 0.106437292","Aluminum:  2619.000<br />lwr: 0.106526523","Aluminum:  2627.657<br />lwr: 0.106651067","Aluminum:  2630.018<br />lwr: 0.106684987","Aluminum:  2630.450<br />lwr: 0.106691192","Aluminum:  2634.581<br />lwr: 0.106750488","Aluminum:  2647.810<br />lwr: 0.106939974","Aluminum:  2669.586<br />lwr: 0.107250555","Aluminum:  2672.000<br />lwr: 0.107284883","Aluminum:  2696.274<br />lwr: 0.107628966","Aluminum:  2698.230<br />lwr: 0.107656604","Aluminum:  2709.270<br />lwr: 0.107812360","Aluminum:  2737.840<br />lwr: 0.108213537","Aluminum:  2740.800<br />lwr: 0.108254946","Aluminum:  2743.000<br />lwr: 0.108285704","Aluminum:  2763.000<br />lwr: 0.108564595","Aluminum:  2790.000<br />lwr: 0.108939034","Aluminum:  2802.720<br />lwr: 0.109114624","Aluminum:  2807.090<br />lwr: 0.109174830","Aluminum:  2808.280<br />lwr: 0.109191214","Aluminum:  2808.490<br />lwr: 0.109194105","Aluminum:  2818.775<br />lwr: 0.109335518","Aluminum:  2847.260<br />lwr: 0.109725435","Aluminum:  2877.037<br />lwr: 0.110130350","Aluminum:  2886.310<br />lwr: 0.110255893","Aluminum:  2900.000<br />lwr: 0.110440759","Aluminum:  2913.650<br />lwr: 0.110624524","Aluminum:  2929.158<br />lwr: 0.110832628","Aluminum:  2931.600<br />lwr: 0.110865333","Aluminum:  2939.076<br />lwr: 0.110965346","Aluminum:  2944.010<br />lwr: 0.111031262","Aluminum:  2944.066<br />lwr: 0.111032010","Aluminum:  2954.000<br />lwr: 0.111164506","Aluminum:  2957.000<br />lwr: 0.111204463","Aluminum:  2958.811<br />lwr: 0.111228570","Aluminum:  2997.000<br />lwr: 0.111734726","Aluminum:  3008.560<br />lwr: 0.111887119","Aluminum:  3029.720<br />lwr: 0.112165088","Aluminum:  3056.245<br />lwr: 0.112511766","Aluminum:  3062.830<br />lwr: 0.112597529","Aluminum:  3076.000<br />lwr: 0.112768699","Aluminum:  3100.587<br />lwr: 0.113086990","Aluminum:  3102.000<br />lwr: 0.113105232","Aluminum:  3102.896<br />lwr: 0.113116797","Aluminum:  3105.600<br />lwr: 0.113151685","Aluminum:  3112.807<br />lwr: 0.113244577","Aluminum:  3152.230<br />lwr: 0.113750256","Aluminum:  3161.430<br />lwr: 0.113867676","Aluminum:  3162.000<br />lwr: 0.113874943","Aluminum:  3164.560<br />lwr: 0.113907573","Aluminum:  3180.716<br />lwr: 0.114113107","Aluminum:  3181.660<br />lwr: 0.114125095","Aluminum:  3210.491<br />lwr: 0.114490136","Aluminum:  3234.000<br />lwr: 0.114786226","Aluminum:  3234.290<br />lwr: 0.114789870","Aluminum:  3236.928<br />lwr: 0.114823006","Aluminum:  3273.700<br />lwr: 0.115283094","Aluminum:  3275.000<br />lwr: 0.115299298","Aluminum:  3276.100<br />lwr: 0.115313006","Aluminum:  3278.080<br />lwr: 0.115337672","Aluminum:  3281.956<br />lwr: 0.115385932","Aluminum:  3282.839<br />lwr: 0.115396921","Aluminum:  3284.770<br />lwr: 0.115420945","Aluminum:  3307.181<br />lwr: 0.115699106","Aluminum:  3313.481<br />lwr: 0.115777080","Aluminum:  3400.000<br />lwr: 0.116838349","Aluminum:  3403.350<br />lwr: 0.116879087","Aluminum:  3411.500<br />lwr: 0.116978090","Aluminum:  3418.530<br />lwr: 0.117063365","Aluminum:  3437.730<br />lwr: 0.117295687","Aluminum:  3451.720<br />lwr: 0.117464440","Aluminum:  3460.000<br />lwr: 0.117564108","Aluminum:  3466.580<br />lwr: 0.117643203","Aluminum:  3482.766<br />lwr: 0.117837354","Aluminum:  3530.330<br />lwr: 0.118404528","Aluminum:  3605.617<br />lwr: 0.119292264","Aluminum:  3624.320<br />lwr: 0.119510935","Aluminum:  3706.800<br />lwr: 0.120466660","Aluminum:  3739.930<br />lwr: 0.120846676","Aluminum:  3740.938<br />lwr: 0.120858204","Aluminum:  3746.920<br />lwr: 0.120926576","Aluminum:  3770.700<br />lwr: 0.121197675","Aluminum:  3797.610<br />lwr: 0.121503128","Aluminum:  3817.000<br />lwr: 0.121722354","Aluminum:  3862.314<br />lwr: 0.122231888","Aluminum:  3892.890<br />lwr: 0.122573518","Aluminum:  3919.187<br />lwr: 0.122865953","Aluminum:  3964.300<br />lwr: 0.123364687","Aluminum:  3990.310<br />lwr: 0.123650566","Aluminum:  4000.870<br />lwr: 0.123766289","Aluminum:  4010.643<br />lwr: 0.123873211","Aluminum:  4015.608<br />lwr: 0.123927466","Aluminum:  4017.990<br />lwr: 0.123953480","Aluminum:  4022.320<br />lwr: 0.124000743","Aluminum:  4100.130<br />lwr: 0.124844500","Aluminum:  4109.000<br />lwr: 0.124940025","Aluminum:  4213.850<br />lwr: 0.126059224","Aluminum:  4223.620<br />lwr: 0.126162591","Aluminum:  4262.000<br />lwr: 0.126567159","Aluminum:  4319.253<br />lwr: 0.127166312","Aluminum:  4347.880<br />lwr: 0.127463968","Aluminum:  4397.970<br />lwr: 0.127981755","Aluminum:  4398.600<br />lwr: 0.127988243","Aluminum:  4404.900<br />lwr: 0.128053090","Aluminum:  4413.802<br />lwr: 0.128144619","Aluminum:  4431.470<br />lwr: 0.128325923","Aluminum:  4466.000<br />lwr: 0.128678916","Aluminum:  4506.180<br />lwr: 0.129087452","Aluminum:  4519.660<br />lwr: 0.129223984","Aluminum:  4534.800<br />lwr: 0.129377015","Aluminum:  4578.000<br />lwr: 0.129811861","Aluminum:  4679.724<br />lwr: 0.130825418","Aluminum:  4721.000<br />lwr: 0.131232618","Aluminum:  4775.320<br />lwr: 0.131765006","Aluminum:  4829.056<br />lwr: 0.132287828","Aluminum:  4852.940<br />lwr: 0.132518999","Aluminum:  4924.490<br />lwr: 0.133207148","Aluminum:  4940.032<br />lwr: 0.133355770","Aluminum:  4982.140<br />lwr: 0.133756918","Aluminum:  5000.000<br />lwr: 0.133926402","Aluminum:  5023.810<br />lwr: 0.134151741","Aluminum:  5060.340<br />lwr: 0.134496122","Aluminum:  5063.000<br />lwr: 0.134521136","Aluminum:  5074.345<br />lwr: 0.134627726","Aluminum:  5080.363<br />lwr: 0.134684204","Aluminum:  5128.640<br />lwr: 0.135135720","Aluminum:  5149.080<br />lwr: 0.135326059","Aluminum:  5208.540<br />lwr: 0.135876991","Aluminum:  5212.570<br />lwr: 0.135914183","Aluminum:  5263.700<br />lwr: 0.136384453","Aluminum:  5308.000<br />lwr: 0.136789520","Aluminum:  5435.273<br />lwr: 0.137941234","Aluminum:  5553.000<br />lwr: 0.138991129","Aluminum:  5557.760<br />lwr: 0.139033275","Aluminum:  5616.320<br />lwr: 0.139549872","Aluminum:  5632.510<br />lwr: 0.139692080","Aluminum:  5683.264<br />lwr: 0.140136179","Aluminum:  5691.840<br />lwr: 0.140210965","Aluminum:  5839.321<br />lwr: 0.141485812","Aluminum:  5864.040<br />lwr: 0.141697441","Aluminum:  5944.163<br />lwr: 0.142379463","Aluminum:  5978.370<br />lwr: 0.142668828","Aluminum:  6101.770<br />lwr: 0.143703881","Aluminum:  6132.060<br />lwr: 0.143955872","Aluminum:  6143.000<br />lwr: 0.144046687","Aluminum:  6171.030<br />lwr: 0.144278893","Aluminum:  6217.790<br />lwr: 0.144664748","Aluminum:  6226.436<br />lwr: 0.144735888","Aluminum:  6376.780<br />lwr: 0.145962829","Aluminum:  6399.000<br />lwr: 0.146142571","Aluminum:  6507.398<br />lwr: 0.147013681","Aluminum:  6513.000<br />lwr: 0.147058444","Aluminum:  6540.170<br />lwr: 0.147275194","Aluminum:  6560.000<br />lwr: 0.147433021","Aluminum:  6576.330<br />lwr: 0.147562760","Aluminum:  6684.020<br />lwr: 0.148413160","Aluminum:  6687.320<br />lwr: 0.148439079","Aluminum:  6825.000<br />lwr: 0.149513147","Aluminum:  6893.810<br />lwr: 0.150044697","Aluminum:  6905.380<br />lwr: 0.150133736","Aluminum:  6942.000<br />lwr: 0.150414918","Aluminum:  7025.862<br />lwr: 0.151055246","Aluminum:  7109.340<br />lwr: 0.151687748","Aluminum:  7126.600<br />lwr: 0.151817925","Aluminum:  7196.000<br />lwr: 0.152339296","Aluminum:  7301.650<br />lwr: 0.153126787","Aluminum:  7563.000<br />lwr: 0.155043654","Aluminum:  7772.280<br />lwr: 0.156547929","Aluminum:  7779.340<br />lwr: 0.156598216","Aluminum:  7806.600<br />lwr: 0.156792105","Aluminum:  8057.890<br />lwr: 0.158559137","Aluminum:  8101.529<br />lwr: 0.158862350","Aluminum:  8110.616<br />lwr: 0.158925355","Aluminum:  8156.740<br />lwr: 0.159244457","Aluminum:  8172.880<br />lwr: 0.159355843","Aluminum:  8179.610<br />lwr: 0.159402247","Aluminum:  8318.290<br />lwr: 0.160352995","Aluminum:  8356.760<br />lwr: 0.160614914","Aluminum:  8361.000<br />lwr: 0.160643733","Aluminum:  8600.000<br />lwr: 0.162253187","Aluminum:  8737.050<br />lwr: 0.163163070","Aluminum:  9034.470<br />lwr: 0.165106354","Aluminum:  9035.970<br />lwr: 0.165116049","Aluminum:  9388.160<br />lwr: 0.167364136","Aluminum:  9542.662<br />lwr: 0.168333130","Aluminum:  9559.510<br />lwr: 0.168438180","Aluminum:  9700.000<br />lwr: 0.169309531","Aluminum:  9896.680<br />lwr: 0.170515769","Aluminum: 10005.812<br />lwr: 0.171178393","Aluminum: 10050.000<br />lwr: 0.171445362","Aluminum: 10233.858<br />lwr: 0.172548084","Aluminum: 10343.200<br />lwr: 0.173197813","Aluminum: 10379.837<br />lwr: 0.173414522","Aluminum: 10711.560<br />lwr: 0.175354505","Aluminum: 10869.710<br />lwr: 0.176265724","Aluminum: 10891.960<br />lwr: 0.176393232","Aluminum: 10908.460<br />lwr: 0.176487680","Aluminum: 10990.470<br />lwr: 0.176955749","Aluminum: 10990.530<br />lwr: 0.176956090","Aluminum: 11116.490<br />lwr: 0.177670617","Aluminum: 11359.000<br />lwr: 0.179031670","Aluminum: 11526.000<br />lwr: 0.179958032","Aluminum: 11711.000<br />lwr: 0.180974155","Aluminum: 11803.000<br />lwr: 0.181475605","Aluminum: 11855.800<br />lwr: 0.181762252","Aluminum: 11985.000<br />lwr: 0.182460200","Aluminum: 12055.930<br />lwr: 0.182841300","Aluminum: 12219.017<br />lwr: 0.183712079","Aluminum: 12247.000<br />lwr: 0.183860733","Aluminum: 12414.483<br />lwr: 0.184745886","Aluminum: 12430.700<br />lwr: 0.184831182","Aluminum: 12560.000<br />lwr: 0.185508693","Aluminum: 12600.000<br />lwr: 0.185717372","Aluminum: 12641.000<br />lwr: 0.185930823","Aluminum: 12697.000<br />lwr: 0.186221643","Aluminum: 12699.930<br />lwr: 0.186236837","Aluminum: 12800.710<br />lwr: 0.186758047","Aluminum: 12837.925<br />lwr: 0.186949842","Aluminum: 12876.191<br />lwr: 0.187146680","Aluminum: 12911.000<br />lwr: 0.187325406","Aluminum: 13313.000<br />lwr: 0.189367229","Aluminum: 13535.000<br />lwr: 0.190477735","Aluminum: 13578.400<br />lwr: 0.190693454","Aluminum: 13714.000<br />lwr: 0.191364587","Aluminum: 13720.174<br />lwr: 0.191395042","Aluminum: 13775.000<br />lwr: 0.191665098","Aluminum: 13871.300<br />lwr: 0.192137762","Aluminum: 13983.000<br />lwr: 0.192683360","Aluminum: 14157.000<br />lwr: 0.193527669","Aluminum: 14165.940<br />lwr: 0.193570867","Aluminum: 14369.230<br />lwr: 0.194548438","Aluminum: 14376.210<br />lwr: 0.194581844","Aluminum: 14380.579<br />lwr: 0.194602748","Aluminum: 14638.271<br />lwr: 0.195828522","Aluminum: 14744.157<br />lwr: 0.196328144","Aluminum: 14960.965<br />lwr: 0.197343951","Aluminum: 15050.070<br />lwr: 0.197758670","Aluminum: 15400.080<br />lwr: 0.199372501","Aluminum: 15580.000<br />lwr: 0.200192849","Aluminum: 15667.844<br />lwr: 0.200591149","Aluminum: 15747.000<br />lwr: 0.200948819","Aluminum: 15855.930<br />lwr: 0.201439126","Aluminum: 15982.549<br />lwr: 0.202006321","Aluminum: 16187.748<br />lwr: 0.202919373","Aluminum: 16285.040<br />lwr: 0.203349665","Aluminum: 16374.220<br />lwr: 0.203742621","Aluminum: 16378.832<br />lwr: 0.203762906","Aluminum: 16554.910<br />lwr: 0.204534573","Aluminum: 16744.907<br />lwr: 0.205361304","Aluminum: 16986.000<br />lwr: 0.206401671","Aluminum: 17250.000<br />lwr: 0.207529980","Aluminum: 17376.000<br />lwr: 0.208064552","Aluminum: 17668.669<br />lwr: 0.209296627","Aluminum: 18190.640<br />lwr: 0.211461622","Aluminum: 18253.450<br />lwr: 0.211719417","Aluminum: 18567.346<br />lwr: 0.212999228","Aluminum: 18721.000<br />lwr: 0.213620600","Aluminum: 18771.346<br />lwr: 0.213823479","Aluminum: 18915.000<br />lwr: 0.214400431","Aluminum: 18941.560<br />lwr: 0.214506792","Aluminum: 18948.944<br />lwr: 0.214536345","Aluminum: 19043.000<br />lwr: 0.214912128","Aluminum: 19174.000<br />lwr: 0.215433516","Aluminum: 19482.960<br />lwr: 0.216654130","Aluminum: 19494.000<br />lwr: 0.216697513","Aluminum: 19555.370<br />lwr: 0.216938386","Aluminum: 19741.000<br />lwr: 0.217664004","Aluminum: 19770.000<br />lwr: 0.217776964","Aluminum: 19778.615<br />lwr: 0.217810500","Aluminum: 19814.984<br />lwr: 0.217951972","Aluminum: 20147.874<br />lwr: 0.219239140","Aluminum: 20447.460<br />lwr: 0.220385812","Aluminum: 21255.484<br />lwr: 0.223425281","Aluminum: 21460.000<br />lwr: 0.224182685","Aluminum: 22988.650<br />lwr: 0.229701094","Aluminum: 23301.643<br />lwr: 0.230801458","Aluminum: 23502.000<br />lwr: 0.231500821","Aluminum: 23767.000<br />lwr: 0.232419922","Aluminum: 23920.000<br />lwr: 0.232947554","Aluminum: 23973.990<br />lwr: 0.233133220","Aluminum: 24381.260<br />lwr: 0.234525138","Aluminum: 24556.268<br />lwr: 0.235118634","Aluminum: 24654.550<br />lwr: 0.235450734","Aluminum: 24669.671<br />lwr: 0.235501752","Aluminum: 25231.350<br />lwr: 0.237382690","Aluminum: 25590.000<br />lwr: 0.238569585","Aluminum: 25981.900<br />lwr: 0.239854263","Aluminum: 26372.522<br />lwr: 0.241122325","Aluminum: 26929.000<br />lwr: 0.242907965","Aluminum: 27052.400<br />lwr: 0.243300690","Aluminum: 27375.200<br />lwr: 0.244322557","Aluminum: 27477.140<br />lwr: 0.244643639","Aluminum: 27642.276<br />lwr: 0.245162139","Aluminum: 27663.273<br />lwr: 0.245227922","Aluminum: 27760.700<br />lwr: 0.245532737","Aluminum: 27978.000<br />lwr: 0.246210105","Aluminum: 31104.223<br />lwr: 0.255599047","Aluminum: 31230.000<br />lwr: 0.255963728","Aluminum: 31722.000<br />lwr: 0.257381176","Aluminum: 31774.000<br />lwr: 0.257530154","Aluminum: 32181.951<br />lwr: 0.258693472","Aluminum: 32184.000<br />lwr: 0.258699291","Aluminum: 32745.600<br />lwr: 0.260285174","Aluminum: 33202.333<br />lwr: 0.261561987","Aluminum: 34016.422<br />lwr: 0.263809882","Aluminum: 35308.374<br />lwr: 0.267306830","Aluminum: 35573.000<br />lwr: 0.268012829","Aluminum: 35690.000<br />lwr: 0.268323891","Aluminum: 35691.180<br />lwr: 0.268327024","Aluminum: 36720.164<br />lwr: 0.271034647","Aluminum: 37142.860<br />lwr: 0.272132671","Aluminum: 37463.050<br />lwr: 0.272959042","Aluminum: 37847.079<br />lwr: 0.273944163","Aluminum: 38526.000<br />lwr: 0.275670028","Aluminum: 38550.591<br />lwr: 0.275732169","Aluminum: 38606.705<br />lwr: 0.275873872","Aluminum: 39044.600<br />lwr: 0.276975120","Aluminum: 39187.544<br />lwr: 0.277332873","Aluminum: 39434.000<br />lwr: 0.277947710","Aluminum: 39579.000<br />lwr: 0.278308281","Aluminum: 39604.167<br />lwr: 0.278370777","Aluminum: 39947.084<br />lwr: 0.279219769","Aluminum: 40206.800<br />lwr: 0.279859637","Aluminum: 41396.100<br />lwr: 0.282756038","Aluminum: 42860.000<br />lwr: 0.286248129","Aluminum: 42931.000<br />lwr: 0.286415520","Aluminum: 43093.730<br />lwr: 0.286798499","Aluminum: 43385.000<br />lwr: 0.287481661","Aluminum: 43939.000<br />lwr: 0.288772890","Aluminum: 44366.000<br />lwr: 0.289760938","Aluminum: 44434.450<br />lwr: 0.289918753","Aluminum: 44953.234<br />lwr: 0.291109746","Aluminum: 45243.122<br />lwr: 0.291771380","Aluminum: 46587.292<br />lwr: 0.294803924","Aluminum: 48317.759<br />lwr: 0.298625663","Aluminum: 48714.000<br />lwr: 0.299488241","Aluminum: 49005.832<br />lwr: 0.300120629","Aluminum: 52442.580<br />lwr: 0.307390931","Aluminum: 55798.500<br />lwr: 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 <div class="section level2">
 <h2 class="unnumbered" id="references">References<a class="anchor" aria-label="anchor" href="#references"></a>
diff --git a/articles/tbni.html b/articles/tbni.html
index f5de0064..1ca5db6f 100644
--- a/articles/tbni.html
+++ b/articles/tbni.html
@@ -308,13 +308,13 @@ <h3 id="plotting-results">Plotting results<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_tbniscr.html">show_tbniscr</a></span><span class="op">(</span><span class="va">tbniscr</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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data-for="htmlwidget-e5c8c404fe174e4c81bd">{"x":{"data":[{"x":[null,null,null,null,null],"y":[null,32,32,null,null],"text":"","type":"scatter","mode":"lines","line":{"width":1.8897637795275593,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(204,50,49,1)","hoveron":"fills","showlegend":false,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[null,null,null,null,null],"y":[32,46,46,32,32],"text":"","type":"scatter","mode":"lines","line":{"width":1.8897637795275593,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(233,195,24,1)","hoveron":"fills","showlegend":false,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[null,null,null,null,null],"y":[46,null,null,46,46],"text":"","type":"scatter","mode":"lines","line":{"width":1.8897637795275593,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(45,201,56,1)","hoveron":"fills","showlegend":false,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],"y":[53,47,43,45,45,48,50,40,41,45,44,50,49,52,46,47,47,53,53,48,53,45,51,44,40,46],"text":["Year: 1998<br />Segment_TBNI: 53<br />bay_segment: OTB<br />bay_segment: OTB","Year: 1999<br />Segment_TBNI: 47<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2000<br />Segment_TBNI: 43<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2001<br />Segment_TBNI: 45<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2002<br />Segment_TBNI: 45<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2003<br />Segment_TBNI: 48<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2004<br />Segment_TBNI: 50<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2005<br />Segment_TBNI: 40<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2006<br />Segment_TBNI: 41<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2007<br />Segment_TBNI: 45<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2008<br />Segment_TBNI: 44<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2009<br />Segment_TBNI: 50<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2010<br />Segment_TBNI: 49<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2011<br />Segment_TBNI: 52<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2012<br />Segment_TBNI: 46<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2013<br />Segment_TBNI: 47<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2014<br />Segment_TBNI: 47<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2015<br />Segment_TBNI: 53<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2016<br />Segment_TBNI: 53<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2017<br />Segment_TBNI: 48<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2018<br />Segment_TBNI: 53<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2019<br />Segment_TBNI: 45<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2020<br />Segment_TBNI: 51<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2021<br />Segment_TBNI: 44<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2022<br />Segment_TBNI: 40<br />bay_segment: OTB<br />bay_segment: OTB","Year: 2023<br />Segment_TBNI: 46<br />bay_segment: OTB<br />bay_segment: OTB"],"type":"scatter","mode":"lines","line":{"width":4.7244094488188981,"color":"rgba(0,0,0,1)","dash":"dash"},"hoveron":"points","name":"OTB","legendgroup":"OTB","showlegend":true,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],"y":[47,47,44,44,39,41,41,32,41,42,41,41,50,45,44,50,50,51,56,47,44,46,43,37,41,44],"text":["Year: 1998<br />Segment_TBNI: 47<br />bay_segment: HB<br />bay_segment: HB","Year: 1999<br />Segment_TBNI: 47<br />bay_segment: HB<br />bay_segment: HB","Year: 2000<br />Segment_TBNI: 44<br />bay_segment: HB<br />bay_segment: HB","Year: 2001<br />Segment_TBNI: 44<br />bay_segment: HB<br />bay_segment: HB","Year: 2002<br />Segment_TBNI: 39<br />bay_segment: HB<br />bay_segment: HB","Year: 2003<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2004<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2005<br />Segment_TBNI: 32<br />bay_segment: HB<br />bay_segment: HB","Year: 2006<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2007<br />Segment_TBNI: 42<br />bay_segment: HB<br />bay_segment: HB","Year: 2008<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2009<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2010<br />Segment_TBNI: 50<br />bay_segment: HB<br />bay_segment: HB","Year: 2011<br />Segment_TBNI: 45<br />bay_segment: HB<br />bay_segment: HB","Year: 2012<br />Segment_TBNI: 44<br />bay_segment: HB<br />bay_segment: HB","Year: 2013<br />Segment_TBNI: 50<br />bay_segment: HB<br />bay_segment: HB","Year: 2014<br />Segment_TBNI: 50<br />bay_segment: HB<br />bay_segment: HB","Year: 2015<br />Segment_TBNI: 51<br />bay_segment: HB<br />bay_segment: HB","Year: 2016<br />Segment_TBNI: 56<br />bay_segment: HB<br />bay_segment: HB","Year: 2017<br />Segment_TBNI: 47<br />bay_segment: HB<br />bay_segment: HB","Year: 2018<br />Segment_TBNI: 44<br />bay_segment: HB<br />bay_segment: HB","Year: 2019<br />Segment_TBNI: 46<br />bay_segment: HB<br />bay_segment: HB","Year: 2020<br />Segment_TBNI: 43<br />bay_segment: HB<br />bay_segment: HB","Year: 2021<br />Segment_TBNI: 37<br />bay_segment: HB<br />bay_segment: HB","Year: 2022<br />Segment_TBNI: 41<br />bay_segment: HB<br />bay_segment: HB","Year: 2023<br />Segment_TBNI: 44<br />bay_segment: HB<br />bay_segment: HB"],"type":"scatter","mode":"lines","line":{"width":4.7244094488188981,"color":"rgba(0,0,0,1)","dash":"dashdot"},"hoveron":"points","name":"HB","legendgroup":"HB","showlegend":true,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],"y":[51,49,45,47,43,47,50,36,42,41,44,44,51,45,46,45,50,53,49,48,48,44,47,40,45,42],"text":["Year: 1998<br />Segment_TBNI: 51<br />bay_segment: MTB<br />bay_segment: MTB","Year: 1999<br />Segment_TBNI: 49<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2000<br />Segment_TBNI: 45<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2001<br />Segment_TBNI: 47<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2002<br />Segment_TBNI: 43<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2003<br />Segment_TBNI: 47<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2004<br />Segment_TBNI: 50<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2005<br />Segment_TBNI: 36<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2006<br />Segment_TBNI: 42<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2007<br />Segment_TBNI: 41<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2008<br />Segment_TBNI: 44<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2009<br />Segment_TBNI: 44<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2010<br />Segment_TBNI: 51<br />bay_segment: MTB<br 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42<br />bay_segment: MTB<br />bay_segment: MTB"],"type":"scatter","mode":"lines","line":{"width":4.7244094488188981,"color":"rgba(102,102,102,1)","dash":"dot"},"hoveron":"points","name":"MTB","legendgroup":"MTB","showlegend":true,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],"y":[46,47,57,51,57,49,48,36,43,40,42,43,43,50,45,46,50,51,48,53,44,48,52,47,44,45],"text":["Year: 1998<br />Segment_TBNI: 46<br />bay_segment: LTB<br />bay_segment: LTB","Year: 1999<br />Segment_TBNI: 47<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2000<br />Segment_TBNI: 57<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2001<br />Segment_TBNI: 51<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2002<br />Segment_TBNI: 57<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2003<br />Segment_TBNI: 49<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2004<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2005<br />Segment_TBNI: 36<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2006<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2007<br />Segment_TBNI: 40<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2008<br />Segment_TBNI: 42<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2009<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2010<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2011<br />Segment_TBNI: 50<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2012<br />Segment_TBNI: 45<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2013<br />Segment_TBNI: 46<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2014<br />Segment_TBNI: 50<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2015<br />Segment_TBNI: 51<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2016<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2017<br />Segment_TBNI: 53<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2018<br />Segment_TBNI: 44<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2019<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2020<br />Segment_TBNI: 52<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2021<br />Segment_TBNI: 47<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2022<br />Segment_TBNI: 44<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2023<br />Segment_TBNI: 45<br />bay_segment: LTB<br />bay_segment: 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1998<br />Segment_TBNI: 51<br />bay_segment: MTB<br />bay_segment: MTB","Year: 1999<br />Segment_TBNI: 49<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2000<br />Segment_TBNI: 45<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2001<br />Segment_TBNI: 47<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2002<br />Segment_TBNI: 43<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2003<br />Segment_TBNI: 47<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2004<br />Segment_TBNI: 50<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2005<br />Segment_TBNI: 36<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2006<br />Segment_TBNI: 42<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2007<br />Segment_TBNI: 41<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2008<br />Segment_TBNI: 44<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2009<br />Segment_TBNI: 44<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2010<br />Segment_TBNI: 51<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2011<br />Segment_TBNI: 45<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2012<br />Segment_TBNI: 46<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2013<br />Segment_TBNI: 45<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2014<br />Segment_TBNI: 50<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2015<br />Segment_TBNI: 53<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2016<br />Segment_TBNI: 49<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2017<br />Segment_TBNI: 48<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2018<br />Segment_TBNI: 48<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2019<br />Segment_TBNI: 44<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2020<br />Segment_TBNI: 47<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2021<br />Segment_TBNI: 40<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2022<br />Segment_TBNI: 45<br />bay_segment: MTB<br />bay_segment: MTB","Year: 2023<br />Segment_TBNI: 42<br />bay_segment: MTB<br />bay_segment: MTB"],"type":"scatter","mode":"lines","line":{"width":4.7244094488188981,"color":"rgba(102,102,102,1)","dash":"dot"},"hoveron":"points","name":"MTB","legendgroup":"MTB","showlegend":true,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],"y":[46,47,57,51,57,49,48,36,43,40,42,43,43,50,45,46,50,51,48,53,44,48,52,47,44,45],"text":["Year: 1998<br />Segment_TBNI: 46<br />bay_segment: LTB<br />bay_segment: LTB","Year: 1999<br />Segment_TBNI: 47<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2000<br />Segment_TBNI: 57<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2001<br />Segment_TBNI: 51<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2002<br />Segment_TBNI: 57<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2003<br />Segment_TBNI: 49<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2004<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2005<br />Segment_TBNI: 36<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2006<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2007<br />Segment_TBNI: 40<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2008<br />Segment_TBNI: 42<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2009<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2010<br />Segment_TBNI: 43<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2011<br />Segment_TBNI: 50<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2012<br />Segment_TBNI: 45<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2013<br />Segment_TBNI: 46<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2014<br />Segment_TBNI: 50<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2015<br />Segment_TBNI: 51<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2016<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2017<br />Segment_TBNI: 53<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2018<br />Segment_TBNI: 44<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2019<br />Segment_TBNI: 48<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2020<br />Segment_TBNI: 52<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2021<br />Segment_TBNI: 47<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2022<br />Segment_TBNI: 44<br />bay_segment: LTB<br />bay_segment: LTB","Year: 2023<br />Segment_TBNI: 45<br />bay_segment: LTB<br />bay_segment: LTB"],"type":"scatter","mode":"lines","line":{"width":4.7244094488188981,"color":"rgba(102,102,102,1)","dash":"solid"},"hoveron":"points","name":"LTB","legendgroup":"LTB","showlegend":true,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,1997.3499999999999,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001,2023.6500000000001],"y":[32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32],"text":"perc[1]: 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 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_tbniscrall.html">show_tbniscrall</a></span><span class="op">(</span><span class="va">tbniscr</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_tbnimatrix.html">show_tbnimatrix</a></span><span class="op">(</span><span class="va">tbniscr</span>, plotly <span class="op">=</span> <span class="cn">T</span><span class="op">)</span></span></code></pre></div>
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 by the colors in each graph are based on the 33rd and 50th percentiles
 of the distribution of all TBNI scores calculated for Tampa Bay. This
 plotting option is provided for consistency with existing TBEP reporting
diff --git a/articles/tidalcreeks.html b/articles/tidalcreeks.html
index 12c5e6a7..7935319e 100644
--- a/articles/tidalcreeks.html
+++ b/articles/tidalcreeks.html
@@ -349,7 +349,7 @@ <h3 id="indicator-functions">Indicator functions<a class="anchor" aria-label="an
 <code class="sourceCode R"><span><span class="va">cntdat</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/anlz_tdlcrkindic.html">anlz_tdlcrkindic</a></span><span class="op">(</span><span class="va">tidalcreeks</span>, <span class="va">iwrraw</span>, yr <span class="op">=</span> <span class="fl">2023</span><span class="op">)</span></span>
 <span><span class="fu"><a href="../reference/show_tdlcrkindic.html">show_tdlcrkindic</a></span><span class="op">(</span>id <span class="op">=</span> <span class="va">id</span>, cntdat <span class="op">=</span> <span class="va">cntdat</span>, thrsel <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
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<code><a href="../reference/show_tdlcrkindiccdf.html">show_tdlcrkindiccdf()</a></code> function is similar except
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<code><a href="../reference/show_tdlcrkindiccdf.html">show_tdlcrkindiccdf()</a></code> function is similar except
 that empirical cumulative distribution functions (CDF) are plotted to
 evaluate outcomes for a specific creek relative to the entire
 distribution of creeks in southwest Florida. Each indicator and each
@@ -362,7 +362,7 @@ <h3 id="indicator-functions">Indicator functions<a class="anchor" aria-label="an
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/show_tdlcrkindiccdf.html">show_tdlcrkindiccdf</a></span><span class="op">(</span>id <span class="op">=</span> <span class="va">id</span>, cntdat <span class="op">=</span> <span class="va">cntdat</span>, thrsel <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
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 <div class="section level2">
diff --git a/pkgdown.yml b/pkgdown.yml
index e310e9db..c95ebbc8 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -9,7 +9,7 @@ articles:
   tbbi: tbbi.html
   tbni: tbni.html
   tidalcreeks: tidalcreeks.html
-last_built: 2024-10-12T17:49Z
+last_built: 2024-10-12T17:57Z
 urls:
   reference: https://tbep-tech.github.io/tbeptools/reference
   article: https://tbep-tech.github.io/tbeptools/articles
diff --git a/reference/show_annualassess.html b/reference/show_annualassess.html
index 8b4eab1b..8bbb3c66 100644
--- a/reference/show_annualassess.html
+++ b/reference/show_annualassess.html
@@ -98,8 +98,8 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">show_annualassess</span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span><span class="op">)</span></span></span>
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solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25038{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25042{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25043{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-80e58d66"><thead><tr style="overflow-wrap:break-word;"><th class="cl-80e25024"><p class="cl-80e235a8"><span class="cl-80de47f4">Segment</span></p></th><th colspan="2" class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">Chl-a (ug/L)</span></p></th><th colspan="2" class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">Light Penetration (m</span><span class="cl-80de47fe">-1</span><span class="cl-80de47f4">)</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-80e25024"><p class="cl-80e235a8"><span class="cl-80de47f4"></span></p></th><th class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">2023</span></p></th><th class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">target</span></p></th><th class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">2023</span></p></th><th class="cl-80e2502e"><p class="cl-80e235b2"><span class="cl-80de47f4">target</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-80e2502f"><p class="cl-80e235a8"><span class="cl-80de47f4">OTB</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">6.2</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">8.5</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">0.73</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-80e2502f"><p class="cl-80e235a8"><span class="cl-80de47f4">HB</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">6.9</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">13.2</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">0.79</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">1.58</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-80e2502f"><p class="cl-80e235a8"><span class="cl-80de47f4">MTB</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">3.7</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">7.4</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">0.47</span></p></td><td class="cl-80e25038"><p class="cl-80e235b2"><span class="cl-80de47f4">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-80e25042"><p class="cl-80e235a8"><span class="cl-80de47f4">LTB</span></p></td><td class="cl-80e25043"><p class="cl-80e235b2"><span class="cl-80de47f4">2.6</span></p></td><td class="cl-80e25043"><p class="cl-80e235b2"><span class="cl-80de47f4">4.6</span></p></td><td class="cl-80e25043"><p class="cl-80e235b2"><span class="cl-80de47f4">0.54</span></p></td><td class="cl-80e25043"><p class="cl-80e235b2"><span class="cl-80de47f4">0.63</span></p></td></tr></tbody></table></div><span class="r-in"><span><span class="fu">show_annualassess</span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span>, caption <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<style></style><div class="tabwid"><style>.cl-8132123a{}.cl-812cce42{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-812cce4c{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-812f0162{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-812f016c{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 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solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a63{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a6c{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a6d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-81296f18{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}</style><table data-quarto-disable-processing="true" class="table cl-8132123a"><caption style="display:table-caption;margin:0pt;text-align:center;border-bottom: 0.00pt solid transparent;border-top: 0.00pt solid transparent;border-left: 0.00pt solid transparent;border-right: 0.00pt solid transparent;padding-top:3pt;padding-bottom:3pt;padding-left:3pt;padding-right:3pt;line-height: 1;background-color:transparent;"><span class="cl-81296f18">Water quality outcomes for 2023.</span></caption><thead><tr style="overflow-wrap:break-word;"><th class="cl-812f1a58"><p class="cl-812f0162"><span class="cl-812cce42">Segment</span></p></th><th colspan="2" class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">Chl-a (ug/L)</span></p></th><th colspan="2" class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">Light Penetration (m</span><span class="cl-812cce4c">-1</span><span class="cl-812cce42">)</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-812f1a58"><p class="cl-812f0162"><span class="cl-812cce42"></span></p></th><th class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">2023</span></p></th><th class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">target</span></p></th><th class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">2023</span></p></th><th class="cl-812f1a59"><p class="cl-812f016c"><span class="cl-812cce42">target</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-812f1a62"><p class="cl-812f0162"><span class="cl-812cce42">OTB</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">6.2</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">8.5</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">0.73</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-812f1a62"><p class="cl-812f0162"><span class="cl-812cce42">HB</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">6.9</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">13.2</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">0.79</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">1.58</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-812f1a62"><p class="cl-812f0162"><span class="cl-812cce42">MTB</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">3.7</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">7.4</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">0.47</span></p></td><td class="cl-812f1a63"><p class="cl-812f016c"><span class="cl-812cce42">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-812f1a6c"><p class="cl-812f0162"><span class="cl-812cce42">LTB</span></p></td><td class="cl-812f1a6d"><p class="cl-812f016c"><span class="cl-812cce42">2.6</span></p></td><td class="cl-812f1a6d"><p class="cl-812f016c"><span class="cl-812cce42">4.6</span></p></td><td class="cl-812f1a6d"><p class="cl-812f016c"><span class="cl-812cce42">0.54</span></p></td><td class="cl-812f1a6d"><p class="cl-812f016c"><span class="cl-812cce42">0.63</span></p></td></tr></tbody></table></div></code></pre></div>
+<style></style><div class="tabwid"><style>.cl-8c530592{}.cl-8c4bf702{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-8c4bf70c{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-8c4fafc8{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c4fafdc{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c4fca58{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca62{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6c{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6e{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca76{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-8c530592"><thead><tr style="overflow-wrap:break-word;"><th class="cl-8c4fca58"><p class="cl-8c4fafc8"><span class="cl-8c4bf702">Segment</span></p></th><th colspan="2" class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">Chl-a (ug/L)</span></p></th><th colspan="2" class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">Light Penetration (m</span><span class="cl-8c4bf70c">-1</span><span class="cl-8c4bf702">)</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-8c4fca58"><p class="cl-8c4fafc8"><span class="cl-8c4bf702"></span></p></th><th class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">2023</span></p></th><th class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">target</span></p></th><th class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">2023</span></p></th><th class="cl-8c4fca62"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">target</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-8c4fca6c"><p class="cl-8c4fafc8"><span class="cl-8c4bf702">OTB</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">6.2</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">8.5</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.73</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c4fca6c"><p class="cl-8c4fafc8"><span class="cl-8c4bf702">HB</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">6.9</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">13.2</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.79</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">1.58</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c4fca6c"><p class="cl-8c4fafc8"><span class="cl-8c4bf702">MTB</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">3.7</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">7.4</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.47</span></p></td><td class="cl-8c4fca6d"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c4fca6e"><p class="cl-8c4fafc8"><span class="cl-8c4bf702">LTB</span></p></td><td class="cl-8c4fca76"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">2.6</span></p></td><td class="cl-8c4fca76"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">4.6</span></p></td><td class="cl-8c4fca76"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.54</span></p></td><td class="cl-8c4fca76"><p class="cl-8c4fafdc"><span class="cl-8c4bf702">0.63</span></p></td></tr></tbody></table></div><span class="r-in"><span><span class="fu">show_annualassess</span><span class="op">(</span><span class="va">epcdata</span>, yrsel <span class="op">=</span> <span class="fl">2023</span>, caption <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
+<style></style><div class="tabwid"><style>.cl-8ca1351e{}.cl-8c9be05a{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-8c9be064{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-8c9e1898{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c9e18a2{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c9e308a{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e3094{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e3095{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e309e{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e309f{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e30a8{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9865d8{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}</style><table data-quarto-disable-processing="true" class="table cl-8ca1351e"><caption style="display:table-caption;margin:0pt;text-align:center;border-bottom: 0.00pt solid transparent;border-top: 0.00pt solid transparent;border-left: 0.00pt solid transparent;border-right: 0.00pt solid transparent;padding-top:3pt;padding-bottom:3pt;padding-left:3pt;padding-right:3pt;line-height: 1;background-color:transparent;"><span class="cl-8c9865d8">Water quality outcomes for 2023.</span></caption><thead><tr style="overflow-wrap:break-word;"><th class="cl-8c9e308a"><p class="cl-8c9e1898"><span class="cl-8c9be05a">Segment</span></p></th><th colspan="2" class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">Chl-a (ug/L)</span></p></th><th colspan="2" class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">Light Penetration (m</span><span class="cl-8c9be064">-1</span><span class="cl-8c9be05a">)</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-8c9e308a"><p class="cl-8c9e1898"><span class="cl-8c9be05a"></span></p></th><th class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">2023</span></p></th><th class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">target</span></p></th><th class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">2023</span></p></th><th class="cl-8c9e3094"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">target</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-8c9e3095"><p class="cl-8c9e1898"><span class="cl-8c9be05a">OTB</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">6.2</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">8.5</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.73</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c9e3095"><p class="cl-8c9e1898"><span class="cl-8c9be05a">HB</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">6.9</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">13.2</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.79</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">1.58</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c9e3095"><p class="cl-8c9e1898"><span class="cl-8c9be05a">MTB</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">3.7</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">7.4</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.47</span></p></td><td class="cl-8c9e309e"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.83</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8c9e309f"><p class="cl-8c9e1898"><span class="cl-8c9be05a">LTB</span></p></td><td class="cl-8c9e30a8"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">2.6</span></p></td><td class="cl-8c9e30a8"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">4.6</span></p></td><td class="cl-8c9e30a8"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.54</span></p></td><td class="cl-8c9e30a8"><p class="cl-8c9e18a2"><span class="cl-8c9be05a">0.63</span></p></td></tr></tbody></table></div></code></pre></div>
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diff --git a/reference/show_matrixplotly.html b/reference/show_matrixplotly.html
index e3420b19..650d5921 100644
--- a/reference/show_matrixplotly.html
+++ b/reference/show_matrixplotly.html
@@ -90,7 +90,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="show_wqmatrix.html">show_wqmatrix</a></span><span class="op">(</span><span class="va">epcdata</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">show_matrixplotly</span><span class="op">(</span><span class="va">mat</span><span class="op">)</span></span></span>
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diff --git a/reference/show_ratab.html b/reference/show_ratab.html
index faf170dc..fd6fb696 100644
--- a/reference/show_ratab.html
+++ b/reference/show_ratab.html
@@ -120,7 +120,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-msg co"><span class="r-pr">#&gt;</span> Registered S3 method overwritten by 'ftExtra':</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   method                  from     </span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   as_flextable.data.frame flextable</span>
-<style></style><div class="tabwid"><style>.cl-88666538{}.cl-885fd7c2{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-885fd7cc{font-family:'Lato light';font-size:13pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-885fd7d6{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:italic;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-88621942{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8862194c{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-88623134{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623135{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8862313e{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8862313f{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623148{width:0.6in;background-color:rgba(144, 238, 144, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623149{width:0.6in;background-color:rgba(255, 255, 255, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623152{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623153{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-88666538"><tbody><tr style="overflow-wrap:break-word;"><td rowspan="2" class="cl-88623134"><p class="cl-88621942"><span class="cl-885fd7c2">Bay</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Segment</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Reasonable</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Assurance</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Assessment</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Steps</span></p></td><td colspan="5" class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">DATA</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">USED</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">TO</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">ASSESS</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">ANNUAL</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">REASONABLE</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">ASSURANCE</span></p></td><td rowspan="2" class="cl-8862313e"><p class="cl-88621942"><span class="cl-885fd7c2">OUTCOME</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">Year</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">1</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(2022)</span></p></td><td class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">Year</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">2</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(2023)</span></p></td><td class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">Year</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">3</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(2024)</span></p></td><td class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">Year</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">4</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(2025)</span></p></td><td class="cl-88623135"><p class="cl-88621942"><span class="cl-885fd7c2">Year</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">5</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(2026)</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8862313f"><p class="cl-8862194c"><span class="cl-885fd7cc">NMC</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">Action</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">1:</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Determine</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">if</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">observed</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">chlorophyll-a</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">exceeds</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">FDEP</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">threshold</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">of</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">9.3</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">ug/L</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">No</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(7.1)</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">No</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">(6.2)</span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623152"><p class="cl-8862194c"><span class="cl-885fd7c2">All</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">years</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">below</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">threshold</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">so</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">far,</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">not</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">necessary</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">for</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">NMC</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Actions</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">2-5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8862313f"><p class="cl-8862194c"><span class="cl-885fd7cc">NMC</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">Action</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">2:</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Determine</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">if</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">any</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">observed</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">chlorophyll-</span><span class="cl-885fd7d6">a</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">exceedences</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">occurred</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">for</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">2</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">consecutive</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">years</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">No</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">No</span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623152"><p class="cl-8862194c"><span class="cl-885fd7c2">All</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">years</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">met</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">threshold,</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">not</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">necessary</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">for</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">NMC</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Actions</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">3-5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-8862313f"><p class="cl-8862194c"><span class="cl-885fd7cc">NMC</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">Action</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">3:</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Determine</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">if</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">observed</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">hydrologically-normalized</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">total</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">load</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">exceeds</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">federally-recognized</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">TMDL</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">of</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">486</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">tons/year</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">N/A</span></p></td><td class="cl-88623148"><p class="cl-88621942"><span class="cl-885fd7c2">N/A</span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623149"><p class="cl-88621942"><span class="cl-885fd7c2"></span></p></td><td class="cl-88623152"><p class="cl-8862194c"><span class="cl-885fd7c2">Not</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">necessary</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">due</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">to</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">observed</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">water</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">quality</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">and</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">seagrass</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">conditions</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">in</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">the</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">bay</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">segment</span></p></td></tr><tr style="overflow-wrap:break-word;"><td colspan="6" class="cl-8862313f"><p class="cl-8862194c"><span class="cl-885fd7cc">NMC</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">Actions</span><span class="cl-885fd7cc"> </span><span class="cl-885fd7cc">4-5:</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">Determine</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">if</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">any</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">entity/source/facility</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">specific</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">exceedences</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">of</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">5-yr</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">average</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">allocation</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">occurred</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">during</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">implementation</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">period</span></p></td><td class="cl-88623152"><p class="cl-8862194c"><span class="cl-885fd7c2">Not</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">necessary</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">when</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">chlorophyll-</span><span class="cl-885fd7d6">a</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">threshold</span><span class="cl-885fd7c2"> </span><span class="cl-885fd7c2">met</span></p></td></tr></tbody></table></div></code></pre></div>
+<style></style><div class="tabwid"><style>.cl-94093bee{}.cl-94027d36{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-94027d4a{font-family:'Lato light';font-size:13pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-94027d4b{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:italic;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-940614d2{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-940614e6{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 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middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d28{width:2in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d29{width:0.6in;background-color:rgba(144, 238, 144, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d32{width:0.6in;background-color:rgba(255, 255, 255, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d33{width:1.5in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d34{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-94093bee"><tbody><tr style="overflow-wrap:break-word;"><td rowspan="2" class="cl-94062d14"><p class="cl-940614d2"><span class="cl-94027d36">Bay</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Segment</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Reasonable</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Assurance</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Assessment</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Steps</span></p></td><td colspan="5" class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">DATA</span><span class="cl-94027d36"> </span><span class="cl-94027d36">USED</span><span class="cl-94027d36"> </span><span class="cl-94027d36">TO</span><span class="cl-94027d36"> </span><span class="cl-94027d36">ASSESS</span><span class="cl-94027d36"> </span><span class="cl-94027d36">ANNUAL</span><span class="cl-94027d36"> </span><span class="cl-94027d36">REASONABLE</span><span class="cl-94027d36"> </span><span class="cl-94027d36">ASSURANCE</span></p></td><td rowspan="2" class="cl-94062d1f"><p class="cl-940614d2"><span class="cl-94027d36">OUTCOME</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">Year</span><span class="cl-94027d36"> </span><span class="cl-94027d36">1</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(2022)</span></p></td><td class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">Year</span><span class="cl-94027d36"> </span><span class="cl-94027d36">2</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(2023)</span></p></td><td class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">Year</span><span class="cl-94027d36"> </span><span class="cl-94027d36">3</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(2024)</span></p></td><td class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">Year</span><span class="cl-94027d36"> </span><span class="cl-94027d36">4</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(2025)</span></p></td><td class="cl-94062d1e"><p class="cl-940614d2"><span class="cl-94027d36">Year</span><span class="cl-94027d36"> </span><span class="cl-94027d36">5</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(2026)</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-94062d28"><p class="cl-940614e6"><span class="cl-94027d4a">NMC</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">Action</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">1:</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Determine</span><span class="cl-94027d36"> </span><span class="cl-94027d36">if</span><span class="cl-94027d36"> </span><span class="cl-94027d36">observed</span><span class="cl-94027d36"> </span><span class="cl-94027d36">chlorophyll-a</span><span class="cl-94027d36"> </span><span class="cl-94027d36">exceeds</span><span class="cl-94027d36"> </span><span class="cl-94027d36">FDEP</span><span class="cl-94027d36"> </span><span class="cl-94027d36">threshold</span><span class="cl-94027d36"> </span><span class="cl-94027d36">of</span><span class="cl-94027d36"> </span><span class="cl-94027d36">9.3</span><span class="cl-94027d36"> </span><span class="cl-94027d36">ug/L</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">No</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(7.1)</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">No</span><span class="cl-94027d36"> </span><span class="cl-94027d36">(6.2)</span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d33"><p class="cl-940614e6"><span class="cl-94027d36">All</span><span class="cl-94027d36"> </span><span class="cl-94027d36">years</span><span class="cl-94027d36"> </span><span class="cl-94027d36">below</span><span class="cl-94027d36"> </span><span class="cl-94027d36">threshold</span><span class="cl-94027d36"> </span><span class="cl-94027d36">so</span><span class="cl-94027d36"> </span><span class="cl-94027d36">far,</span><span class="cl-94027d36"> </span><span class="cl-94027d36">not</span><span class="cl-94027d36"> </span><span class="cl-94027d36">necessary</span><span class="cl-94027d36"> </span><span class="cl-94027d36">for</span><span class="cl-94027d36"> </span><span class="cl-94027d36">NMC</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Actions</span><span class="cl-94027d36"> </span><span class="cl-94027d36">2-5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-94062d28"><p class="cl-940614e6"><span class="cl-94027d4a">NMC</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">Action</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">2:</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Determine</span><span class="cl-94027d36"> </span><span class="cl-94027d36">if</span><span class="cl-94027d36"> </span><span class="cl-94027d36">any</span><span class="cl-94027d36"> </span><span class="cl-94027d36">observed</span><span class="cl-94027d36"> </span><span class="cl-94027d36">chlorophyll-</span><span class="cl-94027d4b">a</span><span class="cl-94027d36"> </span><span class="cl-94027d36">exceedences</span><span class="cl-94027d36"> </span><span class="cl-94027d36">occurred</span><span class="cl-94027d36"> </span><span class="cl-94027d36">for</span><span class="cl-94027d36"> </span><span class="cl-94027d36">2</span><span class="cl-94027d36"> </span><span class="cl-94027d36">consecutive</span><span class="cl-94027d36"> </span><span class="cl-94027d36">years</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">No</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">No</span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d33"><p class="cl-940614e6"><span class="cl-94027d36">All</span><span class="cl-94027d36"> </span><span class="cl-94027d36">years</span><span class="cl-94027d36"> </span><span class="cl-94027d36">met</span><span class="cl-94027d36"> </span><span class="cl-94027d36">threshold,</span><span class="cl-94027d36"> </span><span class="cl-94027d36">not</span><span class="cl-94027d36"> </span><span class="cl-94027d36">necessary</span><span class="cl-94027d36"> </span><span class="cl-94027d36">for</span><span class="cl-94027d36"> </span><span class="cl-94027d36">NMC</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Actions</span><span class="cl-94027d36"> </span><span class="cl-94027d36">3-5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-94062d28"><p class="cl-940614e6"><span class="cl-94027d4a">NMC</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">Action</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">3:</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Determine</span><span class="cl-94027d36"> </span><span class="cl-94027d36">if</span><span class="cl-94027d36"> </span><span class="cl-94027d36">observed</span><span class="cl-94027d36"> </span><span class="cl-94027d36">hydrologically-normalized</span><span class="cl-94027d36"> </span><span class="cl-94027d36">total</span><span class="cl-94027d36"> </span><span class="cl-94027d36">load</span><span class="cl-94027d36"> </span><span class="cl-94027d36">exceeds</span><span class="cl-94027d36"> </span><span class="cl-94027d36">federally-recognized</span><span class="cl-94027d36"> </span><span class="cl-94027d36">TMDL</span><span class="cl-94027d36"> </span><span class="cl-94027d36">of</span><span class="cl-94027d36"> </span><span class="cl-94027d36">486</span><span class="cl-94027d36"> </span><span class="cl-94027d36">tons/year</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">N/A</span></p></td><td class="cl-94062d29"><p class="cl-940614d2"><span class="cl-94027d36">N/A</span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d32"><p class="cl-940614d2"><span class="cl-94027d36"></span></p></td><td class="cl-94062d33"><p class="cl-940614e6"><span class="cl-94027d36">Not</span><span class="cl-94027d36"> </span><span class="cl-94027d36">necessary</span><span class="cl-94027d36"> </span><span class="cl-94027d36">due</span><span class="cl-94027d36"> </span><span class="cl-94027d36">to</span><span class="cl-94027d36"> </span><span class="cl-94027d36">observed</span><span class="cl-94027d36"> </span><span class="cl-94027d36">water</span><span class="cl-94027d36"> </span><span class="cl-94027d36">quality</span><span class="cl-94027d36"> </span><span class="cl-94027d36">and</span><span class="cl-94027d36"> </span><span class="cl-94027d36">seagrass</span><span class="cl-94027d36"> </span><span class="cl-94027d36">conditions</span><span class="cl-94027d36"> </span><span class="cl-94027d36">in</span><span class="cl-94027d36"> </span><span class="cl-94027d36">the</span><span class="cl-94027d36"> </span><span class="cl-94027d36">bay</span><span class="cl-94027d36"> </span><span class="cl-94027d36">segment</span></p></td></tr><tr style="overflow-wrap:break-word;"><td colspan="6" class="cl-94062d28"><p class="cl-940614e6"><span class="cl-94027d4a">NMC</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">Actions</span><span class="cl-94027d4a"> </span><span class="cl-94027d4a">4-5:</span><span class="cl-94027d36"> </span><span class="cl-94027d36">Determine</span><span class="cl-94027d36"> </span><span class="cl-94027d36">if</span><span class="cl-94027d36"> </span><span class="cl-94027d36">any</span><span class="cl-94027d36"> </span><span class="cl-94027d36">entity/source/facility</span><span class="cl-94027d36"> </span><span class="cl-94027d36">specific</span><span class="cl-94027d36"> </span><span class="cl-94027d36">exceedences</span><span class="cl-94027d36"> </span><span class="cl-94027d36">of</span><span class="cl-94027d36"> </span><span class="cl-94027d36">5-yr</span><span class="cl-94027d36"> </span><span class="cl-94027d36">average</span><span class="cl-94027d36"> </span><span class="cl-94027d36">allocation</span><span class="cl-94027d36"> </span><span class="cl-94027d36">occurred</span><span class="cl-94027d36"> </span><span class="cl-94027d36">during</span><span class="cl-94027d36"> </span><span class="cl-94027d36">implementation</span><span class="cl-94027d36"> </span><span class="cl-94027d36">period</span></p></td><td class="cl-94062d33"><p class="cl-940614e6"><span class="cl-94027d36">Not</span><span class="cl-94027d36"> </span><span class="cl-94027d36">necessary</span><span class="cl-94027d36"> </span><span class="cl-94027d36">when</span><span class="cl-94027d36"> </span><span class="cl-94027d36">chlorophyll-</span><span class="cl-94027d4b">a</span><span class="cl-94027d36"> </span><span class="cl-94027d36">threshold</span><span class="cl-94027d36"> </span><span class="cl-94027d36">met</span></p></td></tr></tbody></table></div></code></pre></div>
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diff --git a/reference/show_sedimentpelaveplotly.html b/reference/show_sedimentpelaveplotly.html
index ad95000d..64ddb99d 100644
--- a/reference/show_sedimentpelaveplotly.html
+++ b/reference/show_sedimentpelaveplotly.html
@@ -76,7 +76,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">p</span> <span class="op">&lt;-</span> <span class="fu"><a href="show_sedimentpelave.html">show_sedimentpelave</a></span><span class="op">(</span><span class="va">sedimentdata</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">show_sedimentpelaveplotly</span><span class="op">(</span><span class="va">p</span><span class="op">)</span></span></span>
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     </div>
   </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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diff --git a/reference/show_segplotly.html b/reference/show_segplotly.html
index cc567339..2db4fdb1 100644
--- a/reference/show_segplotly.html
+++ b/reference/show_segplotly.html
@@ -103,7 +103,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">show_segplotly</span><span class="op">(</span><span class="va">epcdata</span><span class="op">)</span></span></span>
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Outcome: 2, Exceedance: large (size), short (length)","type":"scatter","mode":"lines","line":{"width":0.37795275590551186,"color":"rgba(0,0,0,1)","dash":"solid"},"fill":"toself","fillcolor":"rgba(204,50,49,1)","hoveron":"fills","name":"red","legendgroup":"red","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[1974.5,1975.5,1975.5,1974.5,1974.5,null,1975.5,1976.5,1976.5,1975.5,1975.5],"y":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],"text":"Action: Outcome: 3, Exceedance: large (size), NA 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Outcome: 3, Exceedance: large (size), long (length)","type":"scatter","mode":"lines","line":{"width":0.37795275590551186,"color":"rgba(0,0,0,1)","dash":"solid"},"fill":"toself","fillcolor":"rgba(204,50,49,1)","hoveron":"fills","name":"red","legendgroup":"red","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[1987.5,1988.5,1988.5,1987.5,1987.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1996.5,1997.5,1997.5,1996.5,1996.5],"y":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],"text":"Action: Caution (chla: 0, la: 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1975<br />yval: 0.9780952<br />","yr: 1976<br />yval: 1.1759318<br />","yr: 1977<br />yval: 1.1896016<br />","yr: 1978<br />yval: 1.1682173<br />","yr: 1979<br />yval: 1.7595230<br />","yr: 1980<br />yval: 1.3836268<br />","yr: 1981<br />yval: 1.0469025<br />","yr: 1982<br />yval: 1.0583860<br />","yr: 1983<br />yval: 1.1152678<br />","yr: 1984<br />yval: 1.1617502<br />","yr: 1985<br />yval: 0.9534905<br />","yr: 1986<br />yval: 0.8929313<br />","yr: 1987<br />yval: 0.8536198<br />","yr: 1988<br />yval: 0.8558599<br />","yr: 1989<br />yval: 0.9374651<br />","yr: 1990<br />yval: 0.8353229<br />","yr: 1991<br />yval: 0.8031788<br />","yr: 1992<br />yval: 0.8166729<br />","yr: 1993<br />yval: 0.9133746<br />","yr: 1994<br />yval: 0.7481484<br />","yr: 1995<br />yval: 0.9379637<br />","yr: 1996<br />yval: 0.9202700<br />","yr: 1997<br />yval: 0.8473840<br />","yr: 1998<br />yval: 1.0612729<br />","yr: 1999<br />yval: 0.8801655<br />","yr: 2000<br />yval: 0.7328166<br />","yr: 2001<br />yval: 0.9512714<br />","yr: 2002<br />yval: 0.9272802<br />","yr: 2003<br />yval: 1.0370998<br />","yr: 2004<br />yval: 0.8777406<br />","yr: 2005<br />yval: 0.7693579<br />","yr: 2006<br />yval: 0.6204267<br />","yr: 2007<br />yval: 0.6771304<br />","yr: 2008<br />yval: 0.6962244<br />","yr: 2009<br />yval: 0.8076962<br />","yr: 2010<br />yval: 0.8419635<br />","yr: 2011<br />yval: 0.9122183<br />","yr: 2012<br />yval: 0.6867633<br />","yr: 2013<br />yval: 0.5674502<br />","yr: 2014<br />yval: 0.6056886<br />","yr: 2015<br />yval: 0.5604978<br />","yr: 2016<br />yval: 0.5747356<br />","yr: 2017<br />yval: 0.6821210<br />","yr: 2018<br />yval: 0.6780425<br />","yr: 2019<br />yval: 0.7396049<br />","yr: 2020<br />yval: 0.7686231<br />","yr: 2021<br />yval: 0.7783039<br />","yr: 2022<br />yval: 0.7871073<br />","yr: 2023<br />yval: 0.7344259<br />"],"type":"scatter","mode":"markers+lines","marker":{"autocolorscale":false,"color":"rgba(255,0,0,1)","opacity":1,"size":11.338582677165356,"symbol":"circle","line":{"width":1.8897637795275593,"color":"rgba(255,0,0,1)"}},"hoveron":"points","name":"Annual Mean","legendgroup":"Annual Mean","showlegend":false,"xaxis":"x","yaxis":"y3","hoverinfo":"text","line":{"width":2.8346456692913389,"color":"rgba(255,0,0,1)","dash":"solid"},"frame":null},{"x":[1974.51,2023.49],"y":[0.82999999999999996,0.82999999999999996],"text":"trgnum: 0.83<br />colour: Management Target","type":"scatter","mode":"lines","line":{"width":1.8897637795275593,"color":"rgba(0,0,255,1)","dash":"solid"},"hoveron":"points","name":"Management Target","legendgroup":"Management Target","showlegend":false,"xaxis":"x","yaxis":"y3","hoverinfo":"text","frame":null},{"x":[1974.51,2023.49],"y":[0.85999999999999999,0.85999999999999999],"text":"smlnum: 0.86<br />colour: +1 se (small 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diff --git a/reference/show_tbniscrplotly.html b/reference/show_tbniscrplotly.html
index 6646b7c6..cb4391a0 100644
--- a/reference/show_tbniscrplotly.html
+++ b/reference/show_tbniscrplotly.html
@@ -77,7 +77,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span><span class="va">p</span> <span class="op">&lt;-</span> <span class="fu"><a href="show_tbniscrall.html">show_tbniscrall</a></span><span class="op">(</span><span class="va">tbniscr</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">show_tbniscrplotly</span><span class="op">(</span><span class="va">p</span><span class="op">)</span></span></span>
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-<script type="application/json" 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1998<br />TBNI_Score - seval: 48.17495<br />TBNI_Score + seval: 51.82505","Year: 1999<br />TBNI_Score - seval: 46.19234<br />TBNI_Score + seval: 49.80766","Year: 2000<br />TBNI_Score - seval: 44.21787<br />TBNI_Score + seval: 47.78213","Year: 2001<br />TBNI_Score - seval: 44.22901<br />TBNI_Score + seval: 47.77099","Year: 2002<br />TBNI_Score - seval: 43.20437<br />TBNI_Score + seval: 46.79563","Year: 2003<br />TBNI_Score - seval: 44.14857<br />TBNI_Score + seval: 47.85143","Year: 2004<br />TBNI_Score - seval: 46.15258<br />TBNI_Score + seval: 49.84742","Year: 2005<br />TBNI_Score - seval: 35.68311<br />TBNI_Score + seval: 38.31689","Year: 2006<br />TBNI_Score - seval: 40.58473<br />TBNI_Score + seval: 43.41527","Year: 2007<br />TBNI_Score - seval: 41.63263<br />TBNI_Score + seval: 44.36737","Year: 2008<br />TBNI_Score - seval: 41.54982<br />TBNI_Score + seval: 44.45018","Year: 2009<br />TBNI_Score - seval: 43.55717<br />TBNI_Score + seval: 46.44283","Year: 2010<br />TBNI_Score - 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diff --git a/reference/show_tdlcrkindic.html b/reference/show_tdlcrkindic.html
index 309c957e..1736ec13 100644
--- a/reference/show_tdlcrkindic.html
+++ b/reference/show_tdlcrkindic.html
@@ -93,7 +93,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
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 <span class="r-in"><span><span class="fu">show_tdlcrkindic</span><span class="op">(</span><span class="va">id</span>, <span class="va">cntdat</span>, thrsel <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
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diff --git a/search.json b/search.json
index 256331c0..87f691d8 100644
--- a/search.json
+++ b/search.json
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-[{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to tbeptools","title":"Contributing to tbeptools","text":"outlines propose change tbeptools. detailed info contributing , please see development contributing guide.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to tbeptools","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES: edit roxygen comment .R file R/. : edit .Rd file man/.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"Contributing to tbeptools","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"Contributing to tbeptools","text":"recommend create Git branch pull request (PR). Look Travis AppVeyor build status making changes. README contain badges continuous integration services used package. New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to tbeptools","text":"Please note tbeptools project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"see-tidyverse-development-contributing-guide","dir":"","previous_headings":"","what":"See tidyverse development contributing guide","title":"Contributing to tbeptools","text":"details.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/ISSUE_TEMPLATE.html","id":null,"dir":"","previous_headings":"","what":"Issues reporting guide","title":"Issues reporting guide","text":"Please briefly describe problem output expect. question, please don’t use form. Instead, ask https://stackoverflow.com/ https://community.rstudio.com/. Please include minimal reproducible example (AKA reprex). ’ve never heard reprex , start reading https://www.tidyverse.org/help/#reprex. Brief description problem","code":"# insert reprex here"},{"path":"https://tbep-tech.github.io/tbeptools/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 tbeptools authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Fecal Indicator Bacteria","text":"Fecal Indicator Bacteria (FIB) used track concentrations pathogens surface waters may detrimental human health environment. Exposure risk commonly measured select indicators present human gut can enter environment wastewater discharges, stormwater, illicit sources. Common indicators include concentrations E. coli, Enterococcus, Fecal Coliform number colony forming units (CFU) per 100 mL water. Many monitoring programs routinely measure FIB concentrations select locations. tbeptools package several functions importing reporting data. Two workflows available: Functions use data exclusively Environmental Protection Commission (EPC) Hillsborough County Functions use data several monitoring programs baywide reporting focusing exclusively Enterococcus vignette organized around two workflows. , assessments meant inform progress remediating fecal impairments support prioritization areas investigation. meant support beach monitoring efforts closures recreational uses - alternative reporting products available purpose (see FLDOH Healthy Beaches).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"epc-reporting","dir":"Articles","previous_headings":"","what":"EPC reporting","title":"Fecal Indicator Bacteria","text":"Environmental Protection Commission (EPC) Hillsborough County tracking FIB indicators several decades part long-term monitoring. Functions tbeptools can used download EPC FIB data, analyze results, create summary maps plots. sections describes use functions. functions focused reporting Hillsborough River fecal coliform impairment associated Basin Management Action Plan (BMAP). tools can used track long-term changes FIBs basin assess progress reducing fecal coliform levels. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx available direct download viewable . data include observations stations parameters throughout period record. FIB data collected stations additional water quality data collected. dataset used reporting water quality indicators Tampa Bay (see water quality data vignette). functions tbeptools can used import analyze data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read","dir":"Articles","previous_headings":"EPC reporting","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing FIB data read_importfib(). function downloads latest file one already available location specified xlsx input argument. function operates similarly read_importwq() importing water quality data. Please refer water quality data vignette additional details import function. FIB data can downloaded follows: data object called fibdata also provided package, although may contain current data available EPC. View help file download date. fibdata object includes monthly samples FIB data select stations Hillsborough River basin. stations include samples beginning 1972. default output read_importfib() returns stations FIB data EPC. = F read_importfib(), stations AreaName Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta returned. Values returned E. coli (ecoli), Enterococcus (entero), Fecal Coliform (fcolif), Total Coliform (totcol). Units # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Consult source spreadsheet interpretation codes. Concentrations noted < (detection) > (detection) raw data reported detection limit. fibdata object can used remaining FIB functions.","code":"fibdata <- read_importfib('vignettes/current_data.xlsx', download_latest = T) fibdata #> # A tibble: 77,526 × 18 #>    area   epchc_station class SampleTime             yr    mo Latitude Longitude #>    <chr>          <dbl> <chr> <dttm>              <dbl> <dbl>    <dbl>     <dbl> #>  1 Hills…             2 3M    2024-06-10 14:51:00  2024     6     27.9     -82.5 #>  2 Hills…             6 3M    2024-06-17 09:25:00  2024     6     27.9     -82.5 #>  3 Hills…             7 3M    2024-06-17 09:42:00  2024     6     27.9     -82.5 #>  4 Hills…             8 3M    2024-06-17 12:39:00  2024     6     27.9     -82.4 #>  5 Middl…             9 2     2024-06-17 11:47:00  2024     6     27.8     -82.4 #>  6 Middl…            11 2     2024-06-17 10:04:00  2024     6     27.8     -82.5 #>  7 Middl…            13 2     2024-06-17 10:18:00  2024     6     27.8     -82.5 #>  8 Middl…            14 2     2024-06-17 11:14:00  2024     6     27.8     -82.5 #>  9 Middl…            16 2     2024-06-25 09:37:00  2024     6     27.7     -82.5 #> 10 Middl…            19 2     2024-06-25 09:52:00  2024     6     27.7     -82.6 #> # ℹ 77,516 more rows #> # ℹ 10 more variables: Total_Depth_m <dbl>, Sample_Depth_m <dbl>, ecoli <dbl>, #> #   ecoli_q <chr>, entero <dbl>, entero_q <chr>, fcolif <dbl>, fcolif_q <chr>, #> #   totcol <dbl>, totcol_q <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze","dir":"Articles","previous_headings":"EPC reporting","what":"Analyze","title":"Fecal Indicator Bacteria","text":"Several analysis functions provided working EPC data. functions used internally show functions described , presented explanation data processed. anlz_fibmap() function assigns categories observation fibdata selected month year. results mapped using anlz_fibmap() (see ). categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. ranges (number samples / 100 mL) EPC follows E. coli Enterococcus. yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. areasel argument can indicate either \"Alafia\" \"Hillsborough\" select data corresponding river basins, rows fibdata filtered based selection. stations returned argument NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdata \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection yrsel mosel. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". anlz_fibmatrix() function creates summary FIB categories station year output show_fibmatrix() function described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood fecal coliform concentrations exceed 400 CFU / 100 mL. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat). indic argument must set explicitly 'fcolif' indicate indicator fecal coliform EPC data.","code":"anlz_fibmap(fibdata) #> # A tibble: 77,526 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 77,516 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmap(fibdata, yrsel = 2023, mosel = 7) #> # A tibble: 207 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2023     7     27.9     -82.5    NA    800 Ente… 130 … #>  2 Hillsb…       6 3M     2023     7     27.9     -82.5    NA      2 Ente… < 35  #>  3 Hillsb…       7 3M     2023     7     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2023     7     27.9     -82.4    NA      2 Ente… < 35  #>  5 Middle…       9 2      2023     7     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2023     7     27.7     -82.5    NA      2 Ente… < 35  #> 10 Middle…      19 2      2023     7     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 197 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 47 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2023     7     27.9     -82.5    NA    800 Ente… 130 … #>  2 Hillsb…     105 3M     2023     7     28.0     -82.4    NA    128 Ente… 35 -… #>  3 Hillsb…     106 1      2023     7     28.1     -82.4   144    232 E. c… 126 … #>  4 Lake T…     107 3F     2023     7     28.0     -82.3   570   1550 E. c… 410 … #>  5 Hillsb…     108 3F     2023     7     28.1     -82.2   187    276 E. c… 126 … #>  6 Lake T…     118 3F     2023     7     28.1     -82.3     4      7 E. c… < 126 #>  7 Hillsb…     120 3F     2023     7     28.1     -82.4   100    410 E. c… < 126 #>  8 Lake T…     135 3F     2023     7     28.1     -82.3     4      4 E. c… < 126 #>  9 Hillsb…     137 3M     2023     7     28.0     -82.5    NA    680 Ente… 130 … #> 10 Hillsb…     143 3F     2023     7     28.1     -82.1   800   1333 E. c… 410 … #> # ℹ 37 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmatrix(fibdata, indic = 'fcolif') #> # A tibble: 459 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1974 143     NA      NA        NA   NA    #>  2  1974 108    247.     28.1     -82.2 NA    #>  3  1974 107    269.     28.0     -82.3 NA    #>  4  1974 135     NA      NA        NA   NA    #>  5  1974 118    136.     28.1     -82.3 NA    #>  6  1974 148     NA      NA        NA   NA    #>  7  1974 105    258.     28.0     -82.4 NA    #>  8  1974 152     NA      NA        NA   NA    #>  9  1974 137     NA      NA        NA   NA    #> 10  1975 143     NA      NA        NA   NA    #> # ℹ 449 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show","dir":"Articles","previous_headings":"EPC reporting","what":"Show","title":"Fecal Indicator Bacteria","text":"show_fibmap() function creates map FIB sites thresholds based output anlz_fibmap(). arguments apply anlz_fibmap() also apply show_fibmap() freshwater marine stations categorized relevant thresholds plotted selected year, month, area. Unlike anlz_fibmap(), yrsel mosel arguments required. Sites Hillsborough Alafia river basins can shown using areasel argument. Additional information site can seen placing cursor location. map inset can also seen clicking arrow bottom left map. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data [1]. matrix colors based likelihood fecal indicator bacteria concentrations exceed 400 CFU / 100 mL (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1].  default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year.  default stations used TBEP report #05-13 [3] Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument.  yrrng argument can also used select year range, default 1985 current year data fibdata.  preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) object can returned setting plotly argument TRUE. Finally, map station categories given year can plotted using show_fibmatrixmap(). yrsel argument required, areasel argument can used select specific area. values shown map respective year show_fibmatrix() function.","code":"show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Alafia River') show_fibmatrix(fibdata) show_fibmatrix(fibdata, lagyr = 1) show_fibmatrix(fibdata, stas = c(115, 116)) show_fibmatrix(fibdata, yrrng = c(1990, 2020)) show_fibmatrix(fibdata, asreact = TRUE) show_fibmatrix(fibdata, plotly = TRUE) show_fibmatmap(fibdata, indic = 'fcolif', yrsel = 2020, areasel = c('Hillsborough River', 'Alafia River'))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"manatee-county-reporting","dir":"Articles","previous_headings":"","what":"Manatee County reporting","title":"Fecal Indicator Bacteria","text":"FIB data Manatee County Natural Resources Department can also used functions. data can downloaded follows: convenience, data object name included tbeptools use FIB functions. Note read_importwqp() can used download FIB data organizations, although FIB functions work data Manatee County. Similar workflows EPCHC data can used. Examples functions using Manatee County data:","code":"mancofibdata <- read_importwqp('21FLMANA_WQX', type = 'fib') show_fibmap(mancofibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmatrix(mancofibdata, plotly = TRUE) show_fibmatmap(mancofibdata, yrsel = 2020, indic = 'fcolif', areasel = 'Lower Manatee River')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"baywide-reporting","dir":"Articles","previous_headings":"","what":"Baywide reporting","title":"Fecal Indicator Bacteria","text":"second workflow uses baywide approach summarize FIB data. Select stations identified downstream locations drain Tampa Bay considered important watershed endpoints FIB monitoring. Enterococcus primary indicator stations located terminal downstream locations tidally influenced. functions organized similarly EPC reporting workflow, unique functions working data locations functions repeated EPC workflow differ output depending data inputs.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing Enterococcus data read_importentero(). function retrieves data USEPA water quality portal using API. three arguments stas, startDate, endDate. stas argument can left NULL (default) retrieve data stations based catchprecip data object, described . startDate endDate arguments specify date ranges retrieving data, input format character string 'YYYY-MM-DD'. data request can take time enterodata data object provided package use downstream functions. dataset includes data 53 selected stations 1995-2023. downstream functions also require precipitation data obtained using read_importrain() function. function downloads daily precipitation data Southwest Florida Water Management District (SWFWMD) rainfall FTP website. station, daily cumulative rainfall summarized upstream catchment, catchments site defined pixel locations used describe SWFWMD rainfall data. information available catchpixels data object. Rainfall data downloaded defining years months interest. enterodata data object, catchprecip object provided package use downstream functions. dataset includes daily rainfall data (inches) 53 selected stations 1995-2023. rainfall data used define Enterococcus samples “wet” “dry” based default user-defined thresholds described .","code":"read_importentero(startDate = '1995-01-01', endDate = '2023-12-31') head(enterodata) #>            date   yr mo time time_zone     long_name bay_segment #> 1901 2001-01-16 2001  1                Old Tampa Bay         OTB #> 1902 2001-02-20 2001  2                Old Tampa Bay         OTB #> 1903 2001-03-20 2001  3                Old Tampa Bay         OTB #> 1904 2001-04-17 2001  4                Old Tampa Bay         OTB #> 1905 2001-05-15 2001  5                Old Tampa Bay         OTB #> 1906 2001-06-19 2001  6                Old Tampa Bay         OTB #>               station entero entero_censored MDL entero_units qualifier #> 1901 21FLHILL_WQX-101     80           FALSE  NA      #/100mL        NA #> 1902 21FLHILL_WQX-101    360           FALSE  NA      #/100mL        NA #> 1903 21FLHILL_WQX-101   3900           FALSE  NA      #/100mL        NA #> 1904 21FLHILL_WQX-101     20           FALSE  NA      #/100mL        NA #> 1905 21FLHILL_WQX-101     NA           FALSE  20                     NA #> 1906 21FLHILL_WQX-101     NA           FALSE  20                     NA #>      LabComments Latitude Longitude #> 1901          NA  28.0248  -82.6316 #> 1902          NA  28.0248  -82.6316 #> 1903          NA  28.0248  -82.6316 #> 1904          NA  28.0248  -82.6316 #> 1905          NA  28.0248  -82.6316 #> 1906          NA  28.0248  -82.6316 read_importrain(2021, catchpixels, mos = 1:12, quiet = F) head(catchprecip) #> # A tibble: 6 × 3 #>   station            date        rain #>   <chr>              <date>     <dbl> #> 1 21FLCOSP_WQX-32-03 1995-01-01 0     #> 2 21FLCOSP_WQX-32-03 1995-01-02 0     #> 3 21FLCOSP_WQX-32-03 1995-01-03 0     #> 4 21FLCOSP_WQX-32-03 1995-01-04 0.389 #> 5 21FLCOSP_WQX-32-03 1995-01-05 0     #> 6 21FLCOSP_WQX-32-03 1995-01-06 0.106"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Analyze","title":"Fecal Indicator Bacteria","text":"Several analysis functions provided working Enterococcus data. functions used internally show functions described , presented explanation data processed. function uses Enterococcus precipitation data provided enterodata catchprecip data objects. latter dataset used define “wet” “dry” samples premise Enterococcus concentrations higher wet weather may useful distinguish samples assess progress achieving water quality restoration goals, .e., rainfall may confound assessment management efforts reduce fecal contamination. anlz function optional arguments define temporal_window wet_threshold defining “wet” “dry” samples, passed anlz_fibwetdry() function. arguments define period time preceding sample date cumulative rainfall threshold within time period must met define sample “wet”. arguments default two days half inch, samples defined “wet” greater half inch cumulative rainfall two days preceding including sample date. time rainfall thresholds can changed user. Additionally, anlz functions can also treat samples equally ignoring rainfall data setting wetdry = FALSE, default behavior. anlz_fibwetdry() function defines “wet” “dry” samples described returns original input dataset three additional columns describing total rain (inches) day sampling (rain_sampleDay), total rain period defined temporal_window argument (rain_total), whether sample “wet” logical value (wet_sample). remaining anlz functions anlz_enteromap() prepare data mapping anlz_fibmatrix() prepare data score card. can optionally use anlz_fibwetdry() plot “wet” “dry” samples, described show section. anlz_enteromap() function Enterococcus-specific analogue anlz_fibmap() fecal coliform function described EPC section . function assigns categories observation Enterococcus data frame, can viewed given month year using show_enteromap() (analagous show_fibmap()). categories specific Enterococcus marine waters, noted cat column output. Corresponding colors col column output. ranges (number samples / 100 mL) EPC follows Enterococcus: yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. wetdry argument can used determine whether sample taken rain event (logical wet_sample column output), based user-specified thresholds provided precipitation data object (catchprecip). shows identify wet samples based least 0.5 inches rain occurring two days prior including sample date. areasel argument can indicate one major subwatersheds Tampa Bay (excluding Terra Ceia Bay data exist). example, use Old Tampa Bay stations subwatershed Old Tampa Bay, rows enterodata filtered based selection. stations returned argument set NULL (default). valid options areasel include \"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay\", \"Manatee River\". anlz_fibmatrix() function used show_fibmatrix() function used similarly EPC workflow described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood Enterococcus concentrations exceed 130 CFU / 100 mL. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat). indic argument must set explicitly 'entero' select indicator Enterococcus.","code":"anlz_fibwetdry(enterodata, catchprecip, temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 6,266 × 19 #>    date          yr    mo time  time_zone long_name   bay_segment station entero #>    <date>     <dbl> <dbl> <chr> <chr>     <chr>       <chr>       <chr>    <dbl> #>  1 2001-01-16  2001     1 \"\"    \"\"        Old Tampa … OTB         21FLHI…     80 #>  2 2001-02-20  2001     2 \"\"    \"\"        Old Tampa … OTB         21FLHI…    360 #>  3 2001-03-20  2001     3 \"\"    \"\"        Old Tampa … OTB         21FLHI…   3900 #>  4 2001-04-17  2001     4 \"\"    \"\"        Old Tampa … OTB         21FLHI…     20 #>  5 2001-05-15  2001     5 \"\"    \"\"        Old Tampa … OTB         21FLHI…     NA #>  6 2001-06-19  2001     6 \"\"    \"\"        Old Tampa … OTB         21FLHI…     NA #>  7 2001-07-24  2001     7 \"\"    \"\"        Old Tampa … OTB         21FLHI…   1300 #>  8 2001-08-21  2001     8 \"\"    \"\"        Old Tampa … OTB         21FLHI…    260 #>  9 2001-09-18  2001     9 \"\"    \"\"        Old Tampa … OTB         21FLHI…    420 #> 10 2001-10-16  2001    10 \"\"    \"\"        Old Tampa … OTB         21FLHI…    520 #> # ℹ 6,256 more rows #> # ℹ 10 more variables: entero_censored <lgl>, MDL <int>, entero_units <chr>, #> #   qualifier <lgl>, LabComments <lgl>, Latitude <dbl>, Longitude <dbl>, #> #   rain_sampleDay <dbl>, rain_total <dbl>, wet_sample <lgl> anlz_enteromap(enterodata) #> # A tibble: 6,266 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     5     28.0     -82.6     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2001     6     28.0     -82.6     NA NA    NA    Ente… #>  7 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  8 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #> # ℹ 6,256 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_enteromap(enterodata, yrsel = 2020, mosel = 8) #> # A tibble: 27 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6    220 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     40 35 -… #E9C… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     70 35 -… #E9C… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     50 35 -… #E9C… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     8     27.9     -82.7     20 < 35  #2DC… Ente… #>  6 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4      8 < 35  #2DC… Ente… #>  7 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4   1200 > 999 #CC3… Ente… #>  8 21FLHILL_W… Hillsbor…  2020     8     27.8     -82.4    520 130 … #EE7… Ente… #>  9 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.5    190 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4     90 35 -… #E9C… Ente… #> # ℹ 17 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_enteromap(enterodata, wetdry = TRUE, precipdata = catchprecip,                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 6,266 × 13 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     5     28.0     -82.6     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2001     6     28.0     -82.6     NA NA    NA    Ente… #>  7 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  8 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #> # ℹ 6,256 more rows #> # ℹ 3 more variables: indnm <chr>, conc <dbl>, wet_sample <lgl> anlz_enteromap(enterodata, yrsel = 2023, mosel = 7, areasel = 'Old Tampa Bay') #> # A tibble: 12 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6      5 < 35  #2DC… Ente… #>  2 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6     30 < 35  #2DC… Ente… #>  3 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6     70 35 -… #E9C… Ente… #>  4 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6    220 130 … #EE7… Ente… #>  5 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.5     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6    467 130 … #EE7… Ente… #>  7 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6   3900 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2023     7     28.0     -82.7    798 130 … #EE7… Ente… #>  9 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7    457 130 … #EE7… Ente… #> 10 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7   1860 > 999 #CC3… Ente… #> 11 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7     75 35 -… #E9C… Ente… #> 12 21FLTPA_WQ… Old Tamp…  2023     7     28.0     -82.7   2613 > 999 #CC3… Ente… #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_fibmatrix(enterodata, indic = 'entero') #> # A tibble: 1,200 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 NA    #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Show","title":"Fecal Indicator Bacteria","text":"show_enteromap() function creates map Enterococcus sites thresholds based output anlz_enteromap(). arguments apply anlz_enteromap() also apply show_enteromap(), including classification samples ‘wet’ depending specified thresholds. Wet dry samples differentiated map shapes. Unlike anlz_enteromap(), yrsel mosel arguments required. Additional information site can seen placing cursor location. map inset can also seen clicking arrow bottom left map. Sites specific areas can shown using areasel argument. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data. function primarily designed fecal coliform data, adapted work Enterococcus data. matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 130 CFU / 100 mL Enterococcus (entero fibdata enterodata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1]. stations shown default.  default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year.  Individual stations can selectd using stas argument.  yrrng argument can also used select year range, default date range contained data.  Note subset_wetdry argument can used show_fibmatrix() show wet dry samples based thresholds provided temporal_window wet_threshold. However, recommended scores probability-based comparisons wet dry samples may misleading due different sample sizes, therefore, power detect likelihood exceeding threshold. Specifically, far fewer wet samples dry samples generally receive higher grades due lower power statistical tests. EPC data, HTML table can returned show_fibmatrix() using asreact = TRUE plotly object can returned using plotly = TRUE. See section examples outputs. show_fibmatrix() function also supports baywide reporting bay segment, unlike EPC data. stations baywide reporting selected specifically endpoints drain directly bay segment aggregate summary stations bay segment can indicate MWQA category. calculations station, data aggregated bay segment.  Finally, map station bay segment categories given year can plotted using show_fibmatrixmap(). yrsel argument required, areasel argument can used select specific area. values shown map respective year show_fibmatrix() function.","code":"show_enteromap(enterodata, yrsel = 2020, mosel = 9) show_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5) show_enteromap(enterodata, yrsel = 2023, mosel = 7, areasel = 'Old Tampa Bay') show_fibmatrix(enterodata, indic = 'entero') show_fibmatrix(enterodata, indic = 'entero', lagyr = 1) show_fibmatrix(enterodata,                indic = 'entero',                stas = c('21FLHILL_WQX-101', '21FLHILL_WQX-102', '21FLHILL_WQX-103')) show_fibmatrix(enterodata, indic = 'entero', yrrng = c(2015, 2020)) show_fibmatrix(enterodata, indic = 'entero', bay_segment = c('OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR')) show_fibmatmap(enterodata, indic = 'entero', yrsel = 2020, areasel = c('OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR'))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"retrieving-additional-fib-data","dir":"Articles","previous_headings":"","what":"Retrieving additional FIB data","title":"Fecal Indicator Bacteria","text":"read_importwqp() function can used retrieve data USEPA Water Quality Portal using organization identifier. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'fib', trace = T)  # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Habitat Master Plan","text":"Dashboard: https://shiny.tbep.org/landuse-change/ habitats Tampa Bay provide food, shelter, important services support birds, fish, mammals, invertebrates. Significant habitat alteration loss occurred development activities. address challenges, Habitat Master Plan (2020 Update) [1] provides set targets goals , achieved, provide healthy balanced coverage native habitats Tampa Bay watershed. update builds previous Habitat Master Plan [2] several ways. target goal setting approach informed past changes forty years habitat restoration experience region. approach also identifies possible today rather replicating past ecological conditions accounts potential future effects sea-level rise, climate change, development. Habitat Master Plan defines 10-year (2030) habitat protection restoration targets 30-year (2050) goals. Maps habitat protection restoration opportunity areas targets goals can attained additional products available new plan. Please visit https://tbep.org/habitat-master-plan-update/ additional information.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"datasets","dir":"Articles","previous_headings":"","what":"Datasets","title":"Habitat Master Plan","text":"Three internal datasets tbeptools provide necessary information create Habitat Master Plan report card. Summary annual acreage estimates major habitat type intertidal supratidal strata. Summary annual acreage estimates major habitat type subtidal stratam. table targets goals major habitat type, developed Habitat Master Plan 2020 update [1] (select columns shown). datasets created repository https://github.com/tbep-tech/hmpu-workflow require updates land use cover datasets produced every two three years Southwest Florida Water Management District.","code":"acres #> # A tibble: 90 × 3 #> # Groups:   name [9] #>    name  HMPU_TARGETS                       Acres #>    <chr> <chr>                              <dbl> #>  1 1990  Coastal Uplands                    5078. #>  2 1990  Developed                        372438. #>  3 1990  Forested Freshwater Wetlands     159561. #>  4 1990  Mangrove Forests                  13522. #>  5 1990  Native Uplands                   229990. #>  6 1990  Non-Forested Freshwater Wetlands  54454. #>  7 1990  Open Water                        38357. #>  8 1990  Restorable                       571513. #>  9 1990  Salt Barrens                        468  #> 10 1990  Salt Marshes                       4482. #> # ℹ 80 more rows subtacres #> # A tibble: 65 × 3 #>    name  HMPU_TARGETS    Acres #>    <chr> <chr>           <dbl> #>  1 1988  Open Water   197802.  #>  2 1988  Restorable       72.9 #>  3 1988  Seagrasses    23279.  #>  4 1988  Tidal Flats   21686.  #>  5 1990  Open Water   197058.  #>  6 1990  Restorable       67.0 #>  7 1990  Seagrasses    25218.  #>  8 1990  Tidal Flats   20433.  #>  9 1992  Open Water   195908.  #> 10 1992  Restorable       86.0 #> # ℹ 55 more rows hmptrgs[, c(\"Category\", \"HMPU_TARGETS\", \"Target2030\", \"Goal2050\")] #>      Category                     HMPU_TARGETS Target2030 Goal2050 #> 1    Subtidal                      Hard Bottom      423.0    423.0 #> 2    Subtidal                 Artificial Reefs      166.0    166.0 #> 3    Subtidal                      Tidal Flats    16220.0  16220.0 #> 4    Subtidal                       Seagrasses    40000.0  40000.0 #> 5    Subtidal                      Oyster Bars      221.0    471.0 #> 6  Intertidal                Living Shorelines       21.3     56.3 #> 7  Intertidal                 Total Intertidal    21353.0  23803.0 #> 8  Intertidal                 Mangrove Forests    15300.0  15300.0 #> 9  Intertidal                     Salt Barrens      546.0    796.0 #> 10 Intertidal                     Salt Marshes     4807.0   5457.0 #> 11 Intertidal                Tidal Tributaries        4.0     18.0 #> 12 Supratidal                  Coastal Uplands     3769.0   4219.0 #> 13 Supratidal Non-Forested Freshwater Wetlands    68937.0  71787.0 #> 14 Supratidal     Forested Freshwater Wetlands   152282.0 152732.0 #> 15 Supratidal                   Native Uplands   141050.0 142100.0"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-summary","dir":"Articles","previous_headings":"","what":"Report card summary","title":"Habitat Master Plan","text":"important reporting product Habitat Master Plan report card summarizes attainment targets goals evaluates prior trends identify coverages trending targets goals. Two functions provided tbeptools create report card. anlz_hmpreport() summarizes datasets provide necessary information creating report card. show_hmpreport() generates plot report card. latter can used former provided need view data behind report card. Using anlz_hmpreport() function summarizes acreage coverage estimates habitat type, compares targets goals year data, assesses coverage trend year pairs determine changes trending targets goals. columns follows: year: Year assessment metric: Habitat type assessed Acres: Coverage estimate year lacres: Coverage estimate previous set available data lyr: Year previous set available data category: Strata habitat type Target: 2030 target habitat type Habitat Master Plan Goal: 2050 goal habitat type Habitat Master Plan acresdiff: Difference acres current year previous set available data yeardiff: Difference years current year previous set available data changerate: Acreage change per year current year relative previous set available data targetrate: Annual rate required achieve 2030 target goalrate: Annual rate required achieve 2050 goal targetprop: Proportion target met current year goalprop: Proportion goal met current year targeteval: number indicating target status current year report card goaleval: number indicating goal status current year report card important columns output targetprop, goalprop, targeteval, goaleval. targetprop goalprop columns indicate proportion target goal met habitat type current assessment year. targeteval goaleval columns one four values, -1, 0, 0.5, 1, habitat type year. numbers define habitat status assessment year: -1: target goal met, trending 0: target goal met, trending 0.5: target goal met, trending 1: target goal met, trending ","code":"anlz_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs) #> # A tibble: 150 × 17 #>     year metric      Acres lacres   lyr category Target  Goal acresdiff yeardiff #>    <dbl> <chr>       <dbl>  <dbl> <dbl> <fct>     <dbl> <dbl>     <dbl>    <dbl> #>  1  1990 Seagrasses 25218. 23279.  1988 Subtidal  40000 40000     1939.        2 #>  2  1990 Tidal Fla… 20433. 21686.  1988 Subtidal  16220 16220    -1253.        2 #>  3  1992 Seagrasses 25746. 25218.  1990 Subtidal  40000 40000      528.        2 #>  4  1992 Tidal Fla… 20594. 20433.  1990 Subtidal  16220 16220      161.        2 #>  5  1994 Seagrasses 26524. 25746.  1992 Subtidal  40000 40000      778.        2 #>  6  1994 Tidal Fla… 20244. 20594.  1992 Subtidal  16220 16220     -349.        2 #>  7  1996 Seagrasses 26924. 26524.  1994 Subtidal  40000 40000      400.        2 #>  8  1996 Tidal Fla… 20443. 20244.  1994 Subtidal  16220 16220      199.        2 #>  9  1999 Seagrasses 24840. 26924.  1996 Subtidal  40000 40000    -2083.        3 #> 10  1999 Tidal Fla… 27085. 20443.  1996 Subtidal  16220 16220     6642.        3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate <dbl>, targetrate <dbl>, goalrate <dbl>, #> #   targetprop <dbl>, goalprop <dbl>, targeteval <dbl>, goaleval <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-plot","dir":"Articles","previous_headings":"","what":"Report card plot","title":"Habitat Master Plan","text":"show_hmpreport() can used create Habitat Master Plan report card. anlz_hmpreport() function used internally need used separately. input files . plot shows report card 2030 targets, using typ = \"targets\". colors cell correspond numbers targeteval column (goaleval typ = \"goals\") returned anlz_hmpreport(). numbers cell indicate proportion target targetprop (goal goalprop typ = \"goals\") met habitat type assessment year. Note creation datasets generate summaries continuous year varies subtidal inter/supratidal habitat.  2050 goals report card can shown using typ = \"goals\".  subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data.  Different strata can also selected using strata argument. Note use ycollapse = T remove years without data.  strata can combined single plot collapsed years using patchwork library.  text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5).  alternative form report card can returned attainment targets goals likelihood attainment shown differently using colors shapes, respectively. plotted using twocol = T, red shows target goal met, green shows target goal met, arrow shows target goal likely met, arrow shows target goal likely met.  report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan.","code":"show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'goals') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', ycollapse = T) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = c('Intertidal', 'Supratidal'), ycollapse = T) library(patchwork) library(ggplot2)   p1 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = 'Subtidal', ycollapse = T) p2 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = c('Intertidal', 'Supratidal'), ycollapse = T) + labs(title = NULL)  p1 + p2 + plot_layout(ncol = 2, guides = 'collect') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', text = NULL) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', twocol = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Water Quality Data","text":"Dashboard: https://shiny.tbep.org/wq-dash vignette provides overview functions tbeptools can used work water quality data Tampa Bay. View vignettes topical introductions reporting products (e.g., seagrasess, tidal creeks, etc.). environmental recovery Tampa Bay exceptional success story coastal water quality management. Nitrogen loads mid 1970s estimated 8.2 million kg/yr, approximately 5.5 million kg/yr entering upper Bay alone [2]. Reduced water clarity associated phytoplankton biomass contributed dramatic reduction areal coverage seagrass [3] development hypoxic events, causing decline benthic faunal production [4]. Extensive efforts reduce nutrient loads Bay occurred late 1970s, notable improvements infrastructure wastewater treatment 1979. Improvements water clarity decreases chlorophyll concentrations observed Bay-wide 1980s, conditions generally remaining constant present day [5]. Tracking changes environmental condition past present day possible without long-term monitoring dataset. Data collected monthly Environmental Protection Commission Hillsborough County since 1974 [6,7]. Samples taken forty-five stations water collection monitoring sonde bottom, mid- surface depths, depending parameter. locations monitoring stations fixed cover entire Bay uppermost mesohaline sections lowermost euhaline portions direct interaction Gulf Mexico. 515 observations available different parameters station, e.g., nitrogen, chlorophyll-, secchi depth. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. date, systematic tools importing, analyzing, reporting information data. tbeptools package provides developed address need. Locations long-term monitoring stations Tampa Bay. Bay separated four segments defined chemical, physical, geopolitical boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Water Quality Data","text":"main function importing water quality data read_importwq(). function downloads latest file one already available location specified xlsx input argument. First, create character path location file. one exist, specify desired location name downloaded file. , want put file vignettes folder name current_results.xls. Note file path relative root working directly current R session. can view working directory getwd(). Now pass xlsx object read_importwq() function. get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get message, indication file server downloaded. ’ll data downloaded saved epcdata object finishes downloading. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work monitoring data, read_importwq() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: argument na indicates fields downloaded spreadsheet treated blank values assigned NA. number strings can added function replace fields NA values. data successfully imported, can view assigned object: data include bay segment name, station number, sample time, year, month, latitude, longitude, station depth, sample depth, total nitrogen, secchi depth, chlorophyll, salinity, water temperature, turbidity, water color. parameters can included setting = TRUE read_importwq(). import function also available download format phytoplankton cell count data. read_importphyto() function works similarly import function water quality data. Start specifying path data downloaded set download_latest TRUE. function download summarize data file PlanktonDataList_ThroughCurrentReportMonth.xlsx EPC website. phytoplankton data successfully imported, can view assigned object: data highly summarized raw data file available online. Cell counts (number cells per 0.1mL) selected taxa summed station quarters (.e., Jan/Feb/Mar, Apr/May/Jun, etc.). quarter indicated yrqrt column specified starting date quarter (e.g., 1975-07-01 quarter Jul/Aug/Sep 1975). data primarily used support analyses water quality dashboard: https://shiny.tbep.org/wq-dash/","code":"xlsx <- 'vignettes/current_results.xlsx' epcdata <- read_importwq(xlsx) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File vignettes/current_results.xlsx does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1'  length 24562051 bytes (23.4 MB) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File is current... #> Replacing local file with current... epcdata #> # A tibble: 27,961 × 26 #>    bay_segment epchc_station SampleTime             yr    mo Latitude Longitude #>    <chr>               <dbl> <dttm>              <dbl> <dbl>    <dbl>     <dbl> #>  1 HB                      6 2023-12-19 10:01:00  2023    12     27.9     -82.5 #>  2 HB                      7 2023-12-19 10:12:00  2023    12     27.9     -82.5 #>  3 HB                      8 2023-12-19 12:39:00  2023    12     27.9     -82.4 #>  4 MTB                     9 2023-12-19 11:54:00  2023    12     27.8     -82.4 #>  5 MTB                    11 2023-12-19 10:25:00  2023    12     27.8     -82.5 #>  6 MTB                    13 2023-12-19 10:38:00  2023    12     27.8     -82.5 #>  7 MTB                    14 2023-12-19 11:24:00  2023    12     27.8     -82.5 #>  8 MTB                    16 2023-12-20 09:35:00  2023    12     27.7     -82.5 #>  9 MTB                    19 2023-12-20 09:49:00  2023    12     27.7     -82.6 #> 10 LTB                    23 2023-12-20 13:16:00  2023    12     27.7     -82.6 #> # ℹ 27,951 more rows #> # ℹ 19 more variables: Total_Depth_m <dbl>, Sample_Depth_m <dbl>, tn <dbl>, #> #   tn_q <chr>, sd_m <dbl>, sd_raw_m <dbl>, sd_q <chr>, chla <dbl>, #> #   chla_q <chr>, Sal_Top_ppth <dbl>, Sal_Mid_ppth <dbl>, #> #   Sal_Bottom_ppth <dbl>, Temp_Water_Top_degC <dbl>, #> #   Temp_Water_Mid_degC <dbl>, Temp_Water_Bottom_degC <dbl>, #> #   `Turbidity_JTU-NTU` <chr>, Turbidity_Q <chr>, Color_345_F45_PCU <chr>, … xlsx <- 'phyto_data.xlsx' phytodata <- read_importphyto(xlsx, download_latest = T) #> File vignettes/phyto_data.xlsx does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1'  length 12319508 bytes (11.7 MB) phytodata #> # A tibble: 21,143 × 8 #>    epchc_station Date       name           units  count yrqrt         yr mo    #>    <chr>         <date>     <chr>          <chr>  <dbl> <date>     <dbl> <ord> #>  1 11            1975-07-23 other          /0.1mL     0 1975-07-01  1975 Jul   #>  2 11            1976-01-07 other          /0.1mL     1 1976-01-01  1976 Jan   #>  3 11            1977-01-05 other          /0.1mL     1 1977-01-01  1977 Jan   #>  4 11            1977-04-20 Tripos hircus  /0.1mL     1 1977-04-01  1977 Apr   #>  5 11            1977-04-20 other          /0.1mL     1 1977-04-01  1977 Apr   #>  6 11            1977-07-13 other          /0.1mL    12 1977-07-01  1977 Jul   #>  7 11            1978-01-11 other          /0.1mL    16 1978-01-01  1978 Jan   #>  8 11            1979-02-08 other          /0.1mL     1 1979-01-01  1979 Feb   #>  9 11            1979-05-02 Karenia brevis /0.1mL     1 1979-04-01  1979 May   #> 10 11            1979-05-30 other          /0.1mL     1 1979-04-01  1979 May   #> # ℹ 21,133 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"retrieving-additional-water-quality-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional water quality data","title":"Water Quality Data","text":"water quality functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description water quality. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored organization type = 'wq'. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T)  # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'wq', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Water Quality Data","text":"functions anlz_avedat() anlz_avedatsite() summarize station data bay segments sites, respectively. functions return annual means chlorophyll light attenuation (based Secchi depth measurements) monthly means year chlorophyll light attenuation. summaries used determine bay segment targets water quality met using anlz_attain() anlz_attainsite() function. use anlz_avedat() summarize data bay segment estimate annual monthly means chlorophyll light attenuation. output two-element list annual (ann) monthly (mos) means segment. output can analyzed anlz_attain() determine bay segment outcomes met year. results used plotting functions described . short, chl_la column indicates categorical outcome chlorophyll light attenuation segment. outcomes integer values zero three. relative exceedances water quality thresholds segment, duration magnitude, indicated higher integer values. Similar information can obtained individual sites using anlz_avedatsite() anlz_attainsite(). main difference yes/column metis added indicates target segment threshold site.","code":"avedat <- anlz_avedat(epcdata) avedat #> $ann #> # A tibble: 608 × 4 #>       yr bay_segment var         val #>    <dbl> <chr>       <chr>     <dbl> #>  1  1974 HB          mean_chla 22.4  #>  2  1974 LTB         mean_chla  4.24 #>  3  1974 MTB         mean_chla  9.66 #>  4  1974 OTB         mean_chla 10.2  #>  5  1975 HB          mean_chla 27.9  #>  6  1975 LTB         mean_chla  4.93 #>  7  1975 MTB         mean_chla 11.4  #>  8  1975 OTB         mean_chla 13.2  #>  9  1976 HB          mean_chla 29.5  #> 10  1976 LTB         mean_chla  5.08 #> # ℹ 598 more rows #>  #> $mos #> # A tibble: 4,724 × 5 #>    bay_segment    yr    mo var         val #>    <chr>       <dbl> <dbl> <chr>     <dbl> #>  1 HB           1974     1 mean_chla 36.2  #>  2 LTB          1974     1 mean_chla  1.75 #>  3 MTB          1974     1 mean_chla 11.5  #>  4 OTB          1974     1 mean_chla  4.4  #>  5 HB           1974     2 mean_chla 42.4  #>  6 LTB          1974     2 mean_chla  5.5  #>  7 MTB          1974     2 mean_chla  9.35 #>  8 OTB          1974     2 mean_chla  4.07 #>  9 HB           1974     3 mean_chla 14.9  #> 10 LTB          1974     3 mean_chla  5.88 #> # ℹ 4,714 more rows anlz_attain(avedat) #> # A tibble: 200 × 4 #>    bay_segment    yr chl_la outcome #>    <chr>       <dbl> <chr>  <chr>   #>  1 HB           1974 3_0    yellow  #>  2 HB           1975 3_2    red     #>  3 HB           1976 3_2    red     #>  4 HB           1977 3_2    red     #>  5 HB           1978 3_3    red     #>  6 HB           1979 3_3    red     #>  7 HB           1980 3_3    red     #>  8 HB           1981 3_3    red     #>  9 HB           1982 3_3    red     #> 10 HB           1983 3_0    yellow  #> # ℹ 190 more rows anlz_avedatsite(epcdata) %>% anlz_attainsite #> # A tibble: 2,250 × 9 #>       yr bay_segment epchc_station var     val target smallex thresh met   #>    <dbl> <chr>               <dbl> <chr> <dbl>  <dbl>   <dbl>  <dbl> <chr> #>  1  1974 HB                      6 chla   25.6   13.2    14.1     15 no    #>  2  1974 HB                      7 chla   21.6   13.2    14.1     15 no    #>  3  1974 HB                      8 chla   22.6   13.2    14.1     15 no    #>  4  1974 HB                     44 chla   23.4   13.2    14.1     15 no    #>  5  1974 HB                     52 chla   23.5   13.2    14.1     15 no    #>  6  1974 HB                     55 chla   20.2   13.2    14.1     15 no    #>  7  1974 HB                     70 chla   33.1   13.2    14.1     15 no    #>  8  1974 HB                     71 chla   25.8   13.2    14.1     15 no    #>  9  1974 HB                     73 chla   17.6   13.2    14.1     15 no    #> 10  1974 HB                     80 chla   10.5   13.2    14.1     15 yes   #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Water Quality Data","text":"External package libraries R can used plot time series data. ’s example using popular ggplot2 package. data wrangling dplyr done first filter data want plot.  show_thrplot() function provides descriptive assessment annual trends chosen bay segment relative defined targets thresholds. plot show annual averages across stations Old Tampa bay (bay_segment = \"OTB\") chlorophyll (thr = \"chla\"). red line shows annual trends horizontal blue lines indicate thresholds targets chlorophyll-specific Old Tampa Bay. dashed dotted blue lines indicate +1 +2 standard errors management target shown filled line. target standard errors considered identifying annual segment outcome chlorophyll.  can show plot light attenuation changing thr = \"chla\" thr = \"la\". Note change horizontal reference lines light attenuation target.  year range plot can also specified using yrrng argument, default year range epcdata.  show_thrplot() function uses results anlz_avedat() function. example, can retrieve values plot follows: Similarly, show_boxplot() function provides assessment seasonal changes chlorophyll light attenuation values bay segment. recent year highlighted red default. allows simple evaluation recent year compared historical averages. large exceedance value shown blue text dotted line. corresponds “large” magnitude change +2 standard errors bay segment threshold dotted line shown show_thrplot().   different subset years selected year interest can also viewed changing yrrng yrsel arguments. show 1980 compared monthly averages 2008 2018.  show_thrplot() function useful understand annual variation chlorophyll light attenuation relative management targets bay segment. information plots can provide understanding annual reporting outcomes determined. noted , outcome integer zero three assigned bay segment annual estimate chlorophyll light attenuation. outcomes based exceedance annual estimate threshold target (blue lines show_thrplot()) duration exceedance years prior. following graphic describes logic [8]. Outcomes annual estimates water quality assigned integer value zero three depending magnitude duration exceedence. outcomes assigned chlorophyll light attenuation. duration criteria determined based whether exceedance observed years prior current year. exceedance criteria chlorophyll light-attenuation specific segment. tbeptools package contains targets data file reference determining annual outcomes. file loaded automatically package can viewed command line. final plotting function show_matrix(), creates annual reporting matrix reflects combined outcomes chlorophyll light attenuation. Tracking attainment bay segment specific targets indicators provides framework bay management actions developed initiated. year segment, color-coded management action assigned: Stay Course: Continue planned projects. Report data via annual progress reports Baywide Environmental Monitoring Report. Caution: Review monitoring data nitrogen loading estimates. Begin/continue TAC Management Board development specific management recommendations. Alert: Finalize development implement appropriate management actions get back track. management category action based combination outcomes chlorophyll light attenuation [8]. Management action categories assigned bay segment year based chlorophyll light attenuation outcomes. results can viewed show_matrix().  matrix also ggplot object layout can changed using ggplot elements. Note use txtsz = NULL remove color labels.  preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. Results can also obtained selected year. Outcomes can returned tabular format anlz_yrattain(). table also shows segment averages chlorophyll light attenuation, including associated targets. map showing individual sites achieved chlorophyll targets can obtained show_sitemap(). station averages chlorophyll selected year shown next point. Stations red failed meet segment target.  show_sitemap() function also includes argument specify particular monthly range selected year. option chosen, averages shown continuous values station.  Another map can created show_sitesegmap() similar show_sitemap(), except bay segments shown colored annual outcome. map useful understand site data correspond bay segment.  Bay segment exceedances can also viewed matrix using show_wqmatrix(). thresholds values correspond Florida DEP criteria (large exceedance defined +2 standard errors segment target).  default, show_wqmatrix() function returns chlorophyll exceedances segment. Light attenuation exceedances can viewed changing param argument.  results show_matrix() show_wqmatrix() can combined individual segment using show_segmatrix() function. useful understand water quality parameter driving management outcome given year. plot shows light attenuation chlorophyll outcomes show_wqmatrix() next segment management outcomes show_matrix(). one segment can plotted function call.  Finally, segment plots can shown together using show_segplotly() function combines chlorophyll secchi data given segment. function combines outputs show_thrplot() show_segmatrix(). final plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot. plots, can quickly view summary environmental history water quality Tampa Bay. Degraded conditions common early period record, particularly Old Tampa Bay Hillsborough Bay. Conditions began improve late 1980s early 1990s, good conditions persisting present day. However, recent trends Old Tampa Bay shown conditions changing “stay course” “caution”.","code":"toplo <- epcdata %>%    filter(epchc_station == '52')  ggplot(toplo, aes(x = SampleTime, y = chla)) +    geom_line() +    geom_point() +    scale_y_log10() +    labs(     y = 'Chlorophyll-a concentration (ug/L)',      x = NULL,      title = 'Chlorophyll trends',     subtitle = 'Hillsborough Bay station 52, all dates'     ) +    theme_bw() show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"chla\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\", yrrng = c(2000, 2018)) epcdata %>%    anlz_avedat %>%    .[['ann']] %>%    filter(bay_segment == 'OTB') %>%    filter(var == 'mean_la') %>%    filter(yr >= 2000 & yr <= 2018) #> # A tibble: 19 × 4 #>       yr bay_segment var       val #>    <dbl> <chr>       <chr>   <dbl> #>  1  2000 OTB         mean_la 0.733 #>  2  2001 OTB         mean_la 0.951 #>  3  2002 OTB         mean_la 0.927 #>  4  2003 OTB         mean_la 1.04  #>  5  2004 OTB         mean_la 0.878 #>  6  2005 OTB         mean_la 0.769 #>  7  2006 OTB         mean_la 0.620 #>  8  2007 OTB         mean_la 0.677 #>  9  2008 OTB         mean_la 0.696 #> 10  2009 OTB         mean_la 0.808 #> 11  2010 OTB         mean_la 0.842 #> 12  2011 OTB         mean_la 0.912 #> 13  2012 OTB         mean_la 0.687 #> 14  2013 OTB         mean_la 0.567 #> 15  2014 OTB         mean_la 0.606 #> 16  2015 OTB         mean_la 0.560 #> 17  2016 OTB         mean_la 0.575 #> 18  2017 OTB         mean_la 0.682 #> 19  2018 OTB         mean_la 0.678 show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\") show_boxplot(epcdata, param = 'la', bay_segment = \"HB\") show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\", yrrng = c(2008, 2018), yrsel = 1980) targets #>   bay_segment                      name chla_target chla_smallex chla_thresh #> 1         OTB             Old Tampa Bay         8.5          8.9         9.3 #> 2          HB          Hillsborough Bay        13.2         14.1        15.0 #> 3         MTB          Middle Tampa Bay         7.4          7.9         8.5 #> 4         LTB           Lower Tampa Bay         4.6          4.8         5.1 #> 5        BCBN      Boca Ciega Bay North         7.7          NaN         8.3 #> 6        BCBS      Boca Ciega Bay South         6.1          NaN         6.3 #> 7         TCB            Terra Ceia Bay         7.5          NaN         8.7 #> 8          MR             Manatee River         7.3          NaN         8.8 #> 9       RALTB Remainder Lower Tampa Bay         NaN          NaN         5.1 #>   la_target la_smallex la_thresh #> 1      0.83       0.86      0.88 #> 2      1.58       1.63      1.67 #> 3      0.83       0.87      0.91 #> 4      0.63       0.66      0.68 #> 5       NaN        NaN       NaN #> 6       NaN        NaN       NaN #> 7       NaN        NaN       NaN #> 8       NaN        NaN       NaN #> 9       NaN        NaN       NaN show_matrix(epcdata) show_matrix(epcdata, txtsz = NULL) +   scale_y_continuous(expand = c(0,0), breaks = sort(unique(epcdata$yr))) +    coord_flip() +   theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 7)) show_matrix(epcdata, asreact = TRUE) show_matrix(epcdata, plotly = TRUE) anlz_yrattain(epcdata, yrsel = 2018) #> # A tibble: 4 × 6 #>   bay_segment chla_val chla_target la_val la_target outcome #>   <fct>          <dbl>       <dbl>  <dbl>     <dbl> <chr>   #> 1 OTB             9.22         8.5  0.678      0.83 yellow  #> 2 HB             13.9         13.2  1.09       1.58 green   #> 3 MTB             7.05         7.4  0.570      0.83 green   #> 4 LTB             4.65         4.6  0.593      0.63 green show_sitemap(epcdata, yrsel = 2018) show_sitemap(epcdata, yrsel = 2018, mosel = c(7, 9)) show_sitesegmap(epcdata, yrsel = 2018) show_wqmatrix(epcdata) show_wqmatrix(epcdata, param = 'la') show_segmatrix(epcdata, bay_segment = 'OTB') show_segplotly(epcdata, width = 1000, height = 600)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"reasonable-assurance-reporting","dir":"Articles","previous_headings":"Show","what":"Reasonable Assurance reporting","title":"Water Quality Data","text":"TBEP collaboration Tampa Bay Nitrogen Management Consortium (NMC) reports annually water quality conditions Tampa Bay Reasonable Assurance (RA) plan Florida Department Environmental Protection (FDEP). plan comprehensive approach managing nitrogen pollution Tampa Bay provides “reasonable assurance” designated uses waterbody segments bay maintained restored response potential nutrient impairments. Annual reports FDEP critical part plan tbeptools package includes functions facilitate reporting. functions previously described (e.g., show_wqmatrix()). First, show_annualassess() function can create simple table annual management outcome assessments chlorophyll-light attenuation bay segment. provides summary results given year, including segment-averaged chlorophyll-light attenuation bay segment names colored management outcome. required inputs EPC dataset selected year. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Second, show_ratab() function provides table annual water quality outcomes relative five-year RA reporting period. table includes associated NMC actions followed based water quality outcomes, actions provide reasonable assurance water quality maintained restored following outcomes. results specific four bay segments. Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2)    years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years    years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/   necessary due observed water quality seagrass conditions bay segment NMC Actions 4-5: Determine entity/source/facility specific exceedences 5-yr average allocation occurred implementation period necessary chlorophyll-threshold met show_ratab() function developed 2022-2026 RA period currently work previous RA periods. function may updated future accommodate different periods.","code":"show_annualassess(epcdata, yrsel = 2023) show_annualassess(epcdata, yrsel = 2023, caption = TRUE) show_ratab(epcdata, yrsel = 2023, bay_segment = 'OTB')"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Seagrass Transect Data","text":"two datasets included tbeptools show actively monitored transect locations Tampa Bay. trnpts dataset point object starting location transect trnlns dataset line object showing approximate direction length transect beginning point trnpts. dataset also includes MonAgency column indicates monitoring agency collects data transect. two datasets sf() (simple features) objects easily mapped mapview() view locations. transect data can downloaded Water Atlas using read_transect() function. required argument function training, indicates want download training data complete dataset, .e., training = TRUE training = FALSE (default). former case, small dataset downloaded includes data collected annual training event. primarily used internally TBEP staff assess precision among different training crews. data downloaded JSON object formatted internally using read_formtransect() function. Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates blade length cm. Change training argument FALSE download entire transect database. may take seconds. columns complete transect database describe crew (Crew), monitoring agency (MonitoringAgency), sample date (Date), transect name (Transect), meter location quadrat along transect (Site, m), depth site (Depth, cm), Seagrass species (Savspecies), distance seagrass edge transect (SeagrassEdge, m), seagrass variable (var), average value variable (aveval), standard deviation variable appropriate (sdval). raw, unformatted transect data preferred, use raw = TRUE argument read_transect().","code":"trnpts #> Simple feature collection with 66 features and 11 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.8089 ymin: 27.49925 xmax: -82.39305 ymax: 28.0001 #> Geodetic CRS:  WGS 84 #> First 10 features: #>    SEGMENT TRANSECT TRAN_ID Metermark    ID   LAT_DD   LONG_DD MonAgency STATUS #> 1        1        1    S1T1         0 START 27.99498 -82.68325     EPCHC ACTIVE #> 2        1        3    S1T3         0 START 28.00010 -82.66417     EPCHC ACTIVE #> 3        1        5    S1T5         0 START 27.95788 -82.54663      FDEP ACTIVE #> 4        1        6    S1T6         0 START 27.91348 -82.53282     EPCHC ACTIVE #> 5        1        8    S1T8         0 START 27.86233 -82.56867     EPCHC ACTIVE #> 6        1       13   S1T13         0 START 27.92428 -82.70232     EPCHC ACTIVE #> 7        1       14   S1T14         0 START 27.85533 -82.59738     EPCHC ACTIVE #> 8        1       15   S1T15         0 START 27.87408 -82.53098     EPCHC ACTIVE #> 9        1       16   S1T16         0 START 27.88228 -82.62015     PCDEM ACTIVE #> 10       1       17   S1T17         0 START 27.90498 -82.64793     PCDEM ACTIVE #>    Comments bay_segment                   geometry #> 1      <NA>         OTB POINT (-82.68325 27.99498) #> 2      <NA>         OTB  POINT (-82.66417 28.0001) #> 3      <NA>         OTB POINT (-82.54663 27.95788) #> 4      <NA>         OTB POINT (-82.53282 27.91348) #> 5      <NA>         OTB POINT (-82.56867 27.86233) #> 6      <NA>         OTB POINT (-82.70232 27.92428) #> 7      <NA>         OTB POINT (-82.59738 27.85533) #> 8      <NA>         OTB POINT (-82.53098 27.87408) #> 9      <NA>         OTB POINT (-82.62015 27.88228) #> 10     <NA>         OTB POINT (-82.64793 27.90498) trnlns #> Simple feature collection with 61 features and 7 fields #> Geometry type: LINESTRING #> Dimension:     XYM #> Bounding box:  xmin: -82.8118 ymin: 27.49807 xmax: -82.39306 ymax: 28.0001 #> m_range:       mmin: 0 mmax: 2700 #> Geodetic CRS:  WGS 84 #> First 10 features: #>    OBJECTID  Site Shape_Leng MonAgency ActiveYN Comments #> 1         1  S1T1   300.1400     EPCHC      YES     <NA> #> 2         5 S1T13  1102.6182     EPCHC      YES     <NA> #> 3         6 S1T14   800.4500     EPCHC      YES     <NA> #> 4         7 S1T15   701.0075     EPCHC      YES     <NA> #> 5         8 S1T16   998.9961     PCDEM      YES     <NA> #> 6         9 S1T17  2698.5773     PCDEM      YES     <NA> #> 7        10 S1T18   997.5451     EPCHC      YES     <NA> #> 8        12  S1T3   401.5991     EPCHC      YES     <NA> #> 9        14  S1T5   457.5927      FDEP      YES     <NA> #> 10       15  S1T6   398.6606     EPCHC      YES     <NA> #>                          geometry     bearing #> 1  LINESTRING M (-82.68325 27....  116.533756 #> 2  LINESTRING M (-82.70232 27....   -4.689701 #> 3  LINESTRING M (-82.59738 27....  109.402541 #> 4  LINESTRING M (-82.53098 27....  -85.765142 #> 5  LINESTRING M (-82.62015 27....   13.913960 #> 6  LINESTRING M (-82.64791 27....  -21.165576 #> 7  LINESTRING M (-82.61143 27.... -123.050914 #> 8  LINESTRING M (-82.66417 28.... -128.034327 #> 9  LINESTRING M (-82.54663 27.... -121.861907 #> 10 LINESTRING M (-82.53282 27....  -89.362036 cols <- c(\"#E16A86\", \"#CB7F2F\", \"#9F9400\", \"#50A315\", \"#00AC79\", \"#00AAB7\", \"#009ADE\", \"#A87BE4\", \"#DA65C3\")  mapview(trnpts, zcol = 'MonAgency', lwd = 0, legend = F, homebutton = F, col.regions = cols) +    mapview(trnlns, zcol = 'MonAgency', homebutton = F, layer.name = 'Monitoring Agency', lwd = 4, color = cols) # import training data traindat <- read_transect(training = TRUE)  # view the data traindat #> # A tibble: 1,428 × 11 #>       yr grp   grpact    Crew  MonitoringAgency Site  Depth Species var   aveval #>    <int> <chr> <chr>     <chr> <chr>            <chr> <int> <chr>   <chr>  <dbl> #>  1  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Abun…    3   #>  2  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Blad…    0   #>  3  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Shor…    0   #>  4  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Abun…    0   #>  5  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Blad…    0   #>  6  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Shor…    0   #>  7  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Abun…    5   #>  8  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Blad…   22   #>  9  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Shor…   27.3 #> 10  2020 A     2020: MC… K. H… MCNRD            3       -60 Thalas… Abun…    1   #> # ℹ 1,418 more rows #> # ℹ 1 more variable: sdval <dbl> # import entire transct dataset as JSON transect <- read_transect(training = FALSE)  # view the data transect #> # A tibble: 154,476 × 11 #>    Crew              MonitoringAgency Date       Transect Site  Depth Savspecies #>    <chr>             <chr>            <date>     <chr>    <chr> <int> <chr>      #>  1 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  2 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  3 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  4 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  5 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  6 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  7 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #>  8 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #>  9 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #> 10 A. McClory, A. I… MCNRD            2024-08-13 S4T2     150      -5 Halodule   #> # ℹ 154,466 more rows #> # ℹ 4 more variables: SeagrassEdge <dbl>, var <chr>, aveval <dbl>, sdval <dbl> # raw transect data transectraw <- read_transect(training = FALSE, raw = TRUE)  # view the data transectraw #> # A tibble: 51,806 × 46 #>    IDall AssessmentYear CreatedAt   Crew  CountingTech SeagrassEdge Secchi Sonde #>    <int>          <int> <chr>       <chr> <chr>               <dbl>  <dbl> <lgl> #>  1     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  2     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  3     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  4     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  5     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  6     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  7     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  8     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  9     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #> 10     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #> # ℹ 51,796 more rows #> # ℹ 38 more variables: Weather <chr>, Hidden <lgl>, HiddenReason <lgl>, #> #   IsComplete <lgl>, QASubmittedAt <chr>, ReadyForQA <lgl>, #> #   QACompletedAt <chr>, MonitoringAgency <chr>, Transect <chr>, #> #   BaySegment <chr>, ID <int>, ObservationDate <chr>, Site <int>, #> #   Species <chr>, SpeciesAbundance <chr>, Appearance <chr>, #> #   BladeLength_1 <int>, BladeLength_2 <int>, BladeLength_3 <int>, …"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"calculating-seagrass-frequency-occurrence","dir":"Articles","previous_headings":"","what":"Calculating seagrass frequency occurrence","title":"Seagrass Transect Data","text":"rest seagrass functions tbeptools developed work complete database. show_complot() function (see ) developed training data. rest functions can used estimate plot frequency occurrence data. anlz_transectocc() function summarizes frequency occurrence transects dates collapsing species results across quadrats within transect. Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2 [1]. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species, including Caulerpa spp. (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. second function, anlz_transectave(), takes results anlz_transectocc() estimates annual results across major bay segments seagrass species averaging frequency occurrence across transects. function used internally within show_transectmatrix() function create summary plots. frequency occurrence estimates also binned categories simple trend assessments, e.g., red < 25%, orange 25-50%, yellow 50-75%, green > 75%. Results specific bay segments annual ranges can filtered bay_segment yrrng arguments. third function, anlz_transectavespp(), takes results anlz_transectocc() estimates annual averages across major bay segments last function, results retained individual species. function used internally within show_transectavespp() function create summary plots. summaries aggregated across selected bay segments, .e., default average species/year across segments. Results individual bay segment can returned appropriate argument, e.g., using bay_segment = 'OTB' select Old Tampa Bay. Results can also filtered specific species using species argument, default return . Caulerpa spp. Dapis spp. also included. Results individual bay segments anlz_transectavespp() can retained setting by_seg argument TRUE. Note totals returned case.","code":"transectocc <- anlz_transectocc(transect) transectocc #> # A tibble: 39,546 × 6 #> # Groups:   Date, Transect [1,521] #>    Date       Transect Savspecies              nsites foest bbest #>    <date>     <chr>    <chr>                    <int> <dbl> <dbl> #>  1 1997-10-11 S2T3     \"AA\"                        41     0     0 #>  2 1997-10-11 S2T3     \"Caulerpa\"                  41     0     0 #>  3 1997-10-11 S2T3     \"DA\"                        41     0     0 #>  4 1997-10-11 S2T3     \"DB: Dictyota\\r\\n\"          41     0     0 #>  5 1997-10-11 S2T3     \"DB: Drift Brown\\r\\n\"       41     0     0 #>  6 1997-10-11 S2T3     \"DG: Chaetomorpha\\r\\n\"      41     0     0 #>  7 1997-10-11 S2T3     \"DG: Drift Green\"           41     0     0 #>  8 1997-10-11 S2T3     \"DG: Ulva\"                  41     0     0 #>  9 1997-10-11 S2T3     \"DG: Ulva fasciata\\r\\n\"     41     0     0 #> 10 1997-10-11 S2T3     \"DR: Acanthophora\"          41     0     0 #> # ℹ 39,536 more rows transectave <- anlz_transectave(transectocc) transectave #> # A tibble: 156 × 4 #> # Groups:   bay_segment [6] #>    bay_segment    yr foest focat   #>    <fct>       <dbl> <dbl> <fct>   #>  1 Tampa Bay    1998  58.0 #E9C318 #>  2 OTB          1998  65.5 #E9C318 #>  3 HB           1998  15.0 #CC3231 #>  4 MTB          1998  53.7 #E9C318 #>  5 LTB          1998  80.8 #2DC938 #>  6 BCB          1998  81.0 #2DC938 #>  7 Tampa Bay    1999  51.5 #E9C318 #>  8 OTB          1999  64.7 #E9C318 #>  9 HB           1999  10.1 #CC3231 #> 10 MTB          1999  51.8 #E9C318 #> # ℹ 146 more rows transectavespp <- anlz_transectavespp(transectocc) transectavespp #> # A tibble: 208 × 3 #>       yr Savspecies   foest #>    <dbl> <fct>        <dbl> #>  1  1998 Caulerpa    0.0166 #>  2  1998 Dapis       0      #>  3  1998 Halodule    0.361  #>  4  1998 Halophila   0      #>  5  1998 Ruppia      0.0112 #>  6  1998 Syringodium 0.0451 #>  7  1998 Thalassia   0.254  #>  8  1998 total       0.580  #>  9  1999 Caulerpa    0.0277 #> 10  1999 Dapis       0      #> # ℹ 198 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,170 × 5 #>       yr bay_segment Savspecies  foest nsites #>    <dbl> <fct>       <fct>       <dbl>  <int> #>  1  1998 BCB         Caulerpa    0         96 #>  2  1998 BCB         Dapis       0         96 #>  3  1998 BCB         Halodule    0.613     96 #>  4  1998 BCB         Halophila   0         96 #>  5  1998 BCB         No Cover    0.190     96 #>  6  1998 BCB         Ruppia      0         96 #>  7  1998 BCB         Syringodium 0         96 #>  8  1998 BCB         Thalassia   0.304     96 #>  9  1998 BCB         total       0.810     96 #> 10  1998 HB          Caulerpa    0        285 #> # ℹ 1,160 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Seagrass Transect Data","text":"one plotting function training data. show_compplot() function used compare training data crews selected species (species argument) variable (varplo argument).  rest plotting functions work complete transect data. Data individual transect can viewed show_transect() function entering transect (site) number, species (one many), variable plot. plot shows relative values selected species variable distance along transect (x-axis) year sampling (y-axis). plots provide overall summary temporal spatial changes selected seagrass metric individual location.  plot can also produced plotly interactive plot setting plotly = TRUE inside function. Note size legend merged species legend, point size average abundance species. sizes can viewed mouseover point. show_transect() function can also used plot multiple species. One many species can provided species argument.  plots can also separated facets species using facet = TRUE. useful reduce overplotting multiple species found location.  show_transectsum() function provides alternative summary data individual transect. plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Unlike show_transect(), plot shows aggregated results across quadrats along transect uses summarized data anlz_transectocc() function input. summary matrix frequency occurrence estimates across species can plotted show_transectmatrix(). uses results anlz_transectocc() anlz_transectave() functions estimate annual averages bay segment. continuous frequency occurrence estimates binned color categories described , Table 1 [2].  default color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. don’t necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette.  matrix can also produced plotly interactive plot setting plotly = TRUE inside function. Time series plots annual averages frequency occurrence estimates species can shown show_transectavespp() function. default, estimates averaged across bay segments species. plot representation Figure 2 [2].  Results individual segments species can returned bay_segment species arguments. Use argument total = FALSE omit total frequency occurrence plot.  plot can also produced plotly interactive plot setting plotly = TRUE inside function. alternative plotting species averages time show_transectavespp(), table can created setting asreact = TRUE. Filtering options apply plot also apply table, e.g., filtering four major bay segments specific year ranges. Also note totals returned table. describes methods tbeptools working transect monitoring data. Seagrass coverage maps also created approximately biennially Southwest Florida Water Management District, available https://data-swfwmd.opendata.arcgis.com/. seagrass data object included package shows Tampa Bay coverage total year available data, including 1950s reference estimate. show_seagrasscoverage() function creates flagship seagrass coverage graphic report changes time data.","code":"show_compplot(traindat, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance', base_size = 14) show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance', plotly = T) show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance', facet = TRUE) show_transectsum(transectocc, site = 'S3T10') show_transectmatrix(transectocc) show_transectmatrix(transectocc, neutral = T) show_transectmatrix(transectocc, plotly = T) show_transectavespp(transectocc) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), total = FALSE) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), plotly = T) show_transectavespp(transectocc, asreact = T, bay_segment = c('HB', 'OTB', 'MTB', 'LTB'), yrrng = c(2006, 2012)) show_seagrasscoverage(seagrass)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Benthic Index","text":"Tampa Bay Benthic Index (TBBI) [1,2]) assessment method quantifies ecological health benthic community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available region (e.g., water quality report card, nekton index, etc.). tbeptools package includes several functions described import data required index plot results view trends time. functions described detail . TBBI uses data Tampa Bay Benthic Monitoring Program part Environmental Protection Commission (EPC) Hillsborough Country. data updated annually public site maintained EPC, typically December Summer/Fall sampling. website hosts water quality data used water quality report card. required data TBBI extensive water quality report card data made available zipped folder csv files, available . process downloading working data similar functions tbeptools.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Benthic Index","text":"Data calculating TBBI scores can imported current R session using read_importbenthic() function. function downloads zipped folder base tables used TBBI EPC site data already downloaded location specified input arguments. download data tbeptools, first create character path location want download zipped files. one exist, specify location name downloaded file. , name folder benthic.zip download desktop. Running code return following error: get error message function indicating file found. makes sense file exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved benthicdata object current R session. try run function downloading data, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work benthic data, read_importbenthic() used import data. always receive message File current... local file matches one server. However, data periodically updated posted server. download_latest = TRUE local file date, receive following message:","code":"path <- '~/Desktop/benthic.zip' benthicdata <- read_importbenthic(path) #> Error in read_importbenthic() : File at path does not exist, use download_latest = TRUE benthicdata <- read_importbenthic(path, download_latest = T) #> File ~/Desktop/benthic.zip does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1' length 37122877 bytes (35.4 MB) benthicdata <- read_importbenthic(path, download_latest = T) #> File is current.. #> Replacing local file with current..."},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"calculating-tbbi-scores","dir":"Articles","previous_headings":"","what":"Calculating TBBI scores","title":"Tampa Bay Benthic Index","text":"data imported, can view assigned object. data provided nested tibble includes three different datasets: station information, field sample data (salinity), detailed taxa information. individual datasets can viewed extracting parent object using deframe() function tibble package. anlz_tbbiscr() function uses nested benthicdata estimate TBBI scores site. TBBI scores typically range 0 100 grouped categories describe general condition benthic community. Scores less 73 considered “degraded”, scores 73 87 “intermediate”, scores greater 87 “healthy”. Locations sampled organisms found assigned score zero category “empty sample”. total abundance (TotalAbundance, organisms/m2), species richness (SpeciesRichness) bottom salinity (Salinity, psu) also provided. metrics TBBI corrected salinity bottom measurements taken time sampling required accurate calculation TBBI.","code":"benthicdata #> # A tibble: 3 × 2 #>   name         value                  #>   <chr>        <list>                 #> 1 stations     <tibble [4,787 × 10]>  #> 2 fieldsamples <tibble [5,197 × 3]>   #> 3 taxacounts   <tibble [149,657 × 7]> # see all deframe(benthicdata) #> $stations #> # A tibble: 4,787 × 10 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl> #>  #> $fieldsamples #> # A tibble: 5,197 × 3 #>    StationID date       Salinity #>        <int> <date>        <dbl> #>  1       448 2002-05-21     30.5 #>  2       449 2002-05-20     30.8 #>  3       450 2002-05-21     30.5 #>  4       451 2002-05-21     30.6 #>  5       452 2002-05-20     30   #>  6       453 2002-05-21     30.6 #>  7       454 2002-05-21     30.5 #>  8       455 2002-05-21     30.3 #>  9       456 2002-05-20     30.0 #> 10       457 2002-05-20     29.9 #> # ℹ 5,187 more rows #>  #> $taxacounts #> # A tibble: 149,657 × 7 #>    StationID TaxaCountID TaxaListID FAMILY           NAME     TaxaCount AdjCount #>        <int>       <int>      <int> <chr>            <chr>        <dbl>    <dbl> #>  1     11321      152055       1198 Anomiidae        Anomia …         1       25 #>  2     11321      152056       1224 Carditidae       Cardite…         1       25 #>  3       584      233277        624 Cirratulidae     Chaetoz…         1       25 #>  4     11321      152057       1306 Veneridae        Chione …         3       75 #>  5      3132      239443        352 Pilargidae       Sigambr…        14      350 #>  6     11321      152058       1088 Pyramidellidae   Turboni…         6      150 #>  7      2541      140530        258 NULL             NEMERTEA         8      200 #>  8      2542      140531        258 NULL             NEMERTEA         2       50 #>  9      2992      140631        262 NULL             Palaeon…         4      100 #> 10      3003      140635        285 Tetrastemmatidae Tetrast…         2       50 #> # ℹ 149,647 more rows  # get only station dat deframe(benthicdata)[['stations']] #> # A tibble: 4,787 × 10 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl> tbbiscr <- anlz_tbbiscr(benthicdata) tbbiscr #> # A tibble: 4,787 × 15 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl>, #> #   TotalAbundance <dbl>, SpeciesRichness <dbl>, TBBI <dbl>, TBBICat <chr>, #> #   Salinity <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Benthic Index","text":"TBBI scores can viewed annual averages bay segment using show_tbbimatrix() function. show_tbbimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. baywide estimate also returned, one based samples across locations (“”) another weighted relative surface areas bay segment (“(wt)”). input show_tbbimatrix() function output anlz_tbbiscr() function.  matrix can also produced plotly interactive plot setting plotly = TRUE inside function.","code":"show_tbbimatrix(tbbiscr) show_tbbimatrix(tbbiscr, plotly = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"additional-sediment-data","dir":"Articles","previous_headings":"","what":"Additional sediment data","title":"Tampa Bay Benthic Index","text":"addition biological data, sediment contaminant concentrations measured sites within Tampa Bay. include 100 different constituents grouped broadly metals, organics, physical, . concentrations constituents can compared relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available, relative indications likelihood concentrations toxic effects invertebrates inhabit sediments. functions tbeptools can used retrieve sediment data provide indication concentrations relative TEL PEL thresholds. read_importsediment() function retrieve sediment data Tampa Bay collected annually Environmental Protection Commission Hillsborough County. data retrieved location biological data used calculate TBBI. data imported, can view assigned object. show_sedimentmap() function can used create maps selected parameters relative TEL PEL values. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. selected stations sampled years within yrrng argument. single year data can shown well. map showing concentrations returned TEL PEL values available parameter. Maps total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned. Although totals included sedimentdata object, calculated tbeptools using anlz_sedimentaddtot() function. Simply entering name total parameter show_sedimentmap() function produce summary map. PEL ratio can also used assess relative sediment quality given measured contaminants. show_sedimentpelmap() function creates map average PEL ratios graded F benthic stations monitored Tampa Bay. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station. average PEL ratios grades used create map can also returned data frame using anlz_sedimentpel(). Plots bay segment averages sediment concentrations selected parameters can created show_sedimentave(). plot includes appropriate lines TEL PEL values, well grand mean across segments. former omitted plot unavailable selected parameter.  plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentave(). , total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned even though included sedimentdata object. anlz_sedimentaddtot() function used calculate totals within anlz_sedimentave(). similar plot bay segment averages average PEL ratios can created show_sedimentpelave(). colors indicate grades (green) F (red).  plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentpelave(). show_sedimentalratio() function creates plot selected metal parameter Aluminum. plot provides information concentration parameter relative background levels, Aluminum present common metal Earth’s crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations [3]. linear fit log-log model shown solid black line, 95% prediction intervals. TEL/PEL values, available, also shown horizontal red lines.  plot can returned interactive plotly object using plotly = T.","code":"path <- '~/Desktop/sediment.zip' sedimentdata <- read_importsediment(path, download_latest = T) sedimentdata #> # A tibble: 221,597 × 24 #>    ProgramId ProgramName   FundingProject    yr AreaAbbr StationID StationNumber #>        <int> <chr>         <chr>          <int> <chr>        <int> <chr>         #>  1         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  2         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  3         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  4         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  5         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  6         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  7         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  8         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  9         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> 10         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> # ℹ 221,587 more rows #> # ℹ 17 more variables: Latitude <dbl>, Longitude <dbl>, Replicate <chr>, #> #   SedResultsType <chr>, Parameter <chr>, ValueAdjusted <dbl>, Units <chr>, #> #   Qualifier <chr>, MDLnum <dbl>, PQLnum <dbl>, TEL <dbl>, PEL <dbl>, #> #   BetweenTELPEL <chr>, ExceedsPEL <chr>, PELRatio <dbl>, #> #   PreparationDate <chr>, AnalysisTimeMerge <chr> show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = 2022) show_sedimentmap(sedimentdata, param = 'Selenium', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) show_sedimentpelmap(sedimentdata, yrrng = c(1993, 2022)) anlz_sedimentpel(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 2,233 × 7 #>       yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #>    <int> <chr>    <chr>            <dbl>     <dbl>    <dbl> <fct> #>  1  1993 HB       93HB15            27.8     -82.4  0.0157  B     #>  2  1993 HB       93HB16            27.8     -82.5  0.0261  C     #>  3  1993 HB       93HB23            27.9     -82.4  0.0174  B     #>  4  1993 LTB      93LTB24           27.7     -82.6  0.0124  B     #>  5  1993 LTB      93LTB25           27.6     -82.6  0.0189  B     #>  6  1993 LTB      93LTB26           27.6     -82.7  0.00997 B     #>  7  1993 LTB      93LTB27           27.6     -82.7  0.0125  B     #>  8  1993 LTB      93LTB28           27.6     -82.7  0.0887  D     #>  9  1993 LTB      93LTB29           27.6     -82.6  0.0350  C     #> 10  1993 LTB      93LTB30           27.6     -82.6  0.0496  C     #> # ℹ 2,223 more rows show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022), plotly = T) anlz_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       7.24  41.6 mg/kg  2.64 2.34   2.94     2.57 #> 2 HB        7.24  41.6 mg/kg  2.93 0.665  5.20     2.57 #> 3 LTB       7.24  41.6 mg/kg  2.93 2.47   3.40     2.57 #> 4 MR        7.24  41.6 mg/kg  1.66 1.37   1.95     2.57 #> 5 MTB       7.24  41.6 mg/kg  2.17 1.86   2.48     2.57 #> 6 OTB       7.24  41.6 mg/kg  3.24 0.707  5.78     2.57 #> 7 TCB       7.24  41.6 mg/kg  2.40 1.92   2.88     2.57 anlz_sedimentave(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       3.89  51.7 ug/kg 0.570 0.382 0.757    0.700 #> 2 HB        3.89  51.7 ug/kg 1.77  0.870 2.67     0.700 #> 3 LTB       3.89  51.7 ug/kg 0.218 0.105 0.332    0.700 #> 4 MR        3.89  51.7 ug/kg 0.838 0.517 1.16     0.700 #> 5 MTB       3.89  51.7 ug/kg 0.434 0.285 0.582    0.700 #> 6 OTB       3.89  51.7 ug/kg 0.490 0.274 0.706    0.700 #> 7 TCB       3.89  51.7 ug/kg 0.582 0.202 0.962    0.700 show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022), plotly = T) anlz_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 7 × 5 #>   AreaAbbr    ave    lov    hiv grandave #>   <fct>     <dbl>  <dbl>  <dbl>    <dbl> #> 1 BCB      0.0535 0.0445 0.0625   0.0522 #> 2 HB       0.118  0.0663 0.169    0.0522 #> 3 LTB      0.0281 0.0247 0.0315   0.0522 #> 4 MR       0.0446 0.0375 0.0516   0.0522 #> 5 MTB      0.0374 0.0327 0.0421   0.0522 #> 6 OTB      0.0506 0.0371 0.0642   0.0522 #> 7 TCB      0.0337 0.0265 0.0409   0.0522 show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB')) show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Nekton Index","text":"Tampa Bay Nekton Index (TBNI) [1,2]) multimetric assessment method quantifies ecological health nekton community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available Tampa Bay (e.g., water quality report card, Benthic index, etc.). tbeptools package includes several functions described import data required index, analyze data calculate metrics index scores, plot results view trends time. functions described detail . TBNI uses catch data Florida Fish Wildlife Conservation Commission (FWC) Fish Wildlife Research Institute’s (FWRI) Fisheries-Independent Monitoring (FIM) program. Catch results center-bag seine longest consistent record FIM database used develop TBNI. include counts taxa identification individuals caught near shore areas, generally early recruits, juveniles, smaller-bodied nekton. fish selected invertebrates identified lowest possible taxon (usually species), counted, subset measured. Current protocols established 1998 TBNI estimates unavailable prior date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Nekton Index","text":"Data required calculating TBNI scores can imported current R session using read_importfim() function. function downloads latest FIM file FTP site data already downloaded location specified input arguments. download data, first create character path location file. one exist, specify desired location name downloaded file. , want put file desktop home directory name fimdata.csv. Running code return following error: get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved fimdata object current R session. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current matches file server. Every time tbeptools used work FIM data, read_importfim() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: data successfully imported, can view assigned object: imported data formatted calculating TBNI. columns include Reference FIM sampling site, sampling date, sampling Zone, sampling Grid, NODCCODE unique identifier species, sample year, sample month, total catch Total_N, scientific name, column indicating species included index, several columns indicating species-specific information required metrics. final columns, separate lookup table provided package merged imported FIM data. file, tbnispp, can viewed anytime package loaded: read_importfim() function can also return simple features object sampled stations raw FIM data setting . data matched appropriate bay segments tabulating TBNI scores. resulting dataset indicates sampling occurred can mapped mapview() function. ease use, dataset named fimstations included tbeptools. read_importfim() function processes observed data needed TBNI, including merging rows tbnispp fimstations data. imported, metrics scores can calculated.","code":"csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv) #> Error in read_importfim(csv) : file.exists(csv) is not TRUE fimdata <- read_importfim(csv, download_latest = T) #> File ~/Desktop/fimdata.csv does not exist, replacing with downloaded file...  #> trying URL 'ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv' length 11083878 bytes (10.6 MB) fimdata <- read_importfim(csv, download_latest = T) #> File is current.. #> Replacing local file with current... head(fimdata) #> # A tibble: 6 × 19 #>   Reference    Sampling_Date Latitude Longitude Zone   Grid NODCCODE  Year Month #>   <chr>        <date>           <dbl>     <dbl> <chr> <int> <chr>    <dbl> <dbl> #> 1 TBM19980109… 1998-01-09        28.0     -82.7 A        31 8747020…  1998     1 #> 2 TBM19980109… 1998-01-09        28.0     -82.7 A        31 8805030…  1998     1 #> 3 TBM19980109… 1998-01-09        27.9     -82.7 A        62 6177010…  1998     1 #> 4 TBM19980109… 1998-01-09        27.9     -82.7 A        63 9998000…  1998     1 #> 5 TBM19980109… 1998-01-09        27.9     -82.6 A        65 8820020…  1998     1 #> 6 TBM19980109… 1998-01-09        27.9     -82.6 A        65 8826020…  1998     1 #> # ℹ 10 more variables: Total_N <dbl>, ScientificName <chr>, #> #   Include_TB_Index <chr>, Hab_Cat <chr>, Est_Cat <chr>, Est_Use <chr>, #> #   Feeding_Cat <chr>, Feeding_Guild <chr>, Selected_Taxa <chr>, #> #   bay_segment <chr> head(tbnispp) #>      TSN   NODCCODE               ScientificName Include_TB_Index Hab_Cat #> 1 173245 8860030201 Acanthostracion quadricornis                Y       B #> 2 172986 8858030202             Achirus lineatus                Y       B #> 3 160978 8713070101           Aetobatus narinari                Y       B #> 4 161121 8739010101                Albula vulpes                Y       P #> 5  96600 6179140000               Alpheidae spp.                N       B #> 6 173131 8860020101           Aluterus schoepfii                Y       B #>   Est_Cat Est_Use Feeding_Cat Feeding_Guild Selected_Taxa #> 1      MS       O          TS            ZB             N #> 2      ES       O          TS            ZB             N #> 3      MS       F          TS            ZB             N #> 4      MS       S          TS            ZB             Y #> 5                          DV            DV             N #> 6      MS       F          TS            HV             N fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) mapview(fimstations, zcol = 'bay_segment')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"calculating-metrics-and-tbni-scores","dir":"Articles","previous_headings":"","what":"Calculating metrics and TBNI scores","title":"Tampa Bay Nekton Index","text":"Metrics scores Tampa Bay Nekton Index can calculated using two functions. anlz_tbnimet() function calculates raw metrics anlz_tbniscr() function calculates scored metrics final TBNI score. functions use imported formatted FIM data input. TBNI includes five metrics sensitive stressor gradients provide unique information Nekton community response environmental conditions. metrics include: NumTaxa: Species richness BenthicTaxa: Species richness benthic taxa TaxaSelect: Number “selected” species (.e., commercially /recreationally important) NumGuilds: Number trophic guilds Shannon: Shannon Diversity (H) Raw metrics first calculated observed data scaled standard score 0 - 10 accounting expected relationships environmental gradients 5th/95th percentiles distributions. final TBNI score summed average scores ranging 0 - 100. raw metrics, scored metrics, final TBNI score returned anlz_tbniscr() function. five metrics chosen TBNI appropriate Tampa Bay dataset selected larger pool candidate metrics. potential metrics can calculated using anlz_tbnimet() function. metrics can used standalone assessments developing Nekton index outside Tampa Bay. argument = TRUE must used return metrics, otherwise selected five TBNI returned.","code":"tbniscr <- anlz_tbniscr(fimdata) head(tbniscr) #> # A tibble: 6 × 16 #>   Reference      Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #>   <chr>         <dbl> <dbl> <chr>  <chr>            <dbl>   <dbl>        <dbl> #> 1 TBM1998010906  1998     1 Winter OTB                 18       2            2 #> 2 TBM1998010910  1998     1 Winter OTB                 14       1            1 #> 3 TBM1998010912  1998     1 Winter OTB                  0       0            0 #> 4 TBM1998010914  1998     1 Winter OTB                 20       2            2 #> 5 TBM1998010915  1998     1 Winter MTB                 46       4            4 #> 6 TBM1998010917  1998     1 Winter MTB                 24       2            2 #> # ℹ 8 more variables: BenthicTaxa <dbl>, ScoreBenthicTaxa <dbl>, #> #   TaxaSelect <dbl>, ScoreTaxaSelect <dbl>, NumGuilds <dbl>, #> #   ScoreNumGuilds <dbl>, Shannon <dbl>, ScoreShannon <dbl> tbnimet <- anlz_tbnimet(fimdata, all = T) head(tbnimet) #> # A tibble: 6 × 37 #>   Reference      Year Month Season bay_segment NumTaxa NumIndiv Shannon Simpson #>   <chr>         <dbl> <dbl> <chr>  <chr>         <dbl>    <dbl>   <dbl>   <dbl> #> 1 TBM1998010906  1998     1 Winter OTB               2       17   0.362    1.26 #> 2 TBM1998010910  1998     1 Winter OTB               1        1   0        1    #> 3 TBM1998010912  1998     1 Winter OTB               0        0   0        0    #> 4 TBM1998010914  1998     1 Winter OTB               2        2   0.693    2    #> 5 TBM1998010915  1998     1 Winter MTB               4       11   1.16     2.81 #> 6 TBM1998010917  1998     1 Winter MTB               2        5   0.500    1.47 #> # ℹ 28 more variables: Pielou <dbl>, TaxaSelect <dbl>, NumGuilds <dbl>, #> #   TSTaxa <dbl>, TGTaxa <dbl>, BenthicTaxa <dbl>, PelagicTaxa <dbl>, #> #   OblTaxa <dbl>, MSTaxa <dbl>, ESTaxa <dbl>, SelectIndiv <dbl>, Taxa90 <dbl>, #> #   TSAbund <dbl>, TGAbund <dbl>, BenthicAbund <dbl>, PelagicAbund <dbl>, #> #   OblAbund <dbl>, ESAbund <dbl>, MSAbund <dbl>, Num_LR <dbl>, PropTG <dbl>, #> #   PropTS <dbl>, PropBenthic <dbl>, PropPelagic <dbl>, PropObl <dbl>, #> #   PropMS <dbl>, PropES <dbl>, PropSelect <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Nekton Index","text":"TBNI scores can viewed annual averages using show_tbniscr(), show_tbniscrall() show_tbnimatrix() functions. show_tbniscr() creates line graph values time bay segment, whereas show_tbniscrall() function plots overall average across bay segments time. show_tbnimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. input function output anlz_tbniscr() function.    plots can also produced plotly interactive plots setting plotly = TRUE inside function. breakpoints categorical outcomes TBNI scores shown colors graph based 33rd 50th percentiles distribution TBNI scores calculated Tampa Bay. plotting option provided consistency existing TBEP reporting tools, e.g., water quality report card returned show_matrix(). categorical outcomes serve management guidelines year activities support environmental resources Bay: Stay Course, Caution, Alert [3]. graphs returned plotting functions ggplot objects can modified. can combined using patchwork single graphic showing trends time categorical outcomes matrix continuous scores bottom plot.","code":"show_tbniscr(tbniscr) show_tbniscrall(tbniscr) show_tbnimatrix(tbniscr) show_tbniscr(tbniscr, plotly = T) show_tbniscrall(tbniscr, plotly = T) show_tbnimatrix(tbniscr, plotly = T) p1 <- show_tbnimatrix(tbniscr, txtsz = NULL, rev = TRUE, position = 'bottom') +   scale_y_continuous(expand = c(0,0), breaks = c(1998:2020)) +   coord_flip() +   theme(axis.text.x = element_blank())  p2 <- show_tbniscr(tbniscr)  p1 + p2 + plot_layout(ncol = 1, heights = c(0.3, 1))"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tidal Creek Assessment","text":"Dashboard: https://shiny.tbep.org/tidalcreek-dash/ Tidal creeks (aka tributaries) essential habitats Tampa Bay Estuary serve important focal points understanding watershed inputs affect water quality. fundamental goal Tampa Bay Estuary Program develop effective nutrient management strategies support ecological function tidal creeks. partnership Sarasota Bay NEP, Coastal & Heartland NEP, local government agency stakeholders, open science framework developed assessing tidal creek condition based host commonly collected water quality data [1–3]. assessments can support tracking water quality management goals can help refine restoration management plans priority tributaries, including need hydrologic restoration can support critical nursery habitats sportfishes. tbeptools package includes simple features spatial data object population tidal creeks southwest Florida, called tidalcreeks(). includes 615 polyline features designated water body ID (WBID), creek id (JEI), FDEP class (class, 1 potable water, 2 shellfish harvesting propagation, 3F/3M freshwater/marine fish consumption, recreation, propagation maintenance healthy, well-balanced population fish wildlife). tidal creek assessment framework established based data FDEP Impaired Waters Rule database run 56 available includes data collected January 10th 2019. However, framework intends link future IWR databases refresh site new data becomes available. Raw updated data IWR database required assessment provided tbeptools package iwrraw() data object.","code":"mapview(tidalcreeks, homebutton = F, legend = F)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"assessment","dir":"Articles","previous_headings":"","what":"Assessment","title":"Tidal Creek Assessment","text":"tidal creek assessment framework includes “report card” “indicators” assessment provided separate tabs dashboard. report card provides assessment total nitrogen concentrations (limiting nutrient creeks) based annual geometric average concentrations relative standards developed contributing freshwater streams. indicators based several water quality metrics derived outcomes study describe tidal creek condition provide insights site specific attributes creeks may govern overall creek health.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card","dir":"Articles","previous_headings":"","what":"Report card","title":"Tidal Creek Assessment","text":"report card similar TBEP water quality report card tidal creeks assigned categories within assessment framework intended serve mechanism evaluating data relative need management action, identify stewardship goals , properly pursued, may preclude need regulatory actions. categories established based principally fish biological response indicator. Tidal creeks assigned one five categories: Data: Data unavailable evaluation. Monitor: Creek nitrogen concentrations protect individual creek types within larger population creeks. Caution: Creek nutrients showing signs elevated nutrient concentrations may increase risk eutrophic condition. Investigate: Creek nutrient concentrations margin safety protect creek potential impairment. Prioritize: Creek nutrient concentrations exceeded regulatory standard associated freshwater portion tributary indicating actions needed identify remediative measures reduce nutrients creek. Conceptually, thresholds appear figure . Scoring rubrik tidal creeks based nitrogen thresholds. Prioritize category defined based Florida’s freshwater stream numeric nutrient criteria (NNC).Two different freshwater stream NNC applicable region; West Central NNC 1.65 mg/l Peninsular region NNC 1.54 mg/l. histograms figure represent range annual geometric mean (AGM) nitrogen concentrations associated Prioritize Investigate categories based NNC. example , maximum expected distribution AGMs exceed 1.65 mg/l 1:3 exceedence probability (defined F..C. 62-303) generated using monte carlo simulation highest observed standard deviation data collected first creeks study. Investigate category defined explicit margin safety adjusting distribution find grand geometric average result 1:20 chance exceeding 1.65 mg/l. Assignment creek Caution category depended creek length adjustment described protect smaller creeks elevated nutrient concentrations. tidaltargets() data object included tbeptools includes thresholds. Note “Caution” category function creek length. scoring algorithm derived define final report card outcome creek using entire ten year record available data based following criteria. single exceedance Prioritize Investigate categories year ten year record result classification creek respective category unless least three years data threshold level category. Creeks assigned next lower category one AGM TN given level multiple years (.e., two) given levels defining cutoff points category. example, creek least 4 years data single exceedance Prioritize threshold assigned Investigate category. Outcomes exemplified .","code":"tidaltargets #>         region prioritize investigate #> 1 West Central       1.65        1.38 #> 2    Peninsula       1.54        1.30 #>                                             caution #> 1 1.38 - 0.0174 * (23.78 - (Creek_Length_m / 1000)) #> 2 1.30 - 0.0174 * (23.78 - (Creek_Length_m / 1000))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card-functions","dir":"Articles","previous_headings":"Report card","what":"Report card functions","title":"Tidal Creek Assessment","text":"two primary functions tidal creek assessments anlz_tdlcrk() obtain scores show_tdlcrk() view interactive map results. anlz_tdlcrk() function uses included tidalcreeks() iwrraw() datasets estimate scores: results include unique creek identifier (id, based wbid JEI fields), waterbody id (wbid), creek ID (JEI), FDEP class (class), results assessment remaining columns. columns monitor, caution, investigate, prioritize indicate number years 2012 2021 nitrogen values within ranges appropriate creek type specified within tidaltargets(). score column indicates overall category assigned creek period record. Note many creeks assigned Data value sufficient data unavailable. summation four component columns (monitor, caution, investigate, prioritize) provides number years data available creek. show_tdlcrk() function can used output anlz_tdlcrk() view interactive map results. Creeks color-coded exceedance categories, “Data” creeks shown light blue. report card style matrix can plotted using show_tdlcrkmatrix() function shows overall creek score number years data used estimate overall score. plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency. default, plot shows creeks marine WBID (water body identifier) designation 3M 2. can changed class argument (.e., class c('3M', '2', '3F', '1') marine freshwater WBIDs).","code":"results <- anlz_tdlcrk(tidalcreeks, iwrraw) results #> # A tibble: 615 × 10 #>       id wbid  JEI   name     class monitor caution investigate prioritize score #>    <int> <chr> <chr> <chr>    <chr>   <dbl>   <dbl>       <dbl>      <dbl> <chr> #>  1     1 1983B CC01  Rock Cr… 2          NA      NA          NA         NA No D… #>  2     2 2052  CC01  Rock Cr… 3M         10      NA          NA         NA Moni… #>  3     3 1983B CC02  Oyster … 2          NA      NA          NA         NA No D… #>  4     4 2067  CC02  Oyster … 3M         10      NA          NA         NA Moni… #>  5     5 1983B CC03  Buck Cr… 2          NA      NA          NA         NA No D… #>  6     6 2068  CC03  Buck Cr… 3M          9       1          NA         NA Moni… #>  7     7 2078A CC04  Buck Cr… 2          NA      NA           1         NA Inve… #>  8     8 2078A CC05  Coral C… 2          NA      NA          NA         NA No D… #>  9     9 2078B CC05  Coral C… 2           4       1          NA         NA Moni… #> 10    10 2065C CC06  Catfish… 2          NA      NA          NA         NA No D… #> # ℹ 605 more rows show_tdlcrk(results) show_tdlcrkmatrix(results)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"indicator-functions","dir":"Articles","previous_headings":"Report card","what":"Indicator functions","title":"Tidal Creek Assessment","text":"Water quality Indicators developed provide context interpreting report card outcomes described detail Wessel et al. 2021 include thresholds total nitrogen (>1.1 mg/l), chlorophyll (>11 ug/l), dissolved oxygen (< 42 % saturation), trophic state index score (>55), chlorophyll/nitrogen ratio (>15) ratio nitrates tidal freshwater portion creek (>1) (data available). results indicator relative established thresholds calculated annual basis synthesized 10 year period calculating percentage annual outcomes exceeding identified threshold indicator values total number years available data. integrative summary indicators presented using standardized polar coordinate system Radar Charts provide single multi-metric summary plot results across indicators. anlz_tdlcrkindic() function generates annual outcomes wbid/JEI combination. Individual creek indicators summarized using multivariate response plot called “radar plot” indicates percentage years indicator exceeded respective threshold value. plots created using radar = TRUE argument anlz_tdlcrkindic() function using results show_tdlcrkradar() function. radar plots apply marine WBIDs tidal creeks (Florida DEP class 2, 3M). Indicators without data creek point plot.  General descriptive plots annual outcomes provided interactive plotly graphics using show_tdlcrkindic() show_tdlcrkindiccdf() functions. show_tdlcrindic() function produces bar plots annual outcomes selected creek. creek plot selected id argument integer used filter results anlz_tdlcrkindic() function, latter passed cntdat argument. thrsel argument plots dotted red lines based threshold values. year unique color. show_tdlcrkindiccdf() function similar except empirical cumulative distribution functions (CDF) plotted evaluate outcomes specific creek relative entire distribution creeks southwest Florida. indicator year selected creek plotted CDF curves. Location points indicate comparison population trajectory indicators time (.e., brown older observations blue recent). Holding mouse cursor point shows year holding cursor line shows percentile value CDF.","code":"results <- anlz_tdlcrkindic(tidalcreeks, iwrraw) head(results) #>   id       name  JEI wbid class year    CHLAC    COLOR COND       DO    DOSAT #> 1  2 Rock Creek CC01 2052    3M 2014 2.380249 14.69473   NA 3.308289 60.31523 #> 2  2 Rock Creek CC01 2052    3M 2015 2.647817 21.91113   NA 4.034172 55.41609 #> 3  2 Rock Creek CC01 2052    3M 2016 2.265462 19.13080   NA 3.980251 55.96637 #> 4  2 Rock Creek CC01 2052    3M 2017 2.851726 15.39576   NA 4.157777 60.18017 #> 5  2 Rock Creek CC01 2052    3M 2018 1.934899 11.65500   NA 4.219790 63.32630 #> 6  2 Rock Creek CC01 2052    3M 2019 2.071003  7.21425   NA 3.015847 44.90322 #>          NO23 ORGN    SALIN       TKN        TN         TP TSS     TURB #> 1 0.007575792   NA 26.63714 0.6161702 0.6228782 0.06938150  NA 2.044623 #> 2 0.009361504   NA 19.10494 0.6465161 0.5678241 0.07602770  NA 1.814818 #> 3 0.008532522   NA 25.84531 0.5813818 0.5408161 0.08330509  NA 2.082253 #> 4 0.007447260   NA 24.86909 0.6255197 0.6326848 0.07566682  NA 1.802161 #> 5 0.006994714   NA 31.32419 0.5668727 0.5734574 0.07432007  NA 2.454007 #> 6 0.007047106   NA 31.63214 0.5053022 0.4577485 0.06300538  NA 1.831953 #>   chla_tn_ratio tn_tp_ratio chla_tsi   tn_tsi  tn2_tsi   tp_tsi  tp2_tsi #> 1      3.821371    8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2      4.663093    7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3      4.188970    6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4      4.507341    8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5      3.374095    7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6      4.524324    7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #>    nut_tsi      tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651          NA         NA         NA       0       1 #> 2 47.43600 39.12890          NA         NA         NA       0       1 #> 3 46.38844 37.48223          NA         NA         NA       0       1 #> 4 49.76107 40.82559          NA         NA         NA       0       0 #> 5 47.64821 36.97650          NA         NA         NA       0       1 #> 6 42.80384 35.04375          NA         NA         NA       1       1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = T)  # get random creek id set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id = id, cntdat = cntdat) cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkindic(id = id, cntdat = cntdat, thrsel = TRUE) show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Marcus Beck. Author, maintainer. Meagan Schrandt. Author. Mike Wessel. Author. Ed Sherwood. Author. Gary Raulerson. Author. Adhokshaja Achar Budihal Prasad. Author. Benjamin Best. Author. Kim Cressman. Author.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beck, M.W., Schrandt, M.N., Wessel, M.R., Sherwood, E.T., Raulerson, G.E., Budihal Prasad, .., Best, B.D., (2021). tbeptools: R package synthesizing estuarine data environmental research. Journal Open Source Software, 6(65), 3485, https://doi.org/10.21105/joss.03485","code":"@Article{,   title = {{t}beptools: An {R} package for synthesizing estuarine data for environmental research},   author = {Marcus Beck and Meagan Schrandt and Mike Wessel and Ed Sherwood and Gary Raulerson and Adhokshaja Achar {Budihal Prasad} and Benjamin Best},   journal = {Journal of Open Source Software},   year = {2021},   volume = {6},   number = {65},   pages = {3485},   doi = {10.21105/joss.03485}, }"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"tbeptools","dir":"","previous_headings":"","what":"Data and Indicators for the Tampa Bay Estuary Program","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"R package Tampa Bay Estuary Program functions. Please see vignettes full description.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"package can installed r-universe. source code available tbep-tech GitHub group web page: https://github.com/tbep-tech/tbeptools. Note tbeptools needs installed , needs loaded every new R session (.e., library(tbeptools)). package loaded, can view help files function typing question mark followed function name, e.g., ?read_importwq, console. help files provide brief description function required arguments needed run function.","code":"# enable repos options(repos = c(     tbeptech = 'https://tbep-tech.r-universe.dev',     CRAN = 'https://cloud.r-project.org'))  # install tbeptools install.packages('tbeptools')  # load tbeptools library(tbeptools)"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"vignettes organized topic excellent place start understanding use package. Currently, six vignettes available tbeptools: Water Quality Data: Overview functions working water quality data water quality report card Tampa Bay Nekton Index: Overview functions import, analyze, plot results Tampa Bay Nekton Index Tampa Bay Benthic Index: Overview functions import data Tampa Bay Benthic Index, development Tidal Creeks Assessment: Overview functions import, analyze, plot results assessment tidal creeks southwest Florida Seagrass Transect Data: Overview functions import, analyze, plot results seagrass transect data collected Tampa Bay Habitat Master Plan: Overview functions analyze create report card Tampa Bay Habitat Master Plan 2020 update Fecal Indicator Bacteria: Overview functions import, analyze, plot results Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"core functions tbeptools three categories based mode use. function named using prefix mode use, followed function . prefixes : read: Import current data main site. anlz: Analyze summarize imported data. show: Create plot analyzed data. functions can easily found RStudio loading package typing prefix command line. autofill dialog box pop showing functions apply prefix. eliminates need searching individual functions know category function need (e.g., read, anlz, show). function also includes semi-descriptive suffix generally describes category applies (e.g, water quality, seagrass) (e.g., imports, formats). follow loose convention attempts strike balance description brevity. optimal balance often hard achieve. aid understanding, provide brief description suffixes used . Suffix descriptions: attain: Analyze functions summarize data relative attainment categories specific bay segments ave, med: Analyze functions summarize data averages medians benthic: Applies benthic monitoring data used Tampa Bay Benthic Index entero: Applies Enterococcus, specific type Fecal Indicator Bacteria, fib functions applicable fib: Applies generally Fecal Indicator Bacteria fim: Applies data Fisheries Independent Monitoring program used Tampa Bay Nekton Index form: intermediate function formatting imported data downstream analysis hmp: Functions work Habitat Master Plan data import: function used import data source external package indic: function analyzes plots individual tidal creek indicator values, opposed integrated creek scores iwr: Functions data apply Impaired Waters Rule (IWR) data maintained Florida Department Environmental Protection used source data tidal creek functions matrix: plotting function creates report card style matrix met: function analyses plots individual metrics integrated indices, e.g., TBBI, TBNI phyto: Applies phytoplankton data Hillsborough County Environmental Protection Commission plotly: plotting function returns interactive plotly object scr: function analyses plots summary scores integrated indices, e.g., TBBI, TBNI seg, site: Functions analyze plot results relative bay segments individual monitoring sites tbbi: Applies Tampa Bay Benthic Index (TBBI) tbni: Applies Tampa Bay Nekton Index (TBNI) tdlcrk: Applies tidal creeks transect: Applies seagrass transect data wq: Applies water quality function reference page can also viewed complete list functions organized category, description , links help files. following example demonstrates use subset functions water quality data read file Hillsborough County Environmental Protection Commission long-term monitoring dataset (available https://www.tampabay.wateratlas.usf.edu/), analyze monthly annual averages major bay segments Tampa Bay, plot annual time series one bay segments.  Functions tbeptools also support creation content interactive, online dashboards can facilitate informed decisions without requiring intimate understanding R programming language methods analysis. dashboards include assessments water quality, seagrasses, nekton communities, tidal creeks.","code":"# load the package library(tbeptools)  # read current data wqdat <- read_importwq(xlsx = \"wqdata.xlsx\", download_latest = TRUE) wqdat ## # A tibble: 26,611 x 22 ##   bay_segment epchc_station SampleTime             yr    mo ##   <chr>               <dbl> <dttm>              <dbl> <dbl> ## 1 HB                      6 2021-06-08 10:59:00  2021     6 ## 2 HB                      7 2021-06-08 11:13:00  2021     6 ## 3 HB                      8 2021-06-08 14:15:00  2021     6 ## 4 MTB                     9 2021-06-08 13:14:00  2021     6 ## 5 MTB                    11 2021-06-08 11:30:00  2021     6 ## # ... with 26,606 more rows, and 17 more variables: ## #   Latitude <dbl>, Longitude <dbl>, Total_Depth_m <dbl>, ## #   Sample_Depth_m <dbl>, tn <dbl>, tn_q <chr>, sd_m <dbl>, ## #   sd_raw_m <dbl>, sd_q <chr>, chla <dbl>, chla_q <chr>, ## #   Sal_Top_ppth <dbl>, Sal_Mid_ppth <dbl>, ## #   Sal_Bottom_ppth <dbl>, Temp_Water_Top_degC <dbl>, ## #   Temp_Water_Mid_degC <dbl>, ... # analyze monthly and annual means by bay segment avedat <- anlz_avedat(wqdat) avedat ## $ann ## # A tibble: 584 x 4 ##      yr bay_segment var         val ##   <dbl> <chr>       <chr>     <dbl> ## 1  1974 HB          mean_chla 22.4 ## 2  1974 LTB         mean_chla  4.24 ## 3  1974 MTB         mean_chla  9.66 ## 4  1974 OTB         mean_chla 10.2 ## 5  1975 HB          mean_chla 27.9 ## # ... with 579 more rows ## ## $mos ## # A tibble: 4,484 x 5 ##   bay_segment    yr    mo var         val ##   <chr>       <dbl> <dbl> <chr>     <dbl> ## 1 HB           1974     1 mean_chla 36.2 ## 2 LTB          1974     1 mean_chla  1.75 ## 3 MTB          1974     1 mean_chla 11.5 ## 4 OTB          1974     1 mean_chla  4.4 ## 5 HB           1974     2 mean_chla 42.4 ## # ... with 4,479 more rows # show annual time series of chlorophyll for Hillsborough bay segment show_thrplot(wqdat, bay_segment = \"HB\", yrrng = c(1975, 2020))"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"issues-and-suggestions","dir":"","previous_headings":"","what":"Issues and suggestions","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please report issues suggestions issues link repository. guide posting issues can found .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"contributing","dir":"","previous_headings":"","what":"Contributing","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please view contributing guidelines changes pull requests.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay intertidal and supratidal land use and cover — acres","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"Tampa Bay intertidal supratidal land use cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"acres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"if (FALSE) { # \\dontrun{ load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/acres.RData\"))  save(acres, file = 'data/acres.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories — anlz_attain","title":"Get attainment categories — anlz_attain","text":"Get attainment categories year bay segment using chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories — anlz_attain","text":"","code":"anlz_attain(avedat, magdurout = FALSE, trgs = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories — anlz_attain","text":"avedat result returned anlz_avedat magdurout logical indicating separate magnitude duration estimates returned trgs optional data.frame annual bay segment water quality targets, defaults targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories — anlz_attain","text":"data.frame year bay segment showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories — anlz_attain","text":"","code":"avedat <- anlz_avedat(epcdata) anlz_attain(avedat) #> # A tibble: 200 × 4 #>    bay_segment    yr chl_la outcome #>    <chr>       <dbl> <chr>  <chr>   #>  1 HB           1974 3_0    yellow  #>  2 HB           1975 3_2    red     #>  3 HB           1976 3_2    red     #>  4 HB           1977 3_2    red     #>  5 HB           1978 3_3    red     #>  6 HB           1979 3_3    red     #>  7 HB           1980 3_3    red     #>  8 HB           1981 3_3    red     #>  9 HB           1982 3_3    red     #> 10 HB           1983 3_0    yellow  #> # ℹ 190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Get site attainments — anlz_attainsite","title":"Get site attainments — anlz_attainsite","text":"Get site attainment categories chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get site attainments — anlz_attainsite","text":"","code":"anlz_attainsite(   avedatsite,   thr = c(\"chla\", \"la\"),   trgs = NULL,   yrrng = NULL,   thrs = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get site attainments — anlz_attainsite","text":"avedatsite result returned anlz_avedatsite thr chr string indicating water quality value appropriate threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng optional numeric value year return, defaults thrs logical indicating attainment category relative targets (default) thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get site attainments — anlz_attainsite","text":"data.frame year site showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get site attainments — anlz_attainsite","text":"function simplication attainment categories returned anlz_attain.  Sites compared targets/thresholds apply separately chlorophyll light attenuation.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get site attainments — anlz_attainsite","text":"","code":"avedatsite <- anlz_avedatsite(epcdata) anlz_attainsite(avedatsite) #> # A tibble: 2,250 × 9 #>       yr bay_segment epchc_station var     val target smallex thresh met   #>    <dbl> <chr>               <dbl> <chr> <dbl>  <dbl>   <dbl>  <dbl> <chr> #>  1  1974 HB                      6 chla   25.6   13.2    14.1     15 no    #>  2  1974 HB                      7 chla   21.6   13.2    14.1     15 no    #>  3  1974 HB                      8 chla   22.6   13.2    14.1     15 no    #>  4  1974 HB                     44 chla   23.4   13.2    14.1     15 no    #>  5  1974 HB                     52 chla   23.5   13.2    14.1     15 no    #>  6  1974 HB                     55 chla   20.2   13.2    14.1     15 no    #>  7  1974 HB                     70 chla   33.1   13.2    14.1     15 no    #>  8  1974 HB                     71 chla   25.8   13.2    14.1     15 no    #>  9  1974 HB                     73 chla   17.6   13.2    14.1     15 no    #> 10  1974 HB                     80 chla   10.5   13.2    14.1     15 yes   #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means — anlz_avedat","title":"Estimate annual means — anlz_avedat","text":"Estimate annual means chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means — anlz_avedat","text":"","code":"anlz_avedat(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means — anlz_avedat","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means — anlz_avedat","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means — anlz_avedat","text":"","code":"# view average estimates anlz_avedat(epcdata) #> $ann #> # A tibble: 608 × 4 #>       yr bay_segment var         val #>    <dbl> <chr>       <chr>     <dbl> #>  1  1974 HB          mean_chla 22.4  #>  2  1974 LTB         mean_chla  4.24 #>  3  1974 MTB         mean_chla  9.66 #>  4  1974 OTB         mean_chla 10.2  #>  5  1975 HB          mean_chla 27.9  #>  6  1975 LTB         mean_chla  4.93 #>  7  1975 MTB         mean_chla 11.4  #>  8  1975 OTB         mean_chla 13.2  #>  9  1976 HB          mean_chla 29.5  #> 10  1976 LTB         mean_chla  5.08 #> # ℹ 598 more rows #>  #> $mos #> # A tibble: 4,724 × 5 #>    bay_segment    yr    mo var         val #>    <chr>       <dbl> <dbl> <chr>     <dbl> #>  1 HB           1974     1 mean_chla 36.2  #>  2 LTB          1974     1 mean_chla  1.75 #>  3 MTB          1974     1 mean_chla 11.5  #>  4 OTB          1974     1 mean_chla  4.4  #>  5 HB           1974     2 mean_chla 42.4  #>  6 LTB          1974     2 mean_chla  5.5  #>  7 MTB          1974     2 mean_chla  9.35 #>  8 OTB          1974     2 mean_chla  4.07 #>  9 HB           1974     3 mean_chla 14.9  #> 10 LTB          1974     3 mean_chla  5.88 #> # ℹ 4,714 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means by site — anlz_avedatsite","title":"Estimate annual means by site — anlz_avedatsite","text":"Estimate annual means site chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"anlz_avedatsite(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means by site — anlz_avedatsite","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means by site — anlz_avedatsite","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"# view average estimates anlz_avedatsite(epcdata) #> $ann #> # A tibble: 6,838 × 5 #>       yr bay_segment epchc_station var         val #>    <dbl> <chr>               <dbl> <chr>     <dbl> #>  1  1974 HB                      6 mean_chla  25.6 #>  2  1974 HB                      7 mean_chla  21.6 #>  3  1974 HB                      8 mean_chla  22.6 #>  4  1974 HB                     44 mean_chla  23.4 #>  5  1974 HB                     52 mean_chla  23.5 #>  6  1974 HB                     55 mean_chla  20.2 #>  7  1974 HB                     70 mean_chla  33.1 #>  8  1974 HB                     71 mean_chla  25.8 #>  9  1974 HB                     73 mean_chla  17.6 #> 10  1974 HB                     80 mean_chla  10.5 #> # ℹ 6,828 more rows #>  #> $mos #> # A tibble: 48,727 × 6 #>    bay_segment epchc_station    yr    mo var         val #>    <chr>               <dbl> <dbl> <dbl> <chr>     <dbl> #>  1 HB                      6  1974     1 mean_chla    53 #>  2 HB                      7  1974     1 mean_chla    19 #>  3 HB                      8  1974     1 mean_chla    46 #>  4 HB                     44  1974     1 mean_chla    24 #>  5 HB                     52  1974     1 mean_chla    28 #>  6 HB                     55  1974     1 mean_chla    33 #>  7 HB                     70  1974     1 mean_chla    58 #>  8 HB                     71  1974     1 mean_chla    73 #>  9 HB                     73  1974     1 mean_chla    17 #> 10 HB                     80  1974     1 mean_chla    11 #> # ℹ 48,717 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Enterococcus data — anlz_enteromap","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"Assign threshold categories Enterococcus data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"","code":"anlz_enteromap(   fibdata,   yrsel = NULL,   mosel = NULL,   areasel = NULL,   wetdry = FALSE,   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   assf = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"fibdata data frame Enterococcus sample data returned enterodata anlz_fibwetdry yrsel optional numeric filter data year mosel optional numeric filter data month areasel optional character string filter output stations long_name column enterodata, see details wetdry logical; TRUE, incorporate wet/dry differences (result call anlz_fibwetdry, case temporal_window wet_threshold required). FALSE (default), differentiate wet dry samples. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required wetdry TRUE. number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required wetdry TRUE. inches accumulated defined temporal window, sample defined 'wet' time period assf logical indicating data processed simple features object additional columns show_enteromap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"data.frame similar fibdata assf = FALSE additional columns describing station categories optionally filtered arguments passed function. sf object assf = TRUE additional columns show_enteromap.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"function based anlz_fibmap, specific Enterococcus data downloaded via read_importentero. creates categories mapping using show_enteromap. Optionally, samples defined 'wet' via anlz_fibwetdry, can represented via symbols map.  Categories based relevant thresholds assigned observation.  categories specific Enterococcus marine waters (class 2 3M). station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. areasel argument can indicate valid entries long_name column enterodata.  example, use \"Old Tampa Bay\" stations subwatershed Old Tampa Bay, rows  enterodata filtered based selection.  stations returned argument set NULL (default). valid options areasel include \"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay\", \"Manatee River\".  One options can used.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"","code":"anlz_enteromap(enterodata, yrsel = 2020, mosel = 9) #> # A tibble: 39 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    490 130 … #EE7… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    725 130 … #EE7… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     9     28.0     -82.7    703 130 … #EE7… Ente… #>  6 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7     10 < 35  #2DC… Ente… #>  7 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7   1990 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7    171 130 … #EE7… Ente… #>  9 21FLTPA_WQ… Old Tamp…  2020     9     27.9     -82.6    908 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     9     27.9     -82.4      1 < 35  #2DC… Ente… #> # ℹ 29 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl>  # differentiate wet/dry samples in that time frame anlz_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 39 × 13 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    490 130 … #EE7… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    725 130 … #EE7… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     9     28.0     -82.7    703 130 … #EE7… Ente… #>  6 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7     10 < 35  #2DC… Ente… #>  7 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7   1990 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7    171 130 … #EE7… Ente… #>  9 21FLTPA_WQ… Old Tamp…  2020     9     27.9     -82.6    908 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     9     27.9     -82.4      1 < 35  #2DC… Ente… #> # ℹ 29 more rows #> # ℹ 3 more variables: indnm <chr>, conc <dbl>, wet_sample <lgl>  # as sf object anlz_enteromap(enterodata, assf = TRUE) #> Simple feature collection with 5596 features and 14 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.74598 ymin: 27.49433 xmax: -82.38168 ymax: 28.02571 #> Geodetic CRS:  WGS 84 #> # A tibble: 5,596 × 15 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  6 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  7 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #>  8 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001    11     28.0     -82.6     60 35 -… #E9C… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    12     28.0     -82.6    340 130 … #EE7… Ente… #> # ℹ 5,586 more rows #> # ℹ 5 more variables: grp <fct>, conc <dbl>, wet_sample <fct>, #> #   geometry <POINT [°]>, lab <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"Assign threshold categories Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"anlz_fibmap(fibdata, yrsel = NULL, mosel = NULL, areasel = NULL, assf = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"fibdata input FIB data.frame returned read_importfib read_importwqp, see details yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details assf logical indicating data processed simple features object additional columns show_fibmap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"data.frame similar fibdata mancofibdata assf = FALSE additional columns describing station categories optionally filtered arguments passed function.  sf object assf = TRUE additional columns show_fibmap.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"function used create FIB categories mapping using show_fibmap.  Categories based relevant thresholds assigned observation.  categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively.  station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. Data Manatee County (21FLMANA_WQX) returned read_importwqp can used function.  Data organizations returned function tested. areasel argument can indicate valid entries area column fibdata (read_importfib) mancofibdata (read_importwqp).  example, use either \"Alafia River\" \"Hillsborough River\" corresponding river basins, rows  fibdata filtered based selection.  stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\".  Hillsborough River basin includes values area column fibdata \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\".  areas may present based selection. valid options areasel fibdata include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". One options can used. Valid entries areasel mancofibdata include 'Big Slough', 'Bowlees Creek', 'Braden River', 'Bud Slough',  'Cedar Creek', 'Clay Gully', 'Cooper Creek', 'Curiosity Creek', 'Frog Creek', 'Gamble Creek', 'Gap Creek', 'Gates Creek', 'Gilley Creek', 'Hickory Hammock Creek', 'Lake Manatee', 'Little Manatee River', 'Lower Manatee River', 'Lower Tampa Bay', 'Manatee River Estuary', 'Mcmullen Creek', 'Mill Creek', 'Mud Lake Slough', 'Myakka River', 'Nonsense Creek', 'Palma Sola Bay', 'Piney Point Creek', 'Rattlesnake Slough', 'Sugarhouse Creek', 'Upper Manatee River', 'Ward Lake', 'Williams Creek'. One options can used.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"# assign categories to all anlz_fibmap(fibdata) #> # A tibble: 77,526 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 77,516 more rows #> # ℹ 1 more variable: col <chr>  # filter by year, month, and area anlz_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') #> # A tibble: 24 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Alafia…      74 3M     2020     7     27.9     -82.4    NA    168 Ente… 130 … #>  2 Alafia…     111 3F     2020     7     27.9     -82.2    50   7000 E. c… < 126 #>  3 Alafia…     114 3F     2020     7     27.9     -82.3   447   1560 E. c… 410 … #>  4 Alafia…     115 3F     2020     7     27.9     -82.1    80    260 E. c… < 126 #>  5 Alafia…     116 3F     2020     7     27.9     -82.1    30    367 E. c… < 126 #>  6 Alafia…     139 3F     2020     7     27.7     -82.1    47    100 E. c… < 126 #>  7 Alafia…     151 3F     2020     7     27.9     -82.2    90     25 E. c… < 126 #>  8 Alafia…     153 3M     2020     7     27.9     -82.3    NA   4000 Ente… > 999 #>  9 Alafia…     154 3F     2020     7     27.9     -82.1   433   1367 E. c… 410 … #> 10 Alafia…     155 3F     2020     7     27.9     -82.2   170    233 E. c… 126 … #> # ℹ 14 more rows #> # ℹ 1 more variable: col <chr>  # as sf object anlz_fibmap(fibdata, assf = TRUE) #> Simple feature collection with 28287 features and 16 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.7832 ymin: 27.53248 xmax: -82.05604 ymax: 28.16544 #> Geodetic CRS:  WGS 84 #> # A tibble: 28,287 × 17 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 28,277 more rows #> # ℹ 6 more variables: col <chr>, geometry <POINT [°]>, grp <fct>, conc <dbl>, #> #   cls <chr>, lab <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"Analyze Fecal Indicator Bacteria categories time station bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(   fibdata,   yrrng = NULL,   stas = NULL,   bay_segment = NULL,   indic,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"fibdata input data frame returned read_importfib, read_importentero, read_importwqp, see details yrrng numeric vector indicating min, max years include, defaults range years data, see details stas optional vector stations include, see details bay_segment optional vector bay segment names include, supercedes stas provided, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"tibble object FIB summaries year station including columns estimated geometric mean fecal coliform Enterococcus concentrations (gmean), proportion samples exceeding 400 CFU / 100 mL (fecal coliform) 130 CFU / 100 mL (Enterococcus) (exced), count samples (cnt), category indicating letter outcome based proportion exceedences (cat).  Results can summarized bay segment bay_segment NULL input data read_importentero.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"function used create output plotting matrix stoplight graphic FIB categories station.  output can also summarized bay segment bay_segment NULL input data read_importentero. latter case, stas argument ignored stations within subsegment watershed used evaluate FIB categories. station (bay segment) year combination categorized based likelihood fecal indicator bacteria concentrations exceeding threshold given year.  fecal coliform, default threshold 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata).  Enterococcus, default threshold 130 CFU / 100 mL.  proportions categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed).  default, results year based right-centered window uses previous two years current year calculate probabilities using monthly samples (lagyr = 3). See show_fibmatrix additional details. yrrng can specified several ways.  yrrng = NULL, year range data selected changes chosen.  User-defined values minimum maximum years can also used, minimum maximum can specified, e.g., yrrng = c(2000, 2010) yrrng = c(2000, NA).  latter case, maximum year defined data. default stations fecal coliform data used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins bay_segment NULL input data read_importfib.  include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137).  stations can plotted using stas argument. Input read_importwqp Manatee County (21FLMANA_WQX) FIB data can also used.  function tested organizations.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata, indic = 'fcolif') #> # A tibble: 459 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1974 143     NA      NA        NA   NA    #>  2  1974 108    247.     28.1     -82.2 NA    #>  3  1974 107    269.     28.0     -82.3 NA    #>  4  1974 135     NA      NA        NA   NA    #>  5  1974 118    136.     28.1     -82.3 NA    #>  6  1974 148     NA      NA        NA   NA    #>  7  1974 105    258.     28.0     -82.4 NA    #>  8  1974 152     NA      NA        NA   NA    #>  9  1974 137     NA      NA        NA   NA    #> 10  1975 143     NA      NA        NA   NA    #> # ℹ 449 more rows  # use different indicator anlz_fibmatrix(fibdata, indic = 'entero') #> # A tibble: 216 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  2001 143     NA      NA        NA   NA    #>  2  2001 108     NA      NA        NA   NA    #>  3  2001 107     NA      NA        NA   NA    #>  4  2001 135     NA      NA        NA   NA    #>  5  2001 118     NA      NA        NA   NA    #>  6  2001 148     NA      NA        NA   NA    #>  7  2001 105    165.     28.0     -82.4 NA    #>  8  2001 152    207.     28.0     -82.5 NA    #>  9  2001 137    103.     28.0     -82.5 NA    #> 10  2002 143    320.     28.1     -82.1 NA    #> # ℹ 206 more rows  # use different dataset anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06 #> # A tibble: 1,224 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 A     #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,214 more rows  # same entero data; lower threshold - changes 'cat' scores anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1, threshold = 30) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06 #> # A tibble: 1,224 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 A     #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,214 more rows  # subset to only wet samples anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1, subset_wetdry = \"wet\",                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 1,150 × 6 #>       yr grp                         gmean Latitude Longitude cat   #>    <dbl> <fct>                       <dbl>    <dbl>     <dbl> <chr> #>  1  2001 21FLCOSP_WQX-32-03           NA       NA        NA   NA    #>  2  2001 21FLCOSP_WQX-44-02           NA       NA        NA   NA    #>  3  2001 21FLCOSP_WQX-48-03           NA       NA        NA   NA    #>  4  2001 21FLCOSP_WQX-CENTRAL CANAL   NA       NA        NA   NA    #>  5  2001 21FLCOSP_WQX-COSP580         NA       NA        NA   NA    #>  6  2001 21FLCOSP_WQX-NORTH CANAL     NA       NA        NA   NA    #>  7  2001 21FLCOSP_WQX-SC-01           NA       NA        NA   NA    #>  8  2001 21FLCOSP_WQX-SOUTH CANAL     NA       NA        NA   NA    #>  9  2001 21FLDOH_WQX-MANATEE152       31.6     27.5     -82.7 A     #> 10  2001 21FLHILL_WQX-101           2252.      28.0     -82.6 C     #> # ℹ 1,140 more rows  # Manatee County data anlz_fibmatrix(mancofibdata, indic = 'fcolif', lagyr = 1) #> # A tibble: 1,350 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1995 396    NA       NA        NA   NA    #>  2  1995 BC1    NA       NA        NA   NA    #>  3  1995 BC2    NA       NA        NA   NA    #>  4  1995 BC41   NA       NA        NA   NA    #>  5  1995 BL01   NA       NA        NA   NA    #>  6  1995 BL201  NA       NA        NA   NA    #>  7  1995 BR1    14.8     27.4     -82.5 A     #>  8  1995 BR2    41.1     27.4     -82.5 A     #>  9  1995 BR3    62.4     27.4     -82.5 A     #> 10  1995 BU01A  NA       NA        NA   NA    #> # ℹ 1,340 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"Identify Fecal Indicator Bacteria samples coming 'wet' 'dry' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"","code":"anlz_fibwetdry(fibdata, precipdata, temporal_window = 2, wet_threshold = 0.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"fibdata input data frame precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select stations. temporal_window numeric, number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric, inches accumulated defined temporal window, sample defined 'wet' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"data frame; original fibdata data frame three additional columns. rain_sampleDay total rain (inches) day sampling, rain_total total rain (inches) period time defined temporal_window, wet_sample logical, indicating whether rainfall station's catchment exceeded amount time period specified args.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"function allows user specify threshold declaring sample taken important amount rain important amount days, declaring 'wet'. interest samples taken significant precipitation (definitions vary, user can specify desired thresholds) likely exceed relevant bacterial thresholds. Identifying samples 'wet' allows calculation indices wet dry subsets samples.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"","code":"entero_wetdry <- anlz_fibwetdry(enterodata, catchprecip) head(entero_wetdry) #> # A tibble: 6 × 19 #>   date          yr    mo time  time_zone long_name    bay_segment station entero #>   <date>     <dbl> <dbl> <chr> <chr>     <chr>        <chr>       <chr>    <dbl> #> 1 2001-01-16  2001     1 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     80 #> 2 2001-02-20  2001     2 \"\"    \"\"        Old Tampa B… OTB         21FLHI…    360 #> 3 2001-03-20  2001     3 \"\"    \"\"        Old Tampa B… OTB         21FLHI…   3900 #> 4 2001-04-17  2001     4 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     20 #> 5 2001-05-15  2001     5 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     NA #> 6 2001-06-19  2001     6 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     NA #> # ℹ 10 more variables: entero_censored <lgl>, MDL <int>, entero_units <chr>, #> #   qualifier <lgl>, LabComments <lgl>, Latitude <dbl>, Longitude <dbl>, #> #   rain_sampleDay <dbl>, rain_total <dbl>, wet_sample <lgl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"Evaluate Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"anlz_hmpreport(acres, subtacres, hmptrgs)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"summarized data.frame appropriate creating report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"relevant output columns targeteval goaleval indicate numeric values -1 (target met, trending ), 0 (target met, trending ), 0.5 (target met, trending ), 1 (target met, trending ). Columns output follows: year Year assessment metric Habitat type assessed Acres Coverage estimate year lacres Coverage estimate previous set available data lyr Year previous set available data category Strata habitat type Target 2030 target habitat type Habitat Master Plan Goal 2050 goal habitat type Habitat Master Plan acresdiff Difference acres current year previous set available data yeardiff Difference years current year previous set available data changerate Acreage change per year current year relative previous set available data targetrate Annual rate required achieve 2030 target goalrate Annual rate required achieve 2050 goal targetprop Proportion target met current year goalprop Proportion goal met current year targeteval number indicating target status current year report card goaleval number indicating goal status current year report card numbers targeteval goaleval one four values -1, 0, 0.5, 1. numbers define status assessment year: -1 target goal met, trending 0 target goal met, trending 0.5 target goal met, trending 1 target goal met, trending ","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"# view summarized data for report card anlz_hmpreport(acres, subtacres, hmptrgs) #> # A tibble: 150 × 17 #>     year metric      Acres lacres   lyr category Target  Goal acresdiff yeardiff #>    <dbl> <chr>       <dbl>  <dbl> <dbl> <fct>     <dbl> <dbl>     <dbl>    <dbl> #>  1  1990 Seagrasses 25218. 23279.  1988 Subtidal  40000 40000     1939.        2 #>  2  1990 Tidal Fla… 20433. 21686.  1988 Subtidal  16220 16220    -1253.        2 #>  3  1992 Seagrasses 25746. 25218.  1990 Subtidal  40000 40000      528.        2 #>  4  1992 Tidal Fla… 20594. 20433.  1990 Subtidal  16220 16220      161.        2 #>  5  1994 Seagrasses 26524. 25746.  1992 Subtidal  40000 40000      778.        2 #>  6  1994 Tidal Fla… 20244. 20594.  1992 Subtidal  16220 16220     -349.        2 #>  7  1996 Seagrasses 26924. 26524.  1994 Subtidal  40000 40000      400.        2 #>  8  1996 Tidal Fla… 20443. 20244.  1994 Subtidal  16220 16220      199.        2 #>  9  1999 Seagrasses 24840. 26924.  1996 Subtidal  40000 40000    -2083.        3 #> 10  1999 Tidal Fla… 27085. 20443.  1996 Subtidal  16220 16220     6642.        3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate <dbl>, targetrate <dbl>, goalrate <dbl>, #> #   targetprop <dbl>, goalprop <dbl>, targeteval <dbl>, goaleval <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"Estimate hydrological estimates adjustment factors bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"anlz_hydroload(yrs, noaa_key = NULL, trace = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"yrs numeric vector indicating years return noaa_key user-supplied NOAA key, see details trace logical indicating function progress printed consol","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"data frame hydrological load estimates bay segments requested years","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"function uses rainfall streamflow data NOAA USGS requires API key.  See \"Authentication\" section help file ncdc defunct rnoaa package.  key can added R environment file called later use, see examples. estimates used annual compliance assessment reports produced Tampa Bay Nitrogen Management Consortium. Load estimates adjustment factors based regression models https://drive.google.com/file/d/11NT0NQ2WbPO6pVZaD7P7Z6qjcwO1jxHw/view?usp=drivesdk","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"if (FALSE) { # \\dontrun{ # this function requires an API key # save it to the R environment file (only once) # save the key, do only once cat(\"NOAA_KEY=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX\\n\",    file=file.path(normalizePath(\"~/\"), \".Renviron\"),    append=TRUE)  # retrieve the key after saving, may need to restart R noaa_key <- Sys.getenv('NOAA_key')  # get estimates for 2021 anlz_hydroload(2021, noaa_key)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"Format raw IWR data — anlz_iwrraw","title":"Format raw IWR data — anlz_iwrraw","text":"Format raw IWR data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format raw IWR data — anlz_iwrraw","text":"iwrraw FDEP impaired waters rule data base data.frame tidalcreeks sf object population tidal creeks yr numeric reference year evaluate, scores based ten years data using yr last year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format raw IWR data — anlz_iwrraw","text":"data.frame formatted data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format raw IWR data — anlz_iwrraw","text":"function subsets raw IWR data ten years starting value yr subsets creek population tidalcreeks. Select water quality parameters masterCode filtered names combined continuity.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023) #>        wbid class   JEI year       date masterCode        result rCode #> 1      2052    3M  CC01 2014 2014-03-03      CHLAC  0.5877866649  <NA> #> 2      2052    3M  CC01 2014 2014-03-03      COLOR  0.9162907319     U #> 3      2052    3M  CC01 2014 2014-03-03      DOSAT  4.1835756960     + #> 4      2052    3M  CC01 2014 2014-03-03       NO23 -5.5214609179     U #> 5      2052    3M  CC01 2014 2014-03-03      SALIN  3.5292973843  <NA> #> 6      2052    3M  CC01 2014 2014-03-03        TKN -0.6733445533  <NA> #> 7      2052    3M  CC01 2014 2014-03-03         TN -0.6694306539     + #> 8      2052    3M  CC01 2014 2014-03-03         TP -2.7968814148  <NA> #> 9      2052    3M  CC01 2014 2014-03-03       TURB  1.2527629685  <NA> #> 10     2052    3M  CC01 2014 2014-04-07      CHLAC  0.2623642645     I #> 11     2052    3M  CC01 2014 2014-04-07      COLOR  0.9162907319     U #> 12     2052    3M  CC01 2014 2014-04-07         DO  1.3862943611  <NA> #> 13     2052    3M  CC01 2014 2014-04-07      DOSAT  4.0656020934     + #> 14     2052    3M  CC01 2014 2014-04-07       NO23 -5.2983173665     I #> 15     2052    3M  CC01 2014 2014-04-07      SALIN  3.5582011305  <NA> #> 16     2052    3M  CC01 2014 2014-04-07        TKN -0.6733445533  <NA> #> 17     2052    3M  CC01 2014 2014-04-07         TN -0.6655320135     + #> 18     2052    3M  CC01 2014 2014-04-07         TP -2.6882475738  <NA> #> 19     2052    3M  CC01 2014 2014-04-07       TURB  0.7884573604  <NA> #> 20     2052    3M  CC01 2014 2014-05-05      CHLAC  0.8754687374  <NA> #> 21     2052    3M  CC01 2014 2014-05-05      COLOR  3.4011973817  <NA> #> 22     2052    3M  CC01 2014 2014-05-05         DO  1.5040773968  <NA> #> 23     2052    3M  CC01 2014 2014-05-05      DOSAT  4.1399550735     + #> 24     2052    3M  CC01 2014 2014-05-05       NO23 -4.7105307016     I #> 25     2052    3M  CC01 2014 2014-05-05      SALIN  3.3032169733  <NA> #> 26     2052    3M  CC01 2014 2014-05-05        TKN -0.3856624808  <NA> #> 27     2052    3M  CC01 2014 2014-05-05         TN -0.3797973614     + #> 28     2052    3M  CC01 2014 2014-05-05         TP -2.2072749132  <NA> #> 29     2052    3M  CC01 2014 2014-05-05       TURB  1.2237754316     A #> 30     2052    3M  CC01 2014 2014-06-02      CHLAC  0.8754687374  <NA> #> 31     2052    3M  CC01 2014 2014-06-02      COLOR  2.7080502011  <NA> #> 32     2052    3M  CC01 2014 2014-06-02         DO  0.9555114450  <NA> #> 33     2052    3M  CC01 2014 2014-06-02      DOSAT  3.6635616461     + #> 34     2052    3M  CC01 2014 2014-06-02       NO23 -4.9618451299     I #> 35     2052    3M  CC01 2014 2014-06-02      SALIN  3.4719664526  <NA> #> 36     2052    3M  CC01 2014 2014-06-02        TKN -0.6348782724  <NA> #> 37     2052    3M  CC01 2014 2014-06-02         TN -0.6273594400     + #> 38     2052    3M  CC01 2014 2014-06-02         TP -2.6592600369  <NA> #> 39     2052    3M  CC01 2014 2014-06-02       TURB  0.7419373447  <NA> #> 40     2052    3M  CC01 2014 2014-07-07      CHLAC  1.0986122887  <NA> #> 41     2052    3M  CC01 2014 2014-07-07      COLOR  2.2512917986  <NA> #> 42     2052    3M  CC01 2014 2014-07-07         DO  1.4350845253  <NA> #> 43     2052    3M  CC01 2014 2014-07-07       NO23 -5.5214609179     U #> 44     2052    3M  CC01 2014 2014-07-07        TKN -0.5621189182  <NA> #> 45     2052    3M  CC01 2014 2014-07-07         TN -0.5586162876     + #> 46     2052    3M  CC01 2014 2014-07-07         TP -2.9565115604  <NA> #> 47     2052    3M  CC01 2014 2014-07-07       TURB  1.0986122887  <NA> #> 48     2052    3M  CC01 2014 2014-08-04      CHLAC  1.0296194172  <NA> #> 49     2052    3M  CC01 2014 2014-08-04      COLOR  2.3025850930  <NA> #> 50     2052    3M  CC01 2014 2014-08-04         DO  1.0647107370  <NA> #> 51     2052    3M  CC01 2014 2014-08-04      DOSAT  3.8543938926     + #> 52     2052    3M  CC01 2014 2014-08-04       NO23 -5.5214609179     U #> 53     2052    3M  CC01 2014 2014-08-04      SALIN  3.5292973843  <NA> #> 54     2052    3M  CC01 2014 2014-08-04         TN -0.4748151862     + #> 55     2052    3M  CC01 2014 2014-08-04       TURB  0.5877866649  <NA> #> 56     2052    3M  CC01 2014 2014-09-08      CHLAC  1.4350845253  <NA> #> 57     2052    3M  CC01 2014 2014-09-08      COLOR  2.8332133441  <NA> #> 58     2052    3M  CC01 2014 2014-09-08         DO  0.8329091229  <NA> #> 59     2052    3M  CC01 2014 2014-09-08      DOSAT  3.5779478934     + #> 60     2052    3M  CC01 2014 2014-09-08       NO23 -4.7105307016     I #> 61     2052    3M  CC01 2014 2014-09-08      SALIN  3.4965075615  <NA> #> 62     2052    3M  CC01 2014 2014-09-08        TKN -0.3424903089  <NA> #> 63     2052    3M  CC01 2014 2014-09-08         TN -0.3368723166     + #> 64     2052    3M  CC01 2014 2014-09-08         TP -2.7030626596  <NA> #> 65     2052    3M  CC01 2014 2014-09-08       TURB  0.4700036292  <NA> #> 66     2052    3M  CC01 2014 2014-10-06      CHLAC  1.1314021115  <NA> #> 67     2052    3M  CC01 2014 2014-10-06      COLOR  5.2470240722  <NA> #> 68     2052    3M  CC01 2014 2014-10-06      DOSAT  4.1141471895     + #> 69     2052    3M  CC01 2014 2014-10-06       NO23 -3.8167128256  <NA> #> 70     2052    3M  CC01 2014 2014-10-06      SALIN  2.0918640617  <NA> #> 71     2052    3M  CC01 2014 2014-10-06        TKN  0.0953101798  <NA> #> 72     2052    3M  CC01 2014 2014-10-06         TN  0.1151128071     + #> 73     2052    3M  CC01 2014 2014-10-06         TP -2.3025850930  <NA> #> 74     2052    3M  CC01 2014 2014-10-06       TURB  0.3364722366  <NA> #> 75     2052    3M  CC01 2014 2014-11-03      CHLAC  0.7884573604     A #> 76     2052    3M  CC01 2014 2014-11-03      COLOR  3.5263605246     A #> 77     2052    3M  CC01 2014 2014-11-03      DOSAT  4.8698394841     + #> 78     2052    3M  CC01 2014 2014-11-03       NO23 -4.4228486292  <NA> #> 79     2052    3M  CC01 2014 2014-11-03      SALIN  3.2425923515  <NA> #> 80     2052    3M  CC01 2014 2014-11-03        TKN -0.5276327421  <NA> #> 81     2052    3M  CC01 2014 2014-11-03         TN -0.5074978337     + #> 82     2052    3M  CC01 2014 2014-11-03         TP -2.7806208939  <NA> #> 83     2052    3M  CC01 2014 2014-11-03       TURB  0.1823215568  <NA> #> 84     2052    3M  CC01 2014 2014-12-01      CHLAC  0.5877866649  <NA> #> 85     2052    3M  CC01 2014 2014-12-01      COLOR  2.7725887222     A #> 86     2052    3M  CC01 2014 2014-12-01      DOSAT  4.4272389775     + #> 87     2052    3M  CC01 2014 2014-12-01       NO23 -4.3428059215  <NA> #> 88     2052    3M  CC01 2014 2014-12-01      SALIN  3.3178157727  <NA> #> 89     2052    3M  CC01 2014 2014-12-01        TKN -0.6539264674  <NA> #> 90     2052    3M  CC01 2014 2014-12-01         TN -0.6292338548     + #> 91     2052    3M  CC01 2014 2014-12-01         TP -2.9187712324  <NA> #> 92     2052    3M  CC01 2014 2014-12-01       TURB  0.4700036292  <NA> #> 93     2052    3M  CC01 2015 2015-01-05      CHLAC  0.9932517730  <NA> #> 94     2052    3M  CC01 2015 2015-01-05      COLOR  1.8405496334  <NA> #> 95     2052    3M  CC01 2015 2015-01-05         DO  1.5260563035  <NA> #> 96     2052    3M  CC01 2015 2015-01-05      DOSAT  4.1835756960     + #> 97     2052    3M  CC01 2015 2015-01-05       NO23 -4.9618451299     I #> 98     2052    3M  CC01 2015 2015-01-05      SALIN  3.5438536821  <NA> #> 99     2052    3M  CC01 2015 2015-01-05        TKN -0.8675005677  <NA> #> 100    2052    3M  CC01 2015 2015-01-05         TN -0.8580218238     + #> 101    2052    3M  CC01 2015 2015-01-05         TP -2.6310891600  <NA> #> 102    2052    3M  CC01 2015 2015-01-05       TURB  0.7419373447  <NA> #> 103    2052    3M  CC01 2015 2015-02-02      CHLAC  0.4700036292     I #> 104    2052    3M  CC01 2015 2015-02-02      COLOR  0.9162907319     U #> 105    2052    3M  CC01 2015 2015-02-02         DO  1.7578579176  <NA> #> 106    2052    3M  CC01 2015 2015-02-02      DOSAT  4.3333614627     + #> 107    2052    3M  CC01 2015 2015-02-02       NO23 -5.2983173665     I #> 108    2052    3M  CC01 2015 2015-02-02      SALIN  3.5055573970  <NA> #> 109    2052    3M  CC01 2015 2015-02-02        TKN -1.4696759701     I #> 110    2052    3M  CC01 2015 2015-02-02         TN -1.8078888512     + #> 111    2052    3M  CC01 2015 2015-02-02         TP -3.0365542681  <NA> #> 112    2052    3M  CC01 2015 2015-02-02       TURB  0.6418538862  <NA> #> 113    2052    3M  CC01 2015 2015-04-06      CHLAC  0.8329091229  <NA> #> 114    2052    3M  CC01 2015 2015-04-06      COLOR  2.1162555148  <NA> #> 115    2052    3M  CC01 2015 2015-04-06         DO  1.2237754316  <NA> #> 116    2052    3M  CC01 2015 2015-04-06      DOSAT  3.9180050771     + #> 117    2052    3M  CC01 2015 2015-04-06       NO23 -5.5214609179     U #> 118    2052    3M  CC01 2015 2015-04-06      SALIN  3.5582011305  <NA> #> 119    2052    3M  CC01 2015 2015-04-06        TKN -0.6733445533  <NA> #> 120    2052    3M  CC01 2015 2015-04-06         TN -0.6694306539     + #> 121    2052    3M  CC01 2015 2015-04-06         TP -2.8134107168  <NA> #> 122    2052    3M  CC01 2015 2015-04-06       TURB  0.6931471806  <NA> #> 123    2052    3M  CC01 2015 2015-05-04      CHLAC  0.7884573604  <NA> #> 124    2052    3M  CC01 2015 2015-05-04      COLOR  2.1041341543  <NA> #> 125    2052    3M  CC01 2015 2015-05-04         DO  1.4586150227  <NA> #> 126    2052    3M  CC01 2015 2015-05-04      DOSAT  4.1157798429     + #> 127    2052    3M  CC01 2015 2015-05-04       NO23 -5.5214609179     U #> 128    2052    3M  CC01 2015 2015-05-04      SALIN  3.5292973843  <NA> #> 129    2052    3M  CC01 2015 2015-05-04        TKN -1.0216512475     I #> 130    2052    3M  CC01 2015 2015-05-04         TN -1.8201589437     + #> 131    2052    3M  CC01 2015 2015-05-04         TP -3.0159349809  <NA> #> 132    2052    3M  CC01 2015 2015-05-04       TURB  0.8754687374  <NA> #> 133    2052    3M  CC01 2015 2015-08-03      CHLAC  1.4586150227  <NA> #> 134    2052    3M  CC01 2015 2015-08-03      COLOR  5.3936275464  <NA> #> 135    2052    3M  CC01 2015 2015-08-03         DO  1.0647107370  <NA> #> 136    2052    3M  CC01 2015 2015-08-03      DOSAT  3.6506582413     + #> 137    2052    3M  CC01 2015 2015-08-03       NO23 -4.4228486292  <NA> #> 138    2052    3M  CC01 2015 2015-08-03      SALIN  2.2617630985  <NA> #> 139    2052    3M  CC01 2015 2015-08-03        TKN  1.2809338455  <NA> #> 140    2052    3M  CC01 2015 2015-08-03         TN  1.2842616356     + #> 141    2052    3M  CC01 2015 2015-08-03         TP -2.2072749132  <NA> #> 142    2052    3M  CC01 2015 2015-08-03       TURB  0.4700036292  <NA> #> 143    2052    3M  CC01 2015 2015-09-08      CHLAC  1.6292405397  <NA> #> 144    2052    3M  CC01 2015 2015-09-08      COLOR  4.4773368145  <NA> #> 145    2052    3M  CC01 2015 2015-09-08         DO  1.3350010667  <NA> #> 146    2052    3M  CC01 2015 2015-09-08      DOSAT  3.9454577815     + #> 147    2052    3M  CC01 2015 2015-09-08       NO23 -4.2686979494  <NA> #> 148    2052    3M  CC01 2015 2015-09-08      SALIN  1.7227665977  <NA> #> 149    2052    3M  CC01 2015 2015-09-08        TKN -0.1984509387  <NA> #> 150    2052    3M  CC01 2015 2015-09-08         TN -0.1815218766     + #> 151    2052    3M  CC01 2015 2015-09-08         TP -2.4418471603  <NA> #> 152    2052    3M  CC01 2015 2015-09-08       TURB  0.6931471806  <NA> #> 153    2052    3M  CC01 2015 2015-10-05      CHLAC  0.5877866649  <NA> #> 154    2052    3M  CC01 2015 2015-10-05      COLOR  5.0751738152  <NA> #> 155    2052    3M  CC01 2015 2015-10-05         DO  1.2237754316  <NA> #> 156    2052    3M  CC01 2015 2015-10-05      DOSAT  3.7977338590     + #> 157    2052    3M  CC01 2015 2015-10-05       NO23 -3.4112477175  <NA> #> 158    2052    3M  CC01 2015 2015-10-05      SALIN  2.1282317058  <NA> #> 159    2052    3M  CC01 2015 2015-10-05        TKN  0.0953101798  <NA> #> 160    2052    3M  CC01 2015 2015-10-05         TN  0.1248689820     + #> 161    2052    3M  CC01 2015 2015-10-05         TP -1.9661128564  <NA> #> 162    2052    3M  CC01 2015 2015-10-05       TURB  0.1823215568  <NA> #> 163    2052    3M  CC01 2015 2015-12-07      CHLAC  1.0296194172  <NA> #> 164    2052    3M  CC01 2015 2015-12-07      COLOR  2.7725887222  <NA> #> 165    2052    3M  CC01 2015 2015-12-07         DO  1.5686159179  <NA> #> 166    2052    3M  CC01 2015 2015-12-07      DOSAT  4.1743872699     + #> 167    2052    3M  CC01 2015 2015-12-07       NO23 -3.9633162998  <NA> #> 168    2052    3M  CC01 2015 2015-12-07      SALIN  3.3499040873  <NA> #> 169    2052    3M  CC01 2015 2015-12-07        TKN -0.6348782724  <NA> #> 170    2052    3M  CC01 2015 2015-12-07         TN -0.5996568375     + #> 171    2052    3M  CC01 2015 2015-12-07         TP -2.5010360317  <NA> #> 172    2052    3M  CC01 2015 2015-12-07       TURB  0.4700036292  <NA> #> 173    2052    3M  CC01 2016 2016-02-01      CHLAC  0.5306282511  <NA> #> 174    2052    3M  CC01 2016 2016-02-01      COLOR  4.6051701860  <NA> #> 175    2052    3M  CC01 2016 2016-02-01         DO  1.6863989536  <NA> #> 176    2052    3M  CC01 2016 2016-02-01      DOSAT  4.1383614476     + #> 177    2052    3M  CC01 2016 2016-02-01       NO23 -3.5755507688  <NA> #> 178    2052    3M  CC01 2016 2016-02-01      SALIN  2.6100697927  <NA> #> 179    2052    3M  CC01 2016 2016-02-01        TKN -0.2357223335  <NA> #> 180    2052    3M  CC01 2016 2016-02-01         TN -0.2008929424     + #> 181    2052    3M  CC01 2016 2016-02-01         TP -2.3751557858  <NA> #> 182    2052    3M  CC01 2016 2016-02-01       TURB  0.7419373447  <NA> #> 183    2052    3M  CC01 2016 2016-03-07      CHLAC  0.7419373447  <NA> #> 184    2052    3M  CC01 2016 2016-03-07      COLOR  3.5263605246  <NA> #> 185    2052    3M  CC01 2016 2016-03-07         DO  1.6486586256  <NA> #> 186    2052    3M  CC01 2016 2016-03-07      DOSAT  4.1588830834     + #> 187    2052    3M  CC01 2016 2016-03-07       NO23 -4.9618451299     I #> 188    2052    3M  CC01 2016 2016-03-07      SALIN  2.9957322736  <NA> #> 189    2052    3M  CC01 2016 2016-03-07        TKN -0.5108256238  <NA> #> 190    2052    3M  CC01 2016 2016-03-07         TN -0.5041810810     + #> 191    2052    3M  CC01 2016 2016-03-07         TP -2.4418471603  <NA> #> 192    2052    3M  CC01 2016 2016-03-07       TURB  1.1939224685  <NA> #> 193    2052    3M  CC01 2016 2016-04-04      CHLAC  0.9162907319  <NA> #> 194    2052    3M  CC01 2016 2016-04-04      COLOR  2.5649493575  <NA> #> 195    2052    3M  CC01 2016 2016-04-04         DO  1.4109869737  <NA> #> 196    2052    3M  CC01 2016 2016-04-04      DOSAT  4.0289167569     + #> 197    2052    3M  CC01 2016 2016-04-04       NO23 -4.3428059215  <NA> #> 198    2052    3M  CC01 2016 2016-04-04      SALIN  3.3068867022  <NA> #> 199    2052    3M  CC01 2016 2016-04-04        TKN -0.5108256238  <NA> #> 200    2052    3M  CC01 2016 2016-04-04         TN -0.4893903430     + #> 201    2052    3M  CC01 2016 2016-04-04         TP -2.4534079827  <NA> #> 202    2052    3M  CC01 2016 2016-04-04       TURB  0.9162907319  <NA> #> 203    2052    3M  CC01 2016 2016-05-02      CHLAC  0.4054651081     I #> 204    2052    3M  CC01 2016 2016-05-02      COLOR  2.0149030205  <NA> #> 205    2052    3M  CC01 2016 2016-05-02         DO  1.1939224685  <NA> #> 206    2052    3M  CC01 2016 2016-05-02      DOSAT  3.9298629236     + #> 207    2052    3M  CC01 2016 2016-05-02       NO23 -5.5214609179     U #> 208    2052    3M  CC01 2016 2016-05-02      SALIN  3.5085559000  <NA> #> 209    2052    3M  CC01 2016 2016-05-02        TKN -1.0498221245     I #> 210    2052    3M  CC01 2016 2016-05-02         TN -1.8201589437     + #> 211    2052    3M  CC01 2016 2016-05-02         TP -2.4534079827  <NA> #> 212    2052    3M  CC01 2016 2016-05-02       TURB  0.3364722366  <NA> #> 213    2052    3M  CC01 2016 2016-07-05      CHLAC  0.7419373447  <NA> #> 214    2052    3M  CC01 2016 2016-07-05      COLOR  3.1780538303  <NA> #> 215    2052    3M  CC01 2016 2016-07-05         DO  0.9555114450  <NA> #> 216    2052    3M  CC01 2016 2016-07-05      DOSAT  3.7013019741     + #> 217    2052    3M  CC01 2016 2016-07-05       NO23 -5.5214609179     I #> 218    2052    3M  CC01 2016 2016-07-05      SALIN  3.4078419244  <NA> #> 219    2052    3M  CC01 2016 2016-07-05        TKN -0.5621189182  <NA> #> 220    2052    3M  CC01 2016 2016-07-05         TN -0.5551258827     + #> 221    2052    3M  CC01 2016 2016-07-05         TP -2.3434070875  <NA> #> 222    2052    3M  CC01 2016 2016-07-05       TURB  0.5306282511  <NA> #> 223    2052    3M  CC01 2016 2016-08-01      CHLAC  0.9555114450  <NA> #> 224    2052    3M  CC01 2016 2016-08-01      COLOR  3.1354942159  <NA> #> 225    2052    3M  CC01 2016 2016-08-01         DO  1.2527629685  <NA> #> 226    2052    3M  CC01 2016 2016-08-01      DOSAT  3.9926809084     + #> 227    2052    3M  CC01 2016 2016-08-01       NO23 -4.4228486292  <NA> #> 228    2052    3M  CC01 2016 2016-08-01      SALIN  3.3178157727  <NA> #> 229    2052    3M  CC01 2016 2016-08-01        TKN -0.5276327421  <NA> #> 230    2052    3M  CC01 2016 2016-08-01         TN -0.5074978337     + #> 231    2052    3M  CC01 2016 2016-08-01         TP -2.5510464523  <NA> #> 232    2052    3M  CC01 2016 2016-08-01       TURB  0.2623642645  <NA> #> 233    2052    3M  CC01 2016 2016-10-03      CHLAC  1.5686159179  <NA> #> 234    2052    3M  CC01 2016 2016-10-03      COLOR  3.7135720667  <NA> #> 235    2052    3M  CC01 2016 2016-10-03         DO  1.3083328197  <NA> #> 236    2052    3M  CC01 2016 2016-10-03      DOSAT  3.9982007017     + #> 237    2052    3M  CC01 2016 2016-10-03       NO23 -4.9618451299     I #> 238    2052    3M  CC01 2016 2016-10-03      SALIN  3.1223649245  <NA> #> 239    2052    3M  CC01 2016 2016-10-03        TKN -0.2613647641  <NA> #> 240    2052    3M  CC01 2016 2016-10-03         TN -0.2561834054     + #> 241    2052    3M  CC01 2016 2016-10-03         TP -2.3025850930  <NA> #> 242    2052    3M  CC01 2016 2016-10-03       TURB  0.9555114450  <NA> #> 243    2052    3M  CC01 2016 2016-11-07      CHLAC  1.0296194172  <NA> #> 244    2052    3M  CC01 2016 2016-11-07      COLOR  1.8082887712  <NA> #> 245    2052    3M  CC01 2016 2016-11-07         DO  1.3862943611  <NA> #> 246    2052    3M  CC01 2016 2016-11-07      DOSAT  4.0289167569     + #> 247    2052    3M  CC01 2016 2016-11-07       NO23 -4.6051701860  <NA> #> 248    2052    3M  CC01 2016 2016-11-07      SALIN  3.4531571206  <NA> #> 249    2052    3M  CC01 2016 2016-11-07        TKN -0.4462871026  <NA> #> 250    2052    3M  CC01 2016 2016-11-07         TN -0.4307829161     + #> 251    2052    3M  CC01 2016 2016-11-07         TP -2.5639498571  <NA> #> 252    2052    3M  CC01 2016 2016-11-07       TURB  0.8754687374  <NA> #> 253    2052    3M  CC01 2016 2016-12-05      CHLAC  0.4700036292     I #> 254    2052    3M  CC01 2016 2016-12-05      COLOR  2.0149030205     U #> 255    2052    3M  CC01 2016 2016-12-05         DO  1.5892352051  <NA> #> 256    2052    3M  CC01 2016 2016-12-05      DOSAT  4.2456340098     + #> 257    2052    3M  CC01 2016 2016-12-05       NO23 -4.9618451299     I #> 258    2052    3M  CC01 2016 2016-12-05      SALIN  3.5467396870  <NA> #> 259    2052    3M  CC01 2016 2016-12-05        TKN -0.7765287895  <NA> #> 260    2052    3M  CC01 2016 2016-12-05         TN -0.7678707268     + #> 261    2052    3M  CC01 2016 2016-12-05         TP -2.8824035882  <NA> #> 262    2052    3M  CC01 2016 2016-12-05       TURB  0.7884573604  <NA> #> 263    2052    3M  CC01 2017 2017-02-06      CHLAC  0.7419373447  <NA> #> 264    2052    3M  CC01 2017 2017-02-06      COLOR  1.3609765531     I #> 265    2052    3M  CC01 2017 2017-02-06         DO  1.3862943611  <NA> #> 266    2052    3M  CC01 2017 2017-02-06      DOSAT  3.9889840466     + #> 267    2052    3M  CC01 2017 2017-02-06       NO23 -4.1997050779  <NA> #> 268    2052    3M  CC01 2017 2017-02-06      SALIN  3.5204608025  <NA> #> 269    2052    3M  CC01 2017 2017-02-06        TKN -0.6539264674  <NA> #> 270    2052    3M  CC01 2017 2017-02-06         TN -0.6254885321     + #> 271    2052    3M  CC01 2017 2017-02-06         TP -2.8473122684  <NA> #> 272    2052    3M  CC01 2017 2017-02-06       TURB  0.7419373447  <NA> #> 273    2052    3M  CC01 2017 2017-04-03      CHLAC  0.3364722366     I #> 274    2052    3M  CC01 2017 2017-04-03      COLOR  0.9162907319     U #> 275    2052    3M  CC01 2017 2017-04-03         DO  1.2237754316  <NA> #> 276    2052    3M  CC01 2017 2017-04-03      DOSAT  3.9357395320     + #> 277    2052    3M  CC01 2017 2017-04-03       NO23 -5.5214609179     U #> 278    2052    3M  CC01 2017 2017-04-03      SALIN  3.5610460826  <NA> #> 279    2052    3M  CC01 2017 2017-04-03        TKN -0.5978370008  <NA> #> 280    2052    3M  CC01 2017 2017-04-03         TN -0.5942072327     + #> 281    2052    3M  CC01 2017 2017-04-03         TP -2.7181005370  <NA> #> 282    2052    3M  CC01 2017 2017-04-03       TURB  0.7419373447  <NA> #> 283    2052    3M  CC01 2017 2017-06-05      SALIN  3.4242626546  <NA> #> 284    2052    3M  CC01 2017 2017-06-05         DO  0.8241754430  <NA> #> 285    2052    3M  CC01 2017 2017-06-05      DOSAT  3.4210000090     + #> 286    2052    3M  CC01 2017 2017-06-05      SALIN  2.2533948488  <NA> #> 287    2052    3M  CC01 2017 2017-06-05      CHLAC  0.4054651081     I #> 288    2052    3M  CC01 2017 2017-06-05      COLOR  1.9878743482  <NA> #> 289    2052    3M  CC01 2017 2017-06-05         DO  1.2527629685  <NA> #> 290    2052    3M  CC01 2017 2017-06-05      DOSAT  4.0360089852     + #> 291    2052    3M  CC01 2017 2017-06-05       NO23 -4.9618451299     I #> 292    2052    3M  CC01 2017 2017-06-05      SALIN  3.6506582413  <NA> #> 293    2052    3M  CC01 2017 2017-06-05        TKN -0.6539264674  <NA> #> 294    2052    3M  CC01 2017 2017-06-05         TN -0.6462635947     + #> 295    2052    3M  CC01 2017 2017-06-05         TP -2.8473122684  <NA> #> 296    2052    3M  CC01 2017 2017-06-05       TURB  0.2623642645  <NA> #> 297    2052    3M  CC01 2017 2017-06-05         DO  1.4655675420  <NA> #> 298    2052    3M  CC01 2017 2017-06-05      DOSAT  4.1866198383     + #> 299    2052    3M  CC01 2017 2017-06-05      SALIN  3.5115454388  <NA> #> 300    2052    3M  CC01 2017 2017-07-10      CHLAC  0.9162907319  <NA> #> 301    2052    3M  CC01 2017 2017-07-10      COLOR  3.7376696183     A #> 302    2052    3M  CC01 2017 2017-07-10         DO  1.9021075264  <NA> #> 303    2052    3M  CC01 2017 2017-07-10      DOSAT  4.6482296754     + #> 304    2052    3M  CC01 2017 2017-07-10       NO23 -5.5214609179     I #> 305    2052    3M  CC01 2017 2017-07-10      SALIN  3.3214324132  <NA> #> 306    2052    3M  CC01 2017 2017-07-10        TKN -0.3566749439  <NA> #> 307    2052    3M  CC01 2017 2017-07-10         TN -0.3509769228     + #> 308    2052    3M  CC01 2017 2017-07-10         TP -2.4418471603  <NA> #> 309    2052    3M  CC01 2017 2017-07-10       TURB  0.4700036292  <NA> #> 310    2052    3M  CC01 2017 2017-09-05      CHLAC  2.7725887222  <NA> #> 311    2052    3M  CC01 2017 2017-09-05      COLOR  5.2470240722  <NA> #> 312    2052    3M  CC01 2017 2017-09-05         DO  1.4350845253  <NA> #> 313    2052    3M  CC01 2017 2017-09-05      DOSAT  4.0517849478     + #> 314    2052    3M  CC01 2017 2017-09-05       NO23 -4.1351665567  <NA> #> 315    2052    3M  CC01 2017 2017-09-05      SALIN  2.1282317058  <NA> #> 316    2052    3M  CC01 2017 2017-09-05        TKN  0.1823215568  <NA> #> 317    2052    3M  CC01 2017 2017-09-05         TN  0.1955667835     + #> 318    2052    3M  CC01 2017 2017-09-05         TP -2.1202635362  <NA> #> 319    2052    3M  CC01 2017 2017-09-05       TURB  0.6418538862     A #> 320    2052    3M  CC01 2017 2017-10-02      CHLAC  2.1633230257  <NA> #> 321    2052    3M  CC01 2017 2017-10-02      COLOR  3.8066624898  <NA> #> 322    2052    3M  CC01 2017 2017-10-02       NO23 -4.8283137373     I #> 323    2052    3M  CC01 2017 2017-10-02        TKN -0.5276327421  <NA> #> 324    2052    3M  CC01 2017 2017-10-02         TN -0.5208759596     + #> 325    2052    3M  CC01 2017 2017-10-02         TP -2.3025850930  <NA> #> 326    2052    3M  CC01 2017 2017-10-02       TURB  0.6418538862  <NA> #> 327    2052    3M  CC01 2017 2017-11-06      CHLAC  0.6418538862  <NA> #> 328    2052    3M  CC01 2017 2017-11-06      COLOR  2.5649493575  <NA> #> 329    2052    3M  CC01 2017 2017-11-06         DO  1.6863989536  <NA> #> 330    2052    3M  CC01 2017 2017-11-06      DOSAT  4.3241326563     + #> 331    2052    3M  CC01 2017 2017-11-06       NO23 -4.5098600062  <NA> #> 332    2052    3M  CC01 2017 2017-11-06      SALIN  3.2809112158  <NA> #> 333    2052    3M  CC01 2017 2017-11-06        TKN -0.5108256238  <NA> #> 334    2052    3M  CC01 2017 2017-11-06         TN -0.4926583198     + #> 335    2052    3M  CC01 2017 2017-11-06         TP -2.5770219387  <NA> #> 336    2052    3M  CC01 2017 2017-11-06       TURB  0.4700036292  <NA> #> 337    2052    3M  CC01 2017 2017-12-04      CHLAC  0.4054651081     I #> 338    2052    3M  CC01 2017 2017-12-04      COLOR  2.2512917986  <NA> #> 339    2052    3M  CC01 2017 2017-12-04         DO  1.6486586256  <NA> #> 340    2052    3M  CC01 2017 2017-12-04      DOSAT  4.2835865619     + #> 341    2052    3M  CC01 2017 2017-12-04       NO23 -5.5214609179     I #> 342    2052    3M  CC01 2017 2017-12-04      SALIN  3.4843122884  <NA> #> 343    2052    3M  CC01 2017 2017-12-04        TKN -0.6348782724  <NA> #> 344    2052    3M  CC01 2017 2017-12-04         TN -0.6273594400     + #> 345    2052    3M  CC01 2017 2017-12-04         TP -2.7968814148  <NA> #> 346    2052    3M  CC01 2017 2017-12-04       TURB  0.7419373447  <NA> #> 347    2052    3M  CC01 2018 2018-01-02      CHLAC  0.3364722366     I #> 348    2052    3M  CC01 2018 2018-01-02      COLOR  2.3025850930  <NA> #> 349    2052    3M  CC01 2018 2018-01-02         DO  1.8718021769  <NA> #> 350    2052    3M  CC01 2018 2018-01-02      DOSAT  4.3214801348     + #> 351    2052    3M  CC01 2018 2018-01-02       NO23 -4.6051701860  <NA> #> 352    2052    3M  CC01 2018 2018-01-02      SALIN  3.3214324132  <NA> #> 353    2052    3M  CC01 2018 2018-01-02        TKN -0.7765287895  <NA> #> 354    2052    3M  CC01 2018 2018-01-02         TN -0.7550225843     + #> 355    2052    3M  CC01 2018 2018-01-02         TP -2.6450754019  <NA> #> 356    2052    3M  CC01 2018 2018-01-02       TURB  0.7884573604  <NA> #> 357    2052    3M  CC01 2018 2018-02-05      CHLAC  0.6418538862  <NA> #> 358    2052    3M  CC01 2018 2018-02-05      COLOR  2.1633230257  <NA> #> 359    2052    3M  CC01 2018 2018-02-05         DO  1.9600947840  <NA> #> 360    2052    3M  CC01 2018 2018-02-05      DOSAT  4.5358201079     + #> 361    2052    3M  CC01 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 362    2052    3M  CC01 2018 2018-02-05      SALIN  3.3877743613  <NA> #> 363    2052    3M  CC01 2018 2018-02-05        TKN -0.6348782724  <NA> #> 364    2052    3M  CC01 2018 2018-02-05         TN -0.6051363032     + #> 365    2052    3M  CC01 2018 2018-02-05         TP -2.4304184645  <NA> #> 366    2052    3M  CC01 2018 2018-02-05       TURB  1.8405496334     A #> 367    2052    3M  CC01 2018 2018-03-05      CHLAC  0.3364722366     I #> 368    2052    3M  CC01 2018 2018-03-05      COLOR  1.9459101491  <NA> #> 369    2052    3M  CC01 2018 2018-03-05         DO  2.0412203289  <NA> #> 370    2052    3M  CC01 2018 2018-03-05      DOSAT  4.5890408041     + #> 371    2052    3M  CC01 2018 2018-03-05       NO23 -5.5214609179     U #> 372    2052    3M  CC01 2018 2018-03-05      SALIN  3.4372078192  <NA> #> 373    2052    3M  CC01 2018 2018-03-05        TKN -0.7985076962  <NA> #> 374    2052    3M  CC01 2018 2018-03-05         TN -0.7940730991     + #> 375    2052    3M  CC01 2018 2018-03-05         TP -2.8134107168  <NA> #> 376    2052    3M  CC01 2018 2018-03-05       TURB  0.9932517730  <NA> #> 377    2052    3M  CC01 2018 2018-04-02      CHLAC  0.5306282511     I #> 378    2052    3M  CC01 2018 2018-04-02      COLOR  1.0986122887     I #> 379    2052    3M  CC01 2018 2018-04-02      DOSAT  4.5538768916     + #> 380    2052    3M  CC01 2018 2018-04-02       NO23 -5.5214609179     U #> 381    2052    3M  CC01 2018 2018-04-02      SALIN  3.5025498759  <NA> #> 382    2052    3M  CC01 2018 2018-04-02        TKN -0.7550225843  <NA> #> 383    2052    3M  CC01 2018 2018-04-02         TN -0.7507762934     + #> 384    2052    3M  CC01 2018 2018-04-02         TP -2.8473122684  <NA> #> 385    2052    3M  CC01 2018 2018-04-02       TURB  1.1314021115  <NA> #> 386    2052    3M  CC01 2018 2018-05-07      CHLAC  0.5877866649  <NA> #> 387    2052    3M  CC01 2018 2018-05-07      COLOR  2.1041341543  <NA> #> 388    2052    3M  CC01 2018 2018-05-07         DO  0.8285518176  <NA> #> 389    2052    3M  CC01 2018 2018-05-07      DOSAT  3.5292973843  <NA> #> 390    2052    3M  CC01 2018 2018-05-07       NO23 -5.5214609179     U #> 391    2052    3M  CC01 2018 2018-05-07      SALIN  3.5743099994  <NA> #> 392    2052    3M  CC01 2018 2018-05-07        TKN -0.5621189182  <NA> #> 393    2052    3M  CC01 2018 2018-05-07         TN -0.5586162876     + #> 394    2052    3M  CC01 2018 2018-05-07         TP -2.6310891600  <NA> #> 395    2052    3M  CC01 2018 2018-05-07       TURB  0.7884573604  <NA> #> 396    2052    3M  CC01 2018 2018-07-09      CHLAC  0.9932517730  <NA> #> 397    2052    3M  CC01 2018 2018-07-09      COLOR  4.1743872699  <NA> #> 398    2052    3M  CC01 2018 2018-07-09         DO  1.1216775616  <NA> #> 399    2052    3M  CC01 2018 2018-07-09      DOSAT  3.9140210081  <NA> #> 400    2052    3M  CC01 2018 2018-07-09       NO23 -4.6051701860  <NA> #> 401    2052    3M  CC01 2018 2018-07-09      SALIN  3.4339872045  <NA> #> 402    2052    3M  CC01 2018 2018-07-09        TKN -0.2231435513  <NA> #> 403    2052    3M  CC01 2018 2018-07-09         TN -0.2107210313     + #> 404    2052    3M  CC01 2018 2018-07-09         TP -2.3025850930  <NA> #> 405    2052    3M  CC01 2018 2018-07-09       TURB  0.4054651081  <NA> #> 406    2052    3M  CC01 2018 2018-08-06      CHLAC  1.1939224685  <NA> #> 407    2052    3M  CC01 2018 2018-08-06      COLOR  3.4011973817  <NA> #> 408    2052    3M  CC01 2018 2018-08-06         DO  0.8153648133  <NA> #> 409    2052    3M  CC01 2018 2018-08-06      DOSAT  3.5945687746  <NA> #> 410    2052    3M  CC01 2018 2018-08-06       NO23 -4.8283137373     I #> 411    2052    3M  CC01 2018 2018-08-06      SALIN  3.4534735262  <NA> #> 412    2052    3M  CC01 2018 2018-08-06        TKN -0.2231435513  <NA> #> 413    2052    3M  CC01 2018 2018-08-06         TN -0.2181560098     + #> 414    2052    3M  CC01 2018 2018-08-06         TP -2.5257286443  <NA> #> 415    2052    3M  CC01 2018 2018-08-06       TURB  0.3364722366  <NA> #> 416    2052    3M  CC01 2019 2019-02-04      CHLAC -0.3285040670     I #> 417    2052    3M  CC01 2019 2019-02-04      COLOR  3.4339872045  <NA> #> 418    2052    3M  CC01 2019 2019-02-04         DO  1.6213664833  <NA> #> 419    2052    3M  CC01 2019 2019-02-04      DOSAT  4.1431347264  <NA> #> 420    2052    3M  CC01 2019 2019-02-04       NO23 -3.7297014486  <NA> #> 421    2052    3M  CC01 2019 2019-02-04      SALIN  3.1805507105  <NA> #> 422    2052    3M  CC01 2019 2019-02-04        TKN -0.5978370008  <NA> #> 423    2052    3M  CC01 2019 2019-02-04         TN -0.5551258827     + #> 424    2052    3M  CC01 2019 2019-02-04         TP -2.5902671654  <NA> #> 425    2052    3M  CC01 2019 2019-02-04       TURB  0.5306282511  <NA> #> 426    2052    3M  CC01 2019 2019-03-04      CHLAC  0.4054651081     I #> 427    2052    3M  CC01 2019 2019-03-04      COLOR  2.7080502011  <NA> #> 428    2052    3M  CC01 2019 2019-03-04         DO  1.2781522025  <NA> #> 429    2052    3M  CC01 2019 2019-03-04      DOSAT  3.9531649488  <NA> #> 430    2052    3M  CC01 2019 2019-03-04       NO23 -4.8283137373     I #> 431    2052    3M  CC01 2019 2019-03-04        TKN -0.7985076962  <NA> #> 432    2052    3M  CC01 2019 2019-03-04         TN -0.7896580809     + #> 433    2052    3M  CC01 2019 2019-03-04         TP -2.6172958378  <NA> #> 434    2052    3M  CC01 2019 2019-03-04       TURB  0.4700036292  <NA> #> 435    2052    3M  CC01 2019 2019-04-01      CHLAC  0.9162907319  <NA> #> 436    2052    3M  CC01 2019 2019-04-01      COLOR  2.0014800002  <NA> #> 437    2052    3M  CC01 2019 2019-04-01         DO  1.4883995841  <NA> #> 438    2052    3M  CC01 2019 2019-04-01      DOSAT  4.1620032107  <NA> #> 439    2052    3M  CC01 2019 2019-04-01       NO23 -5.5214609179     I #> 440    2052    3M  CC01 2019 2019-04-01      SALIN  3.4094961845  <NA> #> 441    2052    3M  CC01 2019 2019-04-01        TKN -0.9162907319     I #> 442    2052    3M  CC01 2019 2019-04-01         TN -1.8078888512     + #> 443    2052    3M  CC01 2019 2019-04-01         TP -2.5510464523  <NA> #> 444    2052    3M  CC01 2019 2019-04-01       TURB  0.2623642645  <NA> #> 445    2052    3M  CC01 2019 2019-06-03      CHLAC  0.4700036292     I #> 446    2052    3M  CC01 2019 2019-06-03      COLOR  1.4586150227     I #> 447    2052    3M  CC01 2019 2019-06-03         DO  0.3001045925  <NA> #> 448    2052    3M  CC01 2019 2019-06-03      DOSAT  3.1267605360  <NA> #> 449    2052    3M  CC01 2019 2019-06-03       NO23 -5.5214609179     I #> 450    2052    3M  CC01 2019 2019-06-03      SALIN  3.5871235452  <NA> #> 451    2052    3M  CC01 2019 2019-06-03        TKN -0.7133498879  <NA> #> 452    2052    3M  CC01 2019 2019-06-03         TN -0.7052197618     + #> 453    2052    3M  CC01 2019 2019-06-03         TP -3.1700856607  <NA> #> 454    2052    3M  CC01 2019 2019-06-03       TURB  0.3364722366  <NA> #> 455    2052    3M  CC01 2019 2019-07-01      CHLAC  0.5306282511     I #> 456    2052    3M  CC01 2019 2019-07-01      COLOR  2.2823823857  <NA> #> 457    2052    3M  CC01 2019 2019-07-01         DO  0.9593502213  <NA> #> 458    2052    3M  CC01 2019 2019-07-01      DOSAT  3.7208625000  <NA> #> 459    2052    3M  CC01 2019 2019-07-01       NO23 -5.1159958098     I #> 460    2052    3M  CC01 2019 2019-07-01      SALIN  3.5237099561  <NA> #> 461    2052    3M  CC01 2019 2019-07-01        TKN -0.5978370008  <NA> #> 462    2052    3M  CC01 2019 2019-07-01         TN -0.5905905922     + #> 463    2052    3M  CC01 2019 2019-07-01         TP -2.9957322736  <NA> #> 464    2052    3M  CC01 2019 2019-07-01       TURB  0.4700036292  <NA> #> 465    2052    3M  CC01 2019 2019-10-07      CHLAC  1.8562979904  <NA> #> 466    2052    3M  CC01 2019 2019-10-07      COLOR  1.5260563035     I #> 467    2052    3M  CC01 2019 2019-10-07         DO  1.1755733298  <NA> #> 468    2052    3M  CC01 2019 2019-10-07      DOSAT  3.9120230054  <NA> #> 469    2052    3M  CC01 2019 2019-10-07       NO23 -5.2983173665     I #> 470    2052    3M  CC01 2019 2019-10-07      SALIN  3.5231199856  <NA> #> 471    2052    3M  CC01 2019 2019-10-07        TKN -0.5108256238  <NA> #> 472    2052    3M  CC01 2019 2019-10-07         TN -0.5041810810     + #> 473    2052    3M  CC01 2019 2019-10-07         TP -2.5510464523  <NA> #> 474    2052    3M  CC01 2019 2019-10-07       TURB  0.9555114450  <NA> #> 475    2052    3M  CC01 2019 2019-11-04      CHLAC  1.0986122887  <NA> #> 476    2052    3M  CC01 2019 2019-11-04      COLOR  1.4816045409     I #> 477    2052    3M  CC01 2019 2019-11-04         DO  0.9042181506  <NA> #> 478    2052    3M  CC01 2019 2019-11-04      DOSAT  3.6136169696  <NA> #> 479    2052    3M  CC01 2019 2019-11-04       NO23 -4.5098600062  <NA> #> 480    2052    3M  CC01 2019 2019-11-04      SALIN  3.5010427166  <NA> #> 481    2052    3M  CC01 2019 2019-11-04        TKN -0.5276327421  <NA> #> 482    2052    3M  CC01 2019 2019-11-04         TN -0.5091603444     + #> 483    2052    3M  CC01 2019 2019-11-04         TP -2.6450754019  <NA> #> 484    2052    3M  CC01 2019 2019-11-04       TURB  0.7884573604  <NA> #> 485    2052    3M  CC01 2019 2019-12-02      CHLAC  0.8754687374     I #> 486    2052    3M  CC01 2019 2019-12-02      COLOR  0.9162907319     U #> 487    2052    3M  CC01 2019 2019-12-02       NO23 -5.1159958098     I #> 488    2052    3M  CC01 2019 2019-12-02        TKN -0.7985076962  <NA> #> 489    2052    3M  CC01 2019 2019-12-02         TN -0.7896580809     + #> 490    2052    3M  CC01 2019 2019-12-02         TP -2.9957322736  <NA> #> 491    2052    3M  CC01 2019 2019-12-02       TURB  1.0296194172  <NA> #> 492    2052    3M  CC01 2020 2020-01-06      CHLAC  0.1823215568     I #> 493    2052    3M  CC01 2020 2020-01-06      COLOR  2.3978952728  <NA> #> 494    2052    3M  CC01 2020 2020-01-06         DO  1.8196988379  <NA> #> 495    2052    3M  CC01 2020 2020-01-06      DOSAT  4.3554259529  <NA> #> 496    2052    3M  CC01 2020 2020-01-06       NO23 -3.9120230054  <NA> #> 497    2052    3M  CC01 2020 2020-01-06      SALIN  3.4075107437  <NA> #> 498    2052    3M  CC01 2020 2020-01-06        TKN -0.4942963218  <NA> #> 499    2052    3M  CC01 2020 2020-01-06         TN -0.4620354596     + #> 500    2052    3M  CC01 2020 2020-01-06         TP -2.4889146712  <NA> #> 501    2052    3M  CC01 2020 2020-01-06       TURB  0.5877866649  <NA> #> 502    2052    3M  CC01 2020 2020-02-03      CHLAC  0.4700036292     U #> 503    2052    3M  CC01 2020 2020-02-03      COLOR  1.6677068206     I #> 504    2052    3M  CC01 2020 2020-02-03         DO  1.7647307968  <NA> #> 505    2052    3M  CC01 2020 2020-02-03      DOSAT  4.2959239356  <NA> #> 506    2052    3M  CC01 2020 2020-02-03       NO23 -4.5098600062  <NA> #> 507    2052    3M  CC01 2020 2020-02-03      SALIN  3.4992311219  <NA> #> 508    2052    3M  CC01 2020 2020-02-03        TKN -0.7985076962  <NA> #> 509    2052    3M  CC01 2020 2020-02-03         TN -0.7743572360     + #> 510    2052    3M  CC01 2020 2020-02-03         TP -2.7488721956  <NA> #> 511    2052    3M  CC01 2020 2020-02-03       TURB  0.6931471806  <NA> #> 512    2052    3M  CC01 2020 2020-03-02      CHLAC  0.0953101798     I #> 513    2052    3M  CC01 2020 2020-03-02      COLOR  1.5040773968     I #> 514    2052    3M  CC01 2020 2020-03-02         DO  1.7191887764  <NA> #> 515    2052    3M  CC01 2020 2020-03-02      DOSAT  4.3000027992  <NA> #> 516    2052    3M  CC01 2020 2020-03-02       NO23 -5.5214609179     U #> 517    2052    3M  CC01 2020 2020-03-02      SALIN  3.6730041050  <NA> #> 518    2052    3M  CC01 2020 2020-03-02        TKN -0.9942522733     I #> 519    2052    3M  CC01 2020 2020-03-02         TN -1.8201589437     + #> 520    2052    3M  CC01 2020 2020-03-02         TP -2.8647040111  <NA> #> 521    2052    3M  CC01 2020 2020-03-02       TURB  1.0647107370  <NA> #> 522    2052    3M  CC01 2021 2021-01-04      CHLAC  0.5877866649     I #> 523    2052    3M  CC01 2021 2021-01-04      COLOR  1.6094379124     I #> 524    2052    3M  CC01 2021 2021-01-04       NO23 -4.1997050779  <NA> #> 525    2052    3M  CC01 2021 2021-01-04      SALIN  3.4200191359  <NA> #> 526    2052    3M  CC01 2021 2021-01-04        TKN -0.7339691751  <NA> #> 527    2052    3M  CC01 2021 2021-01-04         TN -0.7031975164     + #> 528    2052    3M  CC01 2021 2021-01-04         TP -2.6882475738  <NA> #> 529    2052    3M  CC01 2021 2021-01-04       TURB  1.0296194172     A #> 530    2052    3M  CC01 2021 2021-04-05      CHLAC  0.4054651081     I #> 531    2052    3M  CC01 2021 2021-04-05      COLOR  1.7227665977     I #> 532    2052    3M  CC01 2021 2021-04-05         DO  2.0605135318  <NA> #> 533    2052    3M  CC01 2021 2021-04-05      DOSAT  4.6784206477  <NA> #> 534    2052    3M  CC01 2021 2021-04-05       NO23 -5.5214609179     U #> 535    2052    3M  CC01 2021 2021-04-05      SALIN  3.5579161896  <NA> #> 536    2052    3M  CC01 2021 2021-04-05        TKN -1.0498221245     I #> 537    2052    3M  CC01 2021 2021-04-05         TN -1.8201589437     + #> 538    2052    3M  CC01 2021 2021-04-05         TP -2.6172958378  <NA> #> 539    2052    3M  CC01 2021 2021-04-05       TURB  0.7419373447  <NA> #> 540    2052    3M  CC01 2021 2021-06-07      CHLAC  1.5040773968  <NA> #> 541    2052    3M  CC01 2021 2021-06-07      COLOR  1.0296194172     I #> 542    2052    3M  CC01 2021 2021-06-07         DO  0.6678293726  <NA> #> 543    2052    3M  CC01 2021 2021-06-07      DOSAT  3.5055573970  <NA> #> 544    2052    3M  CC01 2021 2021-06-07       NO23 -5.5214609179     U #> 545    2052    3M  CC01 2021 2021-06-07      SALIN  3.6301904578  <NA> #> 546    2052    3M  CC01 2021 2021-06-07        TKN -0.6733445533  <NA> #> 547    2052    3M  CC01 2021 2021-06-07         TN -0.6694306539     + #> 548    2052    3M  CC01 2021 2021-06-07         TP -2.9565115604  <NA> #> 549    2052    3M  CC01 2021 2021-06-07       TURB  0.5306282511  <NA> #> 550    2052    3M  CC01 2021 2021-08-02      CHLAC  2.1162555148  <NA> #> 551    2052    3M  CC01 2021 2021-08-02      COLOR  4.4886363697  <NA> #> 552    2052    3M  CC01 2021 2021-08-02         DO  0.7929925155  <NA> #> 553    2052    3M  CC01 2021 2021-08-02      DOSAT  3.5115454388  <NA> #> 554    2052    3M  CC01 2021 2021-08-02       NO23 -4.9618451299     I #> 555    2052    3M  CC01 2021 2021-08-02      SALIN  3.1280754605  <NA> #> 556    2052    3M  CC01 2021 2021-08-02        TKN -0.0618754037  <NA> #> 557    2052    3M  CC01 2021 2021-08-02         TN -0.0576291128     + #> 558    2052    3M  CC01 2021 2021-08-02         TP -2.2072749132  <NA> #> 559    2052    3M  CC01 2021 2021-08-02       TURB  0.9932517730  <NA> #> 560    2052    3M  CC01 2021 2021-09-07      CHLAC  1.5892352051  <NA> #> 561    2052    3M  CC01 2021 2021-09-07      COLOR  5.0106352941  <NA> #> 562    2052    3M  CC01 2021 2021-09-07         DO  0.3364722366  <NA> #> 563    2052    3M  CC01 2021 2021-09-07      DOSAT  2.9652730661  <NA> #> 564    2052    3M  CC01 2021 2021-09-07       NO23 -4.6051701860  <NA> #> 565    2052    3M  CC01 2021 2021-09-07      SALIN  2.9391619221  <NA> #> 566    2052    3M  CC01 2021 2021-09-07        TKN -0.1392620673  <NA> #> 567    2052    3M  CC01 2021 2021-09-07         TN -0.1278333715     + #> 568    2052    3M  CC01 2021 2021-09-07         TP -2.3227878003  <NA> #> 569    2052    3M  CC01 2021 2021-09-07       TURB  0.4054651081  <NA> #> 570    2052    3M  CC01 2021 2021-10-04      CHLAC  3.3672958300  <NA> #> 571    2052    3M  CC01 2021 2021-10-04      COLOR  3.8286413965  <NA> #> 572    2052    3M  CC01 2021 2021-10-04         DO  0.6626879731  <NA> #> 573    2052    3M  CC01 2021 2021-10-04      DOSAT  3.3638415951  <NA> #> 574    2052    3M  CC01 2021 2021-10-04       NO23 -5.5214609179     U #> 575    2052    3M  CC01 2021 2021-10-04      SALIN  3.3304171996  <NA> #> 576    2052    3M  CC01 2021 2021-10-04        TKN -0.2357223335  <NA> #> 577    2052    3M  CC01 2021 2021-10-04         TN -0.2331938872     + #> 578    2052    3M  CC01 2021 2021-10-04         TP -2.3025850930  <NA> #> 579    2052    3M  CC01 2021 2021-10-04       TURB  0.9932517730  <NA> #> 580    2052    3M  CC01 2021 2021-11-01      CHLAC  1.1314021115  <NA> #> 581    2052    3M  CC01 2021 2021-11-01      COLOR  2.7080502011  <NA> #> 582    2052    3M  CC01 2021 2021-11-01         DO  1.2208299214  <NA> #> 583    2052    3M  CC01 2021 2021-11-01      DOSAT  3.8329797981  <NA> #> 584    2052    3M  CC01 2021 2021-11-01       NO23 -3.6888794541  <NA> #> 585    2052    3M  CC01 2021 2021-11-01      SALIN  3.4604092413  <NA> #> 586    2052    3M  CC01 2021 2021-11-01        TKN -0.4942963218  <NA> #> 587    2052    3M  CC01 2021 2021-11-01         TN -0.4541302801     + #> 588    2052    3M  CC01 2021 2021-11-01         TP -2.3025850930  <NA> #> 589    2052    3M  CC01 2021 2021-11-01       TURB  0.4700036292  <NA> #> 590    2052    3M  CC01 2021 2021-12-06      CHLAC  0.9932517730     I #> 591    2052    3M  CC01 2021 2021-12-06      COLOR  0.9162907319     U #> 592    2052    3M  CC01 2021 2021-12-06         DO  1.6752256530  <NA> #> 593    2052    3M  CC01 2021 2021-12-06      DOSAT  4.3027128280  <NA> #> 594    2052    3M  CC01 2021 2021-12-06       NO23 -4.8283137373     I #> 595    2052    3M  CC01 2021 2021-12-06      SALIN  3.4889029621  <NA> #> 596    2052    3M  CC01 2021 2021-12-06        TKN -0.6931471806  <NA> #> 597    2052    3M  CC01 2021 2021-12-06         TN -0.6851790109     + #> 598    2052    3M  CC01 2021 2021-12-06         TP -2.9374633654  <NA> #> 599    2052    3M  CC01 2021 2021-12-06       TURB  1.0647107370  <NA> #> 600    2052    3M  CC01 2022 2022-01-03      CHLAC  0.7419373447     I #> 601    2052    3M  CC01 2022 2022-01-03      COLOR  0.9162907319     U #> 602    2052    3M  CC01 2022 2022-01-03         DO  1.3137236683  <NA> #> 603    2052    3M  CC01 2022 2022-01-03      DOSAT  3.9815490681  <NA> #> 604    2052    3M  CC01 2022 2022-01-03       NO23 -4.8283137373     I #> 605    2052    3M  CC01 2022 2022-01-03      SALIN  3.5207566167  <NA> #> 606    2052    3M  CC01 2022 2022-01-03        TKN -0.9675840263     I #> 607    2052    3M  CC01 2022 2022-01-03         TN -1.8078888512     + #> 608    2052    3M  CC01 2022 2022-01-03         TP -2.5770219387  <NA> #> 609    2052    3M  CC01 2022 2022-01-03       TURB  1.0296194172     A #> 610    2052    3M  CC01 2022 2022-02-07      CHLAC  0.0953101798     I #> 611    2052    3M  CC01 2022 2022-02-07      COLOR  0.9162907319     U #> 612    2052    3M  CC01 2022 2022-02-07         DO  1.5085119938  <NA> #> 613    2052    3M  CC01 2022 2022-02-07      DOSAT  4.0758410907  <NA> #> 614    2052    3M  CC01 2022 2022-02-07       NO23 -4.8283137373     I #> 615    2052    3M  CC01 2022 2022-02-07      SALIN  3.4840054928  <NA> #> 616    2052    3M  CC01 2022 2022-02-07        TKN -0.9162907319  <NA> #> 617    2052    3M  CC01 2022 2022-02-07         TN -0.9063404010     + #> 618    2052    3M  CC01 2022 2022-02-07         TP -2.6036901858  <NA> #> 619    2052    3M  CC01 2022 2022-02-07       TURB  1.2237754316  <NA> #> 620    2052    3M  CC01 2022 2022-03-07      CHLAC  0.0953101798     I #> 621    2052    3M  CC01 2022 2022-03-07      COLOR  0.9162907319     U #> 622    2052    3M  CC01 2022 2022-03-07         DO  0.8109302162  <NA> #> 623    2052    3M  CC01 2022 2022-03-07      DOSAT  3.4657359028  <NA> #> 624    2052    3M  CC01 2022 2022-03-07       NO23 -5.5214609179     U #> 625    2052    3M  CC01 2022 2022-03-07      SALIN  3.5412491371  <NA> #> 626    2052    3M  CC01 2022 2022-03-07         TN -0.4910229965     + #> 627    2052    3M  CC01 2022 2022-03-07         TP -2.9759296463  <NA> #> 628    2052    3M  CC01 2022 2022-03-07       TURB  0.5877866649  <NA> #> 629    2052    3M  CC01 2022 2022-04-04      CHLAC  0.6418538862     I #> 630    2052    3M  CC01 2022 2022-04-04      COLOR  0.9162907319     U #> 631    2052    3M  CC01 2022 2022-04-04         DO  0.6097655716  <NA> #> 632    2052    3M  CC01 2022 2022-04-04      DOSAT  3.2809112158  <NA> #> 633    2052    3M  CC01 2022 2022-04-04       NO23 -5.5214609179     U #> 634    2052    3M  CC01 2022 2022-04-04      SALIN  3.5672766324  <NA> #> 635    2052    3M  CC01 2022 2022-04-04        TKN -0.8915981193  <NA> #> 636    2052    3M  CC01 2022 2022-04-04         TN -0.8867319296     + #> 637    2052    3M  CC01 2022 2022-04-04         TP -2.6736487744  <NA> #> 638    2052    3M  CC01 2022 2022-04-04       TURB  1.0986122887  <NA> #> 639    2052    3M  CC01 2022 2022-05-02      CHLAC  0.8329091229     I #> 640    2052    3M  CC01 2022 2022-05-02      COLOR  0.9162907319     U #> 641    2052    3M  CC01 2022 2022-05-02         DO  0.7178397932  <NA> #> 642    2052    3M  CC01 2022 2022-05-02      DOSAT  3.4242626546  <NA> #> 643    2052    3M  CC01 2022 2022-05-02       NO23 -5.5214609179     U #> 644    2052    3M  CC01 2022 2022-05-02      SALIN  3.6003214271  <NA> #> 645    2052    3M  CC01 2022 2022-05-02        TKN -0.8209805521  <NA> #> 646    2052    3M  CC01 2022 2022-05-02         TN -0.8164453969     + #> 647    2052    3M  CC01 2022 2022-05-02         TP -2.8473122684  <NA> #> 648    2052    3M  CC01 2022 2022-05-02       TURB  0.8329091229  <NA> #> 649    2052    3M  CC01 2022 2022-06-06      CHLAC  1.0986122887  <NA> #> 650    2052    3M  CC01 2022 2022-06-06      COLOR  2.2300144002  <NA> #> 651    2052    3M  CC01 2022 2022-06-06         DO  0.5538851132  <NA> #> 652    2052    3M  CC01 2022 2022-06-06      DOSAT  3.2695689392  <NA> #> 653    2052    3M  CC01 2022 2022-06-06       NO23 -5.5214609179     U #> 654    2052    3M  CC01 2022 2022-06-06      SALIN  3.5195728344  <NA> #> 655    2052    3M  CC01 2022 2022-06-06        TKN -0.7550225843  <NA> #> 656    2052    3M  CC01 2022 2022-06-06         TN 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3M  CC01 2022 2022-08-01      COLOR  1.9021075264  <NA> #> 671    2052    3M  CC01 2022 2022-08-01         DO -0.0943106795  <NA> #> 672    2052    3M  CC01 2022 2022-08-01      DOSAT  2.6946271808  <NA> #> 673    2052    3M  CC01 2022 2022-08-01       NO23 -4.9618451299     I #> 674    2052    3M  CC01 2022 2022-08-01      SALIN  3.5242995788  <NA> #> 675    2052    3M  CC01 2022 2022-08-01        TKN -0.6348782724  <NA> #> 676    2052    3M  CC01 2022 2022-08-01         TN -0.6273594400     + #> 677    2052    3M  CC01 2022 2022-08-01         TP -2.7181005370  <NA> #> 678    2052    3M  CC01 2022 2022-08-01       TURB  0.2623642645  <NA> #> 679    2052    3M  CC01 2022 2022-09-06      CHLAC  1.2809338455  <NA> #> 680    2052    3M  CC01 2022 2022-09-06      COLOR  1.3609765531     I #> 681    2052    3M  CC01 2022 2022-09-06         DO  0.8109302162  <NA> #> 682    2052    3M  CC01 2022 2022-09-06      DOSAT  3.6027767551  <NA> #> 683    2052    3M  CC01 2022 2022-09-06       NO23 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3M  CC01 2022 2022-12-05         TP -2.0402208285  <NA> #> 698    2052    3M  CC01 2022 2022-12-05       TURB  0.6931471806  <NA> #> 699    2052    3M  CC01 2023 2023-01-03      CHLAC  1.2809338455  <NA> #> 700    2052    3M  CC01 2023 2023-01-03      COLOR  2.5649493575  <NA> #> 701    2052    3M  CC01 2023 2023-01-03         DO  1.2641267271  <NA> #> 702    2052    3M  CC01 2023 2023-01-03      DOSAT  3.8897773965  <NA> #> 703    2052    3M  CC01 2023 2023-01-03       NO23 -5.2983173665     I #> 704    2052    3M  CC01 2023 2023-01-03      SALIN  3.3442742343  <NA> #> 705    2052    3M  CC01 2023 2023-01-03        TKN -0.7339691751  <NA> #> 706    2052    3M  CC01 2023 2023-01-03         TN -0.7256703723     + #> 707    2052    3M  CC01 2023 2023-01-03         TP -2.3025850930  <NA> #> 708    2052    3M  CC01 2023 2023-01-03       TURB  0.5306282511  <NA> #> 709    2052    3M  CC01 2023 2023-02-06      CHLAC  0.2623642645     I #> 710    2052    3M  CC01 2023 2023-02-06      COLOR  0.9162907319     U #> 711    2052    3M  CC01 2023 2023-02-06         DO  1.0577902941  <NA> #> 712    2052    3M  CC01 2023 2023-02-06      DOSAT  3.6788291183  <NA> #> 713    2052    3M  CC01 2023 2023-02-06       NO23 -5.2983173665     I #> 714    2052    3M  CC01 2023 2023-02-06      SALIN  3.5237099561  <NA> #> 715    2052    3M  CC01 2023 2023-02-06        TKN -1.1394342832     I #> 716    2052    3M  CC01 2023 2023-02-06         TN -1.8078888512     + #> 717    2052    3M  CC01 2023 2023-02-06         TP -1.8325814637  <NA> #> 718    2052    3M  CC01 2023 2023-02-06       TURB  0.9162907319  <NA> #> 719    2052    3M  CC01 2023 2023-03-06      CHLAC  0.9555114450  <NA> #> 720    2052    3M  CC01 2023 2023-03-06      COLOR  1.5892352051     I #> 721    2052    3M  CC01 2023 2023-03-06       NO23 -5.5214609179     U #> 722    2052    3M  CC01 2023 2023-03-06      SALIN  3.5458747597  <NA> #> 723    2052    3M  CC01 2023 2023-03-06        TKN -0.7765287895  <NA> #> 724    2052    3M  CC01 2023 2023-03-06         TN -0.7721903879     + #> 725    2052    3M  CC01 2023 2023-03-06         TP -2.4079456087  <NA> #> 726    2052    3M  CC01 2023 2023-03-06       TURB  0.4054651081  <NA> #> 727    2067    3M  CC02 2014 2014-02-03      CHLAC  0.5877866649  <NA> #> 728    2067    3M  CC02 2014 2014-02-03      COLOR  2.3978952728     A #> 729    2067    3M  CC02 2014 2014-02-03         DO  1.5892352051  <NA> #> 730    2067    3M  CC02 2014 2014-02-03      DOSAT  4.1478853292     + #> 731    2067    3M  CC02 2014 2014-02-03       NO23 -3.7297014486  <NA> #> 732    2067    3M  CC02 2014 2014-02-03      SALIN  3.3032169733  <NA> #> 733    2067    3M  CC02 2014 2014-02-03        TKN -0.5108256238  <NA> #> 734    2067    3M  CC02 2014 2014-02-03         TN -0.4716049106     + #> 735    2067    3M  CC02 2014 2014-02-03         TP -2.4079456087  <NA> #> 736    2067    3M  CC02 2014 2014-02-03       TURB  1.0647107370  <NA> #> 737    2067    3M  CC02 2014 2014-03-03      CHLAC  1.4109869737  <NA> #> 738    2067    3M  CC02 2014 2014-03-03      COLOR  1.3862943611     I #> 739    2067    3M  CC02 2014 2014-03-03         DO  1.6486586256  <NA> #> 740    2067    3M  CC02 2014 2014-03-03       NO23 -4.7105307016     I #> 741    2067    3M  CC02 2014 2014-03-03      SALIN  3.5292973843  <NA> #> 742    2067    3M  CC02 2014 2014-03-03        TKN -0.6161861394  <NA> #> 743    2067    3M  CC02 2014 2014-03-03         TN -0.6088060321     + #> 744    2067    3M  CC02 2014 2014-03-03         TP -2.6592600369  <NA> #> 745    2067    3M  CC02 2014 2014-03-03       TURB  1.5040773968  <NA> #> 746    2067    3M  CC02 2014 2014-04-07      CHLAC  0.7884573604  <NA> #> 747    2067    3M  CC02 2014 2014-04-07      COLOR  0.9555114450     I #> 748    2067    3M  CC02 2014 2014-04-07         DO  1.5260563035  <NA> #> 749    2067    3M  CC02 2014 2014-04-07      DOSAT  4.2224445648     + #> 750    2067    3M  CC02 2014 2014-04-07       NO23 -4.8283137373     I #> 751    2067    3M  CC02 2014 2014-04-07      SALIN  3.5695326965  <NA> #> 752    2067    3M  CC02 2014 2014-04-07        TKN -0.6931471806  <NA> #> 753    2067    3M  CC02 2014 2014-04-07         TN -0.6851790109     + #> 754    2067    3M  CC02 2014 2014-04-07         TP -2.6882475738  <NA> #> 755    2067    3M  CC02 2014 2014-04-07       TURB  1.3862943611  <NA> #> 756    2067    3M  CC02 2014 2014-05-05      CHLAC  1.3609765531  <NA> #> 757    2067    3M  CC02 2014 2014-05-05      COLOR  2.0412203289  <NA> #> 758    2067    3M  CC02 2014 2014-05-05      DOSAT  4.0775374439     + #> 759    2067    3M  CC02 2014 2014-05-05       NO23 -5.5214609179     I #> 760    2067    3M  CC02 2014 2014-05-05      SALIN  3.5582011305  <NA> #> 761    2067    3M  CC02 2014 2014-05-05        TKN -0.7985076962  <NA> #> 762    2067    3M  CC02 2014 2014-05-05         TN -0.7896580809     + #> 763    2067    3M  CC02 2014 2014-05-05         TP -2.4418471603  <NA> #> 764    2067    3M  CC02 2014 2014-05-05       TURB  1.1939224685  <NA> #> 765    2067    3M  CC02 2014 2014-08-04      CHLAC  1.0296194172  <NA> #> 766    2067    3M  CC02 2014 2014-08-04      COLOR  2.3978952728  <NA> #> 767    2067    3M  CC02 2014 2014-08-04         DO  1.1631508098  <NA> #> 768    2067    3M  CC02 2014 2014-08-04      DOSAT  3.9531649488     + #> 769    2067    3M  CC02 2014 2014-08-04       NO23 -5.2983173665     I #> 770    2067    3M  CC02 2014 2014-08-04      SALIN  3.6163087613  <NA> #> 771    2067    3M  CC02 2014 2014-08-04        TKN -0.5276327421  <NA> #> 772    2067    3M  CC02 2014 2014-08-04         TN -0.5208759596     + #> 773    2067    3M  CC02 2014 2014-08-04         TP -2.3025850930  <NA> #> 774    2067    3M  CC02 2014 2014-08-04       TURB  1.1631508098  <NA> #> 775    2067    3M  CC02 2014 2014-10-06      CHLAC  1.7404661748  <NA> #> 776    2067    3M  CC02 2014 2014-10-06      COLOR  3.3322045102  <NA> #> 777    2067    3M  CC02 2014 2014-10-06      DOSAT  3.9852734672     + #> 778    2067    3M  CC02 2014 2014-10-06       NO23 -4.3428059215  <NA> #> 779    2067    3M  CC02 2014 2014-10-06      SALIN  3.4499875458  <NA> #> 780    2067    3M  CC02 2014 2014-10-06        TKN -0.5276327421  <NA> #> 781    2067    3M  CC02 2014 2014-10-06         TN -0.5058380823     + #> 782    2067    3M  CC02 2014 2014-10-06         TP -1.9661128564  <NA> #> 783    2067    3M  CC02 2014 2014-10-06       TURB  1.0986122887  <NA> #> 784    2067    3M  CC02 2014 2014-11-03      CHLAC  0.4054651081     I #> 785    2067    3M  CC02 2014 2014-11-03      COLOR  2.5649493575  <NA> #> 786    2067    3M  CC02 2014 2014-11-03      DOSAT  4.0724397268     + #> 787    2067    3M  CC02 2014 2014-11-03       NO23 -4.6051701860  <NA> #> 788    2067    3M  CC02 2014 2014-11-03      SALIN  3.4531571206  <NA> #> 789    2067    3M  CC02 2014 2014-11-03        TKN -0.7133498879  <NA> #> 790    2067    3M  CC02 2014 2014-11-03         TN -0.6931471806     + #> 791    2067    3M  CC02 2014 2014-11-03         TP -2.0402208285  <NA> #> 792    2067    3M  CC02 2014 2014-11-03       TURB  1.0647107370  <NA> #> 793    2067    3M  CC02 2014 2014-12-01      CHLAC  0.2623642645     I #> 794    2067    3M  CC02 2014 2014-12-01      COLOR  1.3083328197     I #> 795    2067    3M  CC02 2014 2014-12-01         DO  1.8245492921  <NA> #> 796    2067    3M  CC02 2014 2014-12-01       NO23 -5.2983173665     I #> 797    2067    3M  CC02 2014 2014-12-01      SALIN  3.4626060098  <NA> #> 798    2067    3M  CC02 2014 2014-12-01        TKN -1.2378743560     I #> 799    2067    3M  CC02 2014 2014-12-01         TN -1.8078888512     + #> 800    2067    3M  CC02 2014 2014-12-01         TP -3.0576076773  <NA> #> 801    2067    3M  CC02 2014 2014-12-01       TURB  1.2809338455  <NA> #> 802    2067    3M  CC02 2015 2015-01-05      CHLAC  0.6418538862  <NA> #> 803    2067    3M  CC02 2015 2015-01-05      COLOR  2.1747517215  <NA> #> 804    2067    3M  CC02 2015 2015-01-05         DO  0.9932517730  <NA> #> 805    2067    3M  CC02 2015 2015-01-05      DOSAT  3.6375861597     + #> 806    2067    3M  CC02 2015 2015-01-05       NO23 -4.3428059215  <NA> #> 807    2067    3M  CC02 2015 2015-01-05      SALIN  3.5438536821  <NA> #> 808    2067    3M  CC02 2015 2015-01-05        TKN -0.7765287895  <NA> #> 809    2067    3M  CC02 2015 2015-01-05         TN -0.7486598905     + #> 810    2067    3M  CC02 2015 2015-01-05         TP -2.3025850930  <NA> #> 811    2067    3M  CC02 2015 2015-01-05       TURB  1.3083328197  <NA> #> 812    2067    3M  CC02 2015 2015-03-02      CHLAC  0.5306282511  <NA> #> 813    2067    3M  CC02 2015 2015-03-02      COLOR  2.4849066498  <NA> #> 814    2067    3M  CC02 2015 2015-03-02         DO  1.1939224685  <NA> #> 815    2067    3M  CC02 2015 2015-03-02       NO23 -3.6888794541  <NA> #> 816    2067    3M  CC02 2015 2015-03-02      SALIN  3.4563166809  <NA> #> 817    2067    3M  CC02 2015 2015-03-02        TKN -0.6161861394  <NA> #> 818    2067    3M  CC02 2015 2015-03-02         TN -0.5709295478     + #> 819    2067    3M  CC02 2015 2015-03-02         TP -2.3538783874  <NA> #> 820    2067    3M  CC02 2015 2015-03-02       TURB  1.1314021115  <NA> #> 821    2067    3M  CC02 2015 2015-04-06      CHLAC  1.3350010667  <NA> #> 822    2067    3M  CC02 2015 2015-04-06      COLOR  2.0541237337  <NA> #> 823    2067    3M  CC02 2015 2015-04-06      DOSAT  3.7184382564     + #> 824    2067    3M  CC02 2015 2015-04-06       NO23 -4.6051701860  <NA> #> 825    2067    3M  CC02 2015 2015-04-06      SALIN  3.5695326965  <NA> #> 826    2067    3M  CC02 2015 2015-04-06        TKN -0.3285040670  <NA> #> 827    2067    3M  CC02 2015 2015-04-06         TN -0.3147107448     + #> 828    2067    3M  CC02 2015 2015-04-06         TP -0.7765287895  <NA> #> 829    2067    3M  CC02 2015 2015-04-06       TURB  1.6292405397  <NA> #> 830    2067    3M  CC02 2015 2015-05-04      CHLAC  0.9162907319  <NA> #> 831    2067    3M  CC02 2015 2015-05-04      COLOR  2.0149030205  <NA> #> 832    2067    3M  CC02 2015 2015-05-04       NO23 -4.6051701860     I #> 833    2067    3M  CC02 2015 2015-05-04      SALIN  3.5835189385  <NA> #> 834    2067    3M  CC02 2015 2015-05-04        TKN -0.8209805521  <NA> #> 835    2067    3M  CC02 2015 2015-05-04         TN -0.8119307165     + #> 836    2067    3M  CC02 2015 2015-05-04         TP -2.6310891600  <NA> #> 837    2067    3M  CC02 2015 2015-05-04       TURB  1.3609765531     A #> 838    2067    3M  CC02 2015 2015-06-01      CHLAC  0.4700036292     I #> 839    2067    3M  CC02 2015 2015-06-01      COLOR  2.1860512767  <NA> #> 840    2067    3M  CC02 2015 2015-06-01         DO  1.2237754316  <NA> #> 841    2067    3M  CC02 2015 2015-06-01       NO23 -4.1997050779  <NA> #> 842    2067    3M  CC02 2015 2015-06-01      SALIN  3.5945687746  <NA> #> 843    2067    3M  CC02 2015 2015-06-01        TKN -0.7133498879  <NA> #> 844    2067    3M  CC02 2015 2015-06-01         TN -0.6831968497     + #> 845    2067    3M  CC02 2015 2015-06-01         TP -2.8134107168  <NA> #> 846    2067    3M  CC02 2015 2015-06-01       TURB  0.9555114450  <NA> #> 847    2067    3M  CC02 2015 2015-09-08      CHLAC  1.1631508098  <NA> #> 848    2067    3M  CC02 2015 2015-09-08      COLOR  3.3672958300     A #> 849    2067    3M  CC02 2015 2015-09-08         DO  1.1631508098  <NA> #> 850    2067    3M  CC02 2015 2015-09-08      DOSAT  3.8877303129     + #> 851    2067    3M  CC02 2015 2015-09-08       NO23 -5.1159958098     I #> 852    2067    3M  CC02 2015 2015-09-08      SALIN  3.4078419244  <NA> #> 853    2067    3M  CC02 2015 2015-09-08        TKN -0.3424903089  <NA> #> 854    2067    3M  CC02 2015 2015-09-08         TN -0.3368723166     + #> 855    2067    3M  CC02 2015 2015-09-08         TP -1.3862943611  <NA> #> 856    2067    3M  CC02 2015 2015-09-08       TURB  1.0296194172  <NA> #> 857    2067    3M  CC02 2016 2016-02-01      CHLAC  0.6931471806  <NA> #> 858    2067    3M  CC02 2016 2016-02-01      COLOR  3.2188758249  <NA> #> 859    2067    3M  CC02 2016 2016-02-01         DO  1.4350845253  <NA> #> 860    2067    3M  CC02 2016 2016-02-01      DOSAT  3.9665111907     + #> 861    2067    3M  CC02 2016 2016-02-01       NO23 -3.7297014486  <NA> #> 862    2067    3M  CC02 2016 2016-02-01      SALIN  3.3286266888  <NA> #> 863    2067    3M  CC02 2016 2016-02-01        TKN -0.4942963218  <NA> #> 864    2067    3M  CC02 2016 2016-02-01         TN -0.4557063245     + #> 865    2067    3M  CC02 2016 2016-02-01         TP -2.3227878003  <NA> #> 866    2067    3M  CC02 2016 2016-02-01       TURB  0.8754687374  <NA> #> 867    2067    3M  CC02 2016 2016-03-07      CHLAC  0.8754687374  <NA> #> 868    2067    3M  CC02 2016 2016-03-07      COLOR  3.2188758249  <NA> #> 869    2067    3M  CC02 2016 2016-03-07       NO23 -4.1351665567  <NA> #> 870    2067    3M  CC02 2016 2016-03-07      SALIN  3.3357695763  <NA> #> 871    2067    3M  CC02 2016 2016-03-07        TKN -0.2357223335  <NA> #> 872    2067    3M  CC02 2016 2016-03-07         TN -0.2156715365     + #> 873    2067    3M  CC02 2016 2016-03-07         TP -2.3025850930  <NA> #> 874    2067    3M  CC02 2016 2016-03-07       TURB  1.9315214116  <NA> #> 875    2067    3M  CC02 2016 2016-04-04      CHLAC  0.3364722366     I #> 876    2067    3M  CC02 2016 2016-04-04      COLOR  2.6390573296  <NA> #> 877    2067    3M  CC02 2016 2016-04-04         DO  1.1314021115  <NA> #> 878    2067    3M  CC02 2016 2016-04-04      DOSAT  3.7400477407     + #> 879    2067    3M  CC02 2016 2016-04-04       NO23 -3.9120230054  <NA> #> 880    2067    3M  CC02 2016 2016-04-04      SALIN  3.3809946743  <NA> #> 881    2067    3M  CC02 2016 2016-04-04        TKN -0.7133498879  <NA> #> 882    2067    3M  CC02 2016 2016-04-04         TN -0.6733445533     + #> 883    2067    3M  CC02 2016 2016-04-04         TP -2.3434070875  <NA> #> 884    2067    3M  CC02 2016 2016-04-04       TURB  1.1939224685     A #> 885    2067    3M  CC02 2016 2016-05-02      CHLAC  0.0953101798     I #> 886    2067    3M  CC02 2016 2016-05-02      COLOR  2.4849066498  <NA> #> 887    2067    3M  CC02 2016 2016-05-02         DO  0.7419373447  <NA> #> 888    2067    3M  CC02 2016 2016-05-02      DOSAT  3.4812400893     + #> 889    2067    3M  CC02 2016 2016-05-02       NO23 -4.9618451299     I #> 890    2067    3M  CC02 2016 2016-05-02      SALIN  3.5582011305  <NA> #> 891    2067    3M  CC02 2016 2016-05-02        TKN -0.7339691751  <NA> #> 892    2067    3M  CC02 2016 2016-05-02         TN -0.7256703723     + #> 893    2067    3M  CC02 2016 2016-05-02         TP -2.5257286443  <NA> #> 894    2067    3M  CC02 2016 2016-05-02       TURB  0.9555114450  <NA> #> 895    2067    3M  CC02 2016 2016-06-06      CHLAC  0.2623642645     I #> 896    2067    3M  CC02 2016 2016-06-06      COLOR  3.3672958300  <NA> #> 897    2067    3M  CC02 2016 2016-06-06         DO  0.7884573604  <NA> #> 898    2067    3M  CC02 2016 2016-06-06      DOSAT  3.5351453542     + #> 899    2067    3M  CC02 2016 2016-06-06       NO23 -4.8283137373     I #> 900    2067    3M  CC02 2016 2016-06-06      SALIN  3.4934726578  <NA> #> 901    2067    3M  CC02 2016 2016-06-06        TKN -0.7339691751  <NA> #> 902    2067    3M  CC02 2016 2016-06-06         TN -0.7256703723     + #> 903    2067    3M  CC02 2016 2016-06-06         TP -1.0788096614  <NA> #> 904    2067    3M  CC02 2016 2016-06-06       TURB  0.4700036292  <NA> #> 905    2067    3M  CC02 2016 2016-07-05      CHLAC  1.7047480922  <NA> #> 906    2067    3M  CC02 2016 2016-07-05      COLOR  2.8332133441  <NA> #> 907    2067    3M  CC02 2016 2016-07-05         DO  0.0000000000  <NA> #> 908    2067    3M  CC02 2016 2016-07-05      DOSAT  2.7788192720     + #> 909    2067    3M  CC02 2016 2016-07-05       NO23 -4.7105307016     I #> 910    2067    3M  CC02 2016 2016-07-05      SALIN  3.5174978374  <NA> #> 911    2067    3M  CC02 2016 2016-07-05        TKN  0.6418538862  <NA> #> 912    2067    3M  CC02 2016 2016-07-05         TN  0.6439569364     + #> 913    2067    3M  CC02 2016 2016-07-05         TP -1.7147984281  <NA> #> 914    2067    3M  CC02 2016 2016-07-05       TURB  2.9957322736  <NA> #> 915    2067    3M  CC02 2016 2016-08-01      CHLAC  0.8754687374  <NA> #> 916    2067    3M  CC02 2016 2016-08-01      COLOR  2.7080502011  <NA> #> 917    2067    3M  CC02 2016 2016-08-01         DO  0.4054651081  <NA> #> 918    2067    3M  CC02 2016 2016-08-01      DOSAT  3.1696855807     + #> 919    2067    3M  CC02 2016 2016-08-01       NO23 -4.3428059215  <NA> #> 920    2067    3M  CC02 2016 2016-08-01      SALIN  3.4688560301  <NA> #> 921    2067    3M  CC02 2016 2016-08-01        TKN -0.6161861394  <NA> #> 922    2067    3M  CC02 2016 2016-08-01         TN -0.5923972775     + #> 923    2067    3M  CC02 2016 2016-08-01         TP -2.6310891600  <NA> #> 924    2067    3M  CC02 2016 2016-08-01       TURB  0.9932517730  <NA> #> 925    2067    3M  CC02 2016 2016-10-03      CHLAC  1.1631508098  <NA> #> 926    2067    3M  CC02 2016 2016-10-03      COLOR  4.1271343850  <NA> #> 927    2067    3M  CC02 2016 2016-10-03         DO  0.8754687374  <NA> #> 928    2067    3M  CC02 2016 2016-10-03      DOSAT  3.5174978374     + #> 929    2067    3M  CC02 2016 2016-10-03       NO23 -4.6051701860  <NA> #> 930    2067    3M  CC02 2016 2016-10-03      SALIN  2.7343675094  <NA> #> 931    2067    3M  CC02 2016 2016-10-03        TKN -0.1392620673  <NA> #> 932    2067    3M  CC02 2016 2016-10-03         TN -0.1278333715     + #> 933    2067    3M  CC02 2016 2016-10-03         TP -2.4304184645  <NA> #> 934    2067    3M  CC02 2016 2016-10-03       TURB  0.7419373447  <NA> #> 935    2067    3M  CC02 2016 2016-12-05      CHLAC  0.6418538862     I #> 936    2067    3M  CC02 2016 2016-12-05      COLOR  0.9162907319     U #> 937    2067    3M  CC02 2016 2016-12-05         DO  1.3862943611  <NA> #> 938    2067    3M  CC02 2016 2016-12-05      DOSAT  4.0289167569     + #> 939    2067    3M  CC02 2016 2016-12-05       NO23 -4.1351665567  <NA> #> 940    2067    3M  CC02 2016 2016-12-05      SALIN  3.5438536821  <NA> #> 941    2067    3M  CC02 2016 2016-12-05        TKN -0.3424903089  <NA> #> 942    2067    3M  CC02 2016 2016-12-05         TN -0.3202052642     + #> 943    2067    3M  CC02 2016 2016-12-05         TP -2.5770219387  <NA> #> 944    2067    3M  CC02 2016 2016-12-05       TURB  1.8870696490     A #> 945    2067    3M  CC02 2017 2017-01-03      CHLAC  1.0986122887  <NA> #> 946    2067    3M  CC02 2017 2017-01-03      COLOR  1.5686159179     I #> 947    2067    3M  CC02 2017 2017-01-03         DO  1.3083328197  <NA> #> 948    2067    3M  CC02 2017 2017-01-03      DOSAT  3.9512437186     + #> 949    2067    3M  CC02 2017 2017-01-03       NO23 -3.9633162998  <NA> #> 950    2067    3M  CC02 2017 2017-01-03      SALIN  3.5438536821  <NA> #> 951    2067    3M  CC02 2017 2017-01-03        TKN -0.4780358009  <NA> #> 952    2067    3M  CC02 2017 2017-01-03         TN -0.4478508246     + #> 953    2067    3M  CC02 2017 2017-01-03         TP 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3M  CC02 2017 2017-03-06         DO  1.3862943611  <NA> #> 968    2067    3M  CC02 2017 2017-03-06      DOSAT  3.9778107460     + #> 969    2067    3M  CC02 2017 2017-03-06       NO23 -4.9618451299     I #> 970    2067    3M  CC02 2017 2017-03-06      SALIN  3.5174978374  <NA> #> 971    2067    3M  CC02 2017 2017-03-06        TKN -0.5798184953  <NA> #> 972    2067    3M  CC02 2017 2017-03-06         TN -0.5727010275     + #> 973    2067    3M  CC02 2017 2017-03-06         TP -2.6882475738  <NA> #> 974    2067    3M  CC02 2017 2017-03-06       TURB  1.3083328197  <NA> #> 975    2067    3M  CC02 2017 2017-04-03      CHLAC  0.6931471806  <NA> #> 976    2067    3M  CC02 2017 2017-04-03      COLOR  2.3978952728  <NA> #> 977    2067    3M  CC02 2017 2017-04-03         DO  1.2809338455  <NA> #> 978    2067    3M  CC02 2017 2017-04-03      DOSAT  4.0000338828     + #> 979    2067    3M  CC02 2017 2017-04-03       NO23 -4.9618451299     I #> 980    2067    3M  CC02 2017 2017-04-03      SALIN  3.5835189385  <NA> #> 981    2067    3M  CC02 2017 2017-04-03        TKN -0.4155154440  <NA> #> 982    2067    3M  CC02 2017 2017-04-03         TN -0.4094731295     + #> 983    2067    3M  CC02 2017 2017-04-03         TP -2.6592600369  <NA> #> 984    2067    3M  CC02 2017 2017-04-03       TURB  1.3862943611  <NA> #> 985    2067    3M  CC02 2017 2017-05-01      CHLAC  0.7884573604  <NA> #> 986    2067    3M  CC02 2017 2017-05-01      COLOR  1.5040773968     I #> 987    2067    3M  CC02 2017 2017-05-01         DO  1.2527629685  <NA> #> 988    2067    3M  CC02 2017 2017-05-01      DOSAT  3.9852734672     + #> 989    2067    3M  CC02 2017 2017-05-01       NO23 -5.5214609179     U #> 990    2067    3M  CC02 2017 2017-05-01      SALIN  3.5918177413  <NA> #> 991    2067    3M  CC02 2017 2017-05-01        TKN -0.4462871026  <NA> #> 992    2067    3M  CC02 2017 2017-05-01         TN -0.4431669753     + #> 993    2067    3M  CC02 2017 2017-05-01         TP -3.1010927892  <NA> #> 994    2067    3M  CC02 2017 2017-05-01       TURB  0.8754687374  <NA> #> 995    2067    3M  CC02 2017 2017-07-10      CHLAC  1.0296194172  <NA> #> 996    2067    3M  CC02 2017 2017-07-10      COLOR  3.1354942159  <NA> #> 997    2067    3M  CC02 2017 2017-07-10         DO  1.1314021115  <NA> #> 998    2067    3M  CC02 2017 2017-07-10      DOSAT  3.8938590348     + #> 999    2067    3M  CC02 2017 2017-07-10       NO23 -4.4228486292  <NA> #> 1000   2067    3M  CC02 2017 2017-07-10      SALIN  3.3978584804  <NA> #> 1001   2067    3M  CC02 2017 2017-07-10        TKN -0.4620354596  <NA> #> 1002   2067    3M  CC02 2017 2017-07-10         TN -0.4431669753     + #> 1003   2067    3M  CC02 2017 2017-07-10         TP -2.7181005370  <NA> #> 1004   2067    3M  CC02 2017 2017-07-10       TURB  1.4586150227  <NA> #> 1005   2067    3M  CC02 2017 2017-08-07      CHLAC  1.1631508098  <NA> #> 1006   2067    3M  CC02 2017 2017-08-07      COLOR  3.8712010109  <NA> #> 1007   2067    3M  CC02 2017 2017-08-07         DO  0.8754687374  <NA> #> 1008   2067    3M  CC02 2017 2017-08-07      DOSAT  3.6216707044     + #> 1009   2067    3M  CC02 2017 2017-08-07       NO23 -4.5098600062  <NA> #> 1010   2067    3M  CC02 2017 2017-08-07      SALIN  3.2542429687  <NA> #> 1011   2067    3M  CC02 2017 2017-08-07        TKN -0.4307829161  <NA> #> 1012   2067    3M  CC02 2017 2017-08-07         TN -0.4140014391     + #> 1013   2067    3M  CC02 2017 2017-08-07         TP -2.5639498571  <NA> #> 1014   2067    3M  CC02 2017 2017-08-07       TURB  0.5306282511  <NA> #> 1015   2067    3M  CC02 2017 2017-10-02      CHLAC  1.0986122887  <NA> #> 1016   2067    3M  CC02 2017 2017-10-02      COLOR  3.6888794541  <NA> #> 1017   2067    3M  CC02 2017 2017-10-02       NO23 -5.2983173665     I #> 1018   2067    3M  CC02 2017 2017-10-02        TKN -0.5276327421  <NA> #> 1019   2067    3M  CC02 2017 2017-10-02         TN -0.5208759596     + #> 1020   2067    3M  CC02 2017 2017-10-02         TP -2.3025850930  <NA> #> 1021   2067    3M  CC02 2017 2017-10-02       TURB  1.0296194172  <NA> #> 1022   2067    3M  CC02 2017 2017-11-06      CHLAC  0.9162907319  <NA> #> 1023   2067    3M  CC02 2017 2017-11-06      COLOR  3.2188758249  <NA> #> 1024   2067    3M  CC02 2017 2017-11-06         DO  1.2527629685  <NA> #> 1025   2067    3M  CC02 2017 2017-11-06      DOSAT  3.8938590348     + #> 1026   2067    3M  CC02 2017 2017-11-06       NO23 -4.6051701860  <NA> #> 1027   2067    3M  CC02 2017 2017-11-06      SALIN  3.3499040873  <NA> #> 1028   2067    3M  CC02 2017 2017-11-06        TKN -0.4620354596  <NA> #> 1029   2067    3M  CC02 2017 2017-11-06         TN -0.4462871026     + #> 1030   2067    3M  CC02 2017 2017-11-06         TP -2.6036901858  <NA> #> 1031   2067    3M  CC02 2017 2017-11-06       TURB  0.8754687374     A #> 1032   2067    3M  CC02 2017 2017-12-04      CHLAC  0.7884573604  <NA> #> 1033   2067    3M  CC02 2017 2017-12-04      COLOR  2.5649493575  <NA> #> 1034   2067    3M  CC02 2017 2017-12-04         DO  1.3862943611  <NA> #> 1035   2067    3M  CC02 2017 2017-12-04      DOSAT  4.0181832013     + #> 1036   2067    3M  CC02 2017 2017-12-04       NO23 -4.9618451299     I #> 1037   2067    3M  CC02 2017 2017-12-04      SALIN  3.5025498759  <NA> #> 1038   2067    3M  CC02 2017 2017-12-04        TKN -0.4780358009  <NA> #> 1039   2067    3M  CC02 2017 2017-12-04         TN -0.4716049106     + #> 1040   2067    3M  CC02 2017 2017-12-04         TP -2.6882475738  <NA> #> 1041   2067    3M  CC02 2017 2017-12-04       TURB  1.3862943611     A #> 1042   2067    3M  CC02 2018 2018-01-02      CHLAC  0.9932517730  <NA> #> 1043   2067    3M  CC02 2018 2018-01-02      COLOR  2.5649493575  <NA> #> 1044   2067    3M  CC02 2018 2018-01-02         DO  0.7884573604  <NA> #> 1045   2067    3M  CC02 2018 2018-01-02      DOSAT  3.2580965380     + #> 1046   2067    3M  CC02 2018 2018-01-02       NO23 -4.2686979494  <NA> #> 1047   2067    3M  CC02 2018 2018-01-02      SALIN  3.4688560301  <NA> #> 1048   2067    3M  CC02 2018 2018-01-02        TKN -0.6348782724  <NA> #> 1049   2067    3M  CC02 2018 2018-01-02         TN -0.6088060321     + #> 1050   2067    3M  CC02 2018 2018-01-02         TP -2.3434070875  <NA> #> 1051   2067    3M  CC02 2018 2018-01-02       TURB  1.5260563035  <NA> #> 1052   2067    3M  CC02 2018 2018-02-05      CHLAC  0.0953101798     I #> 1053   2067    3M  CC02 2018 2018-02-05      COLOR  2.6390573296  <NA> #> 1054   2067    3M  CC02 2018 2018-02-05         DO  1.5040773968  <NA> #> 1055   2067    3M  CC02 2018 2018-02-05      DOSAT  4.0724397268     + #> 1056   2067    3M  CC02 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 1057   2067    3M  CC02 2018 2018-02-05      SALIN  3.3877743613  <NA> #> 1058   2067    3M  CC02 2018 2018-02-05        TKN -0.7339691751  <NA> #> 1059   2067    3M  CC02 2018 2018-02-05         TN -0.7011793523     + #> 1060   2067    3M  CC02 2018 2018-02-05         TP -2.7030626596  <NA> #> 1061   2067    3M  CC02 2018 2018-02-05       TURB  1.2809338455  <NA> #> 1062   2067    3M  CC02 2018 2018-03-05      CHLAC  0.6931471806  <NA> #> 1063   2067    3M  CC02 2018 2018-03-05      COLOR  2.0014800002  <NA> #> 1064   2067    3M  CC02 2018 2018-03-05         DO  1.5475625087  <NA> #> 1065   2067    3M  CC02 2018 2018-03-05      DOSAT  4.1351665567     + #> 1066   2067    3M  CC02 2018 2018-03-05       NO23 -5.1159958098     I #> 1067   2067    3M  CC02 2018 2018-03-05      SALIN  3.5835189385  <NA> #> 1068   2067    3M  CC02 2018 2018-03-05        TKN -0.7339691751  <NA> #> 1069   2067    3M  CC02 2018 2018-03-05         TN -0.7256703723     + #> 1070   2067    3M  CC02 2018 2018-03-05         TP -2.7333680091  <NA> #> 1071   2067    3M  CC02 2018 2018-03-05       TURB  1.5892352051     A #> 1072   2067    3M  CC02 2018 2018-04-02      CHLAC  0.6931471806  <NA> #> 1073   2067    3M  CC02 2018 2018-04-02      COLOR  1.2527629685     I #> 1074   2067    3M  CC02 2018 2018-04-02         DO  1.4109869737  <NA> #> 1075   2067    3M  CC02 2018 2018-04-02      DOSAT  4.0926765051     + #> 1076   2067    3M  CC02 2018 2018-04-02       NO23 -4.7105307016     I #> 1077   2067    3M  CC02 2018 2018-04-02      SALIN  3.5945687746  <NA> #> 1078   2067    3M  CC02 2018 2018-04-02        TKN -0.6539264674  <NA> #> 1079   2067    3M  CC02 2018 2018-04-02         TN -0.6462635947     + #> 1080   2067    3M  CC02 2018 2018-04-02         TP -2.5510464523  <NA> #> 1081   2067    3M  CC02 2018 2018-04-02       TURB  1.7227665977  <NA> #> 1082   2067    3M  CC02 2018 2018-05-07      CHLAC  0.5306282511  <NA> #> 1083   2067    3M  CC02 2018 2018-05-07      COLOR  1.8245492921  <NA> #> 1084   2067    3M  CC02 2018 2018-05-07         DO  1.3609765531  <NA> #> 1085   2067    3M  CC02 2018 2018-05-07      DOSAT  3.9608131696  <NA> #> 1086   2067    3M  CC02 2018 2018-05-07       NO23 -5.2983173665     I #> 1087   2067    3M  CC02 2018 2018-05-07      SALIN  3.6027767551  <NA> #> 1088   2067    3M  CC02 2018 2018-05-07        TKN -0.3147107448  <NA> #> 1089   2067    3M  CC02 2018 2018-05-07         TN -0.3092462504     + #> 1090   2067    3M  CC02 2018 2018-05-07         TP -2.7488721956  <NA> #> 1091   2067    3M  CC02 2018 2018-05-07       TURB  1.3083328197  <NA> #> 1092   2067    3M  CC02 2018 2018-07-09      CHLAC  1.6094379124  <NA> #> 1093   2067    3M  CC02 2018 2018-07-09      COLOR  2.7725887222  <NA> #> 1094   2067    3M  CC02 2018 2018-07-09         DO  1.0818051704  <NA> #> 1095   2067    3M  CC02 2018 2018-07-09      DOSAT  3.8308129500  <NA> #> 1096   2067    3M  CC02 2018 2018-07-09       NO23 -5.2983173665     I #> 1097   2067    3M  CC02 2018 2018-07-09      SALIN  3.4741380061  <NA> #> 1098   2067    3M  CC02 2018 2018-07-09        TKN -0.5276327421  <NA> #> 1099   2067    3M  CC02 2018 2018-07-09         TN -0.5208759596     + #> 1100   2067    3M  CC02 2018 2018-07-09       TURB  0.9932517730  <NA> #> 1101   2067    3M  CC02 2018 2018-08-06      CHLAC  1.8562979904  <NA> #> 1102   2067    3M  CC02 2018 2018-08-06      COLOR  3.5263605246     A #> 1103   2067    3M  CC02 2018 2018-08-06         DO  0.8586616190  <NA> #> 1104   2067    3M  CC02 2018 2018-08-06      DOSAT  3.6270040504  <NA> #> 1105   2067    3M  CC02 2018 2018-08-06       NO23 -5.1159958098     I #> 1106   2067    3M  CC02 2018 2018-08-06      SALIN  3.4968105459  <NA> #> 1107   2067    3M  CC02 2018 2018-08-06        TKN -0.2107210313  <NA> #> 1108   2067    3M  CC02 2018 2018-08-06         TN -0.2057949130     + #> 1109   2067    3M  CC02 2018 2018-08-06         TP -2.3968957725  <NA> #> 1110   2067    3M  CC02 2018 2018-08-06       TURB  1.0296194172     A #> 1111   2067    3M  CC02 2019 2019-02-04      CHLAC -0.1984509387     I #> 1112   2067    3M  CC02 2019 2019-02-04      COLOR  3.1354942159  <NA> #> 1113   2067    3M  CC02 2019 2019-02-04         DO  1.3323660191  <NA> #> 1114   2067    3M  CC02 2019 2019-02-04      DOSAT  3.8999504242  <NA> #> 1115   2067    3M  CC02 2019 2019-02-04       NO23 -4.1997050779  <NA> #> 1116   2067    3M  CC02 2019 2019-02-04      SALIN  3.2669037939  <NA> #> 1117   2067    3M  CC02 2019 2019-02-04        TKN -0.6931471806  <NA> #> 1118   2067    3M  CC02 2019 2019-02-04         TN -0.6635883783     + #> 1119   2067    3M  CC02 2019 2019-02-04         TP -2.7181005370  <NA> #> 1120   2067    3M  CC02 2019 2019-02-04       TURB  0.9932517730  <NA> #> 1121   2067    3M  CC02 2019 2019-03-04      CHLAC  0.2623642645     I #> 1122   2067    3M  CC02 2019 2019-03-04      COLOR  3.0445224377  <NA> #> 1123   2067    3M  CC02 2019 2019-03-04       NO23 -5.2983173665     I #> 1124   2067    3M  CC02 2019 2019-03-04      SALIN  3.4381719845  <NA> #> 1125   2067    3M  CC02 2019 2019-03-04        TKN -0.7550225843  <NA> #> 1126   2067    3M  CC02 2019 2019-03-04         TN -0.7465479573     + #> 1127   2067    3M  CC02 2019 2019-03-04         TP -2.7968814148  <NA> #> 1128   2067    3M  CC02 2019 2019-03-04       TURB  0.5877866649  <NA> #> 1129   2067    3M  CC02 2019 2019-04-01      CHLAC -0.2107210313     I #> 1130   2067    3M  CC02 2019 2019-04-01      COLOR  2.0794415417  <NA> #> 1131   2067    3M  CC02 2019 2019-04-01       NO23 -5.5214609179     U #> 1132   2067    3M  CC02 2019 2019-04-01        TKN -0.6161861394  <NA> #> 1133   2067    3M  CC02 2019 2019-04-01         TN -0.6124892775     + #> 1134   2067    3M  CC02 2019 2019-04-01         TP -2.9759296463  <NA> #> 1135   2067    3M  CC02 2019 2019-04-01       TURB  0.4700036292  <NA> #> 1136   2067    3M  CC02 2019 2019-05-06      CHLAC  0.5877866649     I #> 1137   2067    3M  CC02 2019 2019-05-06      COLOR  2.2617630985  <NA> #> 1138   2067    3M  CC02 2019 2019-05-06         DO  0.5877866649  <NA> #> 1139   2067    3M  CC02 2019 2019-05-06      DOSAT  3.3250360207  <NA> #> 1140   2067    3M  CC02 2019 2019-05-06       NO23 -4.8283137373     I #> 1141   2067    3M  CC02 2019 2019-05-06      SALIN  3.5522002552  <NA> #> 1142   2067    3M  CC02 2019 2019-05-06        TKN -0.5108256238  <NA> #> 1143   2067    3M  CC02 2019 2019-05-06         TN -0.5041810810     + #> 1144   2067    3M  CC02 2019 2019-05-06         TP -2.7030626596  <NA> #> 1145   2067    3M  CC02 2019 2019-05-06       TURB  1.0647107370  <NA> #> 1146   2067    3M  CC02 2019 2019-06-03      CHLAC  0.6418538862     I #> 1147   2067    3M  CC02 2019 2019-06-03      COLOR  1.3350010667     I #> 1148   2067    3M  CC02 2019 2019-06-03         DO  0.4700036292  <NA> #> 1149   2067    3M  CC02 2019 2019-06-03      DOSAT  3.2771447330  <NA> #> 1150   2067    3M  CC02 2019 2019-06-03       NO23 -4.3428059215  <NA> #> 1151   2067    3M  CC02 2019 2019-06-03      SALIN  3.5882300460  <NA> #> 1152   2067    3M  CC02 2019 2019-06-03        TKN -0.5447271754  <NA> #> 1153   2067    3M  CC02 2019 2019-06-03         TN -0.5225608800     + #> 1154   2067    3M  CC02 2019 2019-06-03         TP -2.6172958378  <NA> #> 1155   2067    3M  CC02 2019 2019-06-03       TURB  0.6931471806  <NA> #> 1156   2067    3M  CC02 2019 2019-07-01      CHLAC  0.7419373447     I #> 1157   2067    3M  CC02 2019 2019-07-01      COLOR  1.9315214116  <NA> #> 1158   2067    3M  CC02 2019 2019-07-01       NO23 -4.8283137373     I #> 1159   2067    3M  CC02 2019 2019-07-01      SALIN  3.5424075502  <NA> #> 1160   2067    3M  CC02 2019 2019-07-01        TKN -0.5621189182  <NA> #> 1161   2067    3M  CC02 2019 2019-07-01         TN -0.5551258827     + #> 1162   2067    3M  CC02 2019 2019-07-01         TP -3.1941832123  <NA> #> 1163   2067    3M  CC02 2019 2019-07-01       TURB  0.8329091229  <NA> #> 1164   2067    3M  CC02 2019 2019-08-05      CHLAC  0.6418538862     I #> 1165   2067    3M  CC02 2019 2019-08-05      COLOR  3.7841896339     A #> 1166   2067    3M  CC02 2019 2019-08-05         DO  0.6312717768  <NA> #> 1167   2067    3M  CC02 2019 2019-08-05      DOSAT  3.3775875160  <NA> #> 1168   2067    3M  CC02 2019 2019-08-05       NO23 -4.7105307016     I #> 1169   2067    3M  CC02 2019 2019-08-05      SALIN  3.3617633124  <NA> #> 1170   2067    3M  CC02 2019 2019-08-05        TKN -0.4780358009  <NA> #> 1171   2067    3M  CC02 2019 2019-08-05         TN -0.4716049106     + #> 1172   2067    3M  CC02 2019 2019-08-05         TP -3.1010927892  <NA> #> 1173   2067    3M  CC02 2019 2019-08-05       TURB  0.4054651081  <NA> #> 1174   2067    3M  CC02 2019 2019-10-07      CHLAC  1.3350010667  <NA> #> 1175   2067    3M  CC02 2019 2019-10-07      COLOR  1.2809338455     I #> 1176   2067    3M  CC02 2019 2019-10-07         DO  1.0508216248  <NA> #> 1177   2067    3M  CC02 2019 2019-10-07      DOSAT  3.7750571504  <NA> #> 1178   2067    3M  CC02 2019 2019-10-07       NO23 -5.2983173665     I #> 1179   2067    3M  CC02 2019 2019-10-07      SALIN  3.5389282774  <NA> #> 1180   2067    3M  CC02 2019 2019-10-07        TKN -0.6733445533  <NA> #> 1181   2067    3M  CC02 2019 2019-10-07         TN -0.6655320135     + #> 1182   2067    3M  CC02 2019 2019-10-07         TP -2.9759296463  <NA> #> 1183   2067    3M  CC02 2019 2019-10-07       TURB  1.1314021115  <NA> #> 1184   2067    3M  CC02 2019 2019-11-04      CHLAC  1.6292405397  <NA> #> 1185   2067    3M  CC02 2019 2019-11-04      COLOR  1.4816045409     I #> 1186   2067    3M  CC02 2019 2019-11-04         DO  0.4762341790  <NA> #> 1187   2067    3M  CC02 2019 2019-11-04      DOSAT  3.2464909919  <NA> #> 1188   2067    3M  CC02 2019 2019-11-04       NO23 -4.4228486292  <NA> #> 1189   2067    3M  CC02 2019 2019-11-04      SALIN  3.5177945292  <NA> #> 1190   2067    3M  CC02 2019 2019-11-04        TKN -0.4307829161  <NA> #> 1191   2067    3M  CC02 2019 2019-11-04         TN -0.4124897230     + #> 1192   2067    3M  CC02 2019 2019-11-04         TP -2.5257286443  <NA> #> 1193   2067    3M  CC02 2019 2019-11-04       TURB  1.2809338455  <NA> #> 1194   2067    3M  CC02 2019 2019-12-02      CHLAC  0.0953101798     I #> 1195   2067    3M  CC02 2019 2019-12-02      COLOR  0.9162907319     U #> 1196   2067    3M  CC02 2019 2019-12-02         DO  0.9932517730  <NA> #> 1197   2067    3M  CC02 2019 2019-12-02      DOSAT  3.6454498962  <NA> #> 1198   2067    3M  CC02 2019 2019-12-02       NO23 -4.4228486292  <NA> #> 1199   2067    3M  CC02 2019 2019-12-02      SALIN  3.5133348816  <NA> #> 1200   2067    3M  CC02 2019 2019-12-02        TKN -0.7765287895  <NA> #> 1201   2067    3M  CC02 2019 2019-12-02         TN -0.7507762934     + #> 1202   2067    3M  CC02 2019 2019-12-02         TP -2.9374633654  <NA> #> 1203   2067    3M  CC02 2019 2019-12-02       TURB  0.7419373447  <NA> #> 1204   2067    3M  CC02 2020 2020-01-06      CHLAC  0.6931471806     I #> 1205   2067    3M  CC02 2020 2020-01-06      COLOR  2.5649493575  <NA> #> 1206   2067    3M  CC02 2020 2020-01-06       NO23 -4.2686979494  <NA> #> 1207   2067    3M  CC02 2020 2020-01-06      SALIN  3.4775409482  <NA> #> 1208   2067    3M  CC02 2020 2020-01-06        TKN -0.4620354596  <NA> #> 1209   2067    3M  CC02 2020 2020-01-06         TN -0.4400565529     + #> 1210   2067    3M  CC02 2020 2020-01-06         TP -2.3859667019  <NA> #> 1211   2067    3M  CC02 2020 2020-01-06       TURB  1.2809338455  <NA> #> 1212   2067    3M  CC02 2020 2020-02-03      CHLAC  0.9555114450     I #> 1213   2067    3M  CC02 2020 2020-02-03      COLOR  2.2721258855  <NA> #> 1214   2067    3M  CC02 2020 2020-02-03         DO  1.4929040962  <NA> #> 1215   2067    3M  CC02 2020 2020-02-03      DOSAT  4.0360089852  <NA> #> 1216   2067    3M  CC02 2020 2020-02-03       NO23 -4.3428059215  <NA> #> 1217   2067    3M  CC02 2020 2020-02-03      SALIN  3.4691675081  <NA> #> 1218   2067    3M  CC02 2020 2020-02-03        TKN -0.6931471806  <NA> #> 1219   2067    3M  CC02 2020 2020-02-03         TN -0.6674794338     + #> 1220   2067    3M  CC02 2020 2020-02-03         TP -2.5902671654  <NA> #> 1221   2067    3M  CC02 2020 2020-02-03       TURB  0.9932517730  <NA> #> 1222   2067    3M  CC02 2020 2020-03-02      CHLAC  0.5306282511     I #> 1223   2067    3M  CC02 2020 2020-03-02      COLOR  0.9162907319     U #> 1224   2067    3M  CC02 2020 2020-03-02         DO  1.8437192082  <NA> #> 1225   2067    3M  CC02 2020 2020-03-02      DOSAT  4.4067192473  <NA> #> 1226   2067    3M  CC02 2020 2020-03-02       NO23 -5.2983173665     I #> 1227   2067    3M  CC02 2020 2020-03-02      SALIN  3.5222343767  <NA> #> 1228   2067    3M  CC02 2020 2020-03-02         TN -0.8347107449     + #> 1229   2067    3M  CC02 2020 2020-03-02         TP -2.6736487744  <NA> #> 1230   2067    3M  CC02 2020 2020-03-02       TURB  1.7749523509     A #> 1231   2067    3M  CC02 2020 2020-09-08      CHLAC  1.4350845253  <NA> #> 1232   2067    3M  CC02 2020 2020-09-08      COLOR  3.9318256327     A #> 1233   2067    3M  CC02 2020 2020-09-08         DO  0.6259384309  <NA> #> 1234   2067    3M  CC02 2020 2020-09-08      DOSAT  3.3214324132  <NA> #> 1235   2067    3M  CC02 2020 2020-09-08       NO23 -4.2686979494  <NA> #> 1236   2067    3M  CC02 2020 2020-09-08      SALIN  3.2268439945  <NA> #> 1237   2067    3M  CC02 2020 2020-09-08        TKN -0.3856624808  <NA> #> 1238   2067    3M  CC02 2020 2020-09-08         TN -0.3652833185     + #> 1239   2067    3M  CC02 2020 2020-09-08         TP -2.5639498571  <NA> #> 1240   2067    3M  CC02 2020 2020-09-08       TURB  0.7419373447  <NA> #> 1241   2067    3M  CC02 2020 2020-10-05      CHLAC  0.8754687374     I #> 1242   2067    3M  CC02 2020 2020-10-05      COLOR  3.4339872045     A #> 1243   2067    3M  CC02 2020 2020-10-05         DO  0.7793248768  <NA> #> 1244   2067    3M  CC02 2020 2020-10-05      DOSAT  3.4038604991  <NA> #> 1245   2067    3M  CC02 2020 2020-10-05       NO23 -3.6496587410  <NA> #> 1246   2067    3M  CC02 2020 2020-10-05      SALIN  3.3769046891  <NA> #> 1247   2067    3M  CC02 2020 2020-10-05        TKN -0.5447271754  <NA> #> 1248   2067    3M  CC02 2020 2020-10-05         TN -0.5008752929     + #> 1249   2067    3M  CC02 2020 2020-10-05         TP -2.5510464523  <NA> #> 1250   2067    3M  CC02 2020 2020-10-05       TURB  0.8329091229     A #> 1251   2067    3M  CC02 2020 2020-11-02         TN -0.7256703723     + #> 1252   2067    3M  CC02 2020 2020-11-02      CHLAC  1.0647107370  <NA> #> 1253   2067    3M  CC02 2020 2020-11-02      COLOR  3.1354942159  <NA> #> 1254   2067    3M  CC02 2020 2020-11-02         DO  0.7654678421  <NA> #> 1255   2067    3M  CC02 2020 2020-11-02      DOSAT  3.4594662898  <NA> #> 1256   2067    3M  CC02 2020 2020-11-02       NO23 -4.2686979494  <NA> #> 1257   2067    3M  CC02 2020 2020-11-02      SALIN  3.3813347526  <NA> #> 1258   2067    3M  CC02 2020 2020-11-02        TKN -0.7550225843  <NA> #> 1259   2067    3M  CC02 2020 2020-11-02         TP -2.5639498571  <NA> #> 1260   2067    3M  CC02 2020 2020-11-02       TURB  1.3350010667  <NA> #> 1261   2067    3M  CC02 2020 2020-12-07      CHLAC -0.1984509387     U #> 1262   2067    3M  CC02 2020 2020-12-07      COLOR  2.0149030205  <NA> #> 1263   2067    3M  CC02 2020 2020-12-07         DO  1.2919836816  <NA> #> 1264   2067    3M  CC02 2020 2020-12-07      DOSAT  4.0656020934  <NA> #> 1265   2067    3M  CC02 2020 2020-12-07       NO23 -3.6119184130  <NA> #> 1266   2067    3M  CC02 2020 2020-12-07        TKN -0.8439700703  <NA> #> 1267   2067    3M  CC02 2020 2020-12-07         TN -0.7830718881     + #> 1268   2067    3M  CC02 2020 2020-12-07         TP -2.7646205526  <NA> #> 1269   2067    3M  CC02 2020 2020-12-07       TURB  0.6418538862  <NA> #> 1270   2067    3M  CC02 2021 2021-02-01      CHLAC  0.1823215568     I #> 1271   2067    3M  CC02 2021 2021-02-01      COLOR  0.9162907319     U #> 1272   2067    3M  CC02 2021 2021-02-01         DO  1.5953389881  <NA> #> 1273   2067    3M  CC02 2021 2021-02-01      DOSAT  4.1820501426  <NA> #> 1274   2067    3M  CC02 2021 2021-02-01       NO23 -4.9618451299     I #> 1275   2067    3M  CC02 2021 2021-02-01      SALIN  3.4882920885  <NA> #> 1276   2067    3M  CC02 2021 2021-02-01        TKN -0.7133498879  <NA> #> 1277   2067    3M  CC02 2021 2021-02-01         TN -0.7052197618     + #> 1278   2067    3M  CC02 2021 2021-02-01         TP -3.0159349809  <NA> #> 1279   2067    3M  CC02 2021 2021-02-01       TURB  0.7884573604  <NA> #> 1280   2067    3M  CC02 2021 2021-03-01      CHLAC  0.6418538862     I #> 1281   2067    3M  CC02 2021 2021-03-01      COLOR  1.5686159179     I #> 1282   2067    3M  CC02 2021 2021-03-01         DO  1.4327007339  <NA> #> 1283   2067    3M  CC02 2021 2021-03-01      DOSAT  4.1271343850  <NA> #> 1284   2067    3M  CC02 2021 2021-03-01       NO23 -5.1159958098     I #> 1285   2067    3M  CC02 2021 2021-03-01      SALIN  3.5331024525  <NA> #> 1286   2067    3M  CC02 2021 2021-03-01        TKN -0.8209805521  <NA> #> 1287   2067    3M  CC02 2021 2021-03-01         TN -0.8119307165     + #> 1288   2067    3M  CC02 2021 2021-03-01         TP -2.6450754019  <NA> #> 1289   2067    3M  CC02 2021 2021-03-01       TURB  1.5040773968  <NA> #> 1290   2067    3M  CC02 2021 2021-04-05         TN -1.8078888512     + #> 1291   2067    3M  CC02 2021 2021-04-05      CHLAC  0.4054651081     I #> 1292   2067    3M  CC02 2021 2021-04-05      COLOR  1.9021075264  <NA> #> 1293   2067    3M  CC02 2021 2021-04-05         DO  1.1631508098  <NA> #> 1294   2067    3M  CC02 2021 2021-04-05      DOSAT  3.7977338590  <NA> #> 1295   2067    3M  CC02 2021 2021-04-05       NO23 -4.9618451299     I #> 1296   2067    3M  CC02 2021 2021-04-05      SALIN  3.5325179990  <NA> #> 1297   2067    3M  CC02 2021 2021-04-05        TKN -0.9416085399     I #> 1298   2067    3M  CC02 2021 2021-04-05         TP -2.7030626596  <NA> #> 1299   2067    3M  CC02 2021 2021-04-05       TURB  1.1939224685  <NA> #> 1300   2067    3M  CC02 2021 2021-05-03      CHLAC  0.2623642645     I #> 1301   2067    3M  CC02 2021 2021-05-03      COLOR  1.9021075264  <NA> #> 1302   2067    3M  CC02 2021 2021-05-03         DO  0.8064758659  <NA> #> 1303   2067    3M  CC02 2021 2021-05-03      DOSAT  3.5553480615  <NA> #> 1304   2067    3M  CC02 2021 2021-05-03       NO23 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3M  CC02 2021 2021-06-07         TP -3.0159349809  <NA> #> 1319   2067    3M  CC02 2021 2021-06-07       TURB  0.6418538862  <NA> #> 1320   2067    3M  CC02 2021 2021-08-02      CHLAC  2.0668627595  <NA> #> 1321   2067    3M  CC02 2021 2021-08-02      COLOR  4.2626798770  <NA> #> 1322   2067    3M  CC02 2021 2021-08-02         DO  0.5128236264  <NA> #> 1323   2067    3M  CC02 2021 2021-08-02      DOSAT  3.2657594108  <NA> #> 1324   2067    3M  CC02 2021 2021-08-02       NO23 -5.5214609179     U #> 1325   2067    3M  CC02 2021 2021-08-02      SALIN  3.2846635654  <NA> #> 1326   2067    3M  CC02 2021 2021-08-02        TKN -0.1984509387  <NA> #> 1327   2067    3M  CC02 2021 2021-08-02         TN -0.1960148839     + #> 1328   2067    3M  CC02 2021 2021-08-02         TP -2.5639498571  <NA> #> 1329   2067    3M  CC02 2021 2021-08-02       TURB  0.9555114450  <NA> #> 1330   2067    3M  CC02 2021 2021-09-07      CHLAC  2.1633230257  <NA> #> 1331   2067    3M  CC02 2021 2021-09-07      COLOR  3.7841896339  <NA> #> 1332   2067    3M  CC02 2021 2021-09-07         DO  1.6863989536  <NA> #> 1333   2067    3M  CC02 2021 2021-09-07      DOSAT  4.4236483094  <NA> #> 1334   2067    3M  CC02 2021 2021-09-07       NO23 -5.2983173665     I #> 1335   2067    3M  CC02 2021 2021-09-07      SALIN  3.2771447330  <NA> #> 1336   2067    3M  CC02 2021 2021-09-07        TKN -0.1863295782  <NA> #> 1337   2067    3M  CC02 2021 2021-09-07         TN -0.1815218766     + #> 1338   2067    3M  CC02 2021 2021-09-07         TP -2.6310891600  <NA> #> 1339   2067    3M  CC02 2021 2021-09-07       TURB  0.9932517730  <NA> #> 1340   2067    3M  CC02 2021 2021-10-04      CHLAC  1.8718021769  <NA> #> 1341   2067    3M  CC02 2021 2021-10-04      COLOR  2.9444389792  <NA> #> 1342   2067    3M  CC02 2021 2021-10-04         DO  1.2354714714  <NA> #> 1343   2067    3M  CC02 2021 2021-10-04      DOSAT  3.9512437186  <NA> #> 1344   2067    3M  CC02 2021 2021-10-04       NO23 -5.5214609179     I #> 1345   2067    3M  CC02 2021 2021-10-04      SALIN  3.4525240088  <NA> #> 1346   2067    3M  CC02 2021 2021-10-04        TKN -0.5798184953  <NA> #> 1347   2067    3M  CC02 2021 2021-10-04         TN -0.5727010275     + #> 1348   2067    3M  CC02 2021 2021-10-04         TP -2.6882475738  <NA> #> 1349   2067    3M  CC02 2021 2021-10-04       TURB  0.8754687374     A #> 1350   2067    3M  CC02 2021 2021-11-01      CHLAC  1.1939224685  <NA> #> 1351   2067    3M  CC02 2021 2021-11-01      COLOR  2.7080502011  <NA> #> 1352   2067    3M  CC02 2021 2021-11-01         DO  1.4678743481  <NA> #> 1353   2067    3M  CC02 2021 2021-11-01      DOSAT  4.1287459889  <NA> #> 1354   2067    3M  CC02 2021 2021-11-01       NO23 -3.9633162998  <NA> #> 1355   2067    3M  CC02 2021 2021-11-01      SALIN  3.4992311219  <NA> #> 1356   2067    3M  CC02 2021 2021-11-01        TKN -0.5447271754  <NA> #> 1357   2067    3M  CC02 2021 2021-11-01         TN -0.5124936809     + #> 1358   2067    3M  CC02 2021 2021-11-01         TP 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3M  CC02 2022 2022-01-03         DO  1.7578579176  <NA> #> 1373   2067    3M  CC02 2022 2022-01-03      DOSAT  4.4224485492  <NA> #> 1374   2067    3M  CC02 2022 2022-01-03       NO23 -4.5098600062  <NA> #> 1375   2067    3M  CC02 2022 2022-01-03      SALIN  3.5174978374  <NA> #> 1376   2067    3M  CC02 2022 2022-01-03        TKN -0.8675005677  <NA> #> 1377   2067    3M  CC02 2022 2022-01-03         TN -0.8416471889     + #> 1378   2067    3M  CC02 2022 2022-01-03         TP -2.6882475738  <NA> #> 1379   2067    3M  CC02 2022 2022-01-03       TURB  0.7419373447  <NA> #> 1380   2067    3M  CC02 2022 2022-02-07      CHLAC  0.2623642645     I #> 1381   2067    3M  CC02 2022 2022-02-07      COLOR  0.9162907319     U #> 1382   2067    3M  CC02 2022 2022-02-07         DO  1.4996230464  <NA> #> 1383   2067    3M  CC02 2022 2022-02-07      DOSAT  4.0826093060  <NA> #> 1384   2067    3M  CC02 2022 2022-02-07       NO23 -4.5098600062  <NA> #> 1385   2067    3M  CC02 2022 2022-02-07      SALIN  3.5421180727  <NA> #> 1386   2067    3M  CC02 2022 2022-02-07        TKN -0.7985076962  <NA> #> 1387   2067    3M  CC02 2022 2022-02-07         TN -0.7743572360     + #> 1388   2067    3M  CC02 2022 2022-02-07         TP -2.8134107168  <NA> #> 1389   2067    3M  CC02 2022 2022-02-07       TURB  0.5877866649  <NA> #> 1390   2067    3M  CC02 2022 2022-03-07      CHLAC  0.4054651081     I #> 1391   2067    3M  CC02 2022 2022-03-07      COLOR  0.9162907319     U #> 1392   2067    3M  CC02 2022 2022-03-07         DO  1.4206957878  <NA> #> 1393   2067    3M  CC02 2022 2022-03-07      DOSAT  4.1059436981  <NA> #> 1394   2067    3M  CC02 2022 2022-03-07       NO23 -5.5214609179     U #> 1395   2067    3M  CC02 2022 2022-03-07      SALIN  3.5412491371  <NA> #> 1396   2067    3M  CC02 2022 2022-03-07        TKN -0.9162907319     I #> 1397   2067    3M  CC02 2022 2022-03-07         TN -1.8201589437     + #> 1398   2067    3M  CC02 2022 2022-03-07         TP -2.9004220937  <NA> #> 1399   2067    3M  CC02 2022 2022-03-07       TURB  0.9162907319  <NA> #> 1400   2067    3M  CC02 2022 2022-04-04      CHLAC  0.5877866649     I #> 1401   2067    3M  CC02 2022 2022-04-04      COLOR  0.9162907319     U #> 1402   2067    3M  CC02 2022 2022-04-04         DO  1.9430489168  <NA> #> 1403   2067    3M  CC02 2022 2022-04-04      DOSAT  4.6131383556  <NA> #> 1404   2067    3M  CC02 2022 2022-04-04       NO23 -4.7105307016     I #> 1405   2067    3M  CC02 2022 2022-04-04      SALIN  3.5599090728  <NA> #> 1406   2067    3M  CC02 2022 2022-04-04        TKN -1.2729656758     I #> 1407   2067    3M  CC02 2022 2022-04-04         TN -1.8078888512     + #> 1408   2067    3M  CC02 2022 2022-04-04         TP -2.7488721956  <NA> #> 1409   2067    3M  CC02 2022 2022-04-04       TURB  1.0296194172     A #> 1410   2067    3M  CC02 2022 2022-05-02      CHLAC  0.1823215568     I #> 1411   2067    3M  CC02 2022 2022-05-02      COLOR  0.9162907319     U #> 1412   2067    3M  CC02 2022 2022-05-02         DO  1.3244189574  <NA> #> 1413   2067    3M  CC02 2022 2022-05-02      DOSAT  4.0430512678  <NA> #> 1414   2067    3M  CC02 2022 2022-05-02       NO23 -4.7105307016     I #> 1415   2067    3M  CC02 2022 2022-05-02      SALIN  3.5768299503  <NA> #> 1416   2067    3M  CC02 2022 2022-05-02        TKN -0.7339691751  <NA> #> 1417   2067    3M  CC02 2022 2022-05-02         TN -0.7256703723     + #> 1418   2067    3M  CC02 2022 2022-05-02         TP -2.3025850930  <NA> #> 1419   2067    3M  CC02 2022 2022-05-02       TURB  0.4054651081  <NA> #> 1420   2067    3M  CC02 2022 2022-06-06      CHLAC  0.8754687374     I #> 1421   2067    3M  CC02 2022 2022-06-06      COLOR  2.5649493575  <NA> #> 1422   2067    3M  CC02 2022 2022-06-06         DO  1.0296194172  <NA> #> 1423   2067    3M  CC02 2022 2022-06-06      DOSAT  3.7887247891  <NA> #> 1424   2067    3M  CC02 2022 2022-06-06       NO23 -4.7105307016     I #> 1425   2067    3M  CC02 2022 2022-06-06      SALIN  3.5421180727  <NA> #> 1426   2067    3M  CC02 2022 2022-06-06        TKN -0.5621189182  <NA> #> 1427   2067    3M  CC02 2022 2022-06-06         TN -0.5551258827     + #> 1428   2067    3M  CC02 2022 2022-06-06         TP -3.0365542681  <NA> #> 1429   2067    3M  CC02 2022 2022-06-06       TURB  0.9555114450  <NA> #> 1430   2067    3M  CC02 2022 2022-07-05      CHLAC  1.8082887712  <NA> #> 1431   2067    3M  CC02 2022 2022-07-05      COLOR  1.0647107370     I #> 1432   2067    3M  CC02 2022 2022-07-05         DO  1.4255150743  <NA> #> 1433   2067    3M  CC02 2022 2022-07-05      DOSAT  4.2268337453  <NA> #> 1434   2067    3M  CC02 2022 2022-07-05       NO23 -5.2983173665     I #> 1435   2067    3M  CC02 2022 2022-07-05      SALIN  3.5519135990  <NA> #> 1436   2067    3M  CC02 2022 2022-07-05        TKN -0.5108256238  <NA> #> 1437   2067    3M  CC02 2022 2022-07-05         TN -0.5041810810     + #> 1438   2067    3M  CC02 2022 2022-07-05         TP -3.1235656451  <NA> #> 1439   2067    3M  CC02 2022 2022-07-05       TURB  1.3862943611     A #> 1440   2067    3M  CC02 2022 2022-08-01      CHLAC  0.8329091229     I #> 1441   2067    3M  CC02 2022 2022-08-01      COLOR  1.7404661748     I #> 1442   2067    3M  CC02 2022 2022-08-01         DO  1.6370530795  <NA> #> 1443   2067    3M  CC02 2022 2022-08-01      DOSAT  4.4248466319  <NA> #> 1444   2067    3M  CC02 2022 2022-08-01       NO23 -4.6051701860  <NA> #> 1445   2067    3M  CC02 2022 2022-08-01      SALIN  3.5478917608  <NA> #> 1446   2067    3M  CC02 2022 2022-08-01        TKN -0.5108256238  <NA> #> 1447   2067    3M  CC02 2022 2022-08-01         TN -0.4942963218     + #> 1448   2067    3M  CC02 2022 2022-08-01         TP -3.0576076773  <NA> #> 1449   2067    3M  CC02 2022 2022-08-01       TURB  0.8754687374  <NA> #> 1450   2067    3M  CC02 2022 2022-09-06      CHLAC  1.3609765531  <NA> #> 1451   2067    3M  CC02 2022 2022-09-06      COLOR  2.7080502011  <NA> #> 1452   2067    3M  CC02 2022 2022-09-06       NO23 -4.8283137373     I #> 1453   2067    3M  CC02 2022 2022-09-06      SALIN  3.5157158351  <NA> #> 1454   2067    3M  CC02 2022 2022-09-06        TKN -0.7985076962  <NA> #> 1455   2067    3M  CC02 2022 2022-09-06         TN -0.7896580809     + #> 1456   2067    3M  CC02 2022 2022-09-06         TP -3.2441936329  <NA> #> 1457   2067    3M  CC02 2022 2022-09-06       TURB  0.7884573604  <NA> #> 1458   2067    3M  CC02 2022 2022-11-07      CHLAC  2.3978952728  <NA> #> 1459   2067    3M  CC02 2022 2022-11-07      COLOR  3.5553480615     A #> 1460   2067    3M  CC02 2022 2022-11-07         DO  1.4011829736  <NA> #> 1461   2067    3M  CC02 2022 2022-11-07      DOSAT  4.0724397268  <NA> #> 1462   2067    3M  CC02 2022 2022-11-07       NO23 -5.5214609179     U #> 1463   2067    3M  CC02 2022 2022-11-07      SALIN  3.3714252233  <NA> #> 1464   2067    3M  CC02 2022 2022-11-07        TKN -0.3710636814  <NA> #> 1465   2067    3M  CC02 2022 2022-11-07         TN -0.3681693234     + #> 1466   2067    3M  CC02 2022 2022-11-07         TP 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3M  CC02 2023 2023-01-03       NO23 -5.5214609179     U #> 1481   2067    3M  CC02 2023 2023-01-03      SALIN  3.4249139083  <NA> #> 1482   2067    3M  CC02 2023 2023-01-03        TKN -0.5798184953  <NA> #> 1483   2067    3M  CC02 2023 2023-01-03         TN -0.5762534291     + #> 1484   2067    3M  CC02 2023 2023-01-03         TP -2.5383074265  <NA> #> 1485   2067    3M  CC02 2023 2023-01-03       TURB  1.0296194172  <NA> #> 1486   2067    3M  CC02 2023 2023-02-06      CHLAC  0.8754687374     I #> 1487   2067    3M  CC02 2023 2023-02-06      COLOR  2.1747517215  <NA> #> 1488   2067    3M  CC02 2023 2023-02-06         DO  1.8017098001  <NA> #> 1489   2067    3M  CC02 2023 2023-02-06      DOSAT  4.4260435201  <NA> #> 1490   2067    3M  CC02 2023 2023-02-06       NO23 -5.1159958098     I #> 1491   2067    3M  CC02 2023 2023-02-06      SALIN  3.4895134627  <NA> #> 1492   2067    3M  CC02 2023 2023-02-06        TKN -0.7765287895  <NA> #> 1493   2067    3M  CC02 2023 2023-02-06         TN 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3M  CC02 2018 2018-03-13         TP -3.1465551633  <NA> #> 1508   2067    3M  CC02 2018 2018-03-13        TSS  2.4849066498  <NA> #> 1509   2067    3M  CC02 2018 2018-03-13       TURB  1.0296194172  <NA> #> 1510   2067    3M  CC02 2018 2018-05-08      CHLAC  1.3083328197  <NA> #> 1511   2067    3M  CC02 2018 2018-05-08       COND 10.9059926772  <NA> #> 1512   2067    3M  CC02 2018 2018-05-08         DO  1.5953389881  <NA> #> 1513   2067    3M  CC02 2018 2018-05-08      DOSAT  4.2904594411  <NA> #> 1514   2067    3M  CC02 2018 2018-05-08       NO23 -5.5214609179     U #> 1515   2067    3M  CC02 2018 2018-05-08      SALIN  3.5481795720     + #> 1516   2067    3M  CC02 2018 2018-05-08        TKN -0.4462871026  <NA> #> 1517   2067    3M  CC02 2018 2018-05-08         TN -0.4431669753     + #> 1518   2067    3M  CC02 2018 2018-05-08         TP -2.7181005370  <NA> #> 1519   2067    3M  CC02 2018 2018-05-08        TSS  1.6094379124     I #> 1520   2067    3M  CC02 2018 2018-05-08       TURB  1.2237754316  <NA> #> 1521   2067    3M  CC02 2018 2018-06-26      CHLAC  2.5649493575  <NA> #> 1522   2067    3M  CC02 2018 2018-06-26       COND 10.6878456131  <NA> #> 1523   2067    3M  CC02 2018 2018-06-26         DO  1.2947271676  <NA> #> 1524   2067    3M  CC02 2018 2018-06-26      DOSAT  4.0395363257  <NA> #> 1525   2067    3M  CC02 2018 2018-06-26       NO23 -4.9618451299     I #> 1526   2067    3M  CC02 2018 2018-06-26        TKN -0.3566749439  <NA> #> 1527   2067    3M  CC02 2018 2018-06-26         TN -0.3509769228     + #> 1528   2067    3M  CC02 2018 2018-06-26         TP -2.3025850930  <NA> #> 1529   2067    3M  CC02 2018 2018-06-26        TSS  2.0794415417     I #> 1530   2067    3M  CC02 2018 2018-06-26       TURB  1.0647107370     A #> 1531   2067    3M  CC02 2018 2018-09-18      CHLAC  2.3978952728  <NA> #> 1532   2067    3M  CC02 2018 2018-09-18       COND 10.2632925926  <NA> #> 1533   2067    3M  CC02 2018 2018-09-18         DO  0.9745596400  <NA> #> 1534   2067    3M  CC02 2018 2018-09-18      DOSAT  3.6963514690  <NA> #> 1535   2067    3M  CC02 2018 2018-09-18       NO23 -3.2188758249  <NA> #> 1536   2067    3M  CC02 2018 2018-09-18        TKN -0.2231435513  <NA> #> 1537   2067    3M  CC02 2018 2018-09-18         TN -0.1743533871     + #> 1538   2067    3M  CC02 2018 2018-09-18         TP -2.0402208285  <NA> #> 1539   2067    3M  CC02 2018 2018-09-18        TSS  1.3862943611     I #> 1540   2067    3M  CC02 2018 2018-09-18       TURB  0.7884573604  <NA> #> 1541   2067    3M  CC02 2018 2018-12-04      CHLAC  1.2809338455  <NA> #> 1542   2067    3M  CC02 2018 2018-12-04       COND 10.8257007122  <NA> #> 1543   2067    3M  CC02 2018 2018-12-04         DO  1.6272778306  <NA> #> 1544   2067    3M  CC02 2018 2018-12-04      DOSAT  4.3107991254  <NA> #> 1545   2067    3M  CC02 2018 2018-12-04       NO23 -1.9661128564     G #> 1546   2067    3M  CC02 2018 2018-12-04      SALIN  3.4949912609  <NA> #> 1547   2067    3M  CC02 2018 2018-12-04        TKN -0.4155154440  <NA> #> 1548   2067    3M  CC02 2018 2018-12-04         TN -0.2231435513     + #> 1549   2067    3M  CC02 2018 2018-12-04         TP -2.5010360317  <NA> #> 1550   2067    3M  CC02 2018 2018-12-04        TSS  2.3025850930     I #> 1551   2067    3M  CC02 2018 2018-12-04       TURB  0.4054651081  <NA> #> 1552   2068    3M  CC03 2014 2014-01-06      CHLAC  0.3364722366     I #> 1553   2068    3M  CC03 2014 2014-01-06      COLOR  2.5649493575  <NA> #> 1554   2068    3M  CC03 2014 2014-01-06         DO  1.3862943611  <NA> #> 1555   2068    3M  CC03 2014 2014-01-06      DOSAT  3.9963641539     + #> 1556   2068    3M  CC03 2014 2014-01-06       NO23 -4.7105307016     I #> 1557   2068    3M  CC03 2014 2014-01-06      SALIN  3.4904285154  <NA> #> 1558   2068    3M  CC03 2014 2014-01-06        TKN -0.6161861394  <NA> #> 1559   2068    3M  CC03 2014 2014-01-06         TN -0.6088060321     + #> 1560   2068    3M  CC03 2014 2014-01-06         TP -3.1010927892  <NA> #> 1561   2068    3M  CC03 2014 2014-01-06       TURB  0.4054651081  <NA> #> 1562   2068    3M  CC03 2014 2014-02-03      CHLAC  1.8870696490  <NA> #> 1563   2068    3M  CC03 2014 2014-02-03      COLOR  3.5263605246  <NA> #> 1564   2068    3M  CC03 2014 2014-02-03         DO  0.7884573604  <NA> #> 1565   2068    3M  CC03 2014 2014-02-03      DOSAT  3.2921262866     + #> 1566   2068    3M  CC03 2014 2014-02-03       NO23 -3.6888794541  <NA> #> 1567   2068    3M  CC03 2014 2014-02-03      SALIN  2.6602595373  <NA> #> 1568   2068    3M  CC03 2014 2014-02-03        TKN  0.0000000000  <NA> #> 1569   2068    3M  CC03 2014 2014-02-03         TN  0.0246926126     + #> 1570   2068    3M  CC03 2014 2014-02-03         TP -2.3025850930  <NA> #> 1571   2068    3M  CC03 2014 2014-02-03       TURB  0.8329091229  <NA> #> 1572   2068    3M  CC03 2014 2014-03-03      CHLAC  1.0986122887  <NA> #> 1573   2068    3M  CC03 2014 2014-03-03      COLOR  2.8332133441  <NA> #> 1574   2068    3M  CC03 2014 2014-03-03         DO  0.7884573604  <NA> #> 1575   2068    3M  CC03 2014 2014-03-03      DOSAT  3.3638415951     + #> 1576   2068    3M  CC03 2014 2014-03-03       NO23 -5.5214609179     I #> 1577   2068    3M  CC03 2014 2014-03-03      SALIN  3.2657594108  <NA> #> 1578   2068    3M  CC03 2014 2014-03-03        TKN -0.4462871026  <NA> #> 1579   2068    3M  CC03 2014 2014-03-03         TN -0.4400565529     + #> 1580   2068    3M  CC03 2014 2014-03-03         TP -2.6592600369  <NA> #> 1581   2068    3M  CC03 2014 2014-03-03       TURB  0.7884573604  <NA> #> 1582   2068    3M  CC03 2014 2014-04-07      CHLAC  1.2237754316  <NA> #> 1583   2068    3M  CC03 2014 2014-04-07      COLOR  3.4011973817     A #> 1584   2068    3M  CC03 2014 2014-04-07         DO  0.6418538862  <NA> #> 1585   2068    3M  CC03 2014 2014-04-07      DOSAT  3.2580965380     + #> 1586   2068    3M  CC03 2014 2014-04-07       NO23 -4.3428059215  <NA> #> 1587   2068    3M  CC03 2014 2014-04-07      SALIN  3.1000922889  <NA> #> 1588   2068    3M  CC03 2014 2014-04-07        TKN -0.1392620673  <NA> #> 1589   2068    3M  CC03 2014 2014-04-07         TN -0.1244300784     + #> 1590   2068    3M  CC03 2014 2014-04-07         TP -2.3968957725  <NA> #> 1591   2068    3M  CC03 2014 2014-04-07       TURB  0.3364722366     A #> 1592   2068    3M  CC03 2014 2014-05-05      CHLAC  2.3978952728  <NA> #> 1593   2068    3M  CC03 2014 2014-05-05      COLOR  3.9120230054  <NA> #> 1594   2068    3M  CC03 2014 2014-05-05         DO  0.0000000000  <NA> #> 1595   2068    3M  CC03 2014 2014-05-05      DOSAT  2.5649493575     + #> 1596   2068    3M  CC03 2014 2014-05-05       NO23 -3.4112477175  <NA> #> 1597   2068    3M  CC03 2014 2014-05-05      SALIN  2.8622008809  <NA> #> 1598   2068    3M  CC03 2014 2014-05-05        TKN -0.0512932944  <NA> #> 1599   2068    3M  CC03 2014 2014-05-05         TN -0.0171461588     + #> 1600   2068    3M  CC03 2014 2014-05-05         TP -2.3025850930  <NA> #> 1601   2068    3M  CC03 2014 2014-05-05       TURB  1.0647107370  <NA> #> 1602   2068    3M  CC03 2014 2014-06-02      CHLAC  1.8245492921  <NA> #> 1603   2068    3M  CC03 2014 2014-06-02      COLOR  3.9120230054     A #> 1604   2068    3M  CC03 2014 2014-06-02         DO -1.2039728043  <NA> #> 1605   2068    3M  CC03 2014 2014-06-02      DOSAT  1.4350845253     + #> 1606   2068    3M  CC03 2014 2014-06-02       NO23 -5.2983173665     I #> 1607   2068    3M  CC03 2014 2014-06-02      SALIN  3.0633909220  <NA> #> 1608   2068    3M  CC03 2014 2014-06-02        TKN -0.2744368457  <NA> #> 1609   2068    3M  CC03 2014 2014-06-02         TN -0.2691874898     + #> 1610   2068    3M  CC03 2014 2014-06-02         TP -2.9957322736  <NA> #> 1611   2068    3M  CC03 2014 2014-06-02       TURB  0.5877866649  <NA> #> 1612   2068    3M  CC03 2014 2014-07-07      CHLAC  1.4350845253  <NA> #> 1613   2068    3M  CC03 2014 2014-07-07      COLOR  3.6375861597     A #> 1614   2068    3M  CC03 2014 2014-07-07         DO -0.9162907319  <NA> #> 1615   2068    3M  CC03 2014 2014-07-07      DOSAT  1.8562979904     + #> 1616   2068    3M  CC03 2014 2014-07-07       NO23 -5.5214609179     I #> 1617   2068    3M  CC03 2014 2014-07-07      SALIN  3.5438536821  <NA> #> 1618   2068    3M  CC03 2014 2014-07-07        TKN -0.2357223335  <NA> #> 1619   2068    3M  CC03 2014 2014-07-07         TN -0.2306718177     + #> 1620   2068    3M  CC03 2014 2014-07-07         TP -3.1235656451  <NA> #> 1621   2068    3M  CC03 2014 2014-07-07       TURB  1.8082887712  <NA> #> 1622   2068    3M  CC03 2014 2014-08-04      CHLAC  1.6292405397  <NA> #> 1623   2068    3M  CC03 2014 2014-08-04      COLOR  3.6375861597  <NA> #> 1624   2068    3M  CC03 2014 2014-08-04         DO -0.3566749439  <NA> #> 1625   2068    3M  CC03 2014 2014-08-04      DOSAT  2.3887627892     + #> 1626   2068    3M  CC03 2014 2014-08-04       NO23 -5.5214609179     I #> 1627   2068    3M  CC03 2014 2014-08-04      SALIN  3.4242626546  <NA> #> 1628   2068    3M  CC03 2014 2014-08-04        TKN -0.1508228897  <NA> #> 1629   2068    3M  CC03 2014 2014-08-04         TN -0.1461825102     + #> 1630   2068    3M  CC03 2014 2014-08-04         TP -2.9565115604  <NA> #> 1631   2068    3M  CC03 2014 2014-08-04       TURB  1.2809338455  <NA> #> 1632   2068    3M  CC03 2014 2014-09-08      CHLAC  2.3025850930  <NA> #> 1633   2068    3M  CC03 2014 2014-09-08      COLOR  3.2958368660  <NA> #> 1634   2068    3M  CC03 2014 2014-09-08         DO -1.2039728043  <NA> #> 1635   2068    3M  CC03 2014 2014-09-08      DOSAT  1.5040773968     + #> 1636   2068    3M  CC03 2014 2014-09-08       NO23 -5.5214609179     U #> 1637   2068    3M  CC03 2014 2014-09-08      SALIN  3.4011973817  <NA> #> 1638   2068    3M  CC03 2014 2014-09-08        TKN -0.1508228897  <NA> #> 1639   2068    3M  CC03 2014 2014-09-08         TN -0.1485000083     + #> 1640   2068    3M  CC03 2014 2014-09-08         TP -2.8824035882  <NA> #> 1641   2068    3M  CC03 2014 2014-09-08       TURB  1.1631508098  <NA> #> 1642   2068    3M  CC03 2014 2014-10-06      CHLAC  2.3025850930  <NA> #> 1643   2068    3M  CC03 2014 2014-10-06      COLOR  4.1588830834  <NA> #> 1644   2068    3M  CC03 2014 2014-10-06         DO  0.6931471806  <NA> #> 1645   2068    3M  CC03 2014 2014-10-06      DOSAT  3.2464909919     + #> 1646   2068    3M  CC03 2014 2014-10-06       NO23 -4.7105307016     I #> 1647   2068    3M  CC03 2014 2014-10-06      SALIN  2.7080502011  <NA> #> 1648   2068    3M  CC03 2014 2014-10-06        TKN -0.1165338163  <NA> #> 1649   2068    3M  CC03 2014 2014-10-06         TN -0.1120495038     + #> 1650   2068    3M  CC03 2014 2014-10-06         TP -1.9661128564  <NA> #> 1651   2068    3M  CC03 2014 2014-10-06       TURB  1.1631508098  <NA> #> 1652   2068    3M  CC03 2014 2014-11-03      CHLAC  2.3978952728  <NA> #> 1653   2068    3M  CC03 2014 2014-11-03      COLOR  3.5835189385  <NA> #> 1654   2068    3M  CC03 2014 2014-11-03         DO  1.3862943611  <NA> #> 1655   2068    3M  CC03 2014 2014-11-03      DOSAT  3.8543938926     + #> 1656   2068    3M  CC03 2014 2014-11-03       NO23 -4.5098600062  <NA> #> 1657   2068    3M  CC03 2014 2014-11-03      SALIN  3.1612467120  <NA> #> 1658   2068    3M  CC03 2014 2014-11-03        TKN -0.1743533871  <NA> #> 1659   2068    3M  CC03 2014 2014-11-03         TN -0.1613431504     + #> 1660   2068    3M  CC03 2014 2014-11-03         TP -2.6036901858  <NA> #> 1661   2068    3M  CC03 2014 2014-11-03       TURB  1.0647107370  <NA> #> 1662   2068    3M  CC03 2015 2015-01-05      CHLAC  2.0281482473  <NA> #> 1663   2068    3M  CC03 2015 2015-01-05      COLOR  3.2188758249  <NA> #> 1664   2068    3M  CC03 2015 2015-01-05         DO  0.9162907319  <NA> #> 1665   2068    3M  CC03 2015 2015-01-05      DOSAT  3.5438536821     + #> 1666   2068    3M  CC03 2015 2015-01-05       NO23 -4.4228486292  <NA> #> 1667   2068    3M  CC03 2015 2015-01-05      SALIN  3.2995337279  <NA> #> 1668   2068    3M  CC03 2015 2015-01-05        TKN -0.0512932944  <NA> #> 1669   2068    3M  CC03 2015 2015-01-05         TN -0.0387408283     + #> 1670   2068    3M  CC03 2015 2015-01-05         TP -2.5383074265  <NA> #> 1671   2068    3M  CC03 2015 2015-01-05       TURB  0.6418538862  <NA> #> 1672   2068    3M  CC03 2015 2015-02-02      CHLAC  0.6418538862  <NA> #> 1673   2068    3M  CC03 2015 2015-02-02      COLOR  2.3025850930  <NA> #> 1674   2068    3M  CC03 2015 2015-02-02         DO  1.4109869737  <NA> #> 1675   2068    3M  CC03 2015 2015-02-02      DOSAT  3.9778107460     + #> 1676   2068    3M  CC03 2015 2015-02-02       NO23 -5.1159958098     I #> 1677   2068    3M  CC03 2015 2015-02-02      SALIN  3.3911470458  <NA> #> 1678   2068    3M  CC03 2015 2015-02-02        TKN -0.7765287895  <NA> #> 1679   2068    3M  CC03 2015 2015-02-02         TN -0.7678707268     + #> 1680   2068    3M  CC03 2015 2015-02-02         TP -2.9957322736  <NA> #> 1681   2068    3M  CC03 2015 2015-02-02       TURB  0.3364722366  <NA> #> 1682   2068    3M  CC03 2015 2015-03-02      CHLAC  1.6677068206     A #> 1683   2068    3M  CC03 2015 2015-03-02      COLOR  3.1354942159  <NA> #> 1684   2068    3M  CC03 2015 2015-03-02         DO  0.9932517730  <NA> #> 1685   2068    3M  CC03 2015 2015-03-02      DOSAT  3.5862928653     + #> 1686   2068    3M  CC03 2015 2015-03-02       NO23 -4.5098600062  <NA> #> 1687   2068    3M  CC03 2015 2015-03-02      SALIN  3.1311369106  <NA> #> 1688   2068    3M  CC03 2015 2015-03-02        TKN -0.4780358009  <NA> #> 1689   2068    3M  CC03 2015 2015-03-02         TN -0.4604494164     + #> 1690   2068    3M  CC03 2015 2015-03-02         TP -2.8824035882  <NA> #> 1691   2068    3M  CC03 2015 2015-03-02       TURB  0.3364722366  <NA> #> 1692   2068    3M  CC03 2015 2015-04-06      CHLAC  0.8754687374  <NA> #> 1693   2068    3M  CC03 2015 2015-04-06      COLOR  3.0910424534  <NA> #> 1694   2068    3M  CC03 2015 2015-04-06         DO -0.1053605157  <NA> #> 1695   2068    3M  CC03 2015 2015-04-06      DOSAT  2.5494451709     + #> 1696   2068    3M  CC03 2015 2015-04-06       NO23 -5.5214609179     U #> 1697   2068    3M  CC03 2015 2015-04-06      SALIN  3.4011973817  <NA> #> 1698   2068    3M  CC03 2015 2015-04-06        TKN -0.3566749439  <NA> #> 1699   2068    3M  CC03 2015 2015-04-06         TN -0.3538218750     + #> 1700   2068    3M  CC03 2015 2015-04-06         TP -3.2188758249  <NA> #> 1701   2068    3M  CC03 2015 2015-04-06       TURB  0.4700036292  <NA> #> 1702   2068    3M  CC03 2015 2015-05-04      CHLAC  0.9932517730  <NA> #> 1703   2068    3M  CC03 2015 2015-05-04      COLOR  3.2188758249  <NA> #> 1704   2068    3M  CC03 2015 2015-05-04         DO  0.1823215568  <NA> #> 1705   2068    3M  CC03 2015 2015-05-04      DOSAT  2.8622008809     + #> 1706   2068    3M  CC03 2015 2015-05-04       NO23 -4.8283137373     I #> 1707   2068    3M  CC03 2015 2015-05-04      SALIN  3.4904285154  <NA> #> 1708   2068    3M  CC03 2015 2015-05-04        TKN -0.3856624808  <NA> #> 1709   2068    3M  CC03 2015 2015-05-04         TN -0.3797973614     + #> 1710   2068    3M  CC03 2015 2015-05-04         TP -3.2968373663  <NA> #> 1711   2068    3M  CC03 2015 2015-05-04       TURB  0.6931471806  <NA> #> 1712   2068    3M  CC03 2015 2015-06-01      CHLAC  1.7749523509  <NA> #> 1713   2068    3M  CC03 2015 2015-06-01      COLOR  3.3322045102  <NA> #> 1714   2068    3M  CC03 2015 2015-06-01         DO -0.6931471806  <NA> #> 1715   2068    3M  CC03 2015 2015-06-01      DOSAT  2.0149030205     + #> 1716   2068    3M  CC03 2015 2015-06-01       NO23 -5.1159958098     I #> 1717   2068    3M  CC03 2015 2015-06-01      SALIN  3.3945083935  <NA> #> 1718   2068    3M  CC03 2015 2015-06-01        TKN -0.1625189295  <NA> #> 1719   2068    3M  CC03 2015 2015-06-01         TN -0.1578240852     + #> 1720   2068    3M  CC03 2015 2015-06-01         TP -2.9759296463  <NA> #> 1721   2068    3M  CC03 2015 2015-06-01       TURB  0.9555114450  <NA> #> 1722   2068    3M  CC03 2015 2015-08-03      CHLAC  3.1354942159  <NA> #> 1723   2068    3M  CC03 2015 2015-08-03      COLOR  4.1108738642  <NA> #> 1724   2068    3M  CC03 2015 2015-08-03         DO -0.6931471806  <NA> #> 1725   2068    3M  CC03 2015 2015-08-03      DOSAT  1.9021075264     + #> 1726   2068    3M  CC03 2015 2015-08-03       NO23 -4.6051701860     I #> 1727   2068    3M  CC03 2015 2015-08-03      SALIN  2.3887627892  <NA> #> 1728   2068    3M  CC03 2015 2015-08-03        TKN  0.3364722366  <NA> #> 1729   2068    3M  CC03 2015 2015-08-03         TN  0.3393253056     + #> 1730   2068    3M  CC03 2015 2015-08-03         TP -2.4418471603  <NA> #> 1731   2068    3M  CC03 2015 2015-08-03       TURB  1.5892352051  <NA> #> 1732   2068    3M  CC03 2015 2015-09-08      CHLAC  1.7227665977  <NA> #> 1733   2068    3M  CC03 2015 2015-09-08      COLOR  3.8286413965  <NA> #> 1734   2068    3M  CC03 2015 2015-09-08         DO  0.0000000000  <NA> #> 1735   2068    3M  CC03 2015 2015-09-08      DOSAT  2.6602595373     + #> 1736   2068    3M  CC03 2015 2015-09-08       NO23 -4.8283137373     I #> 1737   2068    3M  CC03 2015 2015-09-08      SALIN  2.9014215941  <NA> #> 1738   2068    3M  CC03 2015 2015-09-08        TKN -0.2357223335  <NA> #> 1739   2068    3M  CC03 2015 2015-09-08         TN -0.2306718177     + #> 1740   2068    3M  CC03 2015 2015-09-08         TP -3.0159349809  <NA> #> 1741   2068    3M  CC03 2015 2015-09-08       TURB  0.6931471806  <NA> #> 1742   2068    3M  CC03 2015 2015-10-05      CHLAC  1.4586150227  <NA> #> 1743   2068    3M  CC03 2015 2015-10-05      COLOR  3.2958368660     A #> 1744   2068    3M  CC03 2015 2015-10-05         DO  0.6418538862  <NA> #> 1745   2068    3M  CC03 2015 2015-10-05      DOSAT  3.3214324132     + #> 1746   2068    3M  CC03 2015 2015-10-05       NO23 -5.5214609179     U #> 1747   2068    3M  CC03 2015 2015-10-05      SALIN  3.3741687093  <NA> #> 1748   2068    3M  CC03 2015 2015-10-05        TKN -0.4307829161  <NA> #> 1749   2068    3M  CC03 2015 2015-10-05         TN -0.4277107171     + #> 1750   2068    3M  CC03 2015 2015-10-05         TP -3.0576076773  <NA> #> 1751   2068    3M  CC03 2015 2015-10-05       TURB  0.8754687374  <NA> #> 1752   2068    3M  CC03 2015 2015-12-07      CHLAC  1.3609765531  <NA> #> 1753   2068    3M  CC03 2015 2015-12-07      COLOR  3.2188758249  <NA> #> 1754   2068    3M  CC03 2015 2015-12-07         DO  1.1314021115  <NA> #> 1755   2068    3M  CC03 2015 2015-12-07      DOSAT  3.7447870861     + #> 1756   2068    3M  CC03 2015 2015-12-07       NO23 -4.5098600062  <NA> #> 1757   2068    3M  CC03 2015 2015-12-07      SALIN  3.4144426084  <NA> #> 1758   2068    3M  CC03 2015 2015-12-07        TKN -0.4462871026  <NA> #> 1759   2068    3M  CC03 2015 2015-12-07         TN -0.4292456368     + #> 1760   2068    3M  CC03 2015 2015-12-07         TP -2.8473122684  <NA> #> 1761   2068    3M  CC03 2015 2015-12-07       TURB  1.1939224685  <NA> #> 1762   2068    3M  CC03 2016 2016-01-04      CHLAC  1.3083328197  <NA> #> 1763   2068    3M  CC03 2016 2016-01-04      COLOR  3.3672958300  <NA> #> 1764   2068    3M  CC03 2016 2016-01-04         DO  0.0000000000  <NA> #> 1765   2068    3M  CC03 2016 2016-01-04      DOSAT  2.5176964726     + #> 1766   2068    3M  CC03 2016 2016-01-04       NO23 -4.0173835211  <NA> #> 1767   2068    3M  CC03 2016 2016-01-04      SALIN  3.1904763503  <NA> #> 1768   2068    3M  CC03 2016 2016-01-04        TKN -0.3566749439  <NA> #> 1769   2068    3M  CC03 2016 2016-01-04         TN -0.3312857099     + #> 1770   2068    3M  CC03 2016 2016-01-04         TP -2.6172958378  <NA> #> 1771   2068    3M  CC03 2016 2016-01-04       TURB  0.8754687374  <NA> #> 1772   2068    3M  CC03 2016 2016-02-01      CHLAC  1.0647107370  <NA> #> 1773   2068    3M  CC03 2016 2016-02-01      COLOR  3.6635616461  <NA> #> 1774   2068    3M  CC03 2016 2016-02-01      DOSAT  3.7256934272     + #> 1775   2068    3M  CC03 2016 2016-02-01       NO23 -2.7030626596  <NA> #> 1776   2068    3M  CC03 2016 2016-02-01      SALIN  2.7850112422  <NA> #> 1777   2068    3M  CC03 2016 2016-02-01        TKN -0.2357223335  <NA> #> 1778   2068    3M  CC03 2016 2016-02-01         TN -0.1543173604     + #> 1779   2068    3M  CC03 2016 2016-02-01         TP -2.0402208285  <NA> #> 1780   2068    3M  CC03 2016 2016-02-01       TURB  0.6418538862  <NA> #> 1781   2068    3M  CC03 2016 2016-03-07      CHLAC  1.7227665977  <NA> #> 1782   2068    3M  CC03 2016 2016-03-07      COLOR  3.5835189385  <NA> #> 1783   2068    3M  CC03 2016 2016-03-07         DO  0.8329091229  <NA> #> 1784   2068    3M  CC03 2016 2016-03-07      DOSAT  3.2995337279     + #> 1785   2068    3M  CC03 2016 2016-03-07       NO23 -4.7105307016     I #> 1786   2068    3M  CC03 2016 2016-03-07      SALIN  2.7080502011  <NA> #> 1787   2068    3M  CC03 2016 2016-03-07        TKN -0.3011050928  <NA> #> 1788   2068    3M  CC03 2016 2016-03-07         TN -0.2957142441     + #> 1789   2068    3M  CC03 2016 2016-03-07         TP -2.3025850930  <NA> #> 1790   2068    3M  CC03 2016 2016-03-07       TURB  1.1631508098     A #> 1791   2068    3M  CC03 2016 2016-04-04      CHLAC  0.9932517730  <NA> #> 1792   2068    3M  CC03 2016 2016-04-04      COLOR  3.5263605246  <NA> #> 1793   2068    3M  CC03 2016 2016-04-04         DO  0.9555114450  <NA> #> 1794   2068    3M  CC03 2016 2016-04-04      DOSAT  3.5263605246     + #> 1795   2068    3M  CC03 2016 2016-04-04       NO23 -4.5098600062  <NA> #> 1796   2068    3M  CC03 2016 2016-04-04      SALIN  3.0007198151  <NA> #> 1797   2068    3M  CC03 2016 2016-04-04        TKN -0.3566749439  <NA> #> 1798   2068    3M  CC03 2016 2016-04-04         TN -0.3410828492     + #> 1799   2068    3M  CC03 2016 2016-04-04         TP -2.3859667019  <NA> #> 1800   2068    3M  CC03 2016 2016-04-04       TURB  1.0296194172  <NA> #> 1801   2068    3M  CC03 2016 2016-05-02      CHLAC  0.3364722366     I #> 1802   2068    3M  CC03 2016 2016-05-02      COLOR  3.2580965380  <NA> #> 1803   2068    3M  CC03 2016 2016-05-02         DO  0.7884573604  <NA> #> 1804   2068    3M  CC03 2016 2016-05-02      DOSAT  3.5234150144     + #> 1805   2068    3M  CC03 2016 2016-05-02       NO23 -5.5214609179     U #> 1806   2068    3M  CC03 2016 2016-05-02      SALIN  3.6270040504  <NA> #> 1807   2068    3M  CC03 2016 2016-05-02        TKN -0.3566749439  <NA> #> 1808   2068    3M  CC03 2016 2016-05-02         TN -0.3538218750     + #> 1809   2068    3M  CC03 2016 2016-05-02         TP -2.5639498571  <NA> #> 1810   2068    3M  CC03 2016 2016-05-02       TURB  0.0953101798  <NA> #> 1811   2068    3M  CC03 2017 2017-08-07      CHLAC  2.3978952728  <NA> #> 1812   2068    3M  CC03 2017 2017-08-07      COLOR  4.2195077052  <NA> #> 1813   2068    3M  CC03 2017 2017-08-07      DOSAT  2.3513752572     + #> 1814   2068    3M  CC03 2017 2017-08-07       NO23 -5.5214609179     U #> 1815   2068    3M  CC03 2017 2017-08-07      SALIN  1.4350845253  <NA> #> 1816   2068    3M  CC03 2017 2017-08-07        TKN  0.5306282511  <NA> #> 1817   2068    3M  CC03 2017 2017-08-07         TN  0.5318040302     + #> 1818   2068    3M  CC03 2017 2017-08-07         TP -2.7030626596  <NA> #> 1819   2068    3M  CC03 2017 2017-08-07       TURB  0.9162907319  <NA> #> 1820   2068    3M  CC03 2017 2017-09-05      CHLAC  2.7080502011  <NA> #> 1821   2068    3M  CC03 2017 2017-09-05      COLOR  5.0106352941  <NA> #> 1822   2068    3M  CC03 2017 2017-09-05         DO  0.6931471806  <NA> #> 1823   2068    3M  CC03 2017 2017-09-05      DOSAT  3.2884018875     + #> 1824   2068    3M  CC03 2017 2017-09-05       NO23 -4.4228486292  <NA> #> 1825   2068    3M  CC03 2017 2017-09-05      SALIN  2.2721258855  <NA> #> 1826   2068    3M  CC03 2017 2017-09-05        TKN  0.1823215568  <NA> #> 1827   2068    3M  CC03 2017 2017-09-05         TN  0.1922718876     + #> 1828   2068    3M  CC03 2017 2017-09-05         TP -1.7719568419  <NA> #> 1829   2068    3M  CC03 2017 2017-09-05       TURB  1.3350010667  <NA> #> 1830   2068    3M  CC03 2017 2017-10-02      CHLAC  2.5649493575  <NA> #> 1831   2068    3M  CC03 2017 2017-10-02      COLOR  4.0943445622     A #> 1832   2068    3M  CC03 2017 2017-10-02       NO23 -5.5214609179     U #> 1833   2068    3M  CC03 2017 2017-10-02        TKN -0.0725706928  <NA> #> 1834   2068    3M  CC03 2017 2017-10-02         TN -0.0704224643     + #> 1835   2068    3M  CC03 2017 2017-10-02         TP -2.3025850930  <NA> #> 1836   2068    3M  CC03 2017 2017-10-02       TURB  1.8870696490  <NA> #> 1837   2068    3M  CC03 2017 2017-11-06      CHLAC  1.1631508098  <NA> #> 1838   2068    3M  CC03 2017 2017-11-06      COLOR  3.5835189385  <NA> #> 1839   2068    3M  CC03 2017 2017-11-06         DO  1.3083328197  <NA> #> 1840   2068    3M  CC03 2017 2017-11-06      DOSAT  3.9080149840     + #> 1841   2068    3M  CC03 2017 2017-11-06       NO23 -5.2983173665     I #> 1842   2068    3M  CC03 2017 2017-11-06      SALIN  3.1354942159  <NA> #> 1843   2068    3M  CC03 2017 2017-11-06        TKN -0.2744368457  <NA> #> 1844   2068    3M  CC03 2017 2017-11-06         TN -0.2691874898     + #> 1845   2068    3M  CC03 2017 2017-11-06         TP -2.4418471603  <NA> #> 1846   2068    3M  CC03 2017 2017-11-06       TURB  1.2237754316  <NA> #> 1847   2068    3M  CC03 2018 2018-01-02      CHLAC  1.0647107370  <NA> #> 1848   2068    3M  CC03 2018 2018-01-02      COLOR  3.0445224377  <NA> #> 1849   2068    3M  CC03 2018 2018-01-02       NO23 -4.9618451299     I #> 1850   2068    3M  CC03 2018 2018-01-02      SALIN  3.4563166809  <NA> #> 1851   2068    3M  CC03 2018 2018-01-02        TKN -0.4780358009  <NA> #> 1852   2068    3M  CC03 2018 2018-01-02         TN -0.4716049106     + #> 1853   2068    3M  CC03 2018 2018-01-02         TP -2.4079456087  <NA> #> 1854   2068    3M  CC03 2018 2018-01-02       TURB  1.1314021115  <NA> #> 1855   2068    3M  CC03 2018 2018-02-05      CHLAC  0.9932517730     A #> 1856   2068    3M  CC03 2018 2018-02-05      COLOR  3.2188758249  <NA> #> 1857   2068    3M  CC03 2018 2018-02-05         DO  1.3609765531  <NA> #> 1858   2068    3M  CC03 2018 2018-02-05      DOSAT  3.8979240810     + #> 1859   2068    3M  CC03 2018 2018-02-05       NO23 -4.3428059215  <NA> #> 1860   2068    3M  CC03 2018 2018-02-05      SALIN  3.0587070727  <NA> #> 1861   2068    3M  CC03 2018 2018-02-05        TKN -0.4780358009  <NA> #> 1862   2068    3M  CC03 2018 2018-02-05         TN -0.4572848568     + #> 1863   2068    3M  CC03 2018 2018-02-05         TP -2.6310891600  <NA> #> 1864   2068    3M  CC03 2018 2018-02-05       TURB  0.8754687374  <NA> #> 1865   2068    3M  CC03 2018 2018-03-05      CHLAC  0.6418538862  <NA> #> 1866   2068    3M  CC03 2018 2018-03-05      COLOR  2.5649493575  <NA> #> 1867   2068    3M  CC03 2018 2018-03-05         DO  1.5686159179  <NA> #> 1868   2068    3M  CC03 2018 2018-03-05      DOSAT  4.0517849478     + #> 1869   2068    3M  CC03 2018 2018-03-05       NO23 -5.2983173665     I #> 1870   2068    3M  CC03 2018 2018-03-05      SALIN  3.4781584228  <NA> #> 1871   2068    3M  CC03 2018 2018-03-05        TKN -0.5798184953  <NA> #> 1872   2068    3M  CC03 2018 2018-03-05         TN -0.5727010275     + #> 1873   2068    3M  CC03 2018 2018-03-05         TP -2.7488721956  <NA> #> 1874   2068    3M  CC03 2018 2018-03-05       TURB  2.2407096893  <NA> #> 1875   2068    3M  CC03 2018 2018-04-02      CHLAC -0.5978370008     U #> 1876   2068    3M  CC03 2018 2018-04-02      COLOR  0.9162907319     U #> 1877   2068    3M  CC03 2018 2018-04-02         DO  1.2237754316  <NA> #> 1878   2068    3M  CC03 2018 2018-04-02      DOSAT  3.8877303129     + #> 1879   2068    3M  CC03 2018 2018-04-02       NO23 -3.7297014486  <NA> #> 1880   2068    3M  CC03 2018 2018-04-02      SALIN  3.5553480615  <NA> #> 1881   2068    3M  CC03 2018 2018-04-02        TKN  1.0296194172  <NA> #> 1882   2068    3M  CC03 2018 2018-04-02         TN  1.0381543196     + #> 1883   2068    3M  CC03 2018 2018-04-02         TP -1.7719568419  <NA> #> 1884   2068    3M  CC03 2018 2018-04-02       TURB  1.3862943611  <NA> #> 1885   2068    3M  CC03 2018 2018-05-07      CHLAC  0.4054651081     I #> 1886   2068    3M  CC03 2018 2018-05-07      COLOR  2.6390573296  <NA> #> 1887   2068    3M  CC03 2018 2018-05-07         DO -0.1984509387  <NA> #> 1888   2068    3M  CC03 2018 2018-05-07      DOSAT  2.5416019935  <NA> #> 1889   2068    3M  CC03 2018 2018-05-07       NO23 -5.5214609179     U #> 1890   2068    3M  CC03 2018 2018-05-07      SALIN  3.6109179126  <NA> #> 1891   2068    3M  CC03 2018 2018-05-07        TKN -0.6161861394  <NA> #> 1892   2068    3M  CC03 2018 2018-05-07         TN -0.6124892775     + #> 1893   2068    3M  CC03 2018 2018-05-07         TP -2.8824035882  <NA> #> 1894   2068    3M  CC03 2018 2018-05-07       TURB  0.8754687374  <NA> #> 1895   2068    3M  CC03 2018 2018-08-06      CHLAC  1.5475625087  <NA> #> 1896   2068    3M  CC03 2018 2018-08-06      COLOR  3.8918202981  <NA> #> 1897   2068    3M  CC03 2018 2018-08-06         DO -0.9162907319  <NA> #> 1898   2068    3M  CC03 2018 2018-08-06      DOSAT  1.8245492921  <NA> #> 1899   2068    3M  CC03 2018 2018-08-06       NO23 -5.5214609179     I #> 1900   2068    3M  CC03 2018 2018-08-06      SALIN  3.3332753652  <NA> #> 1901   2068    3M  CC03 2018 2018-08-06        TKN  0.2623642645  <NA> #> 1902   2068    3M  CC03 2018 2018-08-06         TN  0.2654364635     + #> 1903   2068    3M  CC03 2018 2018-08-06         TP -2.4191189092  <NA> #> 1904   2068    3M  CC03 2018 2018-08-06       TURB  1.6486586256  <NA> #> 1905   2068    3M  CC03 2019 2019-03-04      CHLAC  0.2623642645     I #> 1906   2068    3M  CC03 2019 2019-03-04      COLOR  3.6635616461  <NA> #> 1907   2068    3M  CC03 2019 2019-03-04         DO  1.0919233005  <NA> #> 1908   2068    3M  CC03 2019 2019-03-04      DOSAT  3.6506582413  <NA> #> 1909   2068    3M  CC03 2019 2019-03-04       NO23 -5.5214609179     U #> 1910   2068    3M  CC03 2019 2019-03-04      SALIN  2.3105532626  <NA> #> 1911   2068    3M  CC03 2019 2019-03-04        TKN -0.3147107448  <NA> #> 1912   2068    3M  CC03 2019 2019-03-04         TN -0.3119747650     + #> 1913   2068    3M  CC03 2019 2019-03-04         TP -2.3025850930  <NA> #> 1914   2068    3M  CC03 2019 2019-03-04       TURB  0.8754687374  <NA> #> 1915   2068    3M  CC03 2019 2019-05-06      CHLAC  1.3862943611  <NA> #> 1916   2068    3M  CC03 2019 2019-05-06      COLOR  3.4965075615  <NA> #> 1917   2068    3M  CC03 2019 2019-05-06         DO -1.8325814637  <NA> #> 1918   2068    3M  CC03 2019 2019-05-06      DOSAT  0.9932517730  <NA> #> 1919   2068    3M  CC03 2019 2019-05-06       NO23 -5.5214609179     U #> 1920   2068    3M  CC03 2019 2019-05-06      SALIN  3.3809946743  <NA> #> 1921   2068    3M  CC03 2019 2019-05-06        TKN -0.3566749439  <NA> #> 1922   2068    3M  CC03 2019 2019-05-06         TN -0.3538218750     + #> 1923   2068    3M  CC03 2019 2019-05-06         TP -3.0159349809  <NA> #> 1924   2068    3M  CC03 2019 2019-05-06       TURB  0.6418538862  <NA> #> 1925   2068    3M  CC03 2019 2019-06-03      CHLAC  1.0986122887  <NA> #> 1926   2068    3M  CC03 2019 2019-06-03      COLOR  2.9957322736  <NA> #> 1927   2068    3M  CC03 2019 2019-06-03         DO -0.8675005677  <NA> #> 1928   2068    3M  CC03 2019 2019-06-03      DOSAT  1.8870696490  <NA> #> 1929   2068    3M  CC03 2019 2019-06-03       NO23 -5.5214609179     U #> 1930   2068    3M  CC03 2019 2019-06-03      SALIN  3.6068556186  <NA> #> 1931   2068    3M  CC03 2019 2019-06-03        TKN -0.3424903089  <NA> #> 1932   2068    3M  CC03 2019 2019-06-03         TN -0.3396773676     + #> 1933   2068    3M  CC03 2019 2019-06-03         TP -3.0791138825  <NA> #> 1934   2068    3M  CC03 2019 2019-06-03       TURB  0.9555114450  <NA> #> 1935   2068    3M  CC03 2019 2019-07-01      CHLAC  1.9740810260  <NA> #> 1936   2068    3M  CC03 2019 2019-07-01      COLOR  3.2958368660     A #> 1937   2068    3M  CC03 2019 2019-07-01         DO -0.5978370008  <NA> #> 1938   2068    3M  CC03 2019 2019-07-01      DOSAT  2.1517622033  <NA> #> 1939   2068    3M  CC03 2019 2019-07-01       NO23 -5.5214609179     U #> 1940   2068    3M  CC03 2019 2019-07-01      SALIN  3.5160130561  <NA> #> 1941   2068    3M  CC03 2019 2019-07-01        TKN -0.2613647641  <NA> #> 1942   2068    3M  CC03 2019 2019-07-01         TN -0.2587707290     + #> 1943   2068    3M  CC03 2019 2019-07-01         TP -3.0159349809  <NA> #> 1944   2068    3M  CC03 2019 2019-07-01       TURB  1.6486586256     A #> 1945   2068    3M  CC03 2019 2019-10-07         TN -0.6462635947     + #> 1946   2068    3M  CC03 2019 2019-10-07      CHLAC  1.0647107370     I #> 1947   2068    3M  CC03 2019 2019-10-07      COLOR  1.9169226122  <NA> #> 1948   2068    3M  CC03 2019 2019-10-07         DO  0.6931471806  <NA> #> 1949   2068    3M  CC03 2019 2019-10-07      DOSAT  3.4436180975  <NA> #> 1950   2068    3M  CC03 2019 2019-10-07       NO23 -5.1159958098     I #> 1951   2068    3M  CC03 2019 2019-10-07      SALIN  3.5392186796  <NA> #> 1952   2068    3M  CC03 2019 2019-10-07        TKN -0.6539264674  <NA> #> 1953   2068    3M  CC03 2019 2019-10-07         TP -2.5902671654  <NA> #> 1954   2068    3M  CC03 2019 2019-10-07       TURB  0.7884573604  <NA> #> 1955   2068    3M  CC03 2019 2019-11-04      CHLAC  1.7227665977  <NA> #> 1956   2068    3M  CC03 2019 2019-11-04      COLOR  2.8903717579  <NA> #> 1957   2068    3M  CC03 2019 2019-11-04         DO  0.3646431136  <NA> #> 1958   2068    3M  CC03 2019 2019-11-04      DOSAT  3.0349529867  <NA> #> 1959   2068    3M  CC03 2019 2019-11-04       NO23 -4.3428059215  <NA> #> 1960   2068    3M  CC03 2019 2019-11-04      SALIN  3.6030491975  <NA> #> 1961   2068    3M  CC03 2019 2019-11-04        TKN -0.3566749439  <NA> #> 1962   2068    3M  CC03 2019 2019-11-04         TN -0.3382738586     + #> 1963   2068    3M  CC03 2019 2019-11-04         TP -2.7488721956  <NA> #> 1964   2068    3M  CC03 2019 2019-11-04       TURB  1.1631508098  <NA> #> 1965   2068    3M  CC03 2019 2019-12-02      CHLAC  0.8754687374     I #> 1966   2068    3M  CC03 2019 2019-12-02      COLOR  2.1860512767  <NA> #> 1967   2068    3M  CC03 2019 2019-12-02         DO  1.0367368850  <NA> #> 1968   2068    3M  CC03 2019 2019-12-02      DOSAT  3.6988297850  <NA> #> 1969   2068    3M  CC03 2019 2019-12-02       NO23 -4.1997050779  <NA> #> 1970   2068    3M  CC03 2019 2019-12-02      SALIN  3.4977189487  <NA> #> 1971   2068    3M  CC03 2019 2019-12-02        TKN -0.4620354596  <NA> #> 1972   2068    3M  CC03 2019 2019-12-02         TN -0.4385049622     + #> 1973   2068    3M  CC03 2019 2019-12-02         TP -2.9187712324  <NA> #> 1974   2068    3M  CC03 2019 2019-12-02       TURB  0.6418538862  <NA> #> 1975   2068    3M  CC03 2020 2020-01-06      CHLAC  1.2237754316  <NA> #> 1976   2068    3M  CC03 2020 2020-01-06      COLOR  3.5263605246     A #> 1977   2068    3M  CC03 2020 2020-01-06         DO  1.1184149160  <NA> #> 1978   2068    3M  CC03 2020 2020-01-06      DOSAT  3.5862928653  <NA> #> 1979   2068    3M  CC03 2020 2020-01-06       NO23 -4.1997050779  <NA> #> 1980   2068    3M  CC03 2020 2020-01-06      SALIN  2.7491921444  <NA> #> 1981   2068    3M  CC03 2020 2020-01-06        TKN  0.0953101798  <NA> #> 1982   2068    3M  CC03 2020 2020-01-06         TN  0.1088544049     + #> 1983   2068    3M  CC03 2020 2020-01-06         TP -2.5510464523  <NA> #> 1984   2068    3M  CC03 2020 2020-01-06       TURB  1.4350845253  <NA> #> 1985   2068    3M  CC03 2020 2020-02-03      CHLAC  0.5877866649     I #> 1986   2068    3M  CC03 2020 2020-02-03      COLOR  3.3672958300  <NA> #> 1987   2068    3M  CC03 2020 2020-02-03         DO  1.4011829736  <NA> #> 1988   2068    3M  CC03 2020 2020-02-03      DOSAT  3.7909846771  <NA> #> 1989   2068    3M  CC03 2020 2020-02-03       NO23 -4.9618451299     I #> 1990   2068    3M  CC03 2020 2020-02-03      SALIN  3.0819099698  <NA> #> 1991   2068    3M  CC03 2020 2020-02-03        TKN -0.2107210313  <NA> #> 1992   2068    3M  CC03 2020 2020-02-03         TN -0.2057949130     + #> 1993   2068    3M  CC03 2020 2020-02-03         TP -2.7968814148  <NA> #> 1994   2068    3M  CC03 2020 2020-02-03       TURB  0.5877866649  <NA> #> 1995   2068    3M  CC03 2020 2020-03-02      CHLAC  0.6931471806     I #> 1996   2068    3M  CC03 2020 2020-03-02      COLOR  2.6390573296  <NA> #> 1997   2068    3M  CC03 2020 2020-03-02         DO  1.4951487660  <NA> #> 1998   2068    3M  CC03 2020 2020-03-02      DOSAT  4.0360089852  <NA> #> 1999   2068    3M  CC03 2020 2020-03-02       NO23 -5.2983173665     I #> 2000   2068    3M  CC03 2020 2020-03-02      SALIN  3.4600950229  <NA> #> 2001   2068    3M  CC03 2020 2020-03-02        TKN -0.5108256238  <NA> #> 2002   2068    3M  CC03 2020 2020-03-02         TN -0.5041810810     + #> 2003   2068    3M  CC03 2020 2020-03-02         TP -2.6450754019  <NA> #> 2004   2068    3M  CC03 2020 2020-03-02       TURB  1.5040773968  <NA> #> 2005   2068    3M  CC03 2020 2020-09-08      CHLAC  2.7725887222  <NA> #> 2006   2068    3M  CC03 2020 2020-09-08      COLOR  4.8675344505  <NA> #> 2007   2068    3M  CC03 2020 2020-09-08         DO  0.4510756194  <NA> #> 2008   2068    3M  CC03 2020 2020-09-08      DOSAT  3.0155349009  <NA> #> 2009   2068    3M  CC03 2020 2020-09-08       NO23 -5.5214609179     U #> 2010   2068    3M  CC03 2020 2020-09-08      SALIN  1.5151272330  <NA> #> 2011   2068    3M  CC03 2020 2020-09-08        TKN  0.0953101798  <NA> #> 2012   2068    3M  CC03 2020 2020-09-08         TN  0.0971267107     + #> 2013   2068    3M  CC03 2020 2020-09-08         TP -2.2072749132  <NA> #> 2014   2068    3M  CC03 2020 2020-09-08       TURB  1.3862943611  <NA> #> 2015   2068    3M  CC03 2020 2020-10-05      CHLAC  2.0918640617  <NA> #> 2016   2068    3M  CC03 2020 2020-10-05      COLOR  4.2046926194  <NA> #> 2017   2068    3M  CC03 2020 2020-10-05         DO  0.4121096508  <NA> #> 2018   2068    3M  CC03 2020 2020-10-05      DOSAT  3.0587070727  <NA> #> 2019   2068    3M  CC03 2020 2020-10-05       NO23 -4.7105307016     I #> 2020   2068    3M  CC03 2020 2020-10-05      SALIN  3.2027464429  <NA> #> 2021   2068    3M  CC03 2020 2020-10-05        TKN -0.3147107448  <NA> #> 2022   2068    3M  CC03 2020 2020-10-05         TN -0.3092462504     + #> 2023   2068    3M  CC03 2020 2020-10-05         TP -2.5133061243  <NA> #> 2024   2068    3M  CC03 2020 2020-10-05       TURB  1.3350010667  <NA> #> 2025   2068    3M  CC03 2020 2020-11-02      CHLAC  1.4816045409  <NA> #> 2026   2068    3M  CC03 2020 2020-11-02      COLOR  3.6888794541  <NA> #> 2027   2068    3M  CC03 2020 2020-11-02         DO  0.6523251860  <NA> #> 2028   2068    3M  CC03 2020 2020-11-02      DOSAT  3.3428618046  <NA> #> 2029   2068    3M  CC03 2020 2020-11-02       NO23 -4.7105307016     I #> 2030   2068    3M  CC03 2020 2020-11-02      SALIN  3.3721118008  <NA> #> 2031   2068    3M  CC03 2020 2020-11-02        TKN -0.1984509387  <NA> #> 2032   2068    3M  CC03 2020 2020-11-02         TN -0.1935847491     + #> 2033   2068    3M  CC03 2020 2020-11-02         TP -2.6882475738  <NA> #> 2034   2068    3M  CC03 2020 2020-11-02       TURB  1.1939224685  <NA> #> 2035   2068    3M  CC03 2020 2020-12-07      CHLAC  0.4054651081     I #> 2036   2068    3M  CC03 2020 2020-12-07      COLOR  3.2958368660     A #> 2037   2068    3M  CC03 2020 2020-12-07         DO  1.3480731483  <NA> #> 2038   2068    3M  CC03 2020 2020-12-07      DOSAT  3.9278963546  <NA> #> 2039   2068    3M  CC03 2020 2020-12-07       NO23 -3.6119184130  <NA> #> 2040   2068    3M  CC03 2020 2020-12-07      SALIN  3.3641875560  <NA> #> 2041   2068    3M  CC03 2020 2020-12-07        TKN -0.5276327421  <NA> #> 2042   2068    3M  CC03 2020 2020-12-07         TN -0.4828862551     + #> 2043   2068    3M  CC03 2020 2020-12-07         TP -2.6036901858  <NA> #> 2044   2068    3M  CC03 2020 2020-12-07       TURB  0.7419373447  <NA> #> 2045   2068    3M  CC03 2021 2021-01-04      CHLAC  1.3609765531  <NA> #> 2046   2068    3M  CC03 2021 2021-01-04      COLOR  3.1780538303     A #> 2047   2068    3M  CC03 2021 2021-01-04         DO  0.7701082217  <NA> #> 2048   2068    3M  CC03 2021 2021-01-04      DOSAT  3.3393219779  <NA> #> 2049   2068    3M  CC03 2021 2021-01-04       NO23 -4.3428059215  <NA> #> 2050   2068    3M  CC03 2021 2021-01-04      SALIN  3.2638491905  <NA> #> 2051   2068    3M  CC03 2021 2021-01-04        TKN -0.4780358009  <NA> #> 2052   2068    3M  CC03 2021 2021-01-04         TN -0.4572848568     + #> 2053   2068    3M  CC03 2021 2021-01-04         TP -2.3025850930  <NA> #> 2054   2068    3M  CC03 2021 2021-01-04       TURB  0.8329091229  <NA> #> 2055   2068    3M  CC03 2021 2021-02-01      CHLAC  0.3364722366     I #> 2056   2068    3M  CC03 2021 2021-02-01      COLOR  1.9878743482  <NA> #> 2057   2068    3M  CC03 2021 2021-02-01         DO  1.3454723666  <NA> #> 2058   2068    3M  CC03 2021 2021-02-01      DOSAT  3.9156165409  <NA> #> 2059   2068    3M  CC03 2021 2021-02-01       NO23 -4.4228486292  <NA> #> 2060   2068    3M  CC03 2021 2021-02-01      SALIN  3.4937765630  <NA> #> 2061   2068    3M  CC03 2021 2021-02-01        TKN -0.7133498879  <NA> #> 2062   2068    3M  CC03 2021 2021-02-01         TN -0.6891551593     + #> 2063   2068    3M  CC03 2021 2021-02-01         TP -2.7646205526  <NA> #> 2064   2068    3M  CC03 2021 2021-02-01       TURB  1.0647107370  <NA> #> 2065   2068    3M  CC03 2021 2021-04-05      CHLAC  0.5877866649     I #> 2066   2068    3M  CC03 2021 2021-04-05      COLOR  2.5649493575  <NA> #> 2067   2068    3M  CC03 2021 2021-04-05         DO  0.9932517730  <NA> #> 2068   2068    3M  CC03 2021 2021-04-05      DOSAT  3.6323091026  <NA> #> 2069   2068    3M  CC03 2021 2021-04-05       NO23 -5.5214609179     U #> 2070   2068    3M  CC03 2021 2021-04-05      SALIN  3.5984075509  <NA> #> 2071   2068    3M  CC03 2021 2021-04-05        TKN -0.6348782724  <NA> #> 2072   2068    3M  CC03 2021 2021-04-05         TN -0.6311117896     + #> 2073   2068    3M  CC03 2021 2021-04-05         TP -2.9374633654  <NA> #> 2074   2068    3M  CC03 2021 2021-04-05       TURB  0.9162907319  <NA> #> 2075   2068    3M  CC03 2021 2021-05-03      CHLAC  0.4054651081     I #> 2076   2068    3M  CC03 2021 2021-05-03      COLOR  3.0910424534     A #> 2077   2068    3M  CC03 2021 2021-05-03         DO -0.4307829161  <NA> #> 2078   2068    3M  CC03 2021 2021-05-03      DOSAT  2.3125354238  <NA> #> 2079   2068    3M  CC03 2021 2021-05-03       NO23 -5.5214609179     U #> 2080   2068    3M  CC03 2021 2021-05-03      SALIN  3.5931942040  <NA> #> 2081   2068    3M  CC03 2021 2021-05-03        TKN -0.6348782724  <NA> #> 2082   2068    3M  CC03 2021 2021-05-03         TN -0.6311117896     + #> 2083   2068    3M  CC03 2021 2021-05-03         TP -3.1010927892  <NA> #> 2084   2068    3M  CC03 2021 2021-05-03       TURB  1.6094379124     A #> 2085   2068    3M  CC03 2021 2021-06-07      CHLAC  0.8754687374     I #> 2086   2068    3M  CC03 2021 2021-06-07      COLOR  2.9444389792  <NA> #> 2087   2068    3M  CC03 2021 2021-06-07         DO -0.4462871026  <NA> #> 2088   2068    3M  CC03 2021 2021-06-07      DOSAT  2.3418058061  <NA> #> 2089   2068    3M  CC03 2021 2021-06-07       NO23 -5.5214609179     U #> 2090   2068    3M  CC03 2021 2021-06-07      SALIN  3.6444049640  <NA> #> 2091   2068    3M  CC03 2021 2021-06-07        TKN -0.4462871026  <NA> #> 2092   2068    3M  CC03 2021 2021-06-07         TN -0.4431669753     + #> 2093   2068    3M  CC03 2021 2021-06-07         TP -3.1941832123  <NA> #> 2094   2068    3M  CC03 2021 2021-06-07       TURB  0.8754687374  <NA> #> 2095   2068    3M  CC03 2021 2021-08-02      CHLAC  3.2188758249  <NA> #> 2096   2068    3M  CC03 2021 2021-08-02      COLOR  4.4308167988  <NA> #> 2097   2068    3M  CC03 2021 2021-08-02         DO -0.5108256238  <NA> #> 2098   2068    3M  CC03 2021 2021-08-02      DOSAT -0.9162907319  <NA> #> 2099   2068    3M  CC03 2021 2021-08-02       NO23 -5.5214609179     U #> 2100   2068    3M  CC03 2021 2021-08-02      SALIN  2.5733752978  <NA> #> 2101   2068    3M  CC03 2021 2021-08-02        TKN  0.2623642645  <NA> #> 2102   2068    3M  CC03 2021 2021-08-02         TN  0.2639015438     + #> 2103   2068    3M  CC03 2021 2021-08-02         TP -1.9661128564  <NA> #> 2104   2068    3M  CC03 2021 2021-08-02       TURB  1.3862943611  <NA> #> 2105   2068    3M  CC03 2021 2021-09-07      CHLAC  3.6375861597  <NA> #> 2106   2068    3M  CC03 2021 2021-09-07      COLOR  4.4308167988  <NA> #> 2107   2068    3M  CC03 2021 2021-09-07         DO  1.9473377010  <NA> #> 2108   2068    3M  CC03 2021 2021-09-07      DOSAT  4.5119578043  <NA> #> 2109   2068    3M  CC03 2021 2021-09-07       NO23 -5.5214609179     U #> 2110   2068    3M  CC03 2021 2021-09-07      SALIN -3.2188758249  <NA> #> 2111   2068    3M  CC03 2021 2021-09-07        TKN  0.1823215568  <NA> #> 2112   2068    3M  CC03 2021 2021-09-07         TN  0.1839868361     + #> 2113   2068    3M  CC03 2021 2021-09-07         TP -2.2072749132  <NA> #> 2114   2068    3M  CC03 2021 2021-09-07       TURB  1.7047480922  <NA> #> 2115   2068    3M  CC03 2021 2021-10-04      CHLAC  1.8082887712  <NA> #> 2116   2068    3M  CC03 2021 2021-10-04      COLOR  3.8712010109     A #> 2117   2068    3M  CC03 2021 2021-10-04         DO  0.1043600153  <NA> #> 2118   2068    3M  CC03 2021 2021-10-04      DOSAT  2.7472709143  <NA> #> 2119   2068    3M  CC03 2021 2021-10-04       NO23 -4.9618451299     I #> 2120   2068    3M  CC03 2021 2021-10-04      SALIN  3.1527360224  <NA> #> 2121   2068    3M  CC03 2021 2021-10-04        TKN -0.2484613593  <NA> #> 2122   2068    3M  CC03 2021 2021-10-04         TN -0.2433462586     + #> 2123   2068    3M  CC03 2021 2021-10-04         TP -2.4079456087  <NA> #> 2124   2068    3M  CC03 2021 2021-10-04       TURB  0.7419373447  <NA> #> 2125   2068    3M  CC03 2021 2021-11-01      CHLAC  1.3350010667     I #> 2126   2068    3M  CC03 2021 2021-11-01      COLOR  3.7612001157  <NA> #> 2127   2068    3M  CC03 2021 2021-11-01         DO  0.4824261492  <NA> #> 2128   2068    3M  CC03 2021 2021-11-01      DOSAT  3.0726933147  <NA> #> 2129   2068    3M  CC03 2021 2021-11-01       NO23 -4.6051701860     I #> 2130   2068    3M  CC03 2021 2021-11-01      SALIN  3.1797191097  <NA> #> 2131   2068    3M  CC03 2021 2021-11-01        TKN -0.3856624808  <NA> #> 2132   2068    3M  CC03 2021 2021-11-01         TN -0.3797973614     + #> 2133   2068    3M  CC03 2021 2021-11-01         TP -2.4418471603  <NA> #> 2134   2068    3M  CC03 2021 2021-11-01       TURB  0.4054651081     A #> 2135   2068    3M  CC03 2021 2021-12-06      CHLAC  0.7419373447     I #> 2136   2068    3M  CC03 2021 2021-12-06      COLOR  2.7725887222  <NA> #> 2137   2068    3M  CC03 2021 2021-12-06         DO  1.1249295970  <NA> #> 2138   2068    3M  CC03 2021 2021-12-06      DOSAT  3.7495040759  <NA> #> 2139   2068    3M  CC03 2021 2021-12-06       NO23 -4.4228486292  <NA> #> 2140   2068    3M  CC03 2021 2021-12-06      SALIN  3.3931652100  <NA> #> 2141   2068    3M  CC03 2021 2021-12-06        TKN -0.4004775666  <NA> #> 2142   2068    3M  CC03 2021 2021-12-06         TN -0.3827256211     + #> 2143   2068    3M  CC03 2021 2021-12-06         TP -2.4889146712  <NA> #> 2144   2068    3M  CC03 2021 2021-12-06       TURB  1.1631508098  <NA> #> 2145   2068    3M  CC03 2022 2022-01-03      CHLAC  1.2527629685  <NA> #> 2146   2068    3M  CC03 2022 2022-01-03      COLOR  2.6390573296  <NA> #> 2147   2068    3M  CC03 2022 2022-01-03         DO  0.8796267475  <NA> #> 2148   2068    3M  CC03 2022 2022-01-03      DOSAT  3.6480574596  <NA> #> 2149   2068    3M  CC03 2022 2022-01-03       NO23 -4.7105307016     I #> 2150   2068    3M  CC03 2022 2022-01-03      SALIN  3.5007410120  <NA> #> 2151   2068    3M  CC03 2022 2022-01-03        TKN -0.4155154440  <NA> #> 2152   2068    3M  CC03 2022 2022-01-03         TN -0.4094731295     + #> 2153   2068    3M  CC03 2022 2022-01-03         TP -2.3434070875  <NA> #> 2154   2068    3M  CC03 2022 2022-01-03       TURB  0.9555114450  <NA> #> 2155   2068    3M  CC03 2022 2022-02-07      CHLAC -0.1165338163     U #> 2156   2068    3M  CC03 2022 2022-02-07      COLOR  2.3978952728     A #> 2157   2068    3M  CC03 2022 2022-02-07         DO  1.4929040962  <NA> #> 2158   2068    3M  CC03 2022 2022-02-07      DOSAT  4.0517849478  <NA> #> 2159   2068    3M  CC03 2022 2022-02-07       NO23 -5.1159958098     I #> 2160   2068    3M  CC03 2022 2022-02-07      SALIN  3.4651107074  <NA> #> 2161   2068    3M  CC03 2022 2022-02-07        TKN -0.8915981193  <NA> #> 2162   2068    3M  CC03 2022 2022-02-07         TN -0.8818893052     + #> 2163   2068    3M  CC03 2022 2022-02-07         TP -2.6736487744  <NA> #> 2164   2068    3M  CC03 2022 2022-02-07       TURB  0.4054651081  <NA> #> 2165   2068    3M  CC03 2022 2022-03-07      CHLAC  0.7419373447     I #> 2166   2068    3M  CC03 2022 2022-03-07      COLOR  2.3025850930     A #> 2167   2068    3M  CC03 2022 2022-03-07         DO  0.5306282511  <NA> #> 2168   2068    3M  CC03 2022 2022-03-07      DOSAT  3.1863526332  <NA> #> 2169   2068    3M  CC03 2022 2022-03-07       NO23 -5.1159958098     I #> 2170   2068    3M  CC03 2022 2022-03-07      SALIN  3.5331024525  <NA> #> 2171   2068    3M  CC03 2022 2022-03-07        TKN -0.4307829161  <NA> #> 2172   2068    3M  CC03 2022 2022-03-07         TN -0.4246479275     + #> 2173   2068    3M  CC03 2022 2022-03-07         TP -2.8647040111  <NA> #> 2174   2068    3M  CC03 2022 2022-03-07       TURB  0.9555114450  <NA> #> 2175   2068    3M  CC03 2022 2022-04-04      CHLAC  0.0000000000     I #> 2176   2068    3M  CC03 2022 2022-04-04      COLOR  2.5649493575  <NA> #> 2177   2068    3M  CC03 2022 2022-04-04         DO -0.2107210313  <NA> #> 2178   2068    3M  CC03 2022 2022-04-04      DOSAT  2.5416019935  <NA> #> 2179   2068    3M  CC03 2022 2022-04-04       NO23 -5.1159958098     I #> 2180   2068    3M  CC03 2022 2022-04-04        TKN -0.6161861394  <NA> #> 2181   2068    3M  CC03 2022 2022-04-04         TN -0.6088060321     + #> 2182   2068    3M  CC03 2022 2022-04-04         TP -2.9957322736  <NA> #> 2183   2068    3M  CC03 2022 2022-04-04       TURB  1.0986122887  <NA> #> 2184   2068    3M  CC03 2022 2022-05-02      CHLAC  0.3364722366     U #> 2185   2068    3M  CC03 2022 2022-05-02         DO -0.5108256238  <NA> #> 2186   2068    3M  CC03 2022 2022-05-02      DOSAT  2.2082744135  <NA> #> 2187   2068    3M  CC03 2022 2022-05-02       NO23 -5.5214609179     U #> 2188   2068    3M  CC03 2022 2022-05-02      SALIN  3.5366020187  <NA> #> 2189   2068    3M  CC03 2022 2022-05-02         TN -0.5762534291     + #> 2190   2068    3M  CC03 2022 2022-06-06      CHLAC  1.7047480922  <NA> #> 2191   2068    3M  CC03 2022 2022-06-06      COLOR  4.0430512678  <NA> #> 2192   2068    3M  CC03 2022 2022-06-06         DO -0.4462871026  <NA> #> 2193   2068    3M  CC03 2022 2022-06-06      DOSAT  2.1972245773  <NA> #> 2194   2068    3M  CC03 2022 2022-06-06       NO23 -4.6051701860     I #> 2195   2068    3M  CC03 2022 2022-06-06      SALIN  2.9210087274  <NA> #> 2196   2068    3M  CC03 2022 2022-06-06        TKN  0.1823215568  <NA> #> 2197   2068    3M  CC03 2022 2022-06-06         TN  0.1856493469     + #> 2198   2068    3M  CC03 2022 2022-06-06         TP -2.9374633654  <NA> #> 2199   2068    3M  CC03 2022 2022-06-06       TURB  1.3609765531  <NA> #> 2200   2068    3M  CC03 2022 2022-07-05      CHLAC  2.0541237337  <NA> #> 2201   2068    3M  CC03 2022 2022-07-05      COLOR  3.8501476017     A #> 2202   2068    3M  CC03 2022 2022-07-05         DO -0.5447271754  <NA> #> 2203   2068    3M  CC03 2022 2022-07-05      DOSAT  2.1860512767  <NA> #> 2204   2068    3M  CC03 2022 2022-07-05       NO23 -3.9120230054  <NA> #> 2205   2068    3M  CC03 2022 2022-07-05      SALIN  3.2327787300  <NA> #> 2206   2068    3M  CC03 2022 2022-07-05        TKN  0.0953101798  <NA> #> 2207   2068    3M  CC03 2022 2022-07-05         TN  0.1133286853     + #> 2208   2068    3M  CC03 2022 2022-07-05         TP -2.6036901858  <NA> #> 2209   2068    3M  CC03 2022 2022-07-05       TURB  2.0149030205  <NA> #> 2210   2068    3M  CC03 2022 2022-08-01      CHLAC  1.8082887712  <NA> #> 2211   2068    3M  CC03 2022 2022-08-01      COLOR  3.5553480615     A #> 2212   2068    3M  CC03 2022 2022-08-01         DO -0.8209805521  <NA> #> 2213   2068    3M  CC03 2022 2022-08-01      DOSAT  1.9315214116  <NA> #> 2214   2068    3M  CC03 2022 2022-08-01       NO23 -5.2983173665     I #> 2215   2068    3M  CC03 2022 2022-08-01      SALIN  3.3904734183  <NA> #> 2216   2068    3M  CC03 2022 2022-08-01        TKN -0.3011050928  <NA> #> 2217   2068    3M  CC03 2022 2022-08-01         TN -0.2957142441     + #> 2218   2068    3M  CC03 2022 2022-08-01         TP -2.9004220937  <NA> #> 2219   2068    3M  CC03 2022 2022-08-01       TURB  1.0296194172  <NA> #> 2220   2068    3M  CC03 2022 2022-11-07      CHLAC  2.7725887222  <NA> #> 2221   2068    3M  CC03 2022 2022-11-07      COLOR  3.9889840466     A #> 2222   2068    3M  CC03 2022 2022-11-07         DO -0.4462871026  <NA> #> 2223   2068    3M  CC03 2022 2022-11-07      DOSAT  2.2192034841  <NA> #> 2224   2068    3M  CC03 2022 2022-11-07       NO23 -5.5214609179     I #> 2225   2068    3M  CC03 2022 2022-11-07      SALIN  3.1945831323  <NA> #> 2226   2068    3M  CC03 2022 2022-11-07        TKN  0.0000000000  <NA> #> 2227   2068    3M  CC03 2022 2022-11-07         TN  0.0039920213     + #> 2228   2068    3M  CC03 2022 2022-11-07         TP -1.5606477483  <NA> #> 2229   2068    3M  CC03 2022 2022-11-07       TURB  2.7725887222  <NA> #> 2230   2068    3M  CC03 2022 2022-12-05      CHLAC  2.7725887222  <NA> #> 2231   2068    3M  CC03 2022 2022-12-05      COLOR  4.0430512678  <NA> #> 2232   2068    3M  CC03 2022 2022-12-05         DO  0.5766133643  <NA> #> 2233   2068    3M  CC03 2022 2022-12-05      DOSAT  3.1863526332  <NA> #> 2234   2068    3M  CC03 2022 2022-12-05       NO23 -5.5214609179     U #> 2235   2068    3M  CC03 2022 2022-12-05      SALIN  3.0223742045  <NA> #> 2236   2068    3M  CC03 2022 2022-12-05        TKN -0.1625189295  <NA> #> 2237   2068    3M  CC03 2022 2022-12-05         TN -0.1601687522     + #> 2238   2068    3M  CC03 2022 2022-12-05         TP -1.1394342832  <NA> #> 2239   2068    3M  CC03 2022 2022-12-05       TURB  1.5040773968  <NA> #> 2240   2068    3M  CC03 2023 2023-01-03      CHLAC  1.6486586256  <NA> #> 2241   2068    3M  CC03 2023 2023-01-03      COLOR  4.0604430105  <NA> #> 2242   2068    3M  CC03 2023 2023-01-03         DO  0.7080357931  <NA> #> 2243   2068    3M  CC03 2023 2023-01-03      DOSAT  3.2884018875  <NA> #> 2244   2068    3M  CC03 2023 2023-01-03       NO23 -4.2686979494  <NA> #> 2245   2068    3M  CC03 2023 2023-01-03        TKN -0.0512932944  <NA> #> 2246   2068    3M  CC03 2023 2023-01-03         TN -0.0366639844     + #> 2247   2068    3M  CC03 2023 2023-01-03         TP -0.7133498879  <NA> #> 2248   2068    3M  CC03 2023 2023-01-03       TURB  0.3364722366  <NA> #> 2249   2068    3M  CC03 2023 2023-02-06      CHLAC  1.6292405397  <NA> #> 2250   2068    3M  CC03 2023 2023-02-06      COLOR  2.7080502011     A #> 2251   2068    3M  CC03 2023 2023-02-06         DO  1.2781522025  <NA> #> 2252   2068    3M  CC03 2023 2023-02-06      DOSAT  3.8958936235  <NA> #> 2253   2068    3M  CC03 2023 2023-02-06       NO23 -4.6051701860     I #> 2254   2068    3M  CC03 2023 2023-02-06      SALIN  3.4404180948  <NA> #> 2255   2068    3M  CC03 2023 2023-02-06        TKN -0.3566749439  <NA> #> 2256   2068    3M  CC03 2023 2023-02-06         TN -0.3509769228     + #> 2257   2068    3M  CC03 2023 2023-02-06         TP -2.2072749132  <NA> #> 2258   2068    3M  CC03 2023 2023-02-06       TURB  1.1314021115  <NA> #> 2259   2068    3M  CC03 2023 2023-03-06         DO  0.1570037488  <NA> #> 2260   2068    3M  CC03 2023 2023-03-06      DOSAT  2.8791984573  <NA> #> 2261   2068    3M  CC03 2023 2023-03-06      SALIN  3.5962157693  <NA> #> 2262   2068    3M  CC03 2018 2018-03-13      CHLAC  0.9555114450  <NA> #> 2263   2068    3M  CC03 2018 2018-03-13       COND 10.8817948782  <NA> #> 2264   2068    3M  CC03 2018 2018-03-13         DO  2.0794415417  <NA> #> 2265   2068    3M  CC03 2018 2018-03-13      DOSAT  4.6812048723  <NA> #> 2266   2068    3M  CC03 2018 2018-03-13       NO23 -4.7105307016     I #> 2267   2068    3M  CC03 2018 2018-03-13      SALIN  3.6778185068     + #> 2268   2068    3M  CC03 2018 2018-03-13        TKN -0.4942963218  <NA> #> 2269   2068    3M  CC03 2018 2018-03-13         TN -0.4877603508     + #> 2270   2068    3M  CC03 2018 2018-03-13         TP -2.4191189092  <NA> #> 2271   2068    3M  CC03 2018 2018-03-13        TSS  1.3862943611     I #> 2272   2068    3M  CC03 2018 2018-03-13       TURB  1.0647107370  <NA> #> 2273   2068    3M  CC03 2018 2018-05-08      CHLAC  1.1631508098  <NA> #> 2274   2068    3M  CC03 2018 2018-05-08       COND 10.9254527508  <NA> #> 2275   2068    3M  CC03 2018 2018-05-08         DO  1.4973884086  <NA> #> 2276   2068    3M  CC03 2018 2018-05-08      DOSAT  4.2091602367  <NA> #> 2277   2068    3M  CC03 2018 2018-05-08       NO23 -5.5214609179     U #> 2278   2068    3M  CC03 2018 2018-05-08      SALIN  3.5973122606     + #> 2279   2068    3M  CC03 2018 2018-05-08        TKN -0.5108256238  <NA> #> 2280   2068    3M  CC03 2018 2018-05-08         TN -0.5074978337     + #> 2281   2068    3M  CC03 2018 2018-05-08         TP -3.2441936329  <NA> #> 2282   2068    3M  CC03 2018 2018-05-08        TSS  2.0794415417     I #> 2283   2068    3M  CC03 2018 2018-05-08       TURB  1.3083328197  <NA> #> 2284   2068    3M  CC03 2018 2018-06-26      CHLAC  2.4849066498  <NA> #> 2285   2068    3M  CC03 2018 2018-06-26       COND 10.7823463704  <NA> #> 2286   2068    3M  CC03 2018 2018-06-26         DO  1.1118575154  <NA> #> 2287   2068    3M  CC03 2018 2018-06-26      DOSAT  3.8628327612  <NA> #> 2288   2068    3M  CC03 2018 2018-06-26       NO23 -5.5214609179     U #> 2289   2068    3M  CC03 2018 2018-06-26      SALIN  3.3414473773     + #> 2290   2068    3M  CC03 2018 2018-06-26        TKN -0.4155154440  <NA> #> 2291   2068    3M  CC03 2018 2018-06-26         TN -0.4124897230     + #> 2292   2068    3M  CC03 2018 2018-06-26        TSS  2.0794415417     I #> 2293   2068    3M  CC03 2018 2018-06-26       TURB  1.4816045409  <NA> #> 2294   2068    3M  CC03 2018 2018-09-18      CHLAC  2.2617630985  <NA> #> 2295   2068    3M  CC03 2018 2018-09-18       COND  9.9966590834  <NA> #> 2296   2068    3M  CC03 2018 2018-09-18         DO  0.8020015855  <NA> #> 2297   2068    3M  CC03 2018 2018-09-18      DOSAT  3.4812400893  <NA> #> 2298   2068    3M  CC03 2018 2018-09-18       NO23 -4.7105307016     I #> 2299   2068    3M  CC03 2018 2018-09-18        TKN -0.0833816089  <NA> #> 2300   2068    3M  CC03 2018 2018-09-18         TN -0.0790432073     + #> 2301   2068    3M  CC03 2018 2018-09-18         TP -2.3227878003  <NA> #> 2302   2068    3M  CC03 2018 2018-09-18        TSS  1.0986122887     U #> 2303   2068    3M  CC03 2018 2018-09-18       TURB  1.2809338455     A #> 2304   2068    3M  CC03 2018 2018-12-04      CHLAC  1.6486586256  <NA> #> 2305   2068    3M  CC03 2018 2018-12-04       COND 10.7489265434  <NA> #> 2306   2068    3M  CC03 2018 2018-12-04         DO  1.5644405465  <NA> #> 2307   2068    3M  CC03 2018 2018-12-04      DOSAT  4.2239097666  <NA> #> 2308   2068    3M  CC03 2018 2018-12-04       NO23 -1.8971199849     G #> 2309   2068    3M  CC03 2018 2018-12-04      SALIN  3.4094961845  <NA> #> 2310   2068    3M  CC03 2018 2018-12-04        TKN -0.3285040670  <NA> #> 2311   2068    3M  CC03 2018 2018-12-04         TN -0.1392620673     + #> 2312   2068    3M  CC03 2018 2018-12-04         TP -2.6450754019  <NA> #> 2313   2068    3M  CC03 2018 2018-12-04        TSS  2.1972245773     I #> 2314   2068    3M  CC03 2018 2018-12-04       TURB  0.5306282511  <NA> #> 2315  2078A     2  CC04 2019 2019-08-13      CHLAC  3.1780538303  <NA> #> 2316  2078A     2  CC04 2019 2019-08-13       COND  9.8642788393  <NA> #> 2317  2078A     2  CC04 2019 2019-08-13         DO  1.7647307968  <NA> #> 2318  2078A     2  CC04 2019 2019-08-13      DOSAT  4.4176350621  <NA> #> 2319  2078A     2  CC04 2019 2019-08-13       NO23 -5.2983173665     I #> 2320  2078A     2  CC04 2019 2019-08-13      SALIN  2.4274540750  <NA> #> 2321  2078A     2  CC04 2019 2019-08-13        TKN  0.3364722366  <NA> #> 2322  2078A     2  CC04 2019 2019-08-13         TN  0.3393253056     + #> 2323  2078A     2  CC04 2019 2019-08-13         TP -2.9759296463  <NA> #> 2324  2078A     2  CC04 2019 2019-08-13        TSS  1.6094379124     I #> 2325  2078A     2  CC04 2019 2019-08-13       TURB  0.7419373447  <NA> #> 2326  2078B     2  CC05 2019 2019-01-17       COND 10.7433722892  <NA> #> 2327  2078B     2  CC05 2019 2019-01-17         DO  1.9065751437  <NA> #> 2328  2078B     2  CC05 2019 2019-01-17      DOSAT  4.4030540019  <NA> #> 2329  2078B     2  CC05 2019 2019-01-17      SALIN  3.4045251718  <NA> #> 2330  2078B     2  CC05 2019 2019-01-17         TN -0.3827256211     + #> 2331  2078B     2  CC05 2019 2019-01-24      CHLAC  0.2623642645     I #> 2332  2078B     2  CC05 2019 2019-01-24       COND 10.7763069502  <NA> #> 2333  2078B     2  CC05 2019 2019-01-24         DO  1.8702625307  <NA> #> 2334  2078B     2  CC05 2019 2019-01-24      DOSAT  4.4531838290  <NA> #> 2335  2078B     2  CC05 2019 2019-01-24       NO23 -5.1159958098     I #> 2336  2078B     2  CC05 2019 2019-01-24      SALIN  3.4413791713  <NA> #> 2337  2078B     2  CC05 2019 2019-01-24        TKN -0.7985076962  <NA> #> 2338  2078B     2  CC05 2019 2019-01-24         TN -0.7896580809     + #> 2339  2078B     2  CC05 2019 2019-01-24         TP -3.5065578973  <NA> #> 2340  2078B     2  CC05 2019 2019-01-24        TSS  1.0986122887     I #> 2341  2078B     2  CC05 2019 2019-01-24       TURB  0.2623642645  <NA> #> 2342  2078B     2  CC05 2019 2019-03-12      CHLAC  1.2809338455  <NA> #> 2343  2078B     2  CC05 2019 2019-03-12       COND 10.4768935315  <NA> #> 2344  2078B     2  CC05 2019 2019-03-12         DO  1.6992786164  <NA> #> 2345  2078B     2  CC05 2019 2019-03-12      DOSAT  4.3412046402  <NA> #> 2346  2078B     2  CC05 2019 2019-03-12       NO23 -5.5214609179     U #> 2347  2078B     2  CC05 2019 2019-03-12      SALIN  3.1059310659  <NA> #> 2348  2078B     2  CC05 2019 2019-03-12        TKN -0.3424903089  <NA> #> 2349  2078B     2  CC05 2019 2019-03-12         TN -0.3396773676     + #> 2350  2078B     2  CC05 2019 2019-03-12         TP -3.2441936329  <NA> #> 2351  2078B     2  CC05 2019 2019-03-12        TSS  2.1972245773     I #> 2352  2078B     2  CC05 2019 2019-03-12       TURB  0.6931471806  <NA> #> 2353  2078B     2  CC05 2019 2019-04-16      CHLAC  1.4816045409  <NA> #> 2354  2078B     2  CC05 2019 2019-04-16       COND 10.7360705353  <NA> #> 2355  2078B     2  CC05 2019 2019-04-16         DO  1.6505798558  <NA> #> 2356  2078B     2  CC05 2019 2019-04-16      DOSAT  4.3094559418  <NA> #> 2357  2078B     2  CC05 2019 2019-04-16       NO23 -5.5214609179     U #> 2358  2078B     2  CC05 2019 2019-04-16      SALIN  3.3951793093  <NA> #> 2359  2078B     2  CC05 2019 2019-04-16        TKN -0.2484613593  <NA> #> 2360  2078B     2  CC05 2019 2019-04-16         TN -0.2459005384     + #> 2361  2078B     2  CC05 2019 2019-04-16         TP -3.7722610631  <NA> #> 2362  2078B     2  CC05 2019 2019-04-16        TSS  1.6094379124     I #> 2363  2078B     2  CC05 2019 2019-04-16       TURB  0.6418538862  <NA> #> 2364  2078B     2  CC05 2019 2019-06-11      CHLAC  1.1314021115  <NA> #> 2365  2078B     2  CC05 2019 2019-06-11       COND 10.8909447918  <NA> #> 2366  2078B     2  CC05 2019 2019-06-11         DO  1.2059708070  <NA> #> 2367  2078B     2  CC05 2019 2019-06-11      DOSAT  4.0127729085  <NA> #> 2368  2078B     2  CC05 2019 2019-06-11       NO23 -5.5214609179     I #> 2369  2078B     2  CC05 2019 2019-06-11      SALIN  3.5635996377  <NA> #> 2370  2078B     2  CC05 2019 2019-06-11        TKN -0.3285040670  <NA> #> 2371  2078B     2  CC05 2019 2019-06-11         TN -0.3229638866     + #> 2372  2078B     2  CC05 2019 2019-06-11         TP -3.3242363405  <NA> #> 2373  2078B     2  CC05 2019 2019-06-11        TSS  1.0986122887     U #> 2374  2078B     2  CC05 2019 2019-06-11       TURB  0.3364722366  <NA> #> 2375  2078B     2  CC05 2019 2019-08-13      CHLAC  2.8332133441  <NA> #> 2376  2078B     2  CC05 2019 2019-08-13       COND 10.2219412837  <NA> #> 2377  2078B     2  CC05 2019 2019-08-13         DO  1.4036429995  <NA> #> 2378  2078B     2  CC05 2019 2019-08-13      DOSAT  4.0926765051  <NA> #> 2379  2078B     2  CC05 2019 2019-08-13       NO23 -4.6051701860     I #> 2380  2078B     2  CC05 2019 2019-08-13      SALIN  2.8195915758  <NA> #> 2381  2078B     2  CC05 2019 2019-08-13        TKN  0.6418538862  <NA> #> 2382  2078B     2  CC05 2019 2019-08-13         TN  0.6439569364     + #> 2383  2078B     2  CC05 2019 2019-08-13         TP -2.9759296463  <NA> #> 2384  2078B     2  CC05 2019 2019-08-13        TSS  1.7917594692     I #> 2385  2078B     2  CC05 2019 2019-08-13       TURB  0.7884573604  <NA> #> 2386  2078B     2  CC05 2019 2019-08-13       COND 10.3244650523  <NA> #> 2387  2078B     2  CC05 2019 2019-08-13         DO  1.0543120298  <NA> #> 2388  2078B     2  CC05 2019 2019-08-13      DOSAT  3.7541989202  <NA> #> 2389  2078B     2  CC05 2019 2019-08-13      SALIN  2.9322598506  <NA> #> 2390  2078B     2  CC05 2019 2019-10-01       COND 10.7304660807  <NA> #> 2391  2078B     2  CC05 2019 2019-10-01         DO  1.5644405465  <NA> #> 2392  2078B     2  CC05 2019 2019-10-01      DOSAT  4.2724907476  <NA> #> 2393  2078B     2  CC05 2019 2019-10-01      SALIN  3.3864220961  <NA> #> 2394  2078B     2  CC05 2019 2019-11-04       COND 10.7792062586  <NA> #> 2395  2078B     2  CC05 2019 2019-11-04         DO  1.5151272330  <NA> #> 2396  2078B     2  CC05 2019 2019-11-04      DOSAT  4.2061840440  <NA> #> 2397  2078B     2  CC05 2019 2019-11-04      SALIN  3.4423393250  <NA> #> 2398  2078B     2  CC05 2019 2019-11-19      CHLAC  2.6390573296  <NA> #> 2399  2078B     2  CC05 2019 2019-11-19       COND 10.8493565039  <NA> #> 2400  2078B     2  CC05 2019 2019-11-19         DO  2.0135687975  <NA> #> 2401  2078B     2  CC05 2019 2019-11-19      DOSAT  4.6298627986  <NA> #> 2402  2078B     2  CC05 2019 2019-11-19       NO23 -5.5214609179     U #> 2403  2078B     2  CC05 2019 2019-11-19      SALIN  3.5234150144  <NA> #> 2404  2078B     2  CC05 2019 2019-11-19        TKN -0.3011050928  <NA> #> 2405  2078B     2  CC05 2019 2019-11-19         TN -0.2984060358     + #> 2406  2078B     2  CC05 2019 2019-11-19         TP -2.8302178351  <NA> #> 2407  2078B     2  CC05 2019 2019-11-19        TSS  2.0794415417     I #> 2408  2078B     2  CC05 2019 2019-11-19       TURB  1.0296194172     A #> 2409  2078B     2  CC05 2020 2020-02-13      CHLAC  2.1400661635     A #> 2410  2078B     2  CC05 2020 2020-02-13       COND 10.7287588860  <NA> #> 2411  2078B     2  CC05 2020 2020-02-13         DO  1.8961194846  <NA> #> 2412  2078B     2  CC05 2020 2020-02-13      DOSAT  4.5747109785  <NA> #> 2413  2078B     2  CC05 2020 2020-02-13       NO23 -5.5214609179     U #> 2414  2078B     2  CC05 2020 2020-02-13      SALIN  3.3857452771  <NA> #> 2415  2078B     2  CC05 2020 2020-02-13        TKN -0.3424903089  <NA> #> 2416  2078B     2  CC05 2020 2020-02-13         TN -0.3396773676     + #> 2417  2078B     2  CC05 2020 2020-02-13         TP -3.3242363405  <NA> #> 2418  2078B     2  CC05 2020 2020-02-13        TSS  2.2617630985     I #> 2419  2078B     2  CC05 2020 2020-02-13       TURB  1.0296194172  <NA> #> 2420  2078B     2  CC05 2020 2020-03-24      CHLAC  2.2617630985  <NA> #> 2421  2078B     2  CC05 2020 2020-03-24       COND 10.9026109427  <NA> #> 2422  2078B     2  CC05 2020 2020-03-24         DO  1.8357763546  <NA> #> 2423  2078B     2  CC05 2020 2020-03-24      DOSAT  4.5900565482  <NA> #> 2424  2078B     2  CC05 2020 2020-03-24       NO23 -5.5214609179     U #> 2425  2078B     2  CC05 2020 2020-03-24      SALIN  3.5787855313  <NA> #> 2426  2078B     2  CC05 2020 2020-03-24        TKN -0.6161861394  <NA> #> 2427  2078B     2  CC05 2020 2020-03-24         TN -0.6124892775     + #> 2428  2078B     2  CC05 2020 2020-03-24         TP -2.5902671654  <NA> #> 2429  2078B     2  CC05 2020 2020-03-24        TSS  2.4849066498     A #> 2430  2078B     2  CC05 2020 2020-03-24       TURB  1.0647107370  <NA> #> 2431  2078B     2  CC05 2020 2020-06-15      CHLAC  2.8332133441  <NA> #> 2432  2078B     2  CC05 2020 2020-06-15       COND 10.3780433051  <NA> #> 2433  2078B     2  CC05 2020 2020-06-15         DO  1.2325602612  <NA> #> 2434  2078B     2  CC05 2020 2020-06-15      DOSAT  3.9199911751  <NA> #> 2435  2078B     2  CC05 2020 2020-06-15       NO23 -5.5214609179     I #> 2436  2078B     2  CC05 2020 2020-06-15      SALIN  2.9907197317  <NA> #> 2437  2078B     2  CC05 2020 2020-06-15        TKN  0.1823215568  <NA> #> 2438  2078B     2  CC05 2020 2020-06-15         TN  0.1856493469     + #> 2439  2078B     2  CC05 2020 2020-06-15         TP -3.0159349809  <NA> #> 2440  2078B     2  CC05 2020 2020-06-15        TSS  1.6094379124     I #> 2441  2078B     2  CC05 2020 2020-06-15       TURB  0.9932517730  <NA> #> 2442  2078B     2  CC05 2020 2020-07-27      CHLAC  2.5649493575     A #> 2443  2078B     2  CC05 2020 2020-07-27       COND 10.7499993898  <NA> #> 2444  2078B     2  CC05 2020 2020-07-27         DO  1.4422019931  <NA> #> 2445  2078B     2  CC05 2020 2020-07-27      DOSAT  4.2150861799  <NA> #> 2446  2078B     2  CC05 2020 2020-07-27       NO23 -5.5214609179     U #> 2447  2078B     2  CC05 2020 2020-07-27      SALIN  3.4041928906  <NA> #> 2448  2078B     2  CC05 2020 2020-07-27        TKN -0.3424903089  <NA> #> 2449  2078B     2  CC05 2020 2020-07-27         TN -0.3396773676     + #> 2450  2078B     2  CC05 2020 2020-07-27         TP -3.1010927892  <NA> #> 2451  2078B     2  CC05 2020 2020-07-27        TSS  1.6094379124     I #> 2452  2078B     2  CC05 2020 2020-07-27       TURB  1.1631508098  <NA> #> 2453  2078B     2  CC05 2020 2020-08-26      CHLAC  2.8903717579  <NA> #> 2454  2078B     2  CC05 2020 2020-08-26       COND 10.1730947543  <NA> #> 2455  2078B     2  CC05 2020 2020-08-26         DO  1.5062971535  <NA> #> 2456  2078B     2  CC05 2020 2020-08-26      DOSAT  4.1972019477  <NA> #> 2457  2078B     2  CC05 2020 2020-08-26       NO23 -5.5214609179     U #> 2458  2078B     2  CC05 2020 2020-08-26      SALIN  2.7625383864  <NA> #> 2459  2078B     2  CC05 2020 2020-08-26        TKN -0.0618754037  <NA> #> 2460  2078B     2  CC05 2020 2020-08-26         TN -0.0597500044     + #> 2461  2078B     2  CC05 2020 2020-08-26         TP -2.9565115604  <NA> #> 2462  2078B     2  CC05 2020 2020-08-26        TSS  1.7917594692     I #> 2463  2078B     2  CC05 2020 2020-08-26       TURB  1.0647107370  <NA> #> 2464  2078B     2  CC05 2021 2021-01-14      CHLAC  0.9162907319  <NA> #> 2465  2078B     2  CC05 2021 2021-01-14       COND 10.6789517756  <NA> #> 2466  2078B     2  CC05 2021 2021-01-14         DO  1.7422190237  <NA> #> 2467  2078B     2  CC05 2021 2021-01-14      DOSAT  4.2427645673  <NA> #> 2468  2078B     2  CC05 2021 2021-01-14       NO23 -4.6051701860  <NA> #> 2469  2078B     2  CC05 2021 2021-01-14      SALIN  3.3339886320  <NA> #> 2470  2078B     2  CC05 2021 2021-01-14        TKN -0.6348782724  <NA> #> 2471  2078B     2  CC05 2021 2021-01-14         TN -0.6161861394     + #> 2472  2078B     2  CC05 2021 2021-01-14         TP -3.4420193762  <NA> #> 2473  2078B     2  CC05 2021 2021-01-14        TSS  1.0986122887     I #> 2474  2078B     2  CC05 2021 2021-01-14       TURB  0.5306282511  <NA> #> 2475  2078B     2  CC05 2021 2021-02-24       COND 10.7448823096  <NA> #> 2476  2078B     2  CC05 2021 2021-02-24         DO  1.5518087996  <NA> #> 2477  2078B     2  CC05 2021 2021-02-24      DOSAT  4.1987045775  <NA> #> 2478  2078B     2  CC05 2021 2021-02-24       NO23 -4.6051701860     I #> 2479  2078B     2  CC05 2021 2021-02-24      SALIN  3.4061849232  <NA> #> 2480  2078B     2  CC05 2021 2021-02-24        TKN -0.8915981193  <NA> #> 2481  2078B     2  CC05 2021 2021-02-24         TN -0.8818893052     + #> 2482  2078B     2  CC05 2021 2021-02-24         TP -3.2441936329  <NA> #> 2483  2078B     2  CC05 2021 2021-02-24        TSS  1.0986122887     I #> 2484  2078B     2  CC05 2021 2021-03-23      CHLAC  1.1939224685  <NA> #> 2485  2078B     2  CC05 2021 2021-03-23       COND 10.8800451952  <NA> #> 2486  2078B     2  CC05 2021 2021-03-23         DO  1.7783364489  <NA> #> 2487  2078B     2  CC05 2021 2021-03-23      DOSAT  4.4042772436  <NA> #> 2488  2078B     2  CC05 2021 2021-03-23       NO23 -4.9618451299     I #> 2489  2078B     2  CC05 2021 2021-03-23      SALIN  3.5579161896  <NA> #> 2490  2078B     2  CC05 2021 2021-03-23        TKN -0.5447271754  <NA> #> 2491  2078B     2  CC05 2021 2021-03-23         TN -0.5378542962     + #> 2492  2078B     2  CC05 2021 2021-03-23         TP -2.8134107168  <NA> #> 2493  2078B     2  CC05 2021 2021-03-23        TSS  2.4849066498  <NA> #> 2494  2078B     2  CC05 2021 2021-03-23       TURB  1.6863989536  <NA> #> 2495  2078B     2  CC05 2021 2021-07-28      CHLAC  2.5649493575  <NA> #> 2496  2078B     2  CC05 2021 2021-07-28       COND 10.0731881321  <NA> #> 2497  2078B     2  CC05 2021 2021-07-28         DO  0.9001613499  <NA> #> 2498  2078B     2  CC05 2021 2021-07-28      DOSAT  3.6027767551  <NA> #> 2499  2078B     2  CC05 2021 2021-07-28       NO23 -5.5214609179     U #> 2500  2078B     2  CC05 2021 2021-07-28      SALIN  2.6665335209  <NA> #> 2501  2078B     2  CC05 2021 2021-07-28        TKN  0.0000000000  <NA> #> 2502  2078B     2  CC05 2021 2021-07-28         TN  0.0019980027     + #> 2503  2078B     2  CC05 2021 2021-07-28         TP -3.1010927892  <NA> #> 2504  2078B     2  CC05 2021 2021-07-28        TSS  1.3862943611     I #> 2505  2078B     2  CC05 2021 2021-07-28       TURB  1.0296194172  <NA> #> 2506  2078B     2  CC05 2021 2021-08-26      CHLAC  2.4849066498  <NA> #> 2507  2078B     2  CC05 2021 2021-08-26       COND 10.2519942268  <NA> #> 2508  2078B     2  CC05 2021 2021-08-26         DO  1.3737155789  <NA> #> 2509  2078B     2  CC05 2021 2021-08-26      DOSAT  4.0324691585  <NA> #> 2510  2078B     2  CC05 2021 2021-08-26       NO23 -5.5214609179     U #> 2511  2078B     2  CC05 2021 2021-08-26      SALIN  2.8553201198  <NA> #> 2512  2078B     2  CC05 2021 2021-08-26        TKN -0.2231435513  <NA> #> 2513  2078B     2  CC05 2021 2021-08-26         TN -0.2206466711     + #> 2514  2078B     2  CC05 2021 2021-08-26         TP -2.8134107168  <NA> #> 2515  2078B     2  CC05 2021 2021-08-26        TSS  1.9459101491     I #> 2516  2078B     2  CC05 2021 2021-08-26       TURB  0.8754687374  <NA> #> 2517  2078B     2  CC05 2021 2021-09-13      CHLAC  2.5649493575  <NA> #> 2518  2078B     2  CC05 2021 2021-09-13       COND 10.4619312252  <NA> #> 2519  2078B     2  CC05 2021 2021-09-13         DO  1.4929040962  <NA> #> 2520  2078B     2  CC05 2021 2021-09-13      DOSAT  4.2091602367  <NA> #> 2521  2078B     2  CC05 2021 2021-09-13       NO23 -5.5214609179     U #> 2522  2078B     2  CC05 2021 2021-09-13      SALIN  3.0842009215  <NA> #> 2523  2078B     2  CC05 2021 2021-09-13        TKN -0.0943106795  <NA> #> 2524  2078B     2  CC05 2021 2021-09-13         TN -0.0921152889     + #> 2525  2078B     2  CC05 2021 2021-09-13         TP -2.9565115604  <NA> #> 2526  2078B     2  CC05 2021 2021-09-13        TSS  2.0794415417     I #> 2527  2078B     2  CC05 2021 2021-09-13       TURB  1.0986122887     A #> 2528  2078B     2  CC05 2022 2022-04-19      CHLAC  2.3978952728  <NA> #> 2529  2078B     2  CC05 2022 2022-04-19       COND 10.9594532665  <NA> #> 2530  2078B     2  CC05 2022 2022-04-19         DO  1.6486586256  <NA> #> 2531  2078B     2  CC05 2022 2022-04-19      DOSAT  4.3845235149  <NA> #> 2532  2078B     2  CC05 2022 2022-04-19       NO23 -5.5214609179     U #> 2533  2078B     2  CC05 2022 2022-04-19      SALIN  3.6449275666  <NA> #> 2534  2078B     2  CC05 2022 2022-04-19        TKN -0.4462871026  <NA> #> 2535  2078B     2  CC05 2022 2022-04-19         TN -0.4431669753     + #> 2536  2078B     2  CC05 2022 2022-04-19         TP -2.6592600369  <NA> #> 2537  2078B     2  CC05 2022 2022-04-19        TSS  3.0910424534  <NA> #> 2538  2078B     2  CC05 2022 2022-04-19       TURB  1.5892352051     A #> 2539  2078B     2  CC05 2022 2022-05-10      CHLAC  1.9021075264  <NA> #> 2540  2078B     2  CC05 2022 2022-05-10       COND 10.8257603561  <NA> #> 2541  2078B     2  CC05 2022 2022-05-10         DO  1.6114359151  <NA> #> 2542  2078B     2  CC05 2022 2022-05-10      DOSAT  4.3148178850  <NA> #> 2543  2078B     2  CC05 2022 2022-05-10       NO23 -5.5214609179     U #> 2544  2078B     2  CC05 2022 2022-05-10      SALIN  3.4943840964  <NA> #> 2545  2078B     2  CC05 2022 2022-05-10        TKN -0.1984509387  <NA> #> 2546  2078B     2  CC05 2022 2022-05-10         TN -0.1960148839     + #> 2547  2078B     2  CC05 2022 2022-05-10         TP -2.6450754019  <NA> #> 2548  2078B     2  CC05 2022 2022-05-10        TSS  2.1972245773     I #> 2549  2078B     2  CC05 2022 2022-05-10       TURB  1.6486586256  <NA> #> 2550  2078B     2  CC05 2022 2022-09-20      CHLAC  2.2082744135  <NA> #> 2551  2078B     2  CC05 2022 2022-09-20       COND 10.0045990539  <NA> #> 2552  2078B     2  CC05 2022 2022-09-20         DO  0.9001613499  <NA> #> 2553  2078B     2  CC05 2022 2022-09-20      DOSAT  3.5695326965  <NA> #> 2554  2078B     2  CC05 2022 2022-09-20       NO23 -5.5214609179     U #> 2555  2078B     2  CC05 2022 2022-09-20      SALIN  2.5832425505  <NA> #> 2556  2078B     2  CC05 2022 2022-09-20        TKN  0.0953101798  <NA> #> 2557  2078B     2  CC05 2022 2022-09-20         TN  0.0971267107     + #> 2558  2078B     2  CC05 2022 2022-09-20         TP -2.7333680091  <NA> #> 2559  2078B     2  CC05 2022 2022-09-20        TSS  1.3862943611     I #> 2560  2078B     2  CC05 2022 2022-09-20       TURB  0.4054651081     A #> 2561  2078B     2  CC05 2022 2022-10-31      CHLAC  2.7725887222  <NA> #> 2562  2078B     2  CC05 2022 2022-10-31       COND 10.6157508503  <NA> #> 2563  2078B     2  CC05 2022 2022-10-31         DO  1.1505720276  <NA> #> 2564  2078B     2  CC05 2022 2022-10-31      DOSAT  3.8329797981  <NA> #> 2565  2078B     2  CC05 2022 2022-10-31       NO23 -5.5214609179     U #> 2566  2078B     2  CC05 2022 2022-10-31      SALIN  3.2584810795  <NA> #> 2567  2078B     2  CC05 2022 2022-10-31        TKN -1.8325814637     U #> 2568  2078B     2  CC05 2022 2022-10-31         TN -2.5010360317     + #> 2569  2078B     2  CC05 2022 2022-10-31         TP -2.9374633654  <NA> #> 2570  2078B     2  CC05 2022 2022-10-31        TSS  1.7917594692     I #> 2571  2078B     2  CC05 2022 2022-10-31       TURB  1.2237754316  <NA> #> 2572  2078B     2  CC05 2021 2021-03-23      CHLAC  1.5892352051  <NA> #> 2573  2078B     2  CC05 2021 2021-03-23       COND 10.8660128047  <NA> #> 2574  2078B     2  CC05 2021 2021-03-23         DO  2.0162354658  <NA> #> 2575  2078B     2  CC05 2021 2021-03-23      DOSAT  4.6802776585  <NA> #> 2576  2078B     2  CC05 2021 2021-03-23       NO23 -5.5214609179     U #> 2577  2078B     2  CC05 2021 2021-03-23      SALIN  3.5415388662  <NA> #> 2578  2078B     2  CC05 2021 2021-03-23        TKN  0.0953101798  <NA> #> 2579  2078B     2  CC05 2021 2021-03-23         TN  0.0971267107     + #> 2580  2078B     2  CC05 2021 2021-03-23         TP -3.2968373663  <NA> #> 2581  2078B     2  CC05 2021 2021-03-23        TSS  1.0986122887     I #> 2582  2078B     2  CC05 2021 2021-03-23       TURB  0.7884573604  <NA> #> 2583  2078B     2  CC05 2021 2021-07-28      CHLAC  1.5686159179     I #> 2584  2078B     2  CC05 2021 2021-07-28       COND  9.6616070559  <NA> #> 2585  2078B     2  CC05 2021 2021-07-28         DO -0.3566749439  <NA> #> 2586  2078B     2  CC05 2021 2021-07-28      DOSAT  2.3418058061  <NA> #> 2587  2078B     2  CC05 2021 2021-07-28       NO23 -5.5214609179     U #> 2588  2078B     2  CC05 2021 2021-07-28      SALIN  2.2049722641  <NA> #> 2589  2078B     2  CC05 2021 2021-07-28        TKN  0.0953101798  <NA> #> 2590  2078B     2  CC05 2021 2021-07-28         TN  0.0971267107     + #> 2591  2078B     2  CC05 2021 2021-07-28         TP -3.3242363405  <NA> #> 2592  2078B     2  CC05 2021 2021-07-28        TSS  1.0986122887     U #> 2593  2078B     2  CC05 2021 2021-07-28       TURB  0.5306282511  <NA> #> 2594  2078B     2  CC05 2021 2021-08-26      CHLAC  2.5649493575  <NA> #> 2595  2078B     2  CC05 2021 2021-08-26       COND  9.7645702533  <NA> #> 2596  2078B     2  CC05 2021 2021-08-26         DO  0.7030975114  <NA> #> 2597  2078B     2  CC05 2021 2021-08-26      DOSAT  3.3141860047  <NA> #> 2598  2078B     2  CC05 2021 2021-08-26       NO23 -5.5214609179     U #> 2599  2078B     2  CC05 2021 2021-08-26      SALIN  2.3223877203  <NA> #> 2600  2078B     2  CC05 2021 2021-08-26        TKN  0.2623642645  <NA> #> 2601  2078B     2  CC05 2021 2021-08-26         TN  0.2639015438     + #> 2602  2078B     2  CC05 2021 2021-08-26         TP -2.9565115604  <NA> #> 2603  2078B     2  CC05 2021 2021-08-26        TSS  2.3025850930     I #> 2604  2078B     2  CC05 2021 2021-08-26       TURB  2.3978952728  <NA> #> 2605  2078B     2  CC05 2021 2021-09-13      CHLAC  2.8332133441     A #> 2606  2078B     2  CC05 2021 2021-09-13       COND 10.1916695000  <NA> #> 2607  2078B     2  CC05 2021 2021-09-13         DO  1.2296405511  <NA> #> 2608  2078B     2  CC05 2021 2021-09-13      DOSAT  3.9239515763  <NA> #> 2609  2078B     2  CC05 2021 2021-09-13       NO23 -5.5214609179     U #> 2610  2078B     2  CC05 2021 2021-09-13      SALIN  2.7868613815  <NA> #> 2611  2078B     2  CC05 2021 2021-09-13        TKN  0.0953101798  <NA> #> 2612  2078B     2  CC05 2021 2021-09-13         TN  0.0971267107     + #> 2613  2078B     2  CC05 2021 2021-09-13         TP -2.9957322736  <NA> #> 2614  2078B     2  CC05 2021 2021-09-13        TSS  1.6094379124     I #> 2615  2078B     2  CC05 2021 2021-09-13       TURB  1.7578579176  <NA> #> 2616  2078B     2  CC05 2021 2021-10-20      CHLAC  2.7725887222  <NA> #> 2617  2078B     2  CC05 2021 2021-10-20       COND 10.4756810512  <NA> #> 2618  2078B     2  CC05 2021 2021-10-20         DO  0.2700271372  <NA> #> 2619  2078B     2  CC05 2021 2021-10-20      DOSAT  2.9391619221  <NA> #> 2620  2078B     2  CC05 2021 2021-10-20       NO23 -5.5214609179     U #> 2621  2078B     2  CC05 2021 2021-10-20      SALIN  3.1099534176  <NA> #> 2622  2078B     2  CC05 2021 2021-10-20        TKN  0.0953101798  <NA> #> 2623  2078B     2  CC05 2021 2021-10-20         TN  0.0971267107     + #> 2624  2078B     2  CC05 2021 2021-10-20         TP -3.1235656451  <NA> #> 2625  2078B     2  CC05 2021 2021-10-20        TSS  1.9459101491     I #> 2626  2078B     2  CC05 2021 2021-10-20       TURB  1.4109869737  <NA> #> 2627  2078B     2  CC05 2022 2022-04-06      CHLAC  1.8718021769  <NA> #> 2628  2078B     2  CC05 2022 2022-04-06       COND 11.0061250625  <NA> #> 2629  2078B     2  CC05 2022 2022-04-06         DO  0.6365768291  <NA> #> 2630  2078B     2  CC05 2022 2022-04-06      DOSAT  3.3911470458  <NA> #> 2631  2078B     2  CC05 2022 2022-04-06       NO23 -5.5214609179     U #> 2632  2078B     2  CC05 2022 2022-04-06      SALIN  3.6980869349  <NA> #> 2633  2078B     2  CC05 2022 2022-04-06        TKN -0.0512932944  <NA> #> 2634  2078B     2  CC05 2022 2022-04-06         TN -0.0491902442     + #> 2635  2078B     2  CC05 2022 2022-04-06         TP -3.1700856607  <NA> #> 2636  2078B     2  CC05 2022 2022-04-06        TSS  1.3862943611     I #> 2637  2078B     2  CC05 2022 2022-04-06       TURB  0.0953101798  <NA> #> 2638  2078B     2  CC05 2022 2022-05-10      CHLAC  2.5649493575  <NA> #> 2639  2078B     2  CC05 2022 2022-05-10       COND 10.7027274806  <NA> #> 2640  2078B     2  CC05 2022 2022-05-10         DO  1.1281710909  <NA> #> 2641  2078B     2  CC05 2022 2022-05-10      DOSAT  3.7841896339  <NA> #> 2642  2078B     2  CC05 2022 2022-05-10       NO23 -5.5214609179     U #> 2643  2078B     2  CC05 2022 2022-05-10      SALIN  3.3579418730  <NA> #> 2644  2078B     2  CC05 2022 2022-05-10        TKN -0.0512932944  <NA> #> 2645  2078B     2  CC05 2022 2022-05-10         TN -0.0491902442     + #> 2646  2078B     2  CC05 2022 2022-05-10         TP -3.1010927892  <NA> #> 2647  2078B     2  CC05 2022 2022-05-10        TSS  2.1972245773     I #> 2648  2078B     2  CC05 2022 2022-05-10       TURB  1.2237754316  <NA> #> 2649  2078B     2  CC05 2022 2022-09-20      CHLAC  0.8754687374     I #> 2650  2078B     2  CC05 2022 2022-09-20       COND  8.7041705597  <NA> #> 2651  2078B     2  CC05 2022 2022-09-20         DO  0.6830968447  <NA> #> 2652  2078B     2  CC05 2022 2022-09-20      DOSAT  3.2503744919  <NA> #> 2653  2078B     2  CC05 2022 2022-09-20       NO23 -5.5214609179     U #> 2654  2078B     2  CC05 2022 2022-09-20      SALIN  1.1817271954  <NA> #> 2655  2078B     2  CC05 2022 2022-09-20        TKN -0.0100503359  <NA> #> 2656  2078B     2  CC05 2022 2022-09-20         TN -0.0080321717     + #> 2657  2078B     2  CC05 2022 2022-09-20         TP -3.4737680745  <NA> #> 2658  2078B     2  CC05 2022 2022-09-20        TSS  0.6931471806     I #> 2659  2078B     2  CC05 2022 2022-09-20       TURB -0.1053605157     I #> 2660  2078B     2  CC05 2022 2022-10-31      CHLAC  3.1780538303     A #> 2661  2078B     2  CC05 2022 2022-10-31       COND 10.3516289349  <NA> #> 2662  2078B     2  CC05 2022 2022-10-31         DO  0.2231435513  <NA> #> 2663  2078B     2  CC05 2022 2022-10-31      DOSAT  2.8678989020  <NA> #> 2664  2078B     2  CC05 2022 2022-10-31       NO23 -5.5214609179     U #> 2665  2078B     2  CC05 2022 2022-10-31      SALIN  2.9663034629  <NA> #> 2666  2078B     2  CC05 2022 2022-10-31        TKN  0.1823215568  <NA> #> 2667  2078B     2  CC05 2022 2022-10-31         TN  0.1839868361     + #> 2668  2078B     2  CC05 2022 2022-10-31         TP -2.5902671654  <NA> #> 2669  2078B     2  CC05 2022 2022-10-31        TSS  1.9459101491     I #> 2670  2078B     2  CC05 2022 2022-10-31       TURB  3.0910424534  <NA> #> 2671  2078B     2  CC05 2023 2023-02-13      CHLAC  2.4849066498  <NA> #> 2672  2078B     2  CC05 2023 2023-02-13       COND 10.7464115759  <NA> #> 2673  2078B     2  CC05 2023 2023-02-13         DO  1.2892326483  <NA> #> 2674  2078B     2  CC05 2023 2023-02-13      DOSAT  3.8836235309  <NA> #> 2675  2078B     2  CC05 2023 2023-02-13       NO23 -5.5214609179     U #> 2676  2078B     2  CC05 2023 2023-02-13      SALIN  3.4085039568  <NA> #> 2677  2078B     2  CC05 2023 2023-02-13        TKN  0.1823215568  <NA> #> 2678  2078B     2  CC05 2023 2023-02-13         TN  0.1839868361     + #> 2679  2078B     2  CC05 2023 2023-02-13         TP -3.0791138825  <NA> #> 2680  2078B     2  CC05 2023 2023-02-13        TSS  2.6390573296  <NA> #> 2681  2078B     2  CC05 2023 2023-02-13       TURB  1.2237754316  <NA> #> 2682  2078B     2  CC05 2023 2023-04-10       COND 11.0888889713  <NA> #> 2683  2078B     2  CC05 2023 2023-04-10         DO  0.4762341790  <NA> #> 2684  2078B     2  CC05 2023 2023-04-10      DOSAT  3.2188758249  <NA> #> 2685  2078B     2  CC05 2023 2023-04-10       NO23 -3.9120230054     U #> 2686  2078B     2  CC05 2023 2023-04-10      SALIN  3.7934646693  <NA> #> 2687  2078B     2  CC05 2023 2023-04-10        TKN  0.1823215568  <NA> #> 2688  2078B     2  CC05 2023 2023-04-10         TN  0.1906203596     + #> 2689  2078B     2  CC05 2023 2023-04-10         TP -2.9004220937  <NA> #> 2690  2078B     2  CC05 2023 2023-04-10        TSS  1.3862943611     I #> 2691  2078B     2  CC05 2019 2019-06-06      CHLAC  0.7419373447     I #> 2692  2078B     2  CC05 2019 2019-06-06       NO23 -5.2983173665     I #> 2693  2078B     2  CC05 2019 2019-06-06        TKN -0.4004775666  <NA> #> 2694  2078B     2  CC05 2019 2019-06-06         TN -0.3945251681     + #> 2695  2078B     2  CC05 2019 2019-06-06         TP -3.4420193762  <NA> #> 2696   2035    3F CC104 2015 2015-06-04       COND  7.8336002237  <NA> #> 2697   2035    3F CC104 2015 2015-06-04         DO  1.6292405397  <NA> #> 2698   2035    3F CC104 2015 2015-06-04      DOSAT  4.1108738642  <NA> #> 2699   2035    3F CC104 2015 2015-06-04      SALIN  0.2926696140     + #> 2700   2035    3F CC104 2015 2015-08-06       COND  6.3868793194  <NA> #> 2701   2035    3F CC104 2015 2015-08-06         DO  1.7047480922  <NA> #> 2702   2035    3F CC104 2015 2015-08-06      DOSAT  4.2046926194  <NA> #> 2703   2035    3F CC104 2015 2015-08-06      SALIN -1.2729656758     + #> 2704   2035    3F CC104 2015 2015-08-19       COND  6.8351845861  <NA> #> 2705   2035    3F CC104 2015 2015-08-19         DO  1.4109869737  <NA> #> 2706   2035    3F CC104 2015 2015-08-19      DOSAT  3.9318256327  <NA> #> 2707   2035    3F CC104 2015 2015-08-19      SALIN -0.7985076962     + #> 2708   2035    3F CC104 2015 2015-09-15       COND  6.4583382833  <NA> #> 2709   2035    3F CC104 2015 2015-09-15         DO  1.6677068206  <NA> #> 2710   2035    3F CC104 2015 2015-09-15      DOSAT  4.1896547420  <NA> #> 2711   2035    3F CC104 2015 2015-09-15      SALIN -1.2039728043     + #> 2712   2035    3F CC104 2015 2015-11-25       COND  7.2584121506  <NA> #> 2713   2035    3F CC104 2015 2015-11-25         DO  1.8082887712  <NA> #> 2714   2035    3F CC104 2015 2015-11-25      DOSAT  4.2046926194  <NA> #> 2715   2035    3F CC104 2015 2015-11-25      SALIN -0.2231435513     + #> 2716   2035    3F CC104 2015 2015-12-30       COND  7.6563371664  <NA> #> 2717   2035    3F CC104 2015 2015-12-30         DO  1.8562979904  <NA> #> 2718   2035    3F CC104 2015 2015-12-30      DOSAT  4.3040650932  <NA> #> 2719   2035    3F CC104 2015 2015-12-30      SALIN  0.1310282624     + #> 2720   2035    3F CC104 2015 2015-05-21       COND  8.9299648747  <NA> #> 2721   2035    3F CC104 2015 2015-05-21         DO  1.6292405397  <NA> #> 2722   2035    3F CC104 2015 2015-05-21      DOSAT  4.1743872699  <NA> #> 2723   2035    3F CC104 2015 2015-05-21      SALIN  1.3787660947     + #> 2724   2035    3F CC104 2015 2015-06-04       COND  9.1162494486  <NA> #> 2725   2035    3F CC104 2015 2015-06-04         DO  1.5686159179  <NA> #> 2726   2035    3F CC104 2015 2015-06-04      DOSAT  4.1108738642  <NA> #> 2727   2035    3F CC104 2015 2015-06-04      SALIN  1.6054298910     + #> 2728   2035    3F CC104 2015 2015-07-15       COND  7.5559050936  <NA> #> 2729   2035    3F CC104 2015 2015-07-15      SALIN -0.0833816089     + #> 2730   2035    3F CC104 2015 2015-08-06       COND  6.8057225534  <NA> #> 2731   2035    3F CC104 2015 2015-08-06         DO  1.6486586256  <NA> #> 2732   2035    3F CC104 2015 2015-08-06      DOSAT  4.1431347264  <NA> #> 2733   2035    3F CC104 2015 2015-08-06      SALIN -0.8209805521     + #> 2734   2035    3F CC104 2015 2015-08-19       COND  6.6200732065  <NA> #> 2735   2035    3F CC104 2015 2015-08-19         DO  1.4586150227  <NA> #> 2736   2035    3F CC104 2015 2015-08-19      DOSAT  3.9889840466  <NA> #> 2737   2035    3F CC104 2015 2015-08-19      SALIN -1.0216512475     + #> 2738   2035    3F CC104 2015 2015-09-15       COND  6.3315018499  <NA> #> 2739   2035    3F CC104 2015 2015-09-15         DO  1.6677068206  <NA> #> 2740   2035    3F CC104 2015 2015-09-15      DOSAT  4.1588830834  <NA> #> 2741   2035    3F CC104 2015 2015-09-15      SALIN -1.3470736480     + #> 2742   2035    3F CC104 2015 2015-11-25       COND  6.9147308927  <NA> #> 2743   2035    3F CC104 2015 2015-11-25         DO  2.0281482473  <NA> #> 2744   2035    3F CC104 2015 2015-11-25      DOSAT  4.4188406078  <NA> #> 2745   2035    3F CC104 2015 2015-11-25      SALIN -0.5798184953     + #> 2746   2035    3F CC104 2015 2015-12-30       COND  7.5267175614  <NA> #> 2747   2035    3F CC104 2015 2015-12-30         DO  1.8245492921  <NA> #> 2748   2035    3F CC104 2015 2015-12-30      DOSAT  4.2766661190  <NA> #> 2749   2035    3F CC104 2015 2015-12-30      SALIN  0.0000000000     + #> 2750   2035    3F CC104 2015 2015-05-21       COND  9.3336193881  <NA> #> 2751   2035    3F CC104 2015 2015-05-21         DO  1.4109869737  <NA> #> 2752   2035    3F CC104 2015 2015-05-21      DOSAT  4.0073331852  <NA> #> 2753   2035    3F CC104 2015 2015-05-21      SALIN  1.7664416612     + #> 2754   2035    3F CC104 2015 2015-06-04       COND  9.1775072149  <NA> #> 2755   2035    3F CC104 2015 2015-06-04         DO  1.3350010667  <NA> #> 2756   2035    3F CC104 2015 2015-06-04      DOSAT  3.8712010109  <NA> #> 2757   2035    3F CC104 2015 2015-06-04      SALIN  1.6677068206     + #> 2758   2035    3F CC104 2015 2015-07-15       COND  7.9024874372  <NA> #> 2759   2035    3F CC104 2015 2015-07-15      SALIN  0.2546422184     + #> 2760   2035    3F CC104 2015 2015-08-06       COND  6.7765069924  <NA> #> 2761   2035    3F CC104 2015 2015-08-06         DO  1.3350010667  <NA> #> 2762   2035    3F CC104 2015 2015-08-06      DOSAT  3.8918202981  <NA> #> 2763   2035    3F CC104 2015 2015-08-06      SALIN -0.8915981193     + #> 2764   2035    3F CC104 2015 2015-08-19       COND  6.4846352356  <NA> #> 2765   2035    3F CC104 2015 2015-08-19         DO  1.3862943611  <NA> #> 2766   2035    3F CC104 2015 2015-08-19      DOSAT  3.9318256327  <NA> #> 2767   2035    3F CC104 2015 2015-08-19      SALIN -1.2039728043     + #> 2768   2035    3F CC104 2015 2015-09-15       COND  6.2934192788  <NA> #> 2769   2035    3F CC104 2015 2015-09-15         DO  1.6486586256  <NA> #> 2770   2035    3F CC104 2015 2015-09-15      DOSAT  4.1588830834  <NA> #> 2771   2035    3F CC104 2015 2015-09-15      SALIN -1.3862943611     + #> 2772   2035    3F CC104 2015 2015-11-25       COND  6.8101424501  <NA> #> 2773   2035    3F CC104 2015 2015-11-25         DO  1.8870696490  <NA> #> 2774   2035    3F CC104 2015 2015-11-25      DOSAT  4.2766661190  <NA> #> 2775   2035    3F CC104 2015 2015-11-25      SALIN -0.6931471806     + #> 2776   2035    3F CC104 2015 2015-12-30       COND  7.6847839435  <NA> #> 2777   2035    3F CC104 2015 2015-12-30         DO  1.5686159179  <NA> #> 2778   2035    3F CC104 2015 2015-12-30      DOSAT  4.0430512678  <NA> #> 2779   2035    3F CC104 2015 2015-12-30      SALIN  0.1484200051     + #> 2780   2035    3F CC104 2022 2022-01-24       COND  7.5234813126  <NA> #> 2781   2035    3F CC104 2022 2022-01-24         DO  2.2257040487  <NA> #> 2782   2035    3F CC104 2022 2022-01-24      DOSAT  4.4636066217  <NA> #> 2783   2035    3F CC104 2022 2022-01-24      SALIN -0.0512932944  <NA> #> 2784   2035    3F CC104 2022 2022-03-03       COND  7.6722924556  <NA> #> 2785   2035    3F CC104 2022 2022-03-03         DO  2.0108949991  <NA> #> 2786   2035    3F CC104 2022 2022-03-03      DOSAT  4.3870141762  <NA> #> 2787   2035    3F CC104 2022 2022-03-03      SALIN  0.0953101798  <NA> #> 2788   2035    3F CC104 2022 2022-05-23       COND  7.7981126288  <NA> #> 2789   2035    3F CC104 2022 2022-05-23         DO  1.9837562915  <NA> #> 2790   2035    3F CC104 2022 2022-05-23      DOSAT  4.4920014879  <NA> #> 2791   2035    3F CC104 2022 2022-05-23      SALIN  0.2231435513  <NA> #> 2792   2035    3F CC104 2022 2022-06-27       COND  7.0475172214  <NA> #> 2793   2035    3F CC104 2022 2022-06-27         DO  1.8099267732  <NA> #> 2794   2035    3F CC104 2022 2022-06-27      DOSAT  4.3000027992  <NA> #> 2795   2035    3F CC104 2022 2022-06-27      SALIN -0.5621189182  <NA> #> 2796   2035    3F CC104 2023 2023-01-09       COND  6.8232861224  <NA> #> 2797   2035    3F CC104 2023 2023-01-09         DO  1.8991179875  <NA> #> 2798   2035    3F CC104 2023 2023-01-09      DOSAT  4.2696974497  <NA> #> 2799   2035    3F CC104 2023 2023-01-09      SALIN -0.7985076962  <NA> #> 2800   2035    3F CC104 2023 2023-03-14       COND  7.5060421785  <NA> #> 2801   2035    3F CC104 2023 2023-03-14         DO  1.7334238922  <NA> #> 2802   2035    3F CC104 2023 2023-03-14      DOSAT  4.1635596312  <NA> #> 2803   2035    3F CC104 2023 2023-03-14      SALIN -0.0725706928  <NA> #> 2804   2035    3F CC104 2023 2023-05-10       COND  7.6177595766  <NA> #> 2805   2035    3F CC104 2023 2023-05-10         DO  1.6331544391  <NA> #> 2806   2035    3F CC104 2023 2023-05-10      DOSAT  4.0876555741  <NA> #> 2807   2035    3F CC104 2023 2023-05-10      SALIN  0.0392207132  <NA> #> 2808   2035    3F CC104 2022 2022-01-24      CHLAC  0.1823215568     I #> 2809   2035    3F CC104 2022 2022-01-24      COLOR  3.4965075615  <NA> #> 2810   2035    3F CC104 2022 2022-01-24       COND  7.4336665402  <NA> #> 2811   2035    3F CC104 2022 2022-01-24         DO  2.1905355892  <NA> #> 2812   2035    3F CC104 2022 2022-01-24      DOSAT  4.4473461008  <NA> #> 2813   2035    3F CC104 2022 2022-01-24       NO23 -2.3025850930  <NA> #> 2814   2035    3F CC104 2022 2022-01-24      SALIN -0.1508228897  <NA> #> 2815   2035    3F CC104 2022 2022-01-24        TKN -0.4155154440  <NA> #> 2816   2035    3F CC104 2022 2022-01-24         TN -0.2744368457     + #> 2817   2035    3F CC104 2022 2022-01-24         TP -1.0788096614  <NA> #> 2818   2035    3F CC104 2022 2022-01-24        TSS  1.3862943611     I #> 2819   2035    3F CC104 2022 2022-01-24       TURB  2.0541237337  <NA> #> 2820   2035    3F CC104 2022 2022-03-03      CHLAC  0.6418538862     I #> 2821   2035    3F CC104 2022 2022-03-03      COLOR  3.4657359028     A #> 2822   2035    3F CC104 2022 2022-03-03       COND  7.7336835708  <NA> #> 2823   2035    3F CC104 2022 2022-03-03         DO  1.8991179875  <NA> #> 2824   2035    3F CC104 2022 2022-03-03      DOSAT  4.2918283668  <NA> #> 2825   2035    3F CC104 2022 2022-03-03       NO23 -2.3538783874  <NA> #> 2826   2035    3F CC104 2022 2022-03-03      SALIN  0.1655144385  <NA> #> 2827   2035    3F CC104 2022 2022-03-03        TKN -0.4307829161  <NA> #> 2828   2035    3F CC104 2022 2022-03-03         TN -0.2943710606     + #> 2829   2035    3F CC104 2022 2022-03-03         TP -0.9416085399  <NA> #> 2830   2035    3F CC104 2022 2022-03-03        TSS  1.3862943611     I #> 2831   2035    3F CC104 2022 2022-03-03       TURB  2.2407096893     A #> 2832   2035    3F CC104 2022 2022-05-23      CHLAC  3.6109179126  <NA> #> 2833   2035    3F CC104 2022 2022-05-23      COLOR  4.1431347264     A #> 2834   2035    3F CC104 2022 2022-05-23       COND  9.7291936874  <NA> #> 2835   2035    3F CC104 2022 2022-05-23         DO  1.3987168811  <NA> #> 2836   2035    3F CC104 2022 2022-05-23      DOSAT  4.0217738694  <NA> #> 2837   2035    3F CC104 2022 2022-05-23       NO23 -3.1941832123  <NA> #> 2838   2035    3F CC104 2022 2022-05-23      SALIN  2.2854389342  <NA> #> 2839   2035    3F CC104 2022 2022-05-23        TKN  0.0953101798  <NA> #> 2840   2035    3F CC104 2022 2022-05-23         TN  0.1319050709     + #> 2841   2035    3F CC104 2022 2022-05-23         TP -0.3566749439  <NA> #> 2842   2035    3F CC104 2022 2022-05-23        TSS  1.9459101491     I #> 2843   2035    3F CC104 2022 2022-05-23       TURB  2.1633230257     A #> 2844   2035    3F CC104 2022 2022-06-27      CHLAC  1.2527629685     I #> 2845   2035    3F CC104 2022 2022-06-27      COLOR  4.0943445622     A #> 2846   2035    3F CC104 2022 2022-06-27       COND  6.9440872082  <NA> #> 2847   2035    3F CC104 2022 2022-06-27         DO  1.5706970841  <NA> #> 2848   2035    3F CC104 2022 2022-06-27      DOSAT  4.0724397268  <NA> #> 2849   2035    3F CC104 2022 2022-06-27       NO23 -1.5606477483  <NA> #> 2850   2035    3F CC104 2022 2022-06-27      SALIN -0.6733445533  <NA> #> 2851   2035    3F CC104 2022 2022-06-27        TKN  0.0953101798  <NA> #> 2852   2035    3F CC104 2022 2022-06-27         TN  0.2700271372     + #> 2853   2035    3F CC104 2022 2022-06-27         TP -0.3424903089  <NA> #> 2854   2035    3F CC104 2022 2022-06-27        TSS  2.3978952728  <NA> #> 2855   2035    3F CC104 2022 2022-06-27       TURB  2.7080502011  <NA> #> 2856   2035    3F CC104 2023 2023-01-09      CHLAC  2.2512917986  <NA> #> 2857   2035    3F CC104 2023 2023-01-09       COND  6.5666724298  <NA> #> 2858   2035    3F CC104 2023 2023-01-09         DO  1.7647307968  <NA> #> 2859   2035    3F CC104 2023 2023-01-09      DOSAT  4.1239033645  <NA> #> 2860   2035    3F CC104 2023 2023-01-09       NO23 -1.6094379124  <NA> #> 2861   2035    3F CC104 2023 2023-01-09      SALIN -1.0498221245  <NA> #> 2862   2035    3F CC104 2023 2023-01-09        TKN -0.2613647641  <NA> #> 2863   2035    3F CC104 2023 2023-01-09         TN -0.0304592075     + #> 2864   2035    3F CC104 2023 2023-01-09         TP -0.5621189182  <NA> #> 2865   2035    3F CC104 2023 2023-01-09        TSS  1.3862943611     I #> 2866   2035    3F CC104 2023 2023-01-09       TURB  2.5649493575  <NA> #> 2867   2035    3F CC104 2023 2023-03-14      CHLAC  2.8332133441  <NA> #> 2868   2035    3F CC104 2023 2023-03-14       COND  8.7237194369  <NA> #> 2869   2035    3F CC104 2023 2023-03-14         DO  1.0818051704  <NA> #> 2870   2035    3F CC104 2023 2023-03-14      DOSAT  3.5553480615  <NA> #> 2871   2035    3F CC104 2023 2023-03-14       NO23 -2.7646205526  <NA> #> 2872   2035    3F CC104 2023 2023-03-14      SALIN  1.2089603458  <NA> #> 2873   2035    3F CC104 2023 2023-03-14        TKN -0.1392620673  <NA> #> 2874   2035    3F CC104 2023 2023-03-14         TN -0.0693500781     + #> 2875   2035    3F CC104 2023 2023-03-14         TP -0.6733445533  <NA> #> 2876   2035    3F CC104 2023 2023-03-14        TSS  1.7917594692     I #> 2877   2035    3F CC104 2023 2023-03-14       TURB  2.0918640617  <NA> #> 2878   2035    3F CC104 2023 2023-05-10      CHLAC  4.2626798770  <NA> #> 2879   2035    3F CC104 2023 2023-05-10       COND  9.5445958677  <NA> #> 2880   2035    3F CC104 2023 2023-05-10         DO  0.7371640660  <NA> #> 2881   2035    3F CC104 2023 2023-05-10      DOSAT  3.2809112158  <NA> #> 2882   2035    3F CC104 2023 2023-05-10       NO23 -4.1351665567  <NA> #> 2883   2035    3F CC104 2023 2023-05-10      SALIN  2.0881534823  <NA> #> 2884   2035    3F CC104 2023 2023-05-10        TKN  0.1823215568  <NA> #> 2885   2035    3F CC104 2023 2023-05-10         TN  0.1955667835     + #> 2886   2035    3F CC104 2023 2023-05-10         TP -0.4155154440  <NA> #> 2887   2035    3F CC104 2023 2023-05-10        TSS  1.9459101491     I #> 2888   2035    3F CC104 2023 2023-05-10       TURB  2.0541237337  <NA> #> 2889   2035    3F CC104 2022 2022-01-24       COND  9.4453334396  <NA> #> 2890   2035    3F CC104 2022 2022-01-24         DO  2.3832429960  <NA> #> 2891   2035    3F CC104 2022 2022-01-24      DOSAT  4.7949637576  <NA> #> 2892   2035    3F CC104 2022 2022-01-24      SALIN  1.9865035460  <NA> #> 2893   2035    3F CC104 2022 2022-03-03       COND  8.9523465432  <NA> #> 2894   2035    3F CC104 2022 2022-03-03         DO  1.7544036827  <NA> #> 2895   2035    3F CC104 2022 2022-03-03      DOSAT  4.2224445648  <NA> #> 2896   2035    3F CC104 2022 2022-03-03      SALIN  1.4770487244  <NA> #> 2897   2035    3F CC104 2022 2022-05-23       COND  9.9213274707  <NA> #> 2898   2035    3F CC104 2022 2022-05-23         DO  1.2383742310  <NA> #> 2899   2035    3F CC104 2022 2022-05-23      DOSAT  3.8877303129  <NA> #> 2900   2035    3F CC104 2022 2022-05-23      SALIN  2.4923786646  <NA> #> 2901   2035    3F CC104 2022 2022-06-27       COND  7.7948231522  <NA> #> 2902   2035    3F CC104 2022 2022-06-27         DO  1.3660916538  <NA> #> 2903   2035    3F CC104 2022 2022-06-27      DOSAT  3.9019726696  <NA> #> 2904   2035    3F CC104 2022 2022-06-27      SALIN  0.2151113796  <NA> #> 2905   2035    3F CC104 2023 2023-01-09       COND  6.5042881735  <NA> #> 2906   2035    3F CC104 2023 2023-01-09         DO  1.9629077254  <NA> #> 2907   2035    3F CC104 2023 2023-01-09      DOSAT  4.3346729383  <NA> #> 2908   2035    3F CC104 2023 2023-01-09      SALIN -1.1086626245  <NA> #> 2909   2035    3F CC104 2023 2023-03-14       COND  9.1129480260  <NA> #> 2910   2035    3F CC104 2023 2023-03-14         DO  1.4134230285  <NA> #> 2911   2035    3F CC104 2023 2023-03-14      DOSAT  3.9100210028  <NA> #> 2912   2035    3F CC104 2023 2023-03-14      SALIN  1.6253112616  <NA> #> 2913   2035    3F CC104 2023 2023-05-10       COND  9.6875057942  <NA> #> 2914   2035    3F CC104 2023 2023-05-10         DO  1.1216775616  <NA> #> 2915   2035    3F CC104 2023 2023-05-10      DOSAT  3.6913763343  <NA> #> 2916   2035    3F CC104 2023 2023-05-10      SALIN  2.2417729536  <NA> #> 2917   2035    3F CC104 2022 2022-01-24       COND  8.4487001950  <NA> #> 2918   2035    3F CC104 2022 2022-01-24         DO  2.1447610078  <NA> #> 2919   2035    3F CC104 2022 2022-01-24      DOSAT  4.4624538838  <NA> #> 2920   2035    3F CC104 2022 2022-01-24      SALIN  0.9202827531  <NA> #> 2921   2035    3F CC104 2022 2022-03-03       COND  9.6867608690  <NA> #> 2922   2035    3F CC104 2022 2022-03-03         DO  1.4516138272  <NA> #> 2923   2035    3F CC104 2022 2022-03-03      DOSAT  3.9608131696  <NA> #> 2924   2035    3F CC104 2022 2022-03-03      SALIN  2.2449559802  <NA> #> 2925   2035    3F CC104 2022 2022-05-23       COND 10.0031066176  <NA> #> 2926   2035    3F CC104 2022 2022-05-23         DO  1.0986122887  <NA> #> 2927   2035    3F CC104 2022 2022-05-23      DOSAT  3.7518542533  <NA> #> 2928   2035    3F CC104 2022 2022-05-23      SALIN  2.9019708937  <NA> #> 2929   2035    3F CC104 2022 2022-06-27       COND  7.9745328441  <NA> #> 2930   2035    3F CC104 2022 2022-06-27         DO  1.6544112781  <NA> #> 2931   2035    3F CC104 2022 2022-06-27      DOSAT  4.2150861799  <NA> #> 2932   2035    3F CC104 2022 2022-06-27      SALIN  0.4054651081  <NA> #> 2933   2035    3F CC104 2023 2023-01-09       COND  7.0958932211  <NA> #> 2934   2035    3F CC104 2023 2023-01-09         DO  2.1575593209  <NA> #> 2935   2035    3F CC104 2023 2023-01-09      DOSAT  4.5464811896  <NA> #> 2936   2035    3F CC104 2023 2023-01-09      SALIN -0.5108256238  <NA> #> 2937   2035    3F CC104 2023 2023-03-14       COND  9.4841009891  <NA> #> 2938   2035    3F CC104 2023 2023-03-14         DO  0.9820784724  <NA> #> 2939   2035    3F CC104 2023 2023-03-14      DOSAT  3.5292973843  <NA> #> 2940   2035    3F CC104 2023 2023-03-14      SALIN  2.0215475633  <NA> #> 2941   2035    3F CC104 2023 2023-05-10       COND  9.8215722593  <NA> #> 2942   2035    3F CC104 2023 2023-05-10         DO  1.3660916538  <NA> #> 2943   2035    3F CC104 2023 2023-05-10      DOSAT  3.9627161197  <NA> #> 2944   2035    3F CC104 2023 2023-05-10      SALIN  2.3860067011  <NA> #> 2945   2035    3F CC104 2014 2014-05-28       COND  7.0817085861  <NA> #> 2946   2035    3F CC104 2014 2014-05-28         DO  1.5560371357  <NA> #> 2947   2035    3F CC104 2014 2014-05-28      DOSAT  4.0145795938     + #> 2948   2035    3F CC104 2014 2014-05-28      SALIN -0.5276327421  <NA> #> 2949   2035    3F CC104 2014 2014-10-02       COND  5.9506425526  <NA> #> 2950   2035    3F CC104 2014 2014-10-02         DO  1.6770965609  <NA> #> 2951   2035    3F CC104 2014 2014-10-02      DOSAT  4.2061840440     + #> 2952   2035    3F CC104 2014 2014-10-02      SALIN -1.7147984281  <NA> #> 2953   2035    3F CC104 2016 2016-06-02       COND  6.8068293604  <NA> #> 2954   2035    3F CC104 2016 2016-06-02         DO  1.3837912309  <NA> #> 2955   2035    3F CC104 2016 2016-06-02      DOSAT  3.8501476017     + #> 2956   2035    3F CC104 2016 2016-06-02      SALIN -0.8209805521  <NA> #> 2957   2035    3F CC104 2016 2016-09-21       COND  6.3664704477  <NA> #> 2958   2035    3F CC104 2016 2016-09-21         DO  1.6389967147  <NA> #> 2959   2035    3F CC104 2016 2016-09-21      DOSAT  4.1697612015     + #> 2960   2035    3F CC104 2016 2016-09-21      SALIN -1.2729656758  <NA> #> 2961   2035    3F CC104 2017 2017-05-09       COND  6.9791452751  <NA> #> 2962   2035    3F CC104 2017 2017-05-09         DO  1.4134230285  <NA> #> 2963   2035    3F CC104 2017 2017-05-09      DOSAT  3.8220982979     + #> 2964   2035    3F CC104 2017 2017-05-09      SALIN -0.6348782724  <NA> #> 2965   2035    3F CC104 2017 2017-09-27       COND  6.1654178542  <NA> #> 2966   2035    3F CC104 2017 2017-09-27         DO  1.6937790609  <NA> #> 2967   2035    3F CC104 2017 2017-09-27      DOSAT  4.2195077052     + #> 2968   2035    3F CC104 2017 2017-09-27      SALIN -1.4696759701  <NA> #> 2969   2035    3F CC104 2018 2018-06-04       COND  6.2672005485  <NA> #> 2970   2035    3F CC104 2018 2018-06-04         DO  1.6808279085  <NA> #> 2971   2035    3F CC104 2018 2018-06-04      DOSAT  4.2209772132     + #> 2972   2035    3F CC104 2018 2018-06-04      SALIN -1.3862943611  <NA> #> 2973   2035    3F CC104 2018 2018-09-12       COND  6.2265366693  <NA> #> 2974   2035    3F CC104 2018 2018-09-12         DO  1.7749523509  <NA> #> 2975   2035    3F CC104 2018 2018-09-12      DOSAT  4.3040650932     + #> 2976   2035    3F CC104 2018 2018-09-12      SALIN -1.4271163556  <NA> #> 2977   2045    3M  CC15 2018 2018-03-07      CHLAC  2.2617630985  <NA> #> 2978   2045    3M  CC15 2018 2018-03-07       COND 10.0150289273  <NA> #> 2979   2045    3M  CC15 2018 2018-03-07         DO  2.0281482473  <NA> #> 2980   2045    3M  CC15 2018 2018-03-07      DOSAT  4.5475410732  <NA> #> 2981   2045    3M  CC15 2018 2018-03-07       NO23 -5.5214609179     U #> 2982   2045    3M  CC15 2018 2018-03-07      SALIN  2.6595599919     + #> 2983   2045    3M  CC15 2018 2018-03-07        TKN -0.1743533871  <NA> #> 2984   2045    3M  CC15 2018 2018-03-07         TN -0.1719752647     + #> 2985   2045    3M  CC15 2018 2018-03-07         TP -1.8325814637  <NA> #> 2986   2045    3M  CC15 2018 2018-03-07        TSS  1.0986122887     U #> 2987   2045    3M  CC15 2018 2018-03-07       TURB  1.2809338455  <NA> #> 2988   2045    3M  CC15 2018 2018-04-09      CHLAC  1.8870696490  <NA> #> 2989   2045    3M  CC15 2018 2018-04-09       COND 10.4012279368  <NA> #> 2990   2045    3M  CC15 2018 2018-04-09         DO  1.7227665977  <NA> #> 2991   2045    3M  CC15 2018 2018-04-09      DOSAT  4.3438054219  <NA> #> 2992   2045    3M  CC15 2018 2018-04-09       NO23 -5.5214609179     I #> 2993   2045    3M  CC15 2018 2018-04-09      SALIN  3.0017143452     + #> 2994   2045    3M  CC15 2018 2018-04-09        TKN -0.2357223335  <NA> #> 2995   2045    3M  CC15 2018 2018-04-09         TN -0.2306718177     + #> 2996   2045    3M  CC15 2018 2018-04-09         TP -1.5606477483  <NA> #> 2997   2045    3M  CC15 2018 2018-04-09        TSS  2.7080502011  <NA> #> 2998   2045    3M  CC15 2018 2018-04-09       TURB  1.8718021769     A #> 2999   2045    3M  CC15 2018 2018-05-24      CHLAC  2.3978952728  <NA> #> 3000   2045    3M  CC15 2018 2018-05-24       COND  9.3056505518  <NA> #> 3001   2045    3M  CC15 2018 2018-05-24         DO  1.9198594719  <NA> #> 3002   2045    3M  CC15 2018 2018-05-24      DOSAT  4.4589876758  <NA> #> 3003   2045    3M  CC15 2018 2018-05-24       NO23 -3.3524072175  <NA> #> 3004   2045    3M  CC15 2018 2018-05-24      SALIN  1.7833912196     + #> 3005   2045    3M  CC15 2018 2018-05-24        TKN -0.1392620673  <NA> #> 3006   2045    3M  CC15 2018 2018-05-24         TN -0.0998203353     + #> 3007   2045    3M  CC15 2018 2018-05-24         TP -1.6094379124  <NA> #> 3008   2045    3M  CC15 2018 2018-05-24        TSS  1.7917594692     I #> 3009   2045    3M  CC15 2018 2018-05-24       TURB  1.3350010667  <NA> #> 3010   2045    3M  CC15 2018 2018-05-24      SALIN  1.8991179875     + #> 3011   2045    3M  CC15 2018 2018-05-24       COND  9.4091912307  <NA> #> 3012   2045    3M  CC15 2018 2018-05-24         DO  1.7833912196  <NA> #> 3013   2045    3M  CC15 2018 2018-05-24      DOSAT  4.3630986248  <NA> #> 3014   2045    3M  CC15 2018 2018-05-24       COND  9.3056505518  <NA> #> 3015   2045    3M  CC15 2018 2018-05-24         DO  1.9198594719  <NA> #> 3016   2045    3M  CC15 2018 2018-05-24      DOSAT  4.4589876758  <NA> #> 3017   2045    3M  CC15 2018 2018-05-24      SALIN  1.7833912196     + #> 3018   2045    3M  CC15 2018 2018-07-23      CHLAC  2.0149030205  <NA> #> 3019   2045    3M  CC15 2018 2018-07-23       COND  6.5087691370  <NA> #> 3020   2045    3M  CC15 2018 2018-07-23         DO  1.7800242130  <NA> #> 3021   2045    3M  CC15 2018 2018-07-23      DOSAT  4.3567088267  <NA> #> 3022   2045    3M  CC15 2018 2018-07-23       NO23 -1.9661128564  <NA> #> 3023   2045    3M  CC15 2018 2018-07-23      SALIN -1.1394342832  <NA> #> 3024   2045    3M  CC15 2018 2018-07-23        TKN  0.1823215568  <NA> #> 3025   2045    3M  CC15 2018 2018-07-23         TN  0.2926696140     + #> 3026   2045    3M  CC15 2018 2018-07-23         TP -1.1394342832  <NA> #> 3027   2045    3M  CC15 2018 2018-07-23        TSS  1.3862943611     I #> 3028   2045    3M  CC15 2018 2018-07-23       TURB  1.3083328197  <NA> #> 3029   2045    3M  CC15 2018 2018-08-21      CHLAC  2.0794415417  <NA> #> 3030   2045    3M  CC15 2018 2018-08-21       COND  6.4393503711  <NA> #> 3031   2045    3M  CC15 2018 2018-08-21         DO  1.6601310267  <NA> #> 3032   2045    3M  CC15 2018 2018-08-21      DOSAT  4.2341065046  <NA> #> 3033   2045    3M  CC15 2018 2018-08-21       NO23 -2.6736487744  <NA> #> 3034   2045    3M  CC15 2018 2018-08-21      SALIN -1.2039728043  <NA> #> 3035   2045    3M  CC15 2018 2018-08-21        TKN  0.0953101798  <NA> #> 3036   2045    3M  CC15 2018 2018-08-21         TN  0.1561486825     + #> 3037   2045    3M  CC15 2018 2018-08-21         TP -1.2378743560  <NA> #> 3038   2045    3M  CC15 2018 2018-08-21        TSS  1.0986122887     I #> 3039   2045    3M  CC15 2018 2018-08-21       TURB  1.0986122887  <NA> #> 3040   2045    3M  CC15 2018 2018-08-21       COND  6.4264884575  <NA> #> 3041   2045    3M  CC15 2018 2018-08-21         DO  1.6114359151  <NA> #> 3042   2045    3M  CC15 2018 2018-08-21      DOSAT  4.1774594689  <NA> #> 3043   2045    3M  CC15 2018 2018-08-21      SALIN -1.2039728043  <NA> #> 3044   2045    3M  CC15 2019 2019-02-07      CHLAC  3.2188758249     A #> 3045   2045    3M  CC15 2019 2019-02-07       COND  8.6916505732  <NA> #> 3046   2045    3M  CC15 2019 2019-02-07       NO23 -5.1159958098     I #> 3047   2045    3M  CC15 2019 2019-02-07      SALIN  1.1755733298  <NA> #> 3048   2045    3M  CC15 2019 2019-02-07        TKN  0.0953101798  <NA> #> 3049   2045    3M  CC15 2019 2019-02-07         TN  0.0989399479     + #> 3050   2045    3M  CC15 2019 2019-02-07         TP -1.6607312068  <NA> #> 3051   2045    3M  CC15 2019 2019-02-07        TSS  2.3025850930     I #> 3052   2045    3M  CC15 2019 2019-02-07       TURB  2.0281482473  <NA> #> 3053   2045    3M  CC15 2019 2019-03-13      CHLAC  1.8870696490  <NA> #> 3054   2045    3M  CC15 2019 2019-03-13       COND  9.4304392931  <NA> #> 3055   2045    3M  CC15 2019 2019-03-13         DO  1.8961194846  <NA> #> 3056   2045    3M  CC15 2019 2019-03-13      DOSAT  4.4188406078  <NA> #> 3057   2045    3M  CC15 2019 2019-03-13       NO23 -5.2983173665     I #> 3058   2045    3M  CC15 2019 2019-03-13      SALIN  1.9657127764  <NA> #> 3059   2045    3M  CC15 2019 2019-03-13        TKN -0.1625189295  <NA> #> 3060   2045    3M  CC15 2019 2019-03-13         TN -0.1578240852     + #> 3061   2045    3M  CC15 2019 2019-03-13         TP -1.8325814637  <NA> #> 3062   2045    3M  CC15 2019 2019-03-13        TSS  2.0794415417     I #> 3063   2045    3M  CC15 2019 2019-03-13       TURB  1.5892352051  <NA> #> 3064   2045    3M  CC15 2019 2019-04-23      CHLAC  1.7749523509  <NA> #> 3065   2045    3M  CC15 2019 2019-04-23       COND  9.9110588180  <NA> #> 3066   2045    3M  CC15 2019 2019-04-23         DO  1.8562979904  <NA> #> 3067   2045    3M  CC15 2019 2019-04-23      DOSAT  4.3845235149  <NA> #> 3068   2045    3M  CC15 2019 2019-04-23       NO23 -5.5214609179     U #> 3069   2045    3M  CC15 2019 2019-04-23      SALIN  2.4882344399  <NA> #> 3070   2045    3M  CC15 2019 2019-04-23        TKN -0.2744368457  <NA> #> 3071   2045    3M  CC15 2019 2019-04-23         TN -0.2718087233     + #> 3072   2045    3M  CC15 2019 2019-04-23         TP -1.6607312068  <NA> #> 3073   2045    3M  CC15 2019 2019-04-23        TSS  2.0794415417     I #> 3074   2045    3M  CC15 2019 2019-04-23       TURB  1.4586150227  <NA> #> 3075   2045    3M  CC15 2019 2019-07-22      CHLAC  2.4849066498  <NA> #> 3076   2045    3M  CC15 2019 2019-07-22       COND  8.5083542427  <NA> #> 3077   2045    3M  CC15 2019 2019-07-22         DO  1.7227665977  <NA> #> 3078   2045    3M  CC15 2019 2019-07-22      DOSAT  4.3174881135  <NA> #> 3079   2045    3M  CC15 2019 2019-07-22       NO23 -3.5065578973  <NA> #> 3080   2045    3M  CC15 2019 2019-07-22      SALIN  0.9707789172  <NA> #> 3081   2045    3M  CC15 2019 2019-07-22        TKN -0.0512932944  <NA> #> 3082   2045    3M  CC15 2019 2019-07-22         TN -0.0202027073     + #> 3083   2045    3M  CC15 2019 2019-07-22         TP -1.1086626245  <NA> #> 3084   2045    3M  CC15 2019 2019-07-22        TSS  1.6094379124     I #> 3085   2045    3M  CC15 2019 2019-07-22       TURB  1.3862943611  <NA> #> 3086   2045    3M  CC15 2019 2019-09-04       COND  7.2896105215  <NA> #> 3087   2045    3M  CC15 2019 2019-09-04         DO  1.6213664833  <NA> #> 3088   2045    3M  CC15 2019 2019-09-04      DOSAT  4.2061840440  <NA> #> 3089   2045    3M  CC15 2019 2019-09-04       NO23 -2.4191189092  <NA> #> 3090   2045    3M  CC15 2019 2019-09-04      SALIN -0.3147107448  <NA> #> 3091   2045    3M  CC15 2019 2019-09-04        TKN  0.1823215568  <NA> #> 3092   2045    3M  CC15 2019 2019-09-04         TN  0.2538667240     + #> 3093   2045    3M  CC15 2019 2019-09-04         TP -0.9675840263  <NA> #> 3094   2045    3M  CC15 2019 2019-09-04        TSS  1.0986122887     I #> 3095   2045    3M  CC15 2019 2019-09-04       TURB  1.0986122887  <NA> #> 3096   2045    3M  CC15 2020 2020-02-18      CHLAC  2.7080502011  <NA> #> 3097   2045    3M  CC15 2020 2020-02-18       COND 10.0136863448  <NA> #> 3098   2045    3M  CC15 2020 2020-02-18         DO  1.9358598132  <NA> #> 3099   2045    3M  CC15 2020 2020-02-18      DOSAT  4.5272086445  <NA> #> 3100   2045    3M  CC15 2020 2020-02-18       NO23 -4.8283137373     I #> 3101   2045    3M  CC15 2020 2020-02-18      SALIN  2.5967461315  <NA> #> 3102   2045    3M  CC15 2020 2020-02-18        TKN -0.1165338163  <NA> #> 3103   2045    3M  CC15 2020 2020-02-18         TN -0.1120495038     + #> 3104   2045    3M  CC15 2020 2020-02-18         TP -1.6094379124  <NA> #> 3105   2045    3M  CC15 2020 2020-02-18        TSS  2.7080502011  <NA> #> 3106   2045    3M  CC15 2020 2020-02-18       TURB  1.7227665977  <NA> #> 3107   2045    3M  CC15 2020 2020-02-18       COND 10.0120728629  <NA> #> 3108   2045    3M  CC15 2020 2020-02-18         DO  1.9227877316  <NA> #> 3109   2045    3M  CC15 2020 2020-02-18      DOSAT  4.5086592856  <NA> #> 3110   2045    3M  CC15 2020 2020-02-18      SALIN  2.5952547070  <NA> #> 3111   2045    3M  CC15 2020 2020-06-09      CHLAC  2.4849066498  <NA> #> 3112   2045    3M  CC15 2020 2020-06-09       COND  9.2513863414  <NA> #> 3113   2045    3M  CC15 2020 2020-06-09         DO  1.9315214116  <NA> #> 3114   2045    3M  CC15 2020 2020-06-09      DOSAT  4.5239601306  <NA> #> 3115   2045    3M  CC15 2020 2020-06-09       NO23 -3.3813947544  <NA> #> 3116   2045    3M  CC15 2020 2020-06-09      SALIN  1.7664416612  <NA> #> 3117   2045    3M  CC15 2020 2020-06-09        TKN -0.0304592075  <NA> #> 3118   2045    3M  CC15 2020 2020-06-09         TN  0.0039920213     + #> 3119   2045    3M  CC15 2020 2020-06-09         TP -1.4696759701  <NA> #> 3120   2045    3M  CC15 2020 2020-06-09        TSS  1.0986122887     I #> 3121   2045    3M  CC15 2020 2020-06-09       TURB  0.9162907319  <NA> #> 3122   2045    3M  CC15 2020 2020-06-09       COND  9.5815590414  <NA> #> 3123   2045    3M  CC15 2020 2020-06-09         DO  1.6544112781  <NA> #> 3124   2045    3M  CC15 2020 2020-06-09      DOSAT  4.2076732475  <NA> #> 3125   2045    3M  CC15 2020 2020-06-09      SALIN  2.1552445051  <NA> #> 3126   2045    3M  CC15 2020 2020-08-10       COND  9.2688922589  <NA> #> 3127   2045    3M  CC15 2020 2020-08-10         DO  1.6370530795  <NA> #> 3128   2045    3M  CC15 2020 2020-08-10      DOSAT  4.2710950740  <NA> #> 3129   2045    3M  CC15 2020 2020-08-10      SALIN -1.4567168254  <NA> #> 3130   2045    3M  CC15 2020 2020-08-10       COND  9.4812068515  <NA> #> 3131   2045    3M  CC15 2020 2020-08-10         DO  1.4398351280  <NA> #> 3132   2045    3M  CC15 2020 2020-08-10      DOSAT  4.0758410907  <NA> #> 3133   2045    3M  CC15 2020 2020-08-10      SALIN  0.2207406667  <NA> #> 3134   2045    3M  CC15 2020 2020-09-22      CHLAC  2.2192034841  <NA> #> 3135   2045    3M  CC15 2020 2020-09-22       COND  6.5750758406  <NA> #> 3136   2045    3M  CC15 2020 2020-09-22         DO  1.7934247485  <NA> #> 3137   2045    3M  CC15 2020 2020-09-22      DOSAT  4.3359826962  <NA> #> 3138   2045    3M  CC15 2020 2020-09-22       NO23 -2.7968814148  <NA> #> 3139   2045    3M  CC15 2020 2020-09-22      SALIN -1.0498221245  <NA> #> 3140   2045    3M  CC15 2020 2020-09-22        TKN  0.2623642645  <NA> #> 3141   2045    3M  CC15 2020 2020-09-22         TN  0.3082197237     + #> 3142   2045    3M  CC15 2020 2020-09-22         TP -0.9942522733  <NA> #> 3143   2045    3M  CC15 2020 2020-09-22        TSS  1.3862943611     I #> 3144   2045    3M  CC15 2020 2020-09-22       TURB  1.2809338455  <NA> #> 3145   2045    3M  CC15 2020 2020-10-20      CHLAC  3.0445224377  <NA> #> 3146   2045    3M  CC15 2020 2020-10-20       COND  8.3209349689  <NA> #> 3147   2045    3M  CC15 2020 2020-10-20         DO  1.7119945008  <NA> #> 3148   2045    3M  CC15 2020 2020-10-20      DOSAT  4.2640873368  <NA> #> 3149   2045    3M  CC15 2020 2020-10-20       NO23 -2.5010360317  <NA> #> 3150   2045    3M  CC15 2020 2020-10-20      SALIN  0.7747271676  <NA> #> 3151   2045    3M  CC15 2020 2020-10-20        TKN  0.2623642645  <NA> #> 3152   2045    3M  CC15 2020 2020-10-20         TN  0.3235317253     + #> 3153   2045    3M  CC15 2020 2020-10-20         TP -0.9942522733  <NA> #> 3154   2045    3M  CC15 2020 2020-10-20        TSS  1.6094379124     I #> 3155   2045    3M  CC15 2020 2020-10-20       TURB  1.2809338455  <NA> #> 3156   2045    3M  CC15 2020 2020-12-14      CHLAC  2.6390573296  <NA> #> 3157   2045    3M  CC15 2020 2020-12-14       COND  9.2314166976  <NA> #> 3158   2045    3M  CC15 2020 2020-12-14         DO  2.0930978681  <NA> #> 3159   2045    3M  CC15 2020 2020-12-14      DOSAT  4.5695430083  <NA> #> 3160   2045    3M  CC15 2020 2020-12-14       NO23 -4.9618451299     I #> 3161   2045    3M  CC15 2020 2020-12-14      SALIN  1.7526720805  <NA> #> 3162   2045    3M  CC15 2020 2020-12-14        TKN  0.0000000000  <NA> #> 3163   2045    3M  CC15 2020 2020-12-14         TN  0.0039920213     + #> 3164   2045    3M  CC15 2020 2020-12-14         TP -1.4696759701  <NA> #> 3165   2045    3M  CC15 2020 2020-12-14        TSS  1.6094379124     I #> 3166   2045    3M  CC15 2020 2020-12-14       TURB  1.3609765531     A #> 3167   2045    3M  CC15 2021 2021-02-03      CHLAC  1.7404661748  <NA> #> 3168   2045    3M  CC15 2021 2021-02-03       COND  9.8506140629  <NA> #> 3169   2045    3M  CC15 2021 2021-02-03         DO  2.1424163408  <NA> #> 3170   2045    3M  CC15 2021 2021-02-03      DOSAT  4.5528237056  <NA> #> 3171   2045    3M  CC15 2021 2021-02-03       NO23 -5.5214609179     U #> 3172   2045    3M  CC15 2021 2021-02-03      SALIN  2.4248027257  <NA> #> 3173   2045    3M  CC15 2021 2021-02-03        TKN -0.3424903089  <NA> #> 3174   2045    3M  CC15 2021 2021-02-03         TN -0.3396773676     + #> 3175   2045    3M  CC15 2021 2021-02-03         TP -1.9661128564  <NA> #> 3176   2045    3M  CC15 2021 2021-02-03        TSS  1.3862943611     I #> 3177   2045    3M  CC15 2021 2021-02-03       TURB  1.0296194172  <NA> #> 3178   2045    3M  CC15 2021 2021-03-09      CHLAC  2.4849066498  <NA> #> 3179   2045    3M  CC15 2021 2021-03-09       COND  9.8787336881  <NA> #> 3180   2045    3M  CC15 2021 2021-03-09         DO  2.1690537004  <NA> #> 3181   2045    3M  CC15 2021 2021-03-09      DOSAT  4.6510991179  <NA> #> 3182   2045    3M  CC15 2021 2021-03-09       NO23 -5.5214609179     I #> 3183   2045    3M  CC15 2021 2021-03-09      SALIN  2.4544474423  <NA> #> 3184   2045    3M  CC15 2021 2021-03-09        TKN  0.0000000000  <NA> #> 3185   2045    3M  CC15 2021 2021-03-09         TN  0.0039920213     + #> 3186   2045    3M  CC15 2021 2021-03-09         TP -1.4696759701  <NA> #> 3187   2045    3M  CC15 2021 2021-03-09        TSS  3.2958368660  <NA> #> 3188   2045    3M  CC15 2021 2021-03-09       TURB  2.3978952728     A #> 3189   2045    3M  CC15 2021 2021-05-05      CHLAC  1.8082887712  <NA> #> 3190   2045    3M  CC15 2021 2021-05-05       COND 10.2487071336  <NA> #> 3191   2045    3M  CC15 2021 2021-05-05         DO  1.8082887712  <NA> #> 3192   2045    3M  CC15 2021 2021-05-05      DOSAT  4.4986979415  <NA> #> 3193   2045    3M  CC15 2021 2021-05-05       NO23 -5.5214609179     U #> 3194   2045    3M  CC15 2021 2021-05-05      SALIN  2.8489708922  <NA> #> 3195   2045    3M  CC15 2021 2021-05-05        TKN -0.2231435513  <NA> #> 3196   2045    3M  CC15 2021 2021-05-05         TN -0.2206466711     + #> 3197   2045    3M  CC15 2021 2021-05-05         TP -1.6094379124  <NA> #> 3198   2045    3M  CC15 2021 2021-05-05        TSS  1.9459101491     I #> 3199   2045    3M  CC15 2021 2021-05-05       TURB  1.3350010667  <NA> #> 3200   2045    3M  CC15 2021 2021-06-03      CHLAC  1.8245492921  <NA> #> 3201   2045    3M  CC15 2021 2021-06-03       COND 10.3770473511  <NA> #> 3202   2045    3M  CC15 2021 2021-06-03         DO  1.7715567619  <NA> #> 3203   2045    3M  CC15 2021 2021-06-03      DOSAT  4.4331949212  <NA> #> 3204   2045    3M  CC15 2021 2021-06-03       NO23 -5.5214609179     U #> 3205   2045    3M  CC15 2021 2021-06-03      SALIN  2.9937302709  <NA> #> 3206   2045    3M  CC15 2021 2021-06-03        TKN -0.1743533871  <NA> #> 3207   2045    3M  CC15 2021 2021-06-03         TN -0.1719752647     + #> 3208   2045    3M  CC15 2021 2021-06-03         TP -1.5606477483  <NA> #> 3209   2045    3M  CC15 2021 2021-06-03        TSS  1.7917594692     I #> 3210   2045    3M  CC15 2021 2021-06-03       TURB  1.2237754316  <NA> #> 3211   2045    3M  CC15 2021 2021-07-01      CHLAC  2.1860512767  <NA> #> 3212   2045    3M  CC15 2021 2021-07-01       COND 10.1292277297  <NA> #> 3213   2045    3M  CC15 2021 2021-07-01         DO  1.7351891177  <NA> #> 3214   2045    3M  CC15 2021 2021-07-01      DOSAT  4.3541414312  <NA> #> 3215   2045    3M  CC15 2021 2021-07-01       NO23 -5.5214609179     U #> 3216   2045    3M  CC15 2021 2021-07-01      SALIN  2.7232671669  <NA> #> 3217   2045    3M  CC15 2021 2021-07-01        TKN -0.4155154440  <NA> #> 3218   2045    3M  CC15 2021 2021-07-01         TN -0.4124897230     + #> 3219   2045    3M  CC15 2021 2021-07-01         TP -1.5606477483  <NA> #> 3220   2045    3M  CC15 2021 2021-07-01        TSS  1.0986122887     U #> 3221   2045    3M  CC15 2021 2021-07-01       TURB  1.3083328197  <NA> #> 3222   2045    3M  CC15 2021 2021-07-29      CHLAC  1.5892352051  <NA> #> 3223   2045    3M  CC15 2021 2021-07-29       COND  7.4764723812  <NA> #> 3224   2045    3M  CC15 2021 2021-07-29         DO  1.4303112465  <NA> #> 3225   2045    3M  CC15 2021 2021-07-29      DOSAT  4.0145795938  <NA> #> 3226   2045    3M  CC15 2021 2021-07-29       NO23 -2.4769384801  <NA> #> 3227   2045    3M  CC15 2021 2021-07-29      SALIN -0.1165338163  <NA> #> 3228   2045    3M  CC15 2021 2021-07-29        TKN  0.3364722366  <NA> #> 3229   2045    3M  CC15 2021 2021-07-29         TN  0.3947411447     + #> 3230   2045    3M  CC15 2021 2021-07-29         TP -0.4780358009  <NA> #> 3231   2045    3M  CC15 2021 2021-07-29        TSS  1.7917594692     I #> 3232   2045    3M  CC15 2021 2021-07-29       TURB  1.6292405397  <NA> #> 3233   2045    3M  CC15 2021 2021-08-25      CHLAC  2.7725887222  <NA> #> 3234   2045    3M  CC15 2021 2021-08-25       COND  6.9107507880  <NA> #> 3235   2045    3M  CC15 2021 2021-08-25         DO  1.3376291891  <NA> #> 3236   2045    3M  CC15 2021 2021-08-25      DOSAT  3.9120230054  <NA> #> 3237   2045    3M  CC15 2021 2021-08-25       NO23 -2.9565115604  <NA> #> 3238   2045    3M  CC15 2021 2021-08-25      SALIN -0.7133498879  <NA> #> 3239   2045    3M  CC15 2021 2021-08-25        TKN  0.0953101798  <NA> #> 3240   2045    3M  CC15 2021 2021-08-25         TN  0.1414995623     + #> 3241   2045    3M  CC15 2021 2021-08-25         TP -0.8915981193  <NA> #> 3242   2045    3M  CC15 2021 2021-08-25        TSS  1.0986122887     I #> 3243   2045    3M  CC15 2021 2021-08-25       TURB  1.0647107370  <NA> #> 3244   2045    3M  CC15 2021 2021-09-23      CHLAC  2.2300144002  <NA> #> 3245   2045    3M  CC15 2021 2021-09-23       COND  6.2653012127  <NA> #> 3246   2045    3M  CC15 2021 2021-09-23         DO  1.4060969884  <NA> #> 3247   2045    3M  CC15 2021 2021-09-23      DOSAT  3.9550824949  <NA> #> 3248   2045    3M  CC15 2021 2021-09-23       NO23 -3.0365542681  <NA> #> 3249   2045    3M  CC15 2021 2021-09-23      SALIN -1.3862943611  <NA> #> 3250   2045    3M  CC15 2021 2021-09-23        TKN  0.0953101798  <NA> #> 3251   2045    3M  CC15 2021 2021-09-23         TN  0.1380212979     + #> 3252   2045    3M  CC15 2021 2021-09-23         TP -1.3093333200  <NA> #> 3253   2045    3M  CC15 2021 2021-09-23        TSS  1.3862943611     I #> 3254   2045    3M  CC15 2021 2021-09-23       TURB  1.2527629685  <NA> #> 3255   2045    3M  CC15 2021 2021-10-21      CHLAC  3.5263605246  <NA> #> 3256   2045    3M  CC15 2021 2021-10-21       COND  8.7135820054  <NA> #> 3257   2045    3M  CC15 2021 2021-10-21         DO  1.7732559977  <NA> #> 3258   2045    3M  CC15 2021 2021-10-21      DOSAT  4.2918283668  <NA> #> 3259   2045    3M  CC15 2021 2021-10-21       NO23 -2.9957322736  <NA> #> 3260   2045    3M  CC15 2021 2021-10-21      SALIN  1.1939224685  <NA> #> 3261   2045    3M  CC15 2021 2021-10-21        TKN  0.2623642645  <NA> #> 3262   2045    3M  CC15 2021 2021-10-21         TN  0.3001045925     + #> 3263   2045    3M  CC15 2021 2021-10-21         TP -1.1711829815  <NA> #> 3264   2045    3M  CC15 2021 2021-10-21        TSS  1.6094379124     I #> 3265   2045    3M  CC15 2021 2021-10-21       TURB  1.2809338455  <NA> #> 3266   2045    3M  CC15 2021 2021-11-22       COND  9.2692694395  <NA> #> 3267   2045    3M  CC15 2021 2021-11-22         DO  1.9516081702  <NA> #> 3268   2045    3M  CC15 2021 2021-11-22      DOSAT  4.4647580323  <NA> #> 3269   2045    3M  CC15 2021 2021-11-22       NO23 -4.7105307016     I #> 3270   2045    3M  CC15 2021 2021-11-22      SALIN  1.7917594692  <NA> #> 3271   2045    3M  CC15 2021 2021-11-22        TKN -0.1863295782  <NA> #> 3272   2045    3M  CC15 2021 2021-11-22         TN -0.1815218766     + #> 3273   2045    3M  CC15 2021 2021-11-22         TP -1.7147984281  <NA> #> 3274   2045    3M  CC15 2021 2021-11-22        TSS  1.0986122887     I #> 3275   2045    3M  CC15 2021 2021-11-22       TURB  0.9932517730  <NA> #> 3276   2045    3M  CC15 2022 2022-02-22      CHLAC  1.5040773968  <NA> #> 3277   2045    3M  CC15 2022 2022-02-22       COND 10.3013572215  <NA> #> 3278   2045    3M  CC15 2022 2022-02-22         DO  1.9169226122  <NA> #> 3279   2045    3M  CC15 2022 2022-02-22      DOSAT  4.4986979415  <NA> #> 3280   2045    3M  CC15 2022 2022-02-22       NO23 -5.5214609179     U #> 3281   2045    3M  CC15 2022 2022-02-22      SALIN  2.9139797717  <NA> #> 3282   2045    3M  CC15 2022 2022-02-22        TKN -0.3285040670  <NA> #> 3283   2045    3M  CC15 2022 2022-02-22         TN -0.3257301401     + #> 3284   2045    3M  CC15 2022 2022-02-22         TP -2.0402208285  <NA> #> 3285   2045    3M  CC15 2022 2022-02-22        TSS  2.3978952728  <NA> #> 3286   2045    3M  CC15 2022 2022-02-22       TURB  1.3083328197  <NA> #> 3287   2045    3M  CC15 2022 2022-04-20      CHLAC  0.4700036292     U #> 3288   2045    3M  CC15 2022 2022-04-20       COND 10.5349454823  <NA> #> 3289   2045    3M  CC15 2022 2022-04-20         DO  1.6919391339  <NA> #> 3290   2045    3M  CC15 2022 2022-04-20      DOSAT  4.2972854062  <NA> #> 3291   2045    3M  CC15 2022 2022-04-20       NO23 -5.5214609179     U #> 3292   2045    3M  CC15 2022 2022-04-20      SALIN  3.1722034167  <NA> #> 3293   2045    3M  CC15 2022 2022-04-20        TKN -0.1508228897  <NA> #> 3294   2045    3M  CC15 2022 2022-04-20         TN -0.1485000083     + #> 3295   2045    3M  CC15 2022 2022-04-20         TP -1.9661128564  <NA> #> 3296   2045    3M  CC15 2022 2022-04-20        TSS  2.5649493575  <NA> #> 3297   2045    3M  CC15 2022 2022-04-20       TURB  1.8082887712  <NA> #> 3298   2045    3M  CC15 2022 2022-06-07      CHLAC  1.5260563035  <NA> #> 3299   2045    3M  CC15 2022 2022-06-07       COND 10.2575891884  <NA> #> 3300   2045    3M  CC15 2022 2022-06-07         DO  1.7137979278  <NA> #> 3301   2045    3M  CC15 2022 2022-06-07      DOSAT  4.3870141762  <NA> #> 3302   2045    3M  CC15 2022 2022-06-07       NO23 -4.8283137373     I #> 3303   2045    3M  CC15 2022 2022-06-07      SALIN  2.8604851241  <NA> #> 3304   2045    3M  CC15 2022 2022-06-07        TKN -0.3710636814  <NA> #> 3305   2045    3M  CC15 2022 2022-06-07         TN -0.3652833185     + #> 3306   2045    3M  CC15 2022 2022-06-07         TP -1.5606477483  <NA> #> 3307   2045    3M  CC15 2022 2022-06-07        TSS  2.3025850930  <NA> #> 3308   2045    3M  CC15 2022 2022-06-07       TURB  0.9932517730  <NA> #> 3309   2045    3M  CC15 2022 2022-08-15      CHLAC  3.2188758249  <NA> #> 3310   2045    3M  CC15 2022 2022-08-15       COND  8.2671921859  <NA> #> 3311   2045    3M  CC15 2022 2022-08-15         DO  1.6094379124  <NA> #> 3312   2045    3M  CC15 2022 2022-08-15      DOSAT  4.2136079830  <NA> #> 3313   2045    3M  CC15 2022 2022-08-15       NO23 -4.7105307016     I #> 3314   2045    3M  CC15 2022 2022-08-15      SALIN  0.7129498079  <NA> #> 3315   2045    3M  CC15 2022 2022-08-15        TKN  0.0000000000  <NA> #> 3316   2045    3M  CC15 2022 2022-08-15         TN  0.0039920213     + #> 3317   2045    3M  CC15 2022 2022-08-15         TP -1.2378743560  <NA> #> 3318   2045    3M  CC15 2022 2022-08-15        TSS  1.3862943611     I #> 3319   2045    3M  CC15 2022 2022-08-15       TURB  1.0296194172  <NA> #> 3320   2045    3M  CC15 2022 2022-12-15      CHLAC  4.9416424226  <NA> #> 3321   2045    3M  CC15 2022 2022-12-15       COND  9.5450252980  <NA> #> 3322   2045    3M  CC15 2022 2022-12-15         DO  1.8531680974  <NA> #> 3323   2045    3M  CC15 2022 2022-12-15      DOSAT  4.3681812279  <NA> #> 3324   2045    3M  CC15 2022 2022-12-15       NO23 -5.5214609179     U #> 3325   2045    3M  CC15 2022 2022-12-15      SALIN  2.0881534823  <NA> #> 3326   2045    3M  CC15 2022 2022-12-15        TKN  0.5306282511  <NA> #> 3327   2045    3M  CC15 2022 2022-12-15         TN  0.5318040302     + #> 3328   2045    3M  CC15 2022 2022-12-15         TP -1.0788096614  <NA> #> 3329   2045    3M  CC15 2022 2022-12-15        TSS  2.8332133441  <NA> #> 3330   2045    3M  CC15 2022 2022-12-15       TURB  2.1400661635  <NA> #> 3331   2045    3M  CC15 2023 2023-01-11      CHLAC  2.1400661635  <NA> #> 3332   2045    3M  CC15 2023 2023-01-11       COND  9.5500929367  <NA> #> 3333   2045    3M  CC15 2023 2023-01-11         DO  1.9125010869  <NA> #> 3334   2045    3M  CC15 2023 2023-01-11      DOSAT  4.3630986248  <NA> #> 3335   2045    3M  CC15 2023 2023-01-11       NO23 -4.2686979494  <NA> #> 3336   2045    3M  CC15 2023 2023-01-11      SALIN  2.0992441690  <NA> #> 3337   2045    3M  CC15 2023 2023-01-11        TKN -0.2876820725  <NA> #> 3338   2045    3M  CC15 2023 2023-01-11         TN -0.2691874898     + #> 3339   2045    3M  CC15 2023 2023-01-11         TP -1.6607312068  <NA> #> 3340   2045    3M  CC15 2023 2023-01-11        TSS  1.7917594692     I #> 3341   2045    3M  CC15 2023 2023-01-11       TURB  0.8754687374  <NA> #> 3342   2045    3M  CC15 2023 2023-03-23      CHLAC  1.4109869737     I #> 3343   2045    3M  CC15 2023 2023-03-23       COND 10.2374208545  <NA> #> 3344   2045    3M  CC15 2023 2023-03-23         DO  1.8609745382  <NA> #> 3345   2045    3M  CC15 2023 2023-03-23      DOSAT  4.4030540019  <NA> #> 3346   2045    3M  CC15 2023 2023-03-23       NO23 -5.5214609179     U #> 3347   2045    3M  CC15 2023 2023-03-23      SALIN  2.8449093838  <NA> #> 3348   2045    3M  CC15 2023 2023-03-23        TKN -0.3424903089  <NA> #> 3349   2045    3M  CC15 2023 2023-03-23         TN -0.3396773676     + #> 3350   2045    3M  CC15 2023 2023-03-23         TP -1.5606477483  <NA> #> 3351   2045    3M  CC15 2023 2023-03-23        TSS  1.7917594692     I #> 3352   2045    3M  CC15 2023 2023-03-23       TURB  1.2809338455  <NA> #> 3353   2045    3M  CC15 2023 2023-05-08      CHLAC  1.1314021115  <NA> #> 3354   2045    3M  CC15 2023 2023-05-08       COND 10.4129822911  <NA> #> 3355   2045    3M  CC15 2023 2023-05-08         DO  1.6992786164  <NA> #> 3356   2045    3M  CC15 2023 2023-05-08      DOSAT  4.3148178850  <NA> #> 3357   2045    3M  CC15 2023 2023-05-08       NO23 -5.5214609179     U #> 3358   2045    3M  CC15 2023 2023-05-08      SALIN  3.0359140632  <NA> #> 3359   2045    3M  CC15 2023 2023-05-08        TKN -0.3147107448  <NA> #> 3360   2045    3M  CC15 2023 2023-05-08         TN -0.3119747650     + #> 3361   2045    3M  CC15 2023 2023-05-08         TP -1.6607312068  <NA> #> 3362   2045    3M  CC15 2023 2023-05-08        TSS  2.6390573296  <NA> #> 3363   2045    3M  CC15 2023 2023-05-08       TURB  1.3350010667  <NA> #> 3364   2043    3M  CC16 2014 2014-06-26       COND  9.8119751520  <NA> #> 3365   2043    3M  CC16 2014 2014-06-26         DO  2.4230312461  <NA> #> 3366   2043    3M  CC16 2014 2014-06-26      DOSAT  5.0801613567  <NA> #> 3367   2043    3M  CC16 2014 2014-06-26       COND  9.5792797987  <NA> #> 3368   2043    3M  CC16 2014 2014-06-26         DO  1.2441545940  <NA> #> 3369   2043    3M  CC16 2014 2014-06-26      DOSAT  3.9852734672  <NA> #> 3370   2043    3M  CC16 2018 2018-03-07      CHLAC  1.8870696490  <NA> #> 3371   2043    3M  CC16 2018 2018-03-07       COND 10.1527665775  <NA> #> 3372   2043    3M  CC16 2018 2018-03-07         DO  1.9878743482  <NA> #> 3373   2043    3M  CC16 2018 2018-03-07      DOSAT  4.5347477217  <NA> #> 3374   2043    3M  CC16 2018 2018-03-07       NO23 -5.5214609179     U #> 3375   2043    3M  CC16 2018 2018-03-07      SALIN  2.8081971497     + #> 3376   2043    3M  CC16 2018 2018-03-07        TKN -0.3424903089  <NA> #> 3377   2043    3M  CC16 2018 2018-03-07         TN -0.3396773676     + #> 3378   2043    3M  CC16 2018 2018-03-07         TP -1.7719568419  <NA> #> 3379   2043    3M  CC16 2018 2018-03-07        TSS  1.6094379124     I #> 3380   2043    3M  CC16 2018 2018-03-07       TURB  1.0986122887  <NA> #> 3381   2043    3M  CC16 2018 2018-03-07       COND 10.2049615773  <NA> #> 3382   2043    3M  CC16 2018 2018-03-07         DO  2.0281482473  <NA> #> 3383   2043    3M  CC16 2018 2018-03-07      DOSAT  4.5653893160  <NA> #> 3384   2043    3M  CC16 2018 2018-03-07      SALIN  2.8701690506     + #> 3385   2043    3M  CC16 2018 2018-04-09      CHLAC  1.9315214116  <NA> #> 3386   2043    3M  CC16 2018 2018-04-09       COND 10.4399809231  <NA> #> 3387   2043    3M  CC16 2018 2018-04-09         DO  1.8082887712  <NA> #> 3388   2043    3M  CC16 2018 2018-04-09      DOSAT  4.4426512565  <NA> #> 3389   2043    3M  CC16 2018 2018-04-09       NO23 -5.2983173665     I #> 3390   2043    3M  CC16 2018 2018-04-09      SALIN  3.0445224377     + #> 3391   2043    3M  CC16 2018 2018-04-09        TKN -0.3011050928  <NA> #> 3392   2043    3M  CC16 2018 2018-04-09         TN -0.2957142441     + #> 3393   2043    3M  CC16 2018 2018-04-09         TP -1.6607312068  <NA> #> 3394   2043    3M  CC16 2018 2018-04-09        TSS  2.0794415417     I #> 3395   2043    3M  CC16 2018 2018-04-09       TURB  1.4816045409  <NA> #> 3396   2043    3M  CC16 2018 2018-05-24      CHLAC  2.2925347571  <NA> #> 3397   2043    3M  CC16 2018 2018-05-24       COND  9.8201059436  <NA> #> 3398   2043    3M  CC16 2018 2018-05-24         DO  1.7749523509  <NA> #> 3399   2043    3M  CC16 2018 2018-05-24      DOSAT  4.3719762988  <NA> #> 3400   2043    3M  CC16 2018 2018-05-24       NO23 -4.4228486292  <NA> #> 3401   2043    3M  CC16 2018 2018-05-24      SALIN  2.3360198691     + #> 3402   2043    3M  CC16 2018 2018-05-24        TKN -0.1984509387  <NA> #> 3403   2043    3M  CC16 2018 2018-05-24         TN -0.1839228382     + #> 3404   2043    3M  CC16 2018 2018-05-24         TP -1.6094379124  <NA> #> 3405   2043    3M  CC16 2018 2018-05-24        TSS  2.3025850930     I #> 3406   2043    3M  CC16 2018 2018-05-24       TURB  1.6863989536  <NA> #> 3407   2043    3M  CC16 2018 2018-05-24       COND  9.8362788028  <NA> #> 3408   2043    3M  CC16 2018 2018-05-24         DO  1.7698546338  <NA> #> 3409   2043    3M  CC16 2018 2018-05-24      DOSAT  4.3681812279  <NA> #> 3410   2043    3M  CC16 2018 2018-05-24      SALIN  2.3532782073     + #> 3411   2043    3M  CC16 2018 2018-07-23      CHLAC  2.4849066498  <NA> #> 3412   2043    3M  CC16 2018 2018-07-23       COND  7.2034055211  <NA> #> 3413   2043    3M  CC16 2018 2018-07-23         DO  1.7833912196  <NA> #> 3414   2043    3M  CC16 2018 2018-07-23      DOSAT  4.3694478525  <NA> #> 3415   2043    3M  CC16 2018 2018-07-23       NO23 -2.1202635362  <NA> #> 3416   2043    3M  CC16 2018 2018-07-23      SALIN -0.4004775666  <NA> #> 3417   2043    3M  CC16 2018 2018-07-23        TKN  0.1823215568  <NA> #> 3418   2043    3M  CC16 2018 2018-07-23         TN  0.2776317366     + #> 3419   2043    3M  CC16 2018 2018-07-23         TP -1.1394342832  <NA> #> 3420   2043    3M  CC16 2018 2018-07-23        TSS  1.0986122887     I #> 3421   2043    3M  CC16 2018 2018-07-23       TURB  1.0986122887  <NA> #> 3422   2043    3M  CC16 2018 2018-07-23       COND  7.2034055211  <NA> #> 3423   2043    3M  CC16 2018 2018-07-23         DO  1.7578579176  <NA> #> 3424   2043    3M  CC16 2018 2018-07-23      DOSAT  4.3438054219  <NA> #> 3425   2043    3M  CC16 2018 2018-07-23      SALIN -0.4155154440  <NA> #> 3426   2043    3M  CC16 2018 2018-08-21      CHLAC  2.8332133441     A #> 3427   2043    3M  CC16 2018 2018-08-21       COND  6.5308776277  <NA> #> 3428   2043    3M  CC16 2018 2018-08-21         DO  1.7083778603  <NA> #> 3429   2043    3M  CC16 2018 2018-08-21      DOSAT  4.2931954210  <NA> #> 3430   2043    3M  CC16 2018 2018-08-21       NO23 -2.8824035882  <NA> #> 3431   2043    3M  CC16 2018 2018-08-21      SALIN -1.1086626245  <NA> #> 3432   2043    3M  CC16 2018 2018-08-21        TKN  0.0953101798  <NA> #> 3433   2043    3M  CC16 2018 2018-08-21         TN  0.1449657703     + #> 3434   2043    3M  CC16 2018 2018-08-21         TP -1.2378743560  <NA> #> 3435   2043    3M  CC16 2018 2018-08-21        TSS  1.0986122887     I #> 3436   2043    3M  CC16 2018 2018-08-21       TURB  1.2809338455  <NA> #> 3437   2043    3M  CC16 2018 2018-08-21       COND  6.5337888379  <NA> #> 3438   2043    3M  CC16 2018 2018-08-21         DO  1.6882490929  <NA> #> 3439   2043    3M  CC16 2018 2018-08-21      DOSAT  4.2724907476  <NA> #> 3440   2043    3M  CC16 2018 2018-08-21      SALIN -1.1086626245  <NA> #> 3441   2043    3M  CC16 2019 2019-02-07      CHLAC  3.1354942159  <NA> #> 3442   2043    3M  CC16 2019 2019-02-07       COND  9.1573614472  <NA> #> 3443   2043    3M  CC16 2019 2019-02-07       NO23 -5.5214609179     U #> 3444   2043    3M  CC16 2019 2019-02-07      SALIN  1.6733512382  <NA> #> 3445   2043    3M  CC16 2019 2019-02-07        TKN -0.0725706928  <NA> #> 3446   2043    3M  CC16 2019 2019-02-07         TN -0.0704224643     + #> 3447   2043    3M  CC16 2019 2019-02-07         TP -1.8325814637  <NA> #> 3448   2043    3M  CC16 2019 2019-02-07        TSS  1.9459101491     I #> 3449   2043    3M  CC16 2019 2019-02-07       TURB  1.6863989536  <NA> #> 3450   2043    3M  CC16 2019 2019-03-13      CHLAC  2.1517622033  <NA> #> 3451   2043    3M  CC16 2019 2019-03-13       COND  9.7229244488  <NA> #> 3452   2043    3M  CC16 2019 2019-03-13         DO  1.7369512327  <NA> #> 3453   2043    3M  CC16 2019 2019-03-13      DOSAT  4.2780540443     + #> 3454   2043    3M  CC16 2019 2019-03-13       NO23 -5.5214609179     U #> 3455   2043    3M  CC16 2019 2019-03-13      SALIN  2.2823823857  <NA> #> 3456   2043    3M  CC16 2019 2019-03-13        TKN -0.2613647641  <NA> #> 3457   2043    3M  CC16 2019 2019-03-13         TN -0.2587707290     + #> 3458   2043    3M  CC16 2019 2019-03-13         TP -1.8971199849  <NA> #> 3459   2043    3M  CC16 2019 2019-03-13        TSS  1.6094379124     I #> 3460   2043    3M  CC16 2019 2019-03-13       TURB  1.2527629685  <NA> #> 3461   2043    3M  CC16 2019 2019-03-13       COND  9.7228046524  <NA> #> 3462   2043    3M  CC16 2019 2019-03-13         DO  1.6992786164  <NA> #> 3463   2043    3M  CC16 2019 2019-03-13      DOSAT  4.2398868675  <NA> #> 3464   2043    3M  CC16 2019 2019-03-13      SALIN  2.2823823857  <NA> #> 3465   2043    3M  CC16 2019 2019-04-23      CHLAC  2.3978952728  <NA> #> 3466   2043    3M  CC16 2019 2019-04-23       COND  9.9710060043  <NA> #> 3467   2043    3M  CC16 2019 2019-04-23         DO  1.8341801851  <NA> #> 3468   2043    3M  CC16 2019 2019-04-23      DOSAT  4.3707128748  <NA> #> 3469   2043    3M  CC16 2019 2019-04-23       NO23 -5.5214609179     U #> 3470   2043    3M  CC16 2019 2019-04-23      SALIN  2.5533438113  <NA> #> 3471   2043    3M  CC16 2019 2019-04-23        TKN -0.1863295782  <NA> #> 3472   2043    3M  CC16 2019 2019-04-23         TN -0.1839228382     + #> 3473   2043    3M  CC16 2019 2019-04-23         TP -1.7147984281  <NA> #> 3474   2043    3M  CC16 2019 2019-04-23        TSS  1.6094379124     I #> 3475   2043    3M  CC16 2019 2019-04-23       TURB  1.0296194172  <NA> #> 3476   2043    3M  CC16 2019 2019-07-22      CHLAC  2.4849066498  <NA> #> 3477   2043    3M  CC16 2019 2019-07-22       COND  8.7887458819  <NA> #> 3478   2043    3M  CC16 2019 2019-07-22         DO  1.7850704811  <NA> #> 3479   2043    3M  CC16 2019 2019-07-22      DOSAT  4.3969152472  <NA> #> 3480   2043    3M  CC16 2019 2019-07-22       NO23 -5.5214609179     U #> 3481   2043    3M  CC16 2019 2019-07-22      SALIN  1.2669476035  <NA> #> 3482   2043    3M  CC16 2019 2019-07-22        TKN -0.0833816089  <NA> #> 3483   2043    3M  CC16 2019 2019-07-22         TN -0.0812100554     + #> 3484   2043    3M  CC16 2019 2019-07-22         TP -1.2378743560  <NA> #> 3485   2043    3M  CC16 2019 2019-07-22        TSS  1.0986122887     I #> 3486   2043    3M  CC16 2019 2019-07-22       TURB  1.0986122887  <NA> #> 3487   2043    3M  CC16 2019 2019-09-04      CHLAC  2.3025850930  <NA> #> 3488   2043    3M  CC16 2019 2019-09-04       COND  7.9875244798  <NA> #> 3489   2043    3M  CC16 2019 2019-09-04         DO  1.7101878155  <NA> #> 3490   2043    3M  CC16 2019 2019-09-04      DOSAT  4.2972854062  <NA> #> 3491   2043    3M  CC16 2019 2019-09-04       NO23 -2.3025850930  <NA> #> 3492   2043    3M  CC16 2019 2019-09-04      SALIN  0.4187103349  <NA> #> 3493   2043    3M  CC16 2019 2019-09-04        TKN  0.1823215568  <NA> #> 3494   2043    3M  CC16 2019 2019-09-04         TN  0.2623642645     + #> 3495   2043    3M  CC16 2019 2019-09-04         TP -0.9162907319  <NA> #> 3496   2043    3M  CC16 2019 2019-09-04        TSS  1.7917594692     I #> 3497   2043    3M  CC16 2019 2019-09-04       TURB  1.3350010667  <NA> #> 3498   2043    3M  CC16 2020 2020-02-18      CHLAC  2.3978952728  <NA> #> 3499   2043    3M  CC16 2020 2020-02-18       COND 10.0826374182  <NA> #> 3500   2043    3M  CC16 2020 2020-02-18         DO  2.0202221820  <NA> #> 3501   2043    3M  CC16 2020 2020-02-18      DOSAT  4.6170987569  <NA> #> 3502   2043    3M  CC16 2020 2020-02-18       NO23 -5.5214609179     U #> 3503   2043    3M  CC16 2020 2020-02-18      SALIN  2.6720775406  <NA> #> 3504   2043    3M  CC16 2020 2020-02-18        TKN -0.1984509387  <NA> #> 3505   2043    3M  CC16 2020 2020-02-18         TN -0.1960148839     + #> 3506   2043    3M  CC16 2020 2020-02-18         TP -1.7147984281  <NA> #> 3507   2043    3M  CC16 2020 2020-02-18        TSS  2.4849066498  <NA> #> 3508   2043    3M  CC16 2020 2020-02-18       TURB  1.5260563035  <NA> #> 3509   2043    3M  CC16 2020 2020-02-18       COND 10.0856841015  <NA> #> 3510   2043    3M  CC16 2020 2020-02-18         DO  2.0055258587  <NA> #> 3511   2043    3M  CC16 2020 2020-02-18      DOSAT  4.6001576442  <NA> #> 3512   2043    3M  CC16 2020 2020-02-18      SALIN  2.6755270094  <NA> #> 3513   2043    3M  CC16 2020 2020-06-09      CHLAC  1.9459101491  <NA> #> 3514   2043    3M  CC16 2020 2020-06-09       COND  9.1632487644  <NA> #> 3515   2043    3M  CC16 2020 2020-06-09         DO  1.8779371655  <NA> #> 3516   2043    3M  CC16 2020 2020-06-09      DOSAT  4.4716387934  <NA> #> 3517   2043    3M  CC16 2020 2020-06-09       NO23 -3.5404594490  <NA> #> 3518   2043    3M  CC16 2020 2020-06-09      SALIN  1.6695918353  <NA> #> 3519   2043    3M  CC16 2020 2020-06-09        TKN -0.1743533871  <NA> #> 3520   2043    3M  CC16 2020 2020-06-09         TN -0.1404121537     + #> 3521   2043    3M  CC16 2020 2020-06-09         TP -1.5606477483  <NA> #> 3522   2043    3M  CC16 2020 2020-06-09        TSS  1.0986122887     I #> 3523   2043    3M  CC16 2020 2020-06-09       TURB  0.8329091229  <NA> #> 3524   2043    3M  CC16 2020 2020-06-09       COND  9.4707797080  <NA> #> 3525   2043    3M  CC16 2020 2020-06-09         DO  1.8855533485  <NA> #> 3526   2043    3M  CC16 2020 2020-06-09      DOSAT  4.4986979415  <NA> #> 3527   2043    3M  CC16 2020 2020-06-09      SALIN  2.0041790572  <NA> #> 3528   2043    3M  CC16 2020 2020-08-10       COND  9.6776528834  <NA> #> 3529   2043    3M  CC16 2020 2020-08-10         DO  1.5973653312  <NA> #> 3530   2043    3M  CC16 2020 2020-08-10      DOSAT  4.2541932632  <NA> #> 3531   2043    3M  CC16 2020 2020-08-10      SALIN  2.2093727113  <NA> #> 3532   2043    3M  CC16 2020 2020-09-22      CHLAC  2.1041341543  <NA> #> 3533   2043    3M  CC16 2020 2020-09-22       COND  6.8012830345  <NA> #> 3534   2043    3M  CC16 2020 2020-09-22         DO  1.8500283774  <NA> #> 3535   2043    3M  CC16 2020 2020-09-22      DOSAT  4.3932138241  <NA> #> 3536   2043    3M  CC16 2020 2020-09-22       NO23 -2.6882475738  <NA> #> 3537   2043    3M  CC16 2020 2020-09-22      SALIN -0.8209805521  <NA> #> 3538   2043    3M  CC16 2020 2020-09-22        TKN  0.1823215568  <NA> #> 3539   2043    3M  CC16 2020 2020-09-22         TN  0.2374408560     + #> 3540   2043    3M  CC16 2020 2020-09-22         TP -1.0498221245  <NA> #> 3541   2043    3M  CC16 2020 2020-09-22        TSS  1.3862943611     I #> 3542   2043    3M  CC16 2020 2020-09-22       TURB  1.1314021115     A #> 3543   2043    3M  CC16 2020 2020-10-20      CHLAC  2.3978952728  <NA> #> 3544   2043    3M  CC16 2020 2020-10-20       COND  8.8590793179  <NA> #> 3545   2043    3M  CC16 2020 2020-10-20         DO  1.7281094422  <NA> #> 3546   2043    3M  CC16 2020 2020-10-20      DOSAT  4.2835865619  <NA> #> 3547   2043    3M  CC16 2020 2020-10-20       NO23 -2.2072749132  <NA> #> 3548   2043    3M  CC16 2020 2020-10-20      SALIN  1.3480731483  <NA> #> 3549   2043    3M  CC16 2020 2020-10-20        TKN  0.1823215568  <NA> #> 3550   2043    3M  CC16 2020 2020-10-20         TN  0.2700271372     + #> 3551   2043    3M  CC16 2020 2020-10-20         TP -1.1086626245  <NA> #> 3552   2043    3M  CC16 2020 2020-10-20        TSS  1.7917594692     I #> 3553   2043    3M  CC16 2020 2020-10-20       TURB  1.3350010667  <NA> #> 3554   2043    3M  CC16 2020 2020-12-14      CHLAC  2.6390573296  <NA> #> 3555   2043    3M  CC16 2020 2020-12-14       COND  9.3722891390  <NA> #> 3556   2043    3M  CC16 2020 2020-12-14         DO  2.0554049639  <NA> #> 3557   2043    3M  CC16 2020 2020-12-14      DOSAT  4.5261269786  <NA> #> 3558   2043    3M  CC16 2020 2020-12-14       NO23 -5.5214609179     U #> 3559   2043    3M  CC16 2020 2020-12-14      SALIN  1.9035989510  <NA> #> 3560   2043    3M  CC16 2020 2020-12-14        TKN -0.0408219945  <NA> #> 3561   2043    3M  CC16 2020 2020-12-14         TN -0.0387408283     + #> 3562   2043    3M  CC16 2020 2020-12-14         TP -1.6094379124  <NA> #> 3563   2043    3M  CC16 2020 2020-12-14        TSS  1.6094379124     I #> 3564   2043    3M  CC16 2020 2020-12-14       TURB  1.2237754316  <NA> #> 3565   2043    3M  CC16 2021 2021-02-03      CHLAC  2.3978952728  <NA> #> 3566   2043    3M  CC16 2021 2021-02-03       COND  9.8437906253  <NA> #> 3567   2043    3M  CC16 2021 2021-02-03         DO  2.0360119838  <NA> #> 3568   2043    3M  CC16 2021 2021-02-03      DOSAT  4.4379342666  <NA> #> 3569   2043    3M  CC16 2021 2021-02-03       NO23 -5.5214609179     U #> 3570   2043    3M  CC16 2021 2021-02-03      SALIN  2.4185887688  <NA> #> 3571   2043    3M  CC16 2021 2021-02-03        TKN -0.2484613593  <NA> #> 3572   2043    3M  CC16 2021 2021-02-03         TN -0.2459005384     + #> 3573   2043    3M  CC16 2021 2021-02-03         TP -2.2072749132  <NA> #> 3574   2043    3M  CC16 2021 2021-02-03        TSS  1.3862943611     I #> 3575   2043    3M  CC16 2021 2021-02-03       TURB  1.0986122887  <NA> #> 3576   2043    3M  CC16 2021 2021-03-23      CHLAC  2.5649493575  <NA> #> 3577   2043    3M  CC16 2021 2021-03-23       COND 10.0172179429  <NA> #> 3578   2043    3M  CC16 2021 2021-03-23         DO  1.8484548129  <NA> #> 3579   2043    3M  CC16 2021 2021-03-23      DOSAT  4.3320482649  <NA> #> 3580   2043    3M  CC16 2021 2021-03-23       NO23 -5.5214609179     U #> 3581   2043    3M  CC16 2021 2021-03-23      SALIN  2.6056482675  <NA> #> 3582   2043    3M  CC16 2021 2021-03-23        TKN -0.1165338163  <NA> #> 3583   2043    3M  CC16 2021 2021-03-23         TN -0.1142891464     + #> 3584   2043    3M  CC16 2021 2021-03-23         TP -1.8971199849  <NA> #> 3585   2043    3M  CC16 2021 2021-03-23        TSS  1.7917594692     I #> 3586   2043    3M  CC16 2021 2021-03-23       TURB  1.3862943611  <NA> #> 3587   2043    3M  CC16 2021 2021-05-05      CHLAC  2.2823823857  <NA> #> 3588   2043    3M  CC16 2021 2021-05-05       COND 10.2634321453  <NA> #> 3589   2043    3M  CC16 2021 2021-05-05         DO  1.7263316639  <NA> #> 3590   2043    3M  CC16 2021 2021-05-05      DOSAT  4.4200447019  <NA> #> 3591   2043    3M  CC16 2021 2021-05-05       NO23 -5.5214609179     I #> 3592   2043    3M  CC16 2021 2021-05-05      SALIN  2.8650539499  <NA> #> 3593   2043    3M  CC16 2021 2021-05-05        TKN -0.0833816089  <NA> #> 3594   2043    3M  CC16 2021 2021-05-05         TN -0.0790432073     + #> 3595   2043    3M  CC16 2021 2021-05-05         TP -1.5606477483  <NA> #> 3596   2043    3M  CC16 2021 2021-05-05        TSS  2.0794415417     I #> 3597   2043    3M  CC16 2021 2021-05-05       TURB  1.4816045409  <NA> #> 3598   2043    3M  CC16 2021 2021-06-03      CHLAC  2.4849066498  <NA> #> 3599   2043    3M  CC16 2021 2021-06-03       COND 10.3258753278  <NA> #> 3600   2043    3M  CC16 2021 2021-06-03         DO  1.6524974019  <NA> #> 3601   2043    3M  CC16 2021 2021-06-03      DOSAT  4.3094559418  <NA> #> 3602   2043    3M  CC16 2021 2021-06-03       NO23 -5.5214609179     U #> 3603   2043    3M  CC16 2021 2021-06-03      SALIN  2.9375733594  <NA> #> 3604   2043    3M  CC16 2021 2021-06-03        TKN  0.0000000000  <NA> #> 3605   2043    3M  CC16 2021 2021-06-03         TN  0.0019980027     + #> 3606   2043    3M  CC16 2021 2021-06-03         TP -1.6607312068  <NA> #> 3607   2043    3M  CC16 2021 2021-06-03        TSS  2.0794415417     I #> 3608   2043    3M  CC16 2021 2021-06-03       TURB  1.4109869737  <NA> #> 3609   2043    3M  CC16 2021 2021-07-01      CHLAC  3.0910424534  <NA> #> 3610   2043    3M  CC16 2021 2021-07-01       COND 10.1819522754  <NA> #> 3611   2043    3M  CC16 2021 2021-07-01         DO  1.6956156087  <NA> #> 3612   2043    3M  CC16 2021 2021-07-01      DOSAT  4.3567088267  <NA> #> 3613   2043    3M  CC16 2021 2021-07-01       NO23 -3.0791138825  <NA> #> 3614   2043    3M  CC16 2021 2021-07-01      SALIN  2.7775762638  <NA> #> 3615   2043    3M  CC16 2021 2021-07-01        TKN -0.2357223335  <NA> #> 3616   2043    3M  CC16 2021 2021-07-01         TN -0.1791266659     + #> 3617   2043    3M  CC16 2021 2021-07-01         TP -1.5606477483  <NA> #> 3618   2043    3M  CC16 2021 2021-07-01        TSS  2.3025850930  <NA> #> 3619   2043    3M  CC16 2021 2021-07-01       TURB  1.7404661748  <NA> #> 3620   2043    3M  CC16 2022 2022-02-22      CHLAC  1.0986122887  <NA> #> 3621   2043    3M  CC16 2022 2022-02-22       COND 10.3057809695  <NA> #> 3622   2043    3M  CC16 2022 2022-02-22         DO  1.8794650496  <NA> #> 3623   2043    3M  CC16 2022 2022-02-22      DOSAT  4.4543472963  <NA> #> 3624   2043    3M  CC16 2022 2022-02-22       NO23 -4.9618451299     I #> 3625   2043    3M  CC16 2022 2022-02-22      SALIN  2.9199305601  <NA> #> 3626   2043    3M  CC16 2022 2022-02-22        TKN -0.4307829161  <NA> #> 3627   2043    3M  CC16 2022 2022-02-22         TN -0.4246479275     + #> 3628   2043    3M  CC16 2022 2022-02-22         TP -2.3859667019  <NA> #> 3629   2043    3M  CC16 2022 2022-02-22        TSS  2.3025850930     I #> 3630   2043    3M  CC16 2022 2022-02-22       TURB  0.6931471806  <NA> #> 3631   2043    3M  CC16 2022 2022-06-07      CHLAC  2.7080502011  <NA> #> 3632   2043    3M  CC16 2022 2022-06-07       COND 10.2345882454  <NA> #> 3633   2043    3M  CC16 2022 2022-06-07         DO  1.4182774070  <NA> #> 3634   2043    3M  CC16 2022 2022-06-07      DOSAT  4.1026433650  <NA> #> 3635   2043    3M  CC16 2022 2022-06-07       NO23 -5.5214609179     U #> 3636   2043    3M  CC16 2022 2022-06-07      SALIN  2.8361502037  <NA> #> 3637   2043    3M  CC16 2022 2022-06-07        TKN -0.1165338163  <NA> #> 3638   2043    3M  CC16 2022 2022-06-07         TN -0.1142891464     + #> 3639   2043    3M  CC16 2022 2022-06-07         TP -1.6607312068  <NA> #> 3640   2043    3M  CC16 2022 2022-06-07        TSS  2.5649493575  <NA> #> 3641   2043    3M  CC16 2022 2022-06-07       TURB  1.6863989536  <NA> #> 3642   2043    3M  CC16 2022 2022-08-15      CHLAC  2.9957322736     A #> 3643   2043    3M  CC16 2022 2022-08-15       COND  8.1639409548  <NA> #> 3644   2043    3M  CC16 2022 2022-08-15         DO  1.4350845253  <NA> #> 3645   2043    3M  CC16 2022 2022-08-15      DOSAT  4.0145795938  <NA> #> 3646   2043    3M  CC16 2022 2022-08-15       NO23 -4.7105307016     I #> 3647   2043    3M  CC16 2022 2022-08-15      SALIN  0.6043159669  <NA> #> 3648   2043    3M  CC16 2022 2022-08-15        TKN -0.1278333715  <NA> #> 3649   2043    3M  CC16 2022 2022-08-15         TN -0.1232982163     + #> 3650   2043    3M  CC16 2022 2022-08-15         TP -1.3093333200  <NA> #> 3651   2043    3M  CC16 2022 2022-08-15        TSS  1.3862943611     I #> 3652   2043    3M  CC16 2022 2022-08-15       TURB  1.2527629685  <NA> #> 3653   2043    3M  CC16 2022 2022-12-15      CHLAC  4.8675344505  <NA> #> 3654   2043    3M  CC16 2022 2022-12-15       COND  9.6068992706  <NA> #> 3655   2043    3M  CC16 2022 2022-12-15         DO  2.1781550146  <NA> #> 3656   2043    3M  CC16 2022 2022-12-15      DOSAT  4.6950108900  <NA> #> 3657   2043    3M  CC16 2022 2022-12-15       NO23 -5.5214609179     U #> 3658   2043    3M  CC16 2022 2022-12-15      SALIN  2.1575593209  <NA> #> 3659   2043    3M  CC16 2022 2022-12-15        TKN  0.5306282511  <NA> #> 3660   2043    3M  CC16 2022 2022-12-15         TN  0.5318040302     + #> 3661   2043    3M  CC16 2022 2022-12-15         TP -1.1711829815  <NA> #> 3662   2043    3M  CC16 2022 2022-12-15        TSS  2.8903717579  <NA> #> 3663   2043    3M  CC16 2022 2022-12-15       TURB  1.8562979904  <NA> #> 3664   2043    3M  CC16 2021 2021-02-03      CHLAC  3.1354942159  <NA> #> 3665   2043    3M  CC16 2021 2021-02-03       COND  9.5834200199  <NA> #> 3666   2043    3M  CC16 2021 2021-02-03         DO  2.0041790572  <NA> #> 3667   2043    3M  CC16 2021 2021-02-03      DOSAT  4.4042772436  <NA> #> 3668   2043    3M  CC16 2021 2021-02-03       NO23 -5.5214609179     U #> 3669   2043    3M  CC16 2021 2021-02-03      SALIN  2.1365305087  <NA> #> 3670   2043    3M  CC16 2021 2021-02-03        TKN -0.1278333715  <NA> #> 3671   2043    3M  CC16 2021 2021-02-03         TN -0.1255632230     + #> 3672   2043    3M  CC16 2021 2021-02-03         TP -2.1202635362  <NA> #> 3673   2043    3M  CC16 2021 2021-02-03        TSS  1.9459101491     I #> 3674   2043    3M  CC16 2021 2021-02-03       TURB  1.7578579176  <NA> #> 3675   2043    3M  CC16 2021 2021-03-23      CHLAC  3.2188758249  <NA> #> 3676   2043    3M  CC16 2021 2021-03-23       COND  9.8242819944  <NA> #> 3677   2043    3M  CC16 2021 2021-03-23         DO  1.7867469274  <NA> #> 3678   2043    3M  CC16 2021 2021-03-23      DOSAT  4.2640873368  <NA> #> 3679   2043    3M  CC16 2021 2021-03-23       NO23 -5.5214609179     U #> 3680   2043    3M  CC16 2021 2021-03-23      SALIN  2.3951642743  <NA> #> 3681   2043    3M  CC16 2021 2021-03-23        TKN  0.0953101798  <NA> #> 3682   2043    3M  CC16 2021 2021-03-23         TN  0.0971267107     + #> 3683   2043    3M  CC16 2021 2021-03-23         TP -1.6094379124  <NA> #> 3684   2043    3M  CC16 2021 2021-03-23        TSS  2.3978952728  <NA> #> 3685   2043    3M  CC16 2021 2021-03-23       TURB  2.0412203289  <NA> #> 3686   2043    3M  CC16 2021 2021-05-05      CHLAC  2.7725887222  <NA> #> 3687   2043    3M  CC16 2021 2021-05-05       COND 10.1696522784  <NA> #> 3688   2043    3M  CC16 2021 2021-05-05         DO  1.3711807233  <NA> #> 3689   2043    3M  CC16 2021 2021-05-05      DOSAT  4.0342406382  <NA> #> 3690   2043    3M  CC16 2021 2021-05-05       NO23 -5.5214609179     U #> 3691   2043    3M  CC16 2021 2021-05-05      SALIN  2.7638002162  <NA> #> 3692   2043    3M  CC16 2021 2021-05-05        TKN -0.0304592075  <NA> #> 3693   2043    3M  CC16 2021 2021-05-05         TN -0.0283994745     + #> 3694   2043    3M  CC16 2021 2021-05-05         TP -1.5606477483  <NA> #> 3695   2043    3M  CC16 2021 2021-05-05        TSS  1.7917594692     I #> 3696   2043    3M  CC16 2021 2021-05-05       TURB  1.5260563035  <NA> #> 3697   2043    3M  CC16 2021 2021-06-03      CHLAC  2.8903717579  <NA> #> 3698   2043    3M  CC16 2021 2021-06-03       COND 10.2473963549  <NA> #> 3699   2043    3M  CC16 2021 2021-06-03         DO  1.5475625087  <NA> #> 3700   2043    3M  CC16 2021 2021-06-03      DOSAT  4.2002049529  <NA> #> 3701   2043    3M  CC16 2021 2021-06-03       NO23 -4.9618451299     I #> 3702   2043    3M  CC16 2021 2021-06-03      SALIN  2.8518619031  <NA> #> 3703   2043    3M  CC16 2021 2021-06-03        TKN  0.1823215568  <NA> #> 3704   2043    3M  CC16 2021 2021-06-03         TN  0.1856493469     + #> 3705   2043    3M  CC16 2021 2021-06-03         TP -1.5606477483  <NA> #> 3706   2043    3M  CC16 2021 2021-06-03        TSS  2.3978952728  <NA> #> 3707   2043    3M  CC16 2021 2021-06-03       TURB  1.6486586256  <NA> #> 3708   2043    3M  CC16 2021 2021-07-01      CHLAC  3.4339872045  <NA> #> 3709   2043    3M  CC16 2021 2021-07-01       COND 10.0458547938  <NA> #> 3710   2043    3M  CC16 2021 2021-07-01         DO  1.9837562915  <NA> #> 3711   2043    3M  CC16 2021 2021-07-01      DOSAT  4.6091622073  <NA> #> 3712   2043    3M  CC16 2021 2021-07-01       NO23 -3.4420193762  <NA> #> 3713   2043    3M  CC16 2021 2021-07-01      SALIN  2.6304489551  <NA> #> 3714   2043    3M  CC16 2021 2021-07-01        TKN -0.0304592075  <NA> #> 3715   2043    3M  CC16 2021 2021-07-01         TN  0.0019980027     + #> 3716   2043    3M  CC16 2021 2021-07-01         TP -1.3862943611  <NA> #> 3717   2043    3M  CC16 2021 2021-07-01        TSS  1.7917594692     I #> 3718   2043    3M  CC16 2021 2021-07-01       TURB  1.6677068206  <NA> #> 3719   2043    3M  CC16 2022 2022-02-22      CHLAC  1.6094379124  <NA> #> 3720   2043    3M  CC16 2022 2022-02-22       COND 10.1823685085  <NA> #> 3721   2043    3M  CC16 2022 2022-02-22         DO  1.7422190237  <NA> #> 3722   2043    3M  CC16 2022 2022-02-22      DOSAT  4.3148178850  <NA> #> 3723   2043    3M  CC16 2022 2022-02-22       NO23 -4.6051701860     I #> 3724   2043    3M  CC16 2022 2022-02-22      SALIN  2.7788192720  <NA> #> 3725   2043    3M  CC16 2022 2022-02-22        TKN -0.2484613593  <NA> #> 3726   2043    3M  CC16 2022 2022-02-22         TN -0.2433462586     + #> 3727   2043    3M  CC16 2022 2022-02-22         TP -2.3025850930  <NA> #> 3728   2043    3M  CC16 2022 2022-02-22        TSS  2.4849066498  <NA> #> 3729   2043    3M  CC16 2022 2022-02-22       TURB  1.6486586256  <NA> #> 3730   2043    3M  CC16 2022 2022-06-07      CHLAC  2.1400661635  <NA> #> 3731   2043    3M  CC16 2022 2022-06-07       COND 10.2020724724  <NA> #> 3732   2043    3M  CC16 2022 2022-06-07         DO  1.5151272330  <NA> #> 3733   2043    3M  CC16 2022 2022-06-07      DOSAT  4.1713056034  <NA> #> 3734   2043    3M  CC16 2022 2022-06-07       NO23 -3.9633162998  <NA> #> 3735   2043    3M  CC16 2022 2022-06-07      SALIN  2.7997173896  <NA> #> 3736   2043    3M  CC16 2022 2022-06-07        TKN -0.1625189295  <NA> #> 3737   2043    3M  CC16 2022 2022-06-07         TN -0.1404121537     + #> 3738   2043    3M  CC16 2022 2022-06-07         TP -1.4271163556  <NA> #> 3739   2043    3M  CC16 2022 2022-06-07        TSS  2.3025850930  <NA> #> 3740   2043    3M  CC16 2022 2022-06-07       TURB  1.3350010667  <NA> #> 3741   2043    3M  CC16 2022 2022-08-15      CHLAC  3.0445224377  <NA> #> 3742   2043    3M  CC16 2022 2022-08-15       COND  7.8363697605  <NA> #> 3743   2043    3M  CC16 2022 2022-08-15         DO  1.5539252025  <NA> #> 3744   2043    3M  CC16 2022 2022-08-15      DOSAT  4.1319614258  <NA> #> 3745   2043    3M  CC16 2022 2022-08-15       NO23 -4.0173835211  <NA> #> 3746   2043    3M  CC16 2022 2022-08-15      SALIN  0.2623642645  <NA> #> 3747   2043    3M  CC16 2022 2022-08-15        TKN -0.1863295782  <NA> #> 3748   2043    3M  CC16 2022 2022-08-15         TN -0.1648746432     + #> 3749   2043    3M  CC16 2022 2022-08-15         TP -1.6094379124  <NA> #> 3750   2043    3M  CC16 2022 2022-08-15        TSS  2.0794415417     I #> 3751   2043    3M  CC16 2022 2022-08-15       TURB  1.4109869737  <NA> #> 3752   2043    3M  CC16 2022 2022-12-15      CHLAC  3.6109179126  <NA> #> 3753   2043    3M  CC16 2022 2022-12-15       COND  9.5544264071  <NA> #> 3754   2043    3M  CC16 2022 2022-12-15         DO  1.8405496334  <NA> #> 3755   2043    3M  CC16 2022 2022-12-15      DOSAT  4.3554259529  <NA> #> 3756   2043    3M  CC16 2022 2022-12-15       NO23 -5.5214609179     U #> 3757   2043    3M  CC16 2022 2022-12-15      SALIN  2.0992441690  <NA> #> 3758   2043    3M  CC16 2022 2022-12-15        TKN -0.1743533871  <NA> #> 3759   2043    3M  CC16 2022 2022-12-15         TN -0.1719752647     + #> 3760   2043    3M  CC16 2022 2022-12-15         TP -1.7719568419  <NA> #> 3761   2043    3M  CC16 2022 2022-12-15        TSS  1.7917594692     I #> 3762   2043    3M  CC16 2022 2022-12-15       TURB  1.2809338455  <NA> #> 3763  2048A    3M  CC18 2014 2014-01-06         DO  1.7917594692  <NA> #> 3764  2048A    3M  CC18 2014 2014-01-06      DOSAT  4.3107991254     + #> 3765  2048A    3M  CC18 2014 2014-01-06       NO23 -4.7105307016     I #> 3766  2048A    3M  CC18 2014 2014-01-06      SALIN  3.0819099698  <NA> #> 3767  2048A    3M  CC18 2014 2014-01-06        TKN -0.3011050928  <NA> #> 3768  2048A    3M  CC18 2014 2014-01-06         TN -0.2957142441     + #> 3769  2048A    3M  CC18 2014 2014-01-06         TP -2.7333680091  <NA> #> 3770  2048A    3M  CC18 2014 2014-02-03      CHLAC  1.3350010667  <NA> #> 3771  2048A    3M  CC18 2014 2014-02-03      COLOR  3.2188758249  <NA> #> 3772  2048A    3M  CC18 2014 2014-02-03         DO  1.6677068206  <NA> #> 3773  2048A    3M  CC18 2014 2014-02-03      DOSAT  4.1820501426     + #> 3774  2048A    3M  CC18 2014 2014-02-03       NO23 -4.5098600062  <NA> #> 3775  2048A    3M  CC18 2014 2014-02-03      SALIN  2.9496883351  <NA> #> 3776  2048A    3M  CC18 2014 2014-02-03        TKN -0.6348782724  <NA> #> 3777  2048A    3M  CC18 2014 2014-02-03         TN -0.6143360001     + #> 3778  2048A    3M  CC18 2014 2014-02-03         TP -2.5133061243  <NA> #> 3779  2048A    3M  CC18 2014 2014-02-03       TURB  0.4700036292  <NA> #> 3780  2048A    3M  CC18 2014 2014-03-03      CHLAC  1.0296194172  <NA> #> 3781  2048A    3M  CC18 2014 2014-03-03      COLOR  3.2580965380  <NA> #> 3782  2048A    3M  CC18 2014 2014-03-03      DOSAT  4.3201512310     + #> 3783  2048A    3M  CC18 2014 2014-03-03       NO23 -5.5214609179     I #> 3784  2048A    3M  CC18 2014 2014-03-03      SALIN  3.0349529867  <NA> #> 3785  2048A    3M  CC18 2014 2014-03-03        TKN -0.4155154440  <NA> #> 3786  2048A    3M  CC18 2014 2014-03-03         TN -0.4094731295     + #> 3787  2048A    3M  CC18 2014 2014-03-03         TP -2.3859667019  <NA> #> 3788  2048A    3M  CC18 2014 2014-03-03       TURB  0.6418538862  <NA> #> 3789  2048A    3M  CC18 2014 2014-04-07      CHLAC  1.5892352051  <NA> #> 3790  2048A    3M  CC18 2014 2014-04-07      COLOR  3.3322045102  <NA> #> 3791  2048A    3M  CC18 2014 2014-04-07         DO  2.2082744135  <NA> #> 3792  2048A    3M  CC18 2014 2014-04-07      DOSAT  4.7492705300     + #> 3793  2048A    3M  CC18 2014 2014-04-07       NO23 -4.9618451299     I #> 3794  2048A    3M  CC18 2014 2014-04-07      SALIN  2.0794415417  <NA> #> 3795  2048A    3M  CC18 2014 2014-04-07        TKN -0.4155154440  <NA> #> 3796  2048A    3M  CC18 2014 2014-04-07         TN -0.4094731295     + #> 3797  2048A    3M  CC18 2014 2014-04-07         TP -3.1465551633  <NA> #> 3798  2048A    3M  CC18 2014 2014-04-07       TURB  0.9932517730  <NA> #> 3799  2048A    3M  CC18 2014 2014-05-05      CHLAC  1.5892352051  <NA> #> 3800  2048A    3M  CC18 2014 2014-05-05      COLOR  3.4657359028     A #> 3801  2048A    3M  CC18 2014 2014-05-05         DO  1.5686159179  <NA> #> 3802  2048A    3M  CC18 2014 2014-05-05      DOSAT  4.1866198383     + #> 3803  2048A    3M  CC18 2014 2014-05-05       NO23 -4.3428059215  <NA> #> 3804  2048A    3M  CC18 2014 2014-05-05      SALIN  3.0819099698  <NA> #> 3805  2048A    3M  CC18 2014 2014-05-05        TKN -0.2107210313  <NA> #> 3806  2048A    3M  CC18 2014 2014-05-05         TN -0.1947990783     + #> 3807  2048A    3M  CC18 2014 2014-05-05         TP -1.9661128564  <NA> #> 3808  2048A    3M  CC18 2014 2014-05-05       TURB  1.1314021115     A #> 3809  2048A    3M  CC18 2014 2014-06-02      CHLAC  1.8718021769  <NA> #> 3810  2048A    3M  CC18 2014 2014-06-02      COLOR  3.6635616461     A #> 3811  2048A    3M  CC18 2014 2014-06-02       NO23 -4.6051701860  <NA> #> 3812  2048A    3M  CC18 2014 2014-06-02      SALIN  3.1441522787  <NA> #> 3813  2048A    3M  CC18 2014 2014-06-02        TKN -0.4004775666  <NA> #> 3814  2048A    3M  CC18 2014 2014-06-02         TN -0.3856624808     + #> 3815  2048A    3M  CC18 2014 2014-06-02         TP -1.5606477483  <NA> #> 3816  2048A    3M  CC18 2014 2014-06-02       TURB  0.9555114450  <NA> #> 3817  2048A    3M  CC18 2014 2014-08-04      CHLAC  1.9740810260  <NA> #> 3818  2048A    3M  CC18 2014 2014-08-04      COLOR  4.7874917428  <NA> #> 3819  2048A    3M  CC18 2014 2014-08-04         DO  0.7371640660  <NA> #> 3820  2048A    3M  CC18 2014 2014-08-04      DOSAT  3.3568971228     + #> 3821  2048A    3M  CC18 2014 2014-08-04       NO23 -4.8283137373     I #> 3822  2048A    3M  CC18 2014 2014-08-04        TKN  0.0953101798  <NA> #> 3823  2048A    3M  CC18 2014 2014-08-04         TN  0.0989399479     + #> 3824  2048A    3M  CC18 2014 2014-08-04         TP -1.3862943611  <NA> #> 3825  2048A    3M  CC18 2014 2014-08-04       TURB  1.2527629685  <NA> #> 3826  2048A    3M  CC18 2014 2014-09-08      CHLAC  1.8082887712  <NA> #> 3827  2048A    3M  CC18 2014 2014-09-08      COLOR  4.1108738642  <NA> #> 3828  2048A    3M  CC18 2014 2014-09-08         DO  1.3083328197  <NA> #> 3829  2048A    3M  CC18 2014 2014-09-08      DOSAT  3.8958936235     + #> 3830  2048A    3M  CC18 2014 2014-09-08       NO23 -4.5098600062  <NA> #> 3831  2048A    3M  CC18 2014 2014-09-08      SALIN  2.1162555148  <NA> #> 3832  2048A    3M  CC18 2014 2014-09-08        TKN -0.0833816089  <NA> #> 3833  2048A    3M  CC18 2014 2014-09-08         TN -0.0714960017     + #> 3834  2048A    3M  CC18 2014 2014-09-08         TP -1.4696759701  <NA> #> 3835  2048A    3M  CC18 2014 2014-09-08       TURB  0.5877866649  <NA> #> 3836  2048A    3M  CC18 2014 2014-10-06      CHLAC  2.3978952728  <NA> #> 3837  2048A    3M  CC18 2014 2014-10-06      COLOR  5.1929568509  <NA> #> 3838  2048A    3M  CC18 2014 2014-10-06         DO  2.1400661635  <NA> #> 3839  2048A    3M  CC18 2014 2014-10-06      DOSAT  4.6376373761     + #> 3840  2048A    3M  CC18 2014 2014-10-06       NO23 -3.9633162998  <NA> #> 3841  2048A    3M  CC18 2014 2014-10-06      SALIN  0.5877866649  <NA> #> 3842  2048A    3M  CC18 2014 2014-10-06        TKN -0.0943106795  <NA> #> 3843  2048A    3M  CC18 2014 2014-10-06         TN -0.0736465402     + #> 3844  2048A    3M  CC18 2014 2014-10-06         TP -1.8971199849  <NA> #> 3845  2048A    3M  CC18 2014 2014-10-06       TURB  0.4700036292     A #> 3846  2048A    3M  CC18 2014 2014-11-03      CHLAC  1.8405496334  <NA> #> 3847  2048A    3M  CC18 2014 2014-11-03      COLOR  4.5325994932  <NA> #> 3848  2048A    3M  CC18 2014 2014-11-03       NO23 -4.2686979494  <NA> #> 3849  2048A    3M  CC18 2014 2014-11-03      SALIN  2.5726122302  <NA> #> 3850  2048A    3M  CC18 2014 2014-11-03        TKN -0.1743533871  <NA> #> 3851  2048A    3M  CC18 2014 2014-11-03         TN -0.1578240852     + #> 3852  2048A    3M  CC18 2014 2014-11-03         TP -1.6607312068  <NA> #> 3853  2048A    3M  CC18 2014 2014-11-03       TURB  0.5306282511     A #> 3854  2048A    3M  CC18 2014 2014-12-01      CHLAC  0.6418538862  <NA> #> 3855  2048A    3M  CC18 2014 2014-12-01      COLOR  3.8712010109     A #> 3856  2048A    3M  CC18 2014 2014-12-01         DO  1.7047480922  <NA> #> 3857  2048A    3M  CC18 2014 2014-12-01      SALIN  2.6100697927  <NA> #> 3858  2048A    3M  CC18 2014 2014-12-01         TN -0.0899247075     + #> 3859  2048A    3M  CC18 2014 2014-12-01       TURB  0.0000000000  <NA> #> 3860  2048A    3M  CC18 2015 2015-01-05      CHLAC  2.0149030205  <NA> #> 3861  2048A    3M  CC18 2015 2015-01-05      COLOR  3.5835189385  <NA> #> 3862  2048A    3M  CC18 2015 2015-01-05         DO  1.7578579176  <NA> #> 3863  2048A    3M  CC18 2015 2015-01-05      DOSAT  4.3333614627     + #> 3864  2048A    3M  CC18 2015 2015-01-05       NO23 -3.6496587410  <NA> #> 3865  2048A    3M  CC18 2015 2015-01-05      SALIN  2.9496883351  <NA> #> 3866  2048A    3M  CC18 2015 2015-01-05        TKN -0.5108256238  <NA> #> 3867  2048A    3M  CC18 2015 2015-01-05         TN -0.4684049079     + #> 3868  2048A    3M  CC18 2015 2015-01-05         TP -2.5010360317  <NA> #> 3869  2048A    3M  CC18 2015 2015-01-05       TURB  0.4700036292  <NA> #> 3870  2048A    3M  CC18 2015 2015-02-02      CHLAC  1.5892352051  <NA> #> 3871  2048A    3M  CC18 2015 2015-02-02      COLOR  3.1780538303  <NA> #> 3872  2048A    3M  CC18 2015 2015-02-02      DOSAT  4.1415461637     + #> 3873  2048A    3M  CC18 2015 2015-02-02       NO23 -4.7105307016     I #> 3874  2048A    3M  CC18 2015 2015-02-02      SALIN  2.9957322736  <NA> #> 3875  2048A    3M  CC18 2015 2015-02-02         TN -0.6088060321     + #> 3876  2048A    3M  CC18 2015 2015-02-02       TURB  0.4054651081  <NA> #> 3877  2048A    3M  CC18 2015 2015-03-02      CHLAC  1.3862943611  <NA> #> 3878  2048A    3M  CC18 2015 2015-03-02      COLOR  3.4011973817  <NA> #> 3879  2048A    3M  CC18 2015 2015-03-02         DO  2.0794415417  <NA> #> 3880  2048A    3M  CC18 2015 2015-03-02      DOSAT  4.6395716127     + #> 3881  2048A    3M  CC18 2015 2015-03-02      SALIN  2.9285235239  <NA> #> 3882  2048A    3M  CC18 2015 2015-03-02         TN -0.3147107448     + #> 3883  2048A    3M  CC18 2015 2015-03-02       TURB  0.7884573604  <NA> #> 3884  2048A    3M  CC18 2015 2015-04-06      CHLAC  3.2580965380     A #> 3885  2048A    3M  CC18 2015 2015-04-06      COLOR  3.6109179126  <NA> #> 3886  2048A    3M  CC18 2015 2015-04-06         DO  2.3025850930  <NA> #> 3887  2048A    3M  CC18 2015 2015-04-06      DOSAT  4.8706066495     + #> 3888  2048A    3M  CC18 2015 2015-04-06       NO23 -4.5098600062  <NA> #> 3889  2048A    3M  CC18 2015 2015-04-06      SALIN  2.7278528284  <NA> #> 3890  2048A    3M  CC18 2015 2015-04-06        TKN  0.4700036292  <NA> #> 3891  2048A    3M  CC18 2015 2015-04-06         TN  0.4768551042     + #> 3892  2048A    3M  CC18 2015 2015-04-06         TP -1.2378743560  <NA> #> 3893  2048A    3M  CC18 2015 2015-04-06       TURB  1.5892352051  <NA> #> 3894  2048A    3M  CC18 2015 2015-06-01      CHLAC  1.3083328197  <NA> #> 3895  2048A    3M  CC18 2015 2015-06-01      COLOR  3.6109179126  <NA> #> 3896  2048A    3M  CC18 2015 2015-06-01         DO  1.3609765531  <NA> #> 3897  2048A    3M  CC18 2015 2015-06-01      DOSAT  3.9834130015     + #> 3898  2048A    3M  CC18 2015 2015-06-01       NO23 -4.7105307016     I #> 3899  2048A    3M  CC18 2015 2015-06-01      SALIN  2.9285235239  <NA> #> 3900  2048A    3M  CC18 2015 2015-06-01        TKN -0.3710636814  <NA> #> 3901  2048A    3M  CC18 2015 2015-06-01         TN -0.3652833185     + #> 3902  2048A    3M  CC18 2015 2015-06-01         TP -1.5141277326  <NA> #> 3903  2048A    3M  CC18 2015 2015-06-01       TURB  0.9555114450  <NA> #> 3904  2048A    3M  CC18 2015 2015-08-03      CHLAC  1.6677068206  <NA> #> 3905  2048A    3M  CC18 2015 2015-08-03      COLOR  5.1929568509  <NA> #> 3906  2048A    3M  CC18 2015 2015-08-03       NO23 -4.5098600062  <NA> #> 3907  2048A    3M  CC18 2015 2015-08-03      SALIN  2.1282317058  <NA> #> 3908  2048A    3M  CC18 2015 2015-08-03        TKN -0.0618754037  <NA> #> 3909  2048A    3M  CC18 2015 2015-08-03         TN -0.0502412164     + #> 3910  2048A    3M  CC18 2015 2015-08-03         TP -1.4271163556  <NA> #> 3911  2048A    3M  CC18 2015 2015-08-03       TURB  0.7884573604  <NA> #> 3912  2048A    3M  CC18 2015 2015-09-08      CHLAC  1.7749523509  <NA> #> 3913  2048A    3M  CC18 2015 2015-09-08      COLOR  5.0751738152  <NA> #> 3914  2048A    3M  CC18 2015 2015-09-08         DO  1.2527629685  <NA> #> 3915  2048A    3M  CC18 2015 2015-09-08      DOSAT  3.6163087613     + #> 3916  2048A    3M  CC18 2015 2015-09-08       NO23 -2.9374633654  <NA> #> 3917  2048A    3M  CC18 2015 2015-09-08      SALIN  1.0647107370  <NA> #> 3918  2048A    3M  CC18 2015 2015-09-08        TKN  0.0000000000  <NA> #> 3919  2048A    3M  CC18 2015 2015-09-08         TN  0.0516432332     + #> 3920  2048A    3M  CC18 2015 2015-09-08         TP -1.5606477483  <NA> #> 3921  2048A    3M  CC18 2015 2015-09-08       TURB  0.0953101798  <NA> #> 3922  2048A    3M  CC18 2015 2015-10-05      CHLAC  0.6418538862  <NA> #> 3923  2048A    3M  CC18 2015 2015-10-05      COLOR  5.0751738152  <NA> #> 3924  2048A    3M  CC18 2015 2015-10-05      DOSAT  4.6091622073     + #> 3925  2048A    3M  CC18 2015 2015-10-05       NO23 -3.0576076773  <NA> #> 3926  2048A    3M  CC18 2015 2015-10-05      SALIN  1.9459101491  <NA> #> 3927  2048A    3M  CC18 2015 2015-10-05        TKN -0.0304592075  <NA> #> 3928  2048A    3M  CC18 2015 2015-10-05         TN  0.0168571171     + #> 3929  2048A    3M  CC18 2015 2015-10-05         TP -1.2039728043  <NA> #> 3930  2048A    3M  CC18 2015 2015-10-05       TURB  0.6418538862  <NA> #> 3931  2048A    3M  CC18 2015 2015-12-07      CHLAC  0.8754687374  <NA> #> 3932  2048A    3M  CC18 2015 2015-12-07      COLOR  3.9120230054  <NA> #> 3933  2048A    3M  CC18 2015 2015-12-07         DO  2.5416019935  <NA> #> 3934  2048A    3M  CC18 2015 2015-12-07       NO23 -3.4420193762  <NA> #> 3935  2048A    3M  CC18 2015 2015-12-07        TKN -0.2876820725  <NA> #> 3936  2048A    3M  CC18 2015 2015-12-07         TN -0.2459005384     + #> 3937  2048A    3M  CC18 2015 2015-12-07         TP -2.2072749132  <NA> #> 3938  2048A    3M  CC18 2015 2015-12-07       TURB  0.1823215568  <NA> #> 3939  2048A    3M  CC18 2016 2016-01-04      CHLAC  4.4188406078  <NA> #> 3940  2048A    3M  CC18 2016 2016-01-04      COLOR  3.6888794541     A #> 3941  2048A    3M  CC18 2016 2016-01-04      DOSAT  3.6888794541     + #> 3942  2048A    3M  CC18 2016 2016-01-04       NO23 -3.2968373663  <NA> #> 3943  2048A    3M  CC18 2016 2016-01-04      SALIN  2.8094026954  <NA> #> 3944  2048A    3M  CC18 2016 2016-01-04        TKN -0.1863295782  <NA> #> 3945  2048A    3M  CC18 2016 2016-01-04         TN -0.1427163022     + #> 3946  2048A    3M  CC18 2016 2016-01-04         TP -2.3025850930  <NA> #> 3947  2048A    3M  CC18 2016 2016-01-04       TURB  0.6931471806  <NA> #> 3948  2048A    3M  CC18 2016 2016-02-01      CHLAC  0.8329091229  <NA> #> 3949  2048A    3M  CC18 2016 2016-02-01      COLOR  4.4659081187  <NA> #> 3950  2048A    3M  CC18 2016 2016-02-01         DO  1.5686159179  <NA> #> 3951  2048A    3M  CC18 2016 2016-02-01      DOSAT  4.0018637094     + #> 3952  2048A    3M  CC18 2016 2016-02-01       NO23 -4.8283137373     I #> 3953  2048A    3M  CC18 2016 2016-02-01      SALIN  2.0281482473  <NA> #> 3954  2048A    3M  CC18 2016 2016-02-01        TKN -0.4155154440  <NA> #> 3955  2048A    3M  CC18 2016 2016-02-01         TN -0.4094731295     + #> 3956  2048A    3M  CC18 2016 2016-02-01         TP -2.4304184645  <NA> #> 3957  2048A    3M  CC18 2016 2016-02-01       TURB  0.2623642645     A #> 3958  2048A    3M  CC18 2016 2016-03-07      CHLAC  0.0953101798     I #> 3959  2048A    3M  CC18 2016 2016-03-07      COLOR  4.1108738642  <NA> #> 3960  2048A    3M  CC18 2016 2016-03-07      DOSAT  4.2076732475     + #> 3961  2048A    3M  CC18 2016 2016-03-07       NO23 -4.8283137373     U #> 3962  2048A    3M  CC18 2016 2016-03-07      SALIN  1.9740810260  <NA> #> 3963  2048A    3M  CC18 2016 2016-03-07         TN -0.0790432073     + #> 3964  2048A    3M  CC18 2016 2016-03-07       TURB  0.6931471806  <NA> #> 3965  2048A    3M  CC18 2016 2016-04-04      CHLAC  1.6677068206  <NA> #> 3966  2048A    3M  CC18 2016 2016-04-04      COLOR  3.8918202981  <NA> #> 3967  2048A    3M  CC18 2016 2016-04-04         DO  1.6677068206  <NA> #> 3968  2048A    3M  CC18 2016 2016-04-04      DOSAT  4.1941898972     + #> 3969  2048A    3M  CC18 2016 2016-04-04       NO23 -5.2983173665     I #> 3970  2048A    3M  CC18 2016 2016-04-04      SALIN  2.3978952728  <NA> #> 3971  2048A    3M  CC18 2016 2016-04-04        TKN -0.3011050928  <NA> #> 3972  2048A    3M  CC18 2016 2016-04-04         TN -0.2957142441     + #> 3973  2048A    3M  CC18 2016 2016-04-04         TP -1.9661128564  <NA> #> 3974  2048A    3M  CC18 2016 2016-04-04       TURB  1.0647107370  <NA> #> 3975  2048A    3M  CC18 2016 2016-05-02      CHLAC  1.1314021115  <NA> #> 3976  2048A    3M  CC18 2016 2016-05-02      COLOR  3.8918202981     A #> 3977  2048A    3M  CC18 2016 2016-05-02         DO  1.3862943611  <NA> #> 3978  2048A    3M  CC18 2016 2016-05-02      DOSAT  4.0109629533     + #> 3979  2048A    3M  CC18 2016 2016-05-02       NO23 -5.5214609179     I #> 3980  2048A    3M  CC18 2016 2016-05-02      SALIN  2.7850112422  <NA> #> 3981  2048A    3M  CC18 2016 2016-05-02        TKN -0.1984509387  <NA> #> 3982  2048A    3M  CC18 2016 2016-05-02         TN -0.1935847491     + #> 3983  2048A    3M  CC18 2016 2016-05-02         TP -1.8325814637  <NA> #> 3984  2048A    3M  CC18 2016 2016-05-02       TURB  0.3364722366  <NA> #> 3985  2048A    3M  CC18 2016 2016-07-05      CHLAC  1.4586150227  <NA> #> 3986  2048A    3M  CC18 2016 2016-07-05      COLOR  4.5747109785  <NA> #> 3987  2048A    3M  CC18 2016 2016-07-05      DOSAT  4.0758410907     + #> 3988  2048A    3M  CC18 2016 2016-07-05       NO23 -5.5214609179     I #> 3989  2048A    3M  CC18 2016 2016-07-05      SALIN  2.1400661635  <NA> #> 3990  2048A    3M  CC18 2016 2016-07-05        TKN  0.0000000000  <NA> #> 3991  2048A    3M  CC18 2016 2016-07-05         TN  0.0039920213     + #> 3992  2048A    3M  CC18 2016 2016-07-05         TP -0.9162907319  <NA> #> 3993  2048A    3M  CC18 2016 2016-07-05       TURB  0.6931471806  <NA> #> 3994  2048A    3M  CC18 2016 2016-08-01      CHLAC  1.9878743482  <NA> #> 3995  2048A    3M  CC18 2016 2016-08-01      COLOR  4.4659081187  <NA> #> 3996  2048A    3M  CC18 2016 2016-08-01       NO23 -5.2983173665     I #> 3997  2048A    3M  CC18 2016 2016-08-01      SALIN  1.9878743482  <NA> #> 3998  2048A    3M  CC18 2016 2016-08-01         TN  0.0989399479     + #> 3999  2048A    3M  CC18 2016 2016-08-01       TURB  0.6931471806  <NA> #> 4000  2048A    3M  CC18 2016 2016-10-03      CHLAC  1.9740810260  <NA> #> 4001  2048A    3M  CC18 2016 2016-10-03      COLOR  4.7004803658  <NA> #> 4002  2048A    3M  CC18 2016 2016-10-03         DO  1.8870696490  <NA> #> 4003  2048A    3M  CC18 2016 2016-10-03      DOSAT  4.4438270356     + #> 4004  2048A    3M  CC18 2016 2016-10-03       NO23 -4.8283137373     I #> 4005  2048A    3M  CC18 2016 2016-10-03      SALIN  1.4158531634  <NA> #> 4006  2048A    3M  CC18 2016 2016-10-03        TKN -0.1625189295  <NA> #> 4007  2048A    3M  CC18 2016 2016-10-03         TN -0.1578240852     + #> 4008  2048A    3M  CC18 2016 2016-10-03         TP -1.6607312068  <NA> #> 4009  2048A    3M  CC18 2016 2016-10-03       TURB  0.5306282511  <NA> #> 4010  2048A    3M  CC18 2016 2016-11-07      CHLAC  0.9932517730  <NA> #> 4011  2048A    3M  CC18 2016 2016-11-07      COLOR  3.8918202981  <NA> #> 4012  2048A    3M  CC18 2016 2016-11-07      DOSAT  3.8501476017     + #> 4013  2048A    3M  CC18 2016 2016-11-07       NO23 -4.1997050779  <NA> #> 4014  2048A    3M  CC18 2016 2016-11-07      SALIN  3.0773122605  <NA> #> 4015  2048A    3M  CC18 2016 2016-11-07        TKN -0.3011050928  <NA> #> 4016  2048A    3M  CC18 2016 2016-11-07         TN -0.2810375297     + #> 4017  2048A    3M  CC18 2016 2016-11-07         TP -1.8971199849  <NA> #> 4018  2048A    3M  CC18 2016 2016-11-07       TURB  1.1939224685  <NA> #> 4019  2048A    3M  CC18 2016 2016-12-05      CHLAC  0.9555114450     I #> 4020  2048A    3M  CC18 2016 2016-12-05      COLOR  3.4657359028  <NA> #> 4021  2048A    3M  CC18 2016 2016-12-05         DO  0.9555114450  <NA> #> 4022  2048A    3M  CC18 2016 2016-12-05      DOSAT  3.5263605246     + #> 4023  2048A    3M  CC18 2016 2016-12-05       NO23 -4.2686979494  <NA> #> 4024  2048A    3M  CC18 2016 2016-12-05      SALIN  3.0726933147  <NA> #> 4025  2048A    3M  CC18 2016 2016-12-05        TKN -0.4780358009  <NA> #> 4026  2048A    3M  CC18 2016 2016-12-05         TN -0.4557063245     + #> 4027  2048A    3M  CC18 2016 2016-12-05         TP -2.4191189092  <NA> #> 4028  2048A    3M  CC18 2016 2016-12-05       TURB  0.6418538862  <NA> #> 4029  2048A    3M  CC18 2017 2017-01-03      CHLAC  0.7884573604  <NA> #> 4030  2048A    3M  CC18 2017 2017-01-03      COLOR  3.2580965380     A #> 4031  2048A    3M  CC18 2017 2017-01-03      DOSAT  3.7999735016     + #> 4032  2048A    3M  CC18 2017 2017-01-03       NO23 -4.3428059215  <NA> #> 4033  2048A    3M  CC18 2017 2017-01-03      SALIN  3.1135153092  <NA> #> 4034  2048A    3M  CC18 2017 2017-01-03        TKN -0.4004775666  <NA> #> 4035  2048A    3M  CC18 2017 2017-01-03         TN -0.3812604194     + #> 4036  2048A    3M  CC18 2017 2017-01-03         TP -2.1202635362  <NA> #> 4037  2048A    3M  CC18 2017 2017-01-03       TURB  1.2809338455  <NA> #> 4038  2048A    3M  CC18 2017 2017-02-06      CHLAC  1.4816045409  <NA> #> 4039  2048A    3M  CC18 2017 2017-02-06      COLOR  3.2188758249  <NA> #> 4040  2048A    3M  CC18 2017 2017-02-06      DOSAT  3.7999735016     + #> 4041  2048A    3M  CC18 2017 2017-02-06       NO23 -4.7105307016     I #> 4042  2048A    3M  CC18 2017 2017-02-06      SALIN  3.1135153092  <NA> #> 4043  2048A    3M  CC18 2017 2017-02-06        TKN -0.3011050928  <NA> #> 4044  2048A    3M  CC18 2017 2017-02-06         TN -0.2957142441     + #> 4045  2048A    3M  CC18 2017 2017-02-06         TP -2.3126354288  <NA> #> 4046  2048A    3M  CC18 2017 2017-02-06       TURB  1.0647107370  <NA> #> 4047  2048A    3M  CC18 2017 2017-03-06      CHLAC  1.6677068206  <NA> #> 4048  2048A    3M  CC18 2017 2017-03-06      COLOR  3.0445224377  <NA> #> 4049  2048A    3M  CC18 2017 2017-03-06         DO  2.0541237337  <NA> #> 4050  2048A    3M  CC18 2017 2017-03-06      DOSAT  4.6071681887     + #> 4051  2048A    3M  CC18 2017 2017-03-06       NO23 -5.5214609179     U #> 4052  2048A    3M  CC18 2017 2017-03-06      SALIN  3.2921262866  <NA> #> 4053  2048A    3M  CC18 2017 2017-03-06        TKN -0.3011050928  <NA> #> 4054  2048A    3M  CC18 2017 2017-03-06         TN -0.2984060358     + #> 4055  2048A    3M  CC18 2017 2017-03-06         TP -2.6592600369  <NA> #> 4056  2048A    3M  CC18 2017 2017-03-06       TURB  1.0986122887  <NA> #> 4057  2048A    3M  CC18 2017 2017-04-03      CHLAC  1.5892352051  <NA> #> 4058  2048A    3M  CC18 2017 2017-04-03      COLOR  3.1354942159  <NA> #> 4059  2048A    3M  CC18 2017 2017-04-03         DO  1.7749523509  <NA> #> 4060  2048A    3M  CC18 2017 2017-04-03      DOSAT  4.3040650932     + #> 4061  2048A    3M  CC18 2017 2017-04-03       NO23 -4.7105307016     I #> 4062  2048A    3M  CC18 2017 2017-04-03      SALIN  1.5260563035  <NA> #> 4063  2048A    3M  CC18 2017 2017-04-03         TN -0.2691874898     + #> 4064  2048A    3M  CC18 2017 2017-04-03       TURB  0.9555114450  <NA> #> 4065  2048A    3M  CC18 2017 2017-05-01      CHLAC  2.2407096893     A #> 4066  2048A    3M  CC18 2017 2017-05-01      COLOR  3.4011973817     A #> 4067  2048A    3M  CC18 2017 2017-05-01         DO  1.9169226122  <NA> #> 4068  2048A    3M  CC18 2017 2017-05-01      DOSAT  4.6061696863     + #> 4069  2048A    3M  CC18 2017 2017-05-01       NO23 -5.5214609179     U #> 4070  2048A    3M  CC18 2017 2017-05-01      SALIN  3.4210000090  <NA> #> 4071  2048A    3M  CC18 2017 2017-05-01        TKN  0.0953101798  <NA> #> 4072  2048A    3M  CC18 2017 2017-05-01         TN  0.0971267107     + #> 4073  2048A    3M  CC18 2017 2017-05-01         TP -2.1202635362  <NA> #> 4074  2048A    3M  CC18 2017 2017-05-01       TURB  1.3609765531  <NA> #> 4075  2048A    3M  CC18 2017 2017-06-05      CHLAC  1.4350845253  <NA> #> 4076  2048A    3M  CC18 2017 2017-06-05      COLOR  3.6635616461  <NA> #> 4077  2048A    3M  CC18 2017 2017-06-05         DO  1.8870696490  <NA> #> 4078  2048A    3M  CC18 2017 2017-06-05      DOSAT  4.6141299274     + #> 4079  2048A    3M  CC18 2017 2017-06-05       NO23 -5.2983173665     I #> 4080  2048A    3M  CC18 2017 2017-06-05      SALIN  3.4843122884  <NA> #> 4081  2048A    3M  CC18 2017 2017-06-05         TN -0.1461825102     + #> 4082  2048A    3M  CC18 2017 2017-06-05       TURB  0.8754687374  <NA> #> 4083  2048A    3M  CC18 2017 2017-07-10      CHLAC  2.0281482473  <NA> #> 4084  2048A    3M  CC18 2017 2017-07-10      COLOR  5.1357984371  <NA> #> 4085  2048A    3M  CC18 2017 2017-07-10         DO  0.8754687374  <NA> #> 4086  2048A    3M  CC18 2017 2017-07-10      DOSAT  3.4904285154     + #> 4087  2048A    3M  CC18 2017 2017-07-10      SALIN  2.3513752572  <NA> #> 4088  2048A    3M  CC18 2017 2017-07-10         TN  0.2768738737     + #> 4089  2048A    3M  CC18 2017 2017-07-10       TURB  0.6931471806  <NA> #> 4090  2048A    3M  CC18 2017 2017-08-07      CHLAC  0.7419373447  <NA> #> 4091  2048A    3M  CC18 2017 2017-08-07      COLOR  5.3471075307  <NA> #> 4092  2048A    3M  CC18 2017 2017-08-07      DOSAT  2.9123506646     + #> 4093  2048A    3M  CC18 2017 2017-08-07       NO23 -2.6592600369  <NA> #> 4094  2048A    3M  CC18 2017 2017-08-07      SALIN  0.9162907319  <NA> #> 4095  2048A    3M  CC18 2017 2017-08-07        TKN  0.1823215568  <NA> #> 4096  2048A    3M  CC18 2017 2017-08-07         TN  0.2390169005     + #> 4097  2048A    3M  CC18 2017 2017-08-07         TP -1.3470736480  <NA> #> 4098  2048A    3M  CC18 2017 2017-08-07       TURB  1.0296194172  <NA> #> 4099  2048A    3M  CC18 2017 2017-09-05      CHLAC  2.2512917986  <NA> #> 4100  2048A    3M  CC18 2017 2017-09-05      COLOR  5.2470240722  <NA> #> 4101  2048A    3M  CC18 2017 2017-09-05         DO  2.2721258855  <NA> #> 4102  2048A    3M  CC18 2017 2017-09-05      DOSAT  4.8354879411     + #> 4103  2048A    3M  CC18 2017 2017-09-05       NO23 -3.2968373663  <NA> #> 4104  2048A    3M  CC18 2017 2017-09-05      SALIN  1.1631508098  <NA> #> 4105  2048A    3M  CC18 2017 2017-09-05        TKN  0.0000000000  <NA> #> 4106  2048A    3M  CC18 2017 2017-09-05         TN  0.0363319292     + #> 4107  2048A    3M  CC18 2017 2017-09-05         TP -1.8971199849  <NA> #> 4108  2048A    3M  CC18 2017 2017-09-05       TURB  0.7419373447  <NA> #> 4109  2048A    3M  CC18 2017 2017-11-06      CHLAC  1.2809338455  <NA> #> 4110  2048A    3M  CC18 2017 2017-11-06      COLOR  4.3307333403  <NA> #> 4111  2048A    3M  CC18 2017 2017-11-06         DO  2.0412203289  <NA> #> 4112  2048A    3M  CC18 2017 2017-11-06       NO23 -4.3428059215  <NA> #> 4113  2048A    3M  CC18 2017 2017-11-06      SALIN  2.2721258855  <NA> #> 4114  2048A    3M  CC18 2017 2017-11-06        TKN -0.3285040670  <NA> #> 4115  2048A    3M  CC18 2017 2017-11-06         TN -0.3106095771     + #> 4116  2048A    3M  CC18 2017 2017-11-06         TP -1.8325814637  <NA> #> 4117  2048A    3M  CC18 2017 2017-11-06       TURB  0.3364722366  <NA> #> 4118  2048A    3M  CC18 2017 2017-12-04      CHLAC  0.8329091229  <NA> #> 4119  2048A    3M  CC18 2017 2017-12-04      COLOR  3.8066624898  <NA> #> 4120  2048A    3M  CC18 2017 2017-12-04         DO  2.0794415417  <NA> #> 4121  2048A    3M  CC18 2017 2017-12-04      DOSAT  4.6700211583     + #> 4122  2048A    3M  CC18 2017 2017-12-04       NO23 -5.5214609179     U #> 4123  2048A    3M  CC18 2017 2017-12-04      SALIN  3.3214324132  <NA> #> 4124  2048A    3M  CC18 2017 2017-12-04        TKN -0.2876820725  <NA> #> 4125  2048A    3M  CC18 2017 2017-12-04         TN -0.2850189550     + #> 4126  2048A    3M  CC18 2017 2017-12-04         TP -2.2072749132  <NA> #> 4127  2048A    3M  CC18 2017 2017-12-04       TURB -0.1625189295  <NA> #> 4128  2048A    3M  CC18 2018 2018-01-02      CHLAC  1.5475625087  <NA> #> 4129  2048A    3M  CC18 2018 2018-01-02      COLOR  3.4965075615  <NA> #> 4130  2048A    3M  CC18 2018 2018-01-02      DOSAT  4.3161538905     + #> 4131  2048A    3M  CC18 2018 2018-01-02       NO23 -5.5214609179     U #> 4132  2048A    3M  CC18 2018 2018-01-02      SALIN  2.4248027257  <NA> #> 4133  2048A    3M  CC18 2018 2018-01-02         TN -0.4910229965     + #> 4134  2048A    3M  CC18 2018 2018-01-02       TURB  0.5877866649  <NA> #> 4135  2048A    3M  CC18 2018 2018-03-05      CHLAC  0.8329091229  <NA> #> 4136  2048A    3M  CC18 2018 2018-03-05      COLOR  3.5835189385  <NA> #> 4137  2048A    3M  CC18 2018 2018-03-05       NO23 -5.5214609179     U #> 4138  2048A    3M  CC18 2018 2018-03-05        TKN -0.3011050928  <NA> #> 4139  2048A    3M  CC18 2018 2018-03-05         TN -0.2984060358     + #> 4140  2048A    3M  CC18 2018 2018-03-05         TP -1.8971199849  <NA> #> 4141  2048A    3M  CC18 2018 2018-03-05       TURB  1.0296194172  <NA> #> 4142  2048A    3M  CC18 2018 2018-04-02      CHLAC  1.6677068206  <NA> #> 4143  2048A    3M  CC18 2018 2018-04-02      COLOR  3.3322045102  <NA> #> 4144  2048A    3M  CC18 2018 2018-04-02      DOSAT  4.2513483110     + #> 4145  2048A    3M  CC18 2018 2018-04-02       NO23 -5.2983173665     I #> 4146  2048A    3M  CC18 2018 2018-04-02      SALIN  3.2027464429  <NA> #> 4147  2048A    3M  CC18 2018 2018-04-02        TKN -0.2613647641  <NA> #> 4148  2048A    3M  CC18 2018 2018-04-02         TN -0.2561834054     + #> 4149  2048A    3M  CC18 2018 2018-04-02         TP -1.9661128564  <NA> #> 4150  2048A    3M  CC18 2018 2018-04-02       TURB  1.3083328197  <NA> #> 4151  2048A    3M  CC18 2018 2018-05-07      CHLAC  1.8562979904  <NA> #> 4152  2048A    3M  CC18 2018 2018-05-07      COLOR  3.3322045102     A #> 4153  2048A    3M  CC18 2018 2018-05-07         DO  2.1016921506  <NA> #> 4154  2048A    3M  CC18 2018 2018-05-07      DOSAT  4.6051701860  <NA> #> 4155  2048A    3M  CC18 2018 2018-05-07       NO23 -5.5214609179     I #> 4156  2048A    3M  CC18 2018 2018-05-07      SALIN  3.2812870850  <NA> #> 4157  2048A    3M  CC18 2018 2018-05-07        TKN -0.0943106795  <NA> #> 4158  2048A    3M  CC18 2018 2018-05-07         TN -0.0899247075     + #> 4159  2048A    3M  CC18 2018 2018-05-07         TP -2.2072749132  <NA> #> 4160  2048A    3M  CC18 2018 2018-05-07       TURB  1.2527629685  <NA> #> 4161  2048A    3M  CC18 2018 2018-06-04      CHLAC  1.8405496334  <NA> #> 4162  2048A    3M  CC18 2018 2018-06-04      COLOR  4.6051701860  <NA> #> 4163  2048A    3M  CC18 2018 2018-06-04         DO  2.0906287311  <NA> #> 4164  2048A    3M  CC18 2018 2018-06-04      DOSAT  4.6011621646  <NA> #> 4165  2048A    3M  CC18 2018 2018-06-04       NO23 -4.6051701860     I #> 4166  2048A    3M  CC18 2018 2018-06-04      SALIN  1.8115620965  <NA> #> 4167  2048A    3M  CC18 2018 2018-06-04        TKN -0.0725706928  <NA> #> 4168  2048A    3M  CC18 2018 2018-06-04         TN -0.0682788408     + #> 4169  2048A    3M  CC18 2018 2018-06-04         TP -1.6094379124  <NA> #> 4170  2048A    3M  CC18 2018 2018-06-04       TURB  0.5306282511  <NA> #> 4171  2048A    3M  CC18 2018 2018-07-09      CHLAC  2.4849066498  <NA> #> 4172  2048A    3M  CC18 2018 2018-07-09      COLOR  4.9416424226  <NA> #> 4173  2048A    3M  CC18 2018 2018-07-09         DO  1.4929040962  <NA> #> 4174  2048A    3M  CC18 2018 2018-07-09      DOSAT  4.1415461637  <NA> #> 4175  2048A    3M  CC18 2018 2018-07-09       NO23 -4.9618451299     I #> 4176  2048A    3M  CC18 2018 2018-07-09      SALIN  1.3402504226  <NA> #> 4177  2048A    3M  CC18 2018 2018-07-09        TKN -0.2231435513  <NA> #> 4178  2048A    3M  CC18 2018 2018-07-09         TN -0.2181560098     + #> 4179  2048A    3M  CC18 2018 2018-07-09         TP -1.7719568419  <NA> #> 4180  2048A    3M  CC18 2018 2018-07-09       TURB  0.8754687374  <NA> #> 4181  2048A    3M  CC18 2019 2019-05-06      CHLAC  0.9555114450  <NA> #> 4182  2048A    3M  CC18 2019 2019-05-06      COLOR  3.6109179126  <NA> #> 4183  2048A    3M  CC18 2019 2019-05-06         DO  0.8837675402  <NA> #> 4184  2048A    3M  CC18 2019 2019-05-06      DOSAT  3.5351453542  <NA> #> 4185  2048A    3M  CC18 2019 2019-05-06       NO23 -5.2983173665     I #> 4186  2048A    3M  CC18 2019 2019-05-06      SALIN  2.9719517449  <NA> #> 4187  2048A    3M  CC18 2019 2019-05-06        TKN -0.2744368457  <NA> #> 4188  2048A    3M  CC18 2019 2019-05-06         TN -0.2691874898     + #> 4189  2048A    3M  CC18 2019 2019-05-06         TP -1.7719568419  <NA> #> 4190  2048A    3M  CC18 2019 2019-05-06       TURB  0.7419373447  <NA> #> 4191  2048A    3M  CC18 2019 2019-06-03      CHLAC  1.5686159179  <NA> #> 4192  2048A    3M  CC18 2019 2019-06-03      COLOR  3.7376696183  <NA> #> 4193  2048A    3M  CC18 2019 2019-06-03         DO  0.6418538862  <NA> #> 4194  2048A    3M  CC18 2019 2019-06-03      DOSAT  3.3322045102  <NA> #> 4195  2048A    3M  CC18 2019 2019-06-03       NO23 -5.5214609179     U #> 4196  2048A    3M  CC18 2019 2019-06-03      SALIN  3.0363942553  <NA> #> 4197  2048A    3M  CC18 2019 2019-06-03        TKN -0.0725706928  <NA> #> 4198  2048A    3M  CC18 2019 2019-06-03         TN -0.0704224643     + #> 4199  2048A    3M  CC18 2019 2019-06-03         TP -1.3470736480  <NA> #> 4200  2048A    3M  CC18 2019 2019-06-03       TURB  1.4586150227     A #> 4201  2048A    3M  CC18 2019 2019-07-01      CHLAC  1.6863989536  <NA> #> 4202  2048A    3M  CC18 2019 2019-07-01      COLOR  3.6635616461  <NA> #> 4203  2048A    3M  CC18 2019 2019-07-01         DO  0.9162907319  <NA> #> 4204  2048A    3M  CC18 2019 2019-07-01      DOSAT  3.4483989831  <NA> #> 4205  2048A    3M  CC18 2019 2019-07-01       NO23 -5.5214609179     U #> 4206  2048A    3M  CC18 2019 2019-07-01      SALIN  2.9678470701  <NA> #> 4207  2048A    3M  CC18 2019 2019-07-01        TKN -0.2484613593  <NA> #> 4208  2048A    3M  CC18 2019 2019-07-01         TN -0.2459005384     + #> 4209  2048A    3M  CC18 2019 2019-07-01         TP -1.2729656758  <NA> #> 4210  2048A    3M  CC18 2019 2019-07-01       TURB  0.4054651081  <NA> #> 4211  2048A    3M  CC18 2019 2019-08-05      CHLAC  1.4109869737  <NA> #> 4212  2048A    3M  CC18 2019 2019-08-05      COLOR  5.0751738152  <NA> #> 4213  2048A    3M  CC18 2019 2019-08-05         DO  1.1378330018  <NA> #> 4214  2048A    3M  CC18 2019 2019-08-05      DOSAT  3.7305011288  <NA> #> 4215  2048A    3M  CC18 2019 2019-08-05       NO23 -5.5214609179     I #> 4216  2048A    3M  CC18 2019 2019-08-05      SALIN  1.6134299337  <NA> #> 4217  2048A    3M  CC18 2019 2019-08-05        TKN -0.0618754037  <NA> #> 4218  2048A    3M  CC18 2019 2019-08-05         TN -0.0576291128     + #> 4219  2048A    3M  CC18 2019 2019-08-05         TP -1.5606477483  <NA> #> 4220  2048A    3M  CC18 2019 2019-08-05       TURB  0.8754687374  <NA> #> 4221  2048A    3M  CC18 2019 2019-10-07      CHLAC  1.0986122887     I #> 4222  2048A    3M  CC18 2019 2019-10-07      COLOR  4.3820266347  <NA> #> 4223  2048A    3M  CC18 2019 2019-10-07         DO  1.0152306797  <NA> #> 4224  2048A    3M  CC18 2019 2019-10-07      DOSAT  3.6375861597  <NA> #> 4225  2048A    3M  CC18 2019 2019-10-07       NO23 -4.9618451299     I #> 4226  2048A    3M  CC18 2019 2019-10-07      SALIN  2.7389026646  <NA> #> 4227  2048A    3M  CC18 2019 2019-10-07        TKN -0.1278333715  <NA> #> 4228  2048A    3M  CC18 2019 2019-10-07         TN -0.1232982163     + #> 4229  2048A    3M  CC18 2019 2019-10-07         TP -1.3862943611  <NA> #> 4230  2048A    3M  CC18 2019 2019-10-07       TURB  0.4054651081  <NA> #> 4231  2048A    3M  CC18 2019 2019-11-04      CHLAC  1.0296194172  <NA> #> 4232  2048A    3M  CC18 2019 2019-11-04      COLOR  4.1431347264  <NA> #> 4233  2048A    3M  CC18 2019 2019-11-04         DO  1.2267122913  <NA> #> 4234  2048A    3M  CC18 2019 2019-11-04      DOSAT  3.8177123260  <NA> #> 4235  2048A    3M  CC18 2019 2019-11-04       NO23 -5.5214609179     I #> 4236  2048A    3M  CC18 2019 2019-11-04      SALIN  2.8075938314  <NA> #> 4237  2048A    3M  CC18 2019 2019-11-04        TKN -0.1508228897  <NA> #> 4238  2048A    3M  CC18 2019 2019-11-04         TN -0.1461825102     + #> 4239  2048A    3M  CC18 2019 2019-11-04         TP -1.6094379124  <NA> #> 4240  2048A    3M  CC18 2019 2019-11-04       TURB  0.2623642645     A #> 4241  2048A    3M  CC18 2019 2019-11-04         DO  1.2267122913  <NA> #> 4242  2048A    3M  CC18 2019 2019-11-04      DOSAT  3.8177123260  <NA> #> 4243  2048A    3M  CC18 2019 2019-11-04      SALIN  2.8075938314  <NA> #> 4244  2048A    3M  CC18 2019 2019-12-02      CHLAC  1.2809338455  <NA> #> 4245  2048A    3M  CC18 2019 2019-12-02      COLOR  3.6888794541     A #> 4246  2048A    3M  CC18 2019 2019-12-02         DO  1.5518087996  <NA> #> 4247  2048A    3M  CC18 2019 2019-12-02      DOSAT  4.1059436981  <NA> #> 4248  2048A    3M  CC18 2019 2019-12-02       NO23 -5.5214609179     U #> 4249  2048A    3M  CC18 2019 2019-12-02      SALIN  2.9412760878  <NA> #> 4250  2048A    3M  CC18 2019 2019-12-02        TKN -0.2613647641  <NA> #> 4251  2048A    3M  CC18 2019 2019-12-02         TN -0.2587707290     + #> 4252  2048A    3M  CC18 2019 2019-12-02         TP -2.2072749132  <NA> #> 4253  2048A    3M  CC18 2019 2019-12-02       TURB  0.0953101798  <NA> #> 4254  2048A    3M  CC18 2020 2020-01-06      CHLAC  1.7578579176  <NA> #> 4255  2048A    3M  CC18 2020 2020-01-06      COLOR  3.5263605246  <NA> #> 4256  2048A    3M  CC18 2020 2020-01-06         DO  1.6770965609  <NA> #> 4257  2048A    3M  CC18 2020 2020-01-06      DOSAT  4.1541845626  <NA> #> 4258  2048A    3M  CC18 2020 2020-01-06       NO23 -5.5214609179     U #> 4259  2048A    3M  CC18 2020 2020-01-06      SALIN  2.8713021952  <NA> #> 4260  2048A    3M  CC18 2020 2020-01-06        TKN -0.5276327421  <NA> #> 4261  2048A    3M  CC18 2020 2020-01-06         TN -0.5242486441     + #> 4262  2048A    3M  CC18 2020 2020-01-06         TP -1.8971199849  <NA> #> 4263  2048A    3M  CC18 2020 2020-01-06       TURB  0.3364722366  <NA> #> 4264  2048A    3M  CC18 2020 2020-02-03      CHLAC  2.6390573296  <NA> #> 4265  2048A    3M  CC18 2020 2020-02-03      COLOR  3.3672958300  <NA> #> 4266  2048A    3M  CC18 2020 2020-02-03         DO  1.7137979278  <NA> #> 4267  2048A    3M  CC18 2020 2020-02-03      DOSAT  4.1941898972  <NA> #> 4268  2048A    3M  CC18 2020 2020-02-03       NO23 -4.8283137373     I #> 4269  2048A    3M  CC18 2020 2020-02-03      SALIN  2.9538680695  <NA> #> 4270  2048A    3M  CC18 2020 2020-02-03        TKN -0.0725706928  <NA> #> 4271  2048A    3M  CC18 2020 2020-02-03         TN -0.0682788408     + #> 4272  2048A    3M  CC18 2020 2020-02-03         TP -1.9661128564  <NA> #> 4273  2048A    3M  CC18 2020 2020-02-03       TURB  2.1400661635  <NA> #> 4274  2048A    3M  CC18 2020 2020-03-02      CHLAC  1.8562979904  <NA> #> 4275  2048A    3M  CC18 2020 2020-03-02      COLOR  3.2958368660  <NA> #> 4276  2048A    3M  CC18 2020 2020-03-02         DO  2.1388890003  <NA> #> 4277  2048A    3M  CC18 2020 2020-03-02      DOSAT  4.6530075154  <NA> #> 4278  2048A    3M  CC18 2020 2020-03-02       NO23 -5.5214609179     I #> 4279  2048A    3M  CC18 2020 2020-03-02      SALIN  3.0061775314  <NA> #> 4280  2048A    3M  CC18 2020 2020-03-02        TKN -0.3710636814  <NA> #> 4281  2048A    3M  CC18 2020 2020-03-02         TN -0.3652833185     + #> 4282  2048A    3M  CC18 2020 2020-03-02         TP -2.3025850930  <NA> #> 4283  2048A    3M  CC18 2020 2020-03-02       TURB  1.3609765531  <NA> #> 4284  2048A    3M  CC18 2020 2020-09-08      CHLAC  1.2809338455  <NA> #> 4285  2048A    3M  CC18 2020 2020-09-08      COLOR  4.5432947823  <NA> #> 4286  2048A    3M  CC18 2020 2020-09-08         DO  0.6418538862  <NA> #> 4287  2048A    3M  CC18 2020 2020-09-08      DOSAT  3.2809112158  <NA> #> 4288  2048A    3M  CC18 2020 2020-09-08       NO23 -4.3428059215  <NA> #> 4289  2048A    3M  CC18 2020 2020-09-08      SALIN  2.8237570088  <NA> #> 4290  2048A    3M  CC18 2020 2020-09-08        TKN -0.2231435513  <NA> #> 4291  2048A    3M  CC18 2020 2020-09-08         TN -0.2070241694     + #> 4292  2048A    3M  CC18 2020 2020-09-08         TP -1.3470736480  <NA> #> 4293  2048A    3M  CC18 2020 2020-09-08       TURB  0.9555114450  <NA> #> 4294  2048A    3M  CC18 2020 2020-10-05         DO  1.0885619528  <NA> #> 4295  2048A    3M  CC18 2020 2020-10-05      DOSAT  3.6323091026  <NA> #> 4296  2048A    3M  CC18 2020 2020-10-05       NO23 -3.3524072175  <NA> #> 4297  2048A    3M  CC18 2020 2020-10-05        TKN  0.0000000000  <NA> #> 4298  2048A    3M  CC18 2020 2020-10-05         TN  0.0344014267     + #> 4299  2048A    3M  CC18 2020 2020-10-05         TP -1.4696759701  <NA> #> 4300  2048A    3M  CC18 2020 2020-11-02      CHLAC  1.4816045409     I #> 4301  2048A    3M  CC18 2020 2020-11-02      COLOR  4.7004803658  <NA> #> 4302  2048A    3M  CC18 2020 2020-11-02         DO  1.1631508098  <NA> #> 4303  2048A    3M  CC18 2020 2020-11-02      DOSAT  3.7376696183  <NA> #> 4304  2048A    3M  CC18 2020 2020-11-02       NO23 -3.0365542681  <NA> #> 4305  2048A    3M  CC18 2020 2020-11-02      SALIN  2.2884861686  <NA> #> 4306  2048A    3M  CC18 2020 2020-11-02        TKN -0.1743533871  <NA> #> 4307  2048A    3M  CC18 2020 2020-11-02         TN -0.1187835360     + #> 4308  2048A    3M  CC18 2020 2020-11-02         TP -1.4271163556  <NA> #> 4309  2048A    3M  CC18 2020 2020-11-02       TURB  0.8329091229  <NA> #> 4310  2048A    3M  CC18 2020 2020-12-07      CHLAC  0.6931471806     I #> 4311  2048A    3M  CC18 2020 2020-12-07      COLOR  4.2195077052  <NA> #> 4312  2048A    3M  CC18 2020 2020-12-07         DO  1.7783364489  <NA> #> 4313  2048A    3M  CC18 2020 2020-12-07      DOSAT  4.2297491992  <NA> #> 4314  2048A    3M  CC18 2020 2020-12-07       NO23 -4.6051701860  <NA> #> 4315  2048A    3M  CC18 2020 2020-12-07      SALIN  2.8870328566  <NA> #> 4316  2048A    3M  CC18 2020 2020-12-07        TKN -0.0202027073  <NA> #> 4317  2048A    3M  CC18 2020 2020-12-07         TN -0.0100503359     + #> 4318  2048A    3M  CC18 2020 2020-12-07         TP -1.7719568419  <NA> #> 4319  2048A    3M  CC18 2020 2020-12-07       TURB  1.4350845253  <NA> #> 4320  2048A    3M  CC18 2021 2021-01-04      CHLAC  0.5306282511     I #> 4321  2048A    3M  CC18 2021 2021-01-04      COLOR  3.9120230054     A #> 4322  2048A    3M  CC18 2021 2021-01-04       NO23 -5.1159958098     I #> 4323  2048A    3M  CC18 2021 2021-01-04      SALIN  2.6518325211  <NA> #> 4324  2048A    3M  CC18 2021 2021-01-04        TKN -0.2231435513  <NA> #> 4325  2048A    3M  CC18 2021 2021-01-04         TN -0.2181560098     + #> 4326  2048A    3M  CC18 2021 2021-01-04         TP -2.3025850930  <NA> #> 4327  2048A    3M  CC18 2021 2021-01-04       TURB  0.1823215568  <NA> #> 4328  2048A    3M  CC18 2021 2021-02-01      CHLAC  0.8329091229     I #> 4329  2048A    3M  CC18 2021 2021-02-01      COLOR  3.5553480615  <NA> #> 4330  2048A    3M  CC18 2021 2021-02-01       NO23 -5.5214609179     U #> 4331  2048A    3M  CC18 2021 2021-02-01      SALIN  2.8219739474  <NA> #> 4332  2048A    3M  CC18 2021 2021-02-01        TKN -0.4462871026  <NA> #> 4333  2048A    3M  CC18 2021 2021-02-01         TN -0.4431669753     + #> 4334  2048A    3M  CC18 2021 2021-02-01         TP -2.3025850930  <NA> #> 4335  2048A    3M  CC18 2021 2021-02-01       TURB  0.0000000000  <NA> #> 4336  2048A    3M  CC18 2021 2021-03-01      CHLAC  1.3350010667  <NA> #> 4337  2048A    3M  CC18 2021 2021-03-01      COLOR  3.6109179126  <NA> #> 4338  2048A    3M  CC18 2021 2021-03-01       NO23 -4.9618451299     I #> 4339  2048A    3M  CC18 2021 2021-03-01        TKN -0.5276327421  <NA> #> 4340  2048A    3M  CC18 2021 2021-03-01         TN -0.5208759596     + #> 4341  2048A    3M  CC18 2021 2021-03-01         TP -2.0402208285  <NA> #> 4342  2048A    3M  CC18 2021 2021-03-01       TURB  0.8329091229  <NA> #> 4343  2048A    3M  CC18 2021 2021-04-05      CHLAC  0.4700036292     I #> 4344  2048A    3M  CC18 2021 2021-04-05      COLOR  3.3672958300  <NA> #> 4345  2048A    3M  CC18 2021 2021-04-05         DO  1.8245492921  <NA> #> 4346  2048A    3M  CC18 2021 2021-04-05      DOSAT  4.3870141762  <NA> #> 4347  2048A    3M  CC18 2021 2021-04-05       NO23 -5.2983173665     I #> 4348  2048A    3M  CC18 2021 2021-04-05      SALIN  3.1170645587  <NA> #> 4349  2048A    3M  CC18 2021 2021-04-05        TKN -0.4155154440  <NA> #> 4350  2048A    3M  CC18 2021 2021-04-05         TN -0.4094731295     + #> 4351  2048A    3M  CC18 2021 2021-04-05         TP -2.3434070875  <NA> #> 4352  2048A    3M  CC18 2021 2021-04-05       TURB  0.3364722366  <NA> #> 4353  2048A    3M  CC18 2021 2021-05-03      CHLAC  1.5475625087  <NA> #> 4354  2048A    3M  CC18 2021 2021-05-03      COLOR  3.4339872045     A #> 4355  2048A    3M  CC18 2021 2021-05-03         DO  1.4182774070  <NA> #> 4356  2048A    3M  CC18 2021 2021-05-03      DOSAT  4.1174098352  <NA> #> 4357  2048A    3M  CC18 2021 2021-05-03       NO23 -5.5214609179     I #> 4358  2048A    3M  CC18 2021 2021-05-03      SALIN  3.1726224404  <NA> #> 4359  2048A    3M  CC18 2021 2021-05-03        TKN -0.3566749439  <NA> #> 4360  2048A    3M  CC18 2021 2021-05-03         TN -0.3509769228     + #> 4361  2048A    3M  CC18 2021 2021-05-03         TP -1.8325814637  <NA> #> 4362  2048A    3M  CC18 2021 2021-05-03       TURB  0.5877866649  <NA> #> 4363  2048A    3M  CC18 2021 2021-06-07      CHLAC  1.5686159179     I #> 4364  2048A    3M  CC18 2021 2021-06-07      COLOR  3.5835189385  <NA> #> 4365  2048A    3M  CC18 2021 2021-06-07         DO  1.0508216248  <NA> #> 4366  2048A    3M  CC18 2021 2021-06-07      DOSAT  4.2918283668  <NA> #> 4367  2048A    3M  CC18 2021 2021-06-07       NO23 -5.2983173665     I #> 4368  2048A    3M  CC18 2021 2021-06-07      SALIN  3.2476576263  <NA> #> 4369  2048A    3M  CC18 2021 2021-06-07        TKN -0.2484613593  <NA> #> 4370  2048A    3M  CC18 2021 2021-06-07         TN -0.2433462586     + #> 4371  2048A    3M  CC18 2021 2021-06-07         TP -1.5141277326  <NA> #> 4372  2048A    3M  CC18 2021 2021-06-07       TURB  0.5306282511  <NA> #> 4373  2048A    3M  CC18 2021 2021-08-02      CHLAC  1.8082887712  <NA> #> 4374  2048A    3M  CC18 2021 2021-08-02      COLOR  5.0106352941  <NA> #> 4375  2048A    3M  CC18 2021 2021-08-02         DO  0.0582689081  <NA> #> 4376  2048A    3M  CC18 2021 2021-08-02      DOSAT  2.7080502011  <NA> #> 4377  2048A    3M  CC18 2021 2021-08-02       NO23 -5.5214609179     U #> 4378  2048A    3M  CC18 2021 2021-08-02      SALIN  1.8702625307  <NA> #> 4379  2048A    3M  CC18 2021 2021-08-02        TKN  0.0953101798  <NA> #> 4380  2048A    3M  CC18 2021 2021-08-02         TN  0.0971267107     + #> 4381  2048A    3M  CC18 2021 2021-08-02         TP -0.9416085399  <NA> #> 4382  2048A    3M  CC18 2021 2021-08-02       TURB  1.0986122887     A #> 4383  2048A    3M  CC18 2021 2021-09-07      CHLAC  1.7917594692  <NA> #> 4384  2048A    3M  CC18 2021 2021-09-07      COLOR  4.9416424226  <NA> #> 4385  2048A    3M  CC18 2021 2021-09-07       NO23 -3.6888794541  <NA> #> 4386  2048A    3M  CC18 2021 2021-09-07      SALIN  1.5581446180  <NA> #> 4387  2048A    3M  CC18 2021 2021-09-07        TKN -0.0725706928  <NA> #> 4388  2048A    3M  CC18 2021 2021-09-07         TN -0.0460439385     + #> 4389  2048A    3M  CC18 2021 2021-09-07         TP -1.6094379124  <NA> #> 4390  2048A    3M  CC18 2021 2021-09-07       TURB  0.4054651081  <NA> #> 4391  2048A    3M  CC18 2021 2021-10-04      CHLAC  1.0986122887  <NA> #> 4392  2048A    3M  CC18 2021 2021-10-04      COLOR  5.0106352941  <NA> #> 4393  2048A    3M  CC18 2021 2021-10-04         DO  1.1631508098  <NA> #> 4394  2048A    3M  CC18 2021 2021-10-04      DOSAT  3.7208625000  <NA> #> 4395  2048A    3M  CC18 2021 2021-10-04       NO23 -3.2441936329  <NA> #> 4396  2048A    3M  CC18 2021 2021-10-04      SALIN  1.5390154481  <NA> #> 4397  2048A    3M  CC18 2021 2021-10-04        TKN -0.0304592075  <NA> #> 4398  2048A    3M  CC18 2021 2021-10-04         TN  0.0089597414     + #> 4399  2048A    3M  CC18 2021 2021-10-04         TP -1.4696759701  <NA> #> 4400  2048A    3M  CC18 2021 2021-10-04       TURB -0.1625189295  <NA> #> 4401  2048A    3M  CC18 2021 2021-11-01      CHLAC  0.9162907319     I #> 4402  2048A    3M  CC18 2021 2021-11-01      COLOR  4.3567088267  <NA> #> 4403  2048A    3M  CC18 2021 2021-11-01         DO  1.5973653312  <NA> #> 4404  2048A    3M  CC18 2021 2021-11-01      DOSAT  4.1447207695  <NA> #> 4405  2048A    3M  CC18 2021 2021-11-01       NO23 -3.1700856607  <NA> #> 4406  2048A    3M  CC18 2021 2021-11-01        TKN -0.2744368457  <NA> #> 4407  2048A    3M  CC18 2021 2021-11-01         TN -0.2206466711     + #> 4408  2048A    3M  CC18 2021 2021-11-01         TP -1.5141277326  <NA> #> 4409  2048A    3M  CC18 2021 2021-11-01       TURB  0.0953101798  <NA> #> 4410  2048A    3M  CC18 2021 2021-12-06      CHLAC  0.9932517730     I #> 4411  2048A    3M  CC18 2021 2021-12-06      COLOR  3.4657359028  <NA> #> 4412  2048A    3M  CC18 2021 2021-12-06         DO  1.7351891177  <NA> #> 4413  2048A    3M  CC18 2021 2021-12-06      DOSAT  4.2794400459  <NA> #> 4414  2048A    3M  CC18 2021 2021-12-06       NO23 -5.2983173665     I #> 4415  2048A    3M  CC18 2021 2021-12-06      SALIN  3.4452142671  <NA> #> 4416  2048A    3M  CC18 2021 2021-12-06        TKN -0.7550225843  <NA> #> 4417  2048A    3M  CC18 2021 2021-12-06         TN -0.7465479573     + #> 4418  2048A    3M  CC18 2021 2021-12-06         TP -2.3126354288  <NA> #> 4419  2048A    3M  CC18 2021 2021-12-06       TURB -0.2876820725  <NA> #> 4420  2048A    3M  CC18 2022 2022-01-03      CHLAC  0.8329091229     I #> 4421  2048A    3M  CC18 2022 2022-01-03      COLOR  3.3322045102     A #> 4422  2048A    3M  CC18 2022 2022-01-03         DO  1.6733512382  <NA> #> 4423  2048A    3M  CC18 2022 2022-01-03      DOSAT  4.2541932632  <NA> #> 4424  2048A    3M  CC18 2022 2022-01-03       NO23 -4.9618451299     I #> 4425  2048A    3M  CC18 2022 2022-01-03      SALIN  2.9714395810  <NA> #> 4426  2048A    3M  CC18 2022 2022-01-03        TKN -0.6348782724  <NA> #> 4427  2048A    3M  CC18 2022 2022-01-03         TN -0.6273594400     + #> 4428  2048A    3M  CC18 2022 2022-01-03         TP -2.5902671654  <NA> #> 4429  2048A    3M  CC18 2022 2022-01-03       TURB  0.1823215568  <NA> #> 4430  2048A    3M  CC18 2022 2022-02-07      CHLAC  0.6931471806     I #> 4431  2048A    3M  CC18 2022 2022-02-07      COLOR  3.0910424534     A #> 4432  2048A    3M  CC18 2022 2022-02-07         DO  0.0000000000  <NA> #> 4433  2048A    3M  CC18 2022 2022-02-07      DOSAT  4.0412953411  <NA> #> 4434  2048A    3M  CC18 2022 2022-02-07       NO23 -4.7105307016     I #> 4435  2048A    3M  CC18 2022 2022-02-07      SALIN  3.1144038033  <NA> #> 4436  2048A    3M  CC18 2022 2022-02-07        TKN -0.4620354596  <NA> #> 4437  2048A    3M  CC18 2022 2022-02-07         TN -0.4557063245     + #> 4438  2048A    3M  CC18 2022 2022-02-07         TP -2.4418471603  <NA> #> 4439  2048A    3M  CC18 2022 2022-02-07       TURB  0.6931471806  <NA> #> 4440  2048A    3M  CC18 2022 2022-03-07      CHLAC  1.0647107370     I #> 4441  2048A    3M  CC18 2022 2022-03-07      COLOR  3.2580965380  <NA> #> 4442  2048A    3M  CC18 2022 2022-03-07         DO  1.3217558400  <NA> #> 4443  2048A    3M  CC18 2022 2022-03-07      DOSAT  3.9318256327  <NA> #> 4444  2048A    3M  CC18 2022 2022-03-07       NO23 -4.7105307016     I #> 4445  2048A    3M  CC18 2022 2022-03-07      SALIN  3.2216719122  <NA> #> 4446  2048A    3M  CC18 2022 2022-03-07        TKN -0.0304592075  <NA> #> 4447  2048A    3M  CC18 2022 2022-03-07         TN -0.0263439753     + #> 4448  2048A    3M  CC18 2022 2022-03-07         TP -2.1202635362  <NA> #> 4449  2048A    3M  CC18 2022 2022-03-07       TURB  1.3083328197  <NA> #> 4450  2048A    3M  CC18 2022 2022-04-04      CHLAC  1.7227665977  <NA> #> 4451  2048A    3M  CC18 2022 2022-04-04      COLOR  3.2580965380     A #> 4452  2048A    3M  CC18 2022 2022-04-04         DO  1.3244189574  <NA> #> 4453  2048A    3M  CC18 2022 2022-04-04      DOSAT  3.9415818077  <NA> #> 4454  2048A    3M  CC18 2022 2022-04-04       NO23 -4.6051701860  <NA> #> 4455  2048A    3M  CC18 2022 2022-04-04      SALIN  3.2928695048  <NA> #> 4456  2048A    3M  CC18 2022 2022-04-04        TKN -0.3856624808  <NA> #> 4457  2048A    3M  CC18 2022 2022-04-04         TN -0.3710636814     + #> 4458  2048A    3M  CC18 2022 2022-04-04         TP -1.8325814637  <NA> #> 4459  2048A    3M  CC18 2022 2022-04-04       TURB  1.3350010667  <NA> #> 4460  2048A    3M  CC18 2022 2022-05-02      CHLAC  0.9162907319     I #> 4461  2048A    3M  CC18 2022 2022-05-02      COLOR  3.4965075615     A #> 4462  2048A    3M  CC18 2022 2022-05-02         DO  1.3164082337  <NA> #> 4463  2048A    3M  CC18 2022 2022-05-02      DOSAT  3.9550824949  <NA> #> 4464  2048A    3M  CC18 2022 2022-05-02       NO23 -4.1997050779  <NA> #> 4465  2048A    3M  CC18 2022 2022-05-02      SALIN  3.2343553957  <NA> #> 4466  2048A    3M  CC18 2022 2022-05-02        TKN -0.3566749439  <NA> #> 4467  2048A    3M  CC18 2022 2022-05-02         TN -0.3354727363     + #> 4468  2048A    3M  CC18 2022 2022-05-02         TP -1.8971199849  <NA> #> 4469  2048A    3M  CC18 2022 2022-05-02       TURB  0.8329091229  <NA> #> 4470  2048A    3M  CC18 2022 2022-06-06      CHLAC  1.8562979904  <NA> #> 4471  2048A    3M  CC18 2022 2022-06-06      COLOR  3.5553480615  <NA> #> 4472  2048A    3M  CC18 2022 2022-06-06         DO  1.3480731483  <NA> #> 4473  2048A    3M  CC18 2022 2022-06-06      DOSAT  4.0377742107  <NA> #> 4474  2048A    3M  CC18 2022 2022-06-06       NO23 -5.1159958098     I #> 4475  2048A    3M  CC18 2022 2022-06-06      SALIN  3.1759683239  <NA> #> 4476  2048A    3M  CC18 2022 2022-06-06        TKN -0.4004775666  <NA> #> 4477  2048A    3M  CC18 2022 2022-06-06         TN -0.3945251681     + #> 4478  2048A    3M  CC18 2022 2022-06-06         TP -1.6094379124  <NA> #> 4479  2048A    3M  CC18 2022 2022-06-06       TURB  0.5877866649  <NA> #> 4480  2048A    3M  CC18 2022 2022-09-06      CHLAC  2.3978952728  <NA> #> 4481  2048A    3M  CC18 2022 2022-09-06      COLOR  4.3820266347  <NA> #> 4482  2048A    3M  CC18 2022 2022-09-06         DO  1.1939224685  <NA> #> 4483  2048A    3M  CC18 2022 2022-09-06      DOSAT  3.8372994592  <NA> #> 4484  2048A    3M  CC18 2022 2022-09-06       NO23 -5.5214609179     U #> 4485  2048A    3M  CC18 2022 2022-09-06      SALIN  2.0967901800  <NA> #> 4486  2048A    3M  CC18 2022 2022-09-06        TKN -0.1165338163  <NA> #> 4487  2048A    3M  CC18 2022 2022-09-06         TN -0.1142891464     + #> 4488  2048A    3M  CC18 2022 2022-09-06         TP -1.7147984281  <NA> #> 4489  2048A    3M  CC18 2022 2022-09-06       TURB  1.2527629685  <NA> #> 4490  2048A    3M  CC18 2022 2022-11-07      CHLAC  2.4849066498  <NA> #> 4491  2048A    3M  CC18 2022 2022-11-07      COLOR  4.5849674787  <NA> #> 4492  2048A    3M  CC18 2022 2022-11-07       NO23 -5.5214609179     U #> 4493  2048A    3M  CC18 2022 2022-11-07      SALIN  2.2669579154  <NA> #> 4494  2048A    3M  CC18 2022 2022-11-07        TKN -0.0408219945  <NA> #> 4495  2048A    3M  CC18 2022 2022-11-07         TN -0.0387408283     + #> 4496  2048A    3M  CC18 2022 2022-11-07         TP -1.3093333200  <NA> #> 4497  2048A    3M  CC18 2022 2022-11-07       TURB  0.5306282511  <NA> #> 4498  2048A    3M  CC18 2022 2022-12-05      CHLAC  1.1314021115  <NA> #> 4499  2048A    3M  CC18 2022 2022-12-05      COLOR  4.2341065046  <NA> #> 4500  2048A    3M  CC18 2022 2022-12-05         DO  1.7119945008  <NA> #> 4501  2048A    3M  CC18 2022 2022-12-05      DOSAT  4.2046926194  <NA> #> 4502  2048A    3M  CC18 2022 2022-12-05       NO23 -4.6051701860  <NA> #> 4503  2048A    3M  CC18 2022 2022-12-05      SALIN  2.4475508632  <NA> #> 4504  2048A    3M  CC18 2022 2022-12-05        TKN -0.1984509387  <NA> #> 4505  2048A    3M  CC18 2022 2022-12-05         TN -0.1863295782     + #> 4506  2048A    3M  CC18 2022 2022-12-05         TP -1.7719568419  <NA> #> 4507  2048A    3M  CC18 2022 2022-12-05       TURB -0.0512932944     I #> 4508  2048A    3M  CC18 2023 2023-02-06      CHLAC  1.5260563035  <NA> #> 4509  2048A    3M  CC18 2023 2023-02-06      COLOR  3.4657359028  <NA> #> 4510  2048A    3M  CC18 2023 2023-02-06         DO  1.6863989536  <NA> #> 4511  2048A    3M  CC18 2023 2023-02-06      DOSAT  4.2341065046  <NA> #> 4512  2048A    3M  CC18 2023 2023-02-06       NO23 -5.2983173665     I #> 4513  2048A    3M  CC18 2023 2023-02-06      SALIN  2.9269179576  <NA> #> 4514  2048A    3M  CC18 2023 2023-02-06        TKN -0.4155154440  <NA> #> 4515  2048A    3M  CC18 2023 2023-02-06         TN -0.4094731295     + #> 4516  2048A    3M  CC18 2023 2023-02-06         TP -2.1202635362  <NA> #> 4517  2048A    3M  CC18 2023 2023-02-06       TURB  0.6931471806  <NA> #> 4518  2048A    3M  CC18 2023 2023-03-06      CHLAC  1.8718021769  <NA> #> 4519  2048A    3M  CC18 2023 2023-03-06      COLOR  3.3672958300  <NA> #> 4520  2048A    3M  CC18 2023 2023-03-06         DO  1.1442227999  <NA> #> 4521  2048A    3M  CC18 2023 2023-03-06      DOSAT  3.7977338590  <NA> #> 4522  2048A    3M  CC18 2023 2023-03-06       NO23 -4.4228486292  <NA> #> 4523  2048A    3M  CC18 2023 2023-03-06      SALIN  3.0199369623  <NA> #> 4524  2048A    3M  CC18 2023 2023-03-06        TKN  0.1823215568  <NA> #> 4525  2048A    3M  CC18 2023 2023-03-06         TN  0.1922718876     + #> 4526  2048A    3M  CC18 2023 2023-03-06         TP -1.9661128564  <NA> #> 4527  2048A    3M  CC18 2023 2023-03-06       TURB  0.7884573604  <NA> #> 4528 2060A1     2  CC25 2014 2014-02-12      CHLAC  1.4109869737  <NA> #> 4529 2060A1     2  CC25 2014 2014-02-12      COLOR  3.2188758249  <NA> #> 4530 2060A1     2  CC25 2014 2014-02-12       COND 10.5921245776  <NA> #> 4531 2060A1     2  CC25 2014 2014-02-12         DO  1.9933388426  <NA> #> 4532 2060A1     2  CC25 2014 2014-02-12      DOSAT  4.5570298107     + #> 4533 2060A1     2  CC25 2014 2014-02-12       NO23 -5.5214609179     U #> 4534 2060A1     2  CC25 2014 2014-02-12      SALIN  3.2367157430  <NA> #> 4535 2060A1     2  CC25 2014 2014-02-12        TKN -0.7657178734  <NA> #> 4536 2060A1     2  CC25 2014 2014-02-12         TN -0.7657178734  <NA> #> 4537 2060A1     2  CC25 2014 2014-02-12         TP -2.0099154790  <NA> #> 4538 2060A1     2  CC25 2014 2014-02-12        TSS  1.7917594692  <NA> #> 4539 2060A1     2  CC25 2014 2014-02-12       TURB  0.1823215568  <NA> #> 4540 2060A1     2  CC25 2014 2014-02-12       COND 10.5938809449  <NA> #> 4541 2060A1     2  CC25 2014 2014-02-12         DO  1.9919755159  <NA> #> 4542 2060A1     2  CC25 2014 2014-02-12      DOSAT  4.5559799418     + #> 4543 2060A1     2  CC25 2014 2014-02-12      SALIN  3.2386784522  <NA> #> 4544 2060A1     2  CC25 2014 2014-07-09      CHLAC  2.1838015570  <NA> #> 4545 2060A1     2  CC25 2014 2014-07-09      COLOR  3.8066624898  <NA> #> 4546 2060A1     2  CC25 2014 2014-07-09       COND 10.5001238327  <NA> #> 4547 2060A1     2  CC25 2014 2014-07-09         DO  1.7047480922  <NA> #> 4548 2060A1     2  CC25 2014 2014-07-09      DOSAT  4.4164280614     + #> 4549 2060A1     2  CC25 2014 2014-07-09       NO23 -5.5214609179     U #> 4550 2060A1     2  CC25 2014 2014-07-09      SALIN  3.1271990363  <NA> #> 4551 2060A1     2  CC25 2014 2014-07-09        TKN -0.2319320573  <NA> #> 4552 2060A1     2  CC25 2014 2014-07-09         TN -0.2319320573  <NA> #> 4553 2060A1     2  CC25 2014 2014-07-09         TP -1.3167682985  <NA> #> 4554 2060A1     2  CC25 2014 2014-07-09        TSS  1.9286186519  <NA> #> 4555 2060A1     2  CC25 2014 2014-07-09       TURB  0.8329091229  <NA> #> 4556 2060A1     2  CC25 2014 2014-07-09       COND 10.5012245483  <NA> #> 4557 2060A1     2  CC25 2014 2014-07-09         DO  1.7029282555  <NA> #> 4558 2060A1     2  CC25 2014 2014-07-09      DOSAT  4.4115854369     + #> 4559 2060A1     2  CC25 2014 2014-07-09      SALIN  3.1285133848  <NA> #> 4560 2060A1     2  CC25 2014 2014-08-12      CHLAC  3.6558396000  <NA> #> 4561 2060A1     2  CC25 2014 2014-08-12      COLOR  4.3820266347  <NA> #> 4562 2060A1     2  CC25 2014 2014-08-12       COND  9.9744118909  <NA> #> 4563 2060A1     2  CC25 2014 2014-08-12         DO  1.9643112344  <NA> #> 4564 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6424659707     + #> 4565 2060A1     2  CC25 2014 2014-08-12       NO23 -5.5214609179     U #> 4566 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5478814489  <NA> #> 4567 2060A1     2  CC25 2014 2014-08-12        TKN  0.1484200051  <NA> #> 4568 2060A1     2  CC25 2014 2014-08-12         TN  0.1484200051  <NA> #> 4569 2060A1     2  CC25 2014 2014-08-12         TP -0.9808292530  <NA> #> 4570 2060A1     2  CC25 2014 2014-08-12        TSS  2.3887627892  <NA> #> 4571 2060A1     2  CC25 2014 2014-08-12       TURB  1.6292405397  <NA> #> 4572 2060A1     2  CC25 2014 2014-08-12       COND  9.9753429896  <NA> #> 4573 2060A1     2  CC25 2014 2014-08-12         DO  1.9586853405  <NA> #> 4574 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6366688530     + #> 4575 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5486636156  <NA> #> 4576 2060A1     2  CC25 2014 2014-08-12       COND  9.9753429896  <NA> #> 4577 2060A1     2  CC25 2014 2014-08-12         DO  1.9530276168  <NA> #> 4578 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6308379327     + #> 4579 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5486636156  <NA> #> 4580 2060A1     2  CC25 2014 2014-10-21      CHLAC  0.9555114450  <NA> #> 4581 2060A1     2  CC25 2014 2014-10-21      COLOR  4.7874917428  <NA> #> 4582 2060A1     2  CC25 2014 2014-10-21       COND 10.1330107108  <NA> #> 4583 2060A1     2  CC25 2014 2014-10-21         DO  1.4701758451  <NA> #> 4584 2060A1     2  CC25 2014 2014-10-21      DOSAT  4.0809215419     + #> 4585 2060A1     2  CC25 2014 2014-10-21       NO23 -3.1941832123  <NA> #> 4586 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7258901192  <NA> #> 4587 2060A1     2  CC25 2014 2014-10-21        TKN -0.1053605157  <NA> #> 4588 2060A1     2  CC25 2014 2014-10-21         TN -0.0608121394  <NA> #> 4589 2060A1     2  CC25 2014 2014-10-21         TP -1.4354846053  <NA> #> 4590 2060A1     2  CC25 2014 2014-10-21        TSS  1.5973653312  <NA> #> 4591 2060A1     2  CC25 2014 2014-10-21       TURB  0.8329091229  <NA> #> 4592 2060A1     2  CC25 2014 2014-10-21       COND 10.1472177375  <NA> #> 4593 2060A1     2  CC25 2014 2014-10-21         DO  1.4182774070  <NA> #> 4594 2060A1     2  CC25 2014 2014-10-21      DOSAT  4.0271358125     + #> 4595 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7414849772  <NA> #> 4596 2060A1     2  CC25 2014 2014-10-21       COND 10.1612257486  <NA> #> 4597 2060A1     2  CC25 2014 2014-10-21         DO  1.3862943611  <NA> #> 4598 2060A1     2  CC25 2014 2014-10-21      DOSAT  3.9963641539     + #> 4599 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7581094010  <NA> #> 4600 2060A1     2  CC25 2015 2015-02-03      CHLAC  1.7209792872  <NA> #> 4601 2060A1     2  CC25 2015 2015-02-03      COLOR  3.8066624898  <NA> #> 4602 2060A1     2  CC25 2015 2015-02-03       COND 10.4795389612  <NA> #> 4603 2060A1     2  CC25 2015 2015-02-03         DO  2.1758874399  <NA> #> 4604 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6596583713     + #> 4605 2060A1     2  CC25 2015 2015-02-03       NO23 -5.5214609179     U #> 4606 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1130707660  <NA> #> 4607 2060A1     2  CC25 2015 2015-02-03        TKN -0.4975803970  <NA> #> 4608 2060A1     2  CC25 2015 2015-02-03         TN -0.4975803970  <NA> #> 4609 2060A1     2  CC25 2015 2015-02-03         TP -2.1037342342  <NA> #> 4610 2060A1     2  CC25 2015 2015-02-03        TSS  2.6100697927  <NA> #> 4611 2060A1     2  CC25 2015 2015-02-03       TURB  0.7884573604  <NA> #> 4612 2060A1     2  CC25 2015 2015-02-03       COND 10.4887710872  <NA> #> 4613 2060A1     2  CC25 2015 2015-02-03         DO  2.1644717909  <NA> #> 4614 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6482296754     + #> 4615 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1232455939  <NA> #> 4616 2060A1     2  CC25 2015 2015-02-03       COND 10.4921072037  <NA> #> 4617 2060A1     2  CC25 2015 2015-02-03         DO  2.1621729393  <NA> #> 4618 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6463121293     + #> 4619 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1267605360  <NA> #> 4620 2060A1     2  CC25 2016 2016-09-13      CHLAC  1.4206957878  <NA> #> 4621 2060A1     2  CC25 2016 2016-09-13       COND  8.8724871823  <NA> #> 4622 2060A1     2  CC25 2016 2016-09-13         DO  1.7191887764  <NA> #> 4623 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.3346729383     + #> 4624 2060A1     2  CC25 2016 2016-09-13       NO23 -2.7333680091  <NA> #> 4625 2060A1     2  CC25 2016 2016-09-13      SALIN  1.3584091576  <NA> #> 4626 2060A1     2  CC25 2016 2016-09-13        TKN  0.2851789422  <NA> #> 4627 2060A1     2  CC25 2016 2016-09-13         TN  0.3364722366  <NA> #> 4628 2060A1     2  CC25 2016 2016-09-13         TP -1.2207799226  <NA> #> 4629 2060A1     2  CC25 2016 2016-09-13        TSS  0.4700036292     I #> 4630 2060A1     2  CC25 2016 2016-09-13       TURB  0.6418538862  <NA> #> 4631 2060A1     2  CC25 2016 2016-09-13       COND  9.4834162920  <NA> #> 4632 2060A1     2  CC25 2016 2016-09-13         DO  1.6882490929  <NA> #> 4633 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.3134800921     + #> 4634 2060A1     2  CC25 2016 2016-09-13      SALIN  2.0162354658  <NA> #> 4635 2060A1     2  CC25 2016 2016-09-13       COND  9.6395220067  <NA> #> 4636 2060A1     2  CC25 2016 2016-09-13         DO  1.6544112781  <NA> #> 4637 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.2835865619     + #> 4638 2060A1     2  CC25 2016 2016-09-13      SALIN  2.1849270495  <NA> #> 4639   2046    3M  CC31 2018 2018-03-07      CHLAC  1.6094379124  <NA> #> 4640   2046    3M  CC31 2018 2018-03-07       COND 10.3531928066  <NA> #> 4641   2046    3M  CC31 2018 2018-03-07         DO  1.9021075264  <NA> #> 4642   2046    3M  CC31 2018 2018-03-07      DOSAT  4.4670568839  <NA> #> 4643   2046    3M  CC31 2018 2018-03-07       NO23 -4.7105307016     I #> 4644   2046    3M  CC31 2018 2018-03-07      SALIN  3.0170044088     + #> 4645   2046    3M  CC31 2018 2018-03-07        TKN -0.3710636814  <NA> #> 4646   2046    3M  CC31 2018 2018-03-07         TN -0.3652833185     + #> 4647   2046    3M  CC31 2018 2018-03-07         TP -1.8971199849  <NA> #> 4648   2046    3M  CC31 2018 2018-03-07        TSS  1.3862943611     I #> 4649   2046    3M  CC31 2018 2018-03-07       TURB  0.8754687374  <NA> #> 4650   2046    3M  CC31 2018 2018-04-09      CHLAC  1.2809338455     A #> 4651   2046    3M  CC31 2018 2018-04-09       COND 10.6261935353  <NA> #> 4652   2046    3M  CC31 2018 2018-04-09         DO  1.3083328197  <NA> #> 4653   2046    3M  CC31 2018 2018-04-09      DOSAT  3.9702919136  <NA> #> 4654   2046    3M  CC31 2018 2018-04-09       NO23 -3.7297014486  <NA> #> 4655   2046    3M  CC31 2018 2018-04-09      SALIN  3.2484346271     + #> 4656   2046    3M  CC31 2018 2018-04-09        TKN -0.3147107448  <NA> #> 4657   2046    3M  CC31 2018 2018-04-09         TN -0.2823629110     + #> 4658   2046    3M  CC31 2018 2018-04-09         TP -1.7147984281  <NA> #> 4659   2046    3M  CC31 2018 2018-04-09        TSS  1.6094379124     I #> 4660   2046    3M  CC31 2018 2018-04-09       TURB  0.6931471806  <NA> #> 4661   2046    3M  CC31 2018 2018-05-24      CHLAC  2.7080502011  <NA> #> 4662   2046    3M  CC31 2018 2018-05-24       COND  9.7756541810  <NA> #> 4663   2046    3M  CC31 2018 2018-05-24         DO  1.5303947051  <NA> #> 4664   2046    3M  CC31 2018 2018-05-24      DOSAT  4.1009891049  <NA> #> 4665   2046    3M  CC31 2018 2018-05-24       NO23 -3.1010927892  <NA> #> 4666   2046    3M  CC31 2018 2018-05-24      SALIN  2.3065771143     + #> 4667   2046    3M  CC31 2018 2018-05-24        TKN -0.2613647641  <NA> #> 4668   2046    3M  CC31 2018 2018-05-24         TN -0.2045671657     + #> 4669   2046    3M  CC31 2018 2018-05-24         TP -1.4271163556  <NA> #> 4670   2046    3M  CC31 2018 2018-05-24        TSS  1.6094379124     I #> 4671   2046    3M  CC31 2018 2018-05-24       TURB  0.9932517730  <NA> #> 4672   2046    3M  CC31 2018 2018-07-23      CHLAC  1.4350845253  <NA> #> 4673   2046    3M  CC31 2018 2018-07-23       COND  8.9291703831  <NA> #> 4674   2046    3M  CC31 2018 2018-07-23         DO  1.6937790609  <NA> #> 4675   2046    3M  CC31 2018 2018-07-23      DOSAT  4.3040650932  <NA> #> 4676   2046    3M  CC31 2018 2018-07-23       NO23 -2.0402208285  <NA> #> 4677   2046    3M  CC31 2018 2018-07-23      SALIN  1.4182774070  <NA> #> 4678   2046    3M  CC31 2018 2018-07-23        TKN  0.0000000000  <NA> #> 4679   2046    3M  CC31 2018 2018-07-23         TN  0.1222176327     + #> 4680   2046    3M  CC31 2018 2018-07-23         TP -0.9162907319  <NA> #> 4681   2046    3M  CC31 2018 2018-07-23        TSS  1.3862943611     I #> 4682   2046    3M  CC31 2018 2018-07-23       TURB  0.9162907319     A #> 4683   2046    3M  CC31 2018 2018-08-21      CHLAC  2.7080502011  <NA> #> 4684   2046    3M  CC31 2018 2018-08-21       COND  8.6210125201  <NA> #> 4685   2046    3M  CC31 2018 2018-08-21         DO  1.4586150227  <NA> #> 4686   2046    3M  CC31 2018 2018-08-21      DOSAT  4.0724397268  <NA> #> 4687   2046    3M  CC31 2018 2018-08-21       NO23 -3.4737680745  <NA> #> 4688   2046    3M  CC31 2018 2018-08-21      SALIN  1.0885619528  <NA> #> 4689   2046    3M  CC31 2018 2018-08-21        TKN  1.7047480922  <NA> #> 4690   2046    3M  CC31 2018 2018-08-21         TN  1.7103686310     + #> 4691   2046    3M  CC31 2018 2018-08-21        TSS  1.6094379124     I #> 4692   2046    3M  CC31 2018 2018-08-21       TURB  1.3350010667  <NA> #> 4693   2046    3M  CC31 2018 2018-11-12      CHLAC  1.5686159179  <NA> #> 4694   2046    3M  CC31 2018 2018-11-12       COND 10.1213773269  <NA> #> 4695   2046    3M  CC31 2018 2018-11-12         DO  1.6695918353  <NA> #> 4696   2046    3M  CC31 2018 2018-11-12      DOSAT  4.3121405072  <NA> #> 4697   2046    3M  CC31 2018 2018-11-12       NO23 -3.4112477175  <NA> #> 4698   2046    3M  CC31 2018 2018-11-12      SALIN  2.7127060126  <NA> #> 4699   2046    3M  CC31 2018 2018-11-12        TKN -0.3011050928  <NA> #> 4700   2046    3M  CC31 2018 2018-11-12         TN -0.2574762304     + #> 4701   2046    3M  CC31 2018 2018-11-12         TP -1.8325814637  <NA> #> 4702   2046    3M  CC31 2018 2018-11-12        TSS  1.3862943611     I #> 4703   2046    3M  CC31 2018 2018-11-12       TURB  0.4700036292  <NA> #> 4704   2046    3M  CC31 2018 2018-11-12       COND 10.3160937688  <NA> #> 4705   2046    3M  CC31 2018 2018-11-12         DO  1.5581446180  <NA> #> 4706   2046    3M  CC31 2018 2018-11-12      DOSAT  4.2076732475  <NA> #> 4707   2046    3M  CC31 2018 2018-11-12      SALIN  2.9269179576  <NA> #> 4708   2046    3M  CC31 2019 2019-02-07      CHLAC  3.3672958300  <NA> #> 4709   2046    3M  CC31 2019 2019-02-07       COND  9.8807305654  <NA> #> 4710   2046    3M  CC31 2019 2019-02-07       NO23 -5.5214609179     U #> 4711   2046    3M  CC31 2019 2019-02-07      SALIN  2.4544474423  <NA> #> 4712   2046    3M  CC31 2019 2019-02-07        TKN -0.3710636814  <NA> #> 4713   2046    3M  CC31 2019 2019-02-07         TN -0.3681693234     + #> 4714   2046    3M  CC31 2019 2019-02-07         TP -1.6607312068  <NA> #> 4715   2046    3M  CC31 2019 2019-02-07        TSS  3.3322045102     A #> 4716   2046    3M  CC31 2019 2019-02-07       TURB  2.4849066498     A #> 4717   2046    3M  CC31 2019 2019-03-13      CHLAC  2.3978952728  <NA> #> 4718   2046    3M  CC31 2019 2019-03-13       COND 10.1587109973  <NA> #> 4719   2046    3M  CC31 2019 2019-03-13         DO  1.5830939371  <NA> #> 4720   2046    3M  CC31 2019 2019-03-13      DOSAT  4.1588830834  <NA> #> 4721   2046    3M  CC31 2019 2019-03-13       NO23 -5.5214609179     U #> 4722   2046    3M  CC31 2019 2019-03-13      SALIN  2.7568403653  <NA> #> 4723   2046    3M  CC31 2019 2019-03-13        TKN -0.2876820725  <NA> #> 4724   2046    3M  CC31 2019 2019-03-13         TN -0.2850189550     + #> 4725   2046    3M  CC31 2019 2019-03-13         TP -1.7719568419  <NA> #> 4726   2046    3M  CC31 2019 2019-03-13        TSS  1.3862943611     I #> 4727   2046    3M  CC31 2019 2019-03-13       TURB  0.8754687374  <NA> #> 4728   2046    3M  CC31 2019 2019-04-23      CHLAC  1.8562979904  <NA> #> 4729   2046    3M  CC31 2019 2019-04-23       COND 10.2120745857  <NA> #> 4730   2046    3M  CC31 2019 2019-04-23         DO  1.8389610707  <NA> #> 4731   2046    3M  CC31 2019 2019-04-23      DOSAT  4.4188406078  <NA> #> 4732   2046    3M  CC31 2019 2019-04-23       NO23 -5.5214609179     U #> 4733   2046    3M  CC31 2019 2019-04-23      SALIN  2.8154087194  <NA> #> 4734   2046    3M  CC31 2019 2019-04-23        TKN -0.4307829161  <NA> #> 4735   2046    3M  CC31 2019 2019-04-23         TN -0.4277107171     + #> 4736   2046    3M  CC31 2019 2019-04-23         TP -1.6094379124  <NA> #> 4737   2046    3M  CC31 2019 2019-04-23        TSS  2.5649493575  <NA> #> 4738   2046    3M  CC31 2019 2019-04-23       TURB  1.4350845253  <NA> #> 4739   2046    3M  CC31 2019 2019-07-22      CHLAC  2.0281482473  <NA> #> 4740   2046    3M  CC31 2019 2019-07-22       COND  9.5882287123  <NA> #> 4741   2046    3M  CC31 2019 2019-07-22         DO  1.6808279085  <NA> #> 4742   2046    3M  CC31 2019 2019-07-22      DOSAT  4.3174881135  <NA> #> 4743   2046    3M  CC31 2019 2019-07-22       NO23 -5.1159958098     I #> 4744   2046    3M  CC31 2019 2019-07-22      SALIN  2.1282317058  <NA> #> 4745   2046    3M  CC31 2019 2019-07-22        TKN -0.2484613593  <NA> #> 4746   2046    3M  CC31 2019 2019-07-22         TN -0.2433462586     + #> 4747   2046    3M  CC31 2019 2019-07-22         TP -1.3862943611  <NA> #> 4748   2046    3M  CC31 2019 2019-07-22        TSS  0.6931471806     I #> 4749   2046    3M  CC31 2019 2019-07-22       TURB  0.7419373447  <NA> #> 4750   2046    3M  CC31 2019 2019-09-04      CHLAC  2.6390573296  <NA> #> 4751   2046    3M  CC31 2019 2019-09-04       COND  9.5618419571  <NA> #> 4752   2046    3M  CC31 2019 2019-09-04         DO  1.6486586256  <NA> #> 4753   2046    3M  CC31 2019 2019-09-04      DOSAT  4.2752762647  <NA> #> 4754   2046    3M  CC31 2019 2019-09-04       NO23 -3.1465551633  <NA> #> 4755   2046    3M  CC31 2019 2019-09-04      SALIN  2.1004689089  <NA> #> 4756   2046    3M  CC31 2019 2019-09-04        TKN -0.1863295782  <NA> #> 4757   2046    3M  CC31 2019 2019-09-04         TN -0.1358197231     + #> 4758   2046    3M  CC31 2019 2019-09-04         TP -1.5141277326  <NA> #> 4759   2046    3M  CC31 2019 2019-09-04        TSS  1.3862943611     I #> 4760   2046    3M  CC31 2019 2019-09-04       TURB  0.6418538862  <NA> #> 4761   2046    3M  CC31 2020 2020-01-14       COND 10.2603574775  <NA> #> 4762   2046    3M  CC31 2020 2020-01-14         DO  1.8341801851  <NA> #> 4763   2046    3M  CC31 2020 2020-01-14      DOSAT  4.4140096805  <NA> #> 4764   2046    3M  CC31 2020 2020-01-14      SALIN  2.8690346205  <NA> #> 4765   2046    3M  CC31 2020 2020-02-18      CHLAC  0.8329091229     I #> 4766   2046    3M  CC31 2020 2020-02-18       COND 10.3879178649  <NA> #> 4767   2046    3M  CC31 2020 2020-02-18         DO  1.8976198599  <NA> #> 4768   2046    3M  CC31 2020 2020-02-18      DOSAT  4.5075573571  <NA> #> 4769   2046    3M  CC31 2020 2020-02-18       NO23 -4.8283137373     I #> 4770   2046    3M  CC31 2020 2020-02-18      SALIN  3.0106208860  <NA> #> 4771   2046    3M  CC31 2020 2020-02-18        TKN -0.5447271754  <NA> #> 4772   2046    3M  CC31 2020 2020-02-18         TN -0.5378542962     + #> 4773   2046    3M  CC31 2020 2020-02-18         TP -2.0402208285  <NA> #> 4774   2046    3M  CC31 2020 2020-02-18        TSS  1.0986122887     I #> 4775   2046    3M  CC31 2020 2020-02-18       TURB  0.4700036292  <NA> #> 4776   2046    3M  CC31 2020 2020-06-09      CHLAC  2.9444389792  <NA> #> 4777   2046    3M  CC31 2020 2020-06-09       COND 10.1025842827  <NA> #> 4778   2046    3M  CC31 2020 2020-06-09         DO  1.5973653312  <NA> #> 4779   2046    3M  CC31 2020 2020-06-09      DOSAT  4.2297491992  <NA> #> 4780   2046    3M  CC31 2020 2020-06-09       NO23 -4.9618451299     I #> 4781   2046    3M  CC31 2020 2020-06-09      SALIN  2.6919208192  <NA> #> 4782   2046    3M  CC31 2020 2020-06-09        TKN  0.0000000000  <NA> #> 4783   2046    3M  CC31 2020 2020-06-09         TN  0.0039920213     + #> 4784   2046    3M  CC31 2020 2020-06-09         TP -1.2729656758  <NA> #> 4785   2046    3M  CC31 2020 2020-06-09        TSS  1.3862943611     I #> 4786   2046    3M  CC31 2020 2020-06-09       TURB  0.5306282511  <NA> #> 4787   2046    3M  CC31 2020 2020-08-10       COND 10.0585663729  <NA> #> 4788   2046    3M  CC31 2020 2020-08-10         DO  0.7419373447  <NA> #> 4789   2046    3M  CC31 2020 2020-08-10      DOSAT  3.4177266836  <NA> #> 4790   2046    3M  CC31 2020 2020-08-10      SALIN  2.6426223958  <NA> #> 4791   2046    3M  CC31 2020 2020-09-22      CHLAC  2.4849066498  <NA> #> 4792   2046    3M  CC31 2020 2020-09-22       COND  9.3350328159  <NA> #> 4793   2046    3M  CC31 2020 2020-09-22         DO  1.5789787049  <NA> #> 4794   2046    3M  CC31 2020 2020-09-22      DOSAT  4.1573193614  <NA> #> 4795   2046    3M  CC31 2020 2020-09-22       NO23 -3.0791138825  <NA> #> 4796   2046    3M  CC31 2020 2020-09-22      SALIN  1.8578592709  <NA> #> 4797   2046    3M  CC31 2020 2020-09-22        TKN -0.0408219945  <NA> #> 4798   2046    3M  CC31 2020 2020-09-22         TN  0.0059820717     + #> 4799   2046    3M  CC31 2020 2020-09-22         TP -1.4271163556  <NA> #> 4800   2046    3M  CC31 2020 2020-09-22        TSS  1.0986122887     I #> 4801   2046    3M  CC31 2020 2020-09-22       TURB  0.9932517730  <NA> #> 4802   2046    3M  CC31 2020 2020-10-20      CHLAC  1.4586150227  <NA> #> 4803   2046    3M  CC31 2020 2020-10-20       COND  9.7670949276  <NA> #> 4804   2046    3M  CC31 2020 2020-10-20         DO  1.4085449701  <NA> #> 4805   2046    3M  CC31 2020 2020-10-20      DOSAT  4.0000338828  <NA> #> 4806   2046    3M  CC31 2020 2020-10-20       NO23 -2.5510464523  <NA> #> 4807   2046    3M  CC31 2020 2020-10-20      SALIN  2.3282528397  <NA> #> 4808   2046    3M  CC31 2020 2020-10-20        TKN -0.0833816089  <NA> #> 4809   2046    3M  CC31 2020 2020-10-20         TN -0.0020020027     + #> 4810   2046    3M  CC31 2020 2020-10-20         TP -1.5141277326  <NA> #> 4811   2046    3M  CC31 2020 2020-10-20        TSS  1.0986122887     I #> 4812   2046    3M  CC31 2020 2020-10-20       TURB  0.5877866649  <NA> #> 4813   2046    3M  CC31 2020 2020-12-14      CHLAC  1.0647107370  <NA> #> 4814   2046    3M  CC31 2020 2020-12-14       COND  9.9551782679  <NA> #> 4815   2046    3M  CC31 2020 2020-12-14         DO  1.8293763328  <NA> #> 4816   2046    3M  CC31 2020 2020-12-14      DOSAT  4.3528552574  <NA> #> 4817   2046    3M  CC31 2020 2020-12-14       NO23 -2.7181005370  <NA> #> 4818   2046    3M  CC31 2020 2020-12-14      SALIN  2.5360749364  <NA> #> 4819   2046    3M  CC31 2020 2020-12-14        TKN -0.2107210313  <NA> #> 4820   2046    3M  CC31 2020 2020-12-14         TN -0.1323891880     + #> 4821   2046    3M  CC31 2020 2020-12-14         TP -2.1202635362  <NA> #> 4822   2046    3M  CC31 2020 2020-12-14        TSS  1.6094379124     I #> 4823   2046    3M  CC31 2020 2020-12-14       TURB  0.5306282511  <NA> #> 4824   2046    3M  CC31 2021 2021-02-03      CHLAC  0.9932517730  <NA> #> 4825   2046    3M  CC31 2021 2021-02-03       COND 10.2269830978  <NA> #> 4826   2046    3M  CC31 2021 2021-02-03         DO  2.0655961349  <NA> #> 4827   2046    3M  CC31 2021 2021-02-03      DOSAT  4.5130548971  <NA> #> 4828   2046    3M  CC31 2021 2021-02-03       NO23 -4.0745419349  <NA> #> 4829   2046    3M  CC31 2021 2021-02-03      SALIN  2.8355635214  <NA> #> 4830   2046    3M  CC31 2021 2021-02-03        TKN -0.4780358009  <NA> #> 4831   2046    3M  CC31 2021 2021-02-03         TN -0.4509856234     + #> 4832   2046    3M  CC31 2021 2021-02-03         TP -2.3025850930  <NA> #> 4833   2046    3M  CC31 2021 2021-02-03        TSS  1.7917594692     I #> 4834   2046    3M  CC31 2021 2021-02-03       TURB  0.5306282511  <NA> #> 4835   2046    3M  CC31 2021 2021-03-09      CHLAC  2.0918640617  <NA> #> 4836   2046    3M  CC31 2021 2021-03-09       COND 10.3281668796  <NA> #> 4837   2046    3M  CC31 2021 2021-03-09         DO  2.2523438766  <NA> #> 4838   2046    3M  CC31 2021 2021-03-09      DOSAT  4.7757564866  <NA> #> 4839   2046    3M  CC31 2021 2021-03-09       NO23 -5.5214609179     U #> 4840   2046    3M  CC31 2021 2021-03-09      SALIN  2.9460166813  <NA> #> 4841   2046    3M  CC31 2021 2021-03-09        TKN -0.1863295782  <NA> #> 4842   2046    3M  CC31 2021 2021-03-09         TN -0.1839228382     + #> 4843   2046    3M  CC31 2021 2021-03-09         TP -1.5606477483  <NA> #> 4844   2046    3M  CC31 2021 2021-03-09        TSS  2.8332133441  <NA> #> 4845   2046    3M  CC31 2021 2021-03-09       TURB  2.0412203289  <NA> #> 4846   2046    3M  CC31 2021 2021-05-05      CHLAC  0.9555114450  <NA> #> 4847   2046    3M  CC31 2021 2021-05-05       COND 10.5683895677  <NA> #> 4848   2046    3M  CC31 2021 2021-05-05         DO  1.3402504226  <NA> #> 4849   2046    3M  CC31 2021 2021-05-05      DOSAT  4.0465538984  <NA> #> 4850   2046    3M  CC31 2021 2021-05-05       NO23 -5.5214609179     U #> 4851   2046    3M  CC31 2021 2021-05-05      SALIN  3.2043711387  <NA> #> 4852   2046    3M  CC31 2021 2021-05-05        TKN -0.4620354596  <NA> #> 4853   2046    3M  CC31 2021 2021-05-05         TN -0.4588658848     + #> 4854   2046    3M  CC31 2021 2021-05-05         TP -1.5141277326  <NA> #> 4855   2046    3M  CC31 2021 2021-05-05        TSS  1.7917594692     I #> 4856   2046    3M  CC31 2021 2021-05-05       TURB  0.4700036292  <NA> #> 4857   2046    3M  CC31 2021 2021-06-03      CHLAC  0.9932517730     I #> 4858   2046    3M  CC31 2021 2021-06-03       COND 10.6275033568  <NA> #> 4859   2046    3M  CC31 2021 2021-06-03         DO  0.8329091229  <NA> #> 4860   2046    3M  CC31 2021 2021-06-03      DOSAT  3.5322256441  <NA> #> 4861   2046    3M  CC31 2021 2021-06-03       NO23 -5.5214609179     U #> 4862   2046    3M  CC31 2021 2021-06-03      SALIN  3.2718477096  <NA> #> 4863   2046    3M  CC31 2021 2021-06-03        TKN -0.3285040670  <NA> #> 4864   2046    3M  CC31 2021 2021-06-03         TN -0.3257301401     + #> 4865   2046    3M  CC31 2021 2021-06-03         TP -1.4271163556  <NA> #> 4866   2046    3M  CC31 2021 2021-06-03        TSS  1.0986122887     I #> 4867   2046    3M  CC31 2021 2021-06-03       TURB  0.5306282511  <NA> #> 4868   2046    3M  CC31 2021 2021-07-01      CHLAC  2.7080502011  <NA> #> 4869   2046    3M  CC31 2021 2021-07-01       COND 10.4739019677  <NA> #> 4870   2046    3M  CC31 2021 2021-07-01         DO  1.6770965609  <NA> #> 4871   2046    3M  CC31 2021 2021-07-01      DOSAT  4.3107991254  <NA> #> 4872   2046    3M  CC31 2021 2021-07-01       NO23 -5.2983173665     I #> 4873   2046    3M  CC31 2021 2021-07-01      SALIN  3.1014427280  <NA> #> 4874   2046    3M  CC31 2021 2021-07-01        TKN -0.4462871026  <NA> #> 4875   2046    3M  CC31 2021 2021-07-01         TN -0.4400565529     + #> 4876   2046    3M  CC31 2021 2021-07-01         TP -1.2729656758  <NA> #> 4877   2046    3M  CC31 2021 2021-07-01        TSS  1.7917594692     I #> 4878   2046    3M  CC31 2021 2021-07-01       TURB  0.4054651081  <NA> #> 4879   2046    3M  CC31 2021 2021-07-29      CHLAC  2.9444389792  <NA> #> 4880   2046    3M  CC31 2021 2021-07-29       COND  9.3783094225  <NA> #> 4881   2046    3M  CC31 2021 2021-07-29         DO  1.3558351536  <NA> #> 4882   2046    3M  CC31 2021 2021-07-29      DOSAT  3.9646154555  <NA> #> 4883   2046    3M  CC31 2021 2021-07-29       NO23 -3.3242363405  <NA> #> 4884   2046    3M  CC31 2021 2021-07-29      SALIN  1.9021075264  <NA> #> 4885   2046    3M  CC31 2021 2021-07-29        TKN  0.0953101798  <NA> #> 4886   2046    3M  CC31 2021 2021-07-29         TN  0.1275133203     + #> 4887   2046    3M  CC31 2021 2021-07-29         TP -0.9942522733  <NA> #> 4888   2046    3M  CC31 2021 2021-07-29        TSS  1.6094379124     I #> 4889   2046    3M  CC31 2021 2021-07-29       TURB  1.6094379124  <NA> #> 4890   2046    3M  CC31 2021 2021-08-25      CHLAC  2.4849066498  <NA> #> 4891   2046    3M  CC31 2021 2021-08-25       COND  9.4766200382  <NA> #> 4892   2046    3M  CC31 2021 2021-08-25         DO  0.8153648133  <NA> #> 4893   2046    3M  CC31 2021 2021-08-25      DOSAT  3.4404180948  <NA> #> 4894   2046    3M  CC31 2021 2021-08-25       NO23 -4.0745419349  <NA> #> 4895   2046    3M  CC31 2021 2021-08-25      SALIN  2.0095554142  <NA> #> 4896   2046    3M  CC31 2021 2021-08-25        TKN  0.0000000000  <NA> #> 4897   2046    3M  CC31 2021 2021-08-25         TN  0.0168571171     + #> 4898   2046    3M  CC31 2021 2021-08-25         TP -1.1086626245  <NA> #> 4899   2046    3M  CC31 2021 2021-08-25        TSS  1.7917594692     I #> 4900   2046    3M  CC31 2021 2021-08-25       TURB  1.1939224685  <NA> #> 4901   2046    3M  CC31 2021 2021-09-23      CHLAC  3.0445224377  <NA> #> 4902   2046    3M  CC31 2021 2021-09-23       COND  8.7826296549  <NA> #> 4903   2046    3M  CC31 2021 2021-09-23         DO  1.4747630091  <NA> #> 4904   2046    3M  CC31 2021 2021-09-23      DOSAT  4.0483006237  <NA> #> 4905   2046    3M  CC31 2021 2021-09-23       NO23 -3.0576076773  <NA> #> 4906   2046    3M  CC31 2021 2021-09-23      SALIN  1.2641267271  <NA> #> 4907   2046    3M  CC31 2021 2021-09-23        TKN -0.0943106795  <NA> #> 4908   2046    3M  CC31 2021 2021-09-23         TN -0.0439518875     + #> 4909   2046    3M  CC31 2021 2021-09-23         TP -1.4271163556  <NA> #> 4910   2046    3M  CC31 2021 2021-09-23        TSS  1.3862943611     I #> 4911   2046    3M  CC31 2021 2021-09-23       TURB  1.1631508098  <NA> #> 4912   2046    3M  CC31 2021 2021-10-21      CHLAC  2.3025850930  <NA> #> 4913   2046    3M  CC31 2021 2021-10-21       COND  9.9156631285  <NA> #> 4914   2046    3M  CC31 2021 2021-10-21         DO  1.5040773968  <NA> #> 4915   2046    3M  CC31 2021 2021-10-21      DOSAT  4.0690267542  <NA> #> 4916   2046    3M  CC31 2021 2021-10-21       NO23 -3.1465551633  <NA> #> 4917   2046    3M  CC31 2021 2021-10-21      SALIN  2.4907230351  <NA> #> 4918   2046    3M  CC31 2021 2021-10-21        TKN -0.1278333715  <NA> #> 4919   2046    3M  CC31 2021 2021-10-21         TN -0.0801260445     + #> 4920   2046    3M  CC31 2021 2021-10-21         TP -1.5141277326  <NA> #> 4921   2046    3M  CC31 2021 2021-10-21        TSS  1.0986122887     U #> 4922   2046    3M  CC31 2021 2021-10-21       TURB  0.4700036292     A #> 4923   2046    3M  CC31 2021 2021-11-22       COND 10.1079374614  <NA> #> 4924   2046    3M  CC31 2021 2021-11-22         DO  1.7316555452  <NA> #> 4925   2046    3M  CC31 2021 2021-11-22      DOSAT  4.2877159552  <NA> #> 4926   2046    3M  CC31 2021 2021-11-22       NO23 -2.8134107168  <NA> #> 4927   2046    3M  CC31 2021 2021-11-22      SALIN  2.7020321288  <NA> #> 4928   2046    3M  CC31 2021 2021-11-22        TKN -0.6733445533  <NA> #> 4929   2046    3M  CC31 2021 2021-11-22         TN -0.5621189182     + #> 4930   2046    3M  CC31 2021 2021-11-22         TP -2.3025850930  <NA> #> 4931   2046    3M  CC31 2021 2021-11-22        TSS  1.6094379124     I #> 4932   2046    3M  CC31 2021 2021-11-22       TURB  0.1823215568     A #> 4933   2046    3M  CC31 2022 2022-02-22      CHLAC  1.3083328197  <NA> #> 4934   2046    3M  CC31 2022 2022-02-22       COND 10.5165899421  <NA> #> 4935   2046    3M  CC31 2022 2022-02-22         DO  1.8547342684  <NA> #> 4936   2046    3M  CC31 2022 2022-02-22      DOSAT  4.4320065670  <NA> #> 4937   2046    3M  CC31 2022 2022-02-22       NO23 -5.5214609179     U #> 4938   2046    3M  CC31 2022 2022-02-22      SALIN  3.1527360224  <NA> #> 4939   2046    3M  CC31 2022 2022-02-22        TKN -0.6931471806  <NA> #> 4940   2046    3M  CC31 2022 2022-02-22         TN -0.6891551593     + #> 4941   2046    3M  CC31 2022 2022-02-22         TP -2.4304184645  <NA> #> 4942   2046    3M  CC31 2022 2022-02-22        TSS  2.0794415417     I #> 4943   2046    3M  CC31 2022 2022-02-22       TURB  0.4054651081     A #> 4944   2046    3M  CC31 2022 2022-04-20      CHLAC  1.5260563035  <NA> #> 4945   2046    3M  CC31 2022 2022-04-20       COND 10.6492271832  <NA> #> 4946   2046    3M  CC31 2022 2022-04-20         DO  1.5581446180  <NA> #> 4947   2046    3M  CC31 2022 2022-04-20      DOSAT  4.1805222585  <NA> #> 4948   2046    3M  CC31 2022 2022-04-20       NO23 -5.5214609179     U #> 4949   2046    3M  CC31 2022 2022-04-20      SALIN  3.2987954480  <NA> #> 4950   2046    3M  CC31 2022 2022-04-20        TKN -0.5447271754  <NA> #> 4951   2046    3M  CC31 2022 2022-04-20         TN -0.5412848313     + #> 4952   2046    3M  CC31 2022 2022-04-20         TP -1.8325814637  <NA> #> 4953   2046    3M  CC31 2022 2022-04-20        TSS  2.0794415417     I #> 4954   2046    3M  CC31 2022 2022-04-20       TURB  1.0296194172  <NA> #> 4955   2046    3M  CC31 2022 2022-06-07      CHLAC  1.9021075264  <NA> #> 4956   2046    3M  CC31 2022 2022-06-07       COND 10.4903571304  <NA> #> 4957   2046    3M  CC31 2022 2022-06-07         DO  1.2412685891  <NA> #> 4958   2046    3M  CC31 2022 2022-06-07      DOSAT  3.9318256327  <NA> #> 4959   2046    3M  CC31 2022 2022-06-07       NO23 -5.2983173665     I #> 4960   2046    3M  CC31 2022 2022-06-07      SALIN  3.1188344707  <NA> #> 4961   2046    3M  CC31 2022 2022-06-07        TKN -0.4942963218  <NA> #> 4962   2046    3M  CC31 2022 2022-06-07         TN -0.4877603508     + #> 4963   2046    3M  CC31 2022 2022-06-07         TP -1.4696759701  <NA> #> 4964   2046    3M  CC31 2022 2022-06-07        TSS  2.0794415417     I #> 4965   2046    3M  CC31 2022 2022-06-07       TURB  0.1823215568  <NA> #> 4966   2046    3M  CC31 2022 2022-08-15      CHLAC  2.1282317058  <NA> #> 4967   2046    3M  CC31 2022 2022-08-15       COND  9.6188009891  <NA> #> 4968   2046    3M  CC31 2022 2022-08-15         DO  0.9895411936  <NA> #> 4969   2046    3M  CC31 2022 2022-08-15      DOSAT  3.6054978452  <NA> #> 4970   2046    3M  CC31 2022 2022-08-15       NO23 -3.4737680745  <NA> #> 4971   2046    3M  CC31 2022 2022-08-15      SALIN  2.1667653699  <NA> #> 4972   2046    3M  CC31 2022 2022-08-15        TKN -0.0833816089  <NA> #> 4973   2046    3M  CC31 2022 2022-08-15         TN -0.0502412164     + #> 4974   2046    3M  CC31 2022 2022-08-15         TP -1.4696759701  <NA> #> 4975   2046    3M  CC31 2022 2022-08-15        TSS  1.0986122887     I #> 4976   2046    3M  CC31 2022 2022-08-15       TURB  0.6931471806  <NA> #> 4977   2046    3M  CC31 2022 2022-12-15      CHLAC  0.9555114450  <NA> #> 4978   2046    3M  CC31 2022 2022-12-15       COND 10.2729108893  <NA> #> 4979   2046    3M  CC31 2022 2022-12-15         DO  1.7630170004  <NA> #> 4980   2046    3M  CC31 2022 2022-12-15      DOSAT  4.3267781604  <NA> #> 4981   2046    3M  CC31 2022 2022-12-15       NO23 -2.9759296463  <NA> #> 4982   2046    3M  CC31 2022 2022-12-15      SALIN  2.8836827697  <NA> #> 4983   2046    3M  CC31 2022 2022-12-15        TKN -0.4942963218  <NA> #> 4984   2046    3M  CC31 2022 2022-12-15         TN -0.4140014391     + #> 4985   2046    3M  CC31 2022 2022-12-15         TP -1.6094379124  <NA> #> 4986   2046    3M  CC31 2022 2022-12-15        TSS  2.0794415417     I #> 4987   2046    3M  CC31 2022 2022-12-15       TURB  0.0000000000  <NA> #> 4988   2046    3M  CC31 2023 2023-01-11      CHLAC  2.0668627595  <NA> #> 4989   2046    3M  CC31 2023 2023-01-11       COND 10.2352702390  <NA> #> 4990   2046    3M  CC31 2023 2023-01-11         DO  1.7984040119  <NA> #> 4991   2046    3M  CC31 2023 2023-01-11      DOSAT  4.2849649218  <NA> #> 4992   2046    3M  CC31 2023 2023-01-11       NO23 -3.9633162998  <NA> #> 4993   2046    3M  CC31 2023 2023-01-11      SALIN  2.8443278194  <NA> #> 4994   2046    3M  CC31 2023 2023-01-11        TKN -0.5798184953  <NA> #> 4995   2046    3M  CC31 2023 2023-01-11         TN -0.5464528014     + #> 4996   2046    3M  CC31 2023 2023-01-11         TP -1.8325814637  <NA> #> 4997   2046    3M  CC31 2023 2023-01-11        TSS  1.7917594692     I #> 4998   2046    3M  CC31 2023 2023-01-11       TURB  0.7419373447  <NA> #> 4999   2046    3M  CC31 2023 2023-03-23      CHLAC  1.7578579176  <NA> #> 5000   2046    3M  CC31 2023 2023-03-23       COND 10.4503364755  <NA> #> 5001   2046    3M  CC31 2023 2023-03-23         DO  1.8840347453  <NA> #> 5002   2046    3M  CC31 2023 2023-03-23      DOSAT  4.4461744545  <NA> #> 5003   2046    3M  CC31 2023 2023-03-23       NO23 -5.5214609179     U #> 5004   2046    3M  CC31 2023 2023-03-23      SALIN  3.0796137575  <NA> #> 5005   2046    3M  CC31 2023 2023-03-23        TKN -0.1984509387  <NA> #> 5006   2046    3M  CC31 2023 2023-03-23         TN -0.1960148839     + #> 5007   2046    3M  CC31 2023 2023-03-23         TP -1.1711829815  <NA> #> 5008   2046    3M  CC31 2023 2023-03-23        TSS  2.7725887222  <NA> #> 5009   2046    3M  CC31 2023 2023-03-23       TURB  1.7047480922  <NA> #> 5010   2046    3M  CC31 2023 2023-05-08      CHLAC  1.2809338455  <NA> #> 5011   2046    3M  CC31 2023 2023-05-08       COND 10.5443145959  <NA> #> 5012   2046    3M  CC31 2023 2023-05-08         DO  1.6014057407  <NA> #> 5013   2046    3M  CC31 2023 2023-05-08      DOSAT  4.2370008626  <NA> #> 5014   2046    3M  CC31 2023 2023-05-08       NO23 -4.7105307016     I #> 5015   2046    3M  CC31 2023 2023-05-08      SALIN  3.1813816204  <NA> #> 5016   2046    3M  CC31 2023 2023-05-08        TKN -0.3710636814  <NA> #> 5017   2046    3M  CC31 2023 2023-05-08         TN -0.3652833185     + #> 5018   2046    3M  CC31 2023 2023-05-08         TP -1.6094379124  <NA> #> 5019   2046    3M  CC31 2023 2023-05-08        TSS  1.7917594692     I #> 5020   2046    3M  CC31 2023 2023-05-08       TURB  0.0953101798  <NA> #> 5021  2056E    3M  CC34 2015 2015-04-06      CHLAC  1.5040773968  <NA> #> 5022  2056E    3M  CC34 2015 2015-04-06      COLOR  3.8066624898  <NA> #> 5023  2056E    3M  CC34 2015 2015-04-06       COND 10.4003156667  <NA> #> 5024  2056E    3M  CC34 2015 2015-04-06         DO  2.1317967720  <NA> #> 5025  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7899886230     + #> 5026  2056E    3M  CC34 2015 2015-04-06       NO23 -5.5214609179     U #> 5027  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0194488002  <NA> #> 5028  2056E    3M  CC34 2015 2015-04-06        TKN -0.3509769228  <NA> #> 5029  2056E    3M  CC34 2015 2015-04-06         TN -0.3509769228  <NA> #> 5030  2056E    3M  CC34 2015 2015-04-06         TP -1.6928195214  <NA> #> 5031  2056E    3M  CC34 2015 2015-04-06        TSS  1.6253112616  <NA> #> 5032  2056E    3M  CC34 2015 2015-04-06       TURB  1.0647107370  <NA> #> 5033  2056E    3M  CC34 2015 2015-04-06       COND 10.4033533361  <NA> #> 5034  2056E    3M  CC34 2015 2015-04-06         DO  2.1341664414  <NA> #> 5035  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7899886230     + #> 5036  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0233474406  <NA> #> 5037  2056E    3M  CC34 2015 2015-04-06       COND 10.4069864009  <NA> #> 5038  2056E    3M  CC34 2015 2015-04-06         DO  2.1435893615  <NA> #> 5039  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7949637576     + #> 5040  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0272309406  <NA> #> 5041  2056E    3M  CC36 2015 2015-04-06      CHLAC  1.5040773968  <NA> #> 5042  2056E    3M  CC36 2015 2015-04-06      COLOR  3.8066624898  <NA> #> 5043  2056E    3M  CC36 2015 2015-04-06       COND 10.4003156667  <NA> #> 5044  2056E    3M  CC36 2015 2015-04-06         DO  2.1317967720  <NA> #> 5045  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7899886230     + #> 5046  2056E    3M  CC36 2015 2015-04-06       NO23 -5.5214609179     U #> 5047  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0194488002  <NA> #> 5048  2056E    3M  CC36 2015 2015-04-06        TKN -0.3509769228  <NA> #> 5049  2056E    3M  CC36 2015 2015-04-06         TN -0.3509769228  <NA> #> 5050  2056E    3M  CC36 2015 2015-04-06         TP -1.6928195214  <NA> #> 5051  2056E    3M  CC36 2015 2015-04-06        TSS  1.6253112616  <NA> #> 5052  2056E    3M  CC36 2015 2015-04-06       TURB  1.0647107370  <NA> #> 5053  2056E    3M  CC36 2015 2015-04-06       COND 10.4033533361  <NA> #> 5054  2056E    3M  CC36 2015 2015-04-06         DO  2.1341664414  <NA> #> 5055  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7899886230     + #> 5056  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0233474406  <NA> #> 5057  2056E    3M  CC36 2015 2015-04-06       COND 10.4069864009  <NA> #> 5058  2056E    3M  CC36 2015 2015-04-06         DO  2.1435893615  <NA> #> 5059  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7949637576     + #> 5060  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0272309406  <NA> #> 5061  2056E    3M  CC37 2014 2014-01-06      CHLAC  1.5686159179  <NA> #> 5062  2056E    3M  CC37 2014 2014-01-06      COLOR  2.9957322736     A #> 5063  2056E    3M  CC37 2014 2014-01-06      DOSAT  4.3832758541     + #> 5064  2056E    3M  CC37 2014 2014-01-06       NO23 -4.3428059215  <NA> #> 5065  2056E    3M  CC37 2014 2014-01-06      SALIN  3.3032169733  <NA> #> 5066  2056E    3M  CC37 2014 2014-01-06        TKN -0.5978370008  <NA> #> 5067  2056E    3M  CC37 2014 2014-01-06         TN -0.5744756508     + #> 5068  2056E    3M  CC37 2014 2014-01-06         TP -2.3025850930  <NA> #> 5069  2056E    3M  CC37 2014 2014-01-06       TURB  0.2623642645  <NA> #> 5070  2056E    3M  CC37 2014 2014-02-03      CHLAC  1.4816045409  <NA> #> 5071  2056E    3M  CC37 2014 2014-02-03      COLOR  2.7725887222  <NA> #> 5072  2056E    3M  CC37 2014 2014-02-03         DO  1.8562979904  <NA> #> 5073  2056E    3M  CC37 2014 2014-02-03      DOSAT  4.3502779364     + #> 5074  2056E    3M  CC37 2014 2014-02-03       NO23 -3.2968373663  <NA> #> 5075  2056E    3M  CC37 2014 2014-02-03      SALIN  2.6461747974  <NA> #> 5076  2056E    3M  CC37 2014 2014-02-03        TKN -0.1743533871  <NA> #> 5077  2056E    3M  CC37 2014 2014-02-03         TN -0.1312482866     + #> 5078  2056E    3M  CC37 2014 2014-02-03         TP -2.3025850930  <NA> #> 5079  2056E    3M  CC37 2014 2014-02-03       TURB  0.7419373447  <NA> #> 5080  2056E    3M  CC37 2014 2014-03-03      CHLAC  1.7578579176  <NA> #> 5081  2056E    3M  CC37 2014 2014-03-03      COLOR  2.8903717579     A #> 5082  2056E    3M  CC37 2014 2014-03-03         DO  1.8082887712  <NA> #> 5083  2056E    3M  CC37 2014 2014-03-03      DOSAT  4.3579900568     + #> 5084  2056E    3M  CC37 2014 2014-03-03       NO23 -4.5098600062  <NA> #> 5085  2056E    3M  CC37 2014 2014-03-03      SALIN  3.1000922889  <NA> #> 5086  2056E    3M  CC37 2014 2014-03-03        TKN -0.2744368457  <NA> #> 5087  2056E    3M  CC37 2014 2014-03-03         TN -0.2600669054     + #> 5088  2056E    3M  CC37 2014 2014-03-03         TP -1.8971199849  <NA> #> 5089  2056E    3M  CC37 2014 2014-03-03       TURB  1.0296194172  <NA> #> 5090  2056E    3M  CC37 2014 2014-04-07      CHLAC  2.2721258855  <NA> #> 5091  2056E    3M  CC37 2014 2014-04-07      COLOR  2.9444389792  <NA> #> 5092  2056E    3M  CC37 2014 2014-04-07         DO  1.8718021769  <NA> #> 5093  2056E    3M  CC37 2014 2014-04-07      DOSAT  4.4953553200     + #> 5094  2056E    3M  CC37 2014 2014-04-07       NO23 -4.9618451299     I #> 5095  2056E    3M  CC37 2014 2014-04-07      SALIN  3.1000922889  <NA> #> 5096  2056E    3M  CC37 2014 2014-04-07        TKN -0.4942963218  <NA> #> 5097  2056E    3M  CC37 2014 2014-04-07         TN -0.4877603508     + #> 5098  2056E    3M  CC37 2014 2014-04-07         TP -1.7147984281  <NA> #> 5099  2056E    3M  CC37 2014 2014-04-07       TURB  1.2237754316  <NA> #> 5100  2056E    3M  CC37 2014 2014-05-05      CHLAC  3.0445224377  <NA> #> 5101  2056E    3M  CC37 2014 2014-05-05      COLOR  3.0910424534  <NA> #> 5102  2056E    3M  CC37 2014 2014-05-05         DO  1.7917594692  <NA> #> 5103  2056E    3M  CC37 2014 2014-05-05      DOSAT  4.4152196020     + #> 5104  2056E    3M  CC37 2014 2014-05-05       NO23 -5.1159958098     I #> 5105  2056E    3M  CC37 2014 2014-05-05      SALIN  3.2068032436  <NA> #> 5106  2056E    3M  CC37 2014 2014-05-05        TKN -0.0100503359  <NA> #> 5107  2056E    3M  CC37 2014 2014-05-05         TN -0.0060180723     + #> 5108  2056E    3M  CC37 2014 2014-05-05         TP -1.2729656758  <NA> #> 5109  2056E    3M  CC37 2014 2014-05-05       TURB  1.9315214116  <NA> #> 5110  2056E    3M  CC37 2014 2014-06-02      CHLAC  2.2617630985  <NA> #> 5111  2056E    3M  CC37 2014 2014-06-02      COLOR  3.2188758249  <NA> #> 5112  2056E    3M  CC37 2014 2014-06-02         DO  1.6292405397  <NA> #> 5113  2056E    3M  CC37 2014 2014-06-02      DOSAT  4.3040650932     + #> 5114  2056E    3M  CC37 2014 2014-06-02       NO23 -5.1159958098     I #> 5115  2056E    3M  CC37 2014 2014-06-02      SALIN  3.2425923515  <NA> #> 5116  2056E    3M  CC37 2014 2014-06-02        TKN -0.1625189295  <NA> #> 5117  2056E    3M  CC37 2014 2014-06-02         TN -0.1578240852     + #> 5118  2056E    3M  CC37 2014 2014-06-02         TP -1.0216512475  <NA> #> 5119  2056E    3M  CC37 2014 2014-06-02       TURB  1.4816045409  <NA> #> 5120  2056E    3M  CC37 2014 2014-07-07      CHLAC  2.5649493575  <NA> #> 5121  2056E    3M  CC37 2014 2014-07-07      COLOR  3.3672958300     A #> 5122  2056E    3M  CC37 2014 2014-07-07       NO23 -5.5214609179     I #> 5123  2056E    3M  CC37 2014 2014-07-07      SALIN  3.1398326175  <NA> #> 5124  2056E    3M  CC37 2014 2014-07-07        TKN -0.0304592075  <NA> #> 5125  2056E    3M  CC37 2014 2014-07-07         TN -0.0263439753     + #> 5126  2056E    3M  CC37 2014 2014-07-07         TP -0.9675840263  <NA> #> 5127  2056E    3M  CC37 2014 2014-07-07       TURB  1.5260563035  <NA> #> 5128  2056E    3M  CC37 2014 2014-08-04      CHLAC  2.7080502011  <NA> #> 5129  2056E    3M  CC37 2014 2014-08-04      COLOR  4.0073331852     A #> 5130  2056E    3M  CC37 2014 2014-08-04         DO  1.7047480922  <NA> #> 5131  2056E    3M  CC37 2014 2014-08-04      DOSAT  4.3214801348     + #> 5132  2056E    3M  CC37 2014 2014-08-04       NO23 -4.5098600062  <NA> #> 5133  2056E    3M  CC37 2014 2014-08-04      SALIN  2.4336133554  <NA> #> 5134  2056E    3M  CC37 2014 2014-08-04        TKN  0.0953101798  <NA> #> 5135  2056E    3M  CC37 2014 2014-08-04         TN  0.1052605107     + #> 5136  2056E    3M  CC37 2014 2014-08-04         TP -0.7550225843  <NA> #> 5137  2056E    3M  CC37 2014 2014-08-04       TURB  1.0296194172  <NA> #> 5138  2056E    3M  CC37 2014 2014-09-08      CHLAC  0.5877866649  <NA> #> 5139  2056E    3M  CC37 2014 2014-09-08      COLOR  3.6375861597     A #> 5140  2056E    3M  CC37 2014 2014-09-08      DOSAT  3.7588718259     + #> 5141  2056E    3M  CC37 2014 2014-09-08       NO23 -4.1997050779  <NA> #> 5142  2056E    3M  CC37 2014 2014-09-08      SALIN  2.6318888401  <NA> #> 5143  2056E    3M  CC37 2014 2014-09-08        TKN -0.1743533871  <NA> #> 5144  2056E    3M  CC37 2014 2014-09-08         TN -0.1566538100     + #> 5145  2056E    3M  CC37 2014 2014-09-08         TP -1.0498221245  <NA> #> 5146  2056E    3M  CC37 2014 2014-09-08       TURB  0.6931471806     A #> 5147  2056E    3M  CC37 2014 2014-10-06      CHLAC  1.7917594692  <NA> #> 5148  2056E    3M  CC37 2014 2014-10-06      COLOR  4.1588830834     A #> 5149  2056E    3M  CC37 2014 2014-10-06         DO  1.3350010667  <NA> #> 5150  2056E    3M  CC37 2014 2014-10-06      DOSAT  3.8458832029     + #> 5151  2056E    3M  CC37 2014 2014-10-06       NO23 -2.9957322736  <NA> #> 5152  2056E    3M  CC37 2014 2014-10-06      SALIN  1.9600947840  <NA> #> 5153  2056E    3M  CC37 2014 2014-10-06        TKN -0.1508228897  <NA> #> 5154  2056E    3M  CC37 2014 2014-10-06         TN -0.0943106795     + #> 5155  2056E    3M  CC37 2014 2014-10-06         TP -1.1086626245  <NA> #> 5156  2056E    3M  CC37 2014 2014-10-06       TURB  0.8754687374  <NA> #> 5157  2056E    3M  CC37 2014 2014-11-03      CHLAC  2.1517622033  <NA> #> 5158  2056E    3M  CC37 2014 2014-11-03      COLOR  3.9318256327     A #> 5159  2056E    3M  CC37 2014 2014-11-03         DO  1.8245492921  <NA> #> 5160  2056E    3M  CC37 2014 2014-11-03      DOSAT  4.2499227940     + #> 5161  2056E    3M  CC37 2014 2014-11-03       NO23 -4.2686979494  <NA> #> 5162  2056E    3M  CC37 2014 2014-11-03      SALIN  2.7600099400  <NA> #> 5163  2056E    3M  CC37 2014 2014-11-03        TKN -0.1508228897  <NA> #> 5164  2056E    3M  CC37 2014 2014-11-03         TN -0.1346749033     + #> 5165  2056E    3M  CC37 2014 2014-11-03         TP 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3M  CC37 2015 2015-01-05         DO  1.7917594692  <NA> #> 5180  2056E    3M  CC37 2015 2015-01-05      DOSAT  4.3732381286     + #> 5181  2056E    3M  CC37 2015 2015-01-05       NO23 -3.9633162998  <NA> #> 5182  2056E    3M  CC37 2015 2015-01-05      SALIN  2.9549102790  <NA> #> 5183  2056E    3M  CC37 2015 2015-01-05        TKN -0.4780358009  <NA> #> 5184  2056E    3M  CC37 2015 2015-01-05         TN -0.4478508246     + #> 5185  2056E    3M  CC37 2015 2015-01-05         TP -2.1202635362  <NA> #> 5186  2056E    3M  CC37 2015 2015-01-05       TURB  0.8754687374  <NA> #> 5187  2056E    3M  CC37 2015 2015-02-02      CHLAC  1.6094379124  <NA> #> 5188  2056E    3M  CC37 2015 2015-02-02      COLOR  2.8332133441     A #> 5189  2056E    3M  CC37 2015 2015-02-02         DO  1.8245492921  <NA> #> 5190  2056E    3M  CC37 2015 2015-02-02      DOSAT  4.3333614627     + #> 5191  2056E    3M  CC37 2015 2015-02-02       NO23 -4.6051701860  <NA> #> 5192  2056E    3M  CC37 2015 2015-02-02      SALIN  3.0773122605  <NA> #> 5193  2056E    3M  CC37 2015 2015-02-02        TKN -0.6733445533  <NA> #> 5194  2056E    3M  CC37 2015 2015-02-02         TN -0.6539264674     + #> 5195  2056E    3M  CC37 2015 2015-02-02         TP -2.1202635362  <NA> #> 5196  2056E    3M  CC37 2015 2015-02-02       TURB  0.9162907319  <NA> #> 5197  2056E    3M  CC37 2015 2015-03-02      CHLAC  2.0014800002  <NA> #> 5198  2056E    3M  CC37 2015 2015-03-02      COLOR  3.2958368660  <NA> #> 5199  2056E    3M  CC37 2015 2015-03-02         DO  1.6486586256  <NA> #> 5200  2056E    3M  CC37 2015 2015-03-02      DOSAT  4.2002049529     + #> 5201  2056E    3M  CC37 2015 2015-03-02       NO23 -2.9759296463  <NA> #> 5202  2056E    3M  CC37 2015 2015-03-02      SALIN  2.9285235239  <NA> #> 5203  2056E    3M  CC37 2015 2015-03-02        TKN -0.3566749439  <NA> #> 5204  2056E    3M  CC37 2015 2015-03-02         TN -0.2863496272     + #> 5205  2056E    3M  CC37 2015 2015-03-02         TP -2.0402208285  <NA> #> 5206  2056E    3M  CC37 2015 2015-03-02       TURB  0.7419373447  <NA> #> 5207  2056E    3M  CC37 2015 2015-04-06      CHLAC  1.8245492921  <NA> #> 5208  2056E    3M  CC37 2015 2015-04-06      COLOR  3.2188758249     A #> 5209  2056E    3M  CC37 2015 2015-04-06         DO  1.6292405397  <NA> #> 5210  2056E    3M  CC37 2015 2015-04-06      DOSAT  4.2297491992     + #> 5211  2056E    3M  CC37 2015 2015-04-06       NO23 -4.5098600062  <NA> #> 5212  2056E    3M  CC37 2015 2015-04-06      SALIN  3.0252910758  <NA> #> 5213  2056E    3M  CC37 2015 2015-04-06        TKN -0.1165338163  <NA> #> 5214  2056E    3M  CC37 2015 2015-04-06         TN -0.1042500214     + #> 5215  2056E    3M  CC37 2015 2015-04-06         TP -1.6094379124  <NA> #> 5216  2056E    3M  CC37 2015 2015-04-06       TURB  1.3083328197  <NA> #> 5217  2056E    3M  CC37 2015 2015-05-04      CHLAC  1.7917594692  <NA> #> 5218  2056E    3M  CC37 2015 2015-05-04      COLOR  3.2958368660     A #> 5219  2056E    3M  CC37 2015 2015-05-04         DO  1.4816045409  <NA> #> 5220  2056E    3M  CC37 2015 2015-05-04      DOSAT  4.0724397268     + #> 5221  2056E    3M  CC37 2015 2015-05-04       NO23 -5.2983173665     I #> 5222  2056E    3M  CC37 2015 2015-05-04      SALIN  3.0773122605  <NA> #> 5223  2056E    3M  CC37 2015 2015-05-04        TKN -0.3856624808  <NA> #> 5224  2056E    3M  CC37 2015 2015-05-04         TN -0.3797973614     + #> 5225  2056E    3M  CC37 2015 2015-05-04         TP -2.0402208285  <NA> #> 5226  2056E    3M  CC37 2015 2015-05-04       TURB  1.3350010667  <NA> #> 5227  2056E    3M  CC37 2015 2015-06-01      CHLAC  2.7080502011  <NA> #> 5228  2056E    3M  CC37 2015 2015-06-01      COLOR  3.2188758249     A #> 5229  2056E    3M  CC37 2015 2015-06-01      DOSAT  4.0587173846     + #> 5230  2056E    3M  CC37 2015 2015-06-01       NO23 -5.1159958098     I #> 5231  2056E    3M  CC37 2015 2015-06-01      SALIN  2.8332133441  <NA> #> 5232  2056E    3M  CC37 2015 2015-06-01        TKN  0.0000000000  <NA> #> 5233  2056E    3M  CC37 2015 2015-06-01         TN  0.0039920213     + #> 5234  2056E    3M  CC37 2015 2015-06-01         TP -1.1711829815  <NA> #> 5235  2056E    3M  CC37 2015 2015-06-01       TURB  1.5475625087     A #> 5236  2056E    3M  CC37 2015 2015-08-03      CHLAC  3.2580965380  <NA> #> 5237  2056E    3M  CC37 2015 2015-08-03      COLOR  3.8286413965  <NA> #> 5238  2056E    3M  CC37 2015 2015-08-03         DO  1.9169226122  <NA> #> 5239  2056E    3M  CC37 2015 2015-08-03      DOSAT  4.4784725329     + #> 5240  2056E    3M  CC37 2015 2015-08-03       NO23 -4.0173835211  <NA> #> 5241  2056E    3M  CC37 2015 2015-08-03      SALIN  1.9021075264  <NA> #> 5242  2056E    3M  CC37 2015 2015-08-03        TKN  0.0000000000  <NA> #> 5243  2056E    3M  CC37 2015 2015-08-03         TN  0.0178399181     + #> 5244  2056E    3M  CC37 2015 2015-08-03         TP -0.8439700703  <NA> #> 5245  2056E    3M  CC37 2015 2015-08-03       TURB  1.0986122887     A #> 5246  2056E    3M  CC37 2015 2015-09-08      CHLAC  2.7080502011  <NA> #> 5247  2056E    3M  CC37 2015 2015-09-08      COLOR  4.7004803658     A #> 5248  2056E    3M  CC37 2015 2015-09-08         DO  1.7227665977  <NA> #> 5249  2056E    3M  CC37 2015 2015-09-08      DOSAT  4.3067641502     + #> 5250  2056E    3M  CC37 2015 2015-09-08       NO23 -3.3242363405  <NA> #> 5251  2056E    3M  CC37 2015 2015-09-08      SALIN  1.7749523509  <NA> #> 5252  2056E    3M  CC37 2015 2015-09-08        TKN  0.1823215568  <NA> #> 5253  2056E    3M  CC37 2015 2015-09-08         TN  0.2118803590     + #> 5254  2056E    3M  CC37 2015 2015-09-08         TP -0.2613647641  <NA> #> 5255  2056E    3M  CC37 2015 2015-09-08       TURB  1.3083328197  <NA> #> 5256  2056E    3M  CC37 2015 2015-10-05      CHLAC  2.3978952728  <NA> #> 5257  2056E    3M  CC37 2015 2015-10-05      COLOR  4.5643481915     A #> 5258  2056E    3M  CC37 2015 2015-10-05         DO  1.8562979904  <NA> #> 5259  2056E    3M  CC37 2015 2015-10-05      DOSAT  4.3732381286     + #> 5260  2056E    3M  CC37 2015 2015-10-05       NO23 -3.7722610631  <NA> #> 5261  2056E    3M  CC37 2015 2015-10-05      SALIN  2.2721258855  <NA> #> 5262  2056E    3M  CC37 2015 2015-10-05        TKN -0.2876820725  <NA> #> 5263  2056E    3M  CC37 2015 2015-10-05         TN -0.2574762304     + #> 5264  2056E    3M  CC37 2015 2015-10-05         TP -0.9416085399  <NA> #> 5265  2056E    3M  CC37 2015 2015-10-05       TURB  0.4054651081  <NA> #> 5266  2056E    3M  CC37 2016 2016-02-01      CHLAC  2.6390573296  <NA> #> 5267  2056E    3M  CC37 2016 2016-02-01      COLOR  4.5217885770     A #> 5268  2056E    3M  CC37 2016 2016-02-01       NO23 -1.9661128564  <NA> #> 5269  2056E    3M  CC37 2016 2016-02-01        TKN -0.3285040670  <NA> #> 5270  2056E    3M  CC37 2016 2016-02-01         TN -0.1508228897     + #> 5271  2056E    3M  CC37 2016 2016-02-01         TP -1.0216512475  <NA> #> 5272  2056E    3M  CC37 2016 2016-02-01       TURB  0.9162907319  <NA> #> 5273  2056E    3M  CC37 2016 2016-03-07      CHLAC  2.4849066498  <NA> #> 5274  2056E    3M  CC37 2016 2016-03-07      COLOR  3.8918202981     A #> 5275  2056E    3M  CC37 2016 2016-03-07         DO  1.6331544391  <NA> #> 5276  2056E    3M  CC37 2016 2016-03-07      DOSAT  4.0859763126     + #> 5277  2056E    3M  CC37 2016 2016-03-07       NO23 -4.1997050779  <NA> #> 5278  2056E    3M  CC37 2016 2016-03-07      SALIN  2.7040421797  <NA> #> 5279  2056E    3M  CC37 2016 2016-03-07        TKN -0.3011050928  <NA> #> 5280  2056E    3M  CC37 2016 2016-03-07         TN -0.2810375297     + #> 5281  2056E    3M  CC37 2016 2016-03-07         TP -1.5141277326  <NA> #> 5282  2056E    3M  CC37 2016 2016-03-07       TURB  1.2527629685  <NA> #> 5283  2056E    3M  CC37 2016 2016-04-04      CHLAC  2.3978952728  <NA> #> 5284  2056E    3M  CC37 2016 2016-04-04      COLOR  3.6635616461  <NA> #> 5285  2056E    3M  CC37 2016 2016-04-04         DO  1.3711807233  <NA> #> 5286  2056E    3M  CC37 2016 2016-04-04      DOSAT  3.9512437186     + #> 5287  2056E    3M  CC37 2016 2016-04-04       NO23 -3.5065578973  <NA> #> 5288  2056E    3M  CC37 2016 2016-04-04      SALIN  2.6905648868  <NA> #> 5289  2056E    3M  CC37 2016 2016-04-04        TKN -0.0202027073  <NA> #> 5290  2056E    3M  CC37 2016 2016-04-04         TN  0.0099503309     + #> 5291  2056E    3M  CC37 2016 2016-04-04         TP -1.3470736480  <NA> #> 5292  2056E    3M  CC37 2016 2016-04-04       TURB  1.5260563035  <NA> #> 5293  2056E    3M  CC37 2017 2017-02-06      CHLAC  2.8903717579  <NA> #> 5294  2056E    3M  CC37 2017 2017-02-06      COLOR  2.9444389792     A #> 5295  2056E    3M  CC37 2017 2017-02-06         DO  1.6311994042  <NA> #> 5296  2056E    3M  CC37 2017 2017-02-06      DOSAT  4.2239097666     + #> 5297  2056E    3M  CC37 2017 2017-02-06       NO23 -5.5214609179     U #> 5298  2056E    3M  CC37 2017 2017-02-06      SALIN  3.3138223022  <NA> #> 5299  2056E    3M  CC37 2017 2017-02-06        TKN -0.0943106795  <NA> #> 5300  2056E    3M  CC37 2017 2017-02-06         TN -0.0921152889     + #> 5301  2056E    3M  CC37 2017 2017-02-06         TP -1.7147984281  <NA> #> 5302  2056E    3M  CC37 2017 2017-02-06       TURB  1.8562979904  <NA> #> 5303  2056E    3M  CC37 2017 2017-03-06      CHLAC  2.1517622033  <NA> #> 5304  2056E    3M  CC37 2017 2017-03-06      COLOR  2.7080502011  <NA> #> 5305  2056E    3M  CC37 2017 2017-03-06         DO  1.7191887764  <NA> #> 5306  2056E    3M  CC37 2017 2017-03-06      DOSAT  4.2931954210     + #> 5307  2056E    3M  CC37 2017 2017-03-06       NO23 -5.5214609179     U #> 5308  2056E    3M  CC37 2017 2017-03-06      SALIN  3.3279095859  <NA> #> 5309  2056E    3M  CC37 2017 2017-03-06        TKN -0.1743533871  <NA> #> 5310  2056E    3M  CC37 2017 2017-03-06         TN -0.1719752647     + #> 5311  2056E    3M  CC37 2017 2017-03-06         TP -1.9661128564  <NA> #> 5312  2056E    3M  CC37 2017 2017-03-06       TURB  1.3862943611  <NA> #> 5313  2056E    3M  CC37 2017 2017-04-03      CHLAC  2.3978952728  <NA> #> 5314  2056E    3M  CC37 2017 2017-04-03      COLOR  2.7080502011     A #> 5315  2056E    3M  CC37 2017 2017-04-03         DO  1.5727739281  <NA> #> 5316  2056E    3M  CC37 2017 2017-04-03      DOSAT  4.2640873368     + #> 5317  2056E    3M  CC37 2017 2017-04-03       NO23 -5.5214609179     U #> 5318  2056E    3M  CC37 2017 2017-04-03      SALIN  3.3914836895  <NA> #> 5319  2056E    3M  CC37 2017 2017-04-03        TKN -0.1508228897  <NA> #> 5320  2056E    3M  CC37 2017 2017-04-03         TN -0.1485000083     + #> 5321  2056E    3M  CC37 2017 2017-04-03         TP -1.6607312068  <NA> #> 5322  2056E    3M  CC37 2017 2017-04-03       TURB  1.3862943611     A #> 5323  2056E    3M  CC37 2017 2017-07-10      CHLAC  2.7080502011  <NA> #> 5324  2056E    3M  CC37 2017 2017-07-10      COLOR  4.7874917428     A #> 5325  2056E    3M  CC37 2017 2017-07-10         DO  0.8415671857  <NA> #> 5326  2056E    3M  CC37 2017 2017-07-10      DOSAT  3.4965075615     + #> 5327  2056E    3M  CC37 2017 2017-07-10       NO23 -5.1159958098     I #> 5328  2056E    3M  CC37 2017 2017-07-10        TKN  0.1823215568  <NA> #> 5329  2056E    3M  CC37 2017 2017-07-10         TN  0.1856493469     + #> 5330  2056E    3M  CC37 2017 2017-07-10         TP -0.4780358009  <NA> #> 5331  2056E    3M  CC37 2017 2017-07-10       TURB  1.1939224685  <NA> #> 5332  2056E    3M  CC37 2017 2017-08-07      CHLAC  1.6863989536  <NA> #> 5333  2056E    3M  CC37 2017 2017-08-07      COLOR  4.7004803658  <NA> #> 5334  2056E    3M  CC37 2017 2017-08-07         DO  0.7793248768  <NA> #> 5335  2056E    3M  CC37 2017 2017-08-07      DOSAT  3.4144426084     + #> 5336  2056E    3M  CC37 2017 2017-08-07       NO23 -2.2072749132  <NA> #> 5337  2056E    3M  CC37 2017 2017-08-07      SALIN  1.7647307968  <NA> #> 5338  2056E    3M  CC37 2017 2017-08-07        TKN  0.1823215568  <NA> #> 5339  2056E    3M  CC37 2017 2017-08-07         TN  0.2700271372     + #> 5340  2056E    3M  CC37 2017 2017-08-07         TP -0.8209805521  <NA> #> 5341  2056E    3M  CC37 2017 2017-08-07       TURB  0.7884573604  <NA> #> 5342  2056E    3M  CC37 2017 2017-09-05      CHLAC  2.8332133441  <NA> #> 5343  2056E    3M  CC37 2017 2017-09-05      COLOR  4.4998096703  <NA> #> 5344  2056E    3M  CC37 2017 2017-09-05         DO  1.4516138272  <NA> #> 5345  2056E    3M  CC37 2017 2017-09-05      DOSAT  4.0377742107     + #> 5346  2056E    3M  CC37 2017 2017-09-05       NO23 -2.4889146712  <NA> #> 5347  2056E    3M  CC37 2017 2017-09-05      SALIN  0.1906203596  <NA> #> 5348  2056E    3M  CC37 2017 2017-09-05        TKN -0.0725706928  <NA> #> 5349  2056E    3M  CC37 2017 2017-09-05         TN  0.0129162253     + #> 5350  2056E    3M  CC37 2017 2017-09-05         TP -0.9675840263  <NA> #> 5351  2056E    3M  CC37 2017 2017-09-05       TURB  1.0986122887  <NA> #> 5352  2056E    3M  CC37 2017 2017-10-02      CHLAC  1.9169226122  <NA> #> 5353  2056E    3M  CC37 2017 2017-10-02      COLOR  4.4886363697     A #> 5354  2056E    3M  CC37 2017 2017-10-02       NO23 -2.9565115604  <NA> #> 5355  2056E    3M  CC37 2017 2017-10-02        TKN -0.8675005677  <NA> #> 5356  2056E    3M  CC37 2017 2017-10-02         TN -0.7507762934     + #> 5357  2056E    3M  CC37 2017 2017-10-02         TP -0.6348782724  <NA> #> 5358  2056E    3M  CC37 2017 2017-10-02       TURB  0.7419373447  <NA> #> 5359  2056E    3M  CC37 2017 2017-11-06      CHLAC  1.6292405397  <NA> #> 5360  2056E    3M  CC37 2017 2017-11-06      COLOR  3.8918202981     A #> 5361  2056E    3M  CC37 2017 2017-11-06         DO  1.7595805709  <NA> #> 5362  2056E    3M  CC37 2017 2017-11-06      DOSAT  4.3605476030  <NA> #> 5363  2056E    3M  CC37 2017 2017-11-06       NO23 -3.7722610631  <NA> #> 5364  2056E    3M  CC37 2017 2017-11-06      SALIN  2.9549102790  <NA> #> 5365  2056E    3M  CC37 2017 2017-11-06        TKN -0.4620354596  <NA> #> 5366  2056E    3M  CC37 2017 2017-11-06         TN -0.4261781497     + #> 5367  2056E    3M  CC37 2017 2017-11-06         TP -1.4696759701  <NA> #> 5368  2056E    3M  CC37 2017 2017-11-06       TURB  0.2623642645  <NA> #> 5369  2056E    3M  CC37 2017 2017-12-04      CHLAC  1.6677068206  <NA> #> 5370  2056E    3M  CC37 2017 2017-12-04      COLOR  3.4657359028  <NA> #> 5371  2056E    3M  CC37 2017 2017-12-04         DO  1.5686159179  <NA> #> 5372  2056E    3M  CC37 2017 2017-12-04      DOSAT  4.1541845626  <NA> #> 5373  2056E    3M  CC37 2017 2017-12-04       NO23 -5.5214609179     U #> 5374  2056E    3M  CC37 2017 2017-12-04      SALIN  3.0914968955  <NA> #> 5375  2056E    3M  CC37 2017 2017-12-04        TKN -0.1743533871  <NA> #> 5376  2056E    3M  CC37 2017 2017-12-04         TN -0.1719752647     + #> 5377  2056E    3M  CC37 2017 2017-12-04         TP -1.2039728043  <NA> #> 5378  2056E    3M  CC37 2017 2017-12-04       TURB  1.0647107370  <NA> #> 5379  2056E    3M  CC37 2018 2018-01-02      CHLAC  2.8332133441  <NA> #> 5380  2056E    3M  CC37 2018 2018-01-02      COLOR  3.2188758249  <NA> #> 5381  2056E    3M  CC37 2018 2018-01-02         DO  1.7101878155  <NA> #> 5382  2056E    3M  CC37 2018 2018-01-02      DOSAT  4.1789920363     + #> 5383  2056E    3M  CC37 2018 2018-01-02       NO23 -5.2983173665     I #> 5384  2056E    3M  CC37 2018 2018-01-02      SALIN  3.1045866785  <NA> #> 5385  2056E    3M  CC37 2018 2018-01-02        TKN -0.1278333715  <NA> #> 5386  2056E    3M  CC37 2018 2018-01-02         TN -0.1232982163     + #> 5387  2056E    3M  CC37 2018 2018-01-02         TP -0.6348782724  <NA> #> 5388  2056E    3M  CC37 2018 2018-01-02       TURB  1.5040773968  <NA> #> 5389  2056E    3M  CC37 2018 2018-02-05      CHLAC  3.0445224377  <NA> #> 5390  2056E    3M  CC37 2018 2018-02-05      COLOR  3.0910424534  <NA> #> 5391  2056E    3M  CC37 2018 2018-02-05         DO  1.7227665977  <NA> #> 5392  2056E    3M  CC37 2018 2018-02-05      DOSAT  4.3067641502  <NA> #> 5393  2056E    3M  CC37 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 5394  2056E    3M  CC37 2018 2018-02-05      SALIN  3.1311369106  <NA> #> 5395  2056E    3M  CC37 2018 2018-02-05        TKN -0.5108256238  <NA> #> 5396  2056E    3M  CC37 2018 2018-02-05         TN -0.4845083154     + #> 5397  2056E    3M  CC37 2018 2018-02-05         TP -2.0402208285  <NA> #> 5398  2056E    3M  CC37 2018 2018-02-05       TURB  1.3609765531  <NA> #> 5399  2056E    3M  CC37 2018 2018-03-05      CHLAC  1.9315214116  <NA> #> 5400  2056E    3M  CC37 2018 2018-03-05      COLOR  3.1780538303     A #> 5401  2056E    3M  CC37 2018 2018-03-05         DO  1.4973884086  <NA> #> 5402  2056E    3M  CC37 2018 2018-03-05      DOSAT  4.0656020934  <NA> #> 5403  2056E    3M  CC37 2018 2018-03-05       NO23 -5.2983173665     I #> 5404  2056E    3M  CC37 2018 2018-03-05      SALIN  3.1540172525  <NA> #> 5405  2056E    3M  CC37 2018 2018-03-05        TKN -0.2613647641  <NA> #> 5406  2056E    3M  CC37 2018 2018-03-05         TN -0.2561834054     + #> 5407  2056E    3M  CC37 2018 2018-03-05         TP -1.6607312068  <NA> #> 5408  2056E    3M  CC37 2018 2018-03-05       TURB  1.3083328197  <NA> #> 5409  2056E    3M  CC37 2018 2018-04-02      CHLAC  2.3978952728  <NA> #> 5410  2056E    3M  CC37 2018 2018-04-02      COLOR  2.9444389792     A #> 5411  2056E    3M  CC37 2018 2018-04-02         DO  1.3660916538  <NA> #> 5412  2056E    3M  CC37 2018 2018-04-02      DOSAT  3.9963641539  <NA> #> 5413  2056E    3M  CC37 2018 2018-04-02       NO23 -4.8283137373     I #> 5414  2056E    3M  CC37 2018 2018-04-02      SALIN  3.2461018111  <NA> #> 5415  2056E    3M  CC37 2018 2018-04-02        TKN -0.2613647641  <NA> #> 5416  2056E    3M  CC37 2018 2018-04-02         TN -0.2561834054     + #> 5417  2056E    3M  CC37 2018 2018-04-02         TP -1.6607312068  <NA> #> 5418  2056E    3M  CC37 2018 2018-04-02       TURB  1.4109869737     A #> 5419  2056E    3M  CC37 2018 2018-05-07      CHLAC  2.6390573296  <NA> #> 5420  2056E    3M  CC37 2018 2018-05-07      COLOR  3.0445224377  <NA> #> 5421  2056E    3M  CC37 2018 2018-05-07         DO  1.4011829736  <NA> #> 5422  2056E    3M  CC37 2018 2018-05-07      DOSAT  4.0656020934  <NA> #> 5423  2056E    3M  CC37 2018 2018-05-07       NO23 -5.2983173665     I #> 5424  2056E    3M  CC37 2018 2018-05-07      SALIN  3.3225148596  <NA> #> 5425  2056E    3M  CC37 2018 2018-05-07        TKN -0.0833816089  <NA> #> 5426  2056E    3M  CC37 2018 2018-05-07         TN -0.0790432073     + #> 5427  2056E    3M  CC37 2018 2018-05-07         TP -1.5606477483  <NA> #> 5428  2056E    3M  CC37 2018 2018-05-07       TURB  1.5260563035  <NA> #> 5429  2056E    3M  CC37 2018 2018-06-04      CHLAC  3.2958368660  <NA> #> 5430  2056E    3M  CC37 2018 2018-06-04      COLOR  4.4773368145  <NA> #> 5431  2056E    3M  CC37 2018 2018-06-04         DO  1.9286186519  <NA> #> 5432  2056E    3M  CC37 2018 2018-06-04      DOSAT  4.5390303835  <NA> #> 5433  2056E    3M  CC37 2018 2018-06-04       NO23 -4.0745419349  <NA> #> 5434  2056E    3M  CC37 2018 2018-06-04      SALIN  1.9095425049  <NA> #> 5435  2056E    3M  CC37 2018 2018-06-04        TKN  0.1823215568  <NA> #> 5436  2056E    3M  CC37 2018 2018-06-04         TN  0.1963888140     + #> 5437  2056E    3M  CC37 2018 2018-06-04         TP -0.9942522733  <NA> #> 5438  2056E    3M  CC37 2018 2018-06-04       TURB  1.3862943611  <NA> #> 5439  2056E    3M  CC37 2018 2018-07-09      CHLAC  2.6390573296  <NA> #> 5440  2056E    3M  CC37 2018 2018-07-09      COLOR  4.8675344505  <NA> #> 5441  2056E    3M  CC37 2018 2018-07-09         DO  1.2919836816  <NA> #> 5442  2056E    3M  CC37 2018 2018-07-09      DOSAT  3.7977338590  <NA> #> 5443  2056E    3M  CC37 2018 2018-07-09       NO23 -2.6310891600  <NA> #> 5444  2056E    3M  CC37 2018 2018-07-09      SALIN  1.8148247422  <NA> #> 5445  2056E    3M  CC37 2018 2018-07-09        TKN  0.1823215568  <NA> #> 5446  2056E    3M  CC37 2018 2018-07-09         TN  0.2405904649     + #> 5447  2056E    3M  CC37 2018 2018-07-09         TP -0.8675005677  <NA> #> 5448  2056E    3M  CC37 2018 2018-07-09       TURB  0.6931471806     A #> 5449  2056E    3M  CC37 2018 2018-08-06      CHLAC  1.8562979904  <NA> #> 5450  2056E    3M  CC37 2018 2018-08-06      COLOR  4.8675344505  <NA> #> 5451  2056E    3M  CC37 2018 2018-08-06         DO  1.3428648032  <NA> #> 5452  2056E    3M  CC37 2018 2018-08-06      DOSAT  3.9435216725  <NA> #> 5453  2056E    3M  CC37 2018 2018-08-06       NO23 -1.8325814637  <NA> #> 5454  2056E    3M  CC37 2018 2018-08-06      SALIN  1.1281710909  <NA> #> 5455  2056E    3M  CC37 2018 2018-08-06        TKN  0.0953101798  <NA> #> 5456  2056E    3M  CC37 2018 2018-08-06         TN  0.2311117210     + #> 5457  2056E    3M  CC37 2018 2018-08-06         TP -0.8209805521  <NA> #> 5458  2056E    3M  CC37 2018 2018-08-06       TURB  0.5877866649  <NA> #> 5459  2056E    3M  CC37 2019 2019-02-04      CHLAC  1.9878743482     A #> 5460  2056E    3M  CC37 2019 2019-02-04      COLOR  3.3322045102  <NA> #> 5461  2056E    3M  CC37 2019 2019-02-04         DO  2.0438143640  <NA> #> 5462  2056E    3M  CC37 2019 2019-02-04      DOSAT  4.5622626850  <NA> #> 5463  2056E    3M  CC37 2019 2019-02-04       NO23 -5.2983173665     I #> 5464  2056E    3M  CC37 2019 2019-02-04      SALIN  2.7447035188  <NA> #> 5465  2056E    3M  CC37 2019 2019-02-04        TKN -0.4780358009  <NA> #> 5466  2056E    3M  CC37 2019 2019-02-04         TN -0.4716049106     + #> 5467  2056E    3M  CC37 2019 2019-02-04         TP -1.7147984281  <NA> #> 5468  2056E    3M  CC37 2019 2019-02-04       TURB  0.7884573604  <NA> #> 5469  2056E    3M  CC37 2019 2019-05-06      CHLAC  2.3978952728  <NA> #> 5470  2056E    3M  CC37 2019 2019-05-06      COLOR  3.1780538303     A #> 5471  2056E    3M  CC37 2019 2019-05-06         DO  1.3110318766  <NA> #> 5472  2056E    3M  CC37 2019 2019-05-06      DOSAT  3.9759363312  <NA> #> 5473  2056E    3M  CC37 2019 2019-05-06       NO23 -5.5214609179     U #> 5474  2056E    3M  CC37 2019 2019-05-06      SALIN  3.0320642028  <NA> #> 5475  2056E    3M  CC37 2019 2019-05-06         TN -0.2331938872     + #> 5476  2056E    3M  CC37 2019 2019-05-06         TP -1.4696759701  <NA> #> 5477  2056E    3M  CC37 2019 2019-05-06       TURB  1.3350010667  <NA> #> 5478  2056E    3M  CC37 2019 2019-06-03      CHLAC  2.0281482473  <NA> #> 5479  2056E    3M  CC37 2019 2019-06-03      COLOR  3.2188758249     A #> 5480  2056E    3M  CC37 2019 2019-06-03         DO  1.2864740258  <NA> #> 5481  2056E    3M  CC37 2019 2019-06-03      DOSAT  3.9815490681  <NA> #> 5482  2056E    3M  CC37 2019 2019-06-03       NO23 -5.5214609179     U #> 5483  2056E    3M  CC37 2019 2019-06-03      SALIN  2.9982291538  <NA> #> 5484  2056E    3M  CC37 2019 2019-06-03        TKN -0.0512932944  <NA> #> 5485  2056E    3M  CC37 2019 2019-06-03         TN -0.0491902442     + #> 5486  2056E    3M  CC37 2019 2019-06-03         TP -0.9416085399  <NA> #> 5487  2056E    3M  CC37 2019 2019-06-03       TURB  0.8754687374  <NA> #> 5488  2056E    3M  CC37 2019 2019-07-01      CHLAC  3.1354942159  <NA> #> 5489  2056E    3M  CC37 2019 2019-07-01      COLOR  3.5553480615     A #> 5490  2056E    3M  CC37 2019 2019-07-01         DO  0.6259384309  <NA> #> 5491  2056E    3M  CC37 2019 2019-07-01      DOSAT  3.1441522787  <NA> #> 5492  2056E    3M  CC37 2019 2019-07-01       NO23 -5.5214609179     I #> 5493  2056E    3M  CC37 2019 2019-07-01      SALIN  2.7825390531  <NA> #> 5494  2056E    3M  CC37 2019 2019-07-01        TKN -0.1278333715  <NA> #> 5495  2056E    3M  CC37 2019 2019-07-01         TN -0.1232982163     + #> 5496  2056E    3M  CC37 2019 2019-07-01         TP -0.5798184953  <NA> #> 5497  2056E    3M  CC37 2019 2019-07-01       TURB  1.0296194172  <NA> #> 5498  2056E    3M  CC37 2019 2019-08-05      CHLAC  3.1354942159  <NA> #> 5499  2056E    3M  CC37 2019 2019-08-05      COLOR  4.2341065046     A #> 5500  2056E    3M  CC37 2019 2019-08-05         DO  1.9685099810  <NA> #> 5501  2056E    3M  CC37 2019 2019-08-05      DOSAT  4.5880240272  <NA> #> 5502  2056E    3M  CC37 2019 2019-08-05       NO23 -4.9618451299     I #> 5503  2056E    3M  CC37 2019 2019-08-05      SALIN  2.0744289999  <NA> #> 5504  2056E    3M  CC37 2019 2019-08-05        TKN -0.1053605157  <NA> #> 5505  2056E    3M  CC37 2019 2019-08-05         TN -0.1009259186     + #> 5506  2056E    3M  CC37 2019 2019-08-05         TP -1.1086626245  <NA> #> 5507  2056E    3M  CC37 2019 2019-08-05       TURB  1.1314021115  <NA> #> 5508  2056E    3M  CC37 2019 2019-10-07      CHLAC  2.0794415417  <NA> #> 5509  2056E    3M  CC37 2019 2019-10-07      COLOR  3.7376696183     A #> 5510  2056E    3M  CC37 2019 2019-10-07         DO  1.4036429995  <NA> #> 5511  2056E    3M  CC37 2019 2019-10-07      DOSAT  4.0910056610  <NA> #> 5512  2056E    3M  CC37 2019 2019-10-07       NO23 -5.5214609179     U #> 5513  2056E    3M  CC37 2019 2019-10-07      SALIN  3.0842009215  <NA> #> 5514  2056E    3M  CC37 2019 2019-10-07        TKN -0.3566749439  <NA> #> 5515  2056E    3M  CC37 2019 2019-10-07         TN -0.3538218750     + #> 5516  2056E    3M  CC37 2019 2019-10-07         TP -1.6607312068  <NA> #> 5517  2056E    3M  CC37 2019 2019-10-07       TURB  0.4054651081  <NA> #> 5518  2056E    3M  CC37 2019 2019-11-04      CHLAC  1.1939224685  <NA> #> 5519  2056E    3M  CC37 2019 2019-11-04      COLOR  3.5835189385  <NA> #> 5520  2056E    3M  CC37 2019 2019-11-04         DO  1.6034198401  <NA> #> 5521  2056E    3M  CC37 2019 2019-11-04      DOSAT  4.2470656492  <NA> #> 5522  2056E    3M  CC37 2019 2019-11-04       NO23 -4.4228486292  <NA> #> 5523  2056E    3M  CC37 2019 2019-11-04      SALIN  2.9922261342  <NA> #> 5524  2056E    3M  CC37 2019 2019-11-04        TKN -0.3285040670  <NA> #> 5525  2056E    3M  CC37 2019 2019-11-04         TN -0.3119747650     + #> 5526  2056E    3M  CC37 2019 2019-11-04         TP -1.4271163556  <NA> #> 5527  2056E    3M  CC37 2019 2019-11-04       TURB  0.0000000000  <NA> #> 5528  2056E    3M  CC37 2019 2019-12-02      CHLAC  1.8245492921     A #> 5529  2056E    3M  CC37 2019 2019-12-02      COLOR  3.3322045102  <NA> #> 5530  2056E    3M  CC37 2019 2019-12-02         DO  1.3532545070  <NA> #> 5531  2056E    3M  CC37 2019 2019-12-02      DOSAT  3.9740583963  <NA> #> 5532  2056E    3M  CC37 2019 2019-12-02       NO23 -5.2983173665     I #> 5533  2056E    3M  CC37 2019 2019-12-02      SALIN  3.1363634033  <NA> #> 5534  2056E    3M  CC37 2019 2019-12-02        TKN -0.4942963218  <NA> #> 5535  2056E    3M  CC37 2019 2019-12-02         TN -0.4877603508     + #> 5536  2056E    3M  CC37 2019 2019-12-02         TP -1.8325814637  <NA> #> 5537  2056E    3M  CC37 2019 2019-12-02       TURB  0.7884573604  <NA> #> 5538  2056E    3M  CC37 2020 2020-01-06      CHLAC  2.7080502011  <NA> #> 5539  2056E    3M  CC37 2020 2020-01-06      COLOR  3.1354942159     A #> 5540  2056E    3M  CC37 2020 2020-01-06         DO  2.0055258587  <NA> #> 5541  2056E    3M  CC37 2020 2020-01-06      DOSAT  4.5347477217  <NA> #> 5542  2056E    3M  CC37 2020 2020-01-06       NO23 -4.7105307016     I #> 5543  2056E    3M  CC37 2020 2020-01-06      SALIN  3.0387917630  <NA> #> 5544  2056E    3M  CC37 2020 2020-01-06        TKN -0.3710636814  <NA> #> 5545  2056E    3M  CC37 2020 2020-01-06         TN -0.3652833185     + #> 5546  2056E    3M  CC37 2020 2020-01-06         TP -1.6607312068  <NA> #> 5547  2056E    3M  CC37 2020 2020-01-06       TURB  1.0647107370  <NA> #> 5548  2056E    3M  CC37 2020 2020-02-03      CHLAC  2.5649493575  <NA> #> 5549  2056E    3M  CC37 2020 2020-02-03      COLOR  2.9957322736  <NA> #> 5550  2056E    3M  CC37 2020 2020-02-03         DO  1.8148247422  <NA> #> 5551  2056E    3M  CC37 2020 2020-02-03      DOSAT  4.2808241292  <NA> #> 5552  2056E    3M  CC37 2020 2020-02-03       NO23 -4.3428059215  <NA> #> 5553  2056E    3M  CC37 2020 2020-02-03      SALIN  3.1175073305  <NA> #> 5554  2056E    3M  CC37 2020 2020-02-03        TKN -0.3856624808  <NA> #> 5555  2056E    3M  CC37 2020 2020-02-03         TN -0.3667252798     + #> 5556  2056E    3M  CC37 2020 2020-02-03         TP -1.9661128564  <NA> #> 5557  2056E    3M  CC37 2020 2020-02-03       TURB  1.4109869737     A #> 5558  2056E    3M  CC37 2020 2020-03-02      CHLAC  1.9740810260  <NA> #> 5559  2056E    3M  CC37 2020 2020-03-02      COLOR  2.8903717579  <NA> #> 5560  2056E    3M  CC37 2020 2020-03-02         DO  1.8484548129  <NA> #> 5561  2056E    3M  CC37 2020 2020-03-02      DOSAT  4.3832758541  <NA> #> 5562  2056E    3M  CC37 2020 2020-03-02       NO23 -5.2983173665     I #> 5563  2056E    3M  CC37 2020 2020-03-02      SALIN  3.1320098918  <NA> #> 5564  2056E    3M  CC37 2020 2020-03-02        TKN -0.4004775666  <NA> #> 5565  2056E    3M  CC37 2020 2020-03-02         TN -0.3945251681     + #> 5566  2056E    3M  CC37 2020 2020-03-02         TP -1.9661128564  <NA> #> 5567  2056E    3M  CC37 2020 2020-03-02       TURB  1.2809338455     A #> 5568  2056E    3M  CC37 2020 2020-09-08      CHLAC  1.6486586256  <NA> #> 5569  2056E    3M  CC37 2020 2020-09-08      COLOR  4.4998096703  <NA> #> 5570  2056E    3M  CC37 2020 2020-09-08         DO  0.8837675402  <NA> #> 5571  2056E    3M  CC37 2020 2020-09-08      DOSAT  3.5085559000  <NA> #> 5572  2056E    3M  CC37 2020 2020-09-08       NO23 -3.1465551633  <NA> #> 5573  2056E    3M  CC37 2020 2020-09-08      SALIN  2.2428350886  <NA> #> 5574  2056E    3M  CC37 2020 2020-09-08        TKN -0.1743533871  <NA> #> 5575  2056E    3M  CC37 2020 2020-09-08         TN -0.1244300784     + #> 5576  2056E    3M  CC37 2020 2020-09-08         TP -0.9162907319  <NA> #> 5577  2056E    3M  CC37 2020 2020-09-08       TURB  0.4700036292  <NA> #> 5578  2056E    3M  CC37 2020 2020-10-05      CHLAC  1.7047480922  <NA> #> 5579  2056E    3M  CC37 2020 2020-10-05      COLOR  4.5951198501     A #> 5580  2056E    3M  CC37 2020 2020-10-05         DO  0.8837675402  <NA> #> 5581  2056E    3M  CC37 2020 2020-10-05      DOSAT  3.4657359028  <NA> #> 5582  2056E    3M  CC37 2020 2020-10-05       NO23 -3.2701691193  <NA> #> 5583  2056E    3M  CC37 2020 2020-10-05      SALIN  2.6181254936  <NA> #> 5584  2056E    3M  CC37 2020 2020-10-05        TKN  0.1823215568  <NA> #> 5585  2056E    3M  CC37 2020 2020-10-05         TN  0.2134971743     + #> 5586  2056E    3M  CC37 2020 2020-10-05         TP -0.7765287895  <NA> #> 5587  2056E    3M  CC37 2020 2020-10-05       TURB  0.3364722366  <NA> #> 5588  2056E    3M  CC37 2020 2020-11-02      CHLAC  2.1400661635  <NA> #> 5589  2056E    3M  CC37 2020 2020-11-02      COLOR  4.2046926194  <NA> #> 5590  2056E    3M  CC37 2020 2020-11-02         DO  1.8468787684  <NA> #> 5591  2056E    3M  CC37 2020 2020-11-02      DOSAT  4.4670568839  <NA> #> 5592  2056E    3M  CC37 2020 2020-11-02       NO23 -3.2968373663  <NA> #> 5593  2056E    3M  CC37 2020 2020-11-02      SALIN  2.6525374912  <NA> #> 5594  2056E    3M  CC37 2020 2020-11-02        TKN -0.3147107448  <NA> #> 5595  2056E    3M  CC37 2020 2020-11-02         TN -0.2652684776     + #> 5596  2056E    3M  CC37 2020 2020-11-02         TP -1.3093333200  <NA> #> 5597  2056E    3M  CC37 2020 2020-11-02       TURB  0.6931471806     A #> 5598  2056E    3M  CC37 2020 2020-12-07      CHLAC  1.6677068206  <NA> #> 5599  2056E    3M  CC37 2020 2020-12-07      COLOR  3.8712010109  <NA> #> 5600  2056E    3M  CC37 2020 2020-12-07         DO  1.9050881545  <NA> #> 5601  2056E    3M  CC37 2020 2020-12-07      DOSAT  4.4164280614  <NA> #> 5602  2056E    3M  CC37 2020 2020-12-07       NO23 -3.9633162998  <NA> #> 5603  2056E    3M  CC37 2020 2020-12-07      SALIN  2.8735646396  <NA> #> 5604  2056E    3M  CC37 2020 2020-12-07        TKN -0.4942963218  <NA> #> 5605  2056E    3M  CC37 2020 2020-12-07         TN -0.4636240223     + #> 5606  2056E    3M  CC37 2020 2020-12-07         TP -1.8325814637  <NA> #> 5607  2056E    3M  CC37 2020 2020-12-07       TURB  0.1823215568  <NA> #> 5608  2056E    3M  CC37 2021 2021-01-04      CHLAC  0.8754687374     I #> 5609  2056E    3M  CC37 2021 2021-01-04      COLOR  3.5835189385  <NA> #> 5610  2056E    3M  CC37 2021 2021-01-04         DO  1.4279160358  <NA> #> 5611  2056E    3M  CC37 2021 2021-01-04      DOSAT  3.9569963711  <NA> #> 5612  2056E    3M  CC37 2021 2021-01-04       NO23 -4.1351665567  <NA> #> 5613  2056E    3M  CC37 2021 2021-01-04      SALIN  2.8249439526  <NA> #> 5614  2056E    3M  CC37 2021 2021-01-04        TKN -0.3285040670  <NA> #> 5615  2056E    3M  CC37 2021 2021-01-04         TN -0.3065251603     + #> 5616  2056E    3M  CC37 2021 2021-01-04         TP -1.8971199849  <NA> #> 5617  2056E    3M  CC37 2021 2021-01-04       TURB  0.6418538862  <NA> #> 5618  2056E    3M  CC37 2021 2021-02-01      CHLAC  1.0986122887  <NA> #> 5619  2056E    3M  CC37 2021 2021-02-01      COLOR  3.2958368660     A #> 5620  2056E    3M  CC37 2021 2021-02-01         DO  2.0464016876  <NA> #> 5621  2056E    3M  CC37 2021 2021-02-01      DOSAT  4.5767707115  <NA> #> 5622  2056E    3M  CC37 2021 2021-02-01       NO23 -5.1159958098     I #> 5623  2056E    3M  CC37 2021 2021-02-01      SALIN  2.9957322736  <NA> #> 5624  2056E    3M  CC37 2021 2021-02-01        TKN -0.5108256238  <NA> #> 5625  2056E    3M  CC37 2021 2021-02-01         TN -0.5041810810     + #> 5626  2056E    3M  CC37 2021 2021-02-01         TP -2.1202635362  <NA> #> 5627  2056E    3M  CC37 2021 2021-02-01       TURB  0.6418538862  <NA> #> 5628  2056E    3M  CC37 2021 2021-03-01      CHLAC  1.5260563035  <NA> #> 5629  2056E    3M  CC37 2021 2021-03-01      COLOR  3.2580965380     A #> 5630  2056E    3M  CC37 2021 2021-03-01         DO  1.4134230285  <NA> #> 5631  2056E    3M  CC37 2021 2021-03-01      DOSAT  4.0412953411  <NA> #> 5632  2056E    3M  CC37 2021 2021-03-01       NO23 -5.1159958098     I #> 5633  2056E    3M  CC37 2021 2021-03-01      SALIN  3.0445224377  <NA> #> 5634  2056E    3M  CC37 2021 2021-03-01        TKN -0.6161861394  <NA> #> 5635  2056E    3M  CC37 2021 2021-03-01         TN -0.6088060321     + #> 5636  2056E    3M  CC37 2021 2021-03-01         TP -1.9661128564  <NA> #> 5637  2056E    3M  CC37 2021 2021-03-01       TURB  1.1314021115     A #> 5638  2056E    3M  CC37 2021 2021-04-05      CHLAC  1.7917594692  <NA> #> 5639  2056E    3M  CC37 2021 2021-04-05      COLOR  3.1354942159  <NA> #> 5640  2056E    3M  CC37 2021 2021-04-05         DO  1.5040773968  <NA> #> 5641  2056E    3M  CC37 2021 2021-04-05      DOSAT  4.0604430105  <NA> #> 5642  2056E    3M  CC37 2021 2021-04-05       NO23 -4.5098600062  <NA> #> 5643  2056E    3M  CC37 2021 2021-04-05      SALIN  3.1599747169  <NA> #> 5644  2056E    3M  CC37 2021 2021-04-05        TKN -0.1984509387  <NA> #> 5645  2056E    3M  CC37 2021 2021-04-05         TN -0.1851254841     + #> 5646  2056E    3M  CC37 2021 2021-04-05         TP -1.7719568419  <NA> #> 5647  2056E    3M  CC37 2021 2021-04-05       TURB  1.7047480922  <NA> #> 5648  2056E    3M  CC37 2021 2021-05-03      CHLAC  2.0149030205  <NA> #> 5649  2056E    3M  CC37 2021 2021-05-03      COLOR  3.1354942159  <NA> #> 5650  2056E    3M  CC37 2021 2021-05-03         DO  1.1314021115  <NA> #> 5651  2056E    3M  CC37 2021 2021-05-03      DOSAT  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3M  CC37 2021 2021-10-04       NO23 -3.0576076773  <NA> #> 5693  2056E    3M  CC37 2021 2021-10-04      SALIN  2.4932054526  <NA> #> 5694  2056E    3M  CC37 2021 2021-10-04        TKN  0.0953101798  <NA> #> 5695  2056E    3M  CC37 2021 2021-10-04         TN  0.1371498381     + #> 5696  2056E    3M  CC37 2021 2021-10-04         TP -0.7985076962  <NA> #> 5697  2056E    3M  CC37 2021 2021-10-04       TURB  0.4054651081  <NA> #> 5698  2056E    3M  CC37 2021 2021-11-01      CHLAC  1.7749523509  <NA> #> 5699  2056E    3M  CC37 2021 2021-11-01      COLOR  3.7612001157     A #> 5700  2056E    3M  CC37 2021 2021-11-01         DO  1.2325602612  <NA> #> 5701  2056E    3M  CC37 2021 2021-11-01      DOSAT  3.8177123260  <NA> #> 5702  2056E    3M  CC37 2021 2021-11-01       NO23 -3.5065578973  <NA> #> 5703  2056E    3M  CC37 2021 2021-11-01      SALIN  2.9444389792  <NA> #> 5704  2056E    3M  CC37 2021 2021-11-01        TKN -0.2231435513  <NA> #> 5705  2056E    3M  CC37 2021 2021-11-01         TN 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3M  CC37 2022 2022-12-05      DOSAT  3.9337844972  <NA> #> 5828  2056E    3M  CC37 2022 2022-12-05       NO23 -2.8824035882  <NA> #> 5829  2056E    3M  CC37 2022 2022-12-05      SALIN  2.8219739474  <NA> #> 5830  2056E    3M  CC37 2022 2022-12-05        TKN -0.3147107448  <NA> #> 5831  2056E    3M  CC37 2022 2022-12-05         TN -0.2407984866     + #> 5832  2056E    3M  CC37 2022 2022-12-05         TP -1.4696759701  <NA> #> 5833  2056E    3M  CC37 2022 2022-12-05       TURB  0.5306282511  <NA> #> 5834  2056E    3M  CC37 2023 2023-01-03      CHLAC  2.8903717579  <NA> #> 5835  2056E    3M  CC37 2023 2023-01-03      COLOR  3.4011973817     A #> 5836  2056E    3M  CC37 2023 2023-01-03         DO  1.5953389881  <NA> #> 5837  2056E    3M  CC37 2023 2023-01-03      DOSAT  4.1510399059  <NA> #> 5838  2056E    3M  CC37 2023 2023-01-03       NO23 -3.8167128256  <NA> #> 5839  2056E    3M  CC37 2023 2023-01-03      SALIN  2.9699015135  <NA> #> 5840  2056E    3M  CC37 2023 2023-01-03        TKN -0.1984509387  <NA> #> 5841  2056E    3M  CC37 2023 2023-01-03         TN -0.1719752647     + #> 5842  2056E    3M  CC37 2023 2023-01-03         TP -1.6094379124  <NA> #> 5843  2056E    3M  CC37 2023 2023-01-03       TURB  1.4109869737  <NA> #> 5844  2056E    3M  CC37 2023 2023-02-06      CHLAC  1.8082887712  <NA> #> 5845  2056E    3M  CC37 2023 2023-02-06      COLOR  3.1780538303  <NA> #> 5846  2056E    3M  CC37 2023 2023-02-06         DO  1.5953389881  <NA> #> 5847  2056E    3M  CC37 2023 2023-02-06      DOSAT  4.1510399059  <NA> #> 5848  2056E    3M  CC37 2023 2023-02-06       NO23 -5.5214609179     U #> 5849  2056E    3M  CC37 2023 2023-02-06      SALIN  2.9699015135  <NA> #> 5850  2056E    3M  CC37 2023 2023-02-06        TKN -0.3011050928  <NA> #> 5851  2056E    3M  CC37 2023 2023-02-06         TN -0.2984060358     + #> 5852  2056E    3M  CC37 2023 2023-02-06         TP -1.7147984281  <NA> #> 5853  2056E    3M  CC37 2023 2023-02-06       TURB  0.6418538862  <NA> #> 5854  2056E    3M  CC37 2023 2023-03-06         DO  1.1085626195  <NA> #> 5855  2056E    3M  CC37 2023 2023-03-06      DOSAT  3.7727609381  <NA> #> 5856  2056E    3M  CC37 2023 2023-03-06      SALIN  3.0905878046  <NA> #> 5857  2056E    3M  CC42 2019 2019-10-10      CHLAC  1.5892352051  <NA> #> 5858  2056E    3M  CC42 2019 2019-10-10       COND  9.8078573215  <NA> #> 5859  2056E    3M  CC42 2019 2019-10-10       NO23 -3.7722610631  <NA> #> 5860  2056E    3M  CC42 2019 2019-10-10      SALIN  2.3721111556  <NA> #> 5861  2056E    3M  CC42 2019 2019-10-10        TKN -0.3566749439  <NA> #> 5862  2056E    3M  CC42 2019 2019-10-10         TN -0.3243460568     + #> 5863  2056E    3M  CC42 2019 2019-10-10         TP -1.0498221245  <NA> #> 5864  2056E    3M  CC42 2019 2019-10-10        TSS  1.7917594692     I #> 5865  2056E    3M  CC42 2019 2019-10-10       TURB  1.0647107370  <NA> #> 5866 2056C2    3M  CC45 2014 2014-06-10       COND  9.8892364868  <NA> #> 5867 2056C2    3M  CC45 2014 2014-06-10         DO  1.9344157696  <NA> #> 5868 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.5920849464     + #> 5869 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.4595888418  <NA> #> 5870 2056C2    3M  CC45 2014 2014-06-10       NO23 -5.5214609179     U #> 5871 2056C2    3M  CC45 2014 2014-06-10        TKN  1.2809338455  <NA> #> 5872 2056C2    3M  CC45 2014 2014-06-10         TN  1.2809338455  <NA> #> 5873 2056C2    3M  CC45 2014 2014-06-10        TSS  2.3513752572  <NA> #> 5874 2056C2    3M  CC45 2014 2014-06-10       COND  9.8874597915  <NA> #> 5875 2056C2    3M  CC45 2014 2014-06-10         DO  2.0014800002  <NA> #> 5876 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.6587109529     + #> 5877 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.4587337755  <NA> #> 5878 2056C2    3M  CC45 2014 2014-06-10       COND  9.9269599087  <NA> #> 5879 2056C2    3M  CC45 2014 2014-06-10         DO  1.9933388426  <NA> #> 5880 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.6510991179     + #> 5881 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5014359517  <NA> #> 5882 2056C2    3M  CC45 2014 2014-06-10       COND  9.9782238987  <NA> #> 5883 2056C2    3M  CC45 2014 2014-06-10         DO  1.8916048042  <NA> #> 5884 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.5475410732     + #> 5885 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5572273114  <NA> #> 5886 2056C2    3M  CC45 2014 2014-06-10       COND 10.0037852739  <NA> #> 5887 2056C2    3M  CC45 2014 2014-06-10         DO  1.8017098001  <NA> #> 5888 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.4578295981     + #> 5889 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5862591440  <NA> #> 5890 2056C2    3M  CC45 2014 2014-06-10       COND 10.0950165901  <NA> #> 5891 2056C2    3M  CC45 2014 2014-06-10         DO  1.5475625087  <NA> #> 5892 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.2061840440     + #> 5893 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.6932749155  <NA> #> 5894 2056C2    3M  CC45 2014 2014-06-10       COND 10.1085078656  <NA> #> 5895 2056C2    3M  CC45 2014 2014-06-10         DO  1.4562867329  <NA> #> 5896 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.1141471895     + #> 5897 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.6932749155  <NA> #> 5898 2056C2    3M  CC45 2014 2014-06-10       COND 10.1103391071  <NA> #> 5899 2056C2    3M  CC45 2014 2014-06-10         DO  1.4182774070  <NA> #> 5900 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0775374439     + #> 5901 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7020321288  <NA> #> 5902 2056C2    3M  CC45 2014 2014-06-10       COND 10.1112331617  <NA> #> 5903 2056C2    3M  CC45 2014 2014-06-10         DO  1.4109869737  <NA> #> 5904 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0690267542     + #> 5905 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7027025948  <NA> #> 5906 2056C2    3M  CC45 2014 2014-06-10       COND 10.1134242764  <NA> #> 5907 2056C2    3M  CC45 2014 2014-06-10         DO  1.3787660947  <NA> #> 5908 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0377742107     + #> 5909 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7053799725  <NA> #> 5910 2056C2    3M  CC45 2014 2014-07-10       COND  9.9863570304  <NA> #> 5911 2056C2    3M  CC45 2014 2014-07-10         DO  2.9204697891  <NA> #> 5912 2056C2    3M  CC45 2014 2014-07-10      DOSAT  5.6028565561     + #> 5913 2056C2    3M  CC45 2014 2014-07-10      SALIN  2.5664866368  <NA> #> 5914 2056C2    3M  CC45 2014 2014-07-10       NO23 -4.1351665567     I #> 5915 2056C2    3M  CC45 2014 2014-07-10        TKN  0.5933268453  <NA> #> 5916 2056C2    3M  CC45 2014 2014-07-10         TN  0.5988365011  <NA> #> 5917 2056C2    3M  CC45 2014 2014-07-10        TSS  2.6602595373  <NA> #> 5918 2056C2    3M  CC45 2014 2014-07-10       COND 10.2631181243  <NA> #> 5919 2056C2    3M  CC45 2014 2014-07-10         DO  2.5136560631  <NA> #> 5920 2056C2    3M  CC45 2014 2014-07-10      DOSAT  5.1935122522     + #> 5921 2056C2    3M  CC45 2014 2014-07-10      SALIN  2.7219531063  <NA> #> 5922 2056C2    3M  CC45 2014 2014-07-10       COND 10.5858012624  <NA> #> 5923 2056C2    3M  CC45 2014 2014-07-10         DO  1.3584091576  <NA> #> 5924 2056C2    3M  CC45 2014 2014-07-10      DOSAT  4.0893320204     + #> 5925 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2284300377  <NA> #> 5926 2056C2    3M  CC45 2014 2014-07-10       COND 10.5893079577  <NA> #> 5927 2056C2    3M  CC45 2014 2014-07-10         DO  1.2383742310  <NA> #> 5928 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.9702919136     + #> 5929 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2327787300  <NA> #> 5930 2056C2    3M  CC45 2014 2014-07-10       COND 10.5894086880  <NA> #> 5931 2056C2    3M  CC45 2014 2014-07-10         DO  1.2178757095  <NA> #> 5932 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.9493187902     + #> 5933 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2335673736  <NA> #> 5934 2056C2    3M  CC45 2014 2014-07-10       COND 10.5868621364  <NA> #> 5935 2056C2    3M  CC45 2014 2014-07-10         DO  0.7654678421  <NA> #> 5936 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.4965075615     + #> 5937 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2331731296  <NA> #> 5938   2053     2  CC50 2018 2018-03-15      CHLAC  0.9932517730  <NA> #> 5939   2053     2  CC50 2018 2018-03-15       COND 10.6964800681  <NA> #> 5940   2053     2  CC50 2018 2018-03-15         DO  2.0918640617  <NA> #> 5941   2053     2  CC50 2018 2018-03-15      DOSAT  4.6249728133  <NA> #> 5942   2053     2  CC50 2018 2018-03-15       NO23 -5.5214609179     U #> 5943   2053     2  CC50 2018 2018-03-15      SALIN  3.5010427166     + #> 5944   2053     2  CC50 2018 2018-03-15        TKN -0.5108256238  <NA> #> 5945   2053     2  CC50 2018 2018-03-15         TN -0.5074978337     + #> 5946   2053     2  CC50 2018 2018-03-15         TP -1.8325814637  <NA> #> 5947   2053     2  CC50 2018 2018-03-15        TSS  1.7917594692     I #> 5948   2053     2  CC50 2018 2018-03-15       TURB  1.1631508098     A #> 5949   2053     2  CC50 2018 2018-03-29      CHLAC  1.9459101491  <NA> #> 5950   2053     2  CC50 2018 2018-03-29       COND 10.6310361598  <NA> #> 5951   2053     2  CC50 2018 2018-03-29         DO  1.8405496334  <NA> #> 5952   2053     2  CC50 2018 2018-03-29      DOSAT  4.4426512565  <NA> #> 5953   2053     2  CC50 2018 2018-03-29       NO23 -5.5214609179     U #> 5954   2053     2  CC50 2018 2018-03-29      SALIN  3.3382575819     + #> 5955   2053     2  CC50 2018 2018-03-29        TKN  0.4054651081  <NA> #> 5956   2053     2  CC50 2018 2018-03-29         TN  0.4067975533     + #> 5957   2053     2  CC50 2018 2018-03-29         TP -1.8325814637  <NA> #> 5958   2053     2  CC50 2018 2018-03-29        TSS  2.6390573296  <NA> #> 5959   2053     2  CC50 2018 2018-03-29       TURB  1.7047480922  <NA> #> 5960   2053     2  CC50 2018 2018-04-23      CHLAC  2.0794415417  <NA> #> 5961   2053     2  CC50 2018 2018-04-23       COND 10.6468524493  <NA> #> 5962   2053     2  CC50 2018 2018-04-23         DO  1.9459101491  <NA> #> 5963   2053     2  CC50 2018 2018-04-23      DOSAT  4.6249728133  <NA> #> 5964   2053     2  CC50 2018 2018-04-23       NO23 -5.5214609179     U #> 5965   2053     2  CC50 2018 2018-04-23      SALIN  3.2649957605     + #> 5966   2053     2  CC50 2018 2018-04-23        TKN -0.3710636814  <NA> #> 5967   2053     2  CC50 2018 2018-04-23         TN -0.3681693234     + #> 5968   2053     2  CC50 2018 2018-04-23         TP -1.5141277326  <NA> #> 5969   2053     2  CC50 2018 2018-04-23        TSS  3.3322045102     A #> 5970   2053     2  CC50 2018 2018-04-23       TURB  1.8718021769  <NA> #> 5971   2053     2  CC50 2018 2018-05-10      CHLAC  1.7917594692  <NA> #> 5972   2053     2  CC50 2018 2018-05-10       COND 10.6712318713  <NA> #> 5973   2053     2  CC50 2018 2018-05-10         DO  1.5040773968  <NA> #> 5974   2053     2  CC50 2018 2018-05-10      DOSAT  4.1588830834  <NA> #> 5975   2053     2  CC50 2018 2018-05-10       NO23 -5.2983173665     I #> 5976   2053     2  CC50 2018 2018-05-10      SALIN  3.3214324132  <NA> #> 5977   2053     2  CC50 2018 2018-05-10        TKN -0.1165338163  <NA> #> 5978   2053     2  CC50 2018 2018-05-10         TN -0.1120495038     + #> 5979   2053     2  CC50 2018 2018-05-10         TP -1.3862943611  <NA> #> 5980   2053     2  CC50 2018 2018-05-10        TSS  2.7080502011  <NA> #> 5981   2053     2  CC50 2018 2018-05-10       TURB  1.9021075264  <NA> #> 5982   2053     2  CC50 2018 2018-06-11      CHLAC  2.6390573296  <NA> #> 5983   2053     2  CC50 2018 2018-06-11       COND  9.5468126086  <NA> #> 5984   2053     2  CC50 2018 2018-06-11         DO  1.6094379124  <NA> #> 5985   2053     2  CC50 2018 2018-06-11      DOSAT  4.2341065046  <NA> #> 5986   2053     2  CC50 2018 2018-06-11       NO23 -2.7806208939  <NA> #> 5987   2053     2  CC50 2018 2018-06-11      SALIN  2.0918640617  <NA> #> 5988   2053     2  CC50 2018 2018-06-11        TKN  0.1823215568  <NA> #> 5989   2053     2  CC50 2018 2018-06-11         TN  0.2326977641     + #> 5990   2053     2  CC50 2018 2018-06-11         TP -0.7133498879  <NA> #> 5991   2053     2  CC50 2018 2018-06-11        TSS  1.3862943611     I #> 5992   2053     2  CC50 2018 2018-06-11       TURB  0.7419373447  <NA> #> 5993   2053     2  CC50 2018 2018-06-25      CHLAC  3.4011973817  <NA> #> 5994   2053     2  CC50 2018 2018-06-25       COND 10.0243768698  <NA> #> 5995   2053     2  CC50 2018 2018-06-25         DO  1.7209792872  <NA> #> 5996   2053     2  CC50 2018 2018-06-25      DOSAT  4.3719762988  <NA> #> 5997   2053     2  CC50 2018 2018-06-25       NO23 -2.9374633654  <NA> #> 5998   2053     2  CC50 2018 2018-06-25      SALIN  2.5055259370     + #> 5999   2053     2  CC50 2018 2018-06-25        TKN  0.0953101798  <NA> #> 6000   2053     2  CC50 2018 2018-06-25         TN  0.1423672413     + #> 6001   2053     2  CC50 2018 2018-06-25         TP -0.9162907319  <NA> #> 6002   2053     2  CC50 2018 2018-06-25        TSS  1.3862943611     I #> 6003   2053     2  CC50 2018 2018-06-25       TURB  0.9932517730  <NA> #> 6004   2053     2  CC50 2018 2018-08-07      CHLAC  2.8332133441  <NA> #> 6005   2053     2  CC50 2018 2018-08-07       COND  7.3382381501  <NA> #> 6006   2053     2  CC50 2018 2018-08-07         DO  1.7698546338  <NA> #> 6007   2053     2  CC50 2018 2018-08-07      DOSAT  4.3438054219  <NA> #> 6008   2053     2  CC50 2018 2018-08-07       NO23 -3.1235656451  <NA> #> 6009   2053     2  CC50 2018 2018-08-07      SALIN -0.2613647641  <NA> #> 6010   2053     2  CC50 2018 2018-08-07        TKN  0.0953101798  <NA> #> 6011   2053     2  CC50 2018 2018-08-07         TN  0.1345308930     + #> 6012   2053     2  CC50 2018 2018-08-07         TP -1.2378743560  <NA> #> 6013   2053     2  CC50 2018 2018-08-07        TSS  1.3862943611     I #> 6014   2053     2  CC50 2018 2018-08-07       TURB  0.9162907319     A #> 6015   2053     2  CC50 2018 2018-09-06      CHLAC  2.0014800002  <NA> #> 6016   2053     2  CC50 2018 2018-09-06       COND  8.6513743729  <NA> #> 6017   2053     2  CC50 2018 2018-09-06         DO  1.8341801851  <NA> #> 6018   2053     2  CC50 2018 2018-09-06      DOSAT  4.4236483094  <NA> #> 6019   2053     2  CC50 2018 2018-09-06       NO23 -2.5383074265  <NA> #> 6020   2053     2  CC50 2018 2018-09-06      SALIN  1.1281710909  <NA> #> 6021   2053     2  CC50 2018 2018-09-06        TKN  0.1823215568  <NA> #> 6022   2053     2  CC50 2018 2018-09-06         TN  0.2460785226     + #> 6023   2053     2  CC50 2018 2018-09-06         TP -1.2378743560  <NA> #> 6024   2053     2  CC50 2018 2018-09-06        TSS  1.3862943611     I #> 6025   2053     2  CC50 2018 2018-09-06       TURB  0.6931471806  <NA> #> 6026   2053     2  CC50 2018 2018-09-20      CHLAC  2.5649493575  <NA> #> 6027   2053     2  CC50 2018 2018-09-20       COND  9.3369730229  <NA> #> 6028   2053     2  CC50 2018 2018-09-20         DO  1.6582280766  <NA> #> 6029   2053     2  CC50 2018 2018-09-20      DOSAT  4.1682144108  <NA> #> 6030   2053     2  CC50 2018 2018-09-20       NO23 -4.1351665567  <NA> #> 6031   2053     2  CC50 2018 2018-09-20      SALIN  1.8562979904  <NA> #> 6032   2053     2  CC50 2018 2018-09-20        TKN -0.0725706928  <NA> #> 6033   2053     2  CC50 2018 2018-09-20         TN -0.0555127099     + #> 6034   2053     2  CC50 2018 2018-09-20         TP -1.1394342832  <NA> #> 6035   2053     2  CC50 2018 2018-09-20        TSS  1.3862943611     I #> 6036   2053     2  CC50 2018 2018-09-20       TURB  0.4700036292  <NA> #> 6037   2053     2  CC50 2018 2018-10-24      CHLAC  1.9600947840  <NA> #> 6038   2053     2  CC50 2018 2018-10-24       COND 10.0400269167  <NA> #> 6039   2053     2  CC50 2018 2018-10-24         DO  1.9430489168  <NA> #> 6040   2053     2  CC50 2018 2018-10-24      DOSAT  4.5496574761  <NA> #> 6041   2053     2  CC50 2018 2018-10-24       NO23 -2.7488721956  <NA> #> 6042   2053     2  CC50 2018 2018-10-24      SALIN  2.6246685922  <NA> #> 6043   2053     2  CC50 2018 2018-10-24        TKN -0.3011050928  <NA> #> 6044   2053     2  CC50 2018 2018-10-24         TN -0.2181560098     + #> 6045   2053     2  CC50 2018 2018-10-24         TP -1.4271163556  <NA> #> 6046   2053     2  CC50 2018 2018-10-24        TSS  1.6094379124     I #> 6047   2053     2  CC50 2018 2018-10-24       TURB  0.9162907319  <NA> #> 6048   2053     2  CC50 2019 2019-04-17      CHLAC  1.5892352051     I #> 6049   2053     2  CC50 2019 2019-04-17       COND 10.3074515345  <NA> #> 6050   2053     2  CC50 2019 2019-04-17         DO  1.9878743482  <NA> #> 6051   2053     2  CC50 2019 2019-04-17      DOSAT  4.5981455711  <NA> #> 6052   2053     2  CC50 2019 2019-04-17       NO23 -5.5214609179     U #> 6053   2053     2  CC50 2019 2019-04-17      SALIN  2.9193910403  <NA> #> 6054   2053     2  CC50 2019 2019-04-17        TKN -0.4462871026  <NA> #> 6055   2053     2  CC50 2019 2019-04-17         TN -0.4431669753     + #> 6056   2053     2  CC50 2019 2019-04-17         TP -1.6607312068  <NA> #> 6057   2053     2  CC50 2019 2019-04-17        TSS  2.9444389792     A #> 6058   2053     2  CC50 2019 2019-04-17       TURB  1.0296194172  <NA> #> 6059   2053     2  CC50 2019 2019-07-15      CHLAC  3.0910424534  <NA> #> 6060   2053     2  CC50 2019 2019-07-15       COND 10.0506999322  <NA> #> 6061   2053     2  CC50 2019 2019-07-15         DO  1.9430489168  <NA> #> 6062   2053     2  CC50 2019 2019-07-15      DOSAT  4.5971380143  <NA> #> 6063   2053     2  CC50 2019 2019-07-15       NO23 -5.5214609179     U #> 6064   2053     2  CC50 2019 2019-07-15      SALIN  2.6333266549  <NA> #> 6065   2053     2  CC50 2019 2019-07-15        TKN -0.2107210313  <NA> #> 6066   2053     2  CC50 2019 2019-07-15         TN -0.2082549388     + #> 6067   2053     2  CC50 2019 2019-07-15         TP -1.4696759701  <NA> #> 6068   2053     2  CC50 2019 2019-07-15        TSS  2.0794415417     I #> 6069   2053     2  CC50 2019 2019-07-15       TURB  0.9932517730  <NA> #> 6070   2053     2  CC50 2019 2019-08-19      CHLAC  1.4816045409  <NA> #> 6071   2053     2  CC50 2019 2019-08-19       COND  7.3530819205  <NA> #> 6072   2053     2  CC50 2019 2019-08-19         DO  1.5665304114  <NA> #> 6073   2053     2  CC50 2019 2019-08-19      DOSAT  4.1367652781  <NA> #> 6074   2053     2  CC50 2019 2019-08-19       NO23 -2.6036901858  <NA> #> 6075   2053     2  CC50 2019 2019-08-19      SALIN -0.2484613593  <NA> #> 6076   2053     2  CC50 2019 2019-08-19        TKN  0.3364722366  <NA> #> 6077   2053     2  CC50 2019 2019-08-19         TN  0.3879797938     + #> 6078   2053     2  CC50 2019 2019-08-19         TP -0.8209805521  <NA> #> 6079   2053     2  CC50 2019 2019-08-19        TSS  1.0986122887     I #> 6080   2053     2  CC50 2019 2019-08-19       TURB  0.7884573604  <NA> #> 6081   2053     2  CC50 2019 2019-09-11      CHLAC  3.0910424534  <NA> #> 6082   2053     2  CC50 2019 2019-09-11       COND  9.8378817954  <NA> #> 6083   2053     2  CC50 2019 2019-09-11         DO  1.9139771020  <NA> #> 6084   2053     2  CC50 2019 2019-09-11      DOSAT  4.5475410732  <NA> #> 6085   2053     2  CC50 2019 2019-09-11       NO23 -4.0173835211  <NA> #> 6086   2053     2  CC50 2019 2019-09-11      SALIN  2.4015250408  <NA> #> 6087   2053     2  CC50 2019 2019-09-11        TKN -0.0725706928  <NA> #> 6088   2053     2  CC50 2019 2019-09-11         TN -0.0534007767     + #> 6089   2053     2  CC50 2019 2019-09-11         TP -1.2039728043  <NA> #> 6090   2053     2  CC50 2019 2019-09-11        TSS  1.6094379124     I #> 6091   2053     2  CC50 2019 2019-09-11       TURB  0.7884573604  <NA> #> 6092   2053     2  CC50 2019 2019-10-09      CHLAC  1.1939224685  <NA> #> 6093   2053     2  CC50 2019 2019-10-09       COND 10.2652793829  <NA> #> 6094   2053     2  CC50 2019 2019-10-09         DO  1.7065646232  <NA> #> 6095   2053     2  CC50 2019 2019-10-09      DOSAT  4.3554259529  <NA> #> 6096   2053     2  CC50 2019 2019-10-09       NO23 -5.5214609179     I #> 6097   2053     2  CC50 2019 2019-10-09      SALIN  2.8713021952  <NA> #> 6098   2053     2  CC50 2019 2019-10-09        TKN -0.4155154440  <NA> #> 6099   2053     2  CC50 2019 2019-10-09         TN -0.4094731295     + #> 6100   2053     2  CC50 2019 2019-10-09         TP -1.5141277326  <NA> #> 6101   2053     2  CC50 2019 2019-10-09        TSS  1.0986122887     U #> 6102   2053     2  CC50 2019 2019-10-09       TURB -0.1625189295  <NA> #> 6103   2053     2  CC50 2020 2020-02-13      CHLAC  1.5475625087  <NA> #> 6104   2053     2  CC50 2020 2020-02-13       COND 10.4652439050  <NA> #> 6105   2053     2  CC50 2020 2020-02-13         DO  1.8017098001  <NA> #> 6106   2053     2  CC50 2020 2020-02-13      DOSAT  4.4067192473  <NA> #> 6107   2053     2  CC50 2020 2020-02-13       NO23 -5.5214609179     U #> 6108   2053     2  CC50 2020 2020-02-13      SALIN  3.0946722214  <NA> #> 6109   2053     2  CC50 2020 2020-02-13        TKN -0.4620354596  <NA> #> 6110   2053     2  CC50 2020 2020-02-13         TN -0.4588658848     + #> 6111   2053     2  CC50 2020 2020-02-13         TP -1.8325814637  <NA> #> 6112   2053     2  CC50 2020 2020-02-13        TSS  2.7080502011  <NA> #> 6113   2053     2  CC50 2020 2020-02-13       TURB  2.0014800002     A #> 6114   2053     2  CC50 2020 2020-03-24      CHLAC  1.3350010667  <NA> #> 6115   2053     2  CC50 2020 2020-03-24       COND 10.5688523521  <NA> #> 6116   2053     2  CC50 2020 2020-03-24         DO  1.9401794743  <NA> #> 6117   2053     2  CC50 2020 2020-03-24      DOSAT  4.6434288981  <NA> #> 6118   2053     2  CC50 2020 2020-03-24       NO23 -5.5214609179     U #> 6119   2053     2  CC50 2020 2020-03-24      SALIN  3.2047769005  <NA> #> 6120   2053     2  CC50 2020 2020-03-24        TKN -0.4462871026  <NA> #> 6121   2053     2  CC50 2020 2020-03-24         TN -0.4431669753     + #> 6122   2053     2  CC50 2020 2020-03-24         TP -1.8325814637  <NA> #> 6123   2053     2  CC50 2020 2020-03-24        TSS  2.7725887222  <NA> #> 6124   2053     2  CC50 2020 2020-03-24       TURB  1.5260563035  <NA> #> 6125   2053     2  CC50 2020 2020-06-22      CHLAC  3.1780538303  <NA> #> 6126   2053     2  CC50 2020 2020-06-22       COND  9.9972510823  <NA> #> 6127   2053     2  CC50 2020 2020-06-22         DO  1.7173950539  <NA> #> 6128   2053     2  CC50 2020 2020-06-22      DOSAT  4.3795235045  <NA> #> 6129   2053     2  CC50 2020 2020-06-22       NO23 -4.5098600062  <NA> #> 6130   2053     2  CC50 2020 2020-06-22      SALIN  2.5718485799  <NA> #> 6131   2053     2  CC50 2020 2020-06-22        TKN -0.0100503359  <NA> #> 6132   2053     2  CC50 2020 2020-06-22         TN  0.0009995003     + #> 6133   2053     2  CC50 2020 2020-06-22         TP -1.2039728043  <NA> #> 6134   2053     2  CC50 2020 2020-06-22        TSS  1.7917594692     I #> 6135   2053     2  CC50 2020 2020-06-22       TURB  0.7884573604     A #> 6136   2053     2  CC50 2020 2020-07-27      CHLAC  1.7578579176  <NA> #> 6137   2053     2  CC50 2020 2020-07-27       COND 10.1123293191  <NA> #> 6138   2053     2  CC50 2020 2020-07-27         DO  1.5644405465  <NA> #> 6139   2053     2  CC50 2020 2020-07-27      DOSAT  4.2239097666  <NA> #> 6140   2053     2  CC50 2020 2020-07-27       NO23 -4.1351665567  <NA> #> 6141   2053     2  CC50 2020 2020-07-27      SALIN  2.7006898467  <NA> #> 6142   2053     2  CC50 2020 2020-07-27         TN -0.3481400415     + #> 6143   2053     2  CC50 2020 2020-07-27         TP -1.3093333200  <NA> #> 6144   2053     2  CC50 2020 2020-07-27        TSS  1.0986122887     U #> 6145   2053     2  CC50 2020 2020-07-27       TURB  0.5306282511  <NA> #> 6146   2053     2  CC50 2020 2020-08-26      CHLAC  2.2300144002  <NA> #> 6147   2053     2  CC50 2020 2020-08-26       COND  9.8854254097  <NA> #> 6148   2053     2  CC50 2020 2020-08-26         DO  1.7850704811  <NA> #> 6149   2053     2  CC50 2020 2020-08-26      DOSAT  4.4188406078  <NA> #> 6150   2053     2  CC50 2020 2020-08-26       NO23 -5.5214609179     U #> 6151   2053     2  CC50 2020 2020-08-26      SALIN  2.4535879665  <NA> #> 6152   2053     2  CC50 2020 2020-08-26        TKN -0.1984509387  <NA> #> 6153   2053     2  CC50 2020 2020-08-26         TN -0.1960148839     + #> 6154   2053     2  CC50 2020 2020-08-26         TP -1.3862943611  <NA> #> 6155   2053     2  CC50 2020 2020-08-26        TSS  1.0986122887     U #> 6156   2053     2  CC50 2020 2020-08-26       TURB  0.0953101798  <NA> #> 6157   2053     2  CC50 2021 2021-01-14      CHLAC  1.6094379124     A #> 6158   2053     2  CC50 2021 2021-01-14       COND 10.2228136303  <NA> #> 6159   2053     2  CC50 2021 2021-01-14         DO  2.0967901800  <NA> #> 6160   2053     2  CC50 2021 2021-01-14      DOSAT  4.5580785785  <NA> #> 6161   2053     2  CC50 2021 2021-01-14       NO23 -5.5214609179     I #> 6162   2053     2  CC50 2021 2021-01-14      SALIN  2.8314470792  <NA> #> 6163   2053     2  CC50 2021 2021-01-14        TKN -0.2876820725  <NA> #> 6164   2053     2  CC50 2021 2021-01-14         TN -0.2823629110     + #> 6165   2053     2  CC50 2021 2021-01-14         TP -1.7147984281  <NA> #> 6166   2053     2  CC50 2021 2021-01-14        TSS  2.5649493575     A #> 6167   2053     2  CC50 2021 2021-01-14       TURB  1.4586150227  <NA> #> 6168   2053     2  CC50 2021 2021-02-24       COND 10.2486009183  <NA> #> 6169   2053     2  CC50 2021 2021-02-24         DO  2.0955609236  <NA> #> 6170   2053     2  CC50 2021 2021-02-24      DOSAT  4.6453519756  <NA> #> 6171   2053     2  CC50 2021 2021-02-24       NO23 -5.5214609179     U #> 6172   2053     2  CC50 2021 2021-02-24      SALIN  2.8581928595  <NA> #> 6173   2053     2  CC50 2021 2021-02-24        TKN -0.6733445533  <NA> #> 6174   2053     2  CC50 2021 2021-02-24         TN -0.6694306539     + #> 6175   2053     2  CC50 2021 2021-02-24         TP -1.8971199849  <NA> #> 6176   2053     2  CC50 2021 2021-02-24        TSS  1.0986122887     I #> 6177   2053     2  CC50 2021 2021-03-23      CHLAC  0.9555114450  <NA> #> 6178   2053     2  CC50 2021 2021-03-23       COND 10.5061901968  <NA> #> 6179   2053     2  CC50 2021 2021-03-23         DO  1.9685099810  <NA> #> 6180   2053     2  CC50 2021 2021-03-23      DOSAT  4.5119578043  <NA> #> 6181   2053     2  CC50 2021 2021-03-23       NO23 -5.2983173665     I #> 6182   2053     2  CC50 2021 2021-03-23      SALIN  3.1419947805  <NA> #> 6183   2053     2  CC50 2021 2021-03-23        TKN -0.4620354596  <NA> #> 6184   2053     2  CC50 2021 2021-03-23         TN -0.4557063245     + #> 6185   2053     2  CC50 2021 2021-03-23         TP -1.8971199849  <NA> #> 6186   2053     2  CC50 2021 2021-03-23        TSS  1.0986122887     U #> 6187   2053     2  CC50 2021 2021-03-23       TURB  0.6418538862  <NA> #> 6188   2053     2  CC50 2021 2021-07-28      CHLAC  2.2721258855  <NA> #> 6189   2053     2  CC50 2021 2021-07-28       COND  9.4095190458  <NA> #> 6190   2053     2  CC50 2021 2021-07-28         DO  0.9516578757  <NA> #> 6191   2053     2  CC50 2021 2021-07-28      DOSAT  3.5638829639  <NA> #> 6192   2053     2  CC50 2021 2021-07-28       NO23 -3.1700856607  <NA> #> 6193   2053     2  CC50 2021 2021-07-28      SALIN  1.9373017745  <NA> #> 6194   2053     2  CC50 2021 2021-07-28        TKN  0.1823215568  <NA> #> 6195   2053     2  CC50 2021 2021-07-28         TN  0.2167229835     + #> 6196   2053     2  CC50 2021 2021-07-28         TP -0.7550225843  <NA> #> 6197   2053     2  CC50 2021 2021-07-28        TSS  1.3862943611     I #> 6198   2053     2  CC50 2021 2021-07-28       TURB  1.7404661748  <NA> #> 6199   2053     2  CC50 2021 2021-08-26      CHLAC  1.5260563035  <NA> #> 6200   2053     2  CC50 2021 2021-08-26       COND  9.2069345788  <NA> #> 6201   2053     2  CC50 2021 2021-08-26         DO  1.0296194172  <NA> #> 6202   2053     2  CC50 2021 2021-08-26      DOSAT  3.6270040504  <NA> #> 6203   2053     2  CC50 2021 2021-08-26       NO23 -2.7488721956  <NA> #> 6204   2053     2  CC50 2021 2021-08-26      SALIN  1.7191887764  <NA> #> 6205   2053     2  CC50 2021 2021-08-26        TKN -0.3285040670  <NA> #> 6206   2053     2  CC50 2021 2021-08-26         TN -0.2433462586     + #> 6207   2053     2  CC50 2021 2021-08-26         TP -1.0216512475  <NA> #> 6208   2053     2  CC50 2021 2021-08-26        TSS  1.0986122887     I #> 6209   2053     2  CC50 2021 2021-08-26       TURB  0.9555114450  <NA> #> 6210   2053     2  CC50 2021 2021-09-13      CHLAC  1.7578579176  <NA> #> 6211   2053     2  CC50 2021 2021-09-13       COND  9.5941731800  <NA> #> 6212   2053     2  CC50 2021 2021-09-13         DO  1.4422019931  <NA> #> 6213   2053     2  CC50 2021 2021-09-13      DOSAT  4.0707346966  <NA> #> 6214   2053     2  CC50 2021 2021-09-13       NO23 -2.7806208939  <NA> #> 6215   2053     2  CC50 2021 2021-09-13      SALIN  2.1365305087  <NA> #> 6216   2053     2  CC50 2021 2021-09-13        TKN -0.0618754037  <NA> #> 6217   2053     2  CC50 2021 2021-09-13         TN  0.0019980027     + #> 6218   2053     2  CC50 2021 2021-09-13         TP -1.2039728043  <NA> #> 6219   2053     2  CC50 2021 2021-09-13        TSS  1.0986122887     I #> 6220   2053     2  CC50 2021 2021-09-13       TURB  0.5877866649  <NA> #> 6221   2053     2  CC50 2022 2022-03-16       COND 10.6209126256  <NA> #> 6222   2053     2  CC50 2022 2022-03-16         DO  1.9080599249  <NA> #> 6223   2053     2  CC50 2022 2022-03-16      DOSAT  4.5152454785  <NA> #> 6224   2053     2  CC50 2022 2022-03-16      SALIN  3.2676659890  <NA> #> 6225   2053     2  CC50 2022 2022-05-04       COND 10.6380165709  <NA> #> 6226   2053     2  CC50 2022 2022-05-04         DO  1.8748743759  <NA> #> 6227   2053     2  CC50 2022 2022-05-04      DOSAT  4.5622626850  <NA> #> 6228   2053     2  CC50 2022 2022-05-04      SALIN  3.2839142210  <NA> #> 6229   2053     2  CC50 2022 2022-09-14       COND  8.8230589343  <NA> #> 6230   2053     2  CC50 2022 2022-09-14         DO  1.0367368850  <NA> #> 6231   2053     2  CC50 2022 2022-09-14      DOSAT  3.6296600945  <NA> #> 6232   2053     2  CC50 2022 2022-09-14      SALIN  1.3056264581  <NA> #> 6233   2053     2  CC50 2022 2022-10-31       COND  9.8828255561  <NA> #> 6234   2053     2  CC50 2022 2022-10-31         DO  1.6505798558  <NA> #> 6235   2053     2  CC50 2022 2022-10-31      DOSAT  4.2398868675  <NA> #> 6236   2053     2  CC50 2022 2022-10-31      SALIN  2.4535879665  <NA> #> 6237   2054    3F  CC53 2014 2014-01-06      CHLAC  3.3672958300  <NA> #> 6238   2054    3F  CC53 2014 2014-01-06      COLOR  4.1271343850     A #> 6239   2054    3F  CC53 2014 2014-01-06         DO  1.8245492921  <NA> #> 6240   2054    3F  CC53 2014 2014-01-06      DOSAT  4.2209772132     + #> 6241   2054    3F  CC53 2014 2014-01-06       NO23 -2.5133061243  <NA> #> 6242   2054    3F  CC53 2014 2014-01-06      SALIN  0.3364722366  <NA> #> 6243   2054    3F  CC53 2014 2014-01-06        TKN -0.1625189295  <NA> #> 6244   2054    3F  CC53 2014 2014-01-06         TN -0.0714960017     + #> 6245   2054    3F  CC53 2014 2014-01-06         TP -2.9565115604  <NA> #> 6246   2054    3F  CC53 2014 2014-01-06       TURB  1.1939224685     A #> 6247   2054    3F  CC53 2014 2014-02-03      CHLAC  2.5649493575  <NA> #> 6248   2054    3F  CC53 2014 2014-02-03      COLOR  4.0073331852  <NA> #> 6249   2054    3F  CC53 2014 2014-02-03         DO  2.0014800002  <NA> #> 6250   2054    3F  CC53 2014 2014-02-03      DOSAT  4.3956829611     + #> 6251   2054    3F  CC53 2014 2014-02-03       NO23 -2.1202635362  <NA> #> 6252   2054    3F  CC53 2014 2014-02-03      SALIN -0.3566749439  <NA> #> 6253   2054    3F  CC53 2014 2014-02-03        TKN  0.0953101798  <NA> #> 6254   2054    3F  CC53 2014 2014-02-03         TN  0.1988508587     + #> 6255   2054    3F  CC53 2014 2014-02-03         TP -1.9661128564  <NA> #> 6256   2054    3F  CC53 2014 2014-02-03       TURB  1.3350010667  <NA> #> 6257   2054    3F  CC53 2014 2014-03-03      CHLAC  2.4849066498  <NA> #> 6258   2054    3F  CC53 2014 2014-03-03      COLOR  4.1271343850  <NA> #> 6259   2054    3F  CC53 2014 2014-03-03         DO  1.8082887712  <NA> #> 6260   2054    3F  CC53 2014 2014-03-03      DOSAT  4.2398868675     + #> 6261   2054    3F  CC53 2014 2014-03-03       NO23 -5.5214609179     U #> 6262   2054    3F  CC53 2014 2014-03-03      SALIN  0.8754687374  <NA> #> 6263   2054    3F  CC53 2014 2014-03-03        TKN  0.0953101798  <NA> #> 6264   2054    3F  CC53 2014 2014-03-03         TN  0.0971267107     + #> 6265   2054    3F  CC53 2014 2014-03-03         TP -2.0402208285  <NA> #> 6266   2054    3F  CC53 2014 2014-03-03       TURB  1.7227665977  <NA> #> 6267   2054    3F  CC53 2014 2014-04-07      CHLAC  2.3978952728  <NA> #> 6268   2054    3F  CC53 2014 2014-04-07      COLOR  4.0253516907  <NA> #> 6269   2054    3F  CC53 2014 2014-04-07         DO  1.6292405397  <NA> #> 6270   2054    3F  CC53 2014 2014-04-07      DOSAT  4.0960098415     + #> 6271   2054    3F  CC53 2014 2014-04-07       NO23 -4.3428059215  <NA> #> 6272   2054    3F  CC53 2014 2014-04-07        TKN -0.0943106795  <NA> #> 6273   2054    3F  CC53 2014 2014-04-07         TN -0.0801260445     + #> 6274   2054    3F  CC53 2014 2014-04-07         TP -2.1202635362  <NA> #> 6275   2054    3F  CC53 2014 2014-04-07       TURB  1.1939224685  <NA> #> 6276   2054    3F  CC53 2014 2014-05-05      CHLAC  2.4849066498  <NA> #> 6277   2054    3F  CC53 2014 2014-05-05      COLOR  4.0073331852  <NA> #> 6278   2054    3F  CC53 2014 2014-05-05         DO  1.9459101491  <NA> #> 6279   2054    3F  CC53 2014 2014-05-05      DOSAT  4.4006030202     + #> 6280   2054    3F  CC53 2014 2014-05-05       NO23 -3.5755507688  <NA> #> 6281   2054    3F  CC53 2014 2014-05-05      SALIN  0.4054651081  <NA> #> 6282   2054    3F  CC53 2014 2014-05-05        TKN -0.1053605157  <NA> #> 6283   2054    3F  CC53 2014 2014-05-05         TN -0.0747235462     + #> 6284   2054    3F  CC53 2014 2014-05-05         TP -1.8325814637  <NA> #> 6285   2054    3F  CC53 2014 2014-05-05       TURB  1.0296194172  <NA> #> 6286   2054    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3F  CC53 2016 2016-07-05      DOSAT  3.9100210028     + #> 6503   2054    3F  CC53 2016 2016-07-05       NO23 -2.5770219387  <NA> #> 6504   2054    3F  CC53 2016 2016-07-05      SALIN -1.5606477483  <NA> #> 6505   2054    3F  CC53 2016 2016-07-05        TKN  0.0953101798  <NA> #> 6506   2054    3F  CC53 2016 2016-07-05         TN  0.1621188495     + #> 6507   2054    3F  CC53 2016 2016-07-05         TP -1.7719568419  <NA> #> 6508   2054    3F  CC53 2016 2016-07-05       TURB  0.9932517730  <NA> #> 6509   2054    3F  CC53 2016 2016-08-01      CHLAC  0.6418538862  <NA> #> 6510   2054    3F  CC53 2016 2016-08-01      COLOR  4.7004803658  <NA> #> 6511   2054    3F  CC53 2016 2016-08-01         DO  1.0331844833  <NA> #> 6512   2054    3F  CC53 2016 2016-08-01      DOSAT  3.6189933266     + #> 6513   2054    3F  CC53 2016 2016-08-01       NO23 -3.8632328413  <NA> #> 6514   2054    3F  CC53 2016 2016-08-01      SALIN -2.6592600369  <NA> #> 6515   2054    3F  CC53 2016 2016-08-01        TKN 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3F  CC53 2016 2016-11-07      CHLAC  2.1041341543  <NA> #> 6530   2054    3F  CC53 2016 2016-11-07      COLOR  4.2341065046  <NA> #> 6531   2054    3F  CC53 2016 2016-11-07         DO  2.2544447177  <NA> #> 6532   2054    3F  CC53 2016 2016-11-07      DOSAT  4.7202829931     + #> 6533   2054    3F  CC53 2016 2016-11-07       NO23 -3.2968373663  <NA> #> 6534   2054    3F  CC53 2016 2016-11-07      SALIN -1.1086626245  <NA> #> 6535   2054    3F  CC53 2016 2016-11-07        TKN  0.0000000000  <NA> #> 6536   2054    3F  CC53 2016 2016-11-07         TN  0.0363319292     + #> 6537   2054    3F  CC53 2016 2016-11-07         TP -2.4191189092  <NA> #> 6538   2054    3F  CC53 2016 2016-11-07       TURB  0.9555114450  <NA> #> 6539   2054    3F  CC53 2016 2016-12-05      CHLAC  2.4849066498  <NA> #> 6540   2054    3F  CC53 2016 2016-12-05      COLOR  3.9702919136  <NA> #> 6541   2054    3F  CC53 2016 2016-12-05         DO  1.5518087996  <NA> #> 6542   2054    3F  CC53 2016 2016-12-05      DOSAT  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3F  CC53 2017 2017-01-03         TN -0.3652833185     + #> 6557   2054    3F  CC53 2017 2017-01-03         TP -1.9661128564  <NA> #> 6558   2054    3F  CC53 2017 2017-01-03       TURB  0.9555114450  <NA> #> 6559   2054    3F  CC53 2017 2017-02-06      CHLAC  1.7047480922  <NA> #> 6560   2054    3F  CC53 2017 2017-02-06      COLOR  3.6635616461  <NA> #> 6561   2054    3F  CC53 2017 2017-02-06         DO  1.3609765531  <NA> #> 6562   2054    3F  CC53 2017 2017-02-06      DOSAT  3.7819143201     + #> 6563   2054    3F  CC53 2017 2017-02-06       NO23 -2.6310891600  <NA> #> 6564   2054    3F  CC53 2017 2017-02-06      SALIN  1.2527629685  <NA> #> 6565   2054    3F  CC53 2017 2017-02-06        TKN -0.2876820725  <NA> #> 6566   2054    3F  CC53 2017 2017-02-06         TN -0.1960148839     + #> 6567   2054    3F  CC53 2017 2017-02-06         TP -2.1202635362  <NA> #> 6568   2054    3F  CC53 2017 2017-02-06       TURB  1.1939224685     A #> 6569   2054    3F  CC53 2017 2017-03-06      CHLAC  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3F  CC53 2017 2017-04-03       NO23 -3.4112477175  <NA> #> 6584   2054    3F  CC53 2017 2017-04-03      SALIN  2.1610215287  <NA> #> 6585   2054    3F  CC53 2017 2017-04-03        TKN -0.0725706928  <NA> #> 6586   2054    3F  CC53 2017 2017-04-03         TN -0.0377018672     + #> 6587   2054    3F  CC53 2017 2017-04-03         TP -1.4271163556  <NA> #> 6588   2054    3F  CC53 2017 2017-04-03       TURB  1.0296194172     A #> 6589   2054    3F  CC53 2017 2017-05-01      CHLAC  2.2512917986  <NA> #> 6590   2054    3F  CC53 2017 2017-05-01      COLOR  4.0253516907     A #> 6591   2054    3F  CC53 2017 2017-05-01         DO  1.1817271954  <NA> #> 6592   2054    3F  CC53 2017 2017-05-01      DOSAT  3.7796338174     + #> 6593   2054    3F  CC53 2017 2017-05-01       NO23 -4.7105307016     I #> 6594   2054    3F  CC53 2017 2017-05-01      SALIN  2.6049094422  <NA> #> 6595   2054    3F  CC53 2017 2017-05-01        TKN  0.5306282511  <NA> #> 6596   2054    3F  CC53 2017 2017-05-01         TN  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3F  CC53 2017 2017-07-10        TKN  0.3364722366  <NA> #> 6611   2054    3F  CC53 2017 2017-07-10         TN  0.4317824164     + #> 6612   2054    3F  CC53 2017 2017-07-10         TP -1.4696759701  <NA> #> 6613   2054    3F  CC53 2017 2017-07-10       TURB  1.1939224685  <NA> #> 6614   2054    3F  CC53 2017 2017-11-06      CHLAC  1.8870696490  <NA> #> 6615   2054    3F  CC53 2017 2017-11-06      COLOR  4.9416424226  <NA> #> 6616   2054    3F  CC53 2017 2017-11-06         DO  1.5973653312  <NA> #> 6617   2054    3F  CC53 2017 2017-11-06      DOSAT  4.0621656639  <NA> #> 6618   2054    3F  CC53 2017 2017-11-06       NO23 -1.3470736480  <NA> #> 6619   2054    3F  CC53 2017 2017-11-06      SALIN -1.4696759701  <NA> #> 6620   2054    3F  CC53 2017 2017-11-06        TKN  0.0953101798  <NA> #> 6621   2054    3F  CC53 2017 2017-11-06         TN  0.3074846997     + #> 6622   2054    3F  CC53 2017 2017-11-06         TP -2.0402208285  <NA> #> 6623   2054    3F  CC53 2017 2017-11-06       TURB  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3F  CC53 2018 2018-01-02      DOSAT  4.0758410907     + #> 6638   2054    3F  CC53 2018 2018-01-02       NO23 -2.0402208285  <NA> #> 6639   2054    3F  CC53 2018 2018-01-02      SALIN -0.8915981193  <NA> #> 6640   2054    3F  CC53 2018 2018-01-02        TKN  0.0000000000  <NA> #> 6641   2054    3F  CC53 2018 2018-01-02         TN  0.1222176327     + #> 6642   2054    3F  CC53 2018 2018-01-02         TP -1.9661128564  <NA> #> 6643   2054    3F  CC53 2018 2018-01-02       TURB  1.8245492921  <NA> #> 6644   2054    3F  CC53 2018 2018-02-05      CHLAC  3.5263605246  <NA> #> 6645   2054    3F  CC53 2018 2018-02-05      COLOR  4.2484952420  <NA> #> 6646   2054    3F  CC53 2018 2018-02-05         DO  1.9712993831  <NA> #> 6647   2054    3F  CC53 2018 2018-02-05      DOSAT  4.3681812279  <NA> #> 6648   2054    3F  CC53 2018 2018-02-05       NO23 -0.9416085399  <NA> #> 6649   2054    3F  CC53 2018 2018-02-05      SALIN -0.9416085399  <NA> #> 6650   2054    3F  CC53 2018 2018-02-05        TKN  0.1823215568  <NA> #> 6651   2054    3F  CC53 2018 2018-02-05         TN  0.4637340162     + #> 6652   2054    3F  CC53 2018 2018-02-05         TP -1.7719568419  <NA> #> 6653   2054    3F  CC53 2018 2018-02-05       TURB  1.8870696490  <NA> #> 6654   2054    3F  CC53 2018 2018-05-07      CHLAC  2.6390573296  <NA> #> 6655   2054    3F  CC53 2018 2018-05-07      COLOR  3.9318256327  <NA> #> 6656   2054    3F  CC53 2018 2018-05-07         DO  1.3217558400  <NA> #> 6657   2054    3F  CC53 2018 2018-05-07      DOSAT  3.8877303129  <NA> #> 6658   2054    3F  CC53 2018 2018-05-07       NO23 -5.1159958098     I #> 6659   2054    3F  CC53 2018 2018-05-07      SALIN  1.9974177062  <NA> #> 6660   2054    3F  CC53 2018 2018-05-07        TKN -0.0100503359  <NA> #> 6661   2054    3F  CC53 2018 2018-05-07         TN -0.0060180723     + #> 6662   2054    3F  CC53 2018 2018-05-07         TP -1.3862943611  <NA> #> 6663   2054    3F  CC53 2018 2018-05-07       TURB  1.1939224685  <NA> #> 6664   2054    3F  CC53 2018 2018-07-09      CHLAC  0.9162907319  <NA> #> 6665   2054    3F  CC53 2018 2018-07-09      COLOR  5.0106352941  <NA> #> 6666   2054    3F  CC53 2018 2018-07-09         DO  1.3532545070  <NA> #> 6667   2054    3F  CC53 2018 2018-07-09      DOSAT  3.9435216725  <NA> #> 6668   2054    3F  CC53 2018 2018-07-09       NO23 -4.3428059215  <NA> #> 6669   2054    3F  CC53 2018 2018-07-09      SALIN -3.2188758249  <NA> #> 6670   2054    3F  CC53 2018 2018-07-09        TKN  0.0953101798  <NA> #> 6671   2054    3F  CC53 2018 2018-07-09         TN  0.1070590723     + #> 6672   2054    3F  CC53 2018 2018-07-09         TP -2.5510464523  <NA> #> 6673   2054    3F  CC53 2018 2018-07-09       TURB  0.9555114450  <NA> #> 6674   2054    3F  CC53 2019 2019-02-04      CHLAC  1.2527629685  <NA> #> 6675   2054    3F  CC53 2019 2019-02-04      COLOR  4.2766661190  <NA> #> 6676   2054    3F  CC53 2019 2019-02-04         DO  1.7011051010  <NA> #> 6677   2054    3F  CC53 2019 2019-02-04      DOSAT  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3F  CC53 2019 2019-03-04         TN  0.2239432315     + #> 6692   2054    3F  CC53 2019 2019-03-04         TP -2.2072749132  <NA> #> 6693   2054    3F  CC53 2019 2019-03-04       TURB  2.0918640617  <NA> #> 6694   2054    3F  CC53 2019 2019-04-01      CHLAC  2.0794415417  <NA> #> 6695   2054    3F  CC53 2019 2019-04-01      COLOR  4.1896547420  <NA> #> 6696   2054    3F  CC53 2019 2019-04-01         DO  1.6074359098  <NA> #> 6697   2054    3F  CC53 2019 2019-04-01      DOSAT  4.0775374439  <NA> #> 6698   2054    3F  CC53 2019 2019-04-01       NO23 -4.8283137373     I #> 6699   2054    3F  CC53 2019 2019-04-01      SALIN -0.9675840263  <NA> #> 6700   2054    3F  CC53 2019 2019-04-01        TKN  0.0000000000  <NA> #> 6701   2054    3F  CC53 2019 2019-04-01         TN  0.0039920213     + #> 6702   2054    3F  CC53 2019 2019-04-01         TP -2.3434070875  <NA> #> 6703   2054    3F  CC53 2019 2019-04-01       TURB  1.0986122887  <NA> #> 6704   2054    3F  CC53 2019 2019-05-06      CHLAC  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3F  CC53 2019 2019-08-05       NO23 -2.3859667019  <NA> #> 6719   2054    3F  CC53 2019 2019-08-05      SALIN -1.7719568419  <NA> #> 6720   2054    3F  CC53 2019 2019-08-05        TKN  0.4700036292  <NA> #> 6721   2054    3F  CC53 2019 2019-08-05         TN  0.5259112612     + #> 6722   2054    3F  CC53 2019 2019-08-05         TP -1.3862943611  <NA> #> 6723   2054    3F  CC53 2019 2019-08-05       TURB  0.9162907319  <NA> #> 6724   2054    3F  CC53 2020 2020-01-06      CHLAC  1.8405496334  <NA> #> 6725   2054    3F  CC53 2020 2020-01-06      COLOR  3.8712010109     A #> 6726   2054    3F  CC53 2020 2020-01-06         DO  1.7439688054  <NA> #> 6727   2054    3F  CC53 2020 2020-01-06      DOSAT  4.1255201797  <NA> #> 6728   2054    3F  CC53 2020 2020-01-06       NO23 -2.8824035882  <NA> #> 6729   2054    3F  CC53 2020 2020-01-06      SALIN -0.5276327421  <NA> #> 6730   2054    3F  CC53 2020 2020-01-06        TKN -0.4155154440  <NA> #> 6731   2054    3F  CC53 2020 2020-01-06         TN 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3F  CC53 2020 2020-03-02      COLOR  3.8501476017  <NA> #> 6746   2054    3F  CC53 2020 2020-03-02         DO  1.9657127764  <NA> #> 6747   2054    3F  CC53 2020 2020-03-02      DOSAT  4.3451032806  <NA> #> 6748   2054    3F  CC53 2020 2020-03-02       NO23 -5.5214609179     U #> 6749   2054    3F  CC53 2020 2020-03-02      SALIN -0.5621189182  <NA> #> 6750   2054    3F  CC53 2020 2020-03-02        TKN  0.0000000000  <NA> #> 6751   2054    3F  CC53 2020 2020-03-02         TN  0.0019980027     + #> 6752   2054    3F  CC53 2020 2020-03-02         TP -1.9661128564  <NA> #> 6753   2054    3F  CC53 2020 2020-03-02       TURB  1.4816045409     A #> 6754   2054    3F  CC53 2020 2020-09-08      CHLAC  0.8754687374     I #> 6755   2054    3F  CC53 2020 2020-09-08      COLOR  5.5214609179  <NA> #> 6756   2054    3F  CC53 2020 2020-09-08         DO  1.5325568681  <NA> #> 6757   2054    3F  CC53 2020 2020-09-08      DOSAT  4.0621656639  <NA> #> 6758   2054    3F  CC53 2020 2020-09-08       NO23 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3F  CC53 2021 2021-03-01        TKN  0.0953101798  <NA> #> 6800   2054    3F  CC53 2021 2021-03-01         TN  0.0971267107     + #> 6801   2054    3F  CC53 2021 2021-03-01         TP -2.0402208285  <NA> #> 6802   2054    3F  CC53 2021 2021-03-01       TURB  1.2237754316  <NA> #> 6803   2054    3F  CC53 2021 2021-04-05      CHLAC  1.7047480922  <NA> #> 6804   2054    3F  CC53 2021 2021-04-05      COLOR  3.9889840466     A #> 6805   2054    3F  CC53 2021 2021-04-05       NO23 -5.5214609179     I #> 6806   2054    3F  CC53 2021 2021-04-05      SALIN  0.9122827105  <NA> #> 6807   2054    3F  CC53 2021 2021-04-05        TKN -0.2484613593  <NA> #> 6808   2054    3F  CC53 2021 2021-04-05         TN -0.2433462586     + #> 6809   2054    3F  CC53 2021 2021-04-05         TP -1.8971199849  <NA> #> 6810   2054    3F  CC53 2021 2021-04-05       TURB  0.8754687374  <NA> #> 6811   2054    3F  CC53 2021 2021-05-03      CHLAC  1.4350845253  <NA> #> 6812   2054    3F  CC53 2021 2021-05-03      COLOR  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3F  CC53 2021 2021-06-07      SALIN  1.9300710850  <NA> #> 6827   2054    3F  CC53 2021 2021-06-07        TKN -0.0833816089  <NA> #> 6828   2054    3F  CC53 2021 2021-06-07         TN -0.0418642041     + #> 6829   2054    3F  CC53 2021 2021-06-07         TP -1.1711829815  <NA> #> 6830   2054    3F  CC53 2021 2021-06-07       TURB  0.6931471806  <NA> #> 6831   2054    3F  CC53 2021 2021-08-02      CHLAC  1.8870696490  <NA> #> 6832   2054    3F  CC53 2021 2021-08-02      COLOR  5.0106352941  <NA> #> 6833   2054    3F  CC53 2021 2021-08-02         DO  0.9669838462  <NA> #> 6834   2054    3F  CC53 2021 2021-08-02      DOSAT  3.5467396870  <NA> #> 6835   2054    3F  CC53 2021 2021-08-02       NO23 -3.5065578973  <NA> #> 6836   2054    3F  CC53 2021 2021-08-02      SALIN -1.4271163556  <NA> #> 6837   2054    3F  CC53 2021 2021-08-02        TKN  0.4054651081  <NA> #> 6838   2054    3F  CC53 2021 2021-08-02         TN  0.4252677354     + #> 6839   2054    3F  CC53 2021 2021-08-02         TP 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3F  CC53 2021 2021-10-04         DO  1.0296194172  <NA> #> 6854   2054    3F  CC53 2021 2021-10-04      DOSAT  3.5524868292  <NA> #> 6855   2054    3F  CC53 2021 2021-10-04       NO23 -2.9004220937  <NA> #> 6856   2054    3F  CC53 2021 2021-10-04      SALIN -2.0402208285  <NA> #> 6857   2054    3F  CC53 2021 2021-10-04        TKN -0.0725706928  <NA> #> 6858   2054    3F  CC53 2021 2021-10-04         TN -0.0151136378     + #> 6859   2054    3F  CC53 2021 2021-10-04         TP -1.7719568419  <NA> #> 6860   2054    3F  CC53 2021 2021-10-04       TURB  0.7419373447     A #> 6861   2054    3F  CC53 2021 2021-11-01      CHLAC  2.1282317058  <NA> #> 6862   2054    3F  CC53 2021 2021-11-01      COLOR  4.2766661190  <NA> #> 6863   2054    3F  CC53 2021 2021-11-01         DO  1.0681530812  <NA> #> 6864   2054    3F  CC53 2021 2021-11-01      DOSAT  3.5322256441  <NA> #> 6865   2054    3F  CC53 2021 2021-11-01       NO23 -2.6450754019  <NA> #> 6866   2054    3F  CC53 2021 2021-11-01      SALIN 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3F  CC53 2022 2022-01-03         DO  1.3402504226  <NA> #> 6881   2054    3F  CC53 2022 2022-01-03      DOSAT  3.8286413965  <NA> #> 6882   2054    3F  CC53 2022 2022-01-03       NO23 -4.1997050779  <NA> #> 6883   2054    3F  CC53 2022 2022-01-03      SALIN  1.3376291891  <NA> #> 6884   2054    3F  CC53 2022 2022-01-03        TKN -0.1053605157  <NA> #> 6885   2054    3F  CC53 2022 2022-01-03         TN -0.0888312137     + #> 6886   2054    3F  CC53 2022 2022-01-03         TP -1.7719568419  <NA> #> 6887   2054    3F  CC53 2022 2022-01-03       TURB  0.6418538862  <NA> #> 6888   2054    3F  CC53 2022 2022-02-07      CHLAC  2.2082744135  <NA> #> 6889   2054    3F  CC53 2022 2022-02-07      COLOR  3.8286413965  <NA> #> 6890   2054    3F  CC53 2022 2022-02-07         DO  1.7047480922  <NA> #> 6891   2054    3F  CC53 2022 2022-02-07      DOSAT  4.1541845626  <NA> #> 6892   2054    3F  CC53 2022 2022-02-07       NO23 -4.9618451299     I #> 6893   2054    3F  CC53 2022 2022-02-07      SALIN  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3F  CC53 2022 2022-04-04         DO  1.1908875648  <NA> #> 6908   2054    3F  CC53 2022 2022-04-04      DOSAT  3.7208625000  <NA> #> 6909   2054    3F  CC53 2022 2022-04-04       NO23 -4.1997050779  <NA> #> 6910   2054    3F  CC53 2022 2022-04-04      SALIN  2.1860512767  <NA> #> 6911   2054    3F  CC53 2022 2022-04-04        TKN -0.3147107448  <NA> #> 6912   2054    3F  CC53 2022 2022-04-04         TN -0.2943710606     + #> 6913   2054    3F  CC53 2022 2022-04-04         TP -1.2378743560  <NA> #> 6914   2054    3F  CC53 2022 2022-04-04       TURB  1.0296194172  <NA> #> 6915   2054    3F  CC53 2022 2022-05-02      CHLAC  2.4849066498  <NA> #> 6916   2054    3F  CC53 2022 2022-05-02      COLOR  4.0073331852  <NA> #> 6917   2054    3F  CC53 2022 2022-05-02       NO23 -3.9120230054  <NA> #> 6918   2054    3F  CC53 2022 2022-05-02      SALIN  2.5152741864  <NA> #> 6919   2054    3F  CC53 2022 2022-05-02        TKN  0.0953101798  <NA> #> 6920   2054    3F  CC53 2022 2022-05-02         TN  0.1133286853     + #> 6921   2054    3F  CC53 2022 2022-05-02         TP -1.1394342832  <NA> #> 6922   2054    3F  CC53 2022 2022-05-02       TURB  1.0986122887  <NA> #> 6923   2054    3F  CC53 2022 2022-12-05      CHLAC  1.6094379124  <NA> #> 6924   2054    3F  CC53 2022 2022-12-05      COLOR  4.7004803658  <NA> #> 6925   2054    3F  CC53 2022 2022-12-05       NO23 -1.4696759701  <NA> #> 6926   2054    3F  CC53 2022 2022-12-05      SALIN -1.3862943611  <NA> #> 6927   2054    3F  CC53 2022 2022-12-05        TKN -0.0833816089  <NA> #> 6928   2054    3F  CC53 2022 2022-12-05         TN  0.1397619424     + #> 6929   2054    3F  CC53 2022 2022-12-05         TP -1.8971199849  <NA> #> 6930   2054    3F  CC53 2022 2022-12-05       TURB  1.3350010667  <NA> #> 6931   2054    3F  CC53 2023 2023-01-03      CHLAC  2.3978952728  <NA> #> 6932   2054    3F  CC53 2023 2023-01-03      COLOR  4.2484952420     A #> 6933   2054    3F  CC53 2023 2023-01-03         DO  2.1090003439  <NA> #> 6934   2054    3F  CC53 2023 2023-01-03      DOSAT  4.5261269786  <NA> #> 6935   2054    3F  CC53 2023 2023-01-03       NO23 -1.4271163556  <NA> #> 6936   2054    3F  CC53 2023 2023-01-03      SALIN -1.1086626245  <NA> #> 6937   2054    3F  CC53 2023 2023-01-03        TKN -0.1625189295  <NA> #> 6938   2054    3F  CC53 2023 2023-01-03         TN  0.0861776962     + #> 6939   2054    3F  CC53 2023 2023-01-03         TP -2.3025850930  <NA> #> 6940   2054    3F  CC53 2023 2023-01-03       TURB  0.7884573604  <NA> #> 6941   2054    3F  CC53 2023 2023-02-06      CHLAC  3.4965075615  <NA> #> 6942   2054    3F  CC53 2023 2023-02-06      COLOR  4.0253516907  <NA> #> 6943   2054    3F  CC53 2023 2023-02-06         DO  1.9740810260  <NA> #> 6944   2054    3F  CC53 2023 2023-02-06      DOSAT  4.3919769655  <NA> #> 6945   2054    3F  CC53 2023 2023-02-06       NO23 -5.2983173665     I #> 6946   2054    3F  CC53 2023 2023-02-06      SALIN -0.4780358009  <NA> #> 6947   2054    3F  CC53 2023 2023-02-06        TKN  0.0953101798  <NA> #> 6948   2054    3F  CC53 2023 2023-02-06         TN  0.0989399479     + #> 6949   2054    3F  CC53 2023 2023-02-06         TP -1.8325814637  <NA> #> 6950   2054    3F  CC53 2023 2023-02-06       TURB  1.6863989536  <NA> #> 6951   2054    3F  CC53 2023 2023-03-06         DO  1.5623463049  <NA> #> 6952   2054    3F  CC53 2023 2023-03-06      DOSAT  4.0253516907  <NA> #> 6953   2054    3F  CC53 2023 2023-03-06      SALIN  0.8501509294  <NA> #> 6954   2054    3F  CC53 2014 2014-04-07      CHLAC  1.0986122887  <NA> #> 6955   2054    3F  CC53 2014 2014-04-07      COLOR  5.0751738152  <NA> #> 6956   2054    3F  CC53 2014 2014-04-07       COND  7.1701195434  <NA> #> 6957   2054    3F  CC53 2014 2014-04-07         DO  1.7029282555  <NA> #> 6958   2054    3F  CC53 2014 2014-04-07      DOSAT  4.0976723523  <NA> #> 6959   2054    3F  CC53 2014 2014-04-07       NO23 -3.1700856607  <NA> #> 6960   2054    3F  CC53 2014 2014-04-07      SALIN -0.3566749439     + #> 6961   2054    3F  CC53 2014 2014-04-07        TKN  0.6418538862  <NA> #> 6962   2054    3F  CC53 2014 2014-04-07         TN  0.6637183699     + #> 6963   2054    3F  CC53 2014 2014-04-07         TP  0.0953101798  <NA> #> 6964   2054    3F  CC53 2014 2014-04-07        TSS  2.9444389792  <NA> #> 6965   2054    3F  CC53 2014 2014-04-07       TURB  2.7725887222  <NA> #> 6966   2054    3F  CC53 2015 2015-05-21       COND  7.9291264873  <NA> #> 6967   2054    3F  CC53 2015 2015-05-21         DO  1.4109869737  <NA> #> 6968   2054    3F  CC53 2015 2015-05-21      DOSAT  3.9702919136  <NA> #> 6969   2054    3F  CC53 2015 2015-05-21      SALIN  0.2851789422     + #> 6970   2054    3F  CC53 2015 2015-07-15       COND  6.5439118456  <NA> #> 6971   2054    3F  CC53 2015 2015-07-15       COND  6.5453496603  <NA> #> 6972   2054    3F  CC53 2015 2015-07-15      SALIN -1.1711829815     + #> 6973   2054    3F  CC53 2015 2015-08-06       COND  4.9052747784  <NA> #> 6974   2054    3F  CC53 2015 2015-08-06         DO  1.4109869737  <NA> #> 6975   2054    3F  CC53 2015 2015-08-06      DOSAT  3.9702919136  <NA> #> 6976   2054    3F  CC53 2015 2015-08-19       COND  4.8751973232  <NA> #> 6977   2054    3F  CC53 2015 2015-08-19         DO  1.2527629685  <NA> #> 6978   2054    3F  CC53 2015 2015-08-19      DOSAT  3.8501476017  <NA> #> 6979   2054    3F  CC53 2015 2015-09-15       COND  5.4764635519  <NA> #> 6980   2054    3F  CC53 2015 2015-09-15         DO  1.1314021115  <NA> #> 6981   2054    3F  CC53 2015 2015-09-15      DOSAT  3.6888794541  <NA> #> 6982   2054    3F  CC53 2015 2015-09-15      SALIN -2.2072749132     + #> 6983   2054    3F  CC53 2015 2015-09-15       COND  5.4764635519  <NA> #> 6984   2054    3F  CC53 2015 2015-09-15         DO  1.0986122887  <NA> #> 6985   2054    3F  CC53 2015 2015-09-15      DOSAT  3.6635616461  <NA> #> 6986   2054    3F  CC53 2015 2015-09-15      SALIN -2.2072749132     + #> 6987   2054    3F  CC53 2015 2015-11-25       COND  6.2225762681  <NA> #> 6988   2054    3F  CC53 2015 2015-11-25         DO  1.7047480922  <NA> #> 6989   2054    3F  CC53 2015 2015-11-25      DOSAT  4.1431347264  <NA> #> 6990   2054    3F  CC53 2015 2015-11-25      SALIN -1.3470736480     + #> 6991   2054    3F  CC53 2015 2015-11-25       COND  6.2285110036  <NA> #> 6992   2054    3F  CC53 2015 2015-11-25         DO  1.6863989536  <NA> #> 6993   2054    3F  CC53 2015 2015-11-25      DOSAT  4.1431347264  <NA> #> 6994   2054    3F  CC53 2015 2015-11-25      SALIN -1.3470736480     + #> 6995   2054    3F  CC53 2021 2021-02-02       COND  7.0184017991  <NA> #> 6996   2054    3F  CC53 2021 2021-02-02         DO  1.9183921202  <NA> #> 6997   2054    3F  CC53 2021 2021-02-02      DOSAT  4.2822062994  <NA> #> 6998   2054    3F  CC53 2021 2021-02-02      SALIN -0.5798184953  <NA> #> 6999   2054    3F  CC53 2021 2021-03-16       COND  7.8504931809  <NA> #> 7000   2054    3F  CC53 2021 2021-03-16         DO  1.7783364489  <NA> #> 7001   2054    3F  CC53 2021 2021-03-16      DOSAT  4.2527717988  <NA> #> 7002   2054    3F  CC53 2021 2021-03-16      SALIN  0.2776317366  <NA> #> 7003   2054    3F  CC53 2021 2021-09-30       COND  4.8880909413  <NA> #> 7004   2054    3F  CC53 2021 2021-09-30         DO  1.3532545070  <NA> #> 7005   2054    3F  CC53 2021 2021-09-30      DOSAT  3.8774315607  <NA> #> 7006   2054    3F  CC53 2021 2021-09-30      SALIN -2.8134107168  <NA> #> 7007   2054    3F  CC53 2021 2021-09-30       COND  4.8797670189  <NA> #> 7008   2054    3F  CC53 2021 2021-09-30         DO  1.2412685891  <NA> #> 7009   2054    3F  CC53 2021 2021-09-30      DOSAT  3.7750571504  <NA> #> 7010   2054    3F  CC53 2021 2021-09-30      SALIN -2.8134107168  <NA> #> 7011   2054    3F  CC53 2021 2021-10-27       COND  6.5250296578  <NA> #> 7012   2054    3F  CC53 2021 2021-10-27         DO  1.5195132049  <NA> #> 7013   2054    3F  CC53 2021 2021-10-27      DOSAT  4.0412953411  <NA> #> 7014   2054    3F  CC53 2021 2021-10-27      SALIN -1.1086626245  <NA> #> 7015   2054    3F  CC53 2021 2021-10-27       COND  6.5264948596  <NA> #> 7016   2054    3F  CC53 2021 2021-10-27         DO  1.5129270121  <NA> #> 7017   2054    3F  CC53 2021 2021-10-27      DOSAT  4.0342406382  <NA> #> 7018   2054    3F  CC53 2021 2021-10-27      SALIN -1.1086626245  <NA> #> 7019   2054    3F  CC53 2021 2021-11-18       COND  4.7104306966  <NA> #> 7020   2054    3F  CC53 2021 2021-11-18         DO  1.8578592709  <NA> #> 7021   2054    3F  CC53 2021 2021-11-18      DOSAT  4.2682978693  <NA> #> 7022   2054    3F  CC53 2021 2021-11-18      SALIN -2.9957322736  <NA> #> 7023   2059    3M  CC55 2015 2015-05-21       COND  9.9007337643  <NA> #> 7024   2059    3M  CC55 2015 2015-05-21         DO  1.2237754316  <NA> #> 7025   2059    3M  CC55 2015 2015-05-21      DOSAT  3.8286413965  <NA> #> 7026   2059    3M  CC55 2015 2015-05-21      SALIN  2.4105422345     + #> 7027   2059    3M  CC55 2015 2015-07-15       COND  6.7190131544  <NA> #> 7028   2059    3M  CC55 2015 2015-07-15      SALIN -0.9416085399     + #> 7029   2059    3M  CC55 2015 2015-08-06       COND  6.4019171967  <NA> #> 7030   2059    3M  CC55 2015 2015-08-06         DO  1.6292405397  <NA> #> 7031   2059    3M  CC55 2015 2015-08-06      DOSAT  4.1896547420  <NA> #> 7032   2059    3M  CC55 2015 2015-08-06      SALIN -1.3093333200     + #> 7033   2059    3M  CC55 2015 2015-08-19       COND  6.2785214242  <NA> #> 7034   2059    3M  CC55 2015 2015-08-19         DO  1.6094379124  <NA> #> 7035   2059    3M  CC55 2015 2015-08-19      DOSAT  4.1431347264  <NA> #> 7036   2059    3M  CC55 2015 2015-08-19      SALIN -1.3862943611     + #> 7037   2059    3M  CC55 2015 2015-09-15       COND  6.2205901701  <NA> #> 7038   2059    3M  CC55 2015 2015-09-15         DO  1.4816045409  <NA> #> 7039   2059    3M  CC55 2015 2015-09-15      DOSAT  4.0073331852  <NA> #> 7040   2059    3M  CC55 2015 2015-09-15      SALIN -1.4271163556     + #> 7041   2059    3M  CC55 2015 2015-10-08      CHLAC  0.2623642645     I #> 7042   2059    3M  CC55 2015 2015-10-08       COND  6.3969296552  <NA> #> 7043   2059    3M  CC55 2015 2015-10-08         DO  1.6486586256  <NA> #> 7044   2059    3M  CC55 2015 2015-10-08      DOSAT  4.2046926194  <NA> #> 7045   2059    3M  CC55 2015 2015-10-08       NO23 -2.7646205526  <NA> #> 7046   2059    3M  CC55 2015 2015-10-08      SALIN -1.2378743560     + #> 7047   2059    3M  CC55 2015 2015-10-08        TKN -0.1625189295  <NA> #> 7048   2059    3M  CC55 2015 2015-10-08         TN -0.0910193984     + #> 7049   2059    3M  CC55 2015 2015-10-08         TP -2.6310891600  <NA> #> 7050   2059    3M  CC55 2015 2015-10-08        TSS  1.9459101491     I #> 7051   2059    3M  CC55 2015 2015-10-08       TURB  2.0794415417  <NA> #> 7052   2059    3M  CC55 2015 2015-11-05      CHLAC  0.5877866649  <NA> #> 7053   2059    3M  CC55 2015 2015-11-05       COND  6.6982680541  <NA> #> 7054   2059    3M  CC55 2015 2015-11-05         DO  1.9600947840  <NA> #> 7055   2059    3M  CC55 2015 2015-11-05      DOSAT  4.4773368145  <NA> #> 7056   2059    3M  CC55 2015 2015-11-05      SALIN -0.9416085399     + #> 7057   2059    3M  CC55 2015 2015-11-05         TN -0.0693500781     + #> 7058   2059    3M  CC55 2015 2015-11-05        TSS  1.7917594692     I #> 7059   2059    3M  CC55 2015 2015-11-05       TURB  2.2721258855  <NA> #> 7060   2059    3M  CC55 2015 2015-11-25       COND  6.7007311095  <NA> #> 7061   2059    3M  CC55 2015 2015-11-25         DO  2.0014800002  <NA> #> 7062   2059    3M  CC55 2015 2015-11-25      DOSAT  4.4188406078  <NA> #> 7063   2059    3M  CC55 2015 2015-11-25      SALIN -0.8209805521     + #> 7064   2059    3M  CC55 2015 2015-12-03      CHLAC  0.5306282511  <NA> #> 7065   2059    3M  CC55 2015 2015-12-03      COLOR  4.7004803658  <NA> #> 7066   2059    3M  CC55 2015 2015-12-03       COND  6.8448154792  <NA> #> 7067   2059    3M  CC55 2015 2015-12-03         DO  1.8900953699  <NA> #> 7068   2059    3M  CC55 2015 2015-12-03      DOSAT  4.3694478525  <NA> #> 7069   2059    3M  CC55 2015 2015-12-03       NO23 -2.7488721956  <NA> #> 7070   2059    3M  CC55 2015 2015-12-03      SALIN -0.7550225843     + #> 7071   2059    3M  CC55 2015 2015-12-03        TKN -0.2357223335  <NA> #> 7072   2059    3M  CC55 2015 2015-12-03         TN -0.1578240852     + #> 7073   2059    3M  CC55 2015 2015-12-03         TP -2.8647040111  <NA> #> 7074   2059    3M  CC55 2015 2015-12-03        TSS  1.3862943611     I #> 7075   2059    3M  CC55 2015 2015-12-03       TURB  2.1282317058  <NA> #> 7076   2059    3M  CC55 2015 2015-05-21       COND  7.3472997007  <NA> #> 7077   2059    3M  CC55 2015 2015-05-21         DO  0.9932517730  <NA> #> 7078   2059    3M  CC55 2015 2015-05-21      DOSAT  3.4657359028  <NA> #> 7079   2059    3M  CC55 2015 2015-05-21      SALIN -0.3285040670     + #> 7080   2059    3M  CC55 2015 2015-07-15       COND  9.6044074351  <NA> #> 7081   2059    3M  CC55 2015 2015-08-06       COND  6.4068799861  <NA> #> 7082   2059    3M  CC55 2015 2015-08-06         DO  1.6486586256  <NA> #> 7083   2059    3M  CC55 2015 2015-08-06      DOSAT  4.2195077052  <NA> #> 7084   2059    3M  CC55 2015 2015-08-06      SALIN -1.3093333200     + #> 7085   2059    3M  CC55 2015 2015-08-19       COND  6.2653012127  <NA> #> 7086   2059    3M  CC55 2015 2015-08-19         DO  1.3862943611  <NA> #> 7087   2059    3M  CC55 2015 2015-08-19      DOSAT  4.0604430105  <NA> #> 7088   2059    3M  CC55 2015 2015-08-19      SALIN -1.4271163556     + #> 7089   2059    3M  CC55 2015 2015-09-15       COND  6.2519038832  <NA> #> 7090   2059    3M  CC55 2015 2015-09-15         DO  1.6863989536  <NA> #> 7091   2059    3M  CC55 2015 2015-09-15      DOSAT  4.1271343850  <NA> #> 7092   2059    3M  CC55 2015 2015-09-15      SALIN -1.4271163556     + #> 7093   2059    3M  CC55 2015 2015-11-25       COND  8.4348979487  <NA> #> 7094   2059    3M  CC55 2015 2015-11-25         DO -0.1053605157  <NA> #> 7095   2059    3M  CC55 2015 2015-11-25      DOSAT  2.3025850930  <NA> #> 7096   2059    3M  CC55 2015 2015-11-25      SALIN  1.0152306797     + #> 7097   2059    3M  CC56 2015 2015-05-21       COND  9.6019769721  <NA> #> 7098   2059    3M  CC56 2015 2015-05-21         DO  0.6931471806  <NA> #> 7099   2059    3M  CC56 2015 2015-05-21      DOSAT  3.1780538303  <NA> #> 7100   2059    3M  CC56 2015 2015-05-21      SALIN  2.1459312829     + #> 7101   2059    3M  CC56 2015 2015-07-15       COND  8.4859089014  <NA> #> 7102   2059    3M  CC56 2015 2015-07-15      SALIN  0.9001613499     + #> 7103   2059    3M  CC56 2015 2015-08-06       COND  6.3952615981  <NA> #> 7104   2059    3M  CC56 2015 2015-08-06         DO  0.9932517730  <NA> #> 7105   2059    3M  CC56 2015 2015-08-06      DOSAT  3.4657359028  <NA> #> 7106   2059    3M  CC56 2015 2015-08-06      SALIN -1.3093333200     + #> 7107   2059    3M  CC56 2015 2015-08-19       COND  6.1820849067  <NA> #> 7108   2059    3M  CC56 2015 2015-08-19         DO  0.9932517730  <NA> #> 7109   2059    3M  CC56 2015 2015-08-19      DOSAT  3.4965075615  <NA> #> 7110   2059    3M  CC56 2015 2015-08-19      SALIN -1.5141277326     + #> 7111   2059    3M  CC56 2015 2015-09-15       COND  6.2576675879  <NA> #> 7112   2059    3M  CC56 2015 2015-09-15         DO  0.0953101798  <NA> #> 7113   2059    3M  CC56 2015 2015-09-15      DOSAT  2.5649493575  <NA> #> 7114   2059    3M  CC56 2015 2015-09-15      SALIN -1.4271163556     + #> 7115   2059    3M  CC56 2015 2015-11-25       COND  7.6343372356  <NA> #> 7116   2059    3M  CC56 2015 2015-11-25         DO  0.9555114450  <NA> #> 7117   2059    3M  CC56 2015 2015-11-25      DOSAT  3.4011973817  <NA> #> 7118   2059    3M  CC56 2015 2015-11-25      SALIN  0.1570037488     + #> 7119   2059    3M  CC56 2015 2015-05-21       COND  9.9350831141  <NA> #> 7120   2059    3M  CC56 2015 2015-05-21         DO  0.7884573604  <NA> #> 7121   2059    3M  CC56 2015 2015-05-21      DOSAT  3.3672958300  <NA> #> 7122   2059    3M  CC56 2015 2015-05-21      SALIN  2.4865719291     + #> 7123   2059    3M  CC56 2015 2015-07-15      CHLAC  1.0986122887  <NA> #> 7124   2059    3M  CC56 2015 2015-07-15       COND  9.6128678361  <NA> #> 7125   2059    3M  CC56 2015 2015-07-15       NO23 -5.5214609179     U #> 7126   2059    3M  CC56 2015 2015-07-15      SALIN  2.0881534823     + #> 7127   2059    3M  CC56 2015 2015-07-15        TKN  0.2623642645  <NA> #> 7128   2059    3M  CC56 2015 2015-07-15         TN  0.2639015438     + #> 7129   2059    3M  CC56 2015 2015-07-15         TP -0.9416085399  <NA> #> 7130   2059    3M  CC56 2015 2015-07-15        TSS  1.0986122887     U #> 7131   2059    3M  CC56 2015 2015-07-15       TURB  1.3862943611  <NA> #> 7132   2059    3M  CC56 2015 2015-08-06       COND  6.5366915976  <NA> #> 7133   2059    3M  CC56 2015 2015-08-06         DO  0.2623642645  <NA> #> 7134   2059    3M  CC56 2015 2015-08-06      DOSAT  2.7725887222  <NA> #> 7135   2059    3M  CC56 2015 2015-08-06      SALIN -1.1394342832     + #> 7136   2059    3M  CC56 2015 2015-08-19      CHLAC  1.0296194172  <NA> #> 7137   2059    3M  CC56 2015 2015-08-19      COLOR  5.4380793089  <NA> #> 7138   2059    3M  CC56 2015 2015-08-19       COND  6.4488893941  <NA> #> 7139   2059    3M  CC56 2015 2015-08-19         DO  0.1823215568  <NA> #> 7140   2059    3M  CC56 2015 2015-08-19      DOSAT  2.7725887222  <NA> #> 7141   2059    3M  CC56 2015 2015-08-19       NO23 -5.5214609179     U #> 7142   2059    3M  CC56 2015 2015-08-19      SALIN -1.2378743560     + #> 7143   2059    3M  CC56 2015 2015-08-19        TKN  0.4054651081  <NA> #> 7144   2059    3M  CC56 2015 2015-08-19         TN  0.4067975533     + #> 7145   2059    3M  CC56 2015 2015-08-19         TP -0.0304592075  <NA> #> 7146   2059    3M  CC56 2015 2015-08-19        TSS  1.7917594692     I #> 7147   2059    3M  CC56 2015 2015-08-19       TURB  1.5686159179  <NA> #> 7148   2059    3M  CC56 2015 2015-09-15       COND  6.8134445995  <NA> #> 7149   2059    3M  CC56 2015 2015-09-15         DO  0.0000000000  <NA> #> 7150   2059    3M  CC56 2015 2015-09-15      DOSAT  2.3025850930  <NA> #> 7151   2059    3M  CC56 2015 2015-09-15      SALIN -0.8439700703     + #> 7152   2059    3M  CC56 2015 2015-11-25       COND  7.8038433035  <NA> #> 7153   2059    3M  CC56 2015 2015-11-25         DO  1.8718021769  <NA> #> 7154   2059    3M  CC56 2015 2015-11-25      DOSAT  4.2626798770  <NA> #> 7155   2059    3M  CC56 2015 2015-11-25      SALIN  0.3576744443     + #> 7156   2059    3M  CC56 2018 2018-03-06      CHLAC  1.7917594692  <NA> #> 7157   2059    3M  CC56 2018 2018-03-06       COND  9.8471817163  <NA> #> 7158   2059    3M  CC56 2018 2018-03-06         DO  0.6205764877  <NA> #> 7159   2059    3M  CC56 2018 2018-03-06      DOSAT  3.0445224377  <NA> #> 7160   2059    3M  CC56 2018 2018-03-06       NO23 -2.6592600369  <NA> #> 7161   2059    3M  CC56 2018 2018-03-06      SALIN  2.5748996883     + #> 7162   2059    3M  CC56 2018 2018-03-06        TKN -0.0833816089  <NA> #> 7163   2059    3M  CC56 2018 2018-03-06         TN -0.0100503359     + #> 7164   2059    3M  CC56 2018 2018-03-06         TP -1.2378743560  <NA> #> 7165   2059    3M  CC56 2018 2018-03-06        TSS  1.0986122887     U #> 7166   2059    3M  CC56 2018 2018-03-06       TURB  0.1823215568  <NA> #> 7167   2059    3M  CC56 2018 2018-03-29      CHLAC  2.1747517215  <NA> #> 7168   2059    3M  CC56 2018 2018-03-29       COND 10.2506170836  <NA> #> 7169   2059    3M  CC56 2018 2018-03-29         DO  1.3083328197  <NA> #> 7170   2059    3M  CC56 2018 2018-03-29      DOSAT  3.8501476017  <NA> #> 7171   2059    3M  CC56 2018 2018-03-29       NO23 -4.7105307016     I #> 7172   2059    3M  CC56 2018 2018-03-29      SALIN  2.9156062291     + #> 7173   2059    3M  CC56 2018 2018-03-29        TKN -0.2484613593  <NA> #> 7174   2059    3M  CC56 2018 2018-03-29         TN -0.2433462586     + #> 7175   2059    3M  CC56 2018 2018-03-29         TP -1.2039728043  <NA> #> 7176   2059    3M  CC56 2018 2018-03-29        TSS  1.3862943611     I #> 7177   2059    3M  CC56 2018 2018-03-29       TURB  0.8754687374  <NA> #> 7178   2059    3M  CC56 2018 2018-04-12       COND 10.0096027833  <NA> #> 7179   2059    3M  CC56 2018 2018-04-12         DO -0.3566749439  <NA> #> 7180   2059    3M  CC56 2018 2018-04-12      DOSAT  2.0794415417  <NA> #> 7181   2059    3M  CC56 2018 2018-04-12      SALIN  2.6932749155     + #> 7182   2059    3M  CC56 2018 2018-04-19      CHLAC  0.0953101798     I #> 7183   2059    3M  CC56 2018 2018-04-19       COND 10.2545668701  <NA> #> 7184   2059    3M  CC56 2018 2018-04-19         DO  1.0260415958  <NA> #> 7185   2059    3M  CC56 2018 2018-04-19      DOSAT  3.5025498759  <NA> #> 7186   2059    3M  CC56 2018 2018-04-19       NO23 -4.6051701860     I #> 7187   2059    3M  CC56 2018 2018-04-19      SALIN  2.9150643705     + #> 7188   2059    3M  CC56 2018 2018-04-19        TKN -0.1863295782  <NA> #> 7189   2059    3M  CC56 2018 2018-04-19         TN -0.1815218766     + #> 7190   2059    3M  CC56 2018 2018-04-19         TP -1.0788096614  <NA> #> 7191   2059    3M  CC56 2018 2018-04-19        TSS  1.3862943611     I #> 7192   2059    3M  CC56 2018 2018-04-19       TURB  0.1823215568  <NA> #> 7193   2059    3M  CC56 2018 2018-05-10      CHLAC  1.0296194172  <NA> #> 7194   2059    3M  CC56 2018 2018-05-10       COND 10.2722540975  <NA> #> 7195   2059    3M  CC56 2018 2018-05-10         DO -0.1053605157  <NA> #> 7196   2059    3M  CC56 2018 2018-05-10      DOSAT  2.4849066498  <NA> #> 7197   2059    3M  CC56 2018 2018-05-10       NO23 -5.5214609179     U #> 7198   2059    3M  CC56 2018 2018-05-10      SALIN  2.8848007128  <NA> #> 7199   2059    3M  CC56 2018 2018-05-10        TKN -0.0725706928  <NA> #> 7200   2059    3M  CC56 2018 2018-05-10         TN -0.0704224643     + #> 7201   2059    3M  CC56 2018 2018-05-10         TP -0.8209805521  <NA> #> 7202   2059    3M  CC56 2018 2018-05-10        TSS  1.0986122887     I #> 7203   2059    3M  CC56 2018 2018-05-10       TURB  0.5306282511  <NA> #> 7204   2059    3M  CC56 2018 2018-06-25      CHLAC  0.6931471806  <NA> #> 7205   2059    3M  CC56 2018 2018-06-25       COND  7.7536235466  <NA> #> 7206   2059    3M  CC56 2018 2018-06-25         DO  1.0296194172  <NA> #> 7207   2059    3M  CC56 2018 2018-06-25      DOSAT  3.2695689392  <NA> #> 7208   2059    3M  CC56 2018 2018-06-25       NO23 -5.5214609179     U #> 7209   2059    3M  CC56 2018 2018-06-25      SALIN  0.1397619424     + #> 7210   2059    3M  CC56 2018 2018-06-25        TKN  0.2623642645  <NA> #> 7211   2059    3M  CC56 2018 2018-06-25         TN  0.2639015438     + #> 7212   2059    3M  CC56 2018 2018-06-25         TP -1.4696759701  <NA> #> 7213   2059    3M  CC56 2018 2018-06-25        TSS  1.0986122887     I #> 7214   2059    3M  CC56 2018 2018-06-25       TURB  1.3862943611  <NA> #> 7215   2059    3M  CC56 2018 2018-07-17      CHLAC  0.9932517730  <NA> #> 7216   2059    3M  CC56 2018 2018-07-17       COND  6.8437499490  <NA> #> 7217   2059    3M  CC56 2018 2018-07-17         DO -0.1863295782  <NA> #> 7218   2059    3M  CC56 2018 2018-07-17      DOSAT  2.3418058061  <NA> #> 7219   2059    3M  CC56 2018 2018-07-17       NO23 -3.3524072175  <NA> #> 7220   2059    3M  CC56 2018 2018-07-17      SALIN -0.8439700703     + #> 7221   2059    3M  CC56 2018 2018-07-17        TKN  0.2623642645  <NA> #> 7222   2059    3M  CC56 2018 2018-07-17         TN  0.2889312919     + #> 7223   2059    3M  CC56 2018 2018-07-17         TP -1.3093333200  <NA> #> 7224   2059    3M  CC56 2018 2018-07-17        TSS  1.0986122887     I #> 7225   2059    3M  CC56 2018 2018-07-17       TURB  0.0953101798  <NA> #> 7226   2059    3M  CC56 2018 2018-08-01      CHLAC  0.8754687374  <NA> #> 7227   2059    3M  CC56 2018 2018-08-01       COND  6.0038870671  <NA> #> 7228   2059    3M  CC56 2018 2018-08-01         DO  0.7129498079  <NA> #> 7229   2059    3M  CC56 2018 2018-08-01      DOSAT  3.2580965380  <NA> #> 7230   2059    3M  CC56 2018 2018-08-01       NO23 -3.6119184130  <NA> #> 7231   2059    3M  CC56 2018 2018-08-01      SALIN -1.6607312068  <NA> #> 7232   2059    3M  CC56 2018 2018-08-01        TKN  0.0953101798  <NA> #> 7233   2059    3M  CC56 2018 2018-08-01         TN  0.1195592351     + #> 7234   2059    3M  CC56 2018 2018-08-01         TP -1.7719568419  <NA> #> 7235   2059    3M  CC56 2018 2018-08-01        TSS  0.6931471806     U #> 7236   2059    3M  CC56 2018 2018-08-01       TURB  0.0953101798  <NA> #> 7237   2059    3M  CC56 2018 2018-08-20      CHLAC  0.4054651081     I #> 7238   2059    3M  CC56 2018 2018-08-20       NO23 -1.4696759701  <NA> #> 7239   2059    3M  CC56 2018 2018-08-20        TKN -0.3147107448  <NA> #> 7240   2059    3M  CC56 2018 2018-08-20         TN -0.0408219945     + #> 7241   2059    3M  CC56 2018 2018-08-20         TP -0.9416085399  <NA> #> 7242   2059    3M  CC56 2018 2018-08-20        TSS  1.0986122887     U #> 7243   2059    3M  CC56 2018 2018-08-20       TURB  0.7419373447  <NA> #> 7244   2059    3M  CC56 2018 2018-08-21      CHLAC  0.7419373447  <NA> #> 7245   2059    3M  CC56 2018 2018-08-21       COND  5.9401712527  <NA> #> 7246   2059    3M  CC56 2018 2018-08-21         DO  0.9516578757  <NA> #> 7247   2059    3M  CC56 2018 2018-08-21      DOSAT  3.4436180975  <NA> #> 7248   2059    3M  CC56 2018 2018-08-21       NO23 -3.7297014486  <NA> #> 7249   2059    3M  CC56 2018 2018-08-21      SALIN -1.7147984281  <NA> #> 7250   2059    3M  CC56 2018 2018-08-21        TKN  0.0000000000  <NA> #> 7251   2059    3M  CC56 2018 2018-08-21         TN  0.0237165266     + #> 7252   2059    3M  CC56 2018 2018-08-21         TP -1.8325814637  <NA> #> 7253   2059    3M  CC56 2018 2018-08-21        TSS  1.0986122887     I #> 7254   2059    3M  CC56 2018 2018-08-21       TURB  0.3364722366     A #> 7255   2059    3M  CC56 2018 2018-09-20      CHLAC  1.5040773968  <NA> #> 7256   2059    3M  CC56 2018 2018-09-20       COND  7.2661287796  <NA> #> 7257   2059    3M  CC56 2018 2018-09-20         DO  0.9555114450  <NA> #> 7258   2059    3M  CC56 2018 2018-09-20      DOSAT  3.5862928653  <NA> #> 7259   2059    3M  CC56 2018 2018-09-20       NO23 -3.1010927892  <NA> #> 7260   2059    3M  CC56 2018 2018-09-20      SALIN -0.3424903089  <NA> #> 7261   2059    3M  CC56 2018 2018-09-20        TKN  0.1823215568  <NA> #> 7262   2059    3M  CC56 2018 2018-09-20         TN  0.2191355299     + #> 7263   2059    3M  CC56 2018 2018-09-20         TP -1.0788096614  <NA> #> 7264   2059    3M  CC56 2018 2018-09-20        TSS  1.0986122887     I #> 7265   2059    3M  CC56 2018 2018-09-20       TURB  0.9162907319  <NA> #> 7266   2059    3M  CC56 2018 2018-10-24      CHLAC  1.1314021115  <NA> #> 7267   2059    3M  CC56 2018 2018-10-24       COND  9.4323632956  <NA> #> 7268   2059    3M  CC56 2018 2018-10-24         DO  0.5068176024  <NA> #> 7269   2059    3M  CC56 2018 2018-10-24      DOSAT  3.0726933147  <NA> #> 7270   2059    3M  CC56 2018 2018-10-24       NO23 -3.4737680745  <NA> #> 7271   2059    3M  CC56 2018 2018-10-24      SALIN  1.9671123567  <NA> #> 7272   2059    3M  CC56 2018 2018-10-24        TKN -0.0408219945  <NA> #> 7273   2059    3M  CC56 2018 2018-10-24         TN -0.0090407447     + #> 7274   2059    3M  CC56 2018 2018-10-24         TP -1.2039728043  <NA> #> 7275   2059    3M  CC56 2018 2018-10-24        TSS  0.6931471806     I #> 7276   2059    3M  CC56 2018 2018-10-24       TURB  1.7227665977  <NA> #> 7277   2059    3M  CC56 2019 2019-01-16      CHLAC -0.1053605157     I #> 7278   2059    3M  CC56 2019 2019-01-16       COND  9.0122552200  <NA> #> 7279   2059    3M  CC56 2019 2019-01-16         DO  0.3852624008  <NA> #> 7280   2059    3M  CC56 2019 2019-01-16      DOSAT  2.7080502011  <NA> #> 7281   2059    3M  CC56 2019 2019-01-16       NO23 -2.5010360317  <NA> #> 7282   2059    3M  CC56 2019 2019-01-16      SALIN  1.5216989981  <NA> #> 7283   2059    3M  CC56 2019 2019-01-16        TKN -0.0618754037  <NA> #> 7284   2059    3M  CC56 2019 2019-01-16         TN  0.0217614918     + #> 7285   2059    3M  CC56 2019 2019-01-16         TP -1.3862943611  <NA> #> 7286   2059    3M  CC56 2019 2019-01-16        TSS  0.6931471806     U #> 7287   2059    3M  CC56 2019 2019-01-16       TURB  0.0000000000  <NA> #> 7288   2059    3M  CC56 2019 2019-01-24       COND  9.8578100390  <NA> #> 7289   2059    3M  CC56 2019 2019-01-24         DO  1.6770965609  <NA> #> 7290   2059    3M  CC56 2019 2019-01-24      DOSAT  4.1588830834  <NA> #> 7291   2059    3M  CC56 2019 2019-01-24       NO23 -3.2968373663  <NA> #> 7292   2059    3M  CC56 2019 2019-01-24      SALIN  2.4327357775  <NA> #> 7293   2059    3M  CC56 2019 2019-01-24        TKN -0.3147107448  <NA> #> 7294   2059    3M  CC56 2019 2019-01-24         TN -0.2652684776     + #> 7295   2059    3M  CC56 2019 2019-01-24         TP -1.3470736480  <NA> #> 7296   2059    3M  CC56 2019 2019-01-24        TSS  1.0986122887     U #> 7297   2059    3M  CC56 2019 2019-01-24       TURB  0.6418538862  <NA> #> 7298   2059    3M  CC56 2019 2019-03-12      CHLAC  0.1823215568     I #> 7299   2059    3M  CC56 2019 2019-03-12       COND  9.1291303166  <NA> #> 7300   2059    3M  CC56 2019 2019-03-12         DO  0.4824261492  <NA> #> 7301   2059    3M  CC56 2019 2019-03-12      DOSAT  2.9496883351  <NA> #> 7302   2059    3M  CC56 2019 2019-03-12       NO23 -3.2968373663  <NA> #> 7303   2059    3M  CC56 2019 2019-03-12      SALIN  1.6114359151  <NA> #> 7304   2059    3M  CC56 2019 2019-03-12        TKN -0.0408219945  <NA> #> 7305   2059    3M  CC56 2019 2019-03-12         TN -0.0030045090     + #> 7306   2059    3M  CC56 2019 2019-03-12         TP -1.0498221245  <NA> #> 7307   2059    3M  CC56 2019 2019-03-12        TSS  0.6931471806     I #> 7308   2059    3M  CC56 2019 2019-03-12       TURB  0.0000000000  <NA> #> 7309   2059    3M  CC56 2019 2019-04-23      CHLAC  1.1939224685  <NA> #> 7310   2059    3M  CC56 2019 2019-04-23       COND  9.4766200382  <NA> #> 7311   2059    3M  CC56 2019 2019-04-23         DO  0.7929925155  <NA> #> 7312   2059    3M  CC56 2019 2019-04-23      DOSAT  3.3286266888  <NA> #> 7313   2059    3M  CC56 2019 2019-04-23       NO23 -3.5755507688  <NA> #> 7314   2059    3M  CC56 2019 2019-04-23      SALIN  2.0175661380  <NA> #> 7315   2059    3M  CC56 2019 2019-04-23        TKN -0.1984509387  <NA> #> 7316   2059    3M  CC56 2019 2019-04-23         TN -0.1648746432     + #> 7317   2059    3M  CC56 2019 2019-04-23         TP -1.1086626245  <NA> #> 7318   2059    3M  CC56 2019 2019-04-23        TSS  0.6931471806     I #> 7319   2059    3M  CC56 2019 2019-04-23       TURB  0.2623642645  <NA> #> 7320   2059    3M  CC56 2019 2019-06-11      CHLAC  1.8245492921     I #> 7321   2059    3M  CC56 2019 2019-06-11       COND  9.8113722636  <NA> #> 7322   2059    3M  CC56 2019 2019-06-11         DO -1.0216512475  <NA> #> 7323   2059    3M  CC56 2019 2019-06-11      DOSAT  1.6094379124  <NA> #> 7324   2059    3M  CC56 2019 2019-06-11       NO23 -5.5214609179     U #> 7325   2059    3M  CC56 2019 2019-06-11      SALIN  2.4221443281  <NA> #> 7326   2059    3M  CC56 2019 2019-06-11        TKN  0.0000000000  <NA> #> 7327   2059    3M  CC56 2019 2019-06-11         TN  0.0019980027     + #> 7328   2059    3M  CC56 2019 2019-06-11         TP -1.0498221245  <NA> #> 7329   2059    3M  CC56 2019 2019-06-11        TSS  1.3862943611     I #> 7330   2059    3M  CC56 2019 2019-06-11       TURB  1.4350845253     A #> 7331   2059    3M  CC56 2019 2019-08-13      CHLAC  0.4054651081     I #> 7332   2059    3M  CC56 2019 2019-08-13       COND  6.6644090204  <NA> #> 7333   2059    3M  CC56 2019 2019-08-13         DO -0.3285040670  <NA> #> 7334   2059    3M  CC56 2019 2019-08-13      DOSAT  2.2192034841  <NA> #> 7335   2059    3M  CC56 2019 2019-08-13       NO23 -2.7488721956  <NA> #> 7336   2059    3M  CC56 2019 2019-08-13      SALIN -0.9675840263  <NA> #> 7337   2059    3M  CC56 2019 2019-08-13        TKN  0.1823215568  <NA> #> 7338   2059    3M  CC56 2019 2019-08-13         TN  0.2342812957     + #> 7339   2059    3M  CC56 2019 2019-08-13         TP -1.3470736480  <NA> #> 7340   2059    3M  CC56 2019 2019-08-13        TSS  0.6931471806     I #> 7341   2059    3M  CC56 2019 2019-08-13       TURB  0.0000000000  <NA> #> 7342   2059    3M  CC56 2019 2019-10-01       COND  8.7345600900  <NA> #> 7343   2059    3M  CC56 2019 2019-10-01         DO  0.1310282624  <NA> #> 7344   2059    3M  CC56 2019 2019-10-01      DOSAT  2.6532419646  <NA> #> 7345   2059    3M  CC56 2019 2019-10-01      SALIN  1.2149127444  <NA> #> 7346   2059    3M  CC56 2019 2019-11-04       COND  8.7934603611  <NA> #> 7347   2059    3M  CC56 2019 2019-11-04         DO  0.0000000000  <NA> #> 7348   2059    3M  CC56 2019 2019-11-04      DOSAT  2.5649493575  <NA> #> 7349   2059    3M  CC56 2019 2019-11-04      SALIN  1.2809338455  <NA> #> 7350   2059    3M  CC56 2019 2019-11-19      CHLAC  1.2809338455  <NA> #> 7351   2059    3M  CC56 2019 2019-11-19       COND  9.6775902130  <NA> #> 7352   2059    3M  CC56 2019 2019-11-19         DO  0.9631743178  <NA> #> 7353   2059    3M  CC56 2019 2019-11-19      DOSAT  3.4078419244  <NA> #> 7354   2059    3M  CC56 2019 2019-11-19       NO23 -2.9565115604  <NA> #> 7355   2059    3M  CC56 2019 2019-11-19      SALIN  2.2364452905  <NA> #> 7356   2059    3M  CC56 2019 2019-11-19        TKN -0.3011050928  <NA> #> 7357   2059    3M  CC56 2019 2019-11-19         TN -0.2331938872     + #> 7358   2059    3M  CC56 2019 2019-11-19         TP -1.2378743560  <NA> #> 7359   2059    3M  CC56 2019 2019-11-19        TSS  1.0986122887     U #> 7360   2059    3M  CC56 2019 2019-11-19       TURB  0.1823215568  <NA> #> 7361   2059    3M  CC56 2020 2020-01-28      CHLAC  0.7419373447     U #> 7362   2059    3M  CC56 2020 2020-01-28       COND  8.9703049530  <NA> #> 7363   2059    3M  CC56 2020 2020-01-28         DO  1.0784095814  <NA> #> 7364   2059    3M  CC56 2020 2020-01-28      DOSAT  3.4468078929  <NA> #> 7365   2059    3M  CC56 2020 2020-01-28       NO23 -1.4271163556  <NA> #> 7366   2059    3M  CC56 2020 2020-01-28      SALIN  1.4747630091  <NA> #> 7367   2059    3M  CC56 2020 2020-01-28        TKN -0.2744368457  <NA> #> 7368   2059    3M  CC56 2020 2020-01-28         TN  0.0000000000     + #> 7369   2059    3M  CC56 2020 2020-01-28         TP -1.9661128564  <NA> #> 7370   2059    3M  CC56 2020 2020-01-28        TSS  0.6931471806     U #> 7371   2059    3M  CC56 2020 2020-01-28       TURB  0.0000000000  <NA> #> 7372   2059    3M  CC56 2020 2020-03-05      CHLAC  0.6418538862     I #> 7373   2059    3M  CC56 2020 2020-03-05       COND 10.0861423871  <NA> #> 7374   2059    3M  CC56 2020 2020-03-05         DO  0.4700036292  <NA> #> 7375   2059    3M  CC56 2020 2020-03-05      DOSAT  2.9957322736  <NA> #> 7376   2059    3M  CC56 2020 2020-03-05       NO23 -2.9004220937  <NA> #> 7377   2059    3M  CC56 2020 2020-03-05      SALIN  2.6817062258  <NA> #> 7378   2059    3M  CC56 2020 2020-03-05        TKN -0.3424903089  <NA> #> 7379   2059    3M  CC56 2020 2020-03-05         TN -0.2678794452     + #> 7380   2059    3M  CC56 2020 2020-03-05         TP -1.2378743560  <NA> #> 7381   2059    3M  CC56 2020 2020-03-05        TSS  1.3862943611     I #> 7382   2059    3M  CC56 2020 2020-03-05       TURB  0.9932517730  <NA> #> 7383   2059    3M  CC56 2020 2020-07-28      CHLAC  1.3083328197  <NA> #> 7384   2059    3M  CC56 2020 2020-07-28       COND  9.3060141220  <NA> #> 7385   2059    3M  CC56 2020 2020-07-28         DO -0.1053605157  <NA> #> 7386   2059    3M  CC56 2020 2020-07-28      DOSAT  2.4849066498  <NA> #> 7387   2059    3M  CC56 2020 2020-07-28       NO23 -3.6119184130  <NA> #> 7388   2059    3M  CC56 2020 2020-07-28      SALIN  1.8261608959  <NA> #> 7389   2059    3M  CC56 2020 2020-07-28        TKN  0.0000000000  <NA> #> 7390   2059    3M  CC56 2020 2020-07-28         TN  0.0266419309     + #> 7391   2059    3M  CC56 2020 2020-07-28         TP -0.6733445533  <NA> #> 7392   2059    3M  CC56 2020 2020-07-28        TSS  0.6931471806     I #> 7393   2059    3M  CC56 2020 2020-07-28       TURB  1.1939224685  <NA> #> 7394   2059    3M  CC56 2020 2020-08-31      CHLAC  0.4700036292     U #> 7395   2059    3M  CC56 2020 2020-08-31       COND  7.2751723195  <NA> #> 7396   2059    3M  CC56 2020 2020-08-31         DO -1.2378743560  <NA> #> 7397   2059    3M  CC56 2020 2020-08-31      DOSAT  1.3083328197  <NA> #> 7398   2059    3M  CC56 2020 2020-08-31       NO23 -3.5404594490  <NA> #> 7399   2059    3M  CC56 2020 2020-08-31      SALIN -0.3285040670  <NA> #> 7400   2059    3M  CC56 2020 2020-08-31        TKN  0.3364722366  <NA> #> 7401   2059    3M  CC56 2020 2020-08-31         TN  0.3569748989     + #> 7402   2059    3M  CC56 2020 2020-08-31         TP -1.3862943611  <NA> #> 7403   2059    3M  CC56 2020 2020-08-31        TSS  0.6931471806     U #> 7404   2059    3M  CC56 2020 2020-08-31       TURB  0.4054651081  <NA> #> 7405   2059    3M  CC56 2020 2020-09-16      CHLAC  0.4700036292     U #> 7406   2059    3M  CC56 2020 2020-09-16       COND  6.8068293604  <NA> #> 7407   2059    3M  CC56 2020 2020-09-16         DO  0.4054651081  <NA> #> 7408   2059    3M  CC56 2020 2020-09-16      DOSAT  2.9444389792  <NA> #> 7409   2059    3M  CC56 2020 2020-09-16       NO23 -2.6882475738  <NA> #> 7410   2059    3M  CC56 2020 2020-09-16      SALIN -0.8209805521  <NA> #> 7411   2059    3M  CC56 2020 2020-09-16        TKN -0.2107210313  <NA> #> 7412   2059    3M  CC56 2020 2020-09-16         TN -0.1301086853     + #> 7413   2059    3M  CC56 2020 2020-09-16         TP -1.3862943611  <NA> #> 7414   2059    3M  CC56 2020 2020-09-16        TSS  0.6931471806     I #> 7415   2059    3M  CC56 2020 2020-09-16       TURB  0.6418538862  <NA> #> 7416   2059    3M  CC56 2023 2023-01-04       COND 10.3353673668  <NA> #> 7417   2059    3M  CC56 2023 2023-01-04         DO  1.8148247422  <NA> #> 7418   2059    3M  CC56 2023 2023-01-04      DOSAT  4.3320482649  <NA> #> 7419   2059    3M  CC56 2023 2023-01-04      SALIN  2.9538680695  <NA> #> 7420   2059    3M  CC56 2023 2023-01-18      CHLAC  0.9932517730     I #> 7421   2059    3M  CC56 2023 2023-01-18       COND 10.0905063931  <NA> #> 7422   2059    3M  CC56 2023 2023-01-18         DO  1.8131947499  <NA> #> 7423   2059    3M  CC56 2023 2023-01-18      DOSAT  4.2541932632  <NA> #> 7424   2059    3M  CC56 2023 2023-01-18       NO23 -1.8971199849  <NA> #> 7425   2059    3M  CC56 2023 2023-01-18      SALIN  2.6864860232  <NA> #> 7426   2059    3M  CC56 2023 2023-01-18        TKN  0.4054651081  <NA> #> 7427   2059    3M  CC56 2023 2023-01-18         TN  0.5007752879     + #> 7428   2059    3M  CC56 2023 2023-01-18         TP -1.7147984281  <NA> #> 7429   2059    3M  CC56 2023 2023-01-18        TSS  1.0986122887     U #> 7430   2059    3M  CC56 2023 2023-01-18       TURB  0.3364722366  <NA> #> 7431   2059    3M  CC56 2023 2023-03-01      CHLAC  2.9957322736  <NA> #> 7432   2059    3M  CC56 2023 2023-03-01       COND 10.0265897497  <NA> #> 7433   2059    3M  CC56 2023 2023-03-01         DO -0.8439700703  <NA> #> 7434   2059    3M  CC56 2023 2023-03-01      DOSAT  1.7227665977  <NA> #> 7435   2059    3M  CC56 2023 2023-03-01       NO23 -0.4780358009  <NA> #> 7436   2059    3M  CC56 2023 2023-03-01      SALIN  2.6130066524  <NA> #> 7437   2059    3M  CC56 2023 2023-03-01        TKN  0.9555114450  <NA> #> 7438   2059    3M  CC56 2023 2023-03-01         TN  1.1693813596     + #> 7439   2059    3M  CC56 2023 2023-03-01         TP -0.8209805521  <NA> #> 7440   2059    3M  CC56 2023 2023-03-01        TSS  3.4965075615  <NA> #> 7441   2059    3M  CC56 2023 2023-03-01       TURB  4.0073331852  <NA> #> 7442   2059    3M  CC56 2023 2023-03-15      CHLAC  1.5260563035     I #> 7443   2059    3M  CC56 2023 2023-03-15       COND 10.0164590312  <NA> #> 7444   2059    3M  CC56 2023 2023-03-15         DO -0.7550225843  <NA> #> 7445   2059    3M  CC56 2023 2023-03-15      DOSAT  1.8082887712  <NA> #> 7446   2059    3M  CC56 2023 2023-03-15       NO23 -0.2107210313  <NA> #> 7447   2059    3M  CC56 2023 2023-03-15      SALIN  2.6026896854  <NA> #> 7448   2059    3M  CC56 2023 2023-03-15        TKN  0.7419373447  <NA> #> 7449   2059    3M  CC56 2023 2023-03-15         TN  1.0681530812     + #> 7450   2059    3M  CC56 2023 2023-03-15         TP -1.1711829815  <NA> #> 7451   2059    3M  CC56 2023 2023-03-15        TSS  3.3322045102  <NA> #> 7452   2059    3M  CC56 2023 2023-03-15       TURB  3.6109179126  <NA> #> 7453   2059    3M  CC56 2023 2023-05-02       COND  7.8264431355  <NA> #> 7454   2059    3M  CC56 2023 2023-05-02         DO  0.7514160887  <NA> #> 7455   2059    3M  CC56 2023 2023-05-02      DOSAT  3.2503744919  <NA> #> 7456   2059    3M  CC56 2023 2023-05-02      SALIN  0.2390169005  <NA> #> 7457   2059    3M  CC56 2018 2018-07-16      CHLAC  1.1314021115  <NA> #> 7458   2059    3M  CC56 2018 2018-07-16      COLOR  5.9661467391  <NA> #> 7459   2059    3M  CC56 2018 2018-07-16       COND  6.0969500550  <NA> #> 7460   2059    3M  CC56 2018 2018-07-16         DO  0.1988508587  <NA> #> 7461   2059    3M  CC56 2018 2018-07-16      DOSAT  2.7536607124  <NA> #> 7462   2059    3M  CC56 2018 2018-07-16       NO23 -3.1700856607  <NA> #> 7463   2059    3M  CC56 2018 2018-07-16      SALIN -1.6094379124     + #> 7464   2059    3M  CC56 2018 2018-07-16        TKN  0.2623642645  <NA> #> 7465   2059    3M  CC56 2018 2018-07-16         TN  0.2941610385     + #> 7466   2059    3M  CC56 2018 2018-07-16         TP -1.4271163556  <NA> #> 7467   2059    3M  CC56 2018 2018-07-16        TSS  0.6931471806     I #> 7468   2059    3M  CC56 2018 2018-07-16       TURB -0.0512932944  <NA> #> 7469   2063    3M  CC64 2014 2014-01-06      CHLAC  1.3862943611  <NA> #> 7470   2063    3M  CC64 2014 2014-01-06      COLOR  2.6390573296  <NA> #> 7471   2063    3M  CC64 2014 2014-01-06         DO  1.7785053535  <NA> #> 7472   2063    3M  CC64 2014 2014-01-06      DOSAT  4.3412046402     + #> 7473   2063    3M  CC64 2014 2014-01-06       NO23 -5.1159958098     I #> 7474   2063    3M  CC64 2014 2014-01-06      SALIN  3.3534067178  <NA> #> 7475   2063    3M  CC64 2014 2014-01-06        TKN -0.8915981193  <NA> #> 7476   2063    3M  CC64 2014 2014-01-06         TN -0.8818893052     + #> 7477   2063    3M  CC64 2014 2014-01-06         TP -2.4889146712  <NA> #> 7478   2063    3M  CC64 2014 2014-01-06       TURB  0.4700036292  <NA> #> 7479   2063    3M  CC64 2014 2014-02-03      CHLAC  0.1823215568     I #> 7480   2063    3M  CC64 2014 2014-02-03      COLOR  1.7227665977     I #> 7481   2063    3M  CC64 2014 2014-02-03         DO  1.6992786164  <NA> #> 7482   2063    3M  CC64 2014 2014-02-03      DOSAT  4.2527717988     + #> 7483   2063    3M  CC64 2014 2014-02-03       NO23 -4.7105307016     I #> 7484   2063    3M  CC64 2014 2014-02-03      SALIN  3.3432150991  <NA> #> 7485   2063    3M  CC64 2014 2014-02-03        TKN -0.7339691751  <NA> #> 7486   2063    3M  CC64 2014 2014-02-03         TN -0.7256703723     + #> 7487   2063    3M  CC64 2014 2014-02-03         TP -2.4534079827  <NA> #> 7488   2063    3M  CC64 2014 2014-02-03       TURB  0.1823215568  <NA> #> 7489   2063    3M  CC64 2014 2014-03-03      CHLAC  1.3609765531  <NA> #> 7490   2063    3M  CC64 2014 2014-03-03      COLOR  2.3025850930  <NA> #> 7491   2063    3M  CC64 2014 2014-03-03         DO  1.7173950539  <NA> #> 7492   2063    3M  CC64 2014 2014-03-03      DOSAT  4.3201512310     + #> 7493   2063    3M  CC64 2014 2014-03-03       NO23 -5.2983173665     I #> 7494   2063    3M  CC64 2014 2014-03-03      SALIN  3.3307749174  <NA> #> 7495   2063    3M  CC64 2014 2014-03-03        TKN -0.6161861394  <NA> #> 7496   2063    3M  CC64 2014 2014-03-03         TN -0.6088060321     + #> 7497   2063    3M  CC64 2014 2014-03-03         TP -2.3644604967  <NA> #> 7498   2063    3M  CC64 2014 2014-03-03       TURB  0.4054651081  <NA> #> 7499   2063    3M  CC64 2014 2014-04-07      CHLAC  1.2237754316  <NA> #> 7500   2063    3M  CC64 2014 2014-04-07      COLOR  2.6390573296  <NA> #> 7501   2063    3M  CC64 2014 2014-04-07         DO  1.3244189574  <NA> #> 7502   2063    3M  CC64 2014 2014-04-07      DOSAT  3.9759363312     + #> 7503   2063    3M  CC64 2014 2014-04-07       NO23 -4.8283137373     I #> 7504   2063    3M  CC64 2014 2014-04-07      SALIN  3.3246762438  <NA> #> 7505   2063    3M  CC64 2014 2014-04-07        TKN -0.4942963218  <NA> #> 7506   2063    3M  CC64 2014 2014-04-07         TN -0.4877603508     + #> 7507   2063    3M  CC64 2014 2014-04-07         TP -2.3330443005  <NA> #> 7508   2063    3M  CC64 2014 2014-04-07       TURB  0.8329091229  <NA> #> 7509   2063    3M  CC64 2014 2014-05-05      CHLAC  1.3350010667  <NA> #> 7510   2063    3M  CC64 2014 2014-05-05      COLOR  2.6390573296  <NA> #> 7511   2063    3M  CC64 2014 2014-05-05         DO  1.4398351280  <NA> #> 7512   2063    3M  CC64 2014 2014-05-05      DOSAT  4.0910056610     + #> 7513   2063    3M  CC64 2014 2014-05-05       NO23 -4.9618451299     I #> 7514   2063    3M  CC64 2014 2014-05-05      SALIN  3.3039519972  <NA> #> 7515   2063    3M  CC64 2014 2014-05-05        TKN -0.4780358009  <NA> #> 7516   2063    3M  CC64 2014 2014-05-05         TN -0.4716049106     + #> 7517   2063    3M  CC64 2014 2014-05-05         TP -2.2072749132  <NA> #> 7518   2063    3M  CC64 2014 2014-05-05       TURB  0.9555114450  <NA> #> 7519   2063    3M  CC64 2014 2014-06-02      CHLAC  1.3083328197  <NA> #> 7520   2063    3M  CC64 2014 2014-06-02      COLOR  2.3978952728  <NA> #> 7521   2063    3M  CC64 2014 2014-06-02         DO  1.0116009117  <NA> #> 7522   2063    3M  CC64 2014 2014-06-02      DOSAT  3.7111300630     + #> 7523   2063    3M  CC64 2014 2014-06-02       NO23 -5.1159958098     I #> 7524   2063    3M  CC64 2014 2014-06-02      SALIN  3.3347013904  <NA> #> 7525   2063    3M  CC64 2014 2014-06-02        TKN -0.4462871026  <NA> #> 7526   2063    3M  CC64 2014 2014-06-02         TN -0.4400565529     + #> 7527   2063    3M  CC64 2014 2014-06-02         TP -2.0402208285  <NA> #> 7528   2063    3M  CC64 2014 2014-06-02       TURB  0.6931471806  <NA> #> 7529   2063    3M  CC64 2014 2014-07-07      CHLAC  1.7047480922  <NA> #> 7530   2063    3M  CC64 2014 2014-07-07      COLOR  3.1354942159  <NA> #> 7531   2063    3M  CC64 2014 2014-07-07      DOSAT  3.7495040759     + #> 7532   2063    3M  CC64 2014 2014-07-07       NO23 -4.5098600062  <NA> #> 7533   2063    3M  CC64 2014 2014-07-07      SALIN  3.2611687371  <NA> #> 7534   2063    3M  CC64 2014 2014-07-07        TKN -0.1863295782  <NA> #> 7535   2063    3M  CC64 2014 2014-07-07         TN -0.1731636190     + #> 7536   2063    3M  CC64 2014 2014-07-07         TP -2.0402208285  <NA> #> 7537   2063    3M  CC64 2014 2014-07-07       TURB  0.6931471806  <NA> #> 7538   2063    3M  CC64 2014 2014-08-04      CHLAC  2.4849066498  <NA> #> 7539   2063    3M  CC64 2014 2014-08-04      COLOR  3.7612001157  <NA> #> 7540   2063    3M  CC64 2014 2014-08-04         DO  0.9932517730  <NA> #> 7541   2063    3M  CC64 2014 2014-08-04      DOSAT  3.6863763239     + #> 7542   2063    3M  CC64 2014 2014-08-04       NO23 -4.8283137373     I #> 7543   2063    3M  CC64 2014 2014-08-04      SALIN  2.9439125248  <NA> #> 7544   2063    3M  CC64 2014 2014-08-04        TKN -0.1743533871  <NA> #> 7545   2063    3M  CC64 2014 2014-08-04         TN -0.1696027844     + #> 7546   2063    3M  CC64 2014 2014-08-04         TP -1.6607312068  <NA> #> 7547   2063    3M  CC64 2014 2014-08-04       TURB  1.0296194172  <NA> #> 7548   2063    3M  CC64 2014 2014-09-08      CHLAC  0.9162907319  <NA> #> 7549   2063    3M  CC64 2014 2014-09-08      COLOR  3.4011973817  <NA> #> 7550   2063    3M  CC64 2014 2014-09-08         DO  0.7178397932  <NA> #> 7551   2063    3M  CC64 2014 2014-09-08      DOSAT  3.3911470458     + #> 7552   2063    3M  CC64 2014 2014-09-08       NO23 -4.1351665567  <NA> #> 7553   2063    3M  CC64 2014 2014-09-08      SALIN  2.9242362718  <NA> #> 7554   2063    3M  CC64 2014 2014-09-08        TKN -0.2231435513  <NA> #> 7555   2063    3M  CC64 2014 2014-09-08         TN -0.2033409240     + #> 7556   2063    3M  CC64 2014 2014-09-08         TP -1.9661128564  <NA> #> 7557   2063    3M  CC64 2014 2014-09-08       TURB -0.0512932944  <NA> #> 7558   2063    3M  CC64 2014 2014-10-06      CHLAC  1.5040773968  <NA> #> 7559   2063    3M  CC64 2014 2014-10-06      COLOR  4.5951198501  <NA> #> 7560   2063    3M  CC64 2014 2014-10-06         DO  0.9162907319  <NA> #> 7561   2063    3M  CC64 2014 2014-10-06      DOSAT  3.4781584228     + #> 7562   2063    3M  CC64 2014 2014-10-06       NO23 -3.3813947544  <NA> #> 7563   2063    3M  CC64 2014 2014-10-06      SALIN  2.0819384219  <NA> #> 7564   2063    3M  CC64 2014 2014-10-06        TKN -0.0408219945  <NA> #> 7565   2063    3M  CC64 2014 2014-10-06         TN -0.0060180723     + #> 7566   2063    3M  CC64 2014 2014-10-06         TP -1.8325814637  <NA> #> 7567   2063    3M  CC64 2014 2014-10-06       TURB  0.4054651081  <NA> #> 7568   2063    3M  CC64 2014 2014-11-03      CHLAC  0.9162907319  <NA> #> 7569   2063    3M  CC64 2014 2014-11-03      COLOR  3.7841896339  <NA> #> 7570   2063    3M  CC64 2014 2014-11-03         DO  1.5686159179  <NA> #> 7571   2063    3M  CC64 2014 2014-11-03      DOSAT  4.0826093060     + #> 7572   2063    3M  CC64 2014 2014-11-03       NO23 -3.5065578973  <NA> #> 7573   2063    3M  CC64 2014 2014-11-03      SALIN  2.9423314968  <NA> #> 7574   2063    3M  CC64 2014 2014-11-03        TKN -0.3285040670  <NA> #> 7575   2063    3M  CC64 2014 2014-11-03         TN -0.2876820725     + #> 7576   2063    3M  CC64 2014 2014-11-03         TP -1.9661128564  <NA> #> 7577   2063    3M  CC64 2014 2014-11-03       TURB  0.5306282511  <NA> #> 7578   2063    3M  CC64 2014 2014-12-01      CHLAC  0.4700036292     I #> 7579   2063    3M  CC64 2014 2014-12-01      COLOR  3.4011973817  <NA> #> 7580   2063    3M  CC64 2014 2014-12-01         DO  1.6956156087  <NA> #> 7581   2063    3M  CC64 2014 2014-12-01      DOSAT  4.1941898972     + #> 7582   2063    3M  CC64 2014 2014-12-01       NO23 -2.7181005370  <NA> #> 7583   2063    3M  CC64 2014 2014-12-01      SALIN  3.0449985149  <NA> #> 7584   2063    3M  CC64 2014 2014-12-01        TKN -0.3566749439  <NA> #> 7585   2063    3M  CC64 2014 2014-12-01         TN -0.2665731092     + #> 7586   2063    3M  CC64 2014 2014-12-01         TP -2.3025850930  <NA> #> 7587   2063    3M  CC64 2014 2014-12-01       TURB  0.4700036292  <NA> #> 7588   2063    3M  CC64 2015 2015-01-05      CHLAC  0.7884573604     A #> 7589   2063    3M  CC64 2015 2015-01-05      COLOR  2.9444389792  <NA> #> 7590   2063    3M  CC64 2015 2015-01-05       NO23 -2.8824035882  <NA> #> 7591   2063    3M  CC64 2015 2015-01-05      SALIN  3.2592497190  <NA> #> 7592   2063    3M  CC64 2015 2015-01-05        TKN -0.5621189182  <NA> #> 7593   2063    3M  CC64 2015 2015-01-05         TN -0.4684049079     + #> 7594   2063    3M  CC64 2015 2015-01-05         TP -2.3025850930  <NA> #> 7595   2063    3M  CC64 2015 2015-01-05       TURB  0.6931471806  <NA> #> 7596   2063    3M  CC64 2015 2015-02-02      CHLAC  0.2623642645     I #> 7597   2063    3M  CC64 2015 2015-02-02      COLOR  2.3025850930  <NA> #> 7598   2063    3M  CC64 2015 2015-02-02      DOSAT  4.3932138241     + #> 7599   2063    3M  CC64 2015 2015-02-02       NO23 -4.3428059215  <NA> #> 7600   2063    3M  CC64 2015 2015-02-02      SALIN  3.3214324132  <NA> #> 7601   2063    3M  CC64 2015 2015-02-02        TKN -0.9942522733     I #> 7602   2063    3M  CC64 2015 2015-02-02         TN -1.7544636845     + #> 7603   2063    3M  CC64 2015 2015-02-02         TP -2.4534079827  <NA> #> 7604   2063    3M  CC64 2015 2015-02-02       TURB  0.7884573604     A #> 7605   2063    3M  CC64 2015 2015-03-02      CHLAC  1.1631508098     A #> 7606   2063    3M  CC64 2015 2015-03-02      COLOR  2.8903717579  <NA> #> 7607   2063    3M  CC64 2015 2015-03-02         DO  1.9430489168  <NA> #> 7608   2063    3M  CC64 2015 2015-03-02      DOSAT  4.5152454785     + #> 7609   2063    3M  CC64 2015 2015-03-02       NO23 -3.1941832123  <NA> #> 7610   2063    3M  CC64 2015 2015-03-02      SALIN  3.2136622578  <NA> #> 7611   2063    3M  CC64 2015 2015-03-02        TKN -0.4942963218  <NA> #> 7612   2063    3M  CC64 2015 2015-03-02         TN -0.4292456368     + #> 7613   2063    3M  CC64 2015 2015-03-02         TP -2.2072749132  <NA> #> 7614   2063    3M  CC64 2015 2015-03-02       TURB  0.8754687374  <NA> #> 7615   2063    3M  CC64 2015 2015-04-06      CHLAC  0.9162907319  <NA> #> 7616   2063    3M  CC64 2015 2015-04-06      COLOR  2.9957322736  <NA> #> 7617   2063    3M  CC64 2015 2015-04-06         DO  1.3558351536  <NA> #> 7618   2063    3M  CC64 2015 2015-04-06      DOSAT  4.0036901940     + #> 7619   2063    3M  CC64 2015 2015-04-06       NO23 -4.6051701860  <NA> #> 7620   2063    3M  CC64 2015 2015-04-06      SALIN  3.2268439945  <NA> #> 7621   2063    3M  CC64 2015 2015-04-06        TKN -0.4462871026  <NA> #> 7622   2063    3M  CC64 2015 2015-04-06         TN 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3M  CC64 2015 2015-06-01         DO  1.0647107370  <NA> #> 7637   2063    3M  CC64 2015 2015-06-01      DOSAT  3.7773481021     + #> 7638   2063    3M  CC64 2015 2015-06-01       NO23 -4.6051701860     I #> 7639   2063    3M  CC64 2015 2015-06-01      SALIN  3.3214324132  <NA> #> 7640   2063    3M  CC64 2015 2015-06-01        TKN -0.5621189182  <NA> #> 7641   2063    3M  CC64 2015 2015-06-01         TN -0.5551258827     + #> 7642   2063    3M  CC64 2015 2015-06-01         TP -2.3025850930  <NA> #> 7643   2063    3M  CC64 2015 2015-06-01       TURB  0.4700036292  <NA> #> 7644   2063    3M  CC64 2015 2015-08-03      CHLAC  2.2407096893  <NA> #> 7645   2063    3M  CC64 2015 2015-08-03      COLOR  4.1588830834  <NA> #> 7646   2063    3M  CC64 2015 2015-08-03         DO  0.7654678421  <NA> #> 7647   2063    3M  CC64 2015 2015-08-03      DOSAT  3.4045251718     + #> 7648   2063    3M  CC64 2015 2015-08-03       NO23 -4.6051701860     I #> 7649   2063    3M  CC64 2015 2015-08-03      SALIN  2.8039662579  <NA> #> 7650   2063    3M  CC64 2015 2015-08-03        TKN -0.0512932944  <NA> #> 7651   2063    3M  CC64 2015 2015-08-03         TN -0.0470916075     + #> 7652   2063    3M  CC64 2015 2015-08-03         TP -2.0402208285  <NA> #> 7653   2063    3M  CC64 2015 2015-08-03       TURB  0.5877866649  <NA> #> 7654   2063    3M  CC64 2015 2015-09-08      CHLAC  1.3609765531  <NA> #> 7655   2063    3M  CC64 2015 2015-09-08      COLOR  4.5432947823  <NA> #> 7656   2063    3M  CC64 2015 2015-09-08       NO23 -3.6888794541  <NA> #> 7657   2063    3M  CC64 2015 2015-09-08      SALIN  1.3584091576  <NA> #> 7658   2063    3M  CC64 2015 2015-09-08        TKN -0.1743533871  <NA> #> 7659   2063    3M  CC64 2015 2015-09-08         TN -0.1450257721     + #> 7660   2063    3M  CC64 2015 2015-09-08         TP -2.2072749132  <NA> #> 7661   2063    3M  CC64 2015 2015-09-08       TURB  0.5306282511  <NA> #> 7662   2063    3M  CC64 2015 2015-10-05      CHLAC  1.5892352051  <NA> #> 7663   2063    3M  CC64 2015 2015-10-05      COLOR  4.5643481915  <NA> #> 7664   2063    3M  CC64 2015 2015-10-05         DO  1.1085626195  <NA> #> 7665   2063    3M  CC64 2015 2015-10-05      DOSAT  3.6888794541     + #> 7666   2063    3M  CC64 2015 2015-10-05       NO23 -3.3524072175  <NA> #> 7667   2063    3M  CC64 2015 2015-10-05      SALIN  2.4069451083  <NA> #> 7668   2063    3M  CC64 2015 2015-10-05        TKN -0.1984509387  <NA> #> 7669   2063    3M  CC64 2015 2015-10-05         TN -0.1566538100     + #> 7670   2063    3M  CC64 2015 2015-10-05         TP -1.5606477483  <NA> #> 7671   2063    3M  CC64 2015 2015-10-05       TURB  0.3364722366     A #> 7672   2063    3M  CC64 2015 2015-12-07      CHLAC  0.9555114450  <NA> #> 7673   2063    3M  CC64 2015 2015-12-07      COLOR  3.4965075615  <NA> #> 7674   2063    3M  CC64 2015 2015-12-07         DO  1.1314021115  <NA> #> 7675   2063    3M  CC64 2015 2015-12-07      DOSAT  3.6988297850     + #> 7676   2063    3M  CC64 2015 2015-12-07       NO23 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3M  CC64 2016 2016-01-04         TP -2.0402208285  <NA> #> 7691   2063    3M  CC64 2016 2016-01-04       TURB  0.9162907319  <NA> #> 7692   2063    3M  CC64 2016 2016-02-01      COLOR  4.1896547420     A #> 7693   2063    3M  CC64 2016 2016-02-01      DOSAT  4.5053498507     + #> 7694   2063    3M  CC64 2016 2016-02-01       NO23 -4.1997050779  <NA> #> 7695   2063    3M  CC64 2016 2016-02-01      SALIN  1.9810014689  <NA> #> 7696   2063    3M  CC64 2016 2016-02-01        TKN -0.5447271754  <NA> #> 7697   2063    3M  CC64 2016 2016-02-01         TN -0.5191938734     + #> 7698   2063    3M  CC64 2016 2016-02-01         TP -2.8473122684  <NA> #> 7699   2063    3M  CC64 2016 2016-02-01       TURB  0.5877866649  <NA> #> 7700   2063    3M  CC64 2016 2016-03-07      CHLAC  0.6418538862     I #> 7701   2063    3M  CC64 2016 2016-03-07      COLOR  3.7841896339  <NA> #> 7702   2063    3M  CC64 2016 2016-03-07       NO23 -4.1997050779  <NA> #> 7703   2063    3M  CC64 2016 2016-03-07      SALIN  2.6159349122  <NA> #> 7704   2063    3M  CC64 2016 2016-03-07        TKN -0.2231435513  <NA> #> 7705   2063    3M  CC64 2016 2016-03-07         TN -0.2045671657     + #> 7706   2063    3M  CC64 2016 2016-03-07         TP -2.3538783874  <NA> #> 7707   2063    3M  CC64 2016 2016-03-07       TURB  0.4700036292  <NA> #> 7708   2063    3M  CC64 2016 2016-04-04      CHLAC  1.2237754316  <NA> #> 7709   2063    3M  CC64 2016 2016-04-04      COLOR  3.3322045102     A #> 7710   2063    3M  CC64 2016 2016-04-04         DO  1.6094379124  <NA> #> 7711   2063    3M  CC64 2016 2016-04-04      DOSAT  4.2061840440     + #> 7712   2063    3M  CC64 2016 2016-04-04       NO23 -3.7297014486  <NA> #> 7713   2063    3M  CC64 2016 2016-04-04      SALIN  2.9236990707  <NA> #> 7714   2063    3M  CC64 2016 2016-04-04         TN -0.3092462504     + #> 7715   2063    3M  CC64 2016 2016-04-04         TP -2.2072749132  <NA> #> 7716   2063    3M  CC64 2016 2016-04-04       TURB  0.7419373447  <NA> #> 7717   2063    3M  CC64 2016 2016-05-02      CHLAC  0.8754687374  <NA> #> 7718   2063    3M  CC64 2016 2016-05-02      COLOR  3.1780538303  <NA> #> 7719   2063    3M  CC64 2016 2016-05-02         DO  1.1631508098  <NA> #> 7720   2063    3M  CC64 2016 2016-05-02      DOSAT  3.8394523126     + #> 7721   2063    3M  CC64 2016 2016-05-02       NO23 -4.5098600062  <NA> #> 7722   2063    3M  CC64 2016 2016-05-02      SALIN  3.1428583384  <NA> #> 7723   2063    3M  CC64 2016 2016-05-02        TKN -0.5276327421  <NA> #> 7724   2063    3M  CC64 2016 2016-05-02         TN -0.5091603444     + #> 7725   2063    3M  CC64 2016 2016-05-02         TP -2.3025850930  <NA> #> 7726   2063    3M  CC64 2016 2016-05-02       TURB  0.6931471806  <NA> #> 7727   2063    3M  CC64 2016 2016-06-06       NO23 -4.6051701860     I #> 7728   2063    3M  CC64 2016 2016-06-06      SALIN  3.2120525995  <NA> #> 7729   2063    3M  CC64 2016 2016-06-06        TKN -0.4462871026  <NA> #> 7730   2063    3M  CC64 2016 2016-06-06         TN 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3M  CC64 2016 2016-08-01         DO  0.9669838462  <NA> #> 7745   2063    3M  CC64 2016 2016-08-01      DOSAT  3.6428355156     + #> 7746   2063    3M  CC64 2016 2016-08-01       NO23 -4.3428059215  <NA> #> 7747   2063    3M  CC64 2016 2016-08-01      SALIN  2.6232182656  <NA> #> 7748   2063    3M  CC64 2016 2016-08-01        TKN -0.1625189295  <NA> #> 7749   2063    3M  CC64 2016 2016-08-01         TN -0.1473405879     + #> 7750   2063    3M  CC64 2016 2016-08-01         TP -1.9661128564  <NA> #> 7751   2063    3M  CC64 2016 2016-08-01       TURB  0.3364722366  <NA> #> 7752   2063    3M  CC64 2016 2016-10-03      CHLAC  1.3350010667  <NA> #> 7753   2063    3M  CC64 2016 2016-10-03      COLOR  3.9702919136  <NA> #> 7754   2063    3M  CC64 2016 2016-10-03         DO  0.7178397932  <NA> #> 7755   2063    3M  CC64 2016 2016-10-03      DOSAT  3.3568971228     + #> 7756   2063    3M  CC64 2016 2016-10-03       NO23 -4.1351665567  <NA> #> 7757   2063    3M  CC64 2016 2016-10-03      SALIN  2.5892666651  <NA> #> 7758   2063    3M  CC64 2016 2016-10-03        TKN -0.4620354596  <NA> #> 7759   2063    3M  CC64 2016 2016-10-03         TN -0.4369557752     + #> 7760   2063    3M  CC64 2016 2016-10-03         TP -1.8325814637  <NA> #> 7761   2063    3M  CC64 2016 2016-10-03       TURB  0.1823215568  <NA> #> 7762   2063    3M  CC64 2016 2016-11-07      CHLAC  0.8754687374  <NA> #> 7763   2063    3M  CC64 2016 2016-11-07      COLOR  2.8332133441     A #> 7764   2063    3M  CC64 2016 2016-11-07         DO  1.3402504226  <NA> #> 7765   2063    3M  CC64 2016 2016-11-07      DOSAT  3.9473901493     + #> 7766   2063    3M  CC64 2016 2016-11-07       NO23 -4.7105307016     I #> 7767   2063    3M  CC64 2016 2016-11-07      SALIN  3.3178157727  <NA> #> 7768   2063    3M  CC64 2016 2016-11-07        TKN -0.4155154440  <NA> #> 7769   2063    3M  CC64 2016 2016-11-07         TN -0.4094731295     + #> 7770   2063    3M  CC64 2016 2016-11-07         TP -2.3330443005  <NA> #> 7771   2063    3M  CC64 2016 2016-11-07       TURB  0.6418538862  <NA> #> 7772   2063    3M  CC64 2016 2016-12-05      CHLAC  2.6390573296  <NA> #> 7773   2063    3M  CC64 2016 2016-12-05      COLOR  2.7080502011  <NA> #> 7774   2063    3M  CC64 2016 2016-12-05         DO  1.6094379124  <NA> #> 7775   2063    3M  CC64 2016 2016-12-05      DOSAT  4.2165621949     + #> 7776   2063    3M  CC64 2016 2016-12-05       NO23 -5.5214609179     U #> 7777   2063    3M  CC64 2016 2016-12-05      SALIN  3.3792925463  <NA> #> 7778   2063    3M  CC64 2016 2016-12-05        TKN -0.3285040670  <NA> #> 7779   2063    3M  CC64 2016 2016-12-05         TN -0.3257301401     + #> 7780   2063    3M  CC64 2016 2016-12-05         TP -1.7147984281  <NA> #> 7781   2063    3M  CC64 2016 2016-12-05       TURB  0.8329091229  <NA> #> 7782   2063    3M  CC64 2017 2017-01-03      CHLAC  0.7419373447  <NA> #> 7783   2063    3M  CC64 2017 2017-01-03      COLOR  2.1860512767  <NA> #> 7784   2063    3M  CC64 2017 2017-01-03         DO  1.6292405397  <NA> #> 7785   2063    3M  CC64 2017 2017-01-03      DOSAT  4.2370008626     + #> 7786   2063    3M  CC64 2017 2017-01-03       NO23 -5.5214609179     U #> 7787   2063    3M  CC64 2017 2017-01-03      SALIN  3.3911470458  <NA> #> 7788   2063    3M  CC64 2017 2017-01-03        TKN -0.6733445533  <NA> #> 7789   2063    3M  CC64 2017 2017-01-03         TN -0.6694306539     + #> 7790   2063    3M  CC64 2017 2017-01-03         TP -2.3751557858  <NA> #> 7791   2063    3M  CC64 2017 2017-01-03       TURB  0.4700036292  <NA> #> 7792   2063    3M  CC64 2017 2017-02-06      CHLAC  1.3083328197  <NA> #> 7793   2063    3M  CC64 2017 2017-02-06      COLOR  2.2300144002  <NA> #> 7794   2063    3M  CC64 2017 2017-02-06         DO  1.6770965609  <NA> #> 7795   2063    3M  CC64 2017 2017-02-06      DOSAT  4.2654928184     + #> 7796   2063    3M  CC64 2017 2017-02-06       NO23 -3.3242363405  <NA> #> 7797   2063    3M  CC64 2017 2017-02-06      SALIN  3.3965197921  <NA> #> 7798   2063    3M  CC64 2017 2017-02-06        TKN -0.3566749439  <NA> #> 7799   2063    3M  CC64 2017 2017-02-06         TN -0.3065251603     + #> 7800   2063    3M  CC64 2017 2017-02-06         TP -2.4418471603  <NA> #> 7801   2063    3M  CC64 2017 2017-02-06       TURB  0.9555114450  <NA> #> 7802   2063    3M  CC64 2017 2017-03-06      CHLAC  1.2237754316  <NA> #> 7803   2063    3M  CC64 2017 2017-03-06      COLOR  1.7917594692  <NA> #> 7804   2063    3M  CC64 2017 2017-03-06         DO  1.6770965609  <NA> #> 7805   2063    3M  CC64 2017 2017-03-06      DOSAT  4.2598590007     + #> 7806   2063    3M  CC64 2017 2017-03-06       NO23 -5.1159958098     I #> 7807   2063    3M  CC64 2017 2017-03-06      SALIN  3.4124669739  <NA> #> 7808   2063    3M  CC64 2017 2017-03-06        TKN -0.5798184953  <NA> #> 7809   2063    3M  CC64 2017 2017-03-06         TN -0.5727010275     + #> 7810   2063    3M  CC64 2017 2017-03-06         TP -2.5257286443  <NA> #> 7811   2063    3M  CC64 2017 2017-03-06       TURB  0.9932517730  <NA> #> 7812   2063    3M  CC64 2017 2017-04-03      CHLAC  1.4586150227  <NA> #> 7813   2063    3M  CC64 2017 2017-04-03      COLOR  2.3978952728  <NA> #> 7814   2063    3M  CC64 2017 2017-04-03         DO  1.3635373740  <NA> #> 7815   2063    3M  CC64 2017 2017-04-03      DOSAT  4.0638853547     + #> 7816   2063    3M  CC64 2017 2017-04-03       NO23 -4.9618451299     I #> 7817   2063    3M  CC64 2017 2017-04-03      SALIN  3.5115454388  <NA> #> 7818   2063    3M  CC64 2017 2017-04-03        TKN -0.3424903089  <NA> #> 7819   2063    3M  CC64 2017 2017-04-03         TN -0.3368723166     + #> 7820   2063    3M  CC64 2017 2017-04-03         TP -2.4769384801  <NA> #> 7821   2063    3M  CC64 2017 2017-04-03       TURB  0.8754687374  <NA> #> 7822   2063    3M  CC64 2017 2017-05-01      CHLAC  1.0296194172  <NA> #> 7823   2063    3M  CC64 2017 2017-05-01      COLOR  2.6390573296  <NA> #> 7824   2063    3M  CC64 2017 2017-05-01         DO  1.3480731483  <NA> #> 7825   2063    3M  CC64 2017 2017-05-01      DOSAT  4.0604430105     + #> 7826   2063    3M  CC64 2017 2017-05-01       NO23 -5.5214609179     U #> 7827   2063    3M  CC64 2017 2017-05-01      SALIN  3.5377658244  <NA> #> 7828   2063    3M  CC64 2017 2017-05-01        TKN -0.2876820725  <NA> #> 7829   2063    3M  CC64 2017 2017-05-01         TN -0.2850189550     + #> 7830   2063    3M  CC64 2017 2017-05-01         TP -2.6736487744  <NA> #> 7831   2063    3M  CC64 2017 2017-05-01       TURB  0.7419373447  <NA> #> 7832   2063    3M  CC64 2017 2017-06-05      CHLAC  1.3862943611     A #> 7833   2063    3M  CC64 2017 2017-06-05      COLOR  2.7080502011  <NA> #> 7834   2063    3M  CC64 2017 2017-06-05         DO  2.1294214740  <NA> #> 7835   2063    3M  CC64 2017 2017-06-05      DOSAT  4.8835592115     + #> 7836   2063    3M  CC64 2017 2017-06-05       NO23 -4.5098600062  <NA> #> 7837   2063    3M  CC64 2017 2017-06-05      SALIN  3.5322256441  <NA> #> 7838   2063    3M  CC64 2017 2017-06-05        TKN 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3M  CC64 2017 2017-08-07      CHLAC  1.5892352051  <NA> #> 7853   2063    3M  CC64 2017 2017-08-07      COLOR  4.5747109785     A #> 7854   2063    3M  CC64 2017 2017-08-07         DO  0.4121096508  <NA> #> 7855   2063    3M  CC64 2017 2017-08-07      DOSAT  3.0349529867     + #> 7856   2063    3M  CC64 2017 2017-08-07       NO23 -3.7297014486  <NA> #> 7857   2063    3M  CC64 2017 2017-08-07      SALIN  2.0693912058  <NA> #> 7858   2063    3M  CC64 2017 2017-08-07        TKN -0.0202027073  <NA> #> 7859   2063    3M  CC64 2017 2017-08-07         TN  0.0039920213     + #> 7860   2063    3M  CC64 2017 2017-08-07         TP -1.6607312068  <NA> #> 7861   2063    3M  CC64 2017 2017-08-07       TURB  0.6931471806  <NA> #> 7862   2063    3M  CC64 2017 2017-09-05      CHLAC  1.6094379124  <NA> #> 7863   2063    3M  CC64 2017 2017-09-05      COLOR  4.7874917428  <NA> #> 7864   2063    3M  CC64 2017 2017-09-05         DO  0.8586616190  <NA> #> 7865   2063    3M  CC64 2017 2017-09-05      DOSAT  3.4404180948     + #> 7866   2063    3M  CC64 2017 2017-09-05       NO23 -3.0159349809  <NA> #> 7867   2063    3M  CC64 2017 2017-09-05      SALIN  0.9001613499  <NA> #> 7868   2063    3M  CC64 2017 2017-09-05        TKN -0.1508228897  <NA> #> 7869   2063    3M  CC64 2017 2017-09-05         TN -0.0954101848     + #> 7870   2063    3M  CC64 2017 2017-09-05         TP -2.0402208285  <NA> #> 7871   2063    3M  CC64 2017 2017-09-05       TURB  0.5877866649  <NA> #> 7872   2063    3M  CC64 2017 2017-10-02      CHLAC  1.3083328197  <NA> #> 7873   2063    3M  CC64 2017 2017-10-02      COLOR  4.4998096703  <NA> #> 7874   2063    3M  CC64 2017 2017-10-02       NO23 -3.1465551633  <NA> #> 7875   2063    3M  CC64 2017 2017-10-02        TKN -0.9675840263  <NA> #> 7876   2063    3M  CC64 2017 2017-10-02         TN -0.8603830999     + #> 7877   2063    3M  CC64 2017 2017-10-02         TP -1.6094379124  <NA> #> 7878   2063    3M  CC64 2017 2017-10-02       TURB  0.3364722366  <NA> #> 7879   2063    3M  CC64 2017 2017-11-06      CHLAC  0.7419373447  <NA> #> 7880   2063    3M  CC64 2017 2017-11-06      COLOR  3.5835189385  <NA> #> 7881   2063    3M  CC64 2017 2017-11-06         DO  2.0014800002  <NA> #> 7882   2063    3M  CC64 2017 2017-11-06      DOSAT  4.5890408041     + #> 7883   2063    3M  CC64 2017 2017-11-06       NO23 -3.4420193762  <NA> #> 7884   2063    3M  CC64 2017 2017-11-06      SALIN  3.0864866368  <NA> #> 7885   2063    3M  CC64 2017 2017-11-06        TKN -0.5798184953  <NA> #> 7886   2063    3M  CC64 2017 2017-11-06         TN -0.5242486441     + #> 7887   2063    3M  CC64 2017 2017-11-06         TP -1.8971199849  <NA> #> 7888   2063    3M  CC64 2017 2017-11-06       TURB  0.3364722366  <NA> #> 7889   2063    3M  CC64 2017 2017-12-04      CHLAC  0.9162907319  <NA> #> 7890   2063    3M  CC64 2017 2017-12-04      COLOR  3.1780538303  <NA> #> 7891   2063    3M  CC64 2017 2017-12-04         DO  1.5644405465  <NA> #> 7892   2063    3M  CC64 2017 2017-12-04      DOSAT  4.1287459889  <NA> #> 7893   2063    3M  CC64 2017 2017-12-04       NO23 -4.5098600062  <NA> #> 7894   2063    3M  CC64 2017 2017-12-04      SALIN  3.3403852423  <NA> #> 7895   2063    3M  CC64 2017 2017-12-04        TKN -0.5276327421  <NA> #> 7896   2063    3M  CC64 2017 2017-12-04         TN -0.5091603444     + #> 7897   2063    3M  CC64 2017 2017-12-04         TP -2.2072749132  <NA> #> 7898   2063    3M  CC64 2017 2017-12-04       TURB  0.3364722366  <NA> #> 7899   2063    3M  CC64 2018 2018-01-02      CHLAC  2.7725887222  <NA> #> 7900   2063    3M  CC64 2018 2018-01-02      COLOR  3.0910424534  <NA> #> 7901   2063    3M  CC64 2018 2018-01-02      DOSAT  4.0360089852     + #> 7902   2063    3M  CC64 2018 2018-01-02       NO23 -5.5214609179     U #> 7903   2063    3M  CC64 2018 2018-01-02      SALIN  3.2657594108  <NA> #> 7904   2063    3M  CC64 2018 2018-01-02        TKN -0.3147107448  <NA> #> 7905   2063    3M  CC64 2018 2018-01-02         TN -0.3119747650     + #> 7906   2063    3M  CC64 2018 2018-01-02         TP -1.6607312068  <NA> #> 7907   2063    3M  CC64 2018 2018-01-02       TURB  2.3978952728  <NA> #> 7908   2063    3M  CC64 2018 2018-03-05      CHLAC  0.5306282511     I #> 7909   2063    3M  CC64 2018 2018-03-05      COLOR  2.6390573296  <NA> #> 7910   2063    3M  CC64 2018 2018-03-05      DOSAT  4.2416144810  <NA> #> 7911   2063    3M  CC64 2018 2018-03-05       NO23 -5.5214609179     I #> 7912   2063    3M  CC64 2018 2018-03-05      SALIN  3.3467411959  <NA> #> 7913   2063    3M  CC64 2018 2018-03-05        TKN -0.5621189182  <NA> #> 7914   2063    3M  CC64 2018 2018-03-05         TN -0.5551258827     + #> 7915   2063    3M  CC64 2018 2018-03-05         TP -2.1202635362  <NA> #> 7916   2063    3M  CC64 2018 2018-03-05       TURB  0.4700036292  <NA> #> 7917   2063    3M  CC64 2018 2018-04-02      CHLAC  0.7419373447  <NA> #> 7918   2063    3M  CC64 2018 2018-04-02      COLOR  2.3978952728  <NA> #> 7919   2063    3M  CC64 2018 2018-04-02         DO  1.5040773968  <NA> #> 7920   2063    3M  CC64 2018 2018-04-02      DOSAT  3.4307561839  <NA> #> 7921   2063    3M  CC64 2018 2018-04-02       NO23 -4.9618451299     I #> 7922   2063    3M  CC64 2018 2018-04-02      SALIN  3.4330189940  <NA> #> 7923   2063    3M  CC64 2018 2018-04-02        TKN -0.6539264674  <NA> #> 7924   2063    3M  CC64 2018 2018-04-02         TN -0.6462635947     + #> 7925   2063    3M  CC64 2018 2018-04-02         TP -2.2072749132  <NA> #> 7926   2063    3M  CC64 2018 2018-04-02       TURB  0.7884573604  <NA> #> 7927   2063    3M  CC64 2018 2018-05-07      CHLAC  1.4350845253  <NA> #> 7928   2063    3M  CC64 2018 2018-05-07      COLOR  2.5649493575  <NA> #> 7929   2063    3M  CC64 2018 2018-05-07         DO  1.3962446920  <NA> #> 7930   2063    3M  CC64 2018 2018-05-07      DOSAT  4.0842942264  <NA> #> 7931   2063    3M  CC64 2018 2018-05-07       NO23 -5.1159958098     I #> 7932   2063    3M  CC64 2018 2018-05-07      SALIN  3.4388142452  <NA> #> 7933   2063    3M  CC64 2018 2018-05-07        TKN -0.3424903089  <NA> #> 7934   2063    3M  CC64 2018 2018-05-07         TN -0.3368723166     + #> 7935   2063    3M  CC64 2018 2018-05-07         TP -2.0402208285  <NA> #> 7936   2063    3M  CC64 2018 2018-05-07       TURB  1.0986122887  <NA> #> 7937   2063    3M  CC64 2018 2018-07-09      CHLAC  0.9555114450  <NA> #> 7938   2063    3M  CC64 2018 2018-07-09      COLOR  4.5747109785  <NA> #> 7939   2063    3M  CC64 2018 2018-07-09         DO  0.6312717768  <NA> #> 7940   2063    3M  CC64 2018 2018-07-09      DOSAT  3.2308043957  <NA> #> 7941   2063    3M  CC64 2018 2018-07-09       NO23 -3.6119184130  <NA> #> 7942   2063    3M  CC64 2018 2018-07-09      SALIN  1.8640801308  <NA> #> 7943   2063    3M  CC64 2018 2018-07-09        TKN  0.0000000000  <NA> #> 7944   2063    3M  CC64 2018 2018-07-09         TN  0.0266419309     + #> 7945   2063    3M  CC64 2018 2018-07-09         TP -2.3025850930  <NA> #> 7946   2063    3M  CC64 2018 2018-07-09       TURB  0.1823215568  <NA> #> 7947   2063    3M  CC64 2018 2018-08-06      CHLAC  1.0986122887  <NA> #> 7948   2063    3M  CC64 2018 2018-08-06      COLOR  4.5951198501  <NA> #> 7949   2063    3M  CC64 2018 2018-08-06         DO  0.8796267475  <NA> #> 7950   2063    3M  CC64 2018 2018-08-06      DOSAT  3.4339872045  <NA> #> 7951   2063    3M  CC64 2018 2018-08-06       NO23 -3.4737680745  <NA> #> 7952   2063    3M  CC64 2018 2018-08-06      SALIN  1.6448050563  <NA> #> 7953   2063    3M  CC64 2018 2018-08-06        TKN -0.1508228897  <NA> #> 7954   2063    3M  CC64 2018 2018-08-06         TN -0.1154108515     + #> 7955   2063    3M  CC64 2018 2018-08-06         TP -2.3227878003  <NA> #> 7956   2063    3M  CC64 2018 2018-08-06       TURB  0.5877866649  <NA> #> 7957   2063    3M  CC64 2019 2019-02-04      CHLAC  1.1314021115  <NA> #> 7958   2063    3M  CC64 2019 2019-02-04      COLOR  3.0910424534  <NA> #> 7959   2063    3M  CC64 2019 2019-02-04         DO  1.8764069433  <NA> #> 7960   2063    3M  CC64 2019 2019-02-04      DOSAT  4.4200447019  <NA> #> 7961   2063    3M  CC64 2019 2019-02-04       NO23 -4.8283137373     I #> 7962   2063    3M  CC64 2019 2019-02-04      SALIN  3.0928589843  <NA> #> 7963   2063    3M  CC64 2019 2019-02-04        TKN -0.7765287895  <NA> #> 7964   2063    3M  CC64 2019 2019-02-04         TN -0.7678707268     + #> 7965   2063    3M  CC64 2019 2019-02-04         TP -2.3025850930  <NA> #> 7966   2063    3M  CC64 2019 2019-02-04       TURB  0.6418538862  <NA> #> 7967   2063    3M  CC64 2019 2019-03-04      CHLAC  0.8329091229  <NA> #> 7968   2063    3M  CC64 2019 2019-03-04      COLOR  3.1354942159  <NA> #> 7969   2063    3M  CC64 2019 2019-03-04         DO  1.6014057407  <NA> #> 7970   2063    3M  CC64 2019 2019-03-04      DOSAT  4.2297491992  <NA> #> 7971   2063    3M  CC64 2019 2019-03-04       NO23 -4.8283137373     I #> 7972   2063    3M  CC64 2019 2019-03-04      SALIN  2.9992261628  <NA> #> 7973   2063    3M  CC64 2019 2019-03-04        TKN -0.5798184953  <NA> #> 7974   2063    3M  CC64 2019 2019-03-04         TN -0.5727010275     + #> 7975   2063    3M  CC64 2019 2019-03-04         TP -2.3025850930  <NA> #> 7976   2063    3M  CC64 2019 2019-03-04       TURB  0.5306282511  <NA> #> 7977   2063    3M  CC64 2019 2019-04-01      CHLAC  0.4700036292     I #> 7978   2063    3M  CC64 2019 2019-04-01      COLOR  2.7725887222  <NA> #> 7979   2063    3M  CC64 2019 2019-04-01         DO  1.3962446920  <NA> #> 7980   2063    3M  CC64 2019 2019-04-01      DOSAT  3.9889840466  <NA> #> 7981   2063    3M  CC64 2019 2019-04-01       NO23 -4.5098600062  <NA> #> 7982   2063    3M  CC64 2019 2019-04-01      SALIN  3.1210424645  <NA> #> 7983   2063    3M  CC64 2019 2019-04-01        TKN -0.5276327421  <NA> #> 7984   2063    3M  CC64 2019 2019-04-01         TN -0.5091603444     + #> 7985   2063    3M  CC64 2019 2019-04-01         TP -2.3126354288  <NA> #> 7986   2063    3M  CC64 2019 2019-04-01       TURB  0.4700036292  <NA> #> 7987   2063    3M  CC64 2019 2019-05-06      CHLAC  0.6931471806     I #> 7988   2063    3M  CC64 2019 2019-05-06      COLOR  2.9444389792  <NA> #> 7989   2063    3M  CC64 2019 2019-05-06         DO  0.8372475245  <NA> #> 7990   2063    3M  CC64 2019 2019-05-06      DOSAT  3.5292973843  <NA> #> 7991   2063    3M  CC64 2019 2019-05-06       NO23 -4.6051701860     I #> 7992   2063    3M  CC64 2019 2019-05-06      SALIN  3.2331731296  <NA> #> 7993   2063    3M  CC64 2019 2019-05-06        TKN -0.5621189182  <NA> #> 7994   2063    3M  CC64 2019 2019-05-06         TN -0.5551258827     + #> 7995   2063    3M  CC64 2019 2019-05-06         TP -2.2072749132  <NA> #> 7996   2063    3M  CC64 2019 2019-05-06       TURB  0.2623642645  <NA> #> 7997   2063    3M  CC64 2019 2019-06-03      CHLAC  0.7419373447     I #> 7998   2063    3M  CC64 2019 2019-06-03      COLOR  2.8903717579  <NA> #> 7999   2063    3M  CC64 2019 2019-06-03         DO  1.2974631474  <NA> #> 8000   2063    3M  CC64 2019 2019-06-03      DOSAT  3.7220724215  <NA> #> 8001   2063    3M  CC64 2019 2019-06-03       NO23 -5.2983173665     I #> 8002   2063    3M  CC64 2019 2019-06-03      SALIN  3.2703291065  <NA> #> 8003   2063    3M  CC64 2019 2019-06-03        TKN -0.3856624808  <NA> #> 8004   2063    3M  CC64 2019 2019-06-03         TN -0.3797973614     + #> 8005   2063    3M  CC64 2019 2019-06-03         TP -2.3025850930  <NA> #> 8006   2063    3M  CC64 2019 2019-06-03       TURB  0.2623642645  <NA> #> 8007   2063    3M  CC64 2019 2019-07-01      CHLAC  1.0986122887  <NA> #> 8008   2063    3M  CC64 2019 2019-07-01      COLOR  2.8903717579  <NA> #> 8009   2063    3M  CC64 2019 2019-07-01         DO  1.4036429995  <NA> #> 8010   2063    3M  CC64 2019 2019-07-01      DOSAT  4.1108738642  <NA> #> 8011   2063    3M  CC64 2019 2019-07-01       NO23 -5.1159958098     I #> 8012   2063    3M  CC64 2019 2019-07-01      SALIN  3.1675825305  <NA> #> 8013   2063    3M  CC64 2019 2019-07-01        TKN -0.4780358009  <NA> #> 8014   2063    3M  CC64 2019 2019-07-01         TN -0.4716049106     + #> 8015   2063    3M  CC64 2019 2019-07-01         TP -2.2072749132  <NA> #> 8016   2063    3M  CC64 2019 2019-07-01       TURB  0.5877866649  <NA> #> 8017   2063    3M  CC64 2019 2019-08-05      CHLAC  1.7578579176  <NA> #> 8018   2063    3M  CC64 2019 2019-08-05      COLOR  3.9120230054  <NA> #> 8019   2063    3M  CC64 2019 2019-08-05         DO  1.3001916621  <NA> #> 8020   2063    3M  CC64 2019 2019-08-05      DOSAT  3.9702919136  <NA> #> 8021   2063    3M  CC64 2019 2019-08-05       NO23 -5.5214609179     U #> 8022   2063    3M  CC64 2019 2019-08-05      SALIN  2.8273136219  <NA> #> 8023   2063    3M  CC64 2019 2019-08-05        TKN -0.1863295782  <NA> #> 8024   2063    3M  CC64 2019 2019-08-05         TN -0.1839228382     + #> 8025   2063    3M  CC64 2019 2019-08-05         TP -1.8325814637  <NA> #> 8026   2063    3M  CC64 2019 2019-08-05       TURB  0.4700036292  <NA> #> 8027   2063    3M  CC64 2019 2019-10-07      CHLAC  1.1939224685  <NA> #> 8028   2063    3M  CC64 2019 2019-10-07      COLOR  3.2958368660  <NA> #> 8029   2063    3M  CC64 2019 2019-10-07         DO  1.6863989536  <NA> #> 8030   2063    3M  CC64 2019 2019-10-07      DOSAT  4.3412046402  <NA> #> 8031   2063    3M  CC64 2019 2019-10-07       NO23 -5.1159958098     I #> 8032   2063    3M  CC64 2019 2019-10-07      SALIN  3.2672849641  <NA> #> 8033   2063    3M  CC64 2019 2019-10-07        TKN -0.4780358009  <NA> #> 8034   2063    3M  CC64 2019 2019-10-07         TN -0.4716049106     + #> 8035   2063    3M  CC64 2019 2019-10-07         TP -2.1202635362  <NA> #> 8036   2063    3M  CC64 2019 2019-10-07       TURB  0.2623642645  <NA> #> 8037   2063    3M  CC64 2019 2019-11-04      CHLAC  1.1939224685  <NA> #> 8038   2063    3M  CC64 2019 2019-11-04      COLOR  3.1354942159  <NA> #> 8039   2063    3M  CC64 2019 2019-11-04         DO  1.3110318766  <NA> #> 8040   2063    3M  CC64 2019 2019-11-04      DOSAT  3.9646154555  <NA> #> 8041   2063    3M  CC64 2019 2019-11-04       NO23 -4.6051701860  <NA> #> 8042   2063    3M  CC64 2019 2019-11-04      SALIN  3.2503744919  <NA> #> 8043   2063    3M  CC64 2019 2019-11-04        TKN -0.4307829161  <NA> #> 8044   2063    3M  CC64 2019 2019-11-04         TN -0.4155154440     + #> 8045   2063    3M  CC64 2019 2019-11-04         TP -2.1202635362  <NA> #> 8046   2063    3M  CC64 2019 2019-11-04       TURB  0.0953101798  <NA> #> 8047   2063    3M  CC64 2020 2020-01-06      CHLAC  1.0296194172  <NA> #> 8048   2063    3M  CC64 2020 2020-01-06      COLOR  2.8332133441  <NA> #> 8049   2063    3M  CC64 2020 2020-01-06         DO  1.6937790609  <NA> #> 8050   2063    3M  CC64 2020 2020-01-06      DOSAT  4.2312037449  <NA> #> 8051   2063    3M  CC64 2020 2020-01-06       NO23 -4.0745419349  <NA> #> 8052   2063    3M  CC64 2020 2020-01-06      SALIN  3.2188758249  <NA> #> 8053   2063    3M  CC64 2020 2020-01-06        TKN -0.4155154440  <NA> #> 8054   2063    3M  CC64 2020 2020-01-06         TN 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3M  CC64 2020 2020-03-02      COLOR  2.5649493575     A #> 8069   2063    3M  CC64 2020 2020-03-02         DO  1.7749523509  <NA> #> 8070   2063    3M  CC64 2020 2020-03-02      DOSAT  4.3067641502  <NA> #> 8071   2063    3M  CC64 2020 2020-03-02       NO23 -5.5214609179     I #> 8072   2063    3M  CC64 2020 2020-03-02      SALIN  3.2924979647  <NA> #> 8073   2063    3M  CC64 2020 2020-03-02        TKN -0.8915981193  <NA> #> 8074   2063    3M  CC64 2020 2020-03-02         TN -0.8818893052     + #> 8075   2063    3M  CC64 2020 2020-03-02         TP -2.3968957725  <NA> #> 8076   2063    3M  CC64 2020 2020-03-02       TURB  0.2623642645  <NA> #> 8077   2063    3M  CC64 2020 2020-09-08      CHLAC  2.3025850930     A #> 8078   2063    3M  CC64 2020 2020-09-08      COLOR  4.0253516907  <NA> #> 8079   2063    3M  CC64 2020 2020-09-08         DO  0.1484200051  <NA> #> 8080   2063    3M  CC64 2020 2020-09-08      DOSAT  2.8332133441  <NA> #> 8081   2063    3M  CC64 2020 2020-09-08       NO23 -5.1159958098     I #> 8082   2063    3M  CC64 2020 2020-09-08      SALIN  2.9693882982  <NA> #> 8083   2063    3M  CC64 2020 2020-09-08        TKN -0.2231435513  <NA> #> 8084   2063    3M  CC64 2020 2020-09-08         TN -0.2181560098     + #> 8085   2063    3M  CC64 2020 2020-09-08         TP -1.5141277326  <NA> #> 8086   2063    3M  CC64 2020 2020-09-08       TURB  0.5306282511  <NA> #> 8087   2063    3M  CC64 2020 2020-10-05      CHLAC  1.5040773968  <NA> #> 8088   2063    3M  CC64 2020 2020-10-05      COLOR  4.2626798770  <NA> #> 8089   2063    3M  CC64 2020 2020-10-05         DO  1.1600209168  <NA> #> 8090   2063    3M  CC64 2020 2020-10-05      DOSAT  3.7495040759  <NA> #> 8091   2063    3M  CC64 2020 2020-10-05       NO23 -3.0365542681  <NA> #> 8092   2063    3M  CC64 2020 2020-10-05      SALIN  2.5649493575  <NA> #> 8093   2063    3M  CC64 2020 2020-10-05        TKN -0.0408219945  <NA> #> 8094   2063    3M  CC64 2020 2020-10-05         TN  0.0079681696     + #> 8095   2063    3M  CC64 2020 2020-10-05         TP -1.8971199849  <NA> #> 8096   2063    3M  CC64 2020 2020-10-05       TURB  0.0953101798  <NA> #> 8097   2063    3M  CC64 2020 2020-11-02      CHLAC  1.1631508098     I #> 8098   2063    3M  CC64 2020 2020-11-02      COLOR  4.0073331852     A #> 8099   2063    3M  CC64 2020 2020-11-02       NO23 -3.9633162998  <NA> #> 8100   2063    3M  CC64 2020 2020-11-02      SALIN  2.7562052430  <NA> #> 8101   2063    3M  CC64 2020 2020-11-02        TKN -0.3710636814  <NA> #> 8102   2063    3M  CC64 2020 2020-11-02         TN -0.3438997525     + #> 8103   2063    3M  CC64 2020 2020-11-02         TP -2.0402208285  <NA> #> 8104   2063    3M  CC64 2020 2020-11-02       TURB  0.2623642645  <NA> #> 8105   2063    3M  CC64 2020 2020-12-07      CHLAC  0.3364722366     I #> 8106   2063    3M  CC64 2020 2020-12-07      COLOR  3.6635616461  <NA> #> 8107   2063    3M  CC64 2020 2020-12-07         DO  1.6677068206  <NA> #> 8108   2063    3M  CC64 2020 2020-12-07      DOSAT  4.1743872699  <NA> #> 8109   2063    3M  CC64 2020 2020-12-07       NO23 -3.8167128256  <NA> #> 8110   2063    3M  CC64 2020 2020-12-07      SALIN  2.9982291538  <NA> #> 8111   2063    3M  CC64 2020 2020-12-07        TKN -0.3856624808  <NA> #> 8112   2063    3M  CC64 2020 2020-12-07         TN -0.3538218750     + #> 8113   2063    3M  CC64 2020 2020-12-07         TP -2.4769384801  <NA> #> 8114   2063    3M  CC64 2020 2020-12-07       TURB  0.1823215568  <NA> #> 8115   2063    3M  CC64 2021 2021-01-04      CHLAC  0.3364722366     I #> 8116   2063    3M  CC64 2021 2021-01-04      COLOR  3.1780538303  <NA> #> 8117   2063    3M  CC64 2021 2021-01-04         DO  1.4816045409  <NA> #> 8118   2063    3M  CC64 2021 2021-01-04      DOSAT  4.0271358125  <NA> #> 8119   2063    3M  CC64 2021 2021-01-04       NO23 -4.1351665567  <NA> #> 8120   2063    3M  CC64 2021 2021-01-04      SALIN  3.1376657694  <NA> #> 8121   2063    3M  CC64 2021 2021-01-04        TKN -0.5276327421  <NA> #> 8122   2063    3M  CC64 2021 2021-01-04         TN -0.5008752929     + #> 8123   2063    3M  CC64 2021 2021-01-04         TP -2.3025850930  <NA> #> 8124   2063    3M  CC64 2021 2021-01-04       TURB  0.2623642645  <NA> #> 8125   2063    3M  CC64 2021 2021-02-01      CHLAC  0.9932517730  <NA> #> 8126   2063    3M  CC64 2021 2021-02-01      COLOR  2.8332133441  <NA> #> 8127   2063    3M  CC64 2021 2021-02-01         DO  1.8082887712  <NA> #> 8128   2063    3M  CC64 2021 2021-02-01      DOSAT  4.3489867806  <NA> #> 8129   2063    3M  CC64 2021 2021-02-01       NO23 -4.9618451299     I #> 8130   2063    3M  CC64 2021 2021-02-01      SALIN  3.2120525995  <NA> #> 8131   2063    3M  CC64 2021 2021-02-01        TKN -0.5276327421  <NA> #> 8132   2063    3M  CC64 2021 2021-02-01         TN -0.5208759596     + #> 8133   2063    3M  CC64 2021 2021-02-01         TP -2.3751557858  <NA> #> 8134   2063    3M  CC64 2021 2021-02-01       TURB  1.1631508098  <NA> #> 8135   2063    3M  CC64 2021 2021-03-01      CHLAC  0.6418538862     I #> 8136   2063    3M  CC64 2021 2021-03-01      COLOR  2.6390573296  <NA> #> 8137   2063    3M  CC64 2021 2021-03-01         DO  1.5454325825  <NA> #> 8138   2063    3M  CC64 2021 2021-03-01      DOSAT  4.1956970565  <NA> #> 8139   2063    3M  CC64 2021 2021-03-01       NO23 -4.8283137373     I #> 8140   2063    3M  CC64 2021 2021-03-01      SALIN  3.2861605717  <NA> #> 8141   2063    3M  CC64 2021 2021-03-01        TKN -0.9675840263     I #> 8142   2063    3M  CC64 2021 2021-03-01         TN -1.8078888512     + #> 8143   2063    3M  CC64 2021 2021-03-01         TP -2.3859667019  <NA> #> 8144   2063    3M  CC64 2021 2021-03-01       TURB  0.6931471806     A #> 8145   2063    3M  CC64 2021 2021-04-05      CHLAC  1.5475625087  <NA> #> 8146   2063    3M  CC64 2021 2021-04-05      COLOR  2.7080502011  <NA> #> 8147   2063    3M  CC64 2021 2021-04-05         DO  1.6505798558  <NA> #> 8148   2063    3M  CC64 2021 2021-04-05      DOSAT  4.2370008626  <NA> #> 8149   2063    3M  CC64 2021 2021-04-05       NO23 -5.5214609179     U #> 8150   2063    3M  CC64 2021 2021-04-05      SALIN  3.3010086544  <NA> #> 8151   2063    3M  CC64 2021 2021-04-05         TN -0.4277107171     + #> 8152   2063    3M  CC64 2021 2021-04-05         TP -2.2072749132  <NA> #> 8153   2063    3M  CC64 2021 2021-04-05       TURB  1.2527629685  <NA> #> 8154   2063    3M  CC64 2021 2021-05-03      CHLAC  0.9932517730  <NA> #> 8155   2063    3M  CC64 2021 2021-05-03      COLOR  2.9957322736  <NA> #> 8156   2063    3M  CC64 2021 2021-05-03         DO  1.2584609896  <NA> #> 8157   2063    3M  CC64 2021 2021-05-03      DOSAT  3.9740583963  <NA> #> 8158   2063    3M  CC64 2021 2021-05-03       NO23 -5.5214609179     U #> 8159   2063    3M  CC64 2021 2021-05-03      SALIN  3.3641875560  <NA> #> 8160   2063    3M  CC64 2021 2021-05-03        TKN -0.7133498879  <NA> #> 8161   2063    3M  CC64 2021 2021-05-03         TN -0.7092765625     + #> 8162   2063    3M  CC64 2021 2021-05-03         TP 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3M  CC64 2021 2021-08-02         DO  1.4255150743  <NA> #> 8177   2063    3M  CC64 2021 2021-08-02      DOSAT  4.1092331747  <NA> #> 8178   2063    3M  CC64 2021 2021-08-02       NO23 -4.8283137373     I #> 8179   2063    3M  CC64 2021 2021-08-02      SALIN  2.4292177439  <NA> #> 8180   2063    3M  CC64 2021 2021-08-02        TKN -0.1278333715  <NA> #> 8181   2063    3M  CC64 2021 2021-08-02         TN -0.1232982163     + #> 8182   2063    3M  CC64 2021 2021-08-02         TP -1.7719568419  <NA> #> 8183   2063    3M  CC64 2021 2021-08-02       TURB  0.6418538862  <NA> #> 8184   2063    3M  CC64 2021 2021-09-07      CHLAC  0.9555114450  <NA> #> 8185   2063    3M  CC64 2021 2021-09-07      COLOR  4.1271343850  <NA> #> 8186   2063    3M  CC64 2021 2021-09-07         DO  0.9820784724  <NA> #> 8187   2063    3M  CC64 2021 2021-09-07      DOSAT  3.6375861597  <NA> #> 8188   2063    3M  CC64 2021 2021-09-07       NO23 -3.8167128256  <NA> #> 8189   2063    3M  CC64 2021 2021-09-07      SALIN  2.5687881338  <NA> #> 8190   2063    3M  CC64 2021 2021-09-07        TKN -0.1053605157  <NA> #> 8191   2063    3M  CC64 2021 2021-09-07         TN -0.0812100554     + #> 8192   2063    3M  CC64 2021 2021-09-07         TP -1.8325814637  <NA> #> 8193   2063    3M  CC64 2021 2021-09-07       TURB  0.0953101798  <NA> #> 8194   2063    3M  CC64 2021 2021-10-04      CHLAC  1.1939224685  <NA> #> 8195   2063    3M  CC64 2021 2021-10-04      COLOR  3.7841896339  <NA> #> 8196   2063    3M  CC64 2021 2021-10-04         DO  1.0577902941  <NA> #> 8197   2063    3M  CC64 2021 2021-10-04      DOSAT  3.7135720667  <NA> #> 8198   2063    3M  CC64 2021 2021-10-04       NO23 -4.7105307016     I #> 8199   2063    3M  CC64 2021 2021-10-04      SALIN  2.9069010598  <NA> #> 8200   2063    3M  CC64 2021 2021-10-04        TKN -0.3566749439  <NA> #> 8201   2063    3M  CC64 2021 2021-10-04         TN -0.3509769228     + #> 8202   2063    3M  CC64 2021 2021-10-04         TP -1.8325814637  <NA> #> 8203   2063    3M  CC64 2021 2021-10-04       TURB  0.0953101798  <NA> #> 8204   2063    3M  CC64 2021 2021-11-01      CHLAC  0.9162907319     I #> 8205   2063    3M  CC64 2021 2021-11-01      COLOR  3.6109179126     A #> 8206   2063    3M  CC64 2021 2021-11-01         DO  1.0331844833  <NA> #> 8207   2063    3M  CC64 2021 2021-11-01      DOSAT  3.6375861597  <NA> #> 8208   2063    3M  CC64 2021 2021-11-01       NO23 -3.1941832123  <NA> #> 8209   2063    3M  CC64 2021 2021-11-01      SALIN  3.0964821767  <NA> #> 8210   2063    3M  CC64 2021 2021-11-01        TKN -0.3566749439  <NA> #> 8211   2063    3M  CC64 2021 2021-11-01         TN -0.2997546537     + #> 8212   2063    3M  CC64 2021 2021-11-01         TP -1.9661128564  <NA> #> 8213   2063    3M  CC64 2021 2021-11-01       TURB  0.0000000000  <NA> #> 8214   2063    3M  CC64 2021 2021-12-07      CHLAC  0.6931471806     I #> 8215   2063    3M  CC64 2021 2021-12-07      COLOR  2.6390573296     A #> 8216   2063    3M  CC64 2021 2021-12-07         DO  1.6154199841  <NA> #> 8217   2063    3M  CC64 2021 2021-12-07      DOSAT  4.2046926194     + #> 8218   2063    3M  CC64 2021 2021-12-07       NO23 -3.9633162998  <NA> #> 8219   2063    3M  CC64 2021 2021-12-07      SALIN  3.2638491905  <NA> #> 8220   2063    3M  CC64 2021 2021-12-07        TKN -0.3856624808  <NA> #> 8221   2063    3M  CC64 2021 2021-12-07         TN -0.3581045367     + #> 8222   2063    3M  CC64 2021 2021-12-07         TP -2.3434070875  <NA> #> 8223   2063    3M  CC64 2021 2021-12-07       TURB -0.1625189295  <NA> #> 8224   2063    3M  CC64 2022 2022-01-03      CHLAC  0.9932517730  <NA> #> 8225   2063    3M  CC64 2022 2022-01-03      COLOR  2.4849066498  <NA> #> 8226   2063    3M  CC64 2022 2022-01-03         DO  1.5325568681  <NA> #> 8227   2063    3M  CC64 2022 2022-01-03      DOSAT  4.1620032107  <NA> #> 8228   2063    3M  CC64 2022 2022-01-03       NO23 -3.9633162998  <NA> #> 8229   2063    3M  CC64 2022 2022-01-03      SALIN  3.2763897311  <NA> #> 8230   2063    3M  CC64 2022 2022-01-03        TKN -0.6161861394  <NA> #> 8231   2063    3M  CC64 2022 2022-01-03         TN -0.5816058058     + #> 8232   2063    3M  CC64 2022 2022-01-03         TP -2.2072749132  <NA> #> 8233   2063    3M  CC64 2022 2022-01-03       TURB  0.9555114450  <NA> #> 8234   2063    3M  CC64 2022 2022-02-07      CHLAC  0.7419373447     I #> 8235   2063    3M  CC64 2022 2022-02-07      COLOR  1.4586150227     I #> 8236   2063    3M  CC64 2022 2022-02-07         DO  1.6826883742  <NA> #> 8237   2063    3M  CC64 2022 2022-02-07      DOSAT  4.2268337453  <NA> #> 8238   2063    3M  CC64 2022 2022-02-07       NO23 -5.5214609179     I #> 8239   2063    3M  CC64 2022 2022-02-07      SALIN  3.3354136411  <NA> #> 8240   2063    3M  CC64 2022 2022-02-07        TKN -0.8675005677  <NA> #> 8241   2063    3M  CC64 2022 2022-02-07         TN -0.8580218238     + #> 8242   2063    3M  CC64 2022 2022-02-07         TP -2.6736487744  <NA> #> 8243   2063    3M  CC64 2022 2022-02-07       TURB 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3M  CC64 2022 2022-04-04      DOSAT  3.9889840466  <NA> #> 8258   2063    3M  CC64 2022 2022-04-04       NO23 -4.6051701860     I #> 8259   2063    3M  CC64 2022 2022-04-04      SALIN  3.4157575330  <NA> #> 8260   2063    3M  CC64 2022 2022-04-04        TKN -0.9942522733     I #> 8261   2063    3M  CC64 2022 2022-04-04         TN -1.8078888512     + #> 8262   2063    3M  CC64 2022 2022-04-04         TP -2.4079456087  <NA> #> 8263   2063    3M  CC64 2022 2022-04-04       TURB  0.2623642645  <NA> #> 8264   2063    3M  CC64 2022 2022-05-02      CHLAC  1.0986122887  <NA> #> 8265   2063    3M  CC64 2022 2022-05-02      COLOR  1.0647107370     I #> 8266   2063    3M  CC64 2022 2022-05-02         DO  1.3987168811  <NA> #> 8267   2063    3M  CC64 2022 2022-05-02      DOSAT  4.0775374439  <NA> #> 8268   2063    3M  CC64 2022 2022-05-02       NO23 -5.2983173665     I #> 8269   2063    3M  CC64 2022 2022-05-02      SALIN  3.4229588734  <NA> #> 8270   2063    3M  CC64 2022 2022-05-02        TKN -0.5447271754  <NA> #> 8271   2063    3M  CC64 2022 2022-05-02         TN -0.5378542962     + #> 8272   2063    3M  CC64 2022 2022-05-02         TP -2.4651040225  <NA> #> 8273   2063    3M  CC64 2022 2022-05-02       TURB -0.0512932944     I #> 8274   2063    3M  CC64 2022 2022-06-06      CHLAC  1.9459101491  <NA> #> 8275   2063    3M  CC64 2022 2022-06-06      COLOR  3.7612001157     A #> 8276   2063    3M  CC64 2022 2022-06-06         DO  1.3987168811  <NA> #> 8277   2063    3M  CC64 2022 2022-06-06      DOSAT  4.0775374439  <NA> #> 8278   2063    3M  CC64 2022 2022-06-06       NO23 -4.7105307016     I #> 8279   2063    3M  CC64 2022 2022-06-06      SALIN  3.2588654731  <NA> #> 8280   2063    3M  CC64 2022 2022-06-06        TKN -0.1165338163  <NA> #> 8281   2063    3M  CC64 2022 2022-06-06         TN -0.1120495038     + #> 8282   2063    3M  CC64 2022 2022-06-06         TP -2.4304184645  <NA> #> 8283   2063    3M  CC64 2022 2022-06-06       TURB  1.0647107370  <NA> #> 8284   2063    3M  CC64 2022 2022-07-05      CHLAC  1.6292405397  <NA> #> 8285   2063    3M  CC64 2022 2022-07-05      COLOR  2.8903717579  <NA> #> 8286   2063    3M  CC64 2022 2022-07-05       NO23 -5.2983173665     I #> 8287   2063    3M  CC64 2022 2022-07-05      SALIN  3.2534704696  <NA> #> 8288   2063    3M  CC64 2022 2022-07-05        TKN -0.5447271754  <NA> #> 8289   2063    3M  CC64 2022 2022-07-05         TN -0.5378542962     + #> 8290   2063    3M  CC64 2022 2022-07-05         TP -2.1202635362  <NA> #> 8291   2063    3M  CC64 2022 2022-07-05       TURB  0.0953101798  <NA> #> 8292   2063    3M  CC64 2022 2022-08-01      CHLAC  2.1517622033  <NA> #> 8293   2063    3M  CC64 2022 2022-08-01      COLOR  3.2580965380     A #> 8294   2063    3M  CC64 2022 2022-08-01         DO  0.7419373447  <NA> #> 8295   2063    3M  CC64 2022 2022-08-01      DOSAT  3.4499875458  <NA> #> 8296   2063    3M  CC64 2022 2022-08-01       NO23 -4.7105307016     I #> 8297   2063    3M  CC64 2022 2022-08-01      SALIN  3.0991909819  <NA> #> 8298   2063    3M  CC64 2022 2022-08-01        TKN -0.1278333715  <NA> #> 8299   2063    3M  CC64 2022 2022-08-01         TN -0.1232982163     + #> 8300   2063    3M  CC64 2022 2022-08-01         TP -2.1202635362  <NA> #> 8301   2063    3M  CC64 2022 2022-08-01       TURB  0.4700036292  <NA> #> 8302   2063    3M  CC64 2022 2022-09-06      CHLAC  1.9021075264  <NA> #> 8303   2063    3M  CC64 2022 2022-09-06      COLOR  3.9512437186  <NA> #> 8304   2063    3M  CC64 2022 2022-09-06         DO  1.3350010667  <NA> #> 8305   2063    3M  CC64 2022 2022-09-06      DOSAT  4.0324691585  <NA> #> 8306   2063    3M  CC64 2022 2022-09-06       NO23 -5.2983173665     I #> 8307   2063    3M  CC64 2022 2022-09-06      SALIN  2.7856283357  <NA> #> 8308   2063    3M  CC64 2022 2022-09-06        TKN -0.1863295782  <NA> #> 8309   2063    3M  CC64 2022 2022-09-06         TN -0.1815218766     + #> 8310   2063    3M  CC64 2022 2022-09-06         TP -1.8325814637  <NA> #> 8311   2063    3M  CC64 2022 2022-09-06       TURB  0.7419373447  <NA> #> 8312   2063    3M  CC64 2022 2022-11-07      CHLAC  0.8754687374     I #> 8313   2063    3M  CC64 2022 2022-11-07      COLOR  4.2341065046  <NA> #> 8314   2063    3M  CC64 2022 2022-11-07         DO  0.9360933592  <NA> #> 8315   2063    3M  CC64 2022 2022-11-07      DOSAT  3.5263605246  <NA> #> 8316   2063    3M  CC64 2022 2022-11-07       NO23 -3.2968373663  <NA> #> 8317   2063    3M  CC64 2022 2022-11-07      SALIN  2.6049094422  <NA> #> 8318   2063    3M  CC64 2022 2022-11-07        TKN -0.2744368457  <NA> #> 8319   2063    3M  CC64 2022 2022-11-07         TN -0.2269006002     + #> 8320   2063    3M  CC64 2022 2022-11-07         TP -1.7147984281  <NA> #> 8321   2063    3M  CC64 2022 2022-11-07       TURB  0.1823215568  <NA> #> 8322   2063    3M  CC64 2022 2022-12-05      CHLAC  1.0296194172  <NA> #> 8323   2063    3M  CC64 2022 2022-12-05      COLOR  3.6109179126  <NA> #> 8324   2063    3M  CC64 2022 2022-12-05         DO  1.3190856114  <NA> #> 8325   2063    3M  CC64 2022 2022-12-05      DOSAT  3.8918202981  <NA> #> 8326   2063    3M  CC64 2022 2022-12-05       NO23 -2.8647040111  <NA> #> 8327   2063    3M  CC64 2022 2022-12-05      SALIN  2.9992261628  <NA> #> 8328   2063    3M  CC64 2022 2022-12-05        TKN -0.4004775666  <NA> #> 8329   2063    3M  CC64 2022 2022-12-05         TN -0.3188288014     + #> 8330   2063    3M  CC64 2022 2022-12-05         TP -1.7719568419  <NA> #> 8331   2063    3M  CC64 2022 2022-12-05       TURB  1.0296194172  <NA> #> 8332   2063    3M  CC64 2023 2023-01-03      CHLAC  1.3083328197  <NA> #> 8333   2063    3M  CC64 2023 2023-01-03      COLOR  2.7080502011  <NA> #> 8334   2063    3M  CC64 2023 2023-01-03         DO  1.6524974019  <NA> #> 8335   2063    3M  CC64 2023 2023-01-03      DOSAT  3.6133473915  <NA> #> 8336   2063    3M  CC64 2023 2023-01-03       NO23 -3.2188758249  <NA> #> 8337   2063    3M  CC64 2023 2023-01-03      SALIN  3.1582762027  <NA> #> 8338   2063    3M  CC64 2023 2023-01-03        TKN -0.7133498879  <NA> #> 8339   2063    3M  CC64 2023 2023-01-03         TN -0.6348782724     + #> 8340   2063    3M  CC64 2023 2023-01-03         TP -1.9661128564  <NA> #> 8341   2063    3M  CC64 2023 2023-01-03       TURB  0.2623642645  <NA> #> 8342   2063    3M  CC64 2023 2023-02-06      CHLAC  1.0986122887  <NA> #> 8343   2063    3M  CC64 2023 2023-02-06      COLOR  2.7725887222  <NA> #> 8344   2063    3M  CC64 2023 2023-02-06         DO  1.4586150227  <NA> #> 8345   2063    3M  CC64 2023 2023-02-06      DOSAT  4.0430512678  <NA> #> 8346   2063    3M  CC64 2023 2023-02-06       NO23 -4.2686979494  <NA> #> 8347   2063    3M  CC64 2023 2023-02-06      SALIN  3.2284300377  <NA> #> 8348   2063    3M  CC64 2023 2023-02-06        TKN -0.4942963218  <NA> #> 8349   2063    3M  CC64 2023 2023-02-06         TN -0.4716049106     + #> 8350   2063    3M  CC64 2023 2023-02-06         TP -2.0402208285  <NA> #> 8351   2063    3M  CC64 2023 2023-02-06       TURB  0.6418538862  <NA> #> 8352   2063    3M  CC64 2023 2023-03-06      CHLAC  0.9932517730  <NA> #> 8353   2063    3M  CC64 2023 2023-03-06      COLOR  2.7725887222  <NA> #> 8354   2063    3M  CC64 2023 2023-03-06         DO  1.3962446920  <NA> #> 8355   2063    3M  CC64 2023 2023-03-06      DOSAT  4.0758410907  <NA> #> 8356   2063    3M  CC64 2023 2023-03-06       NO23 -4.9618451299     I #> 8357   2063    3M  CC64 2023 2023-03-06      SALIN  3.3170908724  <NA> #> 8358   2063    3M  CC64 2023 2023-03-06        TKN -0.6161861394  <NA> #> 8359   2063    3M  CC64 2023 2023-03-06         TN -0.6088060321     + #> 8360   2063    3M  CC64 2023 2023-03-06         TP -2.0402208285  <NA> #> 8361   2063    3M  CC64 2023 2023-03-06       TURB  0.8754687374  <NA> #> 8362   2063    3M  CC64 2014 2014-01-07      CHLAC  1.0986122887  <NA> #> 8363   2063    3M  CC64 2014 2014-01-07         TN -0.9942522733  <NA> #> 8364   2063    3M  CC64 2014 2014-01-07         TP -2.5510464523  <NA> #> 8365   2063    3M  CC64 2014 2014-02-04      CHLAC  0.0000000000  <NA> #> 8366   2063    3M  CC64 2014 2014-02-04         TN -1.0498221245  <NA> #> 8367   2063    3M  CC64 2014 2014-02-04         TP -2.6310891600  <NA> #> 8368   2063    3M  CC64 2014 2014-03-04      CHLAC  1.3862943611  <NA> #> 8369   2063    3M  CC64 2014 2014-03-04         TN -0.5978370008  <NA> #> 8370   2063    3M  CC64 2014 2014-03-04         TP -2.7333680091  <NA> #> 8371   2063    3M  CC64 2014 2014-04-01      CHLAC  1.0986122887  <NA> #> 8372   2063    3M  CC64 2014 2014-04-01         TN -1.0788096614  <NA> #> 8373   2063    3M  CC64 2014 2014-04-01         TP -2.7181005370  <NA> #> 8374   2063    3M  CC64 2014 2014-06-03      CHLAC  1.3862943611  <NA> #> 8375   2063    3M  CC64 2014 2014-06-03         TN -0.5798184953  <NA> #> 8376   2063    3M  CC64 2014 2014-06-03         TP -2.2072749132  <NA> #> 8377   2063    3M  CC64 2014 2014-09-02      CHLAC  3.1354942159  <NA> #> 8378   2063    3M  CC64 2014 2014-09-02         TP -2.3126354288  <NA> #> 8379   2063    3M  CC64 2014 2014-11-04      CHLAC  0.6931471806  <NA> #> 8380   2063    3M  CC64 2014 2014-11-04         TN -0.5798184953  <NA> #> 8381   2063    3M  CC64 2014 2014-11-04         TP -2.6310891600  <NA> #> 8382   2063    3M  CC64 2014 2014-12-02      CHLAC  0.0000000000  <NA> #> 8383   2063    3M  CC64 2014 2014-12-02         TN -0.4942963218  <NA> #> 8384   2063    3M  CC64 2014 2014-12-02         TP -2.3751557858  <NA> #> 8385   2063    3M  CC64 2015 2015-01-03      CHLAC  0.0000000000  <NA> #> 8386   2063    3M  CC64 2015 2015-01-03         TN -0.3011050928  <NA> #> 8387   2063    3M  CC64 2015 2015-01-03         TP -1.8018098051  <NA> #> 8388   2063    3M  CC64 2015 2015-02-02      CHLAC  0.6931471806  <NA> #> 8389   2063    3M  CC64 2015 2015-03-03      CHLAC  0.0000000000  <NA> #> 8390   2063    3M  CC64 2015 2015-03-03         TN -0.5798184953  <NA> #> 8391   2063    3M  CC64 2015 2015-03-03         TP -2.2730262908  <NA> #> 8392   2063    3M  CC64 2015 2015-04-02      CHLAC  0.6931471806  <NA> #> 8393   2063    3M  CC64 2015 2015-04-02         TN -0.4462871026  <NA> #> 8394   2063    3M  CC64 2015 2015-04-02         TP -2.2926347621  <NA> #> 8395   2063    3M  CC64 2015 2015-05-05      CHLAC  1.0986122887  <NA> #> 8396   2063    3M  CC64 2015 2015-05-05         TN -0.8209805521  <NA> #> 8397   2063    3M  CC64 2015 2015-05-05         TP -2.5257286443  <NA> #> 8398   2063    3M  CC64 2015 2015-09-09      CHLAC  1.0986122887  <NA> #> 8399   2063    3M  CC64 2015 2015-09-09         TN -0.5978370008  <NA> #> 8400   2063    3M  CC64 2015 2015-09-09         TP -2.9759296463  <NA> #> 8401   2063    3M  CC64 2015 2015-10-07      CHLAC  1.6094379124  <NA> #> 8402   2063    3M  CC64 2015 2015-11-04      CHLAC  1.0986122887  <NA> #> 8403   2063    3M  CC64 2015 2015-11-04         TN -0.6539264674  <NA> #> 8404   2063    3M  CC64 2015 2015-11-04         TP -2.6172958378  <NA> #> 8405   2063    3M  CC64 2015 2015-11-15      CHLAC  1.6094379124  <NA> #> 8406   2063    3M  CC64 2015 2015-11-15         TN -0.8439700703  <NA> #> 8407   2063    3M  CC64 2015 2015-11-15         TP -2.7968814148  <NA> #> 8408   2063    3M  CC64 2016 2016-01-06         TN -0.1053605157  <NA> #> 8409   2063    3M  CC64 2016 2016-01-06         TP -2.3126354288  <NA> #> 8410   2063    3M  CC64 2016 2016-02-02      CHLAC  1.6094379124  <NA> #> 8411   2063    3M  CC64 2016 2016-02-02         TN -0.2231435513  <NA> #> 8412   2063    3M  CC64 2016 2016-02-02         TP -2.9957322736  <NA> #> 8413   2063    3M  CC64 2016 2016-06-11      CHLAC  2.5649493575  <NA> #> 8414   2063    3M  CC64 2016 2016-06-11         TN -0.8439700703  <NA> #> 8415   2063    3M  CC64 2016 2016-06-11         TP -2.7488721956  <NA> #> 8416   2063    3M  CC64 2016 2016-07-08      CHLAC  1.0986122887  <NA> #> 8417   2063    3M  CC64 2016 2016-07-08         TN -0.7765287895  <NA> #> 8418   2063    3M  CC64 2016 2016-07-08         TP -3.7722610631  <NA> #> 8419   2063    3M  CC64 2016 2016-10-03      CHLAC  1.0986122887  <NA> #> 8420   2063    3M  CC64 2016 2016-10-03         TN -0.2231435513  <NA> #> 8421   2063    3M  CC64 2016 2016-10-03         TP -2.0874737134  <NA> #> 8422   2063    3M  CC64 2018 2018-12-04      CHLAC  1.0986122887  <NA> #> 8423   2063    3M  CC64 2018 2018-12-04         TN -0.7985076962  <NA> #> 8424   2063    3M  CC64 2018 2018-12-04         TP -2.3644604967  <NA> #> 8425   2063    3M  CC64 2019 2019-01-09      CHLAC  0.6931471806     I #> 8426   2063    3M  CC64 2019 2019-01-09         TN -1.2039728043  <NA> #> 8427   2063    3M  CC64 2019 2019-01-09         TP -2.7333680091  <NA> #> 8428  2065B     2  CC67 2015 2015-04-07      CHLAC  0.6931471806  <NA> #> 8429  2065B     2  CC67 2015 2015-04-07      COLOR  3.4011973817  <NA> #> 8430  2065B     2  CC67 2015 2015-04-07       COND 10.6960274770  <NA> #> 8431  2065B     2  CC67 2015 2015-04-07         DO  1.8164520818  <NA> #> 8432  2065B     2  CC67 2015 2015-04-07      DOSAT  4.4931206822     + #> 8433  2065B     2  CC67 2015 2015-04-07       NO23 -5.1159958098     I #> 8434  2065B     2  CC67 2015 2015-04-07      SALIN  3.3492020865  <NA> #> 8435  2065B     2  CC67 2015 2015-04-07        TKN -0.2587707290  <NA> #> 8436  2065B     2  CC67 2015 2015-04-07         TN -0.2510287548  <NA> #> 8437  2065B     2  CC67 2015 2015-04-07         TP -2.4079456087  <NA> #> 8438  2065B     2  CC67 2015 2015-04-07        TSS  2.2257040487  <NA> #> 8439  2065B     2  CC67 2015 2015-04-07       TURB  0.2623642645  <NA> #> 8440  2065B     2  CC67 2015 2015-04-07       COND 10.6958011046  <NA> #> 8441  2065B     2  CC67 2015 2015-04-07         DO  1.8033586051  <NA> #> 8442  2065B     2  CC67 2015 2015-04-07      DOSAT  4.4796069630     + #> 8443  2065B     2  CC67 2015 2015-04-07      SALIN  3.3488509013  <NA> #> 8444  2065B     2  CC67 2015 2015-11-03      CHLAC  2.0476928434  <NA> #> 8445  2065B     2  CC67 2015 2015-11-03      COLOR  4.0073331852  <NA> #> 8446  2065B     2  CC67 2015 2015-11-03       COND 10.5339611386  <NA> #> 8447  2065B     2  CC67 2015 2015-11-03         DO  2.0731719287  <NA> #> 8448  2065B     2  CC67 2015 2015-11-03      DOSAT  4.7723781050     + #> 8449  2065B     2  CC67 2015 2015-11-03       NO23 -5.5214609179     U #> 8450  2065B     2  CC67 2015 2015-11-03      SALIN  3.1658969001  <NA> #> 8451  2065B     2  CC67 2015 2015-11-03        TKN -0.4557063245  <NA> #> 8452  2065B     2  CC67 2015 2015-11-03         TN -0.4557063245  <NA> #> 8453  2065B     2  CC67 2015 2015-11-03         TP -2.0557250151  <NA> #> 8454  2065B     2  CC67 2015 2015-11-03        TSS  1.7369512327  <NA> #> 8455  2065B     2  CC67 2015 2015-11-03       TURB -0.3566749439  <NA> #> 8456  2065B     2  CC67 2015 2015-11-03       COND 10.5312958918  <NA> #> 8457  2065B     2  CC67 2015 2015-11-03         DO  2.0955609236  <NA> #> 8458  2065B     2  CC67 2015 2015-11-03      DOSAT  4.7966166506     + #> 8459  2065B     2  CC67 2015 2015-11-03      SALIN  3.1629401925  <NA> #> 8460  2065B     2  CC67 2017 2017-04-05      CHLAC -0.0502412164     I #> 8461  2065B     2  CC67 2017 2017-04-05       COND 10.7904503955  <NA> #> 8462  2065B     2  CC67 2017 2017-04-05         DO  1.9586853405  <NA> #> 8463  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6653241088     + #> 8464  2065B     2  CC67 2017 2017-04-05       NO23 -4.8283137373     I #> 8465  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8466  2065B     2  CC67 2017 2017-04-05        TKN -0.4261781497  <NA> #> 8467  2065B     2  CC67 2017 2017-04-05         TN -0.4140014391  <NA> #> 8468  2065B     2  CC67 2017 2017-04-05         TP -2.7030626596  <NA> #> 8469  2065B     2  CC67 2017 2017-04-05        TSS  2.1972245773  <NA> #> 8470  2065B     2  CC67 2017 2017-04-05       TURB  0.0000000000  <NA> #> 8471  2065B     2  CC67 2017 2017-04-05       COND 10.7904771690  <NA> #> 8472  2065B     2  CC67 2017 2017-04-05         DO  1.9699056546  <NA> #> 8473  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6784206477     + #> 8474  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8475  2065B     2  CC67 2017 2017-04-05       COND 10.7905760186  <NA> #> 8476  2065B     2  CC67 2017 2017-04-05         DO  1.9712993831  <NA> #> 8477  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6802776585     + #> 8478  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8479  2065B     2  CC67 2017 2017-04-05       COND 10.7905821964  <NA> #> 8480  2065B     2  CC67 2017 2017-04-05         DO  1.9726911717  <NA> #> 8481  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6812048723     + #> 8482  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8483  2065B     2  CC67 2017 2017-06-05      CHLAC  1.3686394259  <NA> #> 8484  2065B     2  CC67 2017 2017-06-05       NO23 -4.1351665567  <NA> #> 8485  2065B     2  CC67 2017 2017-06-05        TKN -0.2600669054  <NA> #> 8486  2065B     2  CC67 2017 2017-06-05         TN -0.2395270306  <NA> #> 8487  2065B     2  CC67 2017 2017-06-05         TP -2.5770219387  <NA> #> 8488  2065B     2  CC67 2017 2017-06-05        TSS  2.4595888418  <NA> #> 8489  2065B     2  CC67 2017 2017-06-05       TURB  0.0000000000  <NA> #> 8490  2065B     2  CC67 2017 2017-06-05       COND 10.8045448425  <NA> #> 8491  2065B     2  CC67 2017 2017-06-05         DO  1.6134299337  <NA> #> 8492  2065B     2  CC67 2017 2017-06-05      DOSAT  4.3592696476     + #> 8493  2065B     2  CC67 2017 2017-06-05      SALIN  3.4679210137  <NA> #> 8494  2065B     2  CC67 2017 2017-06-05       COND 10.8049143616  <NA> #> 8495  2065B     2  CC67 2017 2017-06-05         DO  1.6524974019  <NA> #> 8496  2065B     2  CC67 2017 2017-06-05      DOSAT  4.3981460166     + #> 8497  2065B     2  CC67 2017 2017-06-05      SALIN  3.4682327830  <NA> #> 8498  2065B     2  CC67 2017 2017-06-05       COND 10.8052533058  <NA> #> 8499  2065B     2  CC67 2017 2017-06-05         DO  1.6677068206  <NA> #> 8500  2065B     2  CC67 2017 2017-06-05      DOSAT  4.4140096805     + #> 8501  2065B     2  CC67 2017 2017-06-05      SALIN  3.4685444551  <NA> #> 8502  2065B     2  CC67 2017 2017-08-15      CHLAC  2.7850112422  <NA> #> 8503  2065B     2  CC67 2017 2017-08-15       COND 10.0070409363  <NA> #> 8504  2065B     2  CC67 2017 2017-08-15         DO  1.7474592103  <NA> #> 8505  2065B     2  CC67 2017 2017-08-15      DOSAT  4.4693504628     + #> 8506  2065B     2  CC67 2017 2017-08-15       NO23 -3.2968373663  <NA> #> 8507  2065B     2  CC67 2017 2017-08-15      SALIN  2.5794589667  <NA> #> 8508  2065B     2  CC67 2017 2017-08-15        TKN  0.0953101798  <NA> #> 8509  2065B     2  CC67 2017 2017-08-15         TN  0.1310282624  <NA> #> 8510  2065B     2  CC67 2017 2017-08-15         TP -1.0555527992  <NA> #> 8511  2065B     2  CC67 2017 2017-08-15        TSS  0.8458682676  <NA> #> 8512  2065B     2  CC67 2017 2017-08-15       TURB  0.6931471806  <NA> #> 8513  2065B     2  CC67 2017 2017-08-15       COND 10.1682757999  <NA> #> 8514  2065B     2  CC67 2017 2017-08-15         DO  0.5822156199  <NA> #> 8515  2065B     2  CC67 2017 2017-08-15      DOSAT  3.2771447330     + #> 8516  2065B     2  CC67 2017 2017-08-15      SALIN  2.7593768283  <NA> #> 8517  2065B     2  CC67 2017 2017-08-15       COND 10.1784604545  <NA> #> 8518  2065B     2  CC67 2017 2017-08-15         DO  0.5306282511  <NA> #> 8519  2065B     2  CC67 2017 2017-08-15      DOSAT  3.2268439945     + #> 8520  2065B     2  CC67 2017 2017-08-15      SALIN  2.7707119622  <NA> #> 8521  2065B     2  CC67 2018 2018-04-09      CHLAC  0.8109302162  <NA> #> 8522  2065B     2  CC67 2018 2018-04-09       COND 10.7756173069  <NA> #> 8523  2065B     2  CC67 2018 2018-04-09         DO  1.9387416596  <NA> #> 8524  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6395716127     + #> 8525  2065B     2  CC67 2018 2018-04-09       NO23 -4.8283137373     I #> 8526  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8527  2065B     2  CC67 2018 2018-04-09        TKN -0.3945251681  <NA> #> 8528  2065B     2  CC67 2018 2018-04-09         TN -0.3827256211  <NA> #> 8529  2065B     2  CC67 2018 2018-04-09         TP -2.5902671654  <NA> #> 8530  2065B     2  CC67 2018 2018-04-09        TSS  1.4816045409  <NA> #> 8531  2065B     2  CC67 2018 2018-04-09       TURB  0.0953101798  <NA> #> 8532  2065B     2  CC67 2018 2018-04-09       COND 10.7754082549  <NA> #> 8533  2065B     2  CC67 2018 2018-04-09         DO  1.9473377010  <NA> #> 8534  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6482296754     + #> 8535  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8536  2065B     2  CC67 2018 2018-04-09       COND 10.7754082549  <NA> #> 8537  2065B     2  CC67 2018 2018-04-09         DO  1.9487632180  <NA> #> 8538  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6501435516     + #> 8539  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8540  2065B     2  CC67 2018 2018-05-23      CHLAC  1.1216775616  <NA> #> 8541  2065B     2  CC67 2018 2018-05-23       COND 10.7435212354  <NA> #> 8542  2065B     2  CC67 2018 2018-05-23         DO  1.8885836539  <NA> #> 8543  2065B     2  CC67 2018 2018-05-23      DOSAT  4.5910712616     + #> 8544  2065B     2  CC67 2018 2018-05-23       NO23 -4.6051701860     I #> 8545  2065B     2  CC67 2018 2018-05-23      SALIN  3.4011973817  <NA> #> 8546  2065B     2  CC67 2018 2018-05-23        TKN -0.1696027844  <NA> #> 8547  2065B     2  CC67 2018 2018-05-23         TN -0.1578240852  <NA> #> 8548  2065B     2  CC67 2018 2018-05-23         TP -2.0794415417  <NA> #> 8549  2065B     2  CC67 2018 2018-05-23        TSS  1.5686159179  <NA> #> 8550  2065B     2  CC67 2018 2018-05-23       TURB  1.0647107370  <NA> #> 8551  2065B     2  CC67 2018 2018-05-23      DOSAT  4.6793495842     + #> 8552  2065B     2  CC67 2018 2018-05-23       COND 10.7527727226  <NA> #> 8553  2065B     2  CC67 2018 2018-05-23         DO  1.9782390362  <NA> #> 8554  2065B     2  CC67 2018 2018-05-23      SALIN  3.4118075608  <NA> #> 8555  2065B     2  CC67 2018 2018-10-11      CHLAC  1.4109869737  <NA> #> 8556  2065B     2  CC67 2018 2018-10-11       COND 10.5316641186  <NA> #> 8557  2065B     2  CC67 2018 2018-10-11         DO  1.6467336972  <NA> #> 8558  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3148178850     + #> 8559  2065B     2  CC67 2018 2018-10-11       NO23 -4.9618451299     I #> 8560  2065B     2  CC67 2018 2018-10-11      SALIN  3.1654750481  <NA> #> 8561  2065B     2  CC67 2018 2018-10-11        TKN -0.1960148839  <NA> #> 8562  2065B     2  CC67 2018 2018-10-11         TN -0.1875351238  <NA> #> 8563  2065B     2  CC67 2018 2018-10-11         TP -2.1202635362  <NA> #> 8564  2065B     2  CC67 2018 2018-10-11        TSS  1.8453002362  <NA> #> 8565  2065B     2  CC67 2018 2018-10-11       TURB  0.6931471806  <NA> #> 8566  2065B     2  CC67 2018 2018-10-11       COND 10.5317548204  <NA> #> 8567  2065B     2  CC67 2018 2018-10-11         DO  1.6448050563  <NA> #> 8568  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3121405072     + #> 8569  2065B     2  CC67 2018 2018-10-11      SALIN  3.1654750481  <NA> #> 8570  2065B     2  CC67 2018 2018-10-11       COND 10.5326214074  <NA> #> 8571  2065B     2  CC67 2018 2018-10-11         DO  1.6370530795  <NA> #> 8572  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3054155323     + #> 8573  2065B     2  CC67 2018 2018-10-11      SALIN  3.1663185741  <NA> #> 8574  2065B     2  CC67 2019 2019-03-05      CHLAC  1.6094379124  <NA> #> 8575  2065B     2  CC67 2019 2019-03-05       COND 10.4627604245  <NA> #> 8576  2065B     2  CC67 2019 2019-03-05         DO  1.8325814637  <NA> #> 8577  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5163389723     + #> 8578  2065B     2  CC67 2019 2019-03-05       NO23 -5.1159958098     U #> 8579  2065B     2  CC67 2019 2019-03-05      SALIN  3.5550051456  <NA> #> 8580  2065B     2  CC67 2019 2019-03-05        TKN -0.2691874898  <NA> #> 8581  2065B     2  CC67 2019 2019-03-05         TN -0.2691874898  <NA> #> 8582  2065B     2  CC67 2019 2019-03-05         TP -2.3644604967  <NA> #> 8583  2065B     2  CC67 2019 2019-03-05        TSS  1.9919755159  <NA> #> 8584  2065B     2  CC67 2019 2019-03-05       TURB  0.8754687374  <NA> #> 8585  2065B     2  CC67 2019 2019-03-05       COND 10.4628461645  <NA> #> 8586  2065B     2  CC67 2019 2019-03-05         DO  1.8309801824  <NA> #> 8587  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5152454785     + #> 8588  2065B     2  CC67 2019 2019-03-05      SALIN  3.5550908856  <NA> #> 8589  2065B     2  CC67 2019 2019-03-05       COND 10.4631604817  <NA> #> 8590  2065B     2  CC67 2019 2019-03-05         DO  1.8277699068  <NA> #> 8591  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5119578043     + #> 8592  2065B     2  CC67 2019 2019-03-05      SALIN  3.5554052027  <NA> #> 8593  2065B     2  CC67 2020 2020-01-15       COND 10.6506753751  <NA> #> 8594  2065B     2  CC67 2020 2020-01-15         DO  2.0592388344  <NA> #> 8595  2065B     2  CC67 2020 2020-01-15      DOSAT  4.6737629775     + #> 8596  2065B     2  CC67 2020 2020-01-15       NO23 -5.1159958098     U #> 8597  2065B     2  CC67 2020 2020-01-15      SALIN  3.3010086544  <NA> #> 8598  2065B     2  CC67 2020 2020-01-15        TKN -0.4109802888  <NA> #> 8599  2065B     2  CC67 2020 2020-01-15         TN -0.4109802888  <NA> #> 8600  2065B     2  CC67 2020 2020-01-15         TP -2.4304184645  <NA> #> 8601  2065B     2  CC67 2020 2020-01-15        TSS  1.4816045409  <NA> #> 8602  2065B     2  CC67 2020 2020-01-15       TURB  0.0000000000  <NA> #> 8603  2065B     2  CC67 2020 2020-01-15       COND 10.6625933392  <NA> #> 8604  2065B     2  CC67 2020 2020-01-15         DO  2.0630580624  <NA> #> 8605  2065B     2  CC67 2020 2020-01-15      DOSAT  4.6756286496     + #> 8606  2065B     2  CC67 2020 2020-01-15      SALIN  3.3141860047  <NA> #> 8607  2065B     2  CC67 2020 2020-02-11       COND 10.6620033783  <NA> #> 8608  2065B     2  CC67 2020 2020-02-11       NO23 -5.1159958098     U #> 8609  2065B     2  CC67 2020 2020-02-11      SALIN  3.3141860047  <NA> #> 8610  2065B     2  CC67 2020 2020-02-11        TKN -0.3538218750  <NA> #> 8611  2065B     2  CC67 2020 2020-02-11         TN -0.3495574762     + #> 8612  2065B     2  CC67 2020 2020-02-11         TP -2.6036901858  <NA> #> 8613  2065B     2  CC67 2020 2020-02-11        TSS  1.2029723040  <NA> #> 8614  2065B     2  CC67 2020 2020-02-11       TURB -0.2613647641  <NA> #> 8615  2065B     2  CC67 2020 2020-02-11       COND 10.6633887669  <NA> #> 8616  2065B     2  CC67 2020 2020-02-11      SALIN  3.3156394933  <NA> #> 8617  2065B     2  CC67 2020 2020-11-04       COND 10.4405071004  <NA> #> 8618  2065B     2  CC67 2020 2020-11-04         DO  1.8033586051  <NA> #> 8619  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3782695858     + #> 8620  2065B     2  CC67 2020 2020-11-04       NO23 -5.1159958098     U #> 8621  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8622  2065B     2  CC67 2020 2020-11-04        TKN -0.9808292530  <NA> #> 8623  2065B     2  CC67 2020 2020-11-04         TN -0.9808292530  <NA> #> 8624  2065B     2  CC67 2020 2020-11-04         TP -1.9173226922  <NA> #> 8625  2065B     2  CC67 2020 2020-11-04        TSS  3.3322045102  <NA> #> 8626  2065B     2  CC67 2020 2020-11-04       TURB  0.5306282511  <NA> #> 8627  2065B     2  CC67 2020 2020-11-04       COND 10.4404486499  <NA> #> 8628  2065B     2  CC67 2020 2020-11-04         DO  1.8000582720  <NA> #> 8629  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3744983683     + #> 8630  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8631  2065B     2  CC67 2020 2020-11-04       COND 10.4404778756  <NA> #> 8632  2065B     2  CC67 2020 2020-11-04         DO  1.7984040119  <NA> #> 8633  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3732381286     + #> 8634  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8635  2065B     2  CC67 2021 2021-05-17       COND 10.7266756661  <NA> #> 8636  2065B     2  CC67 2021 2021-05-17         DO  1.8976198599  <NA> #> 8637  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5859873666     + #> 8638  2065B     2  CC67 2021 2021-05-17       NO23 -5.1159958098     U #> 8639  2065B     2  CC67 2021 2021-05-17      SALIN  3.3830334110  <NA> #> 8640  2065B     2  CC67 2021 2021-05-17        TKN -0.6520052372  <NA> #> 8641  2065B     2  CC67 2021 2021-05-17         TN -0.6520052372  <NA> #> 8642  2065B     2  CC67 2021 2021-05-17         TP -2.2926347621  <NA> #> 8643  2065B     2  CC67 2021 2021-05-17        TSS  2.7343675094  <NA> #> 8644  2065B     2  CC67 2021 2021-05-17       TURB -0.4416105547  <NA> #> 8645  2065B     2  CC67 2021 2021-05-17       COND 10.7266317622  <NA> #> 8646  2065B     2  CC67 2021 2021-05-17         DO  1.9110228901  <NA> #> 8647  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5991521137     + #> 8648  2065B     2  CC67 2021 2021-05-17      SALIN  3.3830334110  <NA> #> 8649  2065B     2  CC67 2021 2021-05-17       COND 10.7261267283  <NA> #> 8650  2065B     2  CC67 2021 2021-05-17         DO  1.9110228901  <NA> #> 8651  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5991521137     + #> 8652  2065B     2  CC67 2021 2021-05-17      SALIN  3.3823542939  <NA> #> 8653   2081    3F  CC67 2016 2016-04-27      CHLAC  1.7404661748  <NA> #> 8654   2081    3F  CC67 2016 2016-04-27      COLOR  4.2046926194  <NA> #> 8655   2081    3F  CC67 2016 2016-04-27       COND  6.3135480463  <NA> #> 8656   2081    3F  CC67 2016 2016-04-27         DO  2.0918640617  <NA> #> 8657   2081    3F  CC67 2016 2016-04-27      DOSAT  4.5849674787  <NA> #> 8658   2081    3F  CC67 2016 2016-04-27       NO23 -4.3428059215  <NA> #> 8659   2081    3F  CC67 2016 2016-04-27      SALIN -1.3093333200     + #> 8660   2081    3F  CC67 2016 2016-04-27        TKN -0.1625189295  <NA> #> 8661   2081    3F  CC67 2016 2016-04-27         TN -0.1473405879     + #> 8662   2081    3F  CC67 2016 2016-04-27         TP -2.9187712324  <NA> #> 8663   2081    3F  CC67 2016 2016-04-27        TSS  1.0986122887     I #> 8664   2081    3F  CC67 2016 2016-04-27       TURB  1.8870696490  <NA> #> 8665   2081    3F  CC67 2016 2016-09-21      CHLAC  2.2082744135     A #> 8666   2081    3F  CC67 2016 2016-09-21      COLOR  4.9416424226  <NA> #> 8667   2081    3F  CC67 2016 2016-09-21       COND  5.8636311756  <NA> #> 8668   2081    3F  CC67 2016 2016-09-21         DO  1.7227665977  <NA> #> 8669   2081    3F  CC67 2016 2016-09-21      DOSAT  4.3040650932  <NA> #> 8670   2081    3F  CC67 2016 2016-09-21       NO23 -2.9565115604  <NA> #> 8671   2081    3F  CC67 2016 2016-09-21      SALIN -1.6094379124  <NA> #> 8672   2081    3F  CC67 2016 2016-09-21        TKN -0.1863295782  <NA> #> 8673   2081    3F  CC67 2016 2016-09-21         TN -0.1255632230     + #> 8674   2081    3F  CC67 2016 2016-09-21         TP -2.3025850930  <NA> #> 8675   2081    3F  CC67 2016 2016-09-21        TSS  2.8332133441  <NA> #> 8676   2081    3F  CC67 2016 2016-09-21       TURB  2.3025850930  <NA> #> 8677   2081    3F  CC67 2016 2016-12-13      CHLAC  0.5306282511     I #> 8678   2081    3F  CC67 2016 2016-12-13      COLOR  4.0253516907  <NA> #> 8679   2081    3F  CC67 2016 2016-12-13       COND  6.2709884319  <NA> #> 8680   2081    3F  CC67 2016 2016-12-13         DO  2.1860512767  <NA> #> 8681   2081    3F  CC67 2016 2016-12-13      DOSAT  4.5951198501  <NA> #> 8682   2081    3F  CC67 2016 2016-12-13       NO23 -1.8971199849  <NA> #> 8683   2081    3F  CC67 2016 2016-12-13      SALIN -1.6094379124  <NA> #> 8684   2081    3F  CC67 2016 2016-12-13        TKN -0.4942963218  <NA> #> 8685   2081    3F  CC67 2016 2016-12-13         TN -0.2744368457     + #> 8686   2081    3F  CC67 2016 2016-12-13         TP -2.9759296463  <NA> #> 8687   2081    3F  CC67 2016 2016-12-13        TSS  1.3862943611     I #> 8688   2081    3F  CC67 2016 2016-12-13       TURB  1.6486586256  <NA> #> 8689   2081    3F  CC67 2016 2016-12-28      CHLAC  1.0296194172  <NA> #> 8690   2081    3F  CC67 2016 2016-12-28      COLOR  4.1896547420     A #> 8691   2081    3F  CC67 2016 2016-12-28       COND  6.2747620212  <NA> #> 8692   2081    3F  CC67 2016 2016-12-28       NO23 -2.2072749132  <NA> #> 8693   2081    3F  CC67 2016 2016-12-28      SALIN -1.3093333200     + #> 8694   2081    3F  CC67 2016 2016-12-28        TKN -0.4004775666  <NA> #> 8695   2081    3F  CC67 2016 2016-12-28         TN -0.2484613593     + #> 8696   2081    3F  CC67 2016 2016-12-28         TP -2.6882475738  <NA> #> 8697   2081    3F  CC67 2016 2016-12-28        TSS  1.7917594692     I #> 8698   2081    3F  CC67 2016 2016-12-28       TURB  1.9878743482     A #> 8699   2081    3F  CC67 2017 2017-07-26      CHLAC  2.3025850930  <NA> #> 8700   2081    3F  CC67 2017 2017-07-26      COLOR  5.3471075307  <NA> #> 8701   2081    3F  CC67 2017 2017-07-26       COND  5.8435444170  <NA> #> 8702   2081    3F  CC67 2017 2017-07-26         DO  1.6486586256  <NA> #> 8703   2081    3F  CC67 2017 2017-07-26      DOSAT  4.2626798770  <NA> #> 8704   2081    3F  CC67 2017 2017-07-26       NO23 -3.3813947544  <NA> #> 8705   2081    3F  CC67 2017 2017-07-26        TKN  0.0953101798  <NA> #> 8706   2081    3F  CC67 2017 2017-07-26         TN  0.1257512053     + #> 8707   2081    3F  CC67 2017 2017-07-26         TP -2.4191189092  <NA> #> 8708   2081    3F  CC67 2017 2017-07-26        TSS  2.4849066498  <NA> #> 8709   2081    3F  CC67 2017 2017-07-26       TURB  1.9315214116  <NA> #> 8710   2081    3F  CC67 2017 2017-08-21      CHLAC  1.4350845253  <NA> #> 8711   2081    3F  CC67 2017 2017-08-21      COLOR  4.7874917428  <NA> #> 8712   2081    3F  CC67 2017 2017-08-21       COND  6.0497334552  <NA> #> 8713   2081    3F  CC67 2017 2017-08-21         DO  1.9169226122  <NA> #> 8714   2081    3F  CC67 2017 2017-08-21      DOSAT  4.5108595065  <NA> #> 8715   2081    3F  CC67 2017 2017-08-21       NO23 -2.9957322736  <NA> #> 8716   2081    3F  CC67 2017 2017-08-21        TKN -0.1984509387  <NA> #> 8717   2081    3F  CC67 2017 2017-08-21         TN -0.1392620673     + #> 8718   2081    3F  CC67 2017 2017-08-21         TP -2.7488721956  <NA> #> 8719   2081    3F  CC67 2017 2017-08-21        TSS  2.3025850930     I #> 8720   2081    3F  CC67 2017 2017-08-21       TURB  1.9740810260     A #> 8721   2081    3F  CC67 2017 2017-10-04      CHLAC  2.0014800002  <NA> #> 8722   2081    3F  CC67 2017 2017-10-04      COLOR  4.7874917428  <NA> #> 8723   2081    3F  CC67 2017 2017-10-04       COND  5.9188938543  <NA> #> 8724   2081    3F  CC67 2017 2017-10-04         DO  1.8718021769  <NA> #> 8725   2081    3F  CC67 2017 2017-10-04      DOSAT  4.3944491547  <NA> #> 8726   2081    3F  CC67 2017 2017-10-04       NO23 -3.1235656451  <NA> #> 8727   2081    3F  CC67 2017 2017-10-04      SALIN -1.7719568419     + #> 8728   2081    3F  CC67 2017 2017-10-04        TKN -0.2231435513  <NA> #> 8729   2081    3F  CC67 2017 2017-10-04         TN -0.1696027844     + #> 8730   2081    3F  CC67 2017 2017-10-04         TP -2.7488721956  <NA> #> 8731   2081    3F  CC67 2017 2017-10-04        TSS  2.0794415417     I #> 8732   2081    3F  CC67 2017 2017-10-04       TURB  1.6486586256     A #> 8733   2081    3F  CC67 2017 2017-11-08      CHLAC  1.7404661748  <NA> #> 8734   2081    3F  CC67 2017 2017-11-08      COLOR  4.2341065046  <NA> #> 8735   2081    3F  CC67 2017 2017-11-08       COND  6.1377270541  <NA> #> 8736   2081    3F  CC67 2017 2017-11-08         DO  2.1747517215  <NA> #> 8737   2081    3F  CC67 2017 2017-11-08      DOSAT  4.6634390941  <NA> #> 8738   2081    3F  CC67 2017 2017-11-08       NO23 -2.7030626596  <NA> #> 8739   2081    3F  CC67 2017 2017-11-08      SALIN -1.4696759701     + #> 8740   2081    3F  CC67 2017 2017-11-08        TKN -0.4942963218  <NA> #> 8741   2081    3F  CC67 2017 2017-11-08         TN -0.3900840061     + #> 8742   2081    3F  CC67 2017 2017-11-08         TP -3.1235656451  <NA> #> 8743   2081    3F  CC67 2017 2017-11-08        TSS  1.0986122887     I #> 8744   2081    3F  CC67 2017 2017-11-08       TURB  1.5686159179  <NA> #> 8745   2081    3F  CC67 2017 2017-11-30      CHLAC  1.6677068206  <NA> #> 8746   2081    3F  CC67 2017 2017-11-30      COLOR  4.1271343850     A #> 8747   2081    3F  CC67 2017 2017-11-30       COND  6.2519038832  <NA> #> 8748   2081    3F  CC67 2017 2017-11-30         DO  2.3025850930  <NA> #> 8749   2081    3F  CC67 2017 2017-11-30      DOSAT  4.7535901911  <NA> #> 8750   2081    3F  CC67 2017 2017-11-30       NO23 -3.2188758249  <NA> #> 8751   2081    3F  CC67 2017 2017-11-30      SALIN -1.3470736480     + #> 8752   2081    3F  CC67 2017 2017-11-30        TKN -0.5798184953  <NA> #> 8753   2081    3F  CC67 2017 2017-11-30         TN -0.5108256238     + #> 8754   2081    3F  CC67 2017 2017-11-30         TP -3.1700856607  <NA> #> 8755   2081    3F  CC67 2017 2017-11-30        TSS  1.3862943611     I #> 8756   2081    3F  CC67 2017 2017-11-30       TURB  1.5475625087  <NA> #> 8757   2081    3F  CC67 2018 2018-04-12       COND  6.1717005974  <NA> #> 8758   2081    3F  CC67 2018 2018-04-12         DO  2.6461747974  <NA> #> 8759   2081    3F  CC67 2018 2018-04-12      DOSAT  5.1239639794  <NA> #> 8760   2081    3F  CC67 2018 2018-04-12      SALIN -1.4696759701     + #> 8761   2081    3F  CC67 2018 2018-04-19      CHLAC  2.2512917986  <NA> #> 8762   2081    3F  CC67 2018 2018-04-19      COLOR  4.0943445622  <NA> #> 8763   2081    3F  CC67 2018 2018-04-19       COND  6.0980742822  <NA> #> 8764   2081    3F  CC67 2018 2018-04-19         DO  2.7317667277  <NA> #> 8765   2081    3F  CC67 2018 2018-04-19      DOSAT  5.3107398865  <NA> #> 8766   2081    3F  CC67 2018 2018-04-19       NO23 -5.5214609179     U #> 8767   2081    3F  CC67 2018 2018-04-19      SALIN -1.6094379124     + #> 8768   2081    3F  CC67 2018 2018-04-19        TKN -0.3424903089  <NA> #> 8769   2081    3F  CC67 2018 2018-04-19         TN -0.3396773676     + #> 8770   2081    3F  CC67 2018 2018-04-19         TP -4.2686979494  <NA> #> 8771   2081    3F  CC67 2018 2018-04-19        TSS  1.0986122887     I #> 8772   2081    3F  CC67 2018 2018-04-19       TURB  0.4054651081  <NA> #> 8773   2081    3F  CC67 2018 2018-07-17      CHLAC  2.3978952728  <NA> #> 8774   2081    3F  CC67 2018 2018-07-17      COLOR  5.2470240722  <NA> #> 8775   2081    3F  CC67 2018 2018-07-17       COND  5.6559918108  <NA> #> 8776   2081    3F  CC67 2018 2018-07-17         DO  1.6677068206  <NA> #> 8777   2081    3F  CC67 2018 2018-07-17      DOSAT  4.2541932632  <NA> #> 8778   2081    3F  CC67 2018 2018-07-17       NO23 -3.8167128256  <NA> #> 8779   2081    3F  CC67 2018 2018-07-17        TKN -0.0304592075  <NA> #> 8780   2081    3F  CC67 2018 2018-07-17         TN -0.0080321717     + #> 8781   2081    3F  CC67 2018 2018-07-17         TP -2.7968814148  <NA> #> 8782   2081    3F  CC67 2018 2018-07-17        TSS  1.7917594692     I #> 8783   2081    3F  CC67 2018 2018-07-17       TURB  1.7047480922  <NA> #> 8784   2081    3F  CC67 2018 2018-08-01      CHLAC  2.0014800002  <NA> #> 8785   2081    3F  CC67 2018 2018-08-01      COLOR  4.9416424226  <NA> #> 8786   2081    3F  CC67 2018 2018-08-01       COND  5.9269260260  <NA> #> 8787   2081    3F  CC67 2018 2018-08-01         DO  1.8900953699  <NA> #> 8788   2081    3F  CC67 2018 2018-08-01      DOSAT  4.4624538838  <NA> #> 8789   2081    3F  CC67 2018 2018-08-01       NO23 -3.2188758249  <NA> #> 8790   2081    3F  CC67 2018 2018-08-01      SALIN -1.7147984281  <NA> #> 8791   2081    3F  CC67 2018 2018-08-01        TKN -0.2613647641  <NA> #> 8792   2081    3F  CC67 2018 2018-08-01         TN -0.2107210313     + #> 8793   2081    3F  CC67 2018 2018-08-01         TP -2.8824035882  <NA> #> 8794   2081    3F  CC67 2018 2018-08-01        TSS  1.7917594692     I #> 8795   2081    3F  CC67 2018 2018-08-01       TURB  1.7404661748  <NA> #> 8796   2081    3F  CC67 2018 2018-08-01       COND  5.9269260260  <NA> #> 8797   2081    3F  CC67 2018 2018-08-01         DO  1.8900953699  <NA> #> 8798   2081    3F  CC67 2018 2018-08-01      DOSAT  4.4624538838  <NA> #> 8799   2081    3F  CC67 2018 2018-08-01      SALIN -1.7147984281  <NA> #> 8800   2081    3F  CC67 2018 2018-08-20      CHLAC  2.2407096893  <NA> #> 8801   2081    3F  CC67 2018 2018-08-20      COLOR  5.0751738152  <NA> #> 8802   2081    3F  CC67 2018 2018-08-20       COND  5.3706380281  <NA> #> 8803   2081    3F  CC67 2018 2018-08-20         DO  1.5216989981  <NA> #> 8804   2081    3F  CC67 2018 2018-08-20      DOSAT  4.0758410907  <NA> #> 8805   2081    3F  CC67 2018 2018-08-20       NO23 -3.4420193762  <NA> #> 8806   2081    3F  CC67 2018 2018-08-20      SALIN -2.3025850930  <NA> #> 8807   2081    3F  CC67 2018 2018-08-20        TKN -0.0618754037  <NA> #> 8808   2081    3F  CC67 2018 2018-08-20         TN -0.0283994745     + #> 8809   2081    3F  CC67 2018 2018-08-20         TP -2.4534079827  <NA> #> 8810   2081    3F  CC67 2018 2018-08-20        TSS  2.1972245773     I #> 8811   2081    3F  CC67 2018 2018-08-20       TURB  1.9315214116  <NA> #> 8812   2081    3F  CC67 2018 2018-09-10      CHLAC  1.5260563035  <NA> #> 8813   2081    3F  CC67 2018 2018-09-10      COLOR  4.4998096703     A #> 8814   2081    3F  CC67 2018 2018-09-10       COND  6.0520891689  <NA> #> 8815   2081    3F  CC67 2018 2018-09-10         DO  1.9865035460  <NA> #> 8816   2081    3F  CC67 2018 2018-09-10      DOSAT  4.5941092386  <NA> #> 8817   2081    3F  CC67 2018 2018-09-10      SALIN -1.6094379124  <NA> #> 8818   2081    3F  CC67 2018 2018-09-10         TN -0.2057949130     + #> 8819   2081    3F  CC67 2018 2018-09-10        TSS  2.3025850930     A #> 8820   2081    3F  CC67 2018 2018-09-10       TURB  2.0281482473  <NA> #> 8821   2081    3F  CC67 2018 2018-11-12      CHLAC  2.2300144002  <NA> #> 8822   2081    3F  CC67 2018 2018-11-12      COLOR  3.9120230054  <NA> #> 8823   2081    3F  CC67 2018 2018-11-12       COND  6.2595814641  <NA> #> 8824   2081    3F  CC67 2018 2018-11-12         DO  2.1174596089  <NA> #> 8825   2081    3F  CC67 2018 2018-11-12      DOSAT  4.6180864113  <NA> #> 8826   2081    3F  CC67 2018 2018-11-12       NO23 -2.3751557858  <NA> #> 8827   2081    3F  CC67 2018 2018-11-12      SALIN -1.3862943611  <NA> #> 8828   2081    3F  CC67 2018 2018-11-12        TKN -0.2484613593  <NA> #> 8829   2081    3F  CC67 2018 2018-11-12         TN -0.1358197231     + #> 8830   2081    3F  CC67 2018 2018-11-12         TP -2.8473122684  <NA> #> 8831   2081    3F  CC67 2018 2018-11-12        TSS  2.1972245773     I #> 8832   2081    3F  CC67 2018 2018-11-12       TURB  2.0014800002     A #> 8833  2082A    3F  CC70 2018 2018-10-18      CHLAC  0.9932517730  <NA> #> 8834  2082A    3F  CC70 2018 2018-10-18      COLOR  4.2484952420  <NA> #> 8835  2082A    3F  CC70 2018 2018-10-18       COND  5.5721540322  <NA> #> 8836  2082A    3F  CC70 2018 2018-10-18         DO  1.7681496036  <NA> #> 8837  2082A    3F  CC70 2018 2018-10-18      DOSAT  4.3148178850  <NA> #> 8838  2082A    3F  CC70 2018 2018-10-18       NO23 -2.1202635362  <NA> #> 8839  2082A    3F  CC70 2018 2018-10-18      SALIN -2.1202635362  <NA> #> 8840  2082A    3F  CC70 2018 2018-10-18        TKN  0.1823215568  <NA> #> 8841  2082A    3F  CC70 2018 2018-10-18         TN  0.2776317366     + #> 8842  2082A    3F  CC70 2018 2018-10-18         TP -3.0365542681  <NA> #> 8843  2082A    3F  CC70 2018 2018-10-18        TSS  2.3978952728     A #> 8844  2082A    3F  CC70 2018 2018-10-18       TURB  1.9600947840  <NA> #> 8845  2082A    3F  CC70 2019 2019-05-08      CHLAC  0.4054651081     I #> 8846  2082A    3F  CC70 2019 2019-05-08      COLOR  3.5263605246     A #> 8847  2082A    3F  CC70 2019 2019-05-08       COND  6.4167322825  <NA> #> 8848  2082A    3F  CC70 2019 2019-05-08         DO  1.6900958155  <NA> #> 8849  2082A    3F  CC70 2019 2019-05-08      DOSAT  4.2384449062  <NA> #> 8850  2082A    3F  CC70 2019 2019-05-08       NO23 -5.5214609179     U #> 8851  2082A    3F  CC70 2019 2019-05-08      SALIN -1.2039728043  <NA> #> 8852  2082A    3F  CC70 2019 2019-05-08        TKN -0.3011050928  <NA> #> 8853  2082A    3F  CC70 2019 2019-05-08         TN -0.2984060358     + #> 8854  2082A    3F  CC70 2019 2019-05-08         TP -3.1941832123  <NA> #> 8855  2082A    3F  CC70 2019 2019-05-08        TSS  0.6931471806     I #> 8856  2082A    3F  CC70 2019 2019-05-08       TURB  1.2527629685  <NA> #> 8857   2079     2  CC74 2017 2017-03-13       COND 11.1102514581  <NA> #> 8858   2079     2  CC74 2017 2017-03-13         DO  2.0668627595  <NA> #> 8859   2079     2  CC74 2017 2017-03-13      DOSAT  4.8362819070  <NA> #> 8860   2079     2  CC74 2017 2017-03-13      SALIN  3.8066624898  <NA> #> 8861   2079     2  CC74 2017 2017-05-15      CHLAC  0.9162907319  <NA> #> 8862   2079     2  CC74 2017 2017-05-15       COND 10.9460055668  <NA> #> 8863   2079     2  CC74 2017 2017-05-15         DO  1.7917594692  <NA> #> 8864   2079     2  CC74 2017 2017-05-15      DOSAT  4.2341065046  <NA> #> 8865   2079     2  CC74 2017 2017-05-15       NO23 -4.8283137373     U #> 8866   2079     2  CC74 2017 2017-05-15      SALIN  3.5759906720     + #> 8867   2079     2  CC74 2017 2017-05-15        TKN -0.3011050928  <NA> #> 8868   2079     2  CC74 2017 2017-05-15         TN -0.2957142441     + #> 8869   2079     2  CC74 2017 2017-05-15         TP -3.6888794541  <NA> #> 8870   2079     2  CC74 2017 2017-05-15        TSS  1.3862943611     I #> 8871   2079     2  CC74 2017 2017-05-15       TURB  0.0000000000  <NA> #> 8872   2079     2  CC74 2017 2017-07-20      CHLAC  1.5475625087  <NA> #> 8873   2079     2  CC74 2017 2017-07-20       COND 10.6434228946  <NA> #> 8874   2079     2  CC74 2017 2017-07-20         DO  1.5040773968  <NA> #> 8875   2079     2  CC74 2017 2017-07-20      DOSAT  4.2484952420  <NA> #> 8876   2079     2  CC74 2017 2017-07-20       NO23 -5.5214609179     U #> 8877   2079     2  CC74 2017 2017-07-20        TKN -0.0943106795  <NA> #> 8878   2079     2  CC74 2017 2017-07-20         TN -0.0921152889     + #> 8879   2079     2  CC74 2017 2017-07-20         TP -3.4112477175  <NA> #> 8880   2079     2  CC74 2017 2017-07-20        TSS  1.0986122887     U #> 8881   2079     2  CC74 2017 2017-07-20       TURB  0.4054651081  <NA> #> 8882   2079     2  CC74 2017 2017-10-24       COND 10.5655567775  <NA> #> 8883   2079     2  CC74 2017 2017-10-24         DO  1.4586150227  <NA> #> 8884   2079     2  CC74 2017 2017-10-24      DOSAT  4.1431347264  <NA> #> 8885   2079     2  CC74 2017 2017-10-24      SALIN  3.1531632815     + #> 8886   2079     2  CC74 2018 2018-03-15      CHLAC  2.0918640617  <NA> #> 8887   2079     2  CC74 2018 2018-03-15       COND 11.0381102787  <NA> #> 8888   2079     2  CC74 2018 2018-03-15         DO  2.2407096893  <NA> #> 8889   2079     2  CC74 2018 2018-03-15      DOSAT  4.9972122738  <NA> #> 8890   2079     2  CC74 2018 2018-03-15       NO23 -4.1997050779  <NA> #> 8891   2079     2  CC74 2018 2018-03-15        TKN -0.1508228897  <NA> #> 8892   2079     2  CC74 2018 2018-03-15         TN -0.1335313926     + #> 8893   2079     2  CC74 2018 2018-03-15         TP -3.1941832123  <NA> #> 8894   2079     2  CC74 2018 2018-03-15        TSS  1.9459101491     I #> 8895   2079     2  CC74 2018 2018-03-15       TURB  1.0986122887  <NA> #> 8896   2079     2  CC74 2018 2018-04-23      CHLAC  2.7725887222  <NA> #> 8897   2079     2  CC74 2018 2018-04-23       COND 10.9748485413  <NA> #> 8898   2079     2  CC74 2018 2018-04-23         DO  2.2823823857  <NA> #> 8899   2079     2  CC74 2018 2018-04-23      DOSAT  5.0498560072  <NA> #> 8900   2079     2  CC74 2018 2018-04-23       NO23 -5.5214609179     U #> 8901   2079     2  CC74 2018 2018-04-23      SALIN  3.5937442590     + #> 8902   2079     2  CC74 2018 2018-04-23        TKN -0.1984509387  <NA> #> 8903   2079     2  CC74 2018 2018-04-23         TN -0.1960148839     + #> 8904   2079     2  CC74 2018 2018-04-23         TP -3.2441936329  <NA> #> 8905   2079     2  CC74 2018 2018-04-23        TSS  2.4849066498  <NA> #> 8906   2079     2  CC74 2018 2018-04-23       TURB  0.6931471806  <NA> #> 8907   2079     2  CC74 2018 2018-06-11      CHLAC  3.1780538303  <NA> #> 8908   2079     2  CC74 2018 2018-06-11       COND 10.6286177789  <NA> #> 8909   2079     2  CC74 2018 2018-06-11         DO  1.8245492921  <NA> #> 8910   2079     2  CC74 2018 2018-06-11      DOSAT  4.5643481915  <NA> #> 8911   2079     2  CC74 2018 2018-06-11       NO23 -5.5214609179     U #> 8912   2079     2  CC74 2018 2018-06-11      SALIN  3.2695689392  <NA> #> 8913   2079     2  CC74 2018 2018-06-11        TKN -0.0943106795  <NA> #> 8914   2079     2  CC74 2018 2018-06-11         TN -0.0921152889     + #> 8915   2079     2  CC74 2018 2018-06-11         TP -2.9957322736  <NA> #> 8916   2079     2  CC74 2018 2018-06-11        TSS  1.7917594692     I #> 8917   2079     2  CC74 2018 2018-06-11       TURB  1.1314021115  <NA> #> 8918   2079     2  CC74 2018 2018-08-07      CHLAC  1.9600947840  <NA> #> 8919   2079     2  CC74 2018 2018-08-07       COND 10.5844609322  <NA> #> 8920   2079     2  CC74 2018 2018-08-07         DO  1.9387416596  <NA> #> 8921   2079     2  CC74 2018 2018-08-07      DOSAT  4.6709579265  <NA> #> 8922   2079     2  CC74 2018 2018-08-07       NO23 -5.5214609179     U #> 8923   2079     2  CC74 2018 2018-08-07      SALIN  3.2200751054  <NA> #> 8924   2079     2  CC74 2018 2018-08-07        TKN -0.0202027073  <NA> #> 8925   2079     2  CC74 2018 2018-08-07         TN -0.0181639706     + #> 8926   2079     2  CC74 2018 2018-08-07         TP -2.6882475738  <NA> #> 8927   2079     2  CC74 2018 2018-08-07        TSS  1.0986122887     U #> 8928   2079     2  CC74 2018 2018-08-07       TURB  0.4054651081  <NA> #> 8929   2079     2  CC74 2018 2018-09-06      CHLAC  1.6486586256  <NA> #> 8930   2079     2  CC74 2018 2018-09-06       COND 10.3441267357  <NA> #> 8931   2079     2  CC74 2018 2018-09-06         DO  1.4231083342  <NA> #> 8932   2079     2  CC74 2018 2018-09-06      DOSAT  4.1026433650  <NA> #> 8933   2079     2  CC74 2018 2018-09-06       NO23 -5.5214609179     U #> 8934   2079     2  CC74 2018 2018-09-06      SALIN  2.9559514035  <NA> #> 8935   2079     2  CC74 2018 2018-09-06        TKN  0.7419373447  <NA> #> 8936   2079     2  CC74 2018 2018-09-06         TN  0.7428892725     + #> 8937   2079     2  CC74 2018 2018-09-06         TP -2.5770219387  <NA> #> 8938   2079     2  CC74 2018 2018-09-06        TSS  1.0986122887     I #> 8939   2079     2  CC74 2018 2018-09-06       TURB  0.0953101798  <NA> #> 8940   2079     2  CC74 2019 2019-04-17      CHLAC  2.1162555148  <NA> #> 8941   2079     2  CC74 2019 2019-04-17       COND 10.8549137412  <NA> #> 8942   2079     2  CC74 2019 2019-04-17         DO  2.2159372863  <NA> #> 8943   2079     2  CC74 2019 2019-04-17      DOSAT  4.9236239171  <NA> #> 8944   2079     2  CC74 2019 2019-04-17       NO23 -5.5214609179     U #> 8945   2079     2  CC74 2019 2019-04-17      SALIN  3.5269485870  <NA> #> 8946   2079     2  CC74 2019 2019-04-17        TKN -0.1278333715  <NA> #> 8947   2079     2  CC74 2019 2019-04-17         TN -0.1255632230     + #> 8948   2079     2  CC74 2019 2019-04-17         TP -3.4737680745  <NA> #> 8949   2079     2  CC74 2019 2019-04-17        TSS  3.4011973817  <NA> #> 8950   2079     2  CC74 2019 2019-04-17       TURB -0.2231435513  <NA> #> 8951   2079     2  CC74 2019 2019-07-15      CHLAC  3.7612001157  <NA> #> 8952   2079     2  CC74 2019 2019-07-15       COND 10.6353745614  <NA> #> 8953   2079     2  CC74 2019 2019-07-15         DO  1.9796212064  <NA> #> 8954   2079     2  CC74 2019 2019-07-15      DOSAT  4.7104306966  <NA> #> 8955   2079     2  CC74 2019 2019-07-15       NO23 -5.5214609179     U #> 8956   2079     2  CC74 2019 2019-07-15      SALIN  3.2782761681  <NA> #> 8957   2079     2  CC74 2019 2019-07-15        TKN  0.0953101798  <NA> #> 8958   2079     2  CC74 2019 2019-07-15         TN  0.0971267107     + #> 8959   2079     2  CC74 2019 2019-07-15         TP -2.7806208939  <NA> #> 8960   2079     2  CC74 2019 2019-07-15        TSS  2.8332133441  <NA> #> 8961   2079     2  CC74 2019 2019-07-15       TURB  1.6094379124  <NA> #> 8962   2079     2  CC74 2019 2019-08-19      CHLAC  2.4849066498  <NA> #> 8963   2079     2  CC74 2019 2019-08-19       COND 10.4673514473  <NA> #> 8964   2079     2  CC74 2019 2019-08-19         DO  1.3635373740  <NA> #> 8965   2079     2  CC74 2019 2019-08-19      DOSAT  4.0826093060  <NA> #> 8966   2079     2  CC74 2019 2019-08-19       NO23 -5.5214609179     U #> 8967   2079     2  CC74 2019 2019-08-19      SALIN  3.0901329490  <NA> #> 8968   2079     2  CC74 2019 2019-08-19        TKN  0.4054651081  <NA> #> 8969   2079     2  CC74 2019 2019-08-19         TN  0.4067975533     + #> 8970   2079     2  CC74 2019 2019-08-19         TP -3.2968373663  <NA> #> 8971   2079     2  CC74 2019 2019-08-19        TSS  2.4849066498  <NA> #> 8972   2079     2  CC74 2019 2019-08-19       TURB  0.7419373447  <NA> #> 8973   2079     2  CC74 2019 2019-09-11      CHLAC  2.9444389792  <NA> #> 8974   2079     2  CC74 2019 2019-09-11       COND 10.7330214205  <NA> #> 8975   2079     2  CC74 2019 2019-09-11         DO  1.7783364489  <NA> #> 8976   2079     2  CC74 2019 2019-09-11      DOSAT  4.5152454785  <NA> #> 8977   2079     2  CC74 2019 2019-09-11       NO23 -5.5214609179     U #> 8978   2079     2  CC74 2019 2019-09-11      SALIN  3.3874364664  <NA> #> 8979   2079     2  CC74 2019 2019-09-11        TKN -0.0100503359  <NA> #> 8980   2079     2  CC74 2019 2019-09-11         TN -0.0080321717     + #> 8981   2079     2  CC74 2019 2019-09-11         TP -2.8647040111  <NA> #> 8982   2079     2  CC74 2019 2019-09-11        TSS  1.3862943611     I #> 8983   2079     2  CC74 2019 2019-09-11       TURB  0.7884573604  <NA> #> 8984   2079     2  CC74 2019 2019-10-09      CHLAC  3.4339872045  <NA> #> 8985   2079     2  CC74 2019 2019-10-09       COND 10.7419897010  <NA> #> 8986   2079     2  CC74 2019 2019-10-09         DO  1.5432981099  <NA> #> 8987   2079     2  CC74 2019 2019-10-09      DOSAT  4.2640873368  <NA> #> 8988   2079     2  CC74 2019 2019-10-09       NO23 -5.5214609179     U #> 8989   2079     2  CC74 2019 2019-10-09      SALIN  3.3981928726  <NA> #> 8990   2079     2  CC74 2019 2019-10-09        TKN -0.1278333715  <NA> #> 8991   2079     2  CC74 2019 2019-10-09         TN -0.1255632230     + #> 8992   2079     2  CC74 2019 2019-10-09         TP -2.8302178351  <NA> #> 8993   2079     2  CC74 2019 2019-10-09        TSS  1.9459101491     I #> 8994   2079     2  CC74 2019 2019-10-09       TURB  0.6931471806  <NA> #> 8995   2079     2  CC74 2020 2020-02-13      CHLAC  2.3978952728  <NA> #> 8996   2079     2  CC74 2020 2020-02-13       COND 10.7930235471  <NA> #> 8997   2079     2  CC74 2020 2020-02-13         DO  2.0464016876  <NA> #> 8998   2079     2  CC74 2020 2020-02-13      DOSAT  4.7388265708  <NA> #> 8999   2079     2  CC74 2020 2020-02-13       NO23 -5.5214609179     U #> 9000   2079     2  CC74 2020 2020-02-13      SALIN  3.4575777151  <NA> #> 9001   2079     2  CC74 2020 2020-02-13        TKN -0.0512932944  <NA> #> 9002   2079     2  CC74 2020 2020-02-13         TN -0.0491902442     + #> 9003   2079     2  CC74 2020 2020-02-13         TP -3.0365542681  <NA> #> 9004   2079     2  CC74 2020 2020-02-13        TSS  2.3025850930     I #> 9005   2079     2  CC74 2020 2020-02-13       TURB  0.6931471806  <NA> #> 9006   2079     2  CC74 2020 2020-03-24      CHLAC  2.0014800002  <NA> #> 9007   2079     2  CC74 2020 2020-03-24       COND 10.9585136130  <NA> #> 9008   2079     2  CC74 2020 2020-03-24         DO  1.8115620965  <NA> #> 9009   2079     2  CC74 2020 2020-03-24      DOSAT  4.5664293577  <NA> #> 9010   2079     2  CC74 2020 2020-03-24       NO23 -5.5214609179     U #> 9011   2079     2  CC74 2020 2020-03-24      SALIN  3.6425737012  <NA> #> 9012   2079     2  CC74 2020 2020-03-24        TKN -0.0512932944  <NA> #> 9013   2079     2  CC74 2020 2020-03-24         TN -0.0491902442     + #> 9014   2079     2  CC74 2020 2020-03-24         TP -3.3242363405  <NA> #> 9015   2079     2  CC74 2020 2020-03-24        TSS  1.6094379124     I #> 9016   2079     2  CC74 2020 2020-03-24       TURB  0.7419373447  <NA> #> 9017   2079     2  CC74 2020 2020-06-15      CHLAC  3.1354942159  <NA> #> 9018   2079     2  CC74 2020 2020-06-15       COND 10.7369834598  <NA> #> 9019   2079     2  CC74 2020 2020-06-15         DO  0.5822156199  <NA> #> 9020   2079     2  CC74 2020 2020-06-15      DOSAT  3.3141860047  <NA> #> 9021   2079     2  CC74 2020 2020-06-15       NO23 -5.5214609179     U #> 9022   2079     2  CC74 2020 2020-06-15      SALIN  3.3924929410  <NA> #> 9023   2079     2  CC74 2020 2020-06-15        TKN  0.3364722366  <NA> #> 9024   2079     2  CC74 2020 2020-06-15         TN  0.3378997886     + #> 9025   2079     2  CC74 2020 2020-06-15         TP -2.7488721956  <NA> #> 9026   2079     2  CC74 2020 2020-06-15        TSS  1.3862943611     I #> 9027   2079     2  CC74 2020 2020-06-15       TURB  2.0668627595  <NA> #> 9028   2079     2  CC74 2020 2020-07-27      CHLAC  3.4339872045  <NA> #> 9029   2079     2  CC74 2020 2020-07-27       COND 10.7988201898  <NA> #> 9030   2079     2  CC74 2020 2020-07-27         DO  1.9572739077  <NA> #> 9031   2079     2  CC74 2020 2020-07-27      DOSAT  4.7326835063  <NA> #> 9032   2079     2  CC74 2020 2020-07-27       NO23 -5.5214609179     U #> 9033   2079     2  CC74 2020 2020-07-27      SALIN  3.4594662898  <NA> #> 9034   2079     2  CC74 2020 2020-07-27        TKN  0.0000000000  <NA> #> 9035   2079     2  CC74 2020 2020-07-27         TN  0.0019980027     + #> 9036   2079     2  CC74 2020 2020-07-27         TP -3.1700856607  <NA> #> 9037   2079     2  CC74 2020 2020-07-27        TSS  1.7917594692     I #> 9038   2079     2  CC74 2020 2020-07-27       TURB  1.2809338455  <NA> #> 9039   2079     2  CC74 2023 2023-02-13      CHLAC  3.3672958300  <NA> #> 9040   2079     2  CC74 2023 2023-02-13       COND 10.8175959048  <NA> #> 9041   2079     2  CC74 2023 2023-02-13         DO  1.8277699068  <NA> #> 9042   2079     2  CC74 2023 2023-02-13      DOSAT  4.4091553021  <NA> #> 9043   2079     2  CC74 2023 2023-02-13       NO23 -5.5214609179     U #> 9044   2079     2  CC74 2023 2023-02-13      SALIN  3.4879865117  <NA> #> 9045   2079     2  CC74 2023 2023-02-13        TKN  0.2623642645  <NA> #> 9046   2079     2  CC74 2023 2023-02-13         TN  0.2639015438     + #> 9047   2079     2  CC74 2023 2023-02-13         TP -2.2072749132  <NA> #> 9048   2079     2  CC74 2023 2023-02-13        TSS  2.8903717579     A #> 9049   2079     2  CC74 2023 2023-02-13       TURB  1.4350845253  <NA> #> 9050   2079     2  CC74 2023 2023-04-10       COND 10.9901959367  <NA> #> 9051   2079     2  CC74 2023 2023-04-10         DO  1.6714733034  <NA> #> 9052   2079     2  CC74 2023 2023-04-10      DOSAT  4.3770140929  <NA> #> 9053   2079     2  CC74 2023 2023-04-10       NO23 -5.5214609179     U #> 9054   2079     2  CC74 2023 2023-04-10      SALIN  3.6810992668  <NA> #> 9055   2079     2  CC74 2023 2023-04-10        TKN -0.0618754037  <NA> #> 9056   2079     2  CC74 2023 2023-04-10         TN -0.0597500044     + #> 9057   2079     2  CC74 2023 2023-04-10         TP -3.4737680745  <NA> #> 9058   2079     2  CC74 2023 2023-04-10        TSS  1.3862943611     I #> 9059   2079     2  CC74 2014 2014-03-26      SALIN  3.5351453542  <NA> #> 9060   2079     2  CC74 2014 2014-03-26      SALIN  3.5351453542  <NA> #> 9061   2079     2  CC74 2014 2014-07-22      SALIN  3.4719664526  <NA> #> 9062   2079     2  CC74 2014 2014-07-22      SALIN  3.4719664526  <NA> #> 9063   2079     2  CC74 2014 2014-09-11         DO  1.5475625087  <NA> #> 9064   2079     2  CC74 2014 2014-09-11      DOSAT  4.3280982926     + #> 9065   2079     2  CC74 2014 2014-09-11      SALIN  3.4011973817  <NA> #> 9066   2079     2  CC74 2015 2015-09-14      SALIN  3.1986731176  <NA> #> 9067   2079     2  CC74 2015 2015-09-14      SALIN  3.1986731176  <NA> #> 9068   2079     2  CC74 2016 2016-05-18         DO  2.1282317058  <NA> #> 9069   2079     2  CC74 2016 2016-05-18      DOSAT  4.8933521335     + #> 9070   2079     2  CC74 2016 2016-05-18      SALIN  3.5145260670  <NA> #> 9071   2079     2  CC74 2016 2016-05-18         DO  2.2721258855  <NA> #> 9072   2079     2  CC74 2016 2016-05-18      DOSAT  5.0395466376     + #> 9073   2079     2  CC74 2016 2016-05-18      SALIN  3.5174978374  <NA> #> 9074   2079     2  CC74 2016 2016-08-01         DO  2.1282317058  <NA> #> 9075   2079     2  CC74 2016 2016-08-01      DOSAT  4.9243509255     + #> 9076   2079     2  CC74 2016 2016-08-01      SALIN  3.4531571206  <NA> #> 9077   2079     2  CC74 2016 2016-08-01         DO  2.1162555148  <NA> #> 9078   2079     2  CC74 2016 2016-08-01      DOSAT  4.9170569471     + #> 9079   2079     2  CC74 2016 2016-08-01      SALIN  3.4995332824  <NA> #> 9080   2079     2  CC74 2016 2016-08-17         DO  2.0014800002  <NA> #> 9081   2079     2  CC74 2016 2016-08-17      DOSAT  4.7578912730     + #> 9082   2079     2  CC74 2016 2016-08-17      SALIN  3.3357695763  <NA> #> 9083   2079     2  CC74 2016 2016-08-17         DO  1.9021075264  <NA> #> 9084   2079     2  CC74 2016 2016-08-17      DOSAT  4.6672055769     + #> 9085   2079     2  CC74 2016 2016-08-17      SALIN  3.4111477125  <NA> #> 9086   2079     2  CC74 2016 2016-09-08         DO  1.9459101491  <NA> #> 9087   2079     2  CC74 2016 2016-09-08      DOSAT  4.6463121293     + #> 9088   2079     2  CC74 2016 2016-09-08      SALIN  3.0492730405  <NA> #> 9089   2079     2  CC74 2016 2016-09-08         DO  1.7749523509  <NA> #> 9090   2079     2  CC74 2016 2016-09-08      DOSAT  4.5009201646     + #>      newComment disqual disqual2 #> 1          <NA>      NA       NA #> 2             U      NA       NA #> 3             +      NA       NA #> 4             U      NA       NA #> 5          <NA>      NA       NA #> 6          <NA>      NA       NA #> 7             +      NA       NA #> 8          <NA>      NA       NA #> 9          <NA>      NA       NA #> 10            I      NA       NA #> 11            U      NA       NA #> 12         <NA>      NA       NA #> 13            +      NA       NA #> 14            I      NA       NA #> 15         <NA>      NA       NA #> 16         <NA>      NA       NA #> 17            +      NA       NA #> 18         <NA>      NA       NA #> 19         <NA>      NA       NA #> 20         <NA>      NA       NA #> 21         <NA>      NA       NA #> 22         <NA>      NA       NA #> 23            +      NA       NA #> 24            I      NA       NA #> 25         <NA>      NA       NA #> 26         <NA>      NA       NA #> 27            +      NA       NA #> 28         <NA>      NA       NA #> 29            A      NA       NA #> 30         <NA>      NA       NA #> 31         <NA>      NA       NA #> 32         <NA>      NA       NA #> 33            +      NA       NA #> 34            I      NA       NA #> 35         <NA>      NA       NA #> 36         <NA>      NA       NA #> 37            +      NA       NA #> 38         <NA>      NA       NA #> 39         <NA>      NA       NA #> 40         <NA>      NA       NA #> 41         <NA>      NA       NA #> 42         <NA>      NA       NA #> 43            U      NA       NA #> 44         <NA>      NA       NA #> 45            +      NA       NA #> 46         <NA>      NA       NA #> 47         <NA>      NA       NA #> 48         <NA>      NA       NA #> 49         <NA>      NA       NA #> 50         <NA>      NA       NA #> 51            +      NA       NA #> 52            U      NA       NA #> 53         <NA>      NA       NA #> 54            +      NA       NA #> 55         <NA>      NA       NA #> 56         <NA>      NA       NA #> 57         <NA>      NA       NA #> 58         <NA>      NA       NA #> 59            +      NA       NA #> 60            I      NA       NA #> 61         <NA>      NA       NA #> 62         <NA>      NA       NA #> 63            +      NA       NA #> 64         <NA>      NA       NA #> 65         <NA>      NA       NA #> 66         <NA>      NA       NA #> 67         <NA>      NA       NA #> 68            +      NA       NA #> 69         <NA>      NA       NA #> 70         <NA>      NA       NA #> 71         <NA>      NA       NA #> 72            +      NA       NA #> 73         <NA>      NA       NA #> 74         <NA>      NA       NA #> 75            A      NA       NA #> 76            A      NA       NA #> 77            +      NA       NA #> 78         <NA>      NA       NA #> 79         <NA>      NA       NA #> 80         <NA>      NA       NA #> 81            +      NA       NA #> 82         <NA>      NA       NA #> 83         <NA>      NA       NA #> 84         <NA>      NA       NA #> 85            A      NA       NA #> 86            +      NA       NA #> 87         <NA>      NA       NA #> 88         <NA>      NA       NA #> 89         <NA>      NA       NA #> 90            +      NA       NA #> 91         <NA>      NA       NA #> 92         <NA>      NA       NA #> 93         <NA>      NA       NA #> 94         <NA>      NA       NA #> 95         <NA>      NA       NA #> 96            +      NA       NA #> 97            I      NA       NA #> 98         <NA>      NA       NA #> 99         <NA>      NA       NA #> 100           +      NA       NA #> 101        <NA>      NA       NA #> 102        <NA>      NA       NA #> 103           I      NA       NA #> 104           U      NA       NA #> 105        <NA>      NA       NA #> 106           +      NA       NA #> 107           I      NA       NA #> 108        <NA>      NA       NA #> 109           I      NA       NA #> 110           +      NA       NA #> 111        <NA>      NA       NA #> 112        <NA>      NA       NA #> 113        <NA>      NA       NA #> 114        <NA>      NA       NA #> 115        <NA>      NA       NA #> 116           +      NA       NA #> 117           U      NA       NA #> 118        <NA>      NA       NA #> 119        <NA>      NA       NA #> 120           +      NA       NA #> 121        <NA>      NA       NA #> 122        <NA>      NA       NA #> 123        <NA>      NA       NA #> 124        <NA>      NA       NA #> 125        <NA>      NA       NA #> 126           +      NA       NA #> 127           U      NA       NA #> 128        <NA>      NA       NA #> 129           I      NA       NA #> 130           +      NA       NA #> 131        <NA>      NA       NA #> 132        <NA>      NA       NA #> 133        <NA>      NA       NA #> 134        <NA>      NA       NA #> 135        <NA>      NA       NA #> 136           +      NA       NA #> 137        <NA>      NA       NA #> 138        <NA>      NA       NA #> 139        <NA>      NA       NA #> 140           +      NA       NA #> 141        <NA>      NA       NA #> 142        <NA>      NA       NA #> 143        <NA>      NA       NA #> 144        <NA>      NA       NA #> 145        <NA>      NA       NA #> 146           +      NA       NA #> 147        <NA>      NA       NA #> 148        <NA>      NA       NA #> 149        <NA>      NA       NA #> 150           +      NA       NA #> 151        <NA>      NA       NA #> 152        <NA>      NA       NA #> 153        <NA>      NA       NA #> 154        <NA>      NA       NA #> 155        <NA>      NA       NA #> 156           +      NA       NA #> 157        <NA>      NA       NA #> 158        <NA>      NA       NA #> 159        <NA>      NA       NA #> 160           +      NA       NA #> 161        <NA>      NA       NA #> 162        <NA>      NA       NA #> 163        <NA>      NA       NA #> 164        <NA>      NA       NA #> 165        <NA>      NA       NA #> 166           +      NA       NA #> 167        <NA>      NA       NA #> 168        <NA>      NA       NA #> 169        <NA>      NA       NA #> 170           +      NA       NA #> 171        <NA>      NA       NA #> 172        <NA>      NA       NA #> 173        <NA>      NA       NA #> 174        <NA>      NA       NA #> 175        <NA>      NA       NA #> 176           +      NA       NA #> 177        <NA>      NA       NA #> 178        <NA>      NA       NA #> 179        <NA>      NA       NA #> 180           +      NA       NA #> 181        <NA>      NA       NA #> 182        <NA>      NA       NA #> 183        <NA>      NA       NA #> 184        <NA>      NA       NA #> 185        <NA>      NA       NA #> 186           +      NA       NA #> 187           I      NA       NA #> 188        <NA>      NA       NA #> 189        <NA>      NA       NA #> 190           +      NA       NA #> 191        <NA>      NA       NA #> 192        <NA>      NA       NA #> 193        <NA>      NA       NA #> 194        <NA>      NA       NA #> 195        <NA>      NA       NA #> 196           +      NA       NA #> 197        <NA>      NA       NA #> 198        <NA>      NA       NA #> 199        <NA>      NA       NA #> 200           +      NA       NA #> 201        <NA>      NA       NA #> 202        <NA>      NA       NA #> 203           I      NA       NA #> 204        <NA>      NA       NA #> 205        <NA>      NA       NA #> 206           +      NA       NA #> 207           U      NA       NA #> 208        <NA>      NA       NA #> 209           I      NA       NA #> 210           +      NA       NA #> 211        <NA>      NA       NA #> 212        <NA>      NA       NA #> 213        <NA>      NA       NA #> 214        <NA>      NA       NA #> 215        <NA>      NA       NA #> 216           +      NA       NA #> 217           I      NA       NA #> 218        <NA>      NA       NA #> 219        <NA>      NA       NA #> 220           +      NA       NA #> 221        <NA>      NA       NA #> 222        <NA>      NA       NA #> 223        <NA>      NA       NA #> 224        <NA>      NA       NA #> 225        <NA>      NA       NA #> 226           +      NA       NA #> 227        <NA>      NA       NA #> 228        <NA>      NA       NA #> 229        <NA>      NA       NA #> 230           +      NA       NA #> 231        <NA>      NA       NA #> 232        <NA>      NA       NA #> 233        <NA>      NA       NA #> 234        <NA>      NA       NA #> 235        <NA>      NA       NA #> 236           +      NA       NA #> 237           I      NA       NA #> 238        <NA>      NA       NA #> 239        <NA>      NA       NA #> 240           +      NA       NA #> 241        <NA>      NA       NA #> 242        <NA>      NA       NA #> 243        <NA>      NA       NA #> 244        <NA>      NA       NA #> 245        <NA>      NA       NA #> 246           +      NA       NA #> 247        <NA>      NA       NA #> 248        <NA>      NA       NA #> 249        <NA>      NA       NA #> 250           +      NA       NA #> 251        <NA>      NA       NA #> 252        <NA>      NA       NA #> 253           I      NA       NA #> 254           U      NA       NA #> 255        <NA>      NA       NA #> 256           +      NA       NA #> 257           I      NA       NA #> 258        <NA>      NA       NA #> 259        <NA>      NA       NA #> 260           +      NA       NA #> 261        <NA>      NA       NA #> 262        <NA>      NA       NA #> 263        <NA>      NA       NA #> 264           I      NA       NA #> 265        <NA>      NA       NA #> 266           +      NA       NA #> 267        <NA>      NA       NA #> 268        <NA>      NA       NA #> 269        <NA>      NA       NA #> 270           +      NA       NA #> 271        <NA>      NA       NA #> 272        <NA>      NA       NA #> 273           I      NA       NA #> 274           U      NA       NA #> 275        <NA>      NA       NA #> 276           +      NA       NA #> 277           U      NA       NA #> 278        <NA>      NA       NA #> 279        <NA>      NA       NA #> 280           +      NA       NA #> 281        <NA>      NA       NA #> 282        <NA>      NA       NA #> 283        <NA>      NA       NA #> 284        <NA>      NA       NA #> 285           +      NA       NA #> 286        <NA>      NA       NA #> 287           I      NA       NA #> 288        <NA>      NA       NA #> 289        <NA>      NA       NA #> 290           +      NA       NA #> 291           I      NA       NA #> 292        <NA>      NA       NA #> 293        <NA>      NA       NA #> 294           +      NA       NA #> 295        <NA>      NA       NA #> 296        <NA>      NA       NA #> 297        <NA>      NA       NA #> 298           +      NA       NA #> 299        <NA>      NA       NA #> 300        <NA>      NA       NA #> 301           A      NA       NA #> 302        <NA>      NA       NA #> 303           +      NA       NA #> 304           I      NA       NA #> 305        <NA>      NA       NA #> 306        <NA>      NA       NA #> 307           +      NA       NA #> 308        <NA>      NA       NA #> 309        <NA>      NA       NA #> 310        <NA>      NA       NA #> 311        <NA>      NA       NA #> 312        <NA>      NA       NA #> 313           +      NA       NA #> 314        <NA>      NA       NA #> 315        <NA>      NA       NA #> 316        <NA>      NA       NA #> 317           +      NA       NA #> 318        <NA>      NA       NA #> 319           A      NA       NA #> 320        <NA>      NA       NA #> 321        <NA>      NA       NA #> 322           I      NA       NA #> 323        <NA>      NA       NA #> 324           +      NA       NA #> 325        <NA>      NA       NA #> 326        <NA>      NA       NA #> 327        <NA>      NA       NA #> 328        <NA>      NA       NA #> 329        <NA>      NA       NA #> 330           +      NA       NA #> 331        <NA>      NA       NA #> 332        <NA>      NA       NA #> 333        <NA>      NA       NA #> 334           +      NA       NA #> 335        <NA>      NA       NA #> 336        <NA>      NA       NA #> 337           I      NA       NA #> 338        <NA>      NA       NA #> 339        <NA>      NA       NA #> 340           +      NA       NA #> 341           I      NA       NA #> 342        <NA>      NA       NA #> 343        <NA>      NA       NA #> 344           +      NA       NA #> 345        <NA>      NA       NA #> 346        <NA>      NA       NA #> 347           I      NA       NA #> 348        <NA>      NA       NA #> 349        <NA>      NA       NA #> 350           +      NA       NA #> 351        <NA>      NA       NA #> 352        <NA>      NA       NA #> 353        <NA>      NA       NA #> 354           +      NA       NA #> 355        <NA>      NA       NA #> 356        <NA>      NA       NA #> 357        <NA>      NA       NA #> 358        <NA>      NA       NA #> 359        <NA>      NA       NA #> 360           +      NA       NA #> 361        <NA>      NA       NA #> 362        <NA>      NA       NA #> 363        <NA>      NA       NA #> 364           +      NA       NA #> 365        <NA>      NA       NA #> 366           A      NA       NA #> 367           I      NA       NA #> 368        <NA>      NA       NA #> 369        <NA>      NA       NA #> 370           +      NA       NA #> 371           U      NA       NA #> 372        <NA>      NA       NA #> 373        <NA>      NA       NA #> 374           +      NA       NA #> 375        <NA>      NA       NA #> 376        <NA>      NA       NA #> 377           I      NA       NA #> 378           I      NA       NA #> 379           +      NA       NA #> 380           U      NA       NA #> 381        <NA>      NA       NA #> 382        <NA>      NA       NA #> 383           +      NA       NA #> 384        <NA>      NA       NA #> 385        <NA>      NA       NA #> 386        <NA>      NA       NA #> 387        <NA>      NA       NA #> 388        <NA>      NA       NA #> 389        <NA>      NA       NA #> 390           U      NA       NA #> 391        <NA>      NA       NA #> 392        <NA>      NA       NA #> 393           +      NA       NA #> 394        <NA>      NA       NA #> 395        <NA>      NA       NA #> 396        <NA>      NA       NA #> 397        <NA>      NA       NA #> 398        <NA>      NA       NA #> 399        <NA>      NA       NA #> 400        <NA>      NA       NA #> 401        <NA>      NA       NA #> 402        <NA>      NA       NA #> 403           +      NA       NA #> 404        <NA>      NA       NA #> 405        <NA>      NA       NA #> 406        <NA>      NA       NA #> 407        <NA>      NA       NA #> 408        <NA>      NA       NA #> 409        <NA>      NA       NA #> 410           I      NA       NA #> 411        <NA>      NA       NA #> 412        <NA>      NA       NA #> 413           +      NA       NA #> 414        <NA>      NA       NA #> 415        <NA>      NA       NA #> 416           I      NA       NA #> 417        <NA>      NA       NA #> 418        <NA>      NA       NA #> 419        <NA>      NA       NA #> 420        <NA>      NA       NA #> 421        <NA>      NA       NA #> 422        <NA>      NA       NA #> 423           +      NA       NA #> 424        <NA>      NA       NA #> 425        <NA>      NA       NA #> 426           I      NA       NA #> 427        <NA>      NA       NA #> 428        <NA>      NA       NA #> 429        <NA>      NA       NA #> 430           I      NA       NA #> 431        <NA>      NA       NA #> 432           +      NA       NA #> 433        <NA>      NA       NA #> 434        <NA>      NA       NA #> 435        <NA>      NA       NA #> 436        <NA>      NA       NA #> 437        <NA>      NA       NA #> 438        <NA>      NA       NA #> 439           I      NA       NA #> 440        <NA>      NA       NA #> 441           I      NA       NA #> 442           +      NA       NA #> 443        <NA>      NA       NA #> 444        <NA>      NA       NA #> 445           I      NA       NA #> 446           I      NA       NA #> 447        <NA>      NA       NA #> 448        <NA>      NA       NA #> 449           I      NA       NA #> 450        <NA>      NA       NA #> 451        <NA>      NA       NA #> 452           +      NA       NA #> 453        <NA>      NA       NA #> 454        <NA>      NA       NA #> 455           I      NA       NA #> 456        <NA>      NA       NA #> 457        <NA>      NA       NA #> 458        <NA>      NA       NA #> 459           I      NA       NA #> 460        <NA>      NA       NA #> 461        <NA>      NA       NA #> 462           +      NA       NA #> 463        <NA>      NA       NA #> 464        <NA>      NA       NA #> 465        <NA>      NA       NA #> 466           I      NA       NA #> 467        <NA>      NA       NA #> 468        <NA>      NA       NA #> 469           I      NA       NA #> 470        <NA>      NA       NA #> 471        <NA>      NA       NA #> 472           +      NA       NA #> 473        <NA>      NA       NA #> 474        <NA>      NA       NA #> 475        <NA>      NA       NA #> 476           I      NA       NA #> 477        <NA>      NA       NA #> 478        <NA>      NA       NA #> 479        <NA>      NA       NA #> 480        <NA>      NA       NA #> 481        <NA>      NA       NA #> 482           +      NA       NA #> 483        <NA>      NA       NA #> 484        <NA>      NA       NA #> 485           I      NA       NA #> 486           U      NA       NA #> 487           I      NA       NA #> 488        <NA>      NA       NA #> 489           +      NA       NA #> 490        <NA>      NA       NA #> 491        <NA>      NA       NA #> 492           I      NA       NA #> 493        <NA>      NA       NA #> 494        <NA>      NA       NA #> 495        <NA>      NA       NA #> 496        <NA>      NA       NA #> 497        <NA>      NA       NA #> 498        <NA>      NA       NA #> 499           +      NA       NA #> 500        <NA>      NA       NA #> 501        <NA>      NA       NA #> 502           U      NA       NA #> 503           I      NA       NA #> 504        <NA>      NA       NA #> 505        <NA>      NA       NA #> 506        <NA>      NA       NA #> 507        <NA>      NA       NA #> 508        <NA>      NA       NA #> 509           +      NA       NA #> 510        <NA>      NA       NA #> 511        <NA>      NA       NA #> 512           I      NA       NA #> 513           I      NA       NA #> 514        <NA>      NA       NA #> 515        <NA>      NA       NA #> 516           U      NA       NA #> 517        <NA>      NA       NA #> 518           I      NA       NA #> 519           +      NA       NA #> 520        <NA>      NA       NA #> 521        <NA>      NA       NA #> 522           I      NA       NA #> 523           I      NA       NA #> 524        <NA>      NA       NA #> 525        <NA>      NA       NA #> 526        <NA>      NA       NA #> 527           +      NA       NA #> 528        <NA>      NA       NA #> 529           A      NA       NA #> 530           I      NA       NA #> 531           I      NA       NA #> 532        <NA>      NA       NA #> 533        <NA>      NA       NA #> 534           U      NA       NA #> 535        <NA>      NA       NA #> 536           I      NA       NA #> 537           +      NA       NA #> 538        <NA>      NA       NA #> 539        <NA>      NA       NA #> 540        <NA>      NA       NA #> 541           I      NA       NA #> 542        <NA>      NA       NA #> 543        <NA>      NA       NA #> 544           U      NA       NA #> 545        <NA>      NA       NA #> 546        <NA>      NA       NA #> 547           +      NA       NA #> 548        <NA>      NA       NA #> 549        <NA>      NA       NA #> 550        <NA>      NA       NA #> 551        <NA>      NA       NA #> 552        <NA>      NA       NA #> 553        <NA>      NA       NA #> 554           I      NA       NA #> 555        <NA>      NA       NA #> 556        <NA>      NA       NA #> 557           +      NA       NA #> 558        <NA>      NA       NA #> 559        <NA>      NA       NA #> 560        <NA>      NA       NA #> 561        <NA>      NA       NA #> 562        <NA>      NA       NA #> 563        <NA>      NA       NA #> 564        <NA>      NA       NA #> 565        <NA>      NA       NA #> 566        <NA>      NA       NA #> 567           +      NA       NA #> 568        <NA>      NA       NA #> 569        <NA>      NA       NA #> 570        <NA>      NA       NA #> 571        <NA>      NA       NA #> 572        <NA>      NA       NA #> 573        <NA>      NA       NA #> 574           U      NA       NA #> 575        <NA>      NA       NA #> 576        <NA>      NA       NA #> 577           +      NA       NA #> 578        <NA>      NA       NA #> 579        <NA>      NA       NA #> 580        <NA>      NA       NA #> 581        <NA>      NA       NA #> 582        <NA>      NA       NA #> 583        <NA>      NA       NA #> 584        <NA>      NA       NA #> 585        <NA>      NA       NA #> 586        <NA>      NA       NA #> 587           +      NA       NA #> 588        <NA>      NA       NA #> 589        <NA>      NA       NA #> 590           I      NA       NA #> 591           U      NA       NA #> 592        <NA>      NA       NA #> 593        <NA>      NA       NA #> 594           I      NA       NA #> 595        <NA>      NA       NA #> 596        <NA>      NA       NA #> 597           +      NA       NA #> 598        <NA>      NA       NA #> 599        <NA>      NA       NA #> 600           I      NA       NA #> 601           U      NA       NA #> 602        <NA>      NA       NA #> 603        <NA>      NA       NA #> 604           I      NA       NA #> 605        <NA>      NA       NA #> 606           I      NA       NA #> 607           +      NA       NA #> 608        <NA>      NA       NA #> 609           A      NA       NA #> 610           I      NA       NA #> 611           U      NA       NA #> 612        <NA>      NA       NA #> 613        <NA>      NA       NA #> 614           I      NA       NA #> 615        <NA>      NA       NA #> 616        <NA>      NA       NA #> 617           +      NA       NA #> 618        <NA>      NA       NA #> 619        <NA>      NA       NA #> 620           I      NA       NA #> 621           U      NA       NA #> 622        <NA>      NA       NA #> 623        <NA>      NA       NA #> 624           U      NA       NA #> 625        <NA>      NA       NA #> 626           +      NA       NA #> 627        <NA>      NA       NA #> 628        <NA>      NA       NA #> 629           I      NA       NA #> 630           U      NA       NA #> 631        <NA>      NA       NA #> 632        <NA>      NA       NA #> 633           U      NA       NA #> 634        <NA>      NA       NA #> 635        <NA>      NA       NA #> 636           +      NA       NA #> 637        <NA>      NA       NA #> 638        <NA>      NA       NA #> 639           I      NA       NA #> 640           U      NA       NA #> 641        <NA>      NA       NA #> 642        <NA>      NA       NA #> 643           U      NA       NA #> 644        <NA>      NA       NA #> 645        <NA>      NA       NA #> 646           +      NA       NA #> 647        <NA>      NA       NA #> 648        <NA>      NA       NA #> 649        <NA>      NA       NA #> 650        <NA>      NA       NA #> 651        <NA>      NA       NA #> 652        <NA>      NA       NA #> 653           U      NA       NA #> 654        <NA>      NA       NA #> 655        <NA>      NA       NA #> 656           +      NA       NA #> 657        <NA>      NA       NA #> 658        <NA>      NA       NA #> 659        <NA>      NA       NA #> 660        <NA>      NA       NA #> 661        <NA>      NA       NA #> 662        <NA>      NA       NA #> 663           I      NA       NA #> 664        <NA>      NA       NA #> 665        <NA>      NA       NA #> 666           +      NA       NA #> 667        <NA>      NA       NA #> 668        <NA>      NA       NA #> 669        <NA>      NA       NA #> 670        <NA>      NA       NA #> 671        <NA>      NA       NA #> 672        <NA>      NA       NA #> 673           I      NA   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<NA>      NA       NA #> 730           +      NA       NA #> 731        <NA>      NA       NA #> 732        <NA>      NA       NA #> 733        <NA>      NA       NA #> 734           +      NA       NA #> 735        <NA>      NA       NA #> 736        <NA>      NA       NA #> 737        <NA>      NA       NA #> 738           I      NA       NA #> 739        <NA>      NA       NA #> 740           I      NA       NA #> 741        <NA>      NA       NA #> 742        <NA>      NA       NA #> 743           +      NA       NA #> 744        <NA>      NA       NA #> 745        <NA>      NA       NA #> 746        <NA>      NA       NA #> 747           I      NA       NA #> 748        <NA>      NA       NA #> 749           +      NA       NA #> 750           I      NA       NA #> 751        <NA>      NA       NA #> 752        <NA>      NA       NA #> 753           +      NA       NA #> 754        <NA>      NA       NA #> 755        <NA>      NA       NA #> 756        <NA>      NA       NA #> 757        <NA>      NA       NA #> 758           +      NA       NA #> 759           I      NA       NA #> 760        <NA>      NA       NA #> 761        <NA>      NA       NA #> 762           +      NA       NA #> 763        <NA>      NA       NA #> 764        <NA>      NA       NA #> 765        <NA>      NA       NA #> 766        <NA>      NA       NA #> 767        <NA>      NA       NA #> 768           +      NA       NA #> 769           I      NA       NA #> 770        <NA>      NA       NA #> 771        <NA>      NA       NA #> 772           +      NA       NA #> 773        <NA>      NA       NA #> 774        <NA>      NA       NA #> 775        <NA>      NA       NA #> 776        <NA>      NA       NA #> 777           +      NA       NA #> 778        <NA>      NA       NA #> 779        <NA>      NA       NA #> 780        <NA>      NA       NA #> 781           +      NA       NA #> 782        <NA>      NA       NA #> 783        <NA>      NA       NA #> 784           I      NA       NA #> 785        <NA>      NA       NA #> 786           +      NA       NA #> 787        <NA>      NA       NA #> 788        <NA>      NA       NA #> 789        <NA>      NA       NA #> 790           +      NA       NA #> 791        <NA>      NA       NA #> 792        <NA>      NA       NA #> 793           I      NA       NA #> 794           I      NA       NA #> 795        <NA>      NA       NA #> 796           I      NA       NA #> 797        <NA>      NA       NA #> 798           I      NA       NA #> 799           +      NA       NA #> 800        <NA>      NA       NA #> 801        <NA>      NA       NA #> 802        <NA>      NA       NA #> 803        <NA>      NA       NA #> 804        <NA>      NA       NA #> 805           +      NA       NA #> 806        <NA>      NA       NA #> 807        <NA>      NA       NA #> 808        <NA>      NA       NA #> 809           +      NA       NA #> 810        <NA>      NA       NA #> 811        <NA>      NA       NA #> 812        <NA>      NA   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#> 924        <NA>      NA       NA #> 925        <NA>      NA       NA #> 926        <NA>      NA       NA #> 927        <NA>      NA       NA #> 928           +      NA       NA #> 929        <NA>      NA       NA #> 930        <NA>      NA       NA #> 931        <NA>      NA       NA #> 932           +      NA       NA #> 933        <NA>      NA       NA #> 934        <NA>      NA       NA #> 935           I      NA       NA #> 936           U      NA       NA #> 937        <NA>      NA       NA #> 938           +      NA       NA #> 939        <NA>      NA       NA #> 940        <NA>      NA       NA #> 941        <NA>      NA       NA #> 942           +      NA       NA #> 943        <NA>      NA       NA #> 944           A      NA       NA #> 945        <NA>      NA       NA #> 946           I      NA       NA #> 947        <NA>      NA       NA #> 948           +      NA       NA #> 949        <NA>      NA       NA #> 950        <NA>      NA       NA #> 951        <NA>      NA   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<NA>      NA       NA #> 1008          +      NA       NA #> 1009       <NA>      NA       NA #> 1010       <NA>      NA       NA #> 1011       <NA>      NA       NA #> 1012          +      NA       NA #> 1013       <NA>      NA       NA #> 1014       <NA>      NA       NA #> 1015       <NA>      NA       NA #> 1016       <NA>      NA       NA #> 1017          I      NA       NA #> 1018       <NA>      NA       NA #> 1019          +      NA       NA #> 1020       <NA>      NA       NA #> 1021       <NA>      NA       NA #> 1022       <NA>      NA       NA #> 1023       <NA>      NA       NA #> 1024       <NA>      NA       NA #> 1025          +      NA       NA #> 1026       <NA>      NA       NA #> 1027       <NA>      NA       NA #> 1028       <NA>      NA       NA #> 1029          +      NA       NA #> 1030       <NA>      NA       NA #> 1031          A      NA       NA #> 1032       <NA>      NA       NA #> 1033       <NA>      NA       NA #> 1034       <NA>      NA       NA #> 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+      NA       NA #> 1119       <NA>      NA       NA #> 1120       <NA>      NA       NA #> 1121          I      NA       NA #> 1122       <NA>      NA       NA #> 1123          I      NA       NA #> 1124       <NA>      NA       NA #> 1125       <NA>      NA       NA #> 1126          +      NA       NA #> 1127       <NA>      NA       NA #> 1128       <NA>      NA       NA #> 1129          I      NA       NA #> 1130       <NA>      NA       NA #> 1131          U      NA       NA #> 1132       <NA>      NA       NA #> 1133          +      NA       NA #> 1134       <NA>      NA       NA #> 1135       <NA>      NA       NA #> 1136          I      NA       NA #> 1137       <NA>      NA       NA #> 1138       <NA>      NA       NA #> 1139       <NA>      NA       NA #> 1140          I      NA       NA #> 1141       <NA>      NA       NA #> 1142       <NA>      NA       NA #> 1143          +      NA       NA #> 1144       <NA>      NA       NA #> 1145       <NA>      NA       NA #> 1146   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<NA>      NA       NA #> 1924       <NA>      NA       NA #> 1925       <NA>      NA       NA #> 1926       <NA>      NA       NA #> 1927       <NA>      NA       NA #> 1928       <NA>      NA       NA #> 1929          U      NA       NA #> 1930       <NA>      NA       NA #> 1931       <NA>      NA       NA #> 1932          +      NA       NA #> 1933       <NA>      NA       NA #> 1934       <NA>      NA       NA #> 1935       <NA>      NA       NA #> 1936          A      NA       NA #> 1937       <NA>      NA       NA #> 1938       <NA>      NA       NA #> 1939          U      NA       NA #> 1940       <NA>      NA       NA #> 1941       <NA>      NA       NA #> 1942          +      NA       NA #> 1943       <NA>      NA       NA #> 1944          A      NA       NA #> 1945          +      NA       NA #> 1946          I      NA       NA #> 1947       <NA>      NA       NA #> 1948       <NA>      NA       NA #> 1949       <NA>      NA       NA #> 1950          I      NA       NA #> 1951       <NA>      NA       NA #> 1952       <NA>      NA       NA #> 1953       <NA>      NA       NA #> 1954       <NA>      NA       NA #> 1955       <NA>      NA       NA #> 1956       <NA>      NA       NA #> 1957       <NA>      NA       NA #> 1958       <NA>      NA       NA #> 1959       <NA>      NA       NA #> 1960       <NA>      NA       NA #> 1961       <NA>      NA       NA #> 1962          +      NA       NA #> 1963       <NA>      NA       NA #> 1964       <NA>      NA       NA #> 1965          I      NA       NA #> 1966       <NA>      NA       NA #> 1967       <NA>      NA       NA #> 1968       <NA>      NA       NA #> 1969       <NA>      NA       NA #> 1970       <NA>      NA       NA #> 1971       <NA>      NA       NA #> 1972          +      NA       NA #> 1973       <NA>      NA       NA #> 1974       <NA>      NA       NA #> 1975       <NA>      NA       NA #> 1976          A      NA       NA #> 1977       <NA>      NA       NA #> 1978       <NA>      NA      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NA       NA #> 2007       <NA>      NA       NA #> 2008       <NA>      NA       NA #> 2009          U      NA       NA #> 2010       <NA>      NA       NA #> 2011       <NA>      NA       NA #> 2012          +      NA       NA #> 2013       <NA>      NA       NA #> 2014       <NA>      NA       NA #> 2015       <NA>      NA       NA #> 2016       <NA>      NA       NA #> 2017       <NA>      NA       NA #> 2018       <NA>      NA       NA #> 2019          I      NA       NA #> 2020       <NA>      NA       NA #> 2021       <NA>      NA       NA #> 2022          +      NA       NA #> 2023       <NA>      NA       NA #> 2024       <NA>      NA       NA #> 2025       <NA>      NA       NA #> 2026       <NA>      NA       NA #> 2027       <NA>      NA       NA #> 2028       <NA>      NA       NA #> 2029          I      NA       NA #> 2030       <NA>      NA       NA #> 2031       <NA>      NA       NA #> 2032          +      NA       NA #> 2033       <NA>      NA       NA #> 2034       <NA>      NA       NA #> 2035          I      NA       NA #> 2036          A      NA       NA #> 2037       <NA>      NA       NA #> 2038       <NA>      NA       NA #> 2039       <NA>      NA       NA #> 2040       <NA>      NA       NA #> 2041       <NA>      NA       NA #> 2042          +      NA       NA #> 2043       <NA>      NA       NA #> 2044       <NA>      NA       NA #> 2045       <NA>      NA       NA #> 2046          A      NA       NA #> 2047       <NA>      NA       NA #> 2048       <NA>      NA       NA #> 2049       <NA>      NA       NA #> 2050       <NA>      NA       NA #> 2051       <NA>      NA       NA #> 2052          +      NA       NA #> 2053       <NA>      NA       NA #> 2054       <NA>      NA       NA #> 2055          I      NA       NA #> 2056       <NA>      NA       NA #> 2057       <NA>      NA       NA #> 2058       <NA>      NA       NA #> 2059       <NA>      NA       NA #> 2060       <NA>      NA       NA #> 2061       <NA>      NA       NA #> 2062          +      NA       NA #> 2063       <NA>      NA       NA #> 2064       <NA>      NA       NA #> 2065          I      NA       NA #> 2066       <NA>      NA       NA #> 2067       <NA>      NA       NA #> 2068       <NA>      NA       NA #> 2069          U      NA       NA #> 2070       <NA>      NA       NA #> 2071       <NA>      NA       NA #> 2072          +      NA       NA #> 2073       <NA>      NA       NA #> 2074       <NA>      NA       NA #> 2075          I      NA       NA #> 2076          A      NA       NA #> 2077       <NA>      NA       NA #> 2078       <NA>      NA       NA #> 2079          U      NA       NA #> 2080       <NA>      NA       NA #> 2081       <NA>      NA       NA #> 2082          +      NA       NA #> 2083       <NA>      NA       NA #> 2084          A      NA       NA #> 2085          I      NA       NA #> 2086       <NA>      NA       NA #> 2087       <NA>      NA       NA #> 2088       <NA>      NA       NA #> 2089          U      NA      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<NA>      NA       NA #> 2146       <NA>      NA       NA #> 2147       <NA>      NA       NA #> 2148       <NA>      NA       NA #> 2149          I      NA       NA #> 2150       <NA>      NA       NA #> 2151       <NA>      NA       NA #> 2152          +      NA       NA #> 2153       <NA>      NA       NA #> 2154       <NA>      NA       NA #> 2155          U      NA       NA #> 2156          A      NA       NA #> 2157       <NA>      NA       NA #> 2158       <NA>      NA       NA #> 2159          I      NA       NA #> 2160       <NA>      NA       NA #> 2161       <NA>      NA       NA #> 2162          +      NA       NA #> 2163       <NA>      NA       NA #> 2164       <NA>      NA       NA #> 2165          I      NA       NA #> 2166          A      NA       NA #> 2167       <NA>      NA       NA #> 2168       <NA>      NA       NA #> 2169          I      NA       NA #> 2170       <NA>      NA       NA #> 2171       <NA>      NA       NA #> 2172          +      NA       NA #> 2173       <NA>      NA       NA #> 2174       <NA>      NA       NA #> 2175          I      NA       NA #> 2176       <NA>      NA       NA #> 2177       <NA>      NA       NA #> 2178       <NA>      NA       NA #> 2179          I      NA       NA #> 2180       <NA>      NA       NA #> 2181          +      NA       NA #> 2182       <NA>      NA       NA #> 2183       <NA>      NA       NA #> 2184          U      NA       NA #> 2185       <NA>      NA       NA #> 2186       <NA>      NA       NA #> 2187          U      NA       NA #> 2188       <NA>      NA       NA #> 2189          +      NA       NA #> 2190       <NA>      NA       NA #> 2191       <NA>      NA       NA #> 2192       <NA>      NA       NA #> 2193       <NA>      NA       NA #> 2194          I      NA       NA #> 2195       <NA>      NA       NA #> 2196       <NA>      NA       NA #> 2197          +      NA       NA #> 2198       <NA>      NA       NA #> 2199       <NA>      NA       NA #> 2200       <NA>      NA      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NA       NA #> 2229       <NA>      NA       NA #> 2230       <NA>      NA       NA #> 2231       <NA>      NA       NA #> 2232       <NA>      NA       NA #> 2233       <NA>      NA       NA #> 2234          U      NA       NA #> 2235       <NA>      NA       NA #> 2236       <NA>      NA       NA #> 2237          +      NA       NA #> 2238       <NA>      NA       NA #> 2239       <NA>      NA       NA #> 2240       <NA>      NA       NA #> 2241       <NA>      NA       NA #> 2242       <NA>      NA       NA #> 2243       <NA>      NA       NA #> 2244       <NA>      NA       NA #> 2245       <NA>      NA       NA #> 2246          +      NA       NA #> 2247       <NA>      NA       NA #> 2248       <NA>      NA       NA #> 2249       <NA>      NA       NA #> 2250          A      NA       NA #> 2251       <NA>      NA       NA #> 2252       <NA>      NA       NA #> 2253          I      NA       NA #> 2254       <NA>      NA       NA #> 2255       <NA>      NA       NA #> 2256          +      NA       NA #> 2257       <NA>      NA       NA #> 2258       <NA>      NA       NA #> 2259       <NA>      NA       NA #> 2260       <NA>      NA       NA #> 2261       <NA>      NA       NA #> 2262       <NA>      NA       NA #> 2263       <NA>      NA       NA #> 2264       <NA>      NA       NA #> 2265       <NA>      NA       NA #> 2266          I      NA       NA #> 2267          +      NA       NA #> 2268       <NA>      NA       NA #> 2269          +      NA       NA #> 2270       <NA>      NA       NA #> 2271          I      NA       NA #> 2272       <NA>      NA       NA #> 2273       <NA>      NA       NA #> 2274       <NA>      NA       NA #> 2275       <NA>      NA       NA #> 2276       <NA>      NA       NA #> 2277          U      NA       NA #> 2278          +      NA       NA #> 2279       <NA>      NA       NA #> 2280          +      NA       NA #> 2281       <NA>      NA       NA #> 2282          I      NA       NA #> 2283       <NA>      NA       NA #> 2284       <NA>      NA       NA #> 2285       <NA>      NA       NA #> 2286       <NA>      NA       NA #> 2287       <NA>      NA       NA #> 2288          U      NA       NA #> 2289          +      NA       NA #> 2290       <NA>      NA       NA #> 2291          +      NA       NA #> 2292          I      NA       NA #> 2293       <NA>      NA       NA #> 2294       <NA>      NA       NA #> 2295       <NA>      NA       NA #> 2296       <NA>      NA       NA #> 2297       <NA>      NA       NA #> 2298          I      NA       NA #> 2299       <NA>      NA       NA #> 2300          +      NA       NA #> 2301       <NA>      NA       NA #> 2302          U      NA       NA #> 2303          A      NA       NA #> 2304       <NA>      NA       NA #> 2305       <NA>      NA       NA #> 2306       <NA>      NA       NA #> 2307       <NA>      NA       NA #> 2308          G      NA       NA #> 2309       <NA>      NA       NA #> 2310       <NA>      NA       NA #> 2311          +      NA       NA #> 2312       <NA>      NA       NA #> 2313          I      NA       NA #> 2314       <NA>      NA       NA #> 2315       <NA>      NA       NA #> 2316       <NA>      NA       NA #> 2317       <NA>      NA       NA #> 2318       <NA>      NA       NA #> 2319          I      NA       NA #> 2320       <NA>      NA       NA #> 2321       <NA>      NA       NA #> 2322          +      NA       NA #> 2323       <NA>      NA       NA #> 2324          I      NA       NA #> 2325       <NA>      NA       NA #> 2326       <NA>      NA       NA #> 2327       <NA>      NA       NA #> 2328       <NA>      NA       NA #> 2329       <NA>      NA       NA #> 2330          +      NA       NA #> 2331          I      NA       NA #> 2332       <NA>      NA       NA #> 2333       <NA>      NA       NA #> 2334       <NA>      NA       NA #> 2335          I      NA       NA #> 2336       <NA>      NA       NA #> 2337       <NA>      NA       NA #> 2338          +      NA       NA #> 2339       <NA>      NA      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NA       NA #> 2368          I      NA       NA #> 2369       <NA>      NA       NA #> 2370       <NA>      NA       NA #> 2371          +      NA       NA #> 2372       <NA>      NA       NA #> 2373          U      NA       NA #> 2374       <NA>      NA       NA #> 2375       <NA>      NA       NA #> 2376       <NA>      NA       NA #> 2377       <NA>      NA       NA #> 2378       <NA>      NA       NA #> 2379          I      NA       NA #> 2380       <NA>      NA       NA #> 2381       <NA>      NA       NA #> 2382          +      NA       NA #> 2383       <NA>      NA       NA #> 2384          I      NA       NA #> 2385       <NA>      NA       NA #> 2386       <NA>      NA       NA #> 2387       <NA>      NA       NA #> 2388       <NA>      NA       NA #> 2389       <NA>      NA       NA #> 2390       <NA>      NA       NA #> 2391       <NA>      NA       NA #> 2392       <NA>      NA       NA #> 2393       <NA>      NA       NA #> 2394       <NA>      NA       NA #> 2395       <NA>      NA       NA #> 2396       <NA>      NA       NA #> 2397       <NA>      NA       NA #> 2398       <NA>      NA       NA #> 2399       <NA>      NA       NA #> 2400       <NA>      NA       NA #> 2401       <NA>      NA       NA #> 2402          U      NA       NA #> 2403       <NA>      NA       NA #> 2404       <NA>      NA       NA #> 2405          +      NA       NA #> 2406       <NA>      NA       NA #> 2407          I      NA       NA #> 2408          A      NA       NA #> 2409          A      NA       NA #> 2410       <NA>      NA       NA #> 2411       <NA>      NA       NA #> 2412       <NA>      NA       NA #> 2413          U      NA       NA #> 2414       <NA>      NA       NA #> 2415       <NA>      NA       NA #> 2416          +      NA       NA #> 2417       <NA>      NA       NA #> 2418          I      NA       NA #> 2419       <NA>      NA       NA #> 2420       <NA>      NA       NA #> 2421       <NA>      NA       NA #> 2422       <NA>      NA       NA #> 2423       <NA>      NA       NA #> 2424          U      NA       NA #> 2425       <NA>      NA       NA #> 2426       <NA>      NA       NA #> 2427          +      NA       NA #> 2428       <NA>      NA       NA #> 2429          A      NA       NA #> 2430       <NA>      NA       NA #> 2431       <NA>      NA       NA #> 2432       <NA>      NA       NA #> 2433       <NA>      NA       NA #> 2434       <NA>      NA       NA #> 2435          I      NA       NA #> 2436       <NA>      NA       NA #> 2437       <NA>      NA       NA #> 2438          +      NA       NA #> 2439       <NA>      NA       NA #> 2440          I      NA       NA #> 2441       <NA>      NA       NA #> 2442          A      NA       NA #> 2443       <NA>      NA       NA #> 2444       <NA>      NA       NA #> 2445       <NA>      NA       NA #> 2446          U      NA       NA #> 2447       <NA>      NA       NA #> 2448       <NA>      NA       NA #> 2449          +      NA       NA #> 2450       <NA>      NA      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NA       NA #> 2479       <NA>      NA       NA #> 2480       <NA>      NA       NA #> 2481          +      NA       NA #> 2482       <NA>      NA       NA #> 2483          I      NA       NA #> 2484       <NA>      NA       NA #> 2485       <NA>      NA       NA #> 2486       <NA>      NA       NA #> 2487       <NA>      NA       NA #> 2488          I      NA       NA #> 2489       <NA>      NA       NA #> 2490       <NA>      NA       NA #> 2491          +      NA       NA #> 2492       <NA>      NA       NA #> 2493       <NA>      NA       NA #> 2494       <NA>      NA       NA #> 2495       <NA>      NA       NA #> 2496       <NA>      NA       NA #> 2497       <NA>      NA       NA #> 2498       <NA>      NA       NA #> 2499          U      NA       NA #> 2500       <NA>      NA       NA #> 2501       <NA>      NA       NA #> 2502          +      NA       NA #> 2503       <NA>      NA       NA #> 2504          I      NA       NA #> 2505       <NA>      NA       NA #> 2506       <NA>      NA       NA #> 2507       <NA>      NA       NA #> 2508       <NA>      NA       NA #> 2509       <NA>      NA       NA #> 2510          U      NA       NA #> 2511       <NA>      NA       NA #> 2512       <NA>      NA       NA #> 2513          +      NA       NA #> 2514       <NA>      NA       NA #> 2515          I      NA       NA #> 2516       <NA>      NA       NA #> 2517       <NA>      NA       NA #> 2518       <NA>      NA       NA #> 2519       <NA>      NA       NA #> 2520       <NA>      NA       NA #> 2521          U      NA       NA #> 2522       <NA>      NA       NA #> 2523       <NA>      NA       NA #> 2524          +      NA       NA #> 2525       <NA>      NA       NA #> 2526          I      NA       NA #> 2527          A      NA       NA #> 2528       <NA>      NA       NA #> 2529       <NA>      NA       NA #> 2530       <NA>      NA       NA #> 2531       <NA>      NA       NA #> 2532          U      NA       NA #> 2533       <NA>      NA       NA #> 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NA       NA #> 2590          +      NA       NA #> 2591       <NA>      NA       NA #> 2592          U      NA       NA #> 2593       <NA>      NA       NA #> 2594       <NA>      NA       NA #> 2595       <NA>      NA       NA #> 2596       <NA>      NA       NA #> 2597       <NA>      NA       NA #> 2598          U      NA       NA #> 2599       <NA>      NA       NA #> 2600       <NA>      NA       NA #> 2601          +      NA       NA #> 2602       <NA>      NA       NA #> 2603          I      NA       NA #> 2604       <NA>      NA       NA #> 2605          A      NA       NA #> 2606       <NA>      NA       NA #> 2607       <NA>      NA       NA #> 2608       <NA>      NA       NA #> 2609          U      NA       NA #> 2610       <NA>      NA       NA #> 2611       <NA>      NA       NA #> 2612          +      NA       NA #> 2613       <NA>      NA       NA #> 2614          I      NA       NA #> 2615       <NA>      NA       NA #> 2616       <NA>      NA       NA #> 2617       <NA>      NA       NA #> 2618       <NA>      NA       NA #> 2619       <NA>      NA       NA #> 2620          U      NA       NA #> 2621       <NA>      NA       NA #> 2622       <NA>      NA       NA #> 2623          +      NA       NA #> 2624       <NA>      NA       NA #> 2625          I      NA       NA #> 2626       <NA>      NA       NA #> 2627       <NA>      NA       NA #> 2628       <NA>      NA       NA #> 2629       <NA>      NA       NA #> 2630       <NA>      NA       NA #> 2631          U      NA       NA #> 2632       <NA>      NA       NA #> 2633       <NA>      NA       NA #> 2634          +      NA       NA #> 2635       <NA>      NA       NA #> 2636          I      NA       NA #> 2637       <NA>      NA       NA #> 2638       <NA>      NA       NA #> 2639       <NA>      NA       NA #> 2640       <NA>      NA       NA #> 2641       <NA>      NA       NA #> 2642          U      NA       NA #> 2643       <NA>      NA       NA #> 2644       <NA>      NA       NA #> 2645          +      NA       NA #> 2646       <NA>      NA       NA #> 2647          I      NA       NA #> 2648       <NA>      NA       NA #> 2649          I      NA       NA #> 2650       <NA>      NA       NA #> 2651       <NA>      NA       NA #> 2652       <NA>      NA       NA #> 2653          U      NA       NA #> 2654       <NA>      NA       NA #> 2655       <NA>      NA       NA #> 2656          +      NA       NA #> 2657       <NA>      NA       NA #> 2658          I      NA       NA #> 2659          I      NA       NA #> 2660          A      NA       NA #> 2661       <NA>      NA       NA #> 2662       <NA>      NA       NA #> 2663       <NA>      NA       NA #> 2664          U      NA       NA #> 2665       <NA>      NA       NA #> 2666       <NA>      NA       NA #> 2667          +      NA       NA #> 2668       <NA>      NA       NA #> 2669          I      NA       NA #> 2670       <NA>      NA       NA #> 2671       <NA>      NA       NA #> 2672       <NA>      NA       NA #> 2673       <NA>      NA       NA #> 2674       <NA>      NA       NA #> 2675          U      NA       NA #> 2676       <NA>      NA       NA #> 2677       <NA>      NA       NA #> 2678          +      NA       NA #> 2679       <NA>      NA       NA #> 2680       <NA>      NA       NA #> 2681       <NA>      NA       NA #> 2682       <NA>      NA       NA #> 2683       <NA>      NA       NA #> 2684       <NA>      NA       NA #> 2685          U      NA       NA #> 2686       <NA>      NA       NA #> 2687       <NA>      NA       NA #> 2688          +      NA       NA #> 2689       <NA>      NA       NA #> 2690          I      NA       NA #> 2691          I      NA       NA #> 2692          I      NA       NA #> 2693       <NA>      NA       NA #> 2694          +      NA       NA #> 2695       <NA>      NA       NA #> 2696       <NA>      NA       NA #> 2697       <NA>      NA       NA #> 2698       <NA>      NA       NA #> 2699          +      NA       NA #> 2700       <NA>      NA       NA #> 2701       <NA>      NA       NA #> 2702       <NA>      NA       NA #> 2703          +      NA       NA #> 2704       <NA>      NA       NA #> 2705       <NA>      NA       NA #> 2706       <NA>      NA       NA #> 2707          +      NA       NA #> 2708       <NA>      NA       NA #> 2709       <NA>      NA       NA #> 2710       <NA>      NA       NA #> 2711          +      NA       NA #> 2712       <NA>      NA       NA #> 2713       <NA>      NA       NA #> 2714       <NA>      NA       NA #> 2715          +      NA       NA #> 2716       <NA>      NA       NA #> 2717       <NA>      NA       NA #> 2718       <NA>      NA       NA #> 2719          +      NA       NA #> 2720       <NA>      NA       NA #> 2721       <NA>      NA       NA #> 2722       <NA>      NA       NA #> 2723          +      NA       NA #> 2724       <NA>      NA       NA #> 2725       <NA>      NA       NA #> 2726       <NA>      NA       NA #> 2727          +      NA       NA #> 2728       <NA>      NA       NA #> 2729          +      NA       NA #> 2730       <NA>      NA       NA #> 2731       <NA>      NA       NA #> 2732       <NA>      NA       NA #> 2733          +      NA       NA #> 2734       <NA>      NA       NA #> 2735       <NA>      NA       NA #> 2736       <NA>      NA       NA #> 2737          +      NA       NA #> 2738       <NA>      NA       NA #> 2739       <NA>      NA       NA #> 2740       <NA>      NA       NA #> 2741          +      NA       NA #> 2742       <NA>      NA       NA #> 2743       <NA>      NA       NA #> 2744       <NA>      NA       NA #> 2745          +      NA       NA #> 2746       <NA>      NA       NA #> 2747       <NA>      NA       NA #> 2748       <NA>      NA       NA #> 2749          +      NA       NA #> 2750       <NA>      NA       NA #> 2751       <NA>      NA       NA #> 2752       <NA>      NA       NA #> 2753          +      NA       NA #> 2754       <NA>      NA       NA #> 2755       <NA>      NA       NA #> 2756       <NA>      NA       NA #> 2757          +      NA       NA #> 2758       <NA>      NA       NA #> 2759          +      NA       NA #> 2760       <NA>      NA       NA #> 2761       <NA>      NA       NA #> 2762       <NA>      NA       NA #> 2763          +      NA       NA #> 2764       <NA>      NA       NA #> 2765       <NA>      NA       NA #> 2766       <NA>      NA       NA #> 2767          +      NA       NA #> 2768       <NA>      NA       NA #> 2769       <NA>      NA       NA #> 2770       <NA>      NA       NA #> 2771          +      NA       NA #> 2772       <NA>      NA       NA #> 2773       <NA>      NA       NA #> 2774       <NA>      NA       NA #> 2775          +      NA       NA #> 2776       <NA>      NA       NA #> 2777       <NA>      NA       NA #> 2778       <NA>      NA       NA #> 2779          +      NA       NA #> 2780       <NA>      NA       NA #> 2781       <NA>      NA       NA #> 2782       <NA>      NA       NA #> 2783       <NA>      NA      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NA       NA #> 2812       <NA>      NA       NA #> 2813       <NA>      NA       NA #> 2814       <NA>      NA       NA #> 2815       <NA>      NA       NA #> 2816          +      NA       NA #> 2817       <NA>      NA       NA #> 2818          I      NA       NA #> 2819       <NA>      NA       NA #> 2820          I      NA       NA #> 2821          A      NA       NA #> 2822       <NA>      NA       NA #> 2823       <NA>      NA       NA #> 2824       <NA>      NA       NA #> 2825       <NA>      NA       NA #> 2826       <NA>      NA       NA #> 2827       <NA>      NA       NA #> 2828          +      NA       NA #> 2829       <NA>      NA       NA #> 2830          I      NA       NA #> 2831          A      NA       NA #> 2832       <NA>      NA       NA #> 2833          A      NA       NA #> 2834       <NA>      NA       NA #> 2835       <NA>      NA       NA #> 2836       <NA>      NA       NA #> 2837       <NA>      NA       NA #> 2838       <NA>      NA       NA #> 2839       <NA>      NA       NA #> 2840          +      NA       NA #> 2841       <NA>      NA       NA #> 2842          I      NA       NA #> 2843          A      NA       NA #> 2844          I      NA       NA #> 2845          A      NA       NA #> 2846       <NA>      NA       NA #> 2847       <NA>      NA       NA #> 2848       <NA>      NA       NA #> 2849       <NA>      NA       NA #> 2850       <NA>      NA       NA #> 2851       <NA>      NA       NA #> 2852          +      NA       NA #> 2853       <NA>      NA       NA #> 2854       <NA>      NA       NA #> 2855       <NA>      NA       NA #> 2856       <NA>      NA       NA #> 2857       <NA>      NA       NA #> 2858       <NA>      NA       NA #> 2859       <NA>      NA       NA #> 2860       <NA>      NA       NA #> 2861       <NA>      NA       NA #> 2862       <NA>      NA       NA #> 2863          +      NA       NA #> 2864       <NA>      NA       NA #> 2865          I      NA       NA #> 2866       <NA>      NA       NA #> 2867       <NA>      NA       NA #> 2868       <NA>      NA       NA #> 2869       <NA>      NA       NA #> 2870       <NA>      NA       NA #> 2871       <NA>      NA       NA #> 2872       <NA>      NA       NA #> 2873       <NA>      NA       NA #> 2874          +      NA       NA #> 2875       <NA>      NA       NA #> 2876          I      NA       NA #> 2877       <NA>      NA       NA #> 2878       <NA>      NA       NA #> 2879       <NA>      NA       NA #> 2880       <NA>      NA       NA #> 2881       <NA>      NA       NA #> 2882       <NA>      NA       NA #> 2883       <NA>      NA       NA #> 2884       <NA>      NA       NA #> 2885          +      NA       NA #> 2886       <NA>      NA       NA #> 2887          I      NA       NA #> 2888       <NA>      NA       NA #> 2889       <NA>      NA       NA #> 2890       <NA>      NA       NA #> 2891       <NA>      NA       NA #> 2892       <NA>      NA       NA #> 2893       <NA>      NA       NA #> 2894       <NA>      NA      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NA       NA #> 2923       <NA>      NA       NA #> 2924       <NA>      NA       NA #> 2925       <NA>      NA       NA #> 2926       <NA>      NA       NA #> 2927       <NA>      NA       NA #> 2928       <NA>      NA       NA #> 2929       <NA>      NA       NA #> 2930       <NA>      NA       NA #> 2931       <NA>      NA       NA #> 2932       <NA>      NA       NA #> 2933       <NA>      NA       NA #> 2934       <NA>      NA       NA #> 2935       <NA>      NA       NA #> 2936       <NA>      NA       NA #> 2937       <NA>      NA       NA #> 2938       <NA>      NA       NA #> 2939       <NA>      NA       NA #> 2940       <NA>      NA       NA #> 2941       <NA>      NA       NA #> 2942       <NA>      NA       NA #> 2943       <NA>      NA       NA #> 2944       <NA>      NA       NA #> 2945       <NA>      NA       NA #> 2946       <NA>      NA       NA #> 2947          +      NA       NA #> 2948       <NA>      NA       NA #> 2949       <NA>      NA       NA #> 2950       <NA>      NA       NA #> 2951          +      NA       NA #> 2952       <NA>      NA       NA #> 2953       <NA>      NA       NA #> 2954       <NA>      NA       NA #> 2955          +      NA       NA #> 2956       <NA>      NA       NA #> 2957       <NA>      NA       NA #> 2958       <NA>      NA       NA #> 2959          +      NA       NA #> 2960       <NA>      NA       NA #> 2961       <NA>      NA       NA #> 2962       <NA>      NA       NA #> 2963          +      NA       NA #> 2964       <NA>      NA       NA #> 2965       <NA>      NA       NA #> 2966       <NA>      NA       NA #> 2967          +      NA       NA #> 2968       <NA>      NA       NA #> 2969       <NA>      NA       NA #> 2970       <NA>      NA       NA #> 2971          +      NA       NA #> 2972       <NA>      NA       NA #> 2973       <NA>      NA       NA #> 2974       <NA>      NA       NA #> 2975          +      NA       NA #> 2976       <NA>      NA       NA #> 2977       <NA>      NA       NA #> 2978       <NA>      NA       NA #> 2979       <NA>      NA       NA #> 2980       <NA>      NA       NA #> 2981          U      NA       NA #> 2982          +      NA       NA #> 2983       <NA>      NA       NA #> 2984          +      NA       NA #> 2985       <NA>      NA       NA #> 2986          U      NA       NA #> 2987       <NA>      NA       NA #> 2988       <NA>      NA       NA #> 2989       <NA>      NA       NA #> 2990       <NA>      NA       NA #> 2991       <NA>      NA       NA #> 2992          I      NA       NA #> 2993          +      NA       NA #> 2994       <NA>      NA       NA #> 2995          +      NA       NA #> 2996       <NA>      NA       NA #> 2997       <NA>      NA       NA #> 2998          A      NA       NA #> 2999       <NA>      NA       NA #> 3000       <NA>      NA       NA #> 3001       <NA>      NA       NA #> 3002       <NA>      NA       NA #> 3003       <NA>      NA       NA #> 3004          +      NA       NA #> 3005       <NA>      NA      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NA       NA #> 3034       <NA>      NA       NA #> 3035       <NA>      NA       NA #> 3036          +      NA       NA #> 3037       <NA>      NA       NA #> 3038          I      NA       NA #> 3039       <NA>      NA       NA #> 3040       <NA>      NA       NA #> 3041       <NA>      NA       NA #> 3042       <NA>      NA       NA #> 3043       <NA>      NA       NA #> 3044          A      NA       NA #> 3045       <NA>      NA       NA #> 3046          I      NA       NA #> 3047       <NA>      NA       NA #> 3048       <NA>      NA       NA #> 3049          +      NA       NA #> 3050       <NA>      NA       NA #> 3051          I      NA       NA #> 3052       <NA>      NA       NA #> 3053       <NA>      NA       NA #> 3054       <NA>      NA       NA #> 3055       <NA>      NA       NA #> 3056       <NA>      NA       NA #> 3057          I      NA       NA #> 3058       <NA>      NA       NA #> 3059       <NA>      NA       NA #> 3060          +      NA       NA #> 3061       <NA>      NA       NA #> 3062          I      NA       NA #> 3063       <NA>      NA       NA #> 3064       <NA>      NA       NA #> 3065       <NA>      NA       NA #> 3066       <NA>      NA       NA #> 3067       <NA>      NA       NA #> 3068          U      NA       NA #> 3069       <NA>      NA       NA #> 3070       <NA>      NA       NA #> 3071          +      NA       NA #> 3072       <NA>      NA       NA #> 3073          I      NA       NA #> 3074       <NA>      NA       NA #> 3075       <NA>      NA       NA #> 3076       <NA>      NA       NA #> 3077       <NA>      NA       NA #> 3078       <NA>      NA       NA #> 3079       <NA>      NA       NA #> 3080       <NA>      NA       NA #> 3081       <NA>      NA       NA #> 3082          +      NA       NA #> 3083       <NA>      NA       NA #> 3084          I      NA       NA #> 3085       <NA>      NA       NA #> 3086       <NA>      NA       NA #> 3087       <NA>      NA       NA #> 3088       <NA>      NA       NA #> 3089       <NA>      NA       NA #> 3090       <NA>      NA       NA #> 3091       <NA>      NA       NA #> 3092          +      NA       NA #> 3093       <NA>      NA       NA #> 3094          I      NA       NA #> 3095       <NA>      NA       NA #> 3096       <NA>      NA       NA #> 3097       <NA>      NA       NA #> 3098       <NA>      NA       NA #> 3099       <NA>      NA       NA #> 3100          I      NA       NA #> 3101       <NA>      NA       NA #> 3102       <NA>      NA       NA #> 3103          +      NA       NA #> 3104       <NA>      NA       NA #> 3105       <NA>      NA       NA #> 3106       <NA>      NA       NA #> 3107       <NA>      NA       NA #> 3108       <NA>      NA       NA #> 3109       <NA>      NA       NA #> 3110       <NA>      NA       NA #> 3111       <NA>      NA       NA #> 3112       <NA>      NA       NA #> 3113       <NA>      NA       NA #> 3114       <NA>      NA       NA #> 3115       <NA>      NA       NA #> 3116       <NA>      NA      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NA       NA #> 3145       <NA>      NA       NA #> 3146       <NA>      NA       NA #> 3147       <NA>      NA       NA #> 3148       <NA>      NA       NA #> 3149       <NA>      NA       NA #> 3150       <NA>      NA       NA #> 3151       <NA>      NA       NA #> 3152          +      NA       NA #> 3153       <NA>      NA       NA #> 3154          I      NA       NA #> 3155       <NA>      NA       NA #> 3156       <NA>      NA       NA #> 3157       <NA>      NA       NA #> 3158       <NA>      NA       NA #> 3159       <NA>      NA       NA #> 3160          I      NA       NA #> 3161       <NA>      NA       NA #> 3162       <NA>      NA       NA #> 3163          +      NA       NA #> 3164       <NA>      NA       NA #> 3165          I      NA       NA #> 3166          A      NA       NA #> 3167       <NA>      NA       NA #> 3168       <NA>      NA       NA #> 3169       <NA>      NA       NA #> 3170       <NA>      NA       NA #> 3171          U      NA       NA #> 3172       <NA>      NA       NA #> 3173       <NA>      NA       NA #> 3174          +      NA       NA #> 3175       <NA>      NA       NA #> 3176          I      NA       NA #> 3177       <NA>      NA       NA #> 3178       <NA>      NA       NA #> 3179       <NA>      NA       NA #> 3180       <NA>      NA       NA #> 3181       <NA>      NA       NA #> 3182          I      NA       NA #> 3183       <NA>      NA       NA #> 3184       <NA>      NA       NA #> 3185          +      NA       NA #> 3186       <NA>      NA       NA #> 3187       <NA>      NA       NA #> 3188          A      NA       NA #> 3189       <NA>      NA       NA #> 3190       <NA>      NA       NA #> 3191       <NA>      NA       NA #> 3192       <NA>      NA       NA #> 3193          U      NA       NA #> 3194       <NA>      NA       NA #> 3195       <NA>      NA       NA #> 3196          +      NA       NA #> 3197       <NA>      NA       NA #> 3198          I      NA       NA #> 3199       <NA>      NA       NA #> 3200       <NA>      NA       NA #> 3201       <NA>      NA       NA #> 3202       <NA>      NA       NA #> 3203       <NA>      NA       NA #> 3204          U      NA       NA #> 3205       <NA>      NA       NA #> 3206       <NA>      NA       NA #> 3207          +      NA       NA #> 3208       <NA>      NA       NA #> 3209          I      NA       NA #> 3210       <NA>      NA       NA #> 3211       <NA>      NA       NA #> 3212       <NA>      NA       NA #> 3213       <NA>      NA       NA #> 3214       <NA>      NA       NA #> 3215          U      NA       NA #> 3216       <NA>      NA       NA #> 3217       <NA>      NA       NA #> 3218          +      NA       NA #> 3219       <NA>      NA       NA #> 3220          U      NA       NA #> 3221       <NA>      NA       NA #> 3222       <NA>      NA       NA #> 3223       <NA>      NA       NA #> 3224       <NA>      NA       NA #> 3225       <NA>      NA       NA #> 3226       <NA>      NA       NA #> 3227       <NA>      NA      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+      NA       NA #> 3284       <NA>      NA       NA #> 3285       <NA>      NA       NA #> 3286       <NA>      NA       NA #> 3287          U      NA       NA #> 3288       <NA>      NA       NA #> 3289       <NA>      NA       NA #> 3290       <NA>      NA       NA #> 3291          U      NA       NA #> 3292       <NA>      NA       NA #> 3293       <NA>      NA       NA #> 3294          +      NA       NA #> 3295       <NA>      NA       NA #> 3296       <NA>      NA       NA #> 3297       <NA>      NA       NA #> 3298       <NA>      NA       NA #> 3299       <NA>      NA       NA #> 3300       <NA>      NA       NA #> 3301       <NA>      NA       NA #> 3302          I      NA       NA #> 3303       <NA>      NA       NA #> 3304       <NA>      NA       NA #> 3305          +      NA       NA #> 3306       <NA>      NA       NA #> 3307       <NA>      NA       NA #> 3308       <NA>      NA       NA #> 3309       <NA>      NA       NA #> 3310       <NA>      NA       NA #> 3311       <NA>      NA       NA #> 3312       <NA>      NA       NA #> 3313          I      NA       NA #> 3314       <NA>      NA       NA #> 3315       <NA>      NA       NA #> 3316          +      NA       NA #> 3317       <NA>      NA       NA #> 3318          I      NA       NA #> 3319       <NA>      NA       NA #> 3320       <NA>      NA       NA #> 3321       <NA>      NA       NA #> 3322       <NA>      NA       NA #> 3323       <NA>      NA       NA #> 3324          U      NA       NA #> 3325       <NA>      NA       NA #> 3326       <NA>      NA       NA #> 3327          +      NA       NA #> 3328       <NA>      NA       NA #> 3329       <NA>      NA       NA #> 3330       <NA>      NA       NA #> 3331       <NA>      NA       NA #> 3332       <NA>      NA       NA #> 3333       <NA>      NA       NA #> 3334       <NA>      NA       NA #> 3335       <NA>      NA       NA #> 3336       <NA>      NA       NA #> 3337       <NA>      NA       NA #> 3338          +      NA       NA #> 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<NA>      NA       NA #> 3423       <NA>      NA       NA #> 3424       <NA>      NA       NA #> 3425       <NA>      NA       NA #> 3426          A      NA       NA #> 3427       <NA>      NA       NA #> 3428       <NA>      NA       NA #> 3429       <NA>      NA       NA #> 3430       <NA>      NA       NA #> 3431       <NA>      NA       NA #> 3432       <NA>      NA       NA #> 3433          +      NA       NA #> 3434       <NA>      NA       NA #> 3435          I      NA       NA #> 3436       <NA>      NA       NA #> 3437       <NA>      NA       NA #> 3438       <NA>      NA       NA #> 3439       <NA>      NA       NA #> 3440       <NA>      NA       NA #> 3441       <NA>      NA       NA #> 3442       <NA>      NA       NA #> 3443          U      NA       NA #> 3444       <NA>      NA       NA #> 3445       <NA>      NA       NA #> 3446          +      NA       NA #> 3447       <NA>      NA       NA #> 3448          I      NA       NA #> 3449       <NA>      NA       NA #> 3450       <NA>      NA       NA #> 3451       <NA>      NA       NA #> 3452       <NA>      NA       NA #> 3453          +      NA       NA #> 3454          U      NA       NA #> 3455       <NA>      NA       NA #> 3456       <NA>      NA       NA #> 3457          +      NA       NA #> 3458       <NA>      NA       NA #> 3459          I      NA       NA #> 3460       <NA>      NA       NA #> 3461       <NA>      NA       NA #> 3462       <NA>      NA       NA #> 3463       <NA>      NA       NA #> 3464       <NA>      NA       NA #> 3465       <NA>      NA       NA #> 3466       <NA>      NA       NA #> 3467       <NA>      NA       NA #> 3468       <NA>      NA       NA #> 3469          U      NA       NA #> 3470       <NA>      NA       NA #> 3471       <NA>      NA       NA #> 3472          +      NA       NA #> 3473       <NA>      NA       NA #> 3474          I      NA       NA #> 3475       <NA>      NA       NA #> 3476       <NA>      NA       NA #> 3477       <NA>      NA      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NA       NA #> 3506       <NA>      NA       NA #> 3507       <NA>      NA       NA #> 3508       <NA>      NA       NA #> 3509       <NA>      NA       NA #> 3510       <NA>      NA       NA #> 3511       <NA>      NA       NA #> 3512       <NA>      NA       NA #> 3513       <NA>      NA       NA #> 3514       <NA>      NA       NA #> 3515       <NA>      NA       NA #> 3516       <NA>      NA       NA #> 3517       <NA>      NA       NA #> 3518       <NA>      NA       NA #> 3519       <NA>      NA       NA #> 3520          +      NA       NA #> 3521       <NA>      NA       NA #> 3522          I      NA       NA #> 3523       <NA>      NA       NA #> 3524       <NA>      NA       NA #> 3525       <NA>      NA       NA #> 3526       <NA>      NA       NA #> 3527       <NA>      NA       NA #> 3528       <NA>      NA       NA #> 3529       <NA>      NA       NA #> 3530       <NA>      NA       NA #> 3531       <NA>      NA       NA #> 3532       <NA>      NA       NA #> 3533       <NA>      NA       NA #> 3534       <NA>      NA       NA #> 3535       <NA>      NA       NA #> 3536       <NA>      NA       NA #> 3537       <NA>      NA       NA #> 3538       <NA>      NA       NA #> 3539          +      NA       NA #> 3540       <NA>      NA       NA #> 3541          I      NA       NA #> 3542          A      NA       NA #> 3543       <NA>      NA       NA #> 3544       <NA>      NA       NA #> 3545       <NA>      NA       NA #> 3546       <NA>      NA       NA #> 3547       <NA>      NA       NA #> 3548       <NA>      NA       NA #> 3549       <NA>      NA       NA #> 3550          +      NA       NA #> 3551       <NA>      NA       NA #> 3552          I      NA       NA #> 3553       <NA>      NA       NA #> 3554       <NA>      NA       NA #> 3555       <NA>      NA       NA #> 3556       <NA>      NA       NA #> 3557       <NA>      NA       NA #> 3558          U      NA       NA #> 3559       <NA>      NA       NA #> 3560       <NA>      NA       NA #> 3561          +      NA       NA #> 3562       <NA>      NA       NA #> 3563          I      NA       NA #> 3564       <NA>      NA       NA #> 3565       <NA>      NA       NA #> 3566       <NA>      NA       NA #> 3567       <NA>      NA       NA #> 3568       <NA>      NA       NA #> 3569          U      NA       NA #> 3570       <NA>      NA       NA #> 3571       <NA>      NA       NA #> 3572          +      NA       NA #> 3573       <NA>      NA       NA #> 3574          I      NA       NA #> 3575       <NA>      NA       NA #> 3576       <NA>      NA       NA #> 3577       <NA>      NA       NA #> 3578       <NA>      NA       NA #> 3579       <NA>      NA       NA #> 3580          U      NA       NA #> 3581       <NA>      NA       NA #> 3582       <NA>      NA       NA #> 3583          +      NA       NA #> 3584       <NA>      NA       NA #> 3585          I      NA       NA #> 3586       <NA>      NA       NA #> 3587       <NA>      NA       NA #> 3588       <NA>      NA      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NA       NA #> 3617       <NA>      NA       NA #> 3618       <NA>      NA       NA #> 3619       <NA>      NA       NA #> 3620       <NA>      NA       NA #> 3621       <NA>      NA       NA #> 3622       <NA>      NA       NA #> 3623       <NA>      NA       NA #> 3624          I      NA       NA #> 3625       <NA>      NA       NA #> 3626       <NA>      NA       NA #> 3627          +      NA       NA #> 3628       <NA>      NA       NA #> 3629          I      NA       NA #> 3630       <NA>      NA       NA #> 3631       <NA>      NA       NA #> 3632       <NA>      NA       NA #> 3633       <NA>      NA       NA #> 3634       <NA>      NA       NA #> 3635          U      NA       NA #> 3636       <NA>      NA       NA #> 3637       <NA>      NA       NA #> 3638          +      NA       NA #> 3639       <NA>      NA       NA #> 3640       <NA>      NA       NA #> 3641       <NA>      NA       NA #> 3642          A      NA       NA #> 3643       <NA>      NA       NA #> 3644       <NA>      NA       NA #> 3645       <NA>      NA       NA #> 3646          I      NA       NA #> 3647       <NA>      NA       NA #> 3648       <NA>      NA       NA #> 3649          +      NA       NA #> 3650       <NA>      NA       NA #> 3651          I      NA       NA #> 3652       <NA>      NA       NA #> 3653       <NA>      NA       NA #> 3654       <NA>      NA       NA #> 3655       <NA>      NA       NA #> 3656       <NA>      NA       NA #> 3657          U      NA       NA #> 3658       <NA>      NA       NA #> 3659       <NA>      NA       NA #> 3660          +      NA       NA #> 3661       <NA>      NA       NA #> 3662       <NA>      NA       NA #> 3663       <NA>      NA       NA #> 3664       <NA>      NA       NA #> 3665       <NA>      NA       NA #> 3666       <NA>      NA       NA #> 3667       <NA>      NA       NA #> 3668          U      NA       NA #> 3669       <NA>      NA       NA #> 3670       <NA>      NA       NA #> 3671          +      NA       NA #> 3672       <NA>      NA       NA #> 3673          I      NA       NA #> 3674       <NA>      NA       NA #> 3675       <NA>      NA       NA #> 3676       <NA>      NA       NA #> 3677       <NA>      NA       NA #> 3678       <NA>      NA       NA #> 3679          U      NA       NA #> 3680       <NA>      NA       NA #> 3681       <NA>      NA       NA #> 3682          +      NA       NA #> 3683       <NA>      NA       NA #> 3684       <NA>      NA       NA #> 3685       <NA>      NA       NA #> 3686       <NA>      NA       NA #> 3687       <NA>      NA       NA #> 3688       <NA>      NA       NA #> 3689       <NA>      NA       NA #> 3690          U      NA       NA #> 3691       <NA>      NA       NA #> 3692       <NA>      NA       NA #> 3693          +      NA       NA #> 3694       <NA>      NA       NA #> 3695          I      NA       NA #> 3696       <NA>      NA       NA #> 3697       <NA>      NA       NA #> 3698       <NA>      NA       NA #> 3699       <NA>      NA      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NA       NA #> 3728       <NA>      NA       NA #> 3729       <NA>      NA       NA #> 3730       <NA>      NA       NA #> 3731       <NA>      NA       NA #> 3732       <NA>      NA       NA #> 3733       <NA>      NA       NA #> 3734       <NA>      NA       NA #> 3735       <NA>      NA       NA #> 3736       <NA>      NA       NA #> 3737          +      NA       NA #> 3738       <NA>      NA       NA #> 3739       <NA>      NA       NA #> 3740       <NA>      NA       NA #> 3741       <NA>      NA       NA #> 3742       <NA>      NA       NA #> 3743       <NA>      NA       NA #> 3744       <NA>      NA       NA #> 3745       <NA>      NA       NA #> 3746       <NA>      NA       NA #> 3747       <NA>      NA       NA #> 3748          +      NA       NA #> 3749       <NA>      NA       NA #> 3750          I      NA       NA #> 3751       <NA>      NA       NA #> 3752       <NA>      NA       NA #> 3753       <NA>      NA       NA #> 3754       <NA>      NA       NA #> 3755       <NA>      NA       NA #> 3756          U      NA       NA #> 3757       <NA>      NA       NA #> 3758       <NA>      NA       NA #> 3759          +      NA       NA #> 3760       <NA>      NA       NA #> 3761          I      NA       NA #> 3762       <NA>      NA       NA #> 3763       <NA>      NA       NA #> 3764          +      NA       NA #> 3765          I      NA       NA #> 3766       <NA>      NA       NA #> 3767       <NA>      NA       NA #> 3768          +      NA       NA #> 3769       <NA>      NA       NA #> 3770       <NA>      NA       NA #> 3771       <NA>      NA       NA #> 3772       <NA>      NA       NA #> 3773          +      NA       NA #> 3774       <NA>      NA       NA #> 3775       <NA>      NA       NA #> 3776       <NA>      NA       NA #> 3777          +      NA       NA #> 3778       <NA>      NA       NA #> 3779       <NA>      NA       NA #> 3780       <NA>      NA       NA #> 3781       <NA>      NA       NA #> 3782          +      NA       NA #> 3783          I      NA       NA #> 3784       <NA>      NA       NA #> 3785       <NA>      NA       NA #> 3786          +      NA       NA #> 3787       <NA>      NA       NA #> 3788       <NA>      NA       NA #> 3789       <NA>      NA       NA #> 3790       <NA>      NA       NA #> 3791       <NA>      NA       NA #> 3792          +      NA       NA #> 3793          I      NA       NA #> 3794       <NA>      NA       NA #> 3795       <NA>      NA       NA #> 3796          +      NA       NA #> 3797       <NA>      NA       NA #> 3798       <NA>      NA       NA #> 3799       <NA>      NA       NA #> 3800          A      NA       NA #> 3801       <NA>      NA       NA #> 3802          +      NA       NA #> 3803       <NA>      NA       NA #> 3804       <NA>      NA       NA #> 3805       <NA>      NA       NA #> 3806          +      NA       NA #> 3807       <NA>      NA       NA #> 3808          A      NA       NA #> 3809       <NA>      NA       NA #> 3810          A      NA      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NA       NA #> 3839          +      NA       NA #> 3840       <NA>      NA       NA #> 3841       <NA>      NA       NA #> 3842       <NA>      NA       NA #> 3843          +      NA       NA #> 3844       <NA>      NA       NA #> 3845          A      NA       NA #> 3846       <NA>      NA       NA #> 3847       <NA>      NA       NA #> 3848       <NA>      NA       NA #> 3849       <NA>      NA       NA #> 3850       <NA>      NA       NA #> 3851          +      NA       NA #> 3852       <NA>      NA       NA #> 3853          A      NA       NA #> 3854       <NA>      NA       NA #> 3855          A      NA       NA #> 3856       <NA>      NA       NA #> 3857       <NA>      NA       NA #> 3858          +      NA       NA #> 3859       <NA>      NA       NA #> 3860       <NA>      NA       NA #> 3861       <NA>      NA       NA #> 3862       <NA>      NA       NA #> 3863          +      NA       NA #> 3864       <NA>      NA       NA #> 3865       <NA>      NA       NA #> 3866       <NA>      NA       NA #> 3867          +      NA       NA #> 3868       <NA>      NA       NA #> 3869       <NA>      NA       NA #> 3870       <NA>      NA       NA #> 3871       <NA>      NA       NA #> 3872          +      NA       NA #> 3873          I      NA       NA #> 3874       <NA>      NA       NA #> 3875          +      NA       NA #> 3876       <NA>      NA       NA #> 3877       <NA>      NA       NA #> 3878       <NA>      NA       NA #> 3879       <NA>      NA       NA #> 3880          +      NA       NA #> 3881       <NA>      NA       NA #> 3882          +      NA       NA #> 3883       <NA>      NA       NA #> 3884          A      NA       NA #> 3885       <NA>      NA       NA #> 3886       <NA>      NA       NA #> 3887          +      NA       NA #> 3888       <NA>      NA       NA #> 3889       <NA>      NA       NA #> 3890       <NA>      NA       NA #> 3891          +      NA       NA #> 3892       <NA>      NA       NA #> 3893       <NA>      NA       NA #> 3894       <NA>      NA       NA #> 3895       <NA>      NA       NA #> 3896       <NA>      NA       NA #> 3897          +      NA       NA #> 3898          I      NA       NA #> 3899       <NA>      NA       NA #> 3900       <NA>      NA       NA #> 3901          +      NA       NA #> 3902       <NA>      NA       NA #> 3903       <NA>      NA       NA #> 3904       <NA>      NA       NA #> 3905       <NA>      NA       NA #> 3906       <NA>      NA       NA #> 3907       <NA>      NA       NA #> 3908       <NA>      NA       NA #> 3909          +      NA       NA #> 3910       <NA>      NA       NA #> 3911       <NA>      NA       NA #> 3912       <NA>      NA       NA #> 3913       <NA>      NA       NA #> 3914       <NA>      NA       NA #> 3915          +      NA       NA #> 3916       <NA>      NA       NA #> 3917       <NA>      NA       NA #> 3918       <NA>      NA       NA #> 3919          +      NA       NA #> 3920       <NA>      NA       NA #> 3921       <NA>      NA      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NA       NA #> 3950       <NA>      NA       NA #> 3951          +      NA       NA #> 3952          I      NA       NA #> 3953       <NA>      NA       NA #> 3954       <NA>      NA       NA #> 3955          +      NA       NA #> 3956       <NA>      NA       NA #> 3957          A      NA       NA #> 3958          I      NA       NA #> 3959       <NA>      NA       NA #> 3960          +      NA       NA #> 3961          U      NA       NA #> 3962       <NA>      NA       NA #> 3963          +      NA       NA #> 3964       <NA>      NA       NA #> 3965       <NA>      NA       NA #> 3966       <NA>      NA       NA #> 3967       <NA>      NA       NA #> 3968          +      NA       NA #> 3969          I      NA       NA #> 3970       <NA>      NA       NA #> 3971       <NA>      NA       NA #> 3972          +      NA       NA #> 3973       <NA>      NA       NA #> 3974       <NA>      NA       NA #> 3975       <NA>      NA       NA #> 3976          A      NA       NA #> 3977       <NA>      NA       NA #> 3978          +      NA       NA #> 3979          I      NA       NA #> 3980       <NA>      NA       NA #> 3981       <NA>      NA       NA #> 3982          +      NA       NA #> 3983       <NA>      NA       NA #> 3984       <NA>      NA       NA #> 3985       <NA>      NA       NA #> 3986       <NA>      NA       NA #> 3987          +      NA       NA #> 3988          I      NA       NA #> 3989       <NA>      NA       NA #> 3990       <NA>      NA       NA #> 3991          +      NA       NA #> 3992       <NA>      NA       NA #> 3993       <NA>      NA       NA #> 3994       <NA>      NA       NA #> 3995       <NA>      NA       NA #> 3996          I      NA       NA #> 3997       <NA>      NA       NA #> 3998          +      NA       NA #> 3999       <NA>      NA       NA #> 4000       <NA>      NA       NA #> 4001       <NA>      NA       NA #> 4002       <NA>      NA       NA #> 4003          +      NA       NA #> 4004          I      NA       NA #> 4005       <NA>      NA       NA #> 4006       <NA>      NA       NA #> 4007          +      NA       NA #> 4008       <NA>      NA       NA #> 4009       <NA>      NA       NA #> 4010       <NA>      NA       NA #> 4011       <NA>      NA       NA #> 4012          +      NA       NA #> 4013       <NA>      NA       NA #> 4014       <NA>      NA       NA #> 4015       <NA>      NA       NA #> 4016          +      NA       NA #> 4017       <NA>      NA       NA #> 4018       <NA>      NA       NA #> 4019          I      NA       NA #> 4020       <NA>      NA       NA #> 4021       <NA>      NA       NA #> 4022          +      NA       NA #> 4023       <NA>      NA       NA #> 4024       <NA>      NA       NA #> 4025       <NA>      NA       NA #> 4026          +      NA       NA #> 4027       <NA>      NA       NA #> 4028       <NA>      NA       NA #> 4029       <NA>      NA       NA #> 4030          A      NA       NA #> 4031          +      NA       NA #> 4032       <NA>      NA      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NA       NA #> 4061          I      NA       NA #> 4062       <NA>      NA       NA #> 4063          +      NA       NA #> 4064       <NA>      NA       NA #> 4065          A      NA       NA #> 4066          A      NA       NA #> 4067       <NA>      NA       NA #> 4068          +      NA       NA #> 4069          U      NA       NA #> 4070       <NA>      NA       NA #> 4071       <NA>      NA       NA #> 4072          +      NA       NA #> 4073       <NA>      NA       NA #> 4074       <NA>      NA       NA #> 4075       <NA>      NA       NA #> 4076       <NA>      NA       NA #> 4077       <NA>      NA       NA #> 4078          +      NA       NA #> 4079          I      NA       NA #> 4080       <NA>      NA       NA #> 4081          +      NA       NA #> 4082       <NA>      NA       NA #> 4083       <NA>      NA       NA #> 4084       <NA>      NA       NA #> 4085       <NA>      NA       NA #> 4086          +      NA       NA #> 4087       <NA>      NA       NA #> 4088          +      NA       NA #> 4089       <NA>      NA       NA #> 4090       <NA>      NA       NA #> 4091       <NA>      NA       NA #> 4092          +      NA       NA #> 4093       <NA>      NA       NA #> 4094       <NA>      NA       NA #> 4095       <NA>      NA       NA #> 4096          +      NA       NA #> 4097       <NA>      NA       NA #> 4098       <NA>      NA       NA #> 4099       <NA>      NA       NA #> 4100       <NA>      NA       NA #> 4101       <NA>      NA       NA #> 4102          +      NA       NA #> 4103       <NA>      NA       NA #> 4104       <NA>      NA       NA #> 4105       <NA>      NA       NA #> 4106          +      NA       NA #> 4107       <NA>      NA       NA #> 4108       <NA>      NA       NA #> 4109       <NA>      NA       NA #> 4110       <NA>      NA       NA #> 4111       <NA>      NA       NA #> 4112       <NA>      NA       NA #> 4113       <NA>      NA       NA #> 4114       <NA>      NA       NA #> 4115          +      NA       NA #> 4116   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4144          +      NA       NA #> 4145          I      NA       NA #> 4146       <NA>      NA       NA #> 4147       <NA>      NA       NA #> 4148          +      NA       NA #> 4149       <NA>      NA       NA #> 4150       <NA>      NA       NA #> 4151       <NA>      NA       NA #> 4152          A      NA       NA #> 4153       <NA>      NA       NA #> 4154       <NA>      NA       NA #> 4155          I      NA       NA #> 4156       <NA>      NA       NA #> 4157       <NA>      NA       NA #> 4158          +      NA       NA #> 4159       <NA>      NA       NA #> 4160       <NA>      NA       NA #> 4161       <NA>      NA       NA #> 4162       <NA>      NA       NA #> 4163       <NA>      NA       NA #> 4164       <NA>      NA       NA #> 4165          I      NA       NA #> 4166       <NA>      NA       NA #> 4167       <NA>      NA       NA #> 4168          +      NA       NA #> 4169       <NA>      NA       NA #> 4170       <NA>      NA       NA #> 4171       <NA>      NA      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NA       NA #> 4200          A      NA       NA #> 4201       <NA>      NA       NA #> 4202       <NA>      NA       NA #> 4203       <NA>      NA       NA #> 4204       <NA>      NA       NA #> 4205          U      NA       NA #> 4206       <NA>      NA       NA #> 4207       <NA>      NA       NA #> 4208          +      NA       NA #> 4209       <NA>      NA       NA #> 4210       <NA>      NA       NA #> 4211       <NA>      NA       NA #> 4212       <NA>      NA       NA #> 4213       <NA>      NA       NA #> 4214       <NA>      NA       NA #> 4215          I      NA       NA #> 4216       <NA>      NA       NA #> 4217       <NA>      NA       NA #> 4218          +      NA       NA #> 4219       <NA>      NA       NA #> 4220       <NA>      NA       NA #> 4221          I      NA       NA #> 4222       <NA>      NA       NA #> 4223       <NA>      NA       NA #> 4224       <NA>      NA       NA #> 4225          I      NA       NA #> 4226       <NA>      NA       NA #> 4227       <NA>      NA       NA #> 4228          +      NA       NA #> 4229       <NA>      NA       NA #> 4230       <NA>      NA       NA #> 4231       <NA>      NA       NA #> 4232       <NA>      NA       NA #> 4233       <NA>      NA       NA #> 4234       <NA>      NA       NA #> 4235          I      NA       NA #> 4236       <NA>      NA       NA #> 4237       <NA>      NA       NA #> 4238          +      NA       NA #> 4239       <NA>      NA       NA #> 4240          A      NA       NA #> 4241       <NA>      NA       NA #> 4242       <NA>      NA       NA #> 4243       <NA>      NA       NA #> 4244       <NA>      NA       NA #> 4245          A      NA       NA #> 4246       <NA>      NA       NA #> 4247       <NA>      NA       NA #> 4248          U      NA       NA #> 4249       <NA>      NA       NA #> 4250       <NA>      NA       NA #> 4251          +      NA       NA #> 4252       <NA>      NA       NA #> 4253       <NA>      NA       NA #> 4254       <NA>      NA       NA #> 4255       <NA>      NA       NA #> 4256       <NA>      NA       NA #> 4257       <NA>      NA       NA #> 4258          U      NA       NA #> 4259       <NA>      NA       NA #> 4260       <NA>      NA       NA #> 4261          +      NA       NA #> 4262       <NA>      NA       NA #> 4263       <NA>      NA       NA #> 4264       <NA>      NA       NA #> 4265       <NA>      NA       NA #> 4266       <NA>      NA       NA #> 4267       <NA>      NA       NA #> 4268          I      NA       NA #> 4269       <NA>      NA       NA #> 4270       <NA>      NA       NA #> 4271          +      NA       NA #> 4272       <NA>      NA       NA #> 4273       <NA>      NA       NA #> 4274       <NA>      NA       NA #> 4275       <NA>      NA       NA #> 4276       <NA>      NA       NA #> 4277       <NA>      NA       NA #> 4278          I      NA       NA #> 4279       <NA>      NA       NA #> 4280       <NA>      NA       NA #> 4281          +      NA       NA #> 4282       <NA>      NA      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NA       NA #> 4311       <NA>      NA       NA #> 4312       <NA>      NA       NA #> 4313       <NA>      NA       NA #> 4314       <NA>      NA       NA #> 4315       <NA>      NA       NA #> 4316       <NA>      NA       NA #> 4317          +      NA       NA #> 4318       <NA>      NA       NA #> 4319       <NA>      NA       NA #> 4320          I      NA       NA #> 4321          A      NA       NA #> 4322          I      NA       NA #> 4323       <NA>      NA       NA #> 4324       <NA>      NA       NA #> 4325          +      NA       NA #> 4326       <NA>      NA       NA #> 4327       <NA>      NA       NA #> 4328          I      NA       NA #> 4329       <NA>      NA       NA #> 4330          U      NA       NA #> 4331       <NA>      NA       NA #> 4332       <NA>      NA       NA #> 4333          +      NA       NA #> 4334       <NA>      NA       NA #> 4335       <NA>      NA       NA #> 4336       <NA>      NA       NA #> 4337       <NA>      NA       NA #> 4338          I      NA       NA #> 4339       <NA>      NA       NA #> 4340          +      NA       NA #> 4341       <NA>      NA       NA #> 4342       <NA>      NA       NA #> 4343          I      NA       NA #> 4344       <NA>      NA       NA #> 4345       <NA>      NA       NA #> 4346       <NA>      NA       NA #> 4347          I      NA       NA #> 4348       <NA>      NA       NA #> 4349       <NA>      NA       NA #> 4350          +      NA       NA #> 4351       <NA>      NA       NA #> 4352       <NA>      NA       NA #> 4353       <NA>      NA       NA #> 4354          A      NA       NA #> 4355       <NA>      NA       NA #> 4356       <NA>      NA       NA #> 4357          I      NA       NA #> 4358       <NA>      NA       NA #> 4359       <NA>      NA       NA #> 4360          +      NA       NA #> 4361       <NA>      NA       NA #> 4362       <NA>      NA       NA #> 4363          I      NA       NA #> 4364       <NA>      NA       NA #> 4365       <NA>      NA       NA #> 4366       <NA>      NA       NA #> 4367          I      NA       NA #> 4368       <NA>      NA       NA #> 4369       <NA>      NA       NA #> 4370          +      NA       NA #> 4371       <NA>      NA       NA #> 4372       <NA>      NA       NA #> 4373       <NA>      NA       NA #> 4374       <NA>      NA       NA #> 4375       <NA>      NA       NA #> 4376       <NA>      NA       NA #> 4377          U      NA       NA #> 4378       <NA>      NA       NA #> 4379       <NA>      NA       NA #> 4380          +      NA       NA #> 4381       <NA>      NA       NA #> 4382          A      NA       NA #> 4383       <NA>      NA       NA #> 4384       <NA>      NA       NA #> 4385       <NA>      NA       NA #> 4386       <NA>      NA       NA #> 4387       <NA>      NA       NA #> 4388          +      NA       NA #> 4389       <NA>      NA       NA #> 4390       <NA>      NA       NA #> 4391       <NA>      NA       NA #> 4392       <NA>      NA       NA #> 4393       <NA>      NA       NA #> 4394       <NA>      NA       NA #> 4395       <NA>      NA       NA #> 4396       <NA>      NA       NA #> 4397       <NA>      NA       NA #> 4398          +      NA       NA #> 4399       <NA>      NA       NA #> 4400       <NA>      NA       NA #> 4401          I      NA       NA #> 4402       <NA>      NA       NA #> 4403       <NA>      NA       NA #> 4404       <NA>      NA       NA #> 4405       <NA>      NA       NA #> 4406       <NA>      NA       NA #> 4407          +      NA       NA #> 4408       <NA>      NA       NA #> 4409       <NA>      NA       NA #> 4410          I      NA       NA #> 4411       <NA>      NA       NA #> 4412       <NA>      NA       NA #> 4413       <NA>      NA       NA #> 4414          I      NA       NA #> 4415       <NA>      NA       NA #> 4416       <NA>      NA       NA #> 4417          +      NA       NA #> 4418       <NA>      NA       NA #> 4419       <NA>      NA       NA #> 4420          I      NA       NA #> 4421          A      NA      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NA       NA #> 4450       <NA>      NA       NA #> 4451          A      NA       NA #> 4452       <NA>      NA       NA #> 4453       <NA>      NA       NA #> 4454       <NA>      NA       NA #> 4455       <NA>      NA       NA #> 4456       <NA>      NA       NA #> 4457          +      NA       NA #> 4458       <NA>      NA       NA #> 4459       <NA>      NA       NA #> 4460          I      NA       NA #> 4461          A      NA       NA #> 4462       <NA>      NA       NA #> 4463       <NA>      NA       NA #> 4464       <NA>      NA       NA #> 4465       <NA>      NA       NA #> 4466       <NA>      NA       NA #> 4467          +      NA       NA #> 4468       <NA>      NA       NA #> 4469       <NA>      NA       NA #> 4470       <NA>      NA       NA #> 4471       <NA>      NA       NA #> 4472       <NA>      NA       NA #> 4473       <NA>      NA       NA #> 4474          I      NA       NA #> 4475       <NA>      NA       NA #> 4476       <NA>      NA       NA #> 4477          +      NA       NA #> 4478       <NA>      NA       NA #> 4479       <NA>      NA       NA #> 4480       <NA>      NA       NA #> 4481       <NA>      NA       NA #> 4482       <NA>      NA       NA #> 4483       <NA>      NA       NA #> 4484          U      NA       NA #> 4485       <NA>      NA       NA #> 4486       <NA>      NA       NA #> 4487          +      NA       NA #> 4488       <NA>      NA       NA #> 4489       <NA>      NA       NA #> 4490       <NA>      NA       NA #> 4491       <NA>      NA       NA #> 4492          U      NA       NA #> 4493       <NA>      NA       NA #> 4494       <NA>      NA       NA #> 4495          +      NA       NA #> 4496       <NA>      NA       NA #> 4497       <NA>      NA       NA #> 4498       <NA>      NA       NA #> 4499       <NA>      NA       NA #> 4500       <NA>      NA       NA #> 4501       <NA>      NA       NA #> 4502       <NA>      NA       NA #> 4503       <NA>      NA       NA #> 4504       <NA>      NA       NA #> 4505          +      NA       NA #> 4506       <NA>      NA       NA #> 4507          I      NA       NA #> 4508       <NA>      NA       NA #> 4509       <NA>      NA       NA #> 4510       <NA>      NA       NA #> 4511       <NA>      NA       NA #> 4512          I      NA       NA #> 4513       <NA>      NA       NA #> 4514       <NA>      NA       NA #> 4515          +      NA       NA #> 4516       <NA>      NA       NA #> 4517       <NA>      NA       NA #> 4518       <NA>      NA       NA #> 4519       <NA>      NA       NA #> 4520       <NA>      NA       NA #> 4521       <NA>      NA       NA #> 4522       <NA>      NA       NA #> 4523       <NA>      NA       NA #> 4524       <NA>      NA       NA #> 4525          +      NA       NA #> 4526       <NA>      NA       NA #> 4527       <NA>      NA       NA #> 4528       <NA>      NA       NA #> 4529       <NA>      NA       NA #> 4530       <NA>      NA       NA #> 4531       <NA>      NA       NA #> 4532          +      NA       NA #> 4533          U      NA       NA #> 4534       <NA>      NA       NA #> 4535       <NA>      NA       NA #> 4536       <NA>      NA       NA #> 4537       <NA>      NA       NA #> 4538       <NA>      NA       NA #> 4539       <NA>      NA       NA #> 4540       <NA>      NA       NA #> 4541       <NA>      NA       NA #> 4542          +      NA       NA #> 4543       <NA>      NA       NA #> 4544       <NA>      NA       NA #> 4545       <NA>      NA       NA #> 4546       <NA>      NA       NA #> 4547       <NA>      NA       NA #> 4548          +      NA       NA #> 4549          U      NA       NA #> 4550       <NA>      NA       NA #> 4551       <NA>      NA       NA #> 4552       <NA>      NA       NA #> 4553       <NA>      NA       NA #> 4554       <NA>      NA       NA #> 4555       <NA>      NA       NA #> 4556       <NA>      NA       NA #> 4557       <NA>      NA       NA #> 4558          +      NA       NA #> 4559       <NA>      NA       NA #> 4560       <NA>      NA       NA #> 4561       <NA>      NA       NA #> 4562       <NA>      NA       NA #> 4563       <NA>      NA       NA #> 4564          +      NA       NA #> 4565          U      NA       NA #> 4566       <NA>      NA       NA #> 4567       <NA>      NA       NA #> 4568       <NA>      NA       NA #> 4569       <NA>      NA       NA #> 4570       <NA>      NA       NA #> 4571       <NA>      NA       NA #> 4572       <NA>      NA       NA #> 4573       <NA>      NA       NA #> 4574          +      NA       NA #> 4575       <NA>      NA       NA #> 4576       <NA>      NA       NA #> 4577       <NA>      NA       NA #> 4578          +      NA       NA #> 4579       <NA>      NA       NA #> 4580       <NA>      NA       NA #> 4581       <NA>      NA       NA #> 4582       <NA>      NA       NA #> 4583       <NA>      NA       NA #> 4584          +      NA       NA #> 4585       <NA>      NA       NA #> 4586       <NA>      NA       NA #> 4587       <NA>      NA       NA #> 4588       <NA>      NA       NA #> 4589       <NA>      NA       NA #> 4590       <NA>      NA       NA #> 4591       <NA>      NA       NA #> 4592       <NA>      NA       NA #> 4593       <NA>      NA       NA #> 4594          +      NA       NA #> 4595       <NA>      NA       NA #> 4596       <NA>      NA       NA #> 4597       <NA>      NA       NA #> 4598          +      NA       NA #> 4599       <NA>      NA       NA #> 4600       <NA>      NA       NA #> 4601       <NA>      NA       NA #> 4602       <NA>      NA       NA #> 4603       <NA>      NA       NA #> 4604          +      NA       NA #> 4605          U      NA       NA #> 4606       <NA>      NA       NA #> 4607       <NA>      NA       NA #> 4608       <NA>      NA       NA #> 4609       <NA>      NA       NA #> 4610       <NA>      NA       NA #> 4611       <NA>      NA       NA #> 4612       <NA>      NA       NA #> 4613       <NA>      NA       NA #> 4614          +      NA       NA #> 4615       <NA>      NA       NA #> 4616       <NA>      NA       NA #> 4617       <NA>      NA       NA #> 4618          +      NA       NA #> 4619       <NA>      NA       NA #> 4620       <NA>      NA       NA #> 4621       <NA>      NA       NA #> 4622       <NA>      NA       NA #> 4623          +      NA       NA #> 4624       <NA>      NA       NA #> 4625       <NA>      NA       NA #> 4626       <NA>      NA       NA #> 4627       <NA>      NA       NA #> 4628       <NA>      NA       NA #> 4629          I      NA       NA #> 4630       <NA>      NA       NA #> 4631       <NA>      NA       NA #> 4632       <NA>      NA       NA #> 4633          +      NA       NA #> 4634       <NA>      NA       NA #> 4635       <NA>      NA       NA #> 4636       <NA>      NA       NA #> 4637          +      NA       NA #> 4638       <NA>      NA       NA #> 4639       <NA>      NA       NA #> 4640       <NA>      NA       NA #> 4641       <NA>      NA       NA #> 4642       <NA>      NA       NA #> 4643          I      NA       NA #> 4644          +      NA       NA #> 4645       <NA>      NA       NA #> 4646          +      NA       NA #> 4647       <NA>      NA       NA #> 4648          I      NA       NA #> 4649       <NA>      NA       NA #> 4650          A      NA       NA #> 4651       <NA>      NA       NA #> 4652       <NA>      NA       NA #> 4653       <NA>      NA       NA #> 4654       <NA>      NA       NA #> 4655          +      NA       NA #> 4656       <NA>      NA       NA #> 4657          +      NA       NA #> 4658       <NA>      NA       NA #> 4659          I      NA       NA #> 4660       <NA>      NA       NA #> 4661       <NA>      NA       NA #> 4662       <NA>      NA       NA #> 4663       <NA>      NA       NA #> 4664       <NA>      NA       NA #> 4665       <NA>      NA       NA #> 4666          +      NA       NA #> 4667       <NA>      NA       NA #> 4668          +      NA       NA #> 4669       <NA>      NA       NA #> 4670          I      NA       NA #> 4671       <NA>      NA      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NA       NA #> 4700          +      NA       NA #> 4701       <NA>      NA       NA #> 4702          I      NA       NA #> 4703       <NA>      NA       NA #> 4704       <NA>      NA       NA #> 4705       <NA>      NA       NA #> 4706       <NA>      NA       NA #> 4707       <NA>      NA       NA #> 4708       <NA>      NA       NA #> 4709       <NA>      NA       NA #> 4710          U      NA       NA #> 4711       <NA>      NA       NA #> 4712       <NA>      NA       NA #> 4713          +      NA       NA #> 4714       <NA>      NA       NA #> 4715          A      NA       NA #> 4716          A      NA       NA #> 4717       <NA>      NA       NA #> 4718       <NA>      NA       NA #> 4719       <NA>      NA       NA #> 4720       <NA>      NA       NA #> 4721          U      NA       NA #> 4722       <NA>      NA       NA #> 4723       <NA>      NA       NA #> 4724          +      NA       NA #> 4725       <NA>      NA       NA #> 4726          I      NA       NA #> 4727       <NA>      NA       NA #> 4728       <NA>      NA       NA #> 4729       <NA>      NA       NA #> 4730       <NA>      NA       NA #> 4731       <NA>      NA       NA #> 4732          U      NA       NA #> 4733       <NA>      NA       NA #> 4734       <NA>      NA       NA #> 4735          +      NA       NA #> 4736       <NA>      NA       NA #> 4737       <NA>      NA       NA #> 4738       <NA>      NA       NA #> 4739       <NA>      NA       NA #> 4740       <NA>      NA       NA #> 4741       <NA>      NA       NA #> 4742       <NA>      NA       NA #> 4743          I      NA       NA #> 4744       <NA>      NA       NA #> 4745       <NA>      NA       NA #> 4746          +      NA       NA #> 4747       <NA>      NA       NA #> 4748          I      NA       NA #> 4749       <NA>      NA       NA #> 4750       <NA>      NA       NA #> 4751       <NA>      NA       NA #> 4752       <NA>      NA       NA #> 4753       <NA>      NA       NA #> 4754       <NA>      NA       NA #> 4755       <NA>      NA       NA #> 4756       <NA>      NA       NA #> 4757          +      NA       NA #> 4758       <NA>      NA       NA #> 4759          I      NA       NA #> 4760       <NA>      NA       NA #> 4761       <NA>      NA       NA #> 4762       <NA>      NA       NA #> 4763       <NA>      NA       NA #> 4764       <NA>      NA       NA #> 4765          I      NA       NA #> 4766       <NA>      NA       NA #> 4767       <NA>      NA       NA #> 4768       <NA>      NA       NA #> 4769          I      NA       NA #> 4770       <NA>      NA       NA #> 4771       <NA>      NA       NA #> 4772          +      NA       NA #> 4773       <NA>      NA       NA #> 4774          I      NA       NA #> 4775       <NA>      NA       NA #> 4776       <NA>      NA       NA #> 4777       <NA>      NA       NA #> 4778       <NA>      NA       NA #> 4779       <NA>      NA       NA #> 4780          I      NA       NA #> 4781       <NA>      NA       NA #> 4782       <NA>      NA      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NA       NA #> 4811          I      NA       NA #> 4812       <NA>      NA       NA #> 4813       <NA>      NA       NA #> 4814       <NA>      NA       NA #> 4815       <NA>      NA       NA #> 4816       <NA>      NA       NA #> 4817       <NA>      NA       NA #> 4818       <NA>      NA       NA #> 4819       <NA>      NA       NA #> 4820          +      NA       NA #> 4821       <NA>      NA       NA #> 4822          I      NA       NA #> 4823       <NA>      NA       NA #> 4824       <NA>      NA       NA #> 4825       <NA>      NA       NA #> 4826       <NA>      NA       NA #> 4827       <NA>      NA       NA #> 4828       <NA>      NA       NA #> 4829       <NA>      NA       NA #> 4830       <NA>      NA       NA #> 4831          +      NA       NA #> 4832       <NA>      NA       NA #> 4833          I      NA       NA #> 4834       <NA>      NA       NA #> 4835       <NA>      NA       NA #> 4836       <NA>      NA       NA #> 4837       <NA>      NA       NA #> 4838       <NA>      NA       NA #> 4839          U      NA       NA #> 4840       <NA>      NA       NA #> 4841       <NA>      NA       NA #> 4842          +      NA       NA #> 4843       <NA>      NA       NA #> 4844       <NA>      NA       NA #> 4845       <NA>      NA       NA #> 4846       <NA>      NA       NA #> 4847       <NA>      NA       NA #> 4848       <NA>      NA       NA #> 4849       <NA>      NA       NA #> 4850          U      NA       NA #> 4851       <NA>      NA       NA #> 4852       <NA>      NA       NA #> 4853          +      NA       NA #> 4854       <NA>      NA       NA #> 4855          I      NA       NA #> 4856       <NA>      NA       NA #> 4857          I      NA       NA #> 4858       <NA>      NA       NA #> 4859       <NA>      NA       NA #> 4860       <NA>      NA       NA #> 4861          U      NA       NA #> 4862       <NA>      NA       NA #> 4863       <NA>      NA       NA #> 4864          +      NA       NA #> 4865       <NA>      NA       NA #> 4866          I      NA       NA #> 4867       <NA>      NA       NA #> 4868       <NA>      NA       NA #> 4869       <NA>      NA       NA #> 4870       <NA>      NA       NA #> 4871       <NA>      NA       NA #> 4872          I      NA       NA #> 4873       <NA>      NA       NA #> 4874       <NA>      NA       NA #> 4875          +      NA       NA #> 4876       <NA>      NA       NA #> 4877          I      NA       NA #> 4878       <NA>      NA       NA #> 4879       <NA>      NA       NA #> 4880       <NA>      NA       NA #> 4881       <NA>      NA       NA #> 4882       <NA>      NA       NA #> 4883       <NA>      NA       NA #> 4884       <NA>      NA       NA #> 4885       <NA>      NA       NA #> 4886          +      NA       NA #> 4887       <NA>      NA       NA #> 4888          I      NA       NA #> 4889       <NA>      NA       NA #> 4890       <NA>      NA       NA #> 4891       <NA>      NA       NA #> 4892       <NA>      NA       NA #> 4893       <NA>      NA      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NA       NA #> 4922          A      NA       NA #> 4923       <NA>      NA       NA #> 4924       <NA>      NA       NA #> 4925       <NA>      NA       NA #> 4926       <NA>      NA       NA #> 4927       <NA>      NA       NA #> 4928       <NA>      NA       NA #> 4929          +      NA       NA #> 4930       <NA>      NA       NA #> 4931          I      NA       NA #> 4932          A      NA       NA #> 4933       <NA>      NA       NA #> 4934       <NA>      NA       NA #> 4935       <NA>      NA       NA #> 4936       <NA>      NA       NA #> 4937          U      NA       NA #> 4938       <NA>      NA       NA #> 4939       <NA>      NA       NA #> 4940          +      NA       NA #> 4941       <NA>      NA       NA #> 4942          I      NA       NA #> 4943          A      NA       NA #> 4944       <NA>      NA       NA #> 4945       <NA>      NA       NA #> 4946       <NA>      NA       NA #> 4947       <NA>      NA       NA #> 4948          U      NA       NA #> 4949       <NA>      NA       NA #> 4950       <NA>      NA       NA #> 4951          +      NA       NA #> 4952       <NA>      NA       NA #> 4953          I      NA       NA #> 4954       <NA>      NA       NA #> 4955       <NA>      NA       NA #> 4956       <NA>      NA       NA #> 4957       <NA>      NA       NA #> 4958       <NA>      NA       NA #> 4959          I      NA       NA #> 4960       <NA>      NA       NA #> 4961       <NA>      NA       NA #> 4962          +      NA       NA #> 4963       <NA>      NA       NA #> 4964          I      NA       NA #> 4965       <NA>      NA       NA #> 4966       <NA>      NA       NA #> 4967       <NA>      NA       NA #> 4968       <NA>      NA       NA #> 4969       <NA>      NA       NA #> 4970       <NA>      NA       NA #> 4971       <NA>      NA       NA #> 4972       <NA>      NA       NA #> 4973          +      NA       NA #> 4974       <NA>      NA       NA #> 4975          I      NA       NA #> 4976       <NA>      NA       NA #> 4977       <NA>      NA       NA #> 4978       <NA>      NA       NA #> 4979       <NA>      NA       NA #> 4980       <NA>      NA       NA #> 4981       <NA>      NA       NA #> 4982       <NA>      NA       NA #> 4983       <NA>      NA       NA #> 4984          +      NA       NA #> 4985       <NA>      NA       NA #> 4986          I      NA       NA #> 4987       <NA>      NA       NA #> 4988       <NA>      NA       NA #> 4989       <NA>      NA       NA #> 4990       <NA>      NA       NA #> 4991       <NA>      NA       NA #> 4992       <NA>      NA       NA #> 4993       <NA>      NA       NA #> 4994       <NA>      NA       NA #> 4995          +      NA       NA #> 4996       <NA>      NA       NA #> 4997          I      NA       NA #> 4998       <NA>      NA       NA #> 4999       <NA>      NA       NA #> 5000       <NA>      NA       NA #> 5001       <NA>      NA       NA #> 5002       <NA>      NA       NA #> 5003          U      NA       NA #> 5004       <NA>      NA      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NA       NA #> 5033       <NA>      NA       NA #> 5034       <NA>      NA       NA #> 5035          +      NA       NA #> 5036       <NA>      NA       NA #> 5037       <NA>      NA       NA #> 5038       <NA>      NA       NA #> 5039          +      NA       NA #> 5040       <NA>      NA       NA #> 5041       <NA>      NA       NA #> 5042       <NA>      NA       NA #> 5043       <NA>      NA       NA #> 5044       <NA>      NA       NA #> 5045          +      NA       NA #> 5046          U      NA       NA #> 5047       <NA>      NA       NA #> 5048       <NA>      NA       NA #> 5049       <NA>      NA       NA #> 5050       <NA>      NA       NA #> 5051       <NA>      NA       NA #> 5052       <NA>      NA       NA #> 5053       <NA>      NA       NA #> 5054       <NA>      NA       NA #> 5055          +      NA       NA #> 5056       <NA>      NA       NA #> 5057       <NA>      NA       NA #> 5058       <NA>      NA       NA #> 5059          +      NA       NA #> 5060       <NA>      NA       NA #> 5061       <NA>      NA       NA #> 5062          A      NA       NA #> 5063          +      NA       NA #> 5064       <NA>      NA       NA #> 5065       <NA>      NA       NA #> 5066       <NA>      NA       NA #> 5067          +      NA       NA #> 5068       <NA>      NA       NA #> 5069       <NA>      NA       NA #> 5070       <NA>      NA       NA #> 5071       <NA>      NA       NA #> 5072       <NA>      NA       NA #> 5073          +      NA       NA #> 5074       <NA>      NA       NA #> 5075       <NA>      NA       NA #> 5076       <NA>      NA       NA #> 5077          +      NA       NA #> 5078       <NA>      NA       NA #> 5079       <NA>      NA       NA #> 5080       <NA>      NA       NA #> 5081          A      NA       NA #> 5082       <NA>      NA       NA #> 5083          +      NA       NA #> 5084       <NA>      NA       NA #> 5085       <NA>      NA       NA #> 5086       <NA>      NA       NA #> 5087          +      NA       NA #> 5088       <NA>      NA       NA #> 5089       <NA>      NA       NA #> 5090       <NA>      NA       NA #> 5091       <NA>      NA       NA #> 5092       <NA>      NA       NA #> 5093          +      NA       NA #> 5094          I      NA       NA #> 5095       <NA>      NA       NA #> 5096       <NA>      NA       NA #> 5097          +      NA       NA #> 5098       <NA>      NA       NA #> 5099       <NA>      NA       NA #> 5100       <NA>      NA       NA #> 5101       <NA>      NA       NA #> 5102       <NA>      NA       NA #> 5103          +      NA       NA #> 5104          I      NA       NA #> 5105       <NA>      NA       NA #> 5106       <NA>      NA       NA #> 5107          +      NA       NA #> 5108       <NA>      NA       NA #> 5109       <NA>      NA       NA #> 5110       <NA>      NA       NA #> 5111       <NA>      NA       NA #> 5112       <NA>      NA       NA #> 5113          +      NA       NA #> 5114          I      NA       NA #> 5115       <NA>      NA      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NA       NA #> 5144          +      NA       NA #> 5145       <NA>      NA       NA #> 5146          A      NA       NA #> 5147       <NA>      NA       NA #> 5148          A      NA       NA #> 5149       <NA>      NA       NA #> 5150          +      NA       NA #> 5151       <NA>      NA       NA #> 5152       <NA>      NA       NA #> 5153       <NA>      NA       NA #> 5154          +      NA       NA #> 5155       <NA>      NA       NA #> 5156       <NA>      NA       NA #> 5157       <NA>      NA       NA #> 5158          A      NA       NA #> 5159       <NA>      NA       NA #> 5160          +      NA       NA #> 5161       <NA>      NA       NA #> 5162       <NA>      NA       NA #> 5163       <NA>      NA       NA #> 5164          +      NA       NA #> 5165       <NA>      NA       NA #> 5166       <NA>      NA       NA #> 5167       <NA>      NA       NA #> 5168       <NA>      NA       NA #> 5169       <NA>      NA       NA #> 5170          +      NA       NA #> 5171       <NA>      NA       NA #> 5172       <NA>      NA       NA #> 5173       <NA>      NA       NA #> 5174          +      NA       NA #> 5175       <NA>      NA       NA #> 5176       <NA>      NA       NA #> 5177       <NA>      NA       NA #> 5178          A      NA       NA #> 5179       <NA>      NA       NA #> 5180          +      NA       NA #> 5181       <NA>      NA       NA #> 5182       <NA>      NA       NA #> 5183       <NA>      NA       NA #> 5184          +      NA       NA #> 5185       <NA>      NA       NA #> 5186       <NA>      NA       NA #> 5187       <NA>      NA       NA #> 5188          A      NA       NA #> 5189       <NA>      NA       NA #> 5190          +      NA       NA #> 5191       <NA>      NA       NA #> 5192       <NA>      NA       NA #> 5193       <NA>      NA       NA #> 5194          +      NA       NA #> 5195       <NA>      NA       NA #> 5196       <NA>      NA       NA #> 5197       <NA>      NA       NA #> 5198       <NA>      NA       NA #> 5199       <NA>      NA       NA #> 5200          +      NA       NA #> 5201       <NA>      NA       NA #> 5202       <NA>      NA       NA #> 5203       <NA>      NA       NA #> 5204          +      NA       NA #> 5205       <NA>      NA       NA #> 5206       <NA>      NA       NA #> 5207       <NA>      NA       NA #> 5208          A      NA       NA #> 5209       <NA>      NA       NA #> 5210          +      NA       NA #> 5211       <NA>      NA       NA #> 5212       <NA>      NA       NA #> 5213       <NA>      NA       NA #> 5214          +      NA       NA #> 5215       <NA>      NA       NA #> 5216       <NA>      NA       NA #> 5217       <NA>      NA       NA #> 5218          A      NA       NA #> 5219       <NA>      NA       NA #> 5220          +      NA       NA #> 5221          I      NA       NA #> 5222       <NA>      NA       NA #> 5223       <NA>      NA       NA #> 5224          +      NA       NA #> 5225       <NA>      NA       NA #> 5226       <NA>      NA      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NA       NA #> 5255       <NA>      NA       NA #> 5256       <NA>      NA       NA #> 5257          A      NA       NA #> 5258       <NA>      NA       NA #> 5259          +      NA       NA #> 5260       <NA>      NA       NA #> 5261       <NA>      NA       NA #> 5262       <NA>      NA       NA #> 5263          +      NA       NA #> 5264       <NA>      NA       NA #> 5265       <NA>      NA       NA #> 5266       <NA>      NA       NA #> 5267          A      NA       NA #> 5268       <NA>      NA       NA #> 5269       <NA>      NA       NA #> 5270          +      NA       NA #> 5271       <NA>      NA       NA #> 5272       <NA>      NA       NA #> 5273       <NA>      NA       NA #> 5274          A      NA       NA #> 5275       <NA>      NA       NA #> 5276          +      NA       NA #> 5277       <NA>      NA       NA #> 5278       <NA>      NA       NA #> 5279       <NA>      NA       NA #> 5280          +      NA       NA #> 5281       <NA>      NA       NA #> 5282       <NA>      NA       NA #> 5283       <NA>      NA       NA #> 5284       <NA>      NA       NA #> 5285       <NA>      NA       NA #> 5286          +      NA       NA #> 5287       <NA>      NA       NA #> 5288       <NA>      NA       NA #> 5289       <NA>      NA       NA #> 5290          +      NA       NA #> 5291       <NA>      NA       NA #> 5292       <NA>      NA       NA #> 5293       <NA>      NA       NA #> 5294          A      NA       NA #> 5295       <NA>      NA       NA #> 5296          +      NA       NA #> 5297          U      NA       NA #> 5298       <NA>      NA       NA #> 5299       <NA>      NA       NA #> 5300          +      NA       NA #> 5301       <NA>      NA       NA #> 5302       <NA>      NA       NA #> 5303       <NA>      NA       NA #> 5304       <NA>      NA       NA #> 5305       <NA>      NA       NA #> 5306          +      NA       NA #> 5307          U      NA       NA #> 5308       <NA>      NA       NA #> 5309       <NA>      NA       NA #> 5310          +      NA       NA #> 5311       <NA>      NA       NA #> 5312       <NA>      NA       NA #> 5313       <NA>      NA       NA #> 5314          A      NA       NA #> 5315       <NA>      NA       NA #> 5316          +      NA       NA #> 5317          U      NA       NA #> 5318       <NA>      NA       NA #> 5319       <NA>      NA       NA #> 5320          +      NA       NA #> 5321       <NA>      NA       NA #> 5322          A      NA       NA #> 5323       <NA>      NA       NA #> 5324          A      NA       NA #> 5325       <NA>      NA       NA #> 5326          +      NA       NA #> 5327          I      NA       NA #> 5328       <NA>      NA       NA #> 5329          +      NA       NA #> 5330       <NA>      NA       NA #> 5331       <NA>      NA       NA #> 5332       <NA>      NA       NA #> 5333       <NA>      NA       NA #> 5334       <NA>      NA       NA #> 5335          +      NA       NA #> 5336       <NA>      NA       NA #> 5337       <NA>      NA      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NA       NA #> 5366          +      NA       NA #> 5367       <NA>      NA       NA #> 5368       <NA>      NA       NA #> 5369       <NA>      NA       NA #> 5370       <NA>      NA       NA #> 5371       <NA>      NA       NA #> 5372       <NA>      NA       NA #> 5373          U      NA       NA #> 5374       <NA>      NA       NA #> 5375       <NA>      NA       NA #> 5376          +      NA       NA #> 5377       <NA>      NA       NA #> 5378       <NA>      NA       NA #> 5379       <NA>      NA       NA #> 5380       <NA>      NA       NA #> 5381       <NA>      NA       NA #> 5382          +      NA       NA #> 5383          I      NA       NA #> 5384       <NA>      NA       NA #> 5385       <NA>      NA       NA #> 5386          +      NA       NA #> 5387       <NA>      NA       NA #> 5388       <NA>      NA       NA #> 5389       <NA>      NA       NA #> 5390       <NA>      NA       NA #> 5391       <NA>      NA       NA #> 5392       <NA>      NA       NA #> 5393       <NA>      NA       NA #> 5394       <NA>      NA       NA #> 5395       <NA>      NA       NA #> 5396          +      NA       NA #> 5397       <NA>      NA       NA #> 5398       <NA>      NA       NA #> 5399       <NA>      NA       NA #> 5400          A      NA       NA #> 5401       <NA>      NA       NA #> 5402       <NA>      NA       NA #> 5403          I      NA       NA #> 5404       <NA>      NA       NA #> 5405       <NA>      NA       NA #> 5406          +      NA       NA #> 5407       <NA>      NA       NA #> 5408       <NA>      NA       NA #> 5409       <NA>      NA       NA #> 5410          A      NA       NA #> 5411       <NA>      NA       NA #> 5412       <NA>      NA       NA #> 5413          I      NA       NA #> 5414       <NA>      NA       NA #> 5415       <NA>      NA       NA #> 5416          +      NA       NA #> 5417       <NA>      NA       NA #> 5418          A      NA       NA #> 5419       <NA>      NA       NA #> 5420       <NA>      NA       NA #> 5421       <NA>      NA       NA #> 5422       <NA>      NA       NA #> 5423          I      NA       NA #> 5424       <NA>      NA       NA #> 5425       <NA>      NA       NA #> 5426          +      NA       NA #> 5427       <NA>      NA       NA #> 5428       <NA>      NA       NA #> 5429       <NA>      NA       NA #> 5430       <NA>      NA       NA #> 5431       <NA>      NA       NA #> 5432       <NA>      NA       NA #> 5433       <NA>      NA       NA #> 5434       <NA>      NA       NA #> 5435       <NA>      NA       NA #> 5436          +      NA       NA #> 5437       <NA>      NA       NA #> 5438       <NA>      NA       NA #> 5439       <NA>      NA       NA #> 5440       <NA>      NA       NA #> 5441       <NA>      NA       NA #> 5442       <NA>      NA       NA #> 5443       <NA>      NA       NA #> 5444       <NA>      NA       NA #> 5445       <NA>      NA       NA #> 5446          +      NA       NA #> 5447       <NA>      NA       NA #> 5448          A      NA      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NA       NA #> 5477       <NA>      NA       NA #> 5478       <NA>      NA       NA #> 5479          A      NA       NA #> 5480       <NA>      NA       NA #> 5481       <NA>      NA       NA #> 5482          U      NA       NA #> 5483       <NA>      NA       NA #> 5484       <NA>      NA       NA #> 5485          +      NA       NA #> 5486       <NA>      NA       NA #> 5487       <NA>      NA       NA #> 5488       <NA>      NA       NA #> 5489          A      NA       NA #> 5490       <NA>      NA       NA #> 5491       <NA>      NA       NA #> 5492          I      NA       NA #> 5493       <NA>      NA       NA #> 5494       <NA>      NA       NA #> 5495          +      NA       NA #> 5496       <NA>      NA       NA #> 5497       <NA>      NA       NA #> 5498       <NA>      NA       NA #> 5499          A      NA       NA #> 5500       <NA>      NA       NA #> 5501       <NA>      NA       NA #> 5502          I      NA       NA #> 5503       <NA>      NA       NA #> 5504       <NA>      NA       NA #> 5505          +      NA       NA #> 5506       <NA>      NA       NA #> 5507       <NA>      NA       NA #> 5508       <NA>      NA       NA #> 5509          A      NA       NA #> 5510       <NA>      NA       NA #> 5511       <NA>      NA       NA #> 5512          U      NA       NA #> 5513       <NA>      NA       NA #> 5514       <NA>      NA       NA #> 5515          +      NA       NA #> 5516       <NA>      NA       NA #> 5517       <NA>      NA       NA #> 5518       <NA>      NA       NA #> 5519       <NA>      NA       NA #> 5520       <NA>      NA       NA #> 5521       <NA>      NA       NA #> 5522       <NA>      NA       NA #> 5523       <NA>      NA       NA #> 5524       <NA>      NA       NA #> 5525          +      NA       NA #> 5526       <NA>      NA       NA #> 5527       <NA>      NA       NA #> 5528          A      NA       NA #> 5529       <NA>      NA       NA #> 5530       <NA>      NA       NA #> 5531       <NA>      NA       NA #> 5532          I      NA       NA #> 5533       <NA>      NA       NA #> 5534       <NA>      NA       NA #> 5535          +      NA       NA #> 5536       <NA>      NA       NA #> 5537       <NA>      NA       NA #> 5538       <NA>      NA       NA #> 5539          A      NA       NA #> 5540       <NA>      NA       NA #> 5541       <NA>      NA       NA #> 5542          I      NA       NA #> 5543       <NA>      NA       NA #> 5544       <NA>      NA       NA #> 5545          +      NA       NA #> 5546       <NA>      NA       NA #> 5547       <NA>      NA       NA #> 5548       <NA>      NA       NA #> 5549       <NA>      NA       NA #> 5550       <NA>      NA       NA #> 5551       <NA>      NA       NA #> 5552       <NA>      NA       NA #> 5553       <NA>      NA       NA #> 5554       <NA>      NA       NA #> 5555          +      NA       NA #> 5556       <NA>      NA       NA #> 5557          A      NA       NA #> 5558       <NA>      NA       NA #> 5559       <NA>      NA      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NA       NA #> 5588       <NA>      NA       NA #> 5589       <NA>      NA       NA #> 5590       <NA>      NA       NA #> 5591       <NA>      NA       NA #> 5592       <NA>      NA       NA #> 5593       <NA>      NA       NA #> 5594       <NA>      NA       NA #> 5595          +      NA       NA #> 5596       <NA>      NA       NA #> 5597          A      NA       NA #> 5598       <NA>      NA       NA #> 5599       <NA>      NA       NA #> 5600       <NA>      NA       NA #> 5601       <NA>      NA       NA #> 5602       <NA>      NA       NA #> 5603       <NA>      NA       NA #> 5604       <NA>      NA       NA #> 5605          +      NA       NA #> 5606       <NA>      NA       NA #> 5607       <NA>      NA       NA #> 5608          I      NA       NA #> 5609       <NA>      NA       NA #> 5610       <NA>      NA       NA #> 5611       <NA>      NA       NA #> 5612       <NA>      NA       NA #> 5613       <NA>      NA       NA #> 5614       <NA>      NA       NA #> 5615          +      NA       NA #> 5616       <NA>      NA       NA #> 5617       <NA>      NA       NA #> 5618       <NA>      NA       NA #> 5619          A      NA       NA #> 5620       <NA>      NA       NA #> 5621       <NA>      NA       NA #> 5622          I      NA       NA #> 5623       <NA>      NA       NA #> 5624       <NA>      NA       NA #> 5625          +      NA       NA #> 5626       <NA>      NA       NA #> 5627       <NA>      NA       NA #> 5628       <NA>      NA       NA #> 5629          A      NA       NA #> 5630       <NA>      NA       NA #> 5631       <NA>      NA       NA #> 5632          I      NA       NA #> 5633       <NA>      NA       NA #> 5634       <NA>      NA       NA #> 5635          +      NA       NA #> 5636       <NA>      NA       NA #> 5637          A      NA       NA #> 5638       <NA>      NA       NA #> 5639       <NA>      NA       NA #> 5640       <NA>      NA       NA #> 5641       <NA>      NA       NA #> 5642       <NA>      NA       NA #> 5643       <NA>      NA       NA #> 5644       <NA>      NA       NA #> 5645          +      NA       NA #> 5646       <NA>      NA       NA #> 5647       <NA>      NA       NA #> 5648       <NA>      NA       NA #> 5649       <NA>      NA       NA #> 5650       <NA>      NA       NA #> 5651       <NA>      NA       NA #> 5652          I      NA       NA #> 5653       <NA>      NA       NA #> 5654       <NA>      NA       NA #> 5655          +      NA       NA #> 5656       <NA>      NA       NA #> 5657       <NA>      NA       NA #> 5658       <NA>      NA       NA #> 5659       <NA>      NA       NA #> 5660       <NA>      NA       NA #> 5661       <NA>      NA       NA #> 5662          U      NA       NA #> 5663       <NA>      NA       NA #> 5664       <NA>      NA       NA #> 5665          +      NA       NA #> 5666       <NA>      NA       NA #> 5667       <NA>      NA       NA #> 5668       <NA>      NA       NA #> 5669       <NA>      NA       NA #> 5670       <NA>      NA       NA #> 5671       <NA>      NA       NA #> 5672          U      NA       NA #> 5673       <NA>      NA       NA #> 5674       <NA>      NA       NA #> 5675          +      NA       NA #> 5676       <NA>      NA       NA #> 5677       <NA>      NA       NA #> 5678       <NA>      NA       NA #> 5679       <NA>      NA       NA #> 5680       <NA>      NA       NA #> 5681       <NA>      NA       NA #> 5682       <NA>      NA       NA #> 5683       <NA>      NA       NA #> 5684       <NA>      NA       NA #> 5685          +      NA       NA #> 5686       <NA>      NA       NA #> 5687          A      NA       NA #> 5688       <NA>      NA       NA #> 5689          A      NA       NA #> 5690       <NA>      NA       NA #> 5691       <NA>      NA       NA #> 5692       <NA>      NA       NA #> 5693       <NA>      NA       NA #> 5694       <NA>      NA       NA #> 5695          +      NA       NA #> 5696       <NA>      NA       NA #> 5697       <NA>      NA       NA #> 5698       <NA>      NA      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NA       NA #> 5727          A      NA       NA #> 5728       <NA>      NA       NA #> 5729       <NA>      NA       NA #> 5730       <NA>      NA       NA #> 5731       <NA>      NA       NA #> 5732       <NA>      NA       NA #> 5733       <NA>      NA       NA #> 5734       <NA>      NA       NA #> 5735          +      NA       NA #> 5736       <NA>      NA       NA #> 5737       <NA>      NA       NA #> 5738       <NA>      NA       NA #> 5739       <NA>      NA       NA #> 5740       <NA>      NA       NA #> 5741       <NA>      NA       NA #> 5742          I      NA       NA #> 5743       <NA>      NA       NA #> 5744       <NA>      NA       NA #> 5745          +      NA       NA #> 5746       <NA>      NA       NA #> 5747       <NA>      NA       NA #> 5748       <NA>      NA       NA #> 5749       <NA>      NA       NA #> 5750       <NA>      NA       NA #> 5751       <NA>      NA       NA #> 5752       <NA>      NA       NA #> 5753       <NA>      NA       NA #> 5754          +      NA       NA #> 5755       <NA>      NA       NA #> 5756       <NA>      NA       NA #> 5757       <NA>      NA       NA #> 5758       <NA>      NA       NA #> 5759       <NA>      NA       NA #> 5760       <NA>      NA       NA #> 5761          I      NA       NA #> 5762       <NA>      NA       NA #> 5763       <NA>      NA       NA #> 5764          +      NA       NA #> 5765       <NA>      NA       NA #> 5766          A      NA       NA #> 5767       <NA>      NA       NA #> 5768       <NA>      NA       NA #> 5769       <NA>      NA       NA #> 5770       <NA>      NA       NA #> 5771          I      NA       NA #> 5772       <NA>      NA       NA #> 5773       <NA>      NA       NA #> 5774          +      NA       NA #> 5775       <NA>      NA       NA #> 5776          A      NA       NA #> 5777       <NA>      NA       NA #> 5778       <NA>      NA       NA #> 5779       <NA>      NA       NA #> 5780       <NA>      NA       NA #> 5781          U      NA       NA #> 5782   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<NA>      NA       NA #> 6116       <NA>      NA       NA #> 6117       <NA>      NA       NA #> 6118          U      NA       NA #> 6119       <NA>      NA       NA #> 6120       <NA>      NA       NA #> 6121          +      NA       NA #> 6122       <NA>      NA       NA #> 6123       <NA>      NA       NA #> 6124       <NA>      NA       NA #> 6125       <NA>      NA       NA #> 6126       <NA>      NA       NA #> 6127       <NA>      NA       NA #> 6128       <NA>      NA       NA #> 6129       <NA>      NA       NA #> 6130       <NA>      NA       NA #> 6131       <NA>      NA       NA #> 6132          +      NA       NA #> 6133       <NA>      NA       NA #> 6134          I      NA       NA #> 6135          A      NA       NA #> 6136       <NA>      NA       NA #> 6137       <NA>      NA       NA #> 6138       <NA>      NA       NA #> 6139       <NA>      NA       NA #> 6140       <NA>      NA       NA #> 6141       <NA>      NA       NA #> 6142          +      NA       NA #> 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<NA>      NA       NA #> 6227       <NA>      NA       NA #> 6228       <NA>      NA       NA #> 6229       <NA>      NA       NA #> 6230       <NA>      NA       NA #> 6231       <NA>      NA       NA #> 6232       <NA>      NA       NA #> 6233       <NA>      NA       NA #> 6234       <NA>      NA       NA #> 6235       <NA>      NA       NA #> 6236       <NA>      NA       NA #> 6237       <NA>      NA       NA #> 6238          A      NA       NA #> 6239       <NA>      NA       NA #> 6240          +      NA       NA #> 6241       <NA>      NA       NA #> 6242       <NA>      NA       NA #> 6243       <NA>      NA       NA #> 6244          +      NA       NA #> 6245       <NA>      NA       NA #> 6246          A      NA       NA #> 6247       <NA>      NA       NA #> 6248       <NA>      NA       NA #> 6249       <NA>      NA       NA #> 6250          +      NA       NA #> 6251       <NA>      NA       NA #> 6252       <NA>      NA       NA #> 6253       <NA>      NA       NA #> 6254          +      NA       NA #> 6255       <NA>      NA       NA #> 6256       <NA>      NA       NA #> 6257       <NA>      NA       NA #> 6258       <NA>      NA       NA #> 6259       <NA>      NA       NA #> 6260          +      NA       NA #> 6261          U      NA       NA #> 6262       <NA>      NA       NA #> 6263       <NA>      NA       NA #> 6264          +      NA       NA #> 6265       <NA>      NA       NA #> 6266       <NA>      NA       NA #> 6267       <NA>      NA       NA #> 6268       <NA>      NA       NA #> 6269       <NA>      NA       NA #> 6270          +      NA       NA #> 6271       <NA>      NA       NA #> 6272       <NA>      NA       NA #> 6273          +      NA       NA #> 6274       <NA>      NA       NA #> 6275       <NA>      NA       NA #> 6276       <NA>      NA       NA #> 6277       <NA>      NA       NA #> 6278       <NA>      NA       NA #> 6279          +      NA       NA #> 6280       <NA>      NA       NA #> 6281       <NA>      NA      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NA       NA #> 6310       <NA>      NA       NA #> 6311       <NA>      NA       NA #> 6312       <NA>      NA       NA #> 6313       <NA>      NA       NA #> 6314       <NA>      NA       NA #> 6315          +      NA       NA #> 6316       <NA>      NA       NA #> 6317       <NA>      NA       NA #> 6318          +      NA       NA #> 6319       <NA>      NA       NA #> 6320       <NA>      NA       NA #> 6321          I      NA       NA #> 6322          A      NA       NA #> 6323       <NA>      NA       NA #> 6324          +      NA       NA #> 6325       <NA>      NA       NA #> 6326       <NA>      NA       NA #> 6327          +      NA       NA #> 6328       <NA>      NA       NA #> 6329          A      NA       NA #> 6330       <NA>      NA       NA #> 6331          A      NA       NA #> 6332          +      NA       NA #> 6333       <NA>      NA       NA #> 6334       <NA>      NA       NA #> 6335       <NA>      NA       NA #> 6336          +      NA       NA #> 6337       <NA>      NA       NA #> 6338       <NA>      NA       NA #> 6339       <NA>      NA       NA #> 6340       <NA>      NA       NA #> 6341       <NA>      NA       NA #> 6342          +      NA       NA #> 6343       <NA>      NA       NA #> 6344       <NA>      NA       NA #> 6345          +      NA       NA #> 6346       <NA>      NA       NA #> 6347       <NA>      NA       NA #> 6348       <NA>      NA       NA #> 6349       <NA>      NA       NA #> 6350       <NA>      NA       NA #> 6351       <NA>      NA       NA #> 6352       <NA>      NA       NA #> 6353          +      NA       NA #> 6354       <NA>      NA       NA #> 6355       <NA>      NA       NA #> 6356       <NA>      NA       NA #> 6357       <NA>      NA       NA #> 6358          +      NA       NA #> 6359          U      NA       NA #> 6360       <NA>      NA       NA #> 6361       <NA>      NA       NA #> 6362          +      NA       NA #> 6363       <NA>      NA       NA #> 6364       <NA>      NA       NA #> 6365       <NA>      NA       NA #> 6366       <NA>      NA       NA #> 6367       <NA>      NA       NA #> 6368          +      NA       NA #> 6369       <NA>      NA       NA #> 6370       <NA>      NA       NA #> 6371          +      NA       NA #> 6372       <NA>      NA       NA #> 6373       <NA>      NA       NA #> 6374       <NA>      NA       NA #> 6375       <NA>      NA       NA #> 6376       <NA>      NA       NA #> 6377          +      NA       NA #> 6378       <NA>      NA       NA #> 6379       <NA>      NA       NA #> 6380          +      NA       NA #> 6381       <NA>      NA       NA #> 6382       <NA>      NA       NA #> 6383       <NA>      NA       NA #> 6384       <NA>      NA       NA #> 6385       <NA>      NA       NA #> 6386          +      NA       NA #> 6387       <NA>      NA       NA #> 6388       <NA>      NA       NA #> 6389          +      NA       NA #> 6390       <NA>      NA       NA #> 6391       <NA>      NA       NA #> 6392       <NA>      NA      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+      NA       NA #> 6449       <NA>      NA       NA #> 6450       <NA>      NA       NA #> 6451          U      NA       NA #> 6452       <NA>      NA       NA #> 6453       <NA>      NA       NA #> 6454          +      NA       NA #> 6455          I      NA       NA #> 6456       <NA>      NA       NA #> 6457       <NA>      NA       NA #> 6458          +      NA       NA #> 6459       <NA>      NA       NA #> 6460          A      NA       NA #> 6461          I      NA       NA #> 6462       <NA>      NA       NA #> 6463       <NA>      NA       NA #> 6464          +      NA       NA #> 6465       <NA>      NA       NA #> 6466       <NA>      NA       NA #> 6467       <NA>      NA       NA #> 6468          +      NA       NA #> 6469       <NA>      NA       NA #> 6470          A      NA       NA #> 6471       <NA>      NA       NA #> 6472       <NA>      NA       NA #> 6473       <NA>      NA       NA #> 6474          +      NA       NA #> 6475       <NA>      NA       NA #> 6476       <NA>      NA       NA #> 6477       <NA>      NA       NA #> 6478          +      NA       NA #> 6479       <NA>      NA       NA #> 6480       <NA>      NA       NA #> 6481       <NA>      NA       NA #> 6482       <NA>      NA       NA #> 6483       <NA>      NA       NA #> 6484          +      NA       NA #> 6485          U      NA       NA #> 6486       <NA>      NA       NA #> 6487       <NA>      NA       NA #> 6488          +      NA       NA #> 6489       <NA>      NA       NA #> 6490       <NA>      NA       NA #> 6491       <NA>      NA       NA #> 6492       <NA>      NA       NA #> 6493       <NA>      NA       NA #> 6494          +      NA       NA #> 6495       <NA>      NA       NA #> 6496       <NA>      NA       NA #> 6497          +      NA       NA #> 6498       <NA>      NA       NA #> 6499       <NA>      NA       NA #> 6500       <NA>      NA       NA #> 6501       <NA>      NA       NA #> 6502          +      NA       NA #> 6503       <NA>      NA       NA #> 6504       <NA>      NA       NA #> 6505       <NA>      NA       NA #> 6506          +      NA       NA #> 6507       <NA>      NA       NA #> 6508       <NA>      NA       NA #> 6509       <NA>      NA       NA #> 6510       <NA>      NA       NA #> 6511       <NA>      NA       NA #> 6512          +      NA       NA #> 6513       <NA>      NA       NA #> 6514       <NA>      NA       NA #> 6515       <NA>      NA       NA #> 6516          +      NA       NA #> 6517       <NA>      NA       NA #> 6518       <NA>      NA       NA #> 6519       <NA>      NA       NA #> 6520       <NA>      NA       NA #> 6521       <NA>      NA       NA #> 6522          +      NA       NA #> 6523       <NA>      NA       NA #> 6524       <NA>      NA       NA #> 6525       <NA>      NA       NA #> 6526          +      NA       NA #> 6527       <NA>      NA       NA #> 6528       <NA>      NA       NA #> 6529       <NA>      NA       NA #> 6530       <NA>      NA       NA #> 6531       <NA>      NA      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<NA>      NA       NA #> 6588          A      NA       NA #> 6589       <NA>      NA       NA #> 6590          A      NA       NA #> 6591       <NA>      NA       NA #> 6592          +      NA       NA #> 6593          I      NA       NA #> 6594       <NA>      NA       NA #> 6595       <NA>      NA       NA #> 6596          +      NA       NA #> 6597       <NA>      NA       NA #> 6598       <NA>      NA       NA #> 6599          A      NA       NA #> 6600       <NA>      NA       NA #> 6601       <NA>      NA       NA #> 6602          +      NA       NA #> 6603       <NA>      NA       NA #> 6604       <NA>      NA       NA #> 6605       <NA>      NA       NA #> 6606       <NA>      NA       NA #> 6607          +      NA       NA #> 6608       <NA>      NA       NA #> 6609       <NA>      NA       NA #> 6610       <NA>      NA       NA #> 6611          +      NA       NA #> 6612       <NA>      NA       NA #> 6613       <NA>      NA       NA #> 6614       <NA>      NA       NA #> 6615       <NA>      NA       NA #> 6616       <NA>      NA       NA #> 6617       <NA>      NA       NA #> 6618       <NA>      NA       NA #> 6619       <NA>      NA       NA #> 6620       <NA>      NA       NA #> 6621          +      NA       NA #> 6622       <NA>      NA       NA #> 6623       <NA>      NA       NA #> 6624       <NA>      NA       NA #> 6625       <NA>      NA       NA #> 6626       <NA>      NA       NA #> 6627       <NA>      NA       NA #> 6628       <NA>      NA       NA #> 6629       <NA>      NA       NA #> 6630       <NA>      NA       NA #> 6631          +      NA       NA #> 6632       <NA>      NA       NA #> 6633          A      NA       NA #> 6634       <NA>      NA       NA #> 6635       <NA>      NA       NA #> 6636       <NA>      NA       NA #> 6637          +      NA       NA #> 6638       <NA>      NA       NA #> 6639       <NA>      NA       NA #> 6640       <NA>      NA       NA #> 6641          +      NA       NA #> 6642       <NA>      NA      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I      NA       NA #> 6699       <NA>      NA       NA #> 6700       <NA>      NA       NA #> 6701          +      NA       NA #> 6702       <NA>      NA       NA #> 6703       <NA>      NA       NA #> 6704       <NA>      NA       NA #> 6705          A      NA       NA #> 6706       <NA>      NA       NA #> 6707       <NA>      NA       NA #> 6708          I      NA       NA #> 6709       <NA>      NA       NA #> 6710       <NA>      NA       NA #> 6711          +      NA       NA #> 6712       <NA>      NA       NA #> 6713       <NA>      NA       NA #> 6714          I      NA       NA #> 6715       <NA>      NA       NA #> 6716       <NA>      NA       NA #> 6717       <NA>      NA       NA #> 6718       <NA>      NA       NA #> 6719       <NA>      NA       NA #> 6720       <NA>      NA       NA #> 6721          +      NA       NA #> 6722       <NA>      NA       NA #> 6723       <NA>      NA       NA #> 6724       <NA>      NA       NA #> 6725          A      NA       NA #> 6726       <NA>      NA       NA #> 6727       <NA>      NA       NA #> 6728       <NA>      NA       NA #> 6729       <NA>      NA       NA #> 6730       <NA>      NA       NA #> 6731          +      NA       NA #> 6732       <NA>      NA       NA #> 6733       <NA>      NA       NA #> 6734       <NA>      NA       NA #> 6735       <NA>      NA       NA #> 6736       <NA>      NA       NA #> 6737       <NA>      NA       NA #> 6738       <NA>      NA       NA #> 6739       <NA>      NA       NA #> 6740       <NA>      NA       NA #> 6741          +      NA       NA #> 6742       <NA>      NA       NA #> 6743       <NA>      NA       NA #> 6744       <NA>      NA       NA #> 6745       <NA>      NA       NA #> 6746       <NA>      NA       NA #> 6747       <NA>      NA       NA #> 6748          U      NA       NA #> 6749       <NA>      NA       NA #> 6750       <NA>      NA       NA #> 6751          +      NA       NA #> 6752       <NA>      NA       NA #> 6753          A      NA       NA #> 6754          I      NA       NA #> 6755       <NA>      NA       NA #> 6756       <NA>      NA       NA #> 6757       <NA>      NA       NA #> 6758       <NA>      NA       NA #> 6759       <NA>      NA       NA #> 6760       <NA>      NA       NA #> 6761          +      NA       NA #> 6762       <NA>      NA       NA #> 6763       <NA>      NA       NA #> 6764       <NA>      NA       NA #> 6765       <NA>      NA       NA #> 6766       <NA>      NA       NA #> 6767       <NA>      NA       NA #> 6768       <NA>      NA       NA #> 6769       <NA>      NA       NA #> 6770       <NA>      NA       NA #> 6771          +      NA       NA #> 6772       <NA>      NA       NA #> 6773       <NA>      NA       NA #> 6774       <NA>      NA       NA #> 6775          A      NA       NA #> 6776       <NA>      NA       NA #> 6777       <NA>      NA       NA #> 6778       <NA>      NA       NA #> 6779       <NA>      NA       NA #> 6780          +      NA       NA #> 6781       <NA>      NA      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<NA>      NA       NA #> 6838          +      NA       NA #> 6839       <NA>      NA       NA #> 6840       <NA>      NA       NA #> 6841          I      NA       NA #> 6842       <NA>      NA       NA #> 6843       <NA>      NA       NA #> 6844       <NA>      NA       NA #> 6845       <NA>      NA       NA #> 6846       <NA>      NA       NA #> 6847       <NA>      NA       NA #> 6848          +      NA       NA #> 6849       <NA>      NA       NA #> 6850       <NA>      NA       NA #> 6851       <NA>      NA       NA #> 6852       <NA>      NA       NA #> 6853       <NA>      NA       NA #> 6854       <NA>      NA       NA #> 6855       <NA>      NA       NA #> 6856       <NA>      NA       NA #> 6857       <NA>      NA       NA #> 6858          +      NA       NA #> 6859       <NA>      NA       NA #> 6860          A      NA       NA #> 6861       <NA>      NA       NA #> 6862       <NA>      NA       NA #> 6863       <NA>      NA       NA #> 6864       <NA>      NA       NA #> 6865       <NA>      NA       NA #> 6866       <NA>      NA       NA #> 6867       <NA>      NA       NA #> 6868          +      NA       NA #> 6869       <NA>      NA       NA #> 6870       <NA>      NA       NA #> 6871       <NA>      NA       NA #> 6872       <NA>      NA       NA #> 6873       <NA>      NA       NA #> 6874       <NA>      NA       NA #> 6875          +      NA       NA #> 6876       <NA>      NA       NA #> 6877       <NA>      NA       NA #> 6878       <NA>      NA       NA #> 6879          A      NA       NA #> 6880       <NA>      NA       NA #> 6881       <NA>      NA       NA #> 6882       <NA>      NA       NA #> 6883       <NA>      NA       NA #> 6884       <NA>      NA       NA #> 6885          +      NA       NA #> 6886       <NA>      NA       NA #> 6887       <NA>      NA       NA #> 6888       <NA>      NA       NA #> 6889       <NA>      NA       NA #> 6890       <NA>      NA       NA #> 6891       <NA>      NA       NA #> 6892          I      NA      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NA       NA #> 6921       <NA>      NA       NA #> 6922       <NA>      NA       NA #> 6923       <NA>      NA       NA #> 6924       <NA>      NA       NA #> 6925       <NA>      NA       NA #> 6926       <NA>      NA       NA #> 6927       <NA>      NA       NA #> 6928          +      NA       NA #> 6929       <NA>      NA       NA #> 6930       <NA>      NA       NA #> 6931       <NA>      NA       NA #> 6932          A      NA       NA #> 6933       <NA>      NA       NA #> 6934       <NA>      NA       NA #> 6935       <NA>      NA       NA #> 6936       <NA>      NA       NA #> 6937       <NA>      NA       NA #> 6938          +      NA       NA #> 6939       <NA>      NA       NA #> 6940       <NA>      NA       NA #> 6941       <NA>      NA       NA #> 6942       <NA>      NA       NA #> 6943       <NA>      NA       NA #> 6944       <NA>      NA       NA #> 6945          I      NA       NA #> 6946       <NA>      NA       NA #> 6947       <NA>      NA       NA #> 6948          +      NA       NA #> 6949       <NA>      NA       NA #> 6950       <NA>      NA       NA #> 6951       <NA>      NA       NA #> 6952       <NA>      NA       NA #> 6953       <NA>      NA       NA #> 6954       <NA>      NA       NA #> 6955       <NA>      NA       NA #> 6956       <NA>      NA       NA #> 6957       <NA>      NA       NA #> 6958       <NA>      NA       NA #> 6959       <NA>      NA       NA #> 6960          +      NA       NA #> 6961       <NA>      NA       NA #> 6962          +      NA       NA #> 6963       <NA>      NA       NA #> 6964       <NA>      NA       NA #> 6965       <NA>      NA       NA #> 6966       <NA>      NA       NA #> 6967       <NA>      NA       NA #> 6968       <NA>      NA       NA #> 6969          +      NA       NA #> 6970       <NA>      NA       NA #> 6971       <NA>      NA       NA #> 6972          +      NA       NA #> 6973       <NA>      NA       NA #> 6974       <NA>      NA       NA #> 6975       <NA>      NA       NA #> 6976       <NA>      NA       NA #> 6977       <NA>      NA       NA #> 6978       <NA>      NA       NA #> 6979       <NA>      NA       NA #> 6980       <NA>      NA       NA #> 6981       <NA>      NA       NA #> 6982          +      NA       NA #> 6983       <NA>      NA       NA #> 6984       <NA>      NA       NA #> 6985       <NA>      NA       NA #> 6986          +      NA       NA #> 6987       <NA>      NA       NA #> 6988       <NA>      NA       NA #> 6989       <NA>      NA       NA #> 6990          +      NA       NA #> 6991       <NA>      NA       NA #> 6992       <NA>      NA       NA #> 6993       <NA>      NA       NA #> 6994          +      NA       NA #> 6995       <NA>      NA       NA #> 6996       <NA>      NA       NA #> 6997       <NA>      NA       NA #> 6998       <NA>      NA       NA #> 6999       <NA>      NA       NA #> 7000       <NA>      NA       NA #> 7001       <NA>      NA       NA #> 7002       <NA>      NA       NA #> 7003       <NA>      NA       NA #> 7004       <NA>      NA       NA #> 7005       <NA>      NA       NA #> 7006       <NA>      NA       NA #> 7007       <NA>      NA       NA #> 7008       <NA>      NA       NA #> 7009       <NA>      NA       NA #> 7010       <NA>      NA       NA #> 7011       <NA>      NA       NA #> 7012       <NA>      NA       NA #> 7013       <NA>      NA       NA #> 7014       <NA>      NA       NA #> 7015       <NA>      NA       NA #> 7016       <NA>      NA       NA #> 7017       <NA>      NA       NA #> 7018       <NA>      NA       NA #> 7019       <NA>      NA       NA #> 7020       <NA>      NA       NA #> 7021       <NA>      NA       NA #> 7022       <NA>      NA       NA #> 7023       <NA>      NA       NA #> 7024       <NA>      NA       NA #> 7025       <NA>      NA       NA #> 7026          +      NA       NA #> 7027       <NA>      NA       NA #> 7028          +      NA       NA #> 7029       <NA>      NA       NA #> 7030       <NA>      NA       NA #> 7031       <NA>      NA      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<NA>      NA       NA #> 7088          +      NA       NA #> 7089       <NA>      NA       NA #> 7090       <NA>      NA       NA #> 7091       <NA>      NA       NA #> 7092          +      NA       NA #> 7093       <NA>      NA       NA #> 7094       <NA>      NA       NA #> 7095       <NA>      NA       NA #> 7096          +      NA       NA #> 7097       <NA>      NA       NA #> 7098       <NA>      NA       NA #> 7099       <NA>      NA       NA #> 7100          +      NA       NA #> 7101       <NA>      NA       NA #> 7102          +      NA       NA #> 7103       <NA>      NA       NA #> 7104       <NA>      NA       NA #> 7105       <NA>      NA       NA #> 7106          +      NA       NA #> 7107       <NA>      NA       NA #> 7108       <NA>      NA       NA #> 7109       <NA>      NA       NA #> 7110          +      NA       NA #> 7111       <NA>      NA       NA #> 7112       <NA>      NA       NA #> 7113       <NA>      NA       NA #> 7114          +      NA       NA #> 7115       <NA>      NA       NA #> 7116       <NA>      NA       NA #> 7117       <NA>      NA       NA #> 7118          +      NA       NA #> 7119       <NA>      NA       NA #> 7120       <NA>      NA       NA #> 7121       <NA>      NA       NA #> 7122          +      NA       NA #> 7123       <NA>      NA       NA #> 7124       <NA>      NA       NA #> 7125          U      NA       NA #> 7126          +      NA       NA #> 7127       <NA>      NA       NA #> 7128          +      NA       NA #> 7129       <NA>      NA       NA #> 7130          U      NA       NA #> 7131       <NA>      NA       NA #> 7132       <NA>      NA       NA #> 7133       <NA>      NA       NA #> 7134       <NA>      NA       NA #> 7135          +      NA       NA #> 7136       <NA>      NA       NA #> 7137       <NA>      NA       NA #> 7138       <NA>      NA       NA #> 7139       <NA>      NA       NA #> 7140       <NA>      NA       NA #> 7141          U      NA       NA #> 7142          +      NA       NA #> 7143       <NA>      NA       NA #> 7144          +      NA       NA #> 7145       <NA>      NA       NA #> 7146          I      NA       NA #> 7147       <NA>      NA       NA #> 7148       <NA>      NA       NA #> 7149       <NA>      NA       NA #> 7150       <NA>      NA       NA #> 7151          +      NA       NA #> 7152       <NA>      NA       NA #> 7153       <NA>      NA       NA #> 7154       <NA>      NA       NA #> 7155          +      NA       NA #> 7156       <NA>      NA       NA #> 7157       <NA>      NA       NA #> 7158       <NA>      NA       NA #> 7159       <NA>      NA       NA #> 7160       <NA>      NA       NA #> 7161          +      NA       NA #> 7162       <NA>      NA       NA #> 7163          +      NA       NA #> 7164       <NA>      NA       NA #> 7165          U      NA       NA #> 7166       <NA>      NA       NA #> 7167       <NA>      NA       NA #> 7168       <NA>      NA       NA #> 7169       <NA>      NA       NA #> 7170       <NA>      NA       NA #> 7171          I      NA       NA #> 7172          +      NA       NA #> 7173       <NA>      NA       NA #> 7174          +      NA       NA #> 7175       <NA>      NA       NA #> 7176          I      NA       NA #> 7177       <NA>      NA       NA #> 7178       <NA>      NA       NA #> 7179       <NA>      NA       NA #> 7180       <NA>      NA       NA #> 7181          +      NA       NA #> 7182          I      NA       NA #> 7183       <NA>      NA       NA #> 7184       <NA>      NA       NA #> 7185       <NA>      NA       NA #> 7186          I      NA       NA #> 7187          +      NA       NA #> 7188       <NA>      NA       NA #> 7189          +      NA       NA #> 7190       <NA>      NA       NA #> 7191          I      NA       NA #> 7192       <NA>      NA       NA #> 7193       <NA>      NA       NA #> 7194       <NA>      NA       NA #> 7195       <NA>      NA       NA #> 7196       <NA>      NA       NA #> 7197          U      NA       NA #> 7198       <NA>      NA       NA #> 7199       <NA>      NA       NA #> 7200          +      NA       NA #> 7201       <NA>      NA       NA #> 7202          I      NA       NA #> 7203       <NA>      NA       NA #> 7204       <NA>      NA       NA #> 7205       <NA>      NA       NA #> 7206       <NA>      NA       NA #> 7207       <NA>      NA       NA #> 7208          U      NA       NA #> 7209          +      NA       NA #> 7210       <NA>      NA       NA #> 7211          +      NA       NA #> 7212       <NA>      NA       NA #> 7213          I      NA       NA #> 7214       <NA>      NA       NA #> 7215       <NA>      NA       NA #> 7216       <NA>      NA       NA #> 7217       <NA>      NA       NA #> 7218       <NA>      NA       NA #> 7219       <NA>      NA       NA #> 7220          +      NA       NA #> 7221       <NA>      NA       NA #> 7222          +      NA       NA #> 7223       <NA>      NA       NA #> 7224          I      NA       NA #> 7225       <NA>      NA       NA #> 7226       <NA>      NA       NA #> 7227       <NA>      NA       NA #> 7228       <NA>      NA       NA #> 7229       <NA>      NA       NA #> 7230       <NA>      NA       NA #> 7231       <NA>      NA       NA #> 7232       <NA>      NA       NA #> 7233          +      NA       NA #> 7234       <NA>      NA       NA #> 7235          U      NA       NA #> 7236       <NA>      NA       NA #> 7237          I      NA       NA #> 7238       <NA>      NA       NA #> 7239       <NA>      NA       NA #> 7240          +      NA       NA #> 7241       <NA>      NA       NA #> 7242          U      NA       NA #> 7243       <NA>      NA       NA #> 7244       <NA>      NA       NA #> 7245       <NA>      NA       NA #> 7246       <NA>      NA       NA #> 7247       <NA>      NA       NA #> 7248       <NA>      NA       NA #> 7249       <NA>      NA       NA #> 7250       <NA>      NA       NA #> 7251          +      NA       NA #> 7252       <NA>      NA       NA #> 7253          I      NA      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NA       NA #> 7282       <NA>      NA       NA #> 7283       <NA>      NA       NA #> 7284          +      NA       NA #> 7285       <NA>      NA       NA #> 7286          U      NA       NA #> 7287       <NA>      NA       NA #> 7288       <NA>      NA       NA #> 7289       <NA>      NA       NA #> 7290       <NA>      NA       NA #> 7291       <NA>      NA       NA #> 7292       <NA>      NA       NA #> 7293       <NA>      NA       NA #> 7294          +      NA       NA #> 7295       <NA>      NA       NA #> 7296          U      NA       NA #> 7297       <NA>      NA       NA #> 7298          I      NA       NA #> 7299       <NA>      NA       NA #> 7300       <NA>      NA       NA #> 7301       <NA>      NA       NA #> 7302       <NA>      NA       NA #> 7303       <NA>      NA       NA #> 7304       <NA>      NA       NA #> 7305          +      NA       NA #> 7306       <NA>      NA       NA #> 7307          I      NA       NA #> 7308       <NA>      NA       NA #> 7309       <NA>      NA       NA #> 7310       <NA>      NA       NA #> 7311       <NA>      NA       NA #> 7312       <NA>      NA       NA #> 7313       <NA>      NA       NA #> 7314       <NA>      NA       NA #> 7315       <NA>      NA       NA #> 7316          +      NA       NA #> 7317       <NA>      NA       NA #> 7318          I      NA       NA #> 7319       <NA>      NA       NA #> 7320          I      NA       NA #> 7321       <NA>      NA       NA #> 7322       <NA>      NA       NA #> 7323       <NA>      NA       NA #> 7324          U      NA       NA #> 7325       <NA>      NA       NA #> 7326       <NA>      NA       NA #> 7327          +      NA       NA #> 7328       <NA>      NA       NA #> 7329          I      NA       NA #> 7330          A      NA       NA #> 7331          I      NA       NA #> 7332       <NA>      NA       NA #> 7333       <NA>      NA       NA #> 7334       <NA>      NA       NA #> 7335       <NA>      NA       NA #> 7336       <NA>      NA       NA #> 7337       <NA>      NA       NA #> 7338          +      NA       NA #> 7339       <NA>      NA       NA #> 7340          I      NA       NA #> 7341       <NA>      NA       NA #> 7342       <NA>      NA       NA #> 7343       <NA>      NA       NA #> 7344       <NA>      NA       NA #> 7345       <NA>      NA       NA #> 7346       <NA>      NA       NA #> 7347       <NA>      NA       NA #> 7348       <NA>      NA       NA #> 7349       <NA>      NA       NA #> 7350       <NA>      NA       NA #> 7351       <NA>      NA       NA #> 7352       <NA>      NA       NA #> 7353       <NA>      NA       NA #> 7354       <NA>      NA       NA #> 7355       <NA>      NA       NA #> 7356       <NA>      NA       NA #> 7357          +      NA       NA #> 7358       <NA>      NA       NA #> 7359          U      NA       NA #> 7360       <NA>      NA       NA #> 7361          U      NA       NA #> 7362       <NA>      NA       NA #> 7363       <NA>      NA       NA #> 7364       <NA>      NA      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NA       NA #> 7393       <NA>      NA       NA #> 7394          U      NA       NA #> 7395       <NA>      NA       NA #> 7396       <NA>      NA       NA #> 7397       <NA>      NA       NA #> 7398       <NA>      NA       NA #> 7399       <NA>      NA       NA #> 7400       <NA>      NA       NA #> 7401          +      NA       NA #> 7402       <NA>      NA       NA #> 7403          U      NA       NA #> 7404       <NA>      NA       NA #> 7405          U      NA       NA #> 7406       <NA>      NA       NA #> 7407       <NA>      NA       NA #> 7408       <NA>      NA       NA #> 7409       <NA>      NA       NA #> 7410       <NA>      NA       NA #> 7411       <NA>      NA       NA #> 7412          +      NA       NA #> 7413       <NA>      NA       NA #> 7414          I      NA       NA #> 7415       <NA>      NA       NA #> 7416       <NA>      NA       NA #> 7417       <NA>      NA       NA #> 7418       <NA>      NA       NA #> 7419       <NA>      NA       NA #> 7420          I      NA       NA #> 7421       <NA>      NA       NA #> 7422       <NA>      NA       NA #> 7423       <NA>      NA       NA #> 7424       <NA>      NA       NA #> 7425       <NA>      NA       NA #> 7426       <NA>      NA       NA #> 7427          +      NA       NA #> 7428       <NA>      NA       NA #> 7429          U      NA       NA #> 7430       <NA>      NA       NA #> 7431       <NA>      NA       NA #> 7432       <NA>      NA       NA #> 7433       <NA>      NA       NA #> 7434       <NA>      NA       NA #> 7435       <NA>      NA       NA #> 7436       <NA>      NA       NA #> 7437       <NA>      NA       NA #> 7438          +      NA       NA #> 7439       <NA>      NA       NA #> 7440       <NA>      NA       NA #> 7441       <NA>      NA       NA #> 7442          I      NA       NA #> 7443       <NA>      NA       NA #> 7444       <NA>      NA       NA #> 7445       <NA>      NA       NA #> 7446       <NA>      NA       NA #> 7447       <NA>      NA       NA #> 7448       <NA>      NA       NA #> 7449          +      NA       NA #> 7450       <NA>      NA       NA #> 7451       <NA>      NA       NA #> 7452       <NA>      NA       NA #> 7453       <NA>      NA       NA #> 7454       <NA>      NA       NA #> 7455       <NA>      NA       NA #> 7456       <NA>      NA       NA #> 7457       <NA>      NA       NA #> 7458       <NA>      NA       NA #> 7459       <NA>      NA       NA #> 7460       <NA>      NA       NA #> 7461       <NA>      NA       NA #> 7462       <NA>      NA       NA #> 7463          +      NA       NA #> 7464       <NA>      NA       NA #> 7465          +      NA       NA #> 7466       <NA>      NA       NA #> 7467          I      NA       NA #> 7468       <NA>      NA       NA #> 7469       <NA>      NA       NA #> 7470       <NA>      NA       NA #> 7471       <NA>      NA       NA #> 7472          +      NA       NA #> 7473          I      NA       NA #> 7474       <NA>      NA       NA #> 7475       <NA>      NA       NA #> 7476          +      NA       NA #> 7477       <NA>      NA       NA #> 7478       <NA>      NA       NA #> 7479          I      NA       NA #> 7480          I      NA       NA #> 7481       <NA>      NA       NA #> 7482          +      NA       NA #> 7483          I      NA       NA #> 7484       <NA>      NA       NA #> 7485       <NA>      NA       NA #> 7486          +      NA       NA #> 7487       <NA>      NA       NA #> 7488       <NA>      NA       NA #> 7489       <NA>      NA       NA #> 7490       <NA>      NA       NA #> 7491       <NA>      NA       NA #> 7492          +      NA       NA #> 7493          I      NA       NA #> 7494       <NA>      NA       NA #> 7495       <NA>      NA       NA #> 7496          +      NA       NA #> 7497       <NA>      NA       NA #> 7498       <NA>      NA       NA #> 7499       <NA>      NA       NA #> 7500       <NA>      NA       NA #> 7501       <NA>      NA       NA #> 7502          +      NA       NA #> 7503          I      NA      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NA       NA #> 7532       <NA>      NA       NA #> 7533       <NA>      NA       NA #> 7534       <NA>      NA       NA #> 7535          +      NA       NA #> 7536       <NA>      NA       NA #> 7537       <NA>      NA       NA #> 7538       <NA>      NA       NA #> 7539       <NA>      NA       NA #> 7540       <NA>      NA       NA #> 7541          +      NA       NA #> 7542          I      NA       NA #> 7543       <NA>      NA       NA #> 7544       <NA>      NA       NA #> 7545          +      NA       NA #> 7546       <NA>      NA       NA #> 7547       <NA>      NA       NA #> 7548       <NA>      NA       NA #> 7549       <NA>      NA       NA #> 7550       <NA>      NA       NA #> 7551          +      NA       NA #> 7552       <NA>      NA       NA #> 7553       <NA>      NA       NA #> 7554       <NA>      NA       NA #> 7555          +      NA       NA #> 7556       <NA>      NA       NA #> 7557       <NA>      NA       NA #> 7558       <NA>      NA       NA #> 7559       <NA>      NA       NA #> 7560       <NA>      NA       NA #> 7561          +      NA       NA #> 7562       <NA>      NA       NA #> 7563       <NA>      NA       NA #> 7564       <NA>      NA       NA #> 7565          +      NA       NA #> 7566       <NA>      NA       NA #> 7567       <NA>      NA       NA #> 7568       <NA>      NA       NA #> 7569       <NA>      NA       NA #> 7570       <NA>      NA       NA #> 7571          +      NA       NA #> 7572       <NA>      NA       NA #> 7573       <NA>      NA       NA #> 7574       <NA>      NA       NA #> 7575          +      NA       NA #> 7576       <NA>      NA       NA #> 7577       <NA>      NA       NA #> 7578          I      NA       NA #> 7579       <NA>      NA       NA #> 7580       <NA>      NA       NA #> 7581          +      NA       NA #> 7582       <NA>      NA       NA #> 7583       <NA>      NA       NA #> 7584       <NA>      NA       NA #> 7585          +      NA       NA #> 7586       <NA>      NA       NA #> 7587       <NA>      NA       NA #> 7588          A      NA       NA #> 7589       <NA>      NA       NA #> 7590       <NA>      NA       NA #> 7591       <NA>      NA       NA #> 7592       <NA>      NA       NA #> 7593          +      NA       NA #> 7594       <NA>      NA       NA #> 7595       <NA>      NA       NA #> 7596          I      NA       NA #> 7597       <NA>      NA       NA #> 7598          +      NA       NA #> 7599       <NA>      NA       NA #> 7600       <NA>      NA       NA #> 7601          I      NA       NA #> 7602          +      NA       NA #> 7603       <NA>      NA       NA #> 7604          A      NA       NA #> 7605          A      NA       NA #> 7606       <NA>      NA       NA #> 7607       <NA>      NA       NA #> 7608          +      NA       NA #> 7609       <NA>      NA       NA #> 7610       <NA>      NA       NA #> 7611       <NA>      NA       NA #> 7612          +      NA       NA #> 7613       <NA>      NA       NA #> 7614       <NA>      NA      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NA       NA #> 7643       <NA>      NA       NA #> 7644       <NA>      NA       NA #> 7645       <NA>      NA       NA #> 7646       <NA>      NA       NA #> 7647          +      NA       NA #> 7648          I      NA       NA #> 7649       <NA>      NA       NA #> 7650       <NA>      NA       NA #> 7651          +      NA       NA #> 7652       <NA>      NA       NA #> 7653       <NA>      NA       NA #> 7654       <NA>      NA       NA #> 7655       <NA>      NA       NA #> 7656       <NA>      NA       NA #> 7657       <NA>      NA       NA #> 7658       <NA>      NA       NA #> 7659          +      NA       NA #> 7660       <NA>      NA       NA #> 7661       <NA>      NA       NA #> 7662       <NA>      NA       NA #> 7663       <NA>      NA       NA #> 7664       <NA>      NA       NA #> 7665          +      NA       NA #> 7666       <NA>      NA       NA #> 7667       <NA>      NA       NA #> 7668       <NA>      NA       NA #> 7669          +      NA       NA #> 7670       <NA>      NA       NA #> 7671          A      NA       NA #> 7672       <NA>      NA       NA #> 7673       <NA>      NA       NA #> 7674       <NA>      NA       NA #> 7675          +      NA       NA #> 7676       <NA>      NA       NA #> 7677       <NA>      NA       NA #> 7678       <NA>      NA       NA #> 7679          +      NA       NA #> 7680       <NA>      NA       NA #> 7681       <NA>      NA       NA #> 7682          I      NA       NA #> 7683       <NA>      NA       NA #> 7684       <NA>      NA       NA #> 7685          +      NA       NA #> 7686       <NA>      NA       NA #> 7687       <NA>      NA       NA #> 7688       <NA>      NA       NA #> 7689          +      NA       NA #> 7690       <NA>      NA       NA #> 7691       <NA>      NA       NA #> 7692          A      NA       NA #> 7693          +      NA       NA #> 7694       <NA>      NA       NA #> 7695       <NA>      NA       NA #> 7696       <NA>      NA       NA #> 7697          +      NA       NA #> 7698       <NA>      NA       NA #> 7699       <NA>      NA       NA #> 7700          I      NA       NA #> 7701       <NA>      NA       NA #> 7702       <NA>      NA       NA #> 7703       <NA>      NA       NA #> 7704       <NA>      NA       NA #> 7705          +      NA       NA #> 7706       <NA>      NA       NA #> 7707       <NA>      NA       NA #> 7708       <NA>      NA       NA #> 7709          A      NA       NA #> 7710       <NA>      NA       NA #> 7711          +      NA       NA #> 7712       <NA>      NA       NA #> 7713       <NA>      NA       NA #> 7714          +      NA       NA #> 7715       <NA>      NA       NA #> 7716       <NA>      NA       NA #> 7717       <NA>      NA       NA #> 7718       <NA>      NA       NA #> 7719       <NA>      NA       NA #> 7720          +      NA       NA #> 7721       <NA>      NA       NA #> 7722       <NA>      NA       NA #> 7723       <NA>      NA       NA #> 7724          +      NA       NA #> 7725       <NA>      NA      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<NA>      NA       NA #> 7782       <NA>      NA       NA #> 7783       <NA>      NA       NA #> 7784       <NA>      NA       NA #> 7785          +      NA       NA #> 7786          U      NA       NA #> 7787       <NA>      NA       NA #> 7788       <NA>      NA       NA #> 7789          +      NA       NA #> 7790       <NA>      NA       NA #> 7791       <NA>      NA       NA #> 7792       <NA>      NA       NA #> 7793       <NA>      NA       NA #> 7794       <NA>      NA       NA #> 7795          +      NA       NA #> 7796       <NA>      NA       NA #> 7797       <NA>      NA       NA #> 7798       <NA>      NA       NA #> 7799          +      NA       NA #> 7800       <NA>      NA       NA #> 7801       <NA>      NA       NA #> 7802       <NA>      NA       NA #> 7803       <NA>      NA       NA #> 7804       <NA>      NA       NA #> 7805          +      NA       NA #> 7806          I      NA       NA #> 7807       <NA>      NA       NA #> 7808       <NA>      NA       NA #> 7809          +      NA       NA #> 7810       <NA>      NA       NA #> 7811       <NA>      NA       NA #> 7812       <NA>      NA       NA #> 7813       <NA>      NA       NA #> 7814       <NA>      NA       NA #> 7815          +      NA       NA #> 7816          I      NA       NA #> 7817       <NA>      NA       NA #> 7818       <NA>      NA       NA #> 7819          +      NA       NA #> 7820       <NA>      NA       NA #> 7821       <NA>      NA       NA #> 7822       <NA>      NA       NA #> 7823       <NA>      NA       NA #> 7824       <NA>      NA       NA #> 7825          +      NA       NA #> 7826          U      NA       NA #> 7827       <NA>      NA       NA #> 7828       <NA>      NA       NA #> 7829          +      NA       NA #> 7830       <NA>      NA       NA #> 7831       <NA>      NA       NA #> 7832          A      NA       NA #> 7833       <NA>      NA       NA #> 7834       <NA>      NA       NA #> 7835          +      NA       NA #> 7836       <NA>      NA      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NA       NA #> 7865          +      NA       NA #> 7866       <NA>      NA       NA #> 7867       <NA>      NA       NA #> 7868       <NA>      NA       NA #> 7869          +      NA       NA #> 7870       <NA>      NA       NA #> 7871       <NA>      NA       NA #> 7872       <NA>      NA       NA #> 7873       <NA>      NA       NA #> 7874       <NA>      NA       NA #> 7875       <NA>      NA       NA #> 7876          +      NA       NA #> 7877       <NA>      NA       NA #> 7878       <NA>      NA       NA #> 7879       <NA>      NA       NA #> 7880       <NA>      NA       NA #> 7881       <NA>      NA       NA #> 7882          +      NA       NA #> 7883       <NA>      NA       NA #> 7884       <NA>      NA       NA #> 7885       <NA>      NA       NA #> 7886          +      NA       NA #> 7887       <NA>      NA       NA #> 7888       <NA>      NA       NA #> 7889       <NA>      NA       NA #> 7890       <NA>      NA       NA #> 7891       <NA>      NA       NA #> 7892       <NA>      NA       NA #> 7893       <NA>      NA       NA #> 7894       <NA>      NA       NA #> 7895       <NA>      NA       NA #> 7896          +      NA       NA #> 7897       <NA>      NA       NA #> 7898       <NA>      NA       NA #> 7899       <NA>      NA       NA #> 7900       <NA>      NA       NA #> 7901          +      NA       NA #> 7902          U      NA       NA #> 7903       <NA>      NA       NA #> 7904       <NA>      NA       NA #> 7905          +      NA       NA #> 7906       <NA>      NA       NA #> 7907       <NA>      NA       NA #> 7908          I      NA       NA #> 7909       <NA>      NA       NA #> 7910       <NA>      NA       NA #> 7911          I      NA       NA #> 7912       <NA>      NA       NA #> 7913       <NA>      NA       NA #> 7914          +      NA       NA #> 7915       <NA>      NA       NA #> 7916       <NA>      NA       NA #> 7917       <NA>      NA       NA #> 7918       <NA>      NA       NA #> 7919       <NA>      NA       NA #> 7920       <NA>      NA       NA #> 7921          I      NA       NA #> 7922       <NA>      NA       NA #> 7923       <NA>      NA       NA #> 7924          +      NA       NA #> 7925       <NA>      NA       NA #> 7926       <NA>      NA       NA #> 7927       <NA>      NA       NA #> 7928       <NA>      NA       NA #> 7929       <NA>      NA       NA #> 7930       <NA>      NA       NA #> 7931          I      NA       NA #> 7932       <NA>      NA       NA #> 7933       <NA>      NA       NA #> 7934          +      NA       NA #> 7935       <NA>      NA       NA #> 7936       <NA>      NA       NA #> 7937       <NA>      NA       NA #> 7938       <NA>      NA       NA #> 7939       <NA>      NA       NA #> 7940       <NA>      NA       NA #> 7941       <NA>      NA       NA #> 7942       <NA>      NA       NA #> 7943       <NA>      NA       NA #> 7944          +      NA       NA #> 7945       <NA>      NA       NA #> 7946       <NA>      NA       NA #> 7947       <NA>      NA      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NA       NA #> 7976       <NA>      NA       NA #> 7977          I      NA       NA #> 7978       <NA>      NA       NA #> 7979       <NA>      NA       NA #> 7980       <NA>      NA       NA #> 7981       <NA>      NA       NA #> 7982       <NA>      NA       NA #> 7983       <NA>      NA       NA #> 7984          +      NA       NA #> 7985       <NA>      NA       NA #> 7986       <NA>      NA       NA #> 7987          I      NA       NA #> 7988       <NA>      NA       NA #> 7989       <NA>      NA       NA #> 7990       <NA>      NA       NA #> 7991          I      NA       NA #> 7992       <NA>      NA       NA #> 7993       <NA>      NA       NA #> 7994          +      NA       NA #> 7995       <NA>      NA       NA #> 7996       <NA>      NA       NA #> 7997          I      NA       NA #> 7998       <NA>      NA       NA #> 7999       <NA>      NA       NA #> 8000       <NA>      NA       NA #> 8001          I      NA       NA #> 8002       <NA>      NA       NA #> 8003       <NA>      NA       NA #> 8004          +      NA       NA #> 8005       <NA>      NA       NA #> 8006       <NA>      NA       NA #> 8007       <NA>      NA       NA #> 8008       <NA>      NA       NA #> 8009       <NA>      NA       NA #> 8010       <NA>      NA       NA #> 8011          I      NA       NA #> 8012       <NA>      NA       NA #> 8013       <NA>      NA       NA #> 8014          +      NA       NA #> 8015       <NA>      NA       NA #> 8016       <NA>      NA       NA #> 8017       <NA>      NA       NA #> 8018       <NA>      NA       NA #> 8019       <NA>      NA       NA #> 8020       <NA>      NA       NA #> 8021          U      NA       NA #> 8022       <NA>      NA       NA #> 8023       <NA>      NA       NA #> 8024          +      NA       NA #> 8025       <NA>      NA       NA #> 8026       <NA>      NA       NA #> 8027       <NA>      NA       NA #> 8028       <NA>      NA       NA #> 8029       <NA>      NA       NA #> 8030       <NA>      NA       NA #> 8031          I      NA       NA #> 8032       <NA>      NA       NA #> 8033       <NA>      NA       NA #> 8034          +      NA       NA #> 8035       <NA>      NA       NA #> 8036       <NA>      NA       NA #> 8037       <NA>      NA       NA #> 8038       <NA>      NA       NA #> 8039       <NA>      NA       NA #> 8040       <NA>      NA       NA #> 8041       <NA>      NA       NA #> 8042       <NA>      NA       NA #> 8043       <NA>      NA       NA #> 8044          +      NA       NA #> 8045       <NA>      NA       NA #> 8046       <NA>      NA       NA #> 8047       <NA>      NA       NA #> 8048       <NA>      NA       NA #> 8049       <NA>      NA       NA #> 8050       <NA>      NA       NA #> 8051       <NA>      NA       NA #> 8052       <NA>      NA       NA #> 8053       <NA>      NA       NA #> 8054          +      NA       NA #> 8055       <NA>      NA       NA #> 8056       <NA>      NA       NA #> 8057          I      NA       NA #> 8058       <NA>      NA      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NA       NA #> 8087       <NA>      NA       NA #> 8088       <NA>      NA       NA #> 8089       <NA>      NA       NA #> 8090       <NA>      NA       NA #> 8091       <NA>      NA       NA #> 8092       <NA>      NA       NA #> 8093       <NA>      NA       NA #> 8094          +      NA       NA #> 8095       <NA>      NA       NA #> 8096       <NA>      NA       NA #> 8097          I      NA       NA #> 8098          A      NA       NA #> 8099       <NA>      NA       NA #> 8100       <NA>      NA       NA #> 8101       <NA>      NA       NA #> 8102          +      NA       NA #> 8103       <NA>      NA       NA #> 8104       <NA>      NA       NA #> 8105          I      NA       NA #> 8106       <NA>      NA       NA #> 8107       <NA>      NA       NA #> 8108       <NA>      NA       NA #> 8109       <NA>      NA       NA #> 8110       <NA>      NA       NA #> 8111       <NA>      NA       NA #> 8112          +      NA       NA #> 8113       <NA>      NA       NA #> 8114       <NA>      NA       NA #> 8115          I      NA       NA #> 8116       <NA>      NA       NA #> 8117       <NA>      NA       NA #> 8118       <NA>      NA       NA #> 8119       <NA>      NA       NA #> 8120       <NA>      NA       NA #> 8121       <NA>      NA       NA #> 8122          +      NA       NA #> 8123       <NA>      NA       NA #> 8124       <NA>      NA       NA #> 8125       <NA>      NA       NA #> 8126       <NA>      NA       NA #> 8127       <NA>      NA       NA #> 8128       <NA>      NA       NA #> 8129          I      NA       NA #> 8130       <NA>      NA       NA #> 8131       <NA>      NA       NA #> 8132          +      NA       NA #> 8133       <NA>      NA       NA #> 8134       <NA>      NA       NA #> 8135          I      NA       NA #> 8136       <NA>      NA       NA #> 8137       <NA>      NA       NA #> 8138       <NA>      NA       NA #> 8139          I      NA       NA #> 8140       <NA>      NA       NA #> 8141          I      NA       NA #> 8142          +      NA       NA #> 8143       <NA>      NA       NA #> 8144          A      NA       NA #> 8145       <NA>      NA       NA #> 8146       <NA>      NA       NA #> 8147       <NA>      NA       NA #> 8148       <NA>      NA       NA #> 8149          U      NA       NA #> 8150       <NA>      NA       NA #> 8151          +      NA       NA #> 8152       <NA>      NA       NA #> 8153       <NA>      NA       NA #> 8154       <NA>      NA       NA #> 8155       <NA>      NA       NA #> 8156       <NA>      NA       NA #> 8157       <NA>      NA       NA #> 8158          U      NA       NA #> 8159       <NA>      NA       NA #> 8160       <NA>      NA       NA #> 8161          +      NA       NA #> 8162       <NA>      NA       NA #> 8163       <NA>      NA       NA #> 8164       <NA>      NA       NA #> 8165       <NA>      NA       NA #> 8166       <NA>      NA       NA #> 8167       <NA>      NA       NA #> 8168       <NA>      NA       NA #> 8169       <NA>      NA      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NA       NA #> 8198          I      NA       NA #> 8199       <NA>      NA       NA #> 8200       <NA>      NA       NA #> 8201          +      NA       NA #> 8202       <NA>      NA       NA #> 8203       <NA>      NA       NA #> 8204          I      NA       NA #> 8205          A      NA       NA #> 8206       <NA>      NA       NA #> 8207       <NA>      NA       NA #> 8208       <NA>      NA       NA #> 8209       <NA>      NA       NA #> 8210       <NA>      NA       NA #> 8211          +      NA       NA #> 8212       <NA>      NA       NA #> 8213       <NA>      NA       NA #> 8214          I      NA       NA #> 8215          A      NA       NA #> 8216       <NA>      NA       NA #> 8217          +      NA       NA #> 8218       <NA>      NA       NA #> 8219       <NA>      NA       NA #> 8220       <NA>      NA       NA #> 8221          +      NA       NA #> 8222       <NA>      NA       NA #> 8223       <NA>      NA       NA #> 8224       <NA>      NA       NA #> 8225       <NA>      NA       NA #> 8226       <NA>      NA       NA #> 8227       <NA>      NA       NA #> 8228       <NA>      NA       NA #> 8229       <NA>      NA       NA #> 8230       <NA>      NA       NA #> 8231          +      NA       NA #> 8232       <NA>      NA       NA #> 8233       <NA>      NA       NA #> 8234          I      NA       NA #> 8235          I      NA       NA #> 8236       <NA>      NA       NA #> 8237       <NA>      NA       NA #> 8238          I      NA       NA #> 8239       <NA>      NA       NA #> 8240       <NA>      NA       NA #> 8241          +      NA       NA #> 8242       <NA>      NA       NA #> 8243          I      NA       NA #> 8244          I      NA       NA #> 8245          I      NA       NA #> 8246       <NA>      NA       NA #> 8247       <NA>      NA       NA #> 8248          U      NA       NA #> 8249       <NA>      NA       NA #> 8250       <NA>      NA       NA #> 8251          +      NA       NA #> 8252       <NA>      NA       NA #> 8253       <NA>      NA       NA #> 8254       <NA>      NA       NA #> 8255       <NA>      NA       NA #> 8256       <NA>      NA       NA #> 8257       <NA>      NA       NA #> 8258          I      NA       NA #> 8259       <NA>      NA       NA #> 8260          I      NA       NA #> 8261          +      NA       NA #> 8262       <NA>      NA       NA #> 8263       <NA>      NA       NA #> 8264       <NA>      NA       NA #> 8265          I      NA       NA #> 8266       <NA>      NA       NA #> 8267       <NA>      NA       NA #> 8268          I      NA       NA #> 8269       <NA>      NA       NA #> 8270       <NA>      NA       NA #> 8271          +      NA       NA #> 8272       <NA>      NA       NA #> 8273          I      NA       NA #> 8274       <NA>      NA       NA #> 8275          A      NA       NA #> 8276       <NA>      NA       NA #> 8277       <NA>      NA       NA #> 8278          I      NA       NA #> 8279       <NA>      NA       NA #> 8280       <NA>      NA      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NA       NA #> 8309          +      NA       NA #> 8310       <NA>      NA       NA #> 8311       <NA>      NA       NA #> 8312          I      NA       NA #> 8313       <NA>      NA       NA #> 8314       <NA>      NA       NA #> 8315       <NA>      NA       NA #> 8316       <NA>      NA       NA #> 8317       <NA>      NA       NA #> 8318       <NA>      NA       NA #> 8319          +      NA       NA #> 8320       <NA>      NA       NA #> 8321       <NA>      NA       NA #> 8322       <NA>      NA       NA #> 8323       <NA>      NA       NA #> 8324       <NA>      NA       NA #> 8325       <NA>      NA       NA #> 8326       <NA>      NA       NA #> 8327       <NA>      NA       NA #> 8328       <NA>      NA       NA #> 8329          +      NA       NA #> 8330       <NA>      NA       NA #> 8331       <NA>      NA       NA #> 8332       <NA>      NA       NA #> 8333       <NA>      NA       NA #> 8334       <NA>      NA       NA #> 8335       <NA>      NA       NA #> 8336       <NA>      NA       NA #> 8337       <NA>      NA       NA #> 8338       <NA>      NA       NA #> 8339          +      NA       NA #> 8340       <NA>      NA       NA #> 8341       <NA>      NA       NA #> 8342       <NA>      NA       NA #> 8343       <NA>      NA       NA #> 8344       <NA>      NA       NA #> 8345       <NA>      NA       NA #> 8346       <NA>      NA       NA #> 8347       <NA>      NA       NA #> 8348       <NA>      NA       NA #> 8349          +      NA       NA #> 8350       <NA>      NA       NA #> 8351       <NA>      NA       NA #> 8352       <NA>      NA       NA #> 8353       <NA>      NA       NA #> 8354       <NA>      NA       NA #> 8355       <NA>      NA       NA #> 8356          I      NA       NA #> 8357       <NA>      NA       NA #> 8358       <NA>      NA       NA #> 8359          +      NA       NA #> 8360       <NA>      NA       NA #> 8361       <NA>      NA       NA #> 8362       <NA>      NA       NA #> 8363       <NA>      NA       NA #> 8364       <NA>      NA       NA #> 8365       <NA>      NA       NA #> 8366       <NA>      NA       NA #> 8367       <NA>      NA       NA #> 8368       <NA>      NA       NA #> 8369       <NA>      NA       NA #> 8370       <NA>      NA       NA #> 8371       <NA>      NA       NA #> 8372       <NA>      NA       NA #> 8373       <NA>      NA       NA #> 8374       <NA>      NA       NA #> 8375       <NA>      NA       NA #> 8376       <NA>      NA       NA #> 8377       <NA>      NA       NA #> 8378       <NA>      NA       NA #> 8379       <NA>      NA       NA #> 8380       <NA>      NA       NA #> 8381       <NA>      NA       NA #> 8382       <NA>      NA       NA #> 8383       <NA>      NA       NA #> 8384       <NA>      NA       NA #> 8385       <NA>      NA       NA #> 8386       <NA>      NA       NA #> 8387       <NA>      NA       NA #> 8388       <NA>      NA       NA #> 8389       <NA>      NA       NA #> 8390       <NA>      NA       NA #> 8391       <NA>      NA      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NA       NA #> 8420       <NA>      NA       NA #> 8421       <NA>      NA       NA #> 8422       <NA>      NA       NA #> 8423       <NA>      NA       NA #> 8424       <NA>      NA       NA #> 8425          I      NA       NA #> 8426       <NA>      NA       NA #> 8427       <NA>      NA       NA #> 8428       <NA>      NA       NA #> 8429       <NA>      NA       NA #> 8430       <NA>      NA       NA #> 8431       <NA>      NA       NA #> 8432          +      NA       NA #> 8433          I      NA       NA #> 8434       <NA>      NA       NA #> 8435       <NA>      NA       NA #> 8436       <NA>      NA       NA #> 8437       <NA>      NA       NA #> 8438       <NA>      NA       NA #> 8439       <NA>      NA       NA #> 8440       <NA>      NA       NA #> 8441       <NA>      NA       NA #> 8442          +      NA       NA #> 8443       <NA>      NA       NA #> 8444       <NA>      NA       NA #> 8445       <NA>      NA       NA #> 8446       <NA>      NA       NA #> 8447       <NA>      NA       NA #> 8448          +      NA       NA #> 8449          U      NA       NA #> 8450       <NA>      NA       NA #> 8451       <NA>      NA       NA #> 8452       <NA>      NA       NA #> 8453       <NA>      NA       NA #> 8454       <NA>      NA       NA #> 8455       <NA>      NA       NA #> 8456       <NA>      NA       NA #> 8457       <NA>      NA       NA #> 8458          +      NA       NA #> 8459       <NA>      NA       NA #> 8460          I      NA       NA #> 8461       <NA>      NA       NA #> 8462       <NA>      NA       NA #> 8463          +      NA       NA #> 8464          I      NA       NA #> 8465       <NA>      NA       NA #> 8466       <NA>      NA       NA #> 8467       <NA>      NA       NA #> 8468       <NA>      NA       NA #> 8469       <NA>      NA       NA #> 8470       <NA>      NA       NA #> 8471       <NA>      NA       NA #> 8472       <NA>      NA       NA #> 8473          +      NA       NA #> 8474       <NA>      NA       NA #> 8475       <NA>      NA       NA #> 8476       <NA>      NA       NA #> 8477          +      NA       NA #> 8478       <NA>      NA       NA #> 8479       <NA>      NA       NA #> 8480       <NA>      NA       NA #> 8481          +      NA       NA #> 8482       <NA>      NA       NA #> 8483       <NA>      NA       NA #> 8484       <NA>      NA       NA #> 8485       <NA>      NA       NA #> 8486       <NA>      NA       NA #> 8487       <NA>      NA       NA #> 8488       <NA>      NA       NA #> 8489       <NA>      NA       NA #> 8490       <NA>      NA       NA #> 8491       <NA>      NA       NA #> 8492          +      NA       NA #> 8493       <NA>      NA       NA #> 8494       <NA>      NA       NA #> 8495       <NA>      NA       NA #> 8496          +      NA       NA #> 8497       <NA>      NA       NA #> 8498       <NA>      NA       NA #> 8499       <NA>      NA       NA #> 8500          +      NA       NA #> 8501       <NA>      NA       NA #> 8502       <NA>      NA      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NA       NA #> 8531       <NA>      NA       NA #> 8532       <NA>      NA       NA #> 8533       <NA>      NA       NA #> 8534          +      NA       NA #> 8535       <NA>      NA       NA #> 8536       <NA>      NA       NA #> 8537       <NA>      NA       NA #> 8538          +      NA       NA #> 8539       <NA>      NA       NA #> 8540       <NA>      NA       NA #> 8541       <NA>      NA       NA #> 8542       <NA>      NA       NA #> 8543          +      NA       NA #> 8544          I      NA       NA #> 8545       <NA>      NA       NA #> 8546       <NA>      NA       NA #> 8547       <NA>      NA       NA #> 8548       <NA>      NA       NA #> 8549       <NA>      NA       NA #> 8550       <NA>      NA       NA #> 8551          +      NA       NA #> 8552       <NA>      NA       NA #> 8553       <NA>      NA       NA #> 8554       <NA>      NA       NA #> 8555       <NA>      NA       NA #> 8556       <NA>      NA       NA #> 8557       <NA>      NA       NA #> 8558          +      NA       NA #> 8559          I      NA       NA #> 8560       <NA>      NA       NA #> 8561       <NA>      NA       NA #> 8562       <NA>      NA       NA #> 8563       <NA>      NA       NA #> 8564       <NA>      NA       NA #> 8565       <NA>      NA       NA #> 8566       <NA>      NA       NA #> 8567       <NA>      NA       NA #> 8568          +      NA       NA #> 8569       <NA>      NA       NA #> 8570       <NA>      NA       NA #> 8571       <NA>      NA       NA #> 8572          +      NA       NA #> 8573       <NA>      NA       NA #> 8574       <NA>      NA       NA #> 8575       <NA>      NA       NA #> 8576       <NA>      NA       NA #> 8577          +      NA       NA #> 8578          U      NA       NA #> 8579       <NA>      NA       NA #> 8580       <NA>      NA       NA #> 8581       <NA>      NA       NA #> 8582       <NA>      NA       NA #> 8583       <NA>      NA       NA #> 8584       <NA>      NA       NA #> 8585       <NA>      NA       NA #> 8586       <NA>      NA       NA #> 8587          +      NA       NA #> 8588       <NA>      NA       NA #> 8589       <NA>      NA       NA #> 8590       <NA>      NA       NA #> 8591          +      NA       NA #> 8592       <NA>      NA       NA #> 8593       <NA>      NA       NA #> 8594       <NA>      NA       NA #> 8595          +      NA       NA #> 8596          U      NA       NA #> 8597       <NA>      NA       NA #> 8598       <NA>      NA       NA #> 8599       <NA>      NA       NA #> 8600       <NA>      NA       NA #> 8601       <NA>      NA       NA #> 8602       <NA>      NA       NA #> 8603       <NA>      NA       NA #> 8604       <NA>      NA       NA #> 8605          +      NA       NA #> 8606       <NA>      NA       NA #> 8607       <NA>      NA       NA #> 8608          U      NA       NA #> 8609       <NA>      NA       NA #> 8610       <NA>      NA       NA #> 8611          +      NA       NA #> 8612       <NA>      NA       NA #> 8613       <NA>      NA       NA #> 8614       <NA>      NA       NA #> 8615       <NA>      NA       NA #> 8616       <NA>      NA       NA #> 8617       <NA>      NA       NA #> 8618       <NA>      NA       NA #> 8619          +      NA       NA #> 8620          U      NA       NA #> 8621       <NA>      NA       NA #> 8622       <NA>      NA       NA #> 8623       <NA>      NA       NA #> 8624       <NA>      NA       NA #> 8625       <NA>      NA       NA #> 8626       <NA>      NA       NA #> 8627       <NA>      NA       NA #> 8628       <NA>      NA       NA #> 8629          +      NA       NA #> 8630       <NA>      NA       NA #> 8631       <NA>      NA       NA #> 8632       <NA>      NA       NA #> 8633          +      NA       NA #> 8634       <NA>      NA       NA #> 8635       <NA>      NA       NA #> 8636       <NA>      NA       NA #> 8637          +      NA       NA #> 8638          U      NA       NA #> 8639       <NA>      NA       NA #> 8640       <NA>      NA       NA #> 8641       <NA>      NA      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I      NA       NA #> 8698          A      NA       NA #> 8699       <NA>      NA       NA #> 8700       <NA>      NA       NA #> 8701       <NA>      NA       NA #> 8702       <NA>      NA       NA #> 8703       <NA>      NA       NA #> 8704       <NA>      NA       NA #> 8705       <NA>      NA       NA #> 8706          +      NA       NA #> 8707       <NA>      NA       NA #> 8708       <NA>      NA       NA #> 8709       <NA>      NA       NA #> 8710       <NA>      NA       NA #> 8711       <NA>      NA       NA #> 8712       <NA>      NA       NA #> 8713       <NA>      NA       NA #> 8714       <NA>      NA       NA #> 8715       <NA>      NA       NA #> 8716       <NA>      NA       NA #> 8717          +      NA       NA #> 8718       <NA>      NA       NA #> 8719          I      NA       NA #> 8720          A      NA       NA #> 8721       <NA>      NA       NA #> 8722       <NA>      NA       NA #> 8723       <NA>      NA       NA #> 8724       <NA>      NA       NA #> 8725       <NA>      NA       NA #> 8726       <NA>      NA       NA #> 8727          +      NA       NA #> 8728       <NA>      NA       NA #> 8729          +      NA       NA #> 8730       <NA>      NA       NA #> 8731          I      NA       NA #> 8732          A      NA       NA #> 8733       <NA>      NA       NA #> 8734       <NA>      NA       NA #> 8735       <NA>      NA       NA #> 8736       <NA>      NA       NA #> 8737       <NA>      NA       NA #> 8738       <NA>      NA       NA #> 8739          +      NA       NA #> 8740       <NA>      NA       NA #> 8741          +      NA       NA #> 8742       <NA>      NA       NA #> 8743          I      NA       NA #> 8744       <NA>      NA       NA #> 8745       <NA>      NA       NA #> 8746          A      NA       NA #> 8747       <NA>      NA       NA #> 8748       <NA>      NA       NA #> 8749       <NA>      NA       NA #> 8750       <NA>      NA       NA #> 8751          +      NA       NA #> 8752       <NA>      NA       NA #> 8753          +      NA       NA #> 8754       <NA>      NA       NA #> 8755          I      NA       NA #> 8756       <NA>      NA       NA #> 8757       <NA>      NA       NA #> 8758       <NA>      NA       NA #> 8759       <NA>      NA       NA #> 8760          +      NA       NA #> 8761       <NA>      NA       NA #> 8762       <NA>      NA       NA #> 8763       <NA>      NA       NA #> 8764       <NA>      NA       NA #> 8765       <NA>      NA       NA #> 8766          U      NA       NA #> 8767          +      NA       NA #> 8768       <NA>      NA       NA #> 8769          +      NA       NA #> 8770       <NA>      NA       NA #> 8771          I      NA       NA #> 8772       <NA>      NA       NA #> 8773       <NA>      NA       NA #> 8774       <NA>      NA       NA #> 8775       <NA>      NA       NA #> 8776       <NA>      NA       NA #> 8777       <NA>      NA       NA #> 8778       <NA>      NA       NA #> 8779       <NA>      NA       NA #> 8780          +      NA      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NA       NA #> 8809       <NA>      NA       NA #> 8810          I      NA       NA #> 8811       <NA>      NA       NA #> 8812       <NA>      NA       NA #> 8813          A      NA       NA #> 8814       <NA>      NA       NA #> 8815       <NA>      NA       NA #> 8816       <NA>      NA       NA #> 8817       <NA>      NA       NA #> 8818          +      NA       NA #> 8819          A      NA       NA #> 8820       <NA>      NA       NA #> 8821       <NA>      NA       NA #> 8822       <NA>      NA       NA #> 8823       <NA>      NA       NA #> 8824       <NA>      NA       NA #> 8825       <NA>      NA       NA #> 8826       <NA>      NA       NA #> 8827       <NA>      NA       NA #> 8828       <NA>      NA       NA #> 8829          +      NA       NA #> 8830       <NA>      NA       NA #> 8831          I      NA       NA #> 8832          A      NA       NA #> 8833       <NA>      NA       NA #> 8834       <NA>      NA       NA #> 8835       <NA>      NA       NA #> 8836       <NA>      NA       NA #> 8837       <NA>      NA       NA #> 8838       <NA>      NA       NA #> 8839       <NA>      NA       NA #> 8840       <NA>      NA       NA #> 8841          +      NA       NA #> 8842       <NA>      NA       NA #> 8843          A      NA       NA #> 8844       <NA>      NA       NA #> 8845          I      NA       NA #> 8846          A      NA       NA #> 8847       <NA>      NA       NA #> 8848       <NA>      NA       NA #> 8849       <NA>      NA       NA #> 8850          U      NA       NA #> 8851       <NA>      NA       NA #> 8852       <NA>      NA       NA #> 8853          +      NA       NA #> 8854       <NA>      NA       NA #> 8855          I      NA       NA #> 8856       <NA>      NA       NA #> 8857       <NA>      NA       NA #> 8858       <NA>      NA       NA #> 8859       <NA>      NA       NA #> 8860       <NA>      NA       NA #> 8861       <NA>      NA       NA #> 8862       <NA>      NA       NA #> 8863       <NA>      NA       NA #> 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+      NA       NA #> 8948       <NA>      NA       NA #> 8949       <NA>      NA       NA #> 8950       <NA>      NA       NA #> 8951       <NA>      NA       NA #> 8952       <NA>      NA       NA #> 8953       <NA>      NA       NA #> 8954       <NA>      NA       NA #> 8955          U      NA       NA #> 8956       <NA>      NA       NA #> 8957       <NA>      NA       NA #> 8958          +      NA       NA #> 8959       <NA>      NA       NA #> 8960       <NA>      NA       NA #> 8961       <NA>      NA       NA #> 8962       <NA>      NA       NA #> 8963       <NA>      NA       NA #> 8964       <NA>      NA       NA #> 8965       <NA>      NA       NA #> 8966          U      NA       NA #> 8967       <NA>      NA       NA #> 8968       <NA>      NA       NA #> 8969          +      NA       NA #> 8970       <NA>      NA       NA #> 8971       <NA>      NA       NA #> 8972       <NA>      NA       NA #> 8973       <NA>      NA       NA #> 8974       <NA>      NA       NA #> 8975   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<NA>      NA       NA #> 9087          +      NA       NA #> 9088       <NA>      NA       NA #> 9089       <NA>      NA       NA #> 9090          +      NA       NA #>  [ reached 'max' / getOption(\"max.print\") -- omitted 165157 rows ]"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert references csv to bib — anlz_refs","title":"Convert references csv to bib — anlz_refs","text":"Convert references csv bib","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert references csv to bib — anlz_refs","text":"","code":"anlz_refs(path)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert references csv to bib — anlz_refs","text":"path chr string path reference csv file data frame object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert references csv to bib — anlz_refs","text":"data frame references formatted bib entries","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert references csv to bib — anlz_refs","text":"","code":"# input and format path <- 'https://raw.githubusercontent.com/tbep-tech/tbep-refs/master/tbep-refs.csv' bibs <- anlz_refs(path)  if (FALSE) { # \\dontrun{ # save output  writeLines(bibs, 'formatted.bib') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":null,"dir":"Reference","previous_headings":"","what":"Add contaminant totals to sediment data — anlz_sedimentaddtot","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"Add contaminant totals sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   param = NULL,   pelave = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" param optional character string parameter filter results pelave logical indicating output used anlz_sedimentpel","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"data.frame object similar input, filtered arguments contaminant totals added. Replicate samples also removed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"function adds totals sedimentdata input total PCBs, total DDT, total LMW PAH, total HMW PAH, total PAH.  Appropriate TEL/PEL values totals also added.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(sedimentdata) #> # A tibble: 62,667 × 24 #>    ProgramId ProgramName   FundingProject    yr AreaAbbr StationID StationNumber #>        <int> <chr>         <chr>          <int> <chr>        <int> <chr>         #>  1         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  2         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  3         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  4         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  5         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  6         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  7         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  8         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  9         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> 10         4 Benthic Moni… TBEP            1993 HB            2464 93HB16        #> # ℹ 62,657 more rows #> # ℹ 17 more variables: Latitude <dbl>, Longitude <dbl>, Replicate <chr>, #> #   SedResultsType <chr>, Parameter <chr>, ValueAdjusted <dbl>, Units <chr>, #> #   Qualifier <chr>, MDLnum <dbl>, PQLnum <dbl>, TEL <dbl>, PEL <dbl>, #> #   BetweenTELPEL <chr>, ExceedsPEL <chr>, PELRatio <dbl>, #> #   PreparationDate <chr>, AnalysisTimeMerge <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"data.frame object average sediment concentrations selected parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(sedimentdata, param = 'Arsenic') #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       7.24  41.6 mg/kg  2.64 2.34   2.94     2.57 #> 2 HB        7.24  41.6 mg/kg  2.93 0.665  5.20     2.57 #> 3 LTB       7.24  41.6 mg/kg  2.93 2.47   3.40     2.57 #> 4 MR        7.24  41.6 mg/kg  1.66 1.37   1.95     2.57 #> 5 MTB       7.24  41.6 mg/kg  2.17 1.86   2.48     2.57 #> 6 OTB       7.24  41.6 mg/kg  3.24 0.707  5.78     2.57 #> 7 TCB       7.24  41.6 mg/kg  2.40 1.92   2.88     2.57"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Get sediment PEL ratios stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"data.frame object average PEL ratios grades station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Average PEL ratios contaminants graded F benthic stations monitored Tampa Bay estimated. PEL measure likely contaminant toxic effect invertebrates inhabit sediment. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station grade applies average. grade breaks PEL ratio 0.00756, 0.02052, 0.08567, 0.28026, lower grades assigned higher breaks.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(sedimentdata) #> # A tibble: 2,233 × 7 #>       yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #>    <int> <chr>    <chr>            <dbl>     <dbl>    <dbl> <fct> #>  1  1993 HB       93HB15            27.8     -82.4  0.0157  B     #>  2  1993 HB       93HB16            27.8     -82.5  0.0261  C     #>  3  1993 HB       93HB23            27.9     -82.4  0.0174  B     #>  4  1993 LTB      93LTB24           27.7     -82.6  0.0124  B     #>  5  1993 LTB      93LTB25           27.6     -82.6  0.0189  B     #>  6  1993 LTB      93LTB26           27.6     -82.7  0.00997 B     #>  7  1993 LTB      93LTB27           27.6     -82.7  0.0125  B     #>  8  1993 LTB      93LTB28           27.6     -82.7  0.0887  D     #>  9  1993 LTB      93LTB29           27.6     -82.6  0.0350  C     #> 10  1993 LTB      93LTB30           27.6     -82.6  0.0496  C     #> # ℹ 2,223 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"data.frame average average PEL ratios bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(sedimentdata) #> # A tibble: 7 × 5 #>   AreaAbbr    ave    lov    hiv grandave #>   <fct>     <dbl>  <dbl>  <dbl>    <dbl> #> 1 BCB      0.0535 0.0445 0.0625   0.0522 #> 2 HB       0.118  0.0663 0.169    0.0522 #> 3 LTB      0.0281 0.0247 0.0315   0.0522 #> 4 MR       0.0446 0.0375 0.0516   0.0522 #> 5 MTB      0.0374 0.0327 0.0421   0.0522 #> 6 OTB      0.0506 0.0371 0.0642   0.0522 #> 7 TCB      0.0337 0.0265 0.0409   0.0522"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Get annual medians Tampa Bay Benthic Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"anlz_tbbimed(   tbbiscr,   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"),   rev = FALSE,   yrrng = c(1993, 2022) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" rev logical factor levels bay segments reversed yrrng numeric indicating year ranges evaluate","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"data frame annual medians bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\"). sampling funded TBEP part routine EPC benthic monitoring program included final categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) anlz_tbbimed(tbbiscr) #> # A tibble: 268 × 6 #> # Rowwise:  #>    bay_segment    yr Degraded Healthy Intermediate TBBICat #>    <fct>       <dbl>    <dbl>   <dbl>        <dbl> <fct>   #>  1 All          1993    0.3     0.244        0.456 Poor    #>  2 All          1994    0.449   0.180        0.371 Poor    #>  3 All          1995    0.133   0.508        0.359 Fair    #>  4 All          1996    0.138   0.569        0.292 Fair    #>  5 All          1997    0.157   0.421        0.421 Fair    #>  6 All          1998    0.231   0.316        0.453 Poor    #>  7 All          1999    0.107   0.377        0.516 Fair    #>  8 All          2000    0.163   0.407        0.430 Fair    #>  9 All          2001    0.231   0.321        0.449 Poor    #> 10 All          2002    0.2     0.425        0.375 Poor    #> # ℹ 258 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"Get Tampa Bay Benthic Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"benthicdata nested tibble formatted read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"single data frame TBBI scores site.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"function calculates scores TBBI based station, taxa, field sample data.  total TBBI scores returned TBBI TBBICat, latter categorical description scores.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata) #> # A tibble: 4,787 × 15 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl>, #> #   TotalAbundance <dbl>, SpeciesRichness <dbl>, TBBI <dbl>, TBBICat <chr>, #> #   Salinity <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"Get annual averages Tampa Bay Nekton Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"anlz_tbniave(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   rev = FALSE,   perc = c(32, 46) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" rev logical factor levels bay segments reversed perc numeric values indicating break points score categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) anlz_tbniave(tbniscr) #> # A tibble: 104 × 5 #>    bay_segment  Year Segment_TBNI Action          outcome #>    <fct>       <dbl>        <dbl> <fct>           <chr>   #>  1 HB           1998           47 Stay the Course green   #>  2 HB           1999           47 Stay the Course green   #>  3 HB           2000           44 Caution         yellow  #>  4 HB           2001           44 Caution         yellow  #>  5 HB           2002           39 Caution         yellow  #>  6 HB           2003           41 Caution         yellow  #>  7 HB           2004           41 Caution         yellow  #>  8 HB           2005           32 Caution         yellow  #>  9 HB           2006           41 Caution         yellow  #> 10 HB           2007           42 Caution         yellow  #> # ℹ 94 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":null,"dir":"Reference","previous_headings":"","what":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"Get raw metrics Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"fimdata data.frame formatted read_importfim logical indicating TBNI metrics returned (default), otherwise calcualted","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"data frame raw metrics wide fomat.  = TRUE, metrics returned, otherwise NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"raw metrics returned addition required TBNI.  row shows metric values station, year, month fish catch data available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata) #> # A tibble: 7,766 × 10 #>    Reference  Year Month Season bay_segment NumTaxa Shannon TaxaSelect NumGuilds #>    <chr>     <dbl> <dbl> <chr>  <chr>         <dbl>   <dbl>      <dbl>     <dbl> #>  1 TBM19980…  1998     1 Winter OTB               2   0.362          0         2 #>  2 TBM19980…  1998     1 Winter OTB               1   0              1         1 #>  3 TBM19980…  1998     1 Winter OTB               0   0              0         0 #>  4 TBM19980…  1998     1 Winter OTB               2   0.693          0         1 #>  5 TBM19980…  1998     1 Winter MTB               4   1.16           1         2 #>  6 TBM19980…  1998     1 Winter MTB               2   0.500          1         1 #>  7 TBM19980…  1998     1 Winter MTB               5   0.426          2         3 #>  8 TBM19980…  1998     1 Winter OTB               0   0              0         0 #>  9 TBM19980…  1998     1 Winter HB                4   0.794          1         4 #> 10 TBM19980…  1998     1 Winter HB                1   0              0         1 #> # ℹ 7,756 more rows #> # ℹ 1 more variable: BenthicTaxa <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"Get Tampa Bay Nekton Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata, raw = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"fimdata data.frame formatted read_importfim raw logical indicating raw metric values also returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"data frame metrics TBNI scores wide format.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"function calculates raw scored metrics TBNI, including NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon.  total TBNI score returned TBNI_Score.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata) #> # A tibble: 7,766 × 16 #>    Reference      Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #>    <chr>         <dbl> <dbl> <chr>  <chr>            <dbl>   <dbl>        <dbl> #>  1 TBM1998010906  1998     1 Winter OTB                 18       2            2 #>  2 TBM1998010910  1998     1 Winter OTB                 14       1            1 #>  3 TBM1998010912  1998     1 Winter OTB                  0       0            0 #>  4 TBM1998010914  1998     1 Winter OTB                 20       2            2 #>  5 TBM1998010915  1998     1 Winter MTB                 46       4            4 #>  6 TBM1998010917  1998     1 Winter MTB                 24       2            2 #>  7 TBM1998010920  1998     1 Winter MTB                 50       5            5 #>  8 TBM1998010922  1998     1 Winter OTB                  0       0            0 #>  9 TBM1998010926  1998     1 Winter HB                  48       4            4 #> 10 TBM1998010928  1998     1 Winter HB                   8       1            1 #> # ℹ 7,756 more rows #> # ℹ 8 more variables: BenthicTaxa <dbl>, ScoreBenthicTaxa <dbl>, #> #   TaxaSelect <dbl>, ScoreTaxaSelect <dbl>, NumGuilds <dbl>, #> #   ScoreNumGuilds <dbl>, Shannon <dbl>, ScoreShannon <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate tidal creek report card scores — anlz_tdlcrk","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"Estimate tidal creek report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, tidtrgs = NULL, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters data base data.frame tidtrgs optional data.frame tidal creek nitrogen targets, defaults tidaltargets yr numeric reference year evaluate, scores based planning period beginning ten years prior date","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"data.frame report card scores creek, prioritize, investigate, caution, monitor, data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) #> # A tibble: 615 × 10 #>       id wbid  JEI   name     class monitor caution investigate prioritize score #>    <int> <chr> <chr> <chr>    <chr>   <dbl>   <dbl>       <dbl>      <dbl> <chr> #>  1     1 1983B CC01  Rock Cr… 2          NA      NA          NA         NA No D… #>  2     2 2052  CC01  Rock Cr… 3M         10      NA          NA         NA Moni… #>  3     3 1983B CC02  Oyster … 2          NA      NA          NA         NA No D… #>  4     4 2067  CC02  Oyster … 3M         10      NA          NA         NA Moni… #>  5     5 1983B CC03  Buck Cr… 2          NA      NA          NA         NA No D… #>  6     6 2068  CC03  Buck Cr… 3M          9       1          NA         NA Moni… #>  7     7 2078A CC04  Buck Cr… 2          NA      NA           1         NA Inve… #>  8     8 2078A CC05  Coral C… 2          NA      NA          NA         NA No D… #>  9     9 2078B CC05  Coral C… 2           4       1          NA         NA Moni… #> 10    10 2065C CC06  Catfish… 2          NA      NA          NA         NA No D… #> # ℹ 605 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Estimate tidal creek water quality indicators support report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters rule data base data.frame yr numeric reference year evaluate, scores based planning period beginning ten years prior date radar logical indicating output show_tdlcrkradar, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"data.frame indicator values tidal creek","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Annual geometric means additional water quality data available wbid, JEI combination.  Florida trophic state index values also estimated data available. Nitrogen ratios estimated JEIs cover source (upstream, freshwater) tidal (downstream) WBIDs, defined ratio concentrations two (.e., ratios > 1 mean source higher concentrations).  Nitrogen ratios given year reflect ratio median nitrogen concentrations measured source tidal segment day.  Note ratio one can obtained source tidal segments minimum detection. Indicators years 10% observations exceed saturation criteria also estimated.  do_bnml do_prop columns show 1 0 given year indicate ten percent observations percent saturation 42.  first column based binomial probability exceedance takes account number observations year second column based simple proportional estimate raw data. radar = TRUE, output returned format use show_tdlcrkradar  Specifically, results calculated percentage years indicator exceeds relevant threshold.  applies marine WBIDs tidal creeks (Florida DEP class 2, 3M).  Six indicators returned percentage exceedances based total nitrogen (tn_ind) greater 1.1 mg/L, chlorophyll (chla_ind) greater 11 ug/L, trophic state index (tsi_ind) greater 55 (100), nitrate/nitrite ratio marine upstream segments (nox_ind) greater one, chlorophyll total nitrogen ratios > 15, percentage years ten percent observations percent saturation 42.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"dat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) head(dat) #>   id       name  JEI wbid class year    CHLAC    COLOR COND       DO    DOSAT #> 1  2 Rock Creek CC01 2052    3M 2014 2.380249 14.69473   NA 3.308289 60.31523 #> 2  2 Rock Creek CC01 2052    3M 2015 2.647817 21.91113   NA 4.034172 55.41609 #> 3  2 Rock Creek CC01 2052    3M 2016 2.265462 19.13080   NA 3.980251 55.96637 #> 4  2 Rock Creek CC01 2052    3M 2017 2.851726 15.39576   NA 4.157777 60.18017 #> 5  2 Rock Creek CC01 2052    3M 2018 1.934899 11.65500   NA 4.219790 63.32630 #> 6  2 Rock Creek CC01 2052    3M 2019 2.071003  7.21425   NA 3.015847 44.90322 #>          NO23 ORGN    SALIN       TKN        TN         TP TSS     TURB #> 1 0.007575792   NA 26.63714 0.6161702 0.6228782 0.06938150  NA 2.044623 #> 2 0.009361504   NA 19.10494 0.6465161 0.5678241 0.07602770  NA 1.814818 #> 3 0.008532522   NA 25.84531 0.5813818 0.5408161 0.08330509  NA 2.082253 #> 4 0.007447260   NA 24.86909 0.6255197 0.6326848 0.07566682  NA 1.802161 #> 5 0.006994714   NA 31.32419 0.5668727 0.5734574 0.07432007  NA 2.454007 #> 6 0.007047106   NA 31.63214 0.5053022 0.4577485 0.06300538  NA 1.831953 #>   chla_tn_ratio tn_tp_ratio chla_tsi   tn_tsi  tn2_tsi   tp_tsi  tp2_tsi #> 1      3.821371    8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2      4.663093    7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3      4.188970    6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4      4.507341    8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5      3.374095    7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6      4.524324    7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #>    nut_tsi      tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651          NA         NA         NA       0       1 #> 2 47.43600 39.12890          NA         NA         NA       0       1 #> 3 46.38844 37.48223          NA         NA         NA       0       1 #> 4 49.76107 40.82559          NA         NA         NA       0       0 #> 5 47.64821 36.97650          NA         NA         NA       0       1 #> 6 42.80384 35.04375          NA         NA         NA       1       1"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"Get annual averages seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"anlz_transectave(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   total = TRUE,   yrrng = c(1998, 2023),   rev = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments yrrng numeric indicating year ranges evaluate rev logical factor levels bay segments reversed","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"focat column returned results shows color category based arbitrary breaks frequency occurrence estimates (foest) 25, 50, 75 percent.  necessarily translate ecological breakpoints.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) anlz_transectave(transectocc) #> # A tibble: 156 × 4 #> # Groups:   bay_segment [6] #>    bay_segment    yr foest focat   #>    <fct>       <dbl> <dbl> <fct>   #>  1 Tampa Bay    1998  58.0 #E9C318 #>  2 OTB          1998  65.5 #E9C318 #>  3 HB           1998  15.0 #CC3231 #>  4 MTB          1998  53.7 #E9C318 #>  5 LTB          1998  80.8 #2DC938 #>  6 BCB          1998  81.0 #2DC938 #>  7 Tampa Bay    1999  51.5 #E9C318 #>  8 OTB          1999  64.7 #E9C318 #>  9 HB           1999  10.1 #CC3231 #> 10 MTB          1999  51.8 #E9C318 #> # ℹ 146 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Get annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"anlz_transectavespp(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   yrrng = c(1998, 2023),   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\",     \"Dapis\"),   total = TRUE,   by_seg = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned by_seg logical indicating separate results bay segments retained","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Frequency occurrence estimates averaged across segments bay_segment by_seg = F, .e., separate results location returned.  Results retained bay segment by_seg = T.  Also note totals across species (total = T) returned by_seg = T.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) anlz_transectavespp(transectocc) #> # A tibble: 208 × 3 #>       yr Savspecies   foest #>    <dbl> <fct>        <dbl> #>  1  1998 Caulerpa    0.0166 #>  2  1998 Dapis       0      #>  3  1998 Halodule    0.361  #>  4  1998 Halophila   0      #>  5  1998 Ruppia      0.0112 #>  6  1998 Syringodium 0.0451 #>  7  1998 Thalassia   0.254  #>  8  1998 total       0.580  #>  9  1999 Caulerpa    0.0277 #> 10  1999 Dapis       0      #> # ℹ 198 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":null,"dir":"Reference","previous_headings":"","what":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Get seagrass average abundance occurrence across transects","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"anlz_transectocc(transect)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"transect data frame returned read_transect","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"data frame abundance frequency occurrence estimates aggregated species, transect, date.  nsites column total number placements sampled along transect particular date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2.  short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect.  estimates obtained seagrass species including Caulerpa (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Sherwood, E.T., Greening, H.S., Johansson, J.O.R., Kaufman, K., Raulerson, G.E. 2017. Tampa Bay (Florida, USA): Documenting seagrass recovery since 1980's reviewing benefits. Southeastern Geographer. 57(3):294-319.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } anlz_transectocc(transect) #> # A tibble: 37,625 × 6 #> # Groups:   Date, Transect [1,505] #>    Date       Transect Savspecies              nsites foest bbest #>    <date>     <chr>    <chr>                    <int> <dbl> <dbl> #>  1 1997-10-11 S2T3     \"AA\"                        41     0     0 #>  2 1997-10-11 S2T3     \"Caulerpa\"                  41     0     0 #>  3 1997-10-11 S2T3     \"DA\"                        41     0     0 #>  4 1997-10-11 S2T3     \"DB: Dictyota\\r\\n\"          41     0     0 #>  5 1997-10-11 S2T3     \"DB: Drift Brown\\r\\n\"       41     0     0 #>  6 1997-10-11 S2T3     \"DG: Chaetomorpha\\r\\n\"      41     0     0 #>  7 1997-10-11 S2T3     \"DG: Drift Green\"           41     0     0 #>  8 1997-10-11 S2T3     \"DG: Ulva\"                  41     0     0 #>  9 1997-10-11 S2T3     \"DG: Ulva fasciata\\r\\n\"     41     0     0 #> 10 1997-10-11 S2T3     \"DR: Acanthophora\"          41     0     0 #> # ℹ 37,615 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories for a chosen year — anlz_yrattain","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"Get attainment categories chosen year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"anlz_yrattain(epcdata, yrsel, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"data.frame chosen year bay segments showing bay segment averages chloropyll concentration, light attenuations, segment targets, attainment categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"# defaults to current year anlz_yrattain(epcdata, yrsel = 2023) #> # A tibble: 4 × 6 #>   bay_segment chla_val chla_target la_val la_target outcome #>   <fct>          <dbl>       <dbl>  <dbl>     <dbl> <chr>   #> 1 OTB             6.21         8.5  0.734      0.83 green   #> 2 HB              6.93        13.2  0.791      1.58 green   #> 3 MTB             3.68         7.4  0.472      0.83 green   #> 4 LTB             2.60         4.6  0.536      0.63 green"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 03132024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"benthicdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"nested tibble 3 rows 2 variables: name chr identifying dataset stations, fieldsamples, taxacounts value list dataframes dataset","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/benthic.zip'  # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE, remove = TRUE)  save(benthicdata, file = 'data/benthicdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Terrain basemap — bsmap","title":"Terrain basemap — bsmap","text":"Terrain basemap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Terrain basemap — bsmap","text":"","code":"bsmap"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Terrain basemap — bsmap","text":"ggmap object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":null,"dir":"Reference","previous_headings":"","what":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"Catchments radar pixels (precip) selected Enterococcus stations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"","code":"catchpixels"},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"data frame two columns: station character string Water Quality Portal station name pixel number; row single pixel Southwest Florida Water Management District's radar-estimated rainfall shapefile","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"Generated data-raw/catchpixels-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/catchpixels-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":null,"dir":"Reference","previous_headings":"","what":"Daily precip by catchment for selected Enterococcus stations — catchprecip","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Daily precip catchment selected Enterococcus stations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"","code":"catchprecip"},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"data frame three columns: station character string Water Quality Portal station name date date rain number; inches rain date, averaged across pixels station's catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Southwest Florida Management District radar-estimated daily rainfall data, ftp://ftp.swfwmd.state.fl.us/pub/radar_rainfall/Daily_Data/","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Daily precipitation data 1995-2023, provided Southwest Florida Water Management District, downloaded pixel level averaged catchment level key Enterococcus sampling stations. Generated data-raw/catchprecip-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/catchprecip-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"Enterococcus data 53 key Enterococcus stations since 1995","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"","code":"enterodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"data frame 6266 rows 16 columns: date date, sample date yr numeric, year sample date mo numeric, month sample date time character, sample time time_zone character, sample time zone long_name character, long name bay segment subwatershed bay_segment character, short name bay segment subwatershed station character, sample station entero numeric, Enterococcus concentration entero_censored logical, whether entero value laboratory MDL, minimum detection limit MDL numeric, minimum detection limit time processing entero_units character, units measurement entero qualifier qualifier codes associated sample LabComments lab comments sample Latitude numeric, latitude decimal degrees Longitude numeric, longitude decimal degrees","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"Water Quality Portal, https://waterqualitydata.us","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"sample dataset containing Enterococcus 53 stations TBEP watershed 1995-2023. Generated data-raw/enterodata-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/enterodata-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All bay data as of 20240201 — epcdata","title":"All bay data as of 20240201 — epcdata","text":"bay data 20240201","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All bay data as of 20240201 — epcdata","text":"","code":"epcdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All bay data as of 20240201 — epcdata","text":"data frame 27961 rows 26 variables: bay_segment chr epchc_station num SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num tn num tn_q chr sd_m num sd_raw_m num sd_q chr chla num chla_q chr Sal_Top_ppth num Sal_Mid_ppth num Sal_Bottom_ppth num Temp_Water_Top_degC num Temp_Water_Mid_degC num Temp_Water_Bottom_degC num Turbidity_JTU-NTU num Turbidity_Q num Color_345_F45_PCU num Color_345_F45_Q num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All bay data as of 20240201 — epcdata","text":"","code":"if (FALSE) { # \\dontrun{ xlsx <- '~/Desktop/epcdata.xlsx' epcdata <- read_importwq(xlsx, download_latest = TRUE)  nrow(epcdata) ncol(epcdata)  save(epcdata, file = 'data/epcdata.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20240814","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"","code":"fibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"data frame 77526 rows 18 variables: area chr epchc_station num class chr SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num ecoli num ecoli_q chr entero num entero_q chr fcolif num fcolif_q chr totcol num totcol_q chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"","code":"if (FALSE) { # \\dontrun{ xlsx <- tempfile(fileext = '.xlsx') fibdata <- read_importfib(xlsx, download_latest = TRUE)  nrow(fibdata) ncol(fibdata)  save(fibdata, file = 'data/fibdata.RData', compress = 'xz')  file.remove(xlsx) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":null,"dir":"Reference","previous_headings":"","what":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"FIM data Tampa Bay Nekton Index current 07092024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"","code":"fimdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"data frame 52042 rows 19 variables: Reference chr Sampling_Date Date Latitude num Longitude num Zone chr Grid int NODCCODE chr Year num Month num Total_N num ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"","code":"if (FALSE) { # \\dontrun{ csv <- '~/Desktop/TampaBay_NektonIndexData.csv'  fimdata <- read_importfim(csv, download_latest = TRUE)  save(fimdata, file = 'data/fimdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"Spatial data object FIM stations including Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"fimstations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"simple features sf object (POINT) 7771 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Reference num bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"if (FALSE) { # \\dontrun{ # file path csv <- '~/Desktop/fimdata.csv'  # load and assign to object fimstations <- read_importfim(csv, download_latest = FALSE, locs = TRUE) save(fimstations, file = 'data/fimstations.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":null,"dir":"Reference","previous_headings":"","what":"Habitat Master Plan targets and goals — hmptrgs","title":"Habitat Master Plan targets and goals — hmptrgs","text":"Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"hmptrgs"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Habitat Master Plan targets and goals — hmptrgs","text":"data frame showing 2030 targets 2050 goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/trgs.RData\"))  hmptrgs <- trgs %>%    rename(Goal2050 = Target2050)  save(hmptrgs, file = 'data/hmptrgs.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"FDEP IWR run 65 — iwrraw","title":"FDEP IWR run 65 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 65 — iwrraw","text":"","code":"iwrraw"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FDEP IWR run 65 — iwrraw","text":"data frame 537946 rows 11 variables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"FDEP IWR run 65 — iwrraw","text":"File created using workflow <https://tbep-tech.github.io/tidalcreek-stats/Creek_select_tbeptools>, example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FDEP IWR run 65 — iwrraw","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  load(file = '../../02_DOCUMENTS/tidal_creeks/iwrraw_run61.RData') iwrraw <- sf::st_set_geometry(iwrraw, NULL) %>%   rename(JEI = jei) save(iwrraw, file = 'data/iwrraw.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Manatee County FIB data as of 20241011 — mancofibdata","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"Manatee County FIB data 20241011","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"","code":"mancofibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"data frame 12765 rows 13 variables: manco_station chr, Station name SampleTime POSIXct, Date/time sampling class chr, Waterbody class (Fresh, Estuary) yr num, Year sampling mo num, Month sampling Latitude num, Latitude, WGS84 Longitude num, Latitude, WGS84 Sample_Depth_m num, Depth sample, meters var chr, Variable name (ecoli, entero, fcolif, totcol) val num, Value variable uni num, Units variable qual num, Qualifier code area chr, Location name based USF Water Alas waterbody name","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"","code":"if (FALSE) { # \\dontrun{ mancofibdata <- read_importwqp('21FLMANA_WQX', type = 'fib')  nrow(mancofibdata) ncol(mancofibdata)  save(mancofibdata, file = 'data/mancofibdata.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Phytoplankton data current as of 03202024 — phytodata","title":"Phytoplankton data current as of 03202024 — phytodata","text":"Phytoplankton data current 03202024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"phytodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Phytoplankton data current as of 03202024 — phytodata","text":"nested tibble 21143 rows 8 variables: epchc_station chr Date Date name chr units chr count num yrqrt Date yr num mo Ord.factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- tempfile(fileext = '.xlsx')  # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE)  nrow(phytodata) ncol(phytodata)  save(phytodata, file = 'data/phytodata.RData', compress = 'xz')  file.remove(path) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":null,"dir":"Reference","previous_headings":"","what":"Download latest file from epchc.org — read_dlcurrent","title":"Download latest file from epchc.org — read_dlcurrent","text":"Download latest file epchc.org","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"read_dlcurrent(locin, download_latest = TRUE, urlin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download latest file from epchc.org — read_dlcurrent","text":"locin chr string path local file, overwrite current download_latest logical download latest file regardless local copy urlin url file location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy specified path locin overwritten new file current download_latest = TRUE.  function nothing download_latest = FALSE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy checked temporary file downloaded location specified urlin.  local file replaced downloaded file MD5 hashes different.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"if (FALSE) { # \\dontrun{ locin <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(locin = locin, urlin = urlin) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Format benthic data Tampa Bay Benthic Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"read_formbenthic(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"pathin path unzipped csv files base tables used calculate benthic index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"nested tibble station, field sample, taxa data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Function used internally within read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"if (FALSE) { # \\dontrun{  # location to download data path <- '~/Desktop/benthic.zip'  # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin)  # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE)  # format benthic data read_formbenthic(pathin = tmppth)  # remove temporary path unlink(tmppth, recursive = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Format Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"read_formfib(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"datin input data.frame loaded read_importepc logical indicating stations FIB data returned, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"lightly formatted data.frame FIB data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Formats input data read_importepc appropriate FIB results, see details read_importfib information.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T)  # final formatting fibdata <- read_formfib(epcall) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Format FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"read_formfim(datin, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"datin input data.frame loaded read_importfim locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Function used internally within read_importfim","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"# file path csv <- url('https://raw.githubusercontent.com/tbep-tech/tbni-proc/master/data/TampaBay_NektonIndexData.csv')  datin <- read.csv(csv)  # load and assign to object fimdata <- read_formfim(datin) #> Warning: attribute variables are assumed to be spatially constant throughout all geometries"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Format phytoplankton data — read_formphyto","title":"Format phytoplankton data — read_formphyto","text":"Format phytoplankton data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format phytoplankton data — read_formphyto","text":"","code":"read_formphyto(datin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format phytoplankton data — read_formphyto","text":"datin input data.frame loaded read_importphyto","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format phytoplankton data — read_formphyto","text":"formatted data.frame phytoplankton count data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format phytoplankton data — read_formphyto","text":"seven taxonomic groups summarized. Pyrodinium bahamense, Karenia brevis, Tripos hircus, Pseudo-nitzschia sp., Pseudo-nitzschia pungens retained species level.  Bacillariophyta Cyanobacteria retained phylum level.  taxa grouped \"\" category.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format phytoplankton data — read_formphyto","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/phyto_data.xlsx'  # load and assign to object phytodata <- read_importphyto(xlsx) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Format sediment data — read_formsediment","title":"Format sediment data — read_formsediment","text":"Format sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format sediment data — read_formsediment","text":"","code":"read_formsediment(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format sediment data — read_formsediment","text":"pathin path unzipped csv files sediment result tables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format sediment data — read_formsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format sediment data — read_formsediment","text":"Function used internally within read_importsediment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format sediment data — read_formsediment","text":"","code":"if (FALSE) { # \\dontrun{  # location to download data path <- '~/Desktop/sediment.zip'  # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin)  # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE)  # format sediment data read_formsediment(pathin = tmppth)  # remove temporary path unlink(tmppth, recursive = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":null,"dir":"Reference","previous_headings":"","what":"Format seagrass transect data from Water Atlas — read_formtransect","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Format seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"read_formtransect(jsn, training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"jsn data frame returned fromJSON training logical input transect training data complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"data frame long format","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Shoot density reported number shoots per square meter corrected quadrat size entered raw data.  Shoot density blade height (cm) based averages across random observations transect point entered separately data form. Abundance reported numeric value 0 - 5 Braun-Blanquet coverage estimates. raw = TRUE, unformatted data returned.  default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"library(jsonlite)  if (FALSE) { # \\dontrun{ # all transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use-with-care' jsn <- fromJSON(url) trndat <- read_formtransect(jsn) } # }  # training transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/training' jsn <- fromJSON(url) trndat <- read_formtransect(jsn, training = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Format water quality data — read_formwq","title":"Format water quality data — read_formwq","text":"Format water quality data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format water quality data — read_formwq","text":"","code":"read_formwq(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format water quality data — read_formwq","text":"datin input data.frame loaded read_importepc logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format water quality data — read_formwq","text":"lightly formatted data.frame chloropyll secchi observations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format water quality data — read_formwq","text":"Secchi data VOB depths secchis < 0.5 ft bottom assigned NA, function used internally within read_importwq","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format water quality data — read_formwq","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T)  # final formatting epcdata <- read_formwq(epcall) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Format data and station metadata from the Water Quality Portal — read_formwqp","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"Format data station metadata Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"read_formwqp(res, sta, org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"res data frame containing results obtained API sta data frame containing station metadata obtained API org chr string indicating organization identifier type chr string indicating data type download, one \"wq\" \"fib\" trace Logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"data frame containing formatted water quality station metadata","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"function used read_importwqp combine, format, process data (res) station metadata (sta) obtained Water Quality Portal selected county data type. resulting data frame includes date, time, station identifier, latitude, longitude, variable name, value, unit, quality flag.  Manatee County FIB data (21FLMANA_WQX) also include area column indicating waterbody name used USF Water Atlas.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"if (FALSE) { # \\dontrun{ url <- list(   Result = \"https://www.waterqualitydata.us/data/Result/search?mimeType=csv&zip=no\",   Station = \"https://www.waterqualitydata.us/data/Station/search?mimeType=csv&zip=no\" )  headers <- c(   \"Content-Type\" = \"application/json\",   \"Accept\" = \"application/zip\" )  body <- list(   organization = c(\"21FLMANA_WQX\"),   sampleMedia = c(\"Water\"),   characteristicType = c(\"Information\", \"Nutrient\", \"Biological, Algae, Phytoplankton,     Photosynthetic Pigments\"),   providers = c(\"STORET\"),   siteType = c(\"Estuary\") )  res <- url[['Result']] %>%   httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>%   httr::content('text') %>%   read.csv(text = .)  sta <- url[['Station']] %>%   httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>%   httr::content('text') %>%   read.csv(text = .)  # combine and format read_formwqp(res, sta, '21FLMANA_WQX', type = 'wq') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import benthic data for Tampa Bay — read_importbenthic","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"Download import benthic data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"read_importbenthic(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"nested tibble station, taxa, field sample data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"function downloads unzips folder base tables used calculate benthic index https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/benthic.zip'  # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Enterococcus data from the Water Quality Portal — read_importentero","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"Download Enterococcus data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"","code":"read_importentero(stas = NULL, startDate, endDate)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"stas character, vector stations.  NULL, defaults stations catchprecip. startDate character, starting date observations YYYY-MM-DD endDate character, ending date observations YYYY-MM-DD","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"data frame containing one row sample. Columns returned : date date, sample date yr numeric, year sample date mo numeric, month sample date time character, sample time time_zone character, sample time zone long_name character, long name bay segment subwatershed bay_segment character, short name bay segment subwatershed station character, sample station entero numeric, Enterococcus concentration entero_censored logical, whether entero value laboratory MDL, minimum detection limit MDL numeric, minimum detection limit time processing entero_units character, units measurement entero qualifier qualifier codes associated sample LabComments lab comments sample Latitude numeric, latitude decimal degrees Longitude numeric, longitude decimal degrees","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"Retrieves Enterococcus sample data selected stations date range Water Quality Portal, https://www.waterqualitydata.us","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"","code":"if (FALSE) { # \\dontrun{ # stations to download stas <- c('21FLHILL_WQX-101', '21FLHILL_WQX-102', '21FLHILL_WQX-103')  # download and read the data entero_in <- read_importentero(stas = stas, startDate = '2023-01-01', endDate = '2023-02-01')  head(entero_in)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and/or import local water quality file for internal use — read_importepc","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Download /import local water quality file internal use","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"read_importepc(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and/or import local water quality file for internal use — read_importepc","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and/or import local water quality file for internal use — read_importepc","text":"unformatted data.frame EPC","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. function used internally read_importwq read_importfib use source data Environmental Protection Commission Hillsborough County.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object epcall <- read_importepc(xlsx, download_latest = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Load local water quality file Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"read_importfib(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating stations FIB data returned, default TRUE, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"data.frame formatted FIB data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Returns FIB data including E. coli, Enterococcus, Fecal Coliform, Total Coliform concentrations waterbody class (freshwater 1 3F, marine 2 3M) stations sample dates, function used internally within read_importfib Values returned E. coli (ecoli), Enterococcus (entero), Fecal Coliform (fcolif), Total Coliform (totcol).  Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown.  Samples notation can determined qualifier columns. = FALSE, stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object fibdata <- read_importfib(xlsx, download_latest = T)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Load local FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"read_importfim(csv, download_latest = FALSE, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"csv chr string path local csv file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing csv available locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Data downloaded ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"if (FALSE) { # \\dontrun{ # file path csv <- '~/Desktop/fimraw.csv'  # load and assign to object fimdata <- read_importfim(csv, download_latest = TRUE) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local phytoplankton cell count file — read_importphyto","title":"Load local phytoplankton cell count file — read_importphyto","text":"Load local phytoplankton cell count file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"read_importphyto(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local phytoplankton cell count file — read_importphyto","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local phytoplankton cell count file — read_importphyto","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local phytoplankton cell count file — read_importphyto","text":"Phytoplankton cell count data downloaded https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/phyto_data.xlsx'  # load and assign to object phytodata <- read_importphyto(xlsx, download_latest = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily precip data and summarise by station catchment — read_importrain","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"Download daily precip data summarise station catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"","code":"read_importrain(curyr, catchpixels, mos = 1:12, quiet = T)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"curyr numeric year catchpixels data.frame columns named 'station' 'pixel'. data frame created key Enterococcus stations, associating station pixels station's catchment layer. tbeptools object 'catchpixels'. mos numeric vector months download quiet logical messages","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"data.frame station, date, rain columns daily average (inches) pixels catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"Data Southwest Florida Water Management District's (SWFWMD) ftp site: ftp://ftp.swfwmd.state.fl.us/pub/radar_rainfall/Daily_Data/","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"","code":"if (FALSE) { # \\dontrun{ read_importrain(2021, catchpixels, quiet = F) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import sediment data for Tampa Bay — read_importsediment","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"Download import sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"read_importsediment(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"function downloads unzips folder results tables https://epcbocc.sharepoint.com/:u:/s/Share/Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). row entries columns \"BetweenTELPEL\" \"ExceedsPEL\" rows \"Qualifier\" column \"U\" \"T\" (detection, detected) assigned NA, regardless entry source data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/sediment.zip'  # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file — read_importwq","title":"Load local water quality file — read_importwq","text":"Load local water quality file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file — read_importwq","text":"","code":"read_importwq(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file — read_importwq","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file — read_importwq","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file — read_importwq","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Water quality parameters returned default total nitrogen (tn), Secchi depth (sd), chlorophyll-(chla), salinity (top, mid, bottom depths, Sal_ prefix), water temperature (top, mid, bottom depths, Temp_Water_ prefix), turbidity (Turbidity_JTU-NTU), water color (Color_345_F45).  Additional qualifier columns include _Q suffix also returned, excluding salinity water temperature.  water quality parameters qualifiers can returned setting = T.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file — read_importwq","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object epcdata <- read_importwq(xlsx, download_latest = T)  # get all water quality parameters epcdataall <- read_importwq(xlsx, download_latest = T, all = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Import data from the Water Quality Portal — read_importwqp","title":"Import data from the Water Quality Portal — read_importwqp","text":"Import data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"read_importwqp(org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import data from the Water Quality Portal — read_importwqp","text":"org chr string indicating organization identifier, see details type chr string indicating data type download, one \"wq\" \"fib\" trace logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import data from the Water Quality Portal — read_importwqp","text":"data frame containing imported data selected county","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import data from the Water Quality Portal — read_importwqp","text":"function retrieves data Water Quality Portal API (https://www.waterqualitydata.us/) selected counties around Tampa Bay watershed. type data returned defined type argument either \"wq\" \"fib\" water quality Fecal Indicator Bacteria data, respectively. org argument retrieves data specific organization. Valid entries org include \"21FLCOSP_WQX\" (City St. Petersburg), \"21FLDOH_WQX\" (Florida Department Health), \"21FLHILL_WQX\" (Hillsborough County), \"21FLMANA_WQX\" (Manatee County), \"21FLPASC_WQX\" (Pasco County), \"21FLPDEM_WQX\" (Pinellas County), \"21FLPOLK_WQX\" (Polk County), \"21FLTPA_WQX\" (Florida Department Environmental Protection, Southwest District).  naming convention follows Organization ID Water Quality Portal. function fetches results station metadata, combines formats using read_formwqp function, returns processed data data frame.  Parameters specific type argument.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"if (FALSE) { # \\dontrun{ # get Manatee County water quality data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T)  # get Pinellas County FIB data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Import JSON seagrass transect data from Water Atlas — read_transect","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"Import JSON seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"read_transect(training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"training logical training data imported complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"function imports JSON file USF Water Atlas.  training = TRUE, dataset TBEP training survey imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/training.  training = FALSE, entire transect survey database imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use--care. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates, blade length cm, short shoot density number shoots per square meter.  short density corrected quadrat size included raw data. raw = TRUE, unformatted data returned.  default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"if (FALSE) { # \\dontrun{ # get training data transect <- read_transect(training = TRUE)  # import all transect data transect <- read_transect() } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass coverage by year — seagrass","title":"Seagrass coverage by year — seagrass","text":"Seagrass coverage year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass coverage by year — seagrass","text":"","code":"seagrass"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass coverage by year — seagrass","text":"data frame used create flagship seagrass coverage graphic: Year int Acres num Hectares num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass coverage by year — seagrass","text":"Original data Southwest Florida Water Management District available online <https://data-swfwmd.opendata.arcgis.com/>.  Totals Tampa Bay.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass coverage by year — seagrass","text":"","code":"if (FALSE) { # \\dontrun{  seagrass <- structure(list(    Year = c(1950L, 1982L, 1988L, 1990L, 1992L, 1994L, 1996L,         1999L, 2001L, 2004L, 2006L, 2008L, 2010L, 2012L, 2014L,         2016L, 2018L, 2020L, 2022L),    Acres = c(40420, 21650, 23285, 25226, 25753, 26518, 26916,         24841, 26078, 27021, 28299, 29647, 32897, 34642, 40294.71,         41655.16, 40651.55, 34298, 30137),    Hectares = c(16357.39, 8761.44, 9423.11, 10208.6, 10421.87,         10731.45, 10892.52, 10052.8, 10553.39, 10935.01, 11452.2,         11997.72, 13312.94, 14019.27, 16306.69, 16857.25, 16451.1,         13880, 12196)  ), class = \"data.frame\", row.names = c(NA, -19L))  save(seagrass, file = 'data/seagrass.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"Sediment data Tampa Bay current 12142023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"sedimentdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"data.frame 216627 rows 24 variables: ProgramId int ProgramName chr FundingProject chr yr int AreaAbbr chr StationID int StationNumber chr Latitude num Longitude num Replicate chr SedResultsType chr Parameter chr ValueAdjusted num Units chr Qualifier chr MDLnum num PQLnum num TEL num PEL num BetweenTELPEL chr ExceedsPEL chr PreparationDate chr AnalysisTimeMerge chr PELGrade Factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/sediment.zip'  # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE, remove = TRUE)  save(sedimentdata, file = 'data/sedimentdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass management areas for Tampa Bay — sgmanagement","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"Seagrass management areas Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"sgmanagement"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"simple features sf object (MULTIPOLYGON) 30 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs areas int","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"polygons seagrass management areas Tampa Bay provide finer division areas within major segments (tbseg) relevance locations seagrass beds.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tools)  # NAD83(HARN) / Florida West (ftUS) # same as sgseg prj <- 2882  # create sf object of boundaries sgmanagement <- st_read(   dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Management_Areas/TBEP_SG_MA_FINAL_Projectfix.shp',   drivers = 'ESRI Shapefile'   ) %>%   select(areas = TBEP_SG_MA) %>%   st_zm() %>%   st_transform(prj)  # save save(sgmanagement, file = 'data/sgmanagement.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass segment reporting boundaries for southwest Florida — sgseg","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"Seagrass segment reporting boundaries southwest Florida","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"sgseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"simple features sf object (POLYGON) 22 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"polygons used Southwest Florida Water Management District summarizing seagrass coverage estimates major coastal estuarine boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tools)  # create sf object of boundaries # make sure projection does not change sgseg <- st_read(   dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Segment_Boundaries/Seagrass_Segment_Boundaries.shp',   drivers = 'ESRI Shapefile'   ) %>%   select(segment = SEAGRASSSE) %>%   mutate(      segment = tolower(segment),      segment = case_when(         segment == 'terra ciea bay' ~ 'Terra Ceia Bay',         T ~ segment      ),      segment = toTitleCase(segment)   )  # save save(sgseg, file = 'data/sgseg.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a table for the annual management outcome assessments — show_annualassess","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Create table annual management outcome assessments chlorophyll-light attenuation bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"","code":"show_annualassess(   epcdata,   yrsel,   partialyr = F,   caption = F,   family = \"Arial\",   txtsz = 12,   width = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter caption logical indicating caption added using set_caption family chr string indicating font family text labels txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"flextable object showing segment-averaged chlorophyll-light attenuation selected year, bay segment names colored management outcome used show_matrix.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63","code":"show_annualassess(epcdata, yrsel = 2023) .cl-80e58d66{}.cl-80de47f4{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-80de47fe{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-80e235a8{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-80e235b2{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-80e25024{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e2502e{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e2502f{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25038{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25042{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-80e25043{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63show_annualassess(epcdata, yrsel = 2023, caption = TRUE) .cl-8132123a{}.cl-812cce42{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-812cce4c{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-812f0162{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-812f016c{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-812f1a58{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a59{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a62{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a63{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a6c{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-812f1a6d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-81296f18{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}Water quality outcomes for 2023.SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Plot monthly chlorophyll light attenuation values bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(   epcdata,   param = c(\"chla\", \"la\"),   yrsel = NULL,   yrrng = c(1975, 2023),   ptsz = 0.5,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   trgs = NULL,   family = NA,   labelexp = TRUE,   txtlab = TRUE,   partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation yrsel numeric year emphasize, shown separate red points plot yrrng numeric vector indicating min, max years include ptsz numeric indicating point size observations yrsel bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" trgs optional data.frame annual bay segment water quality targets, defaults targets family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Points included yrsel plotted box plots using position_jitter. Use ptsz = -1 suppress.  dotted line plot shows large exceedance value.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a bar plot for transect training group comparisons — show_compplot","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"Make bar plot transect training group comparisons","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"show_compplot(   transect,   yr,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\"),   varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"),   base_size = 18,   xtxt = 10,   size = 1 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"transect data frame returned read_transect yr numeric year training data plot site chr string indicating site results plot species chr string indicating species plot varplo chr string indicating variable plot base_size numeric indicating text scaling size plot xtxt numeric indicating text size x-axis labels size numeric indicating line size","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"transect <- read_transect(training = TRUE) show_compplot(transect, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Enterococcus results by month, year, and location — show_enteromap","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"Map Enterococcus results month, year, location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"","code":"show_enteromap(   fibdata,   yrsel,   mosel,   areasel = NULL,   wetdry = FALSE,   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"fibdata data frame Enterococcus sample data returned enterodata anlz_fibwetdry yrsel optional numeric filter data year mosel optional numeric filter data month areasel optional character string filter output stations long_name column enterodata, see details wetdry logical; TRUE, incorporate wet/dry differences (result call anlz_fibwetdry, case temporal_window wet_threshold required). FALSE (default), differentiate wet dry samples. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required wetdry TRUE. number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required wetdry TRUE. inches accumulated defined temporal window, sample defined 'wet' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"","code":"show_enteromap(enterodata, yrsel = 2020, mosel = 9)  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ZRkrAAAAq2fS7IfEsCpr39k1vqpCgLiW5p6X56GknikZLwAAAKvFB9OtRwyqqjY77KssA4hr7Wzv63NRz1szXgAAAFbHZGQ/LYZUWftmV/iqiwDiGpt7X56Lknq2ZMwAAADsPXftsy+dNHtMDqmaftyVJQBxQ4wzoM5GPT1bImMybgAAAPaWvtkr5IAq6rSzC31Vwx9xI8wzIM9HRSNjMm4AAAD2joP77NvUYKpq39lNvsrhj7hJ5lmQ56SikTUZOwAAAHvDkH6/37jZp6advdpfy8GPuEnGWYgz4a/lealmZE3GDgAAwPIZd/ajaiBV1Qfle32VQx9xE80zIc9LRSNzMn4AAACWxxPfb7/Hh+RH1DCqaN/Z1Fc57BE32Twb8txUMzInsidjCAAAYDn4wPmvahAV9nJXDnrEDTfOhjozJY3syRgCAABYPPfut69QA6isze7wVQ14RAxnZ0Sfn4JGBmUcAQAALJa+2avU8CnryM73VQ94RHxpnhF9fgoaGZRxBAAAsDjGnf09NXiq2nd2g696uCPi75hnRZ6jikYWZSwBAAAsBh8w75wfOIV9dNrZr/sqBzsifsY8K4+66ixV9J0ZSwAAACdO3+xZYtjUdWRX+iqHOiIKZ2dGn6eCRiZlPAEAAOyeJw7Y7/fBcuf8oKlq31nvqx7miHhU8+zIc1XQOyObMqYAAAB2hw+//y6GTFn7Zm/0VQ5yRDy6eXbkuapoZFPGFAAAwM65v7OvUQOmqj744i+ykEMcEY9tniF5vioaGZVxBQAAsDN8kJw9P1hK2+y1vsoBjojH4ewM6fNV07MzrgAAAI6fvtl3iaFS1nFn1/uqhzciHrd5luQ5q2hkVcYWAADA8TFpdpUaKkV92IfdK32VgxsRj988Sw+76qzV07MqYwsAAODYTEb2XDlQqtrsXb7KoY2Iu3B2pvR5q6hnVsYXAADA0Rk/z77Ah9x9cpgUtO/soK96WCPirs2zJc9dOT2zIrsyxgAAADTjZr8sB0lR/Xov9VUOakTcvXm25LmraGRXxhgAAMCRTEb29WqAVLVv9mFf5ZBGxBM3z5g8fyX1DMs4AwAAeDI+1M6Tw6Oo/cjO8VUOaEQ8cfOMyfNX0ciwjDMAAIDPcLDZ96jBUdVxs/f7KoczIi7OPGvyHFY0sixjDQAAYEbf2XVqaFTUr/UThzo71V/LwYyIizPOWpw5fy3PYzUjyzLWAAAAtv8DtBeogVFVH2Tv8FUOZURcvHnm5HmsaGRaxhsAAGwyh/fbH500O6SGRUV94N7rqxzGiLg88+zJc1lOz7TItow5AADYVPpm/0sOiqo2e4OvchAj4hKdnT19Lgsa2ZYxBwAAm8ihZn9dDYjCfsjVQxgR98I4g+psljQyLuMOAAA2jb6zi9RwqOq42Wt8VcMXEffAPIPyfFY0Mi7jDgAANom+2ferwVBVH1jv81UOX0TcO/MsynNa0ci6jD0AANgUJs0+qIZCUR90T3Hl4EXEPTXOYpxJdVbr6VmXsQcAAJtA31knB0JR+2Zv81UNXERcgXkm5XmtaGRexh8AAKwzD27ZF0+aPaSGQUV9QN3tqxy2iLg682zKc1tOz7zIvoxBAABYVzz0X3LEECjsuNnrfZWDFhFXZ55NeW6L+pKMQQAAWEcO77eni/Cva7NbfJVDFhELODuj+vwWNDIw4xAAANYNH0qXqvCv6nhkZ/mqBywirtw8o/L8ltQzMOMQAADWiYPNfkgGf1H7Ztf4KocrItYxz6o8xxWNLMxYBACAdaHv7FYV+kW935VDFRFLGmdWneVyRhZmLAIAwDowbvbTKvCr6oPoCl/VMEXEguaZlee5opGJGY8AADBkJiP7s32zx1TYV7Tfsjt9lcMUEeuaZ1ee62puZ6JnY8YkAAAMlb6zU1XQV3Xa2YW+ykGKiHXNsyvPdUUjGzMmAQBgiEyafasK+MLe5MohioiDMM6wOts19YzMuAQAgKHRd/YWGe4F7bfsU369r/bXangi4gCMMxxn2V/Lc17NyMiMSwAAGBLTLfs3KtgL+15XDk9EHJRxltUZL2lkZcYmAAAMgScO2O/um92uQr2oU1cNTEQcpnGm1VkvZ2RlZGbGJwAAVKfv7L+oQK+qD5o3+6qGJSIO0DzT8rxXNDIz4xMAACpzaMu+XAV5Ye9w5bBExEEbZ1ud+ZJGdmaMAgBAVfrOfl2FeGHPd9WQRMRhG2dbnfmSRnZmjAIAQEUO7be/qwK8rM1u8FUNSERcB2dnXJ//gkaGZpwCAEA1+mbvUOFdUb/Wx/rR9r991gMSEQdvnPE46/5a5kA1I0MzTgEAoBLTzn5MBXdVfaC8x1c5HBFxfcyzLnOgopGlGasAAFCBx59nn+sB/fH5wC5s78qhiIhraZx5lQUV/XhkasYrAACsmr7Zz4uwLmvf2Zt8VcMQEdfQPPMyDyoamZrxCgAAq2Tc2deooK6qD5CP+CqHISKur3n2ZS5UNLI1YxYAAFbFZGRnqZCuqg+71/oqByEirq959mUulNSzNWMWAABWgQ+O75IBXdfrXTkEEXEjjAxQ2VDSyNiMWwAA2Gs8hK9S4VzRfsse8et9pb9Www8RN8DIgMgCfy1zopqRsRm3AACwl0y27LkqmKs67uzdvsrhh4ibY2aBzImSetZm7AIAwF5wsNkf7JvdJ0O5oH1nB32VQw8RN8/MBJkX1YysjczN+AUAgGUz7uyXVCCXtdmlvsqBh4gb6CwTdF4UNDI34xcAAJbJZMv+sgriwn7Y1cMOETfZyAaVGTX17M0YBgCAZdEP7Y/oaXaOr2rIIeImO8sGnRsFjezNGAYAgGUwGdk/UQFcVR8M7/dVDzlE3HgzI2R+lNQzOOMYAAAWjQ+F98nwrekn+pG9wlc54BARMyM+4aoMKWdkcMYxAAAskmln/1EFb1Wnzd7hqxxuiIifNrNC5khFI4szlgEAYBEceoH9kb6zqQrdot7ryqGGiCiMzFBZUs7I4sjkjGcAADhR+mb/UwVuWUf2Bl/VMENEPNJZZug8KWhkcsYzAACcCIf2219TQVvVvrPf8lUPM0TEo5jZIXOlopHNGdMAALBb+mavUyFb1mav8VUOMkTEozrLDp0rBY1szpgGAIDdMO3s+1TAVrXv7Dpf9RBDRDyGmSEyXyoaGZ1xDQAAO8WD9Pr5YC3sg32zl/sqBxgi4rHMDHnQVRlT0eszrgEAYCdMmzURqmXtO3ubr3J4ISIer5klMmcqGlmdsQ0AAMfDvVv2xR6gQ/q3Gne7cmghIu7CyBSVNRV9MDI74xsAAI6FB+dL5oK0tH2z1/uqhhUi4o7NTJF5U9SXZHwDAMBT0W/Z00WIlrXv7FZf5bBCRNytmS0ydyoa2Z0xDgAAR2Pc7FIVomUd2Vm+ykGFiLhrZ9mic6egkd0Z4wAAoOg7+5cqQMva7Bpf9ZBCRDxRZxmj86egkeEZ5wAAME/f7BYVnkW9fzISgwkRcVHOMuZ+V2VQOSPDM84BAOCz8ZD8qfnQLO4V7pGDCRFxsUbWqAyq6k9lrAMAQNCfZH+m7+xREZhVvdNVAwkRcRlG5qgsKmdkeWR6xjsAAExmfxuQDM2KepC/zlc1jBARF25mjsyjknqmZ7wDAGw2k5H9bRmURZ12dpOvchghIi7LzB6ZSyX1bM+YBwDYXPpmb5YhWdFmn/LrPcNfy0GEiLgst7PHM8hf63wqZmR7xjwAwGbiYfgj8+FY3Pe6cgghIu6BkUEqm6r6Ixn3AACbxRNP2O/qO/uwCMaaNjvkqxo8iIh75yyLdE4VMzI+sj5jHwBgc5g2+88qGAsbv8VCDx5ExL1zOL/dy42sz9gHANgMDu23L1OBWNZmH/NVDRxExL13lkk6rwoamZ/xDwCw/kw7O12FYVX7Zhf4qgcOIuIem5kk86qikfkZ/wAA68202XeoICzsDa4cNoiIKzSySWVWSSP7cwwAAKwvfWdvVyFY0maP9c1e5a/VkEFEXJnb2eQZ5a91fhUzsj/HAADAeuJB92MqAMva7D2+yiGDiLhyZxml86ugMQNyHAAArBe3Ps8+d0j/AUXfbOKrHi6IiEXMrJI5Vk6fATELciwAAKwPHsY/L4OvqH69b/JVDhZExCpmVskcq2jMghwLAADrwcGT7C+owKuqB/FHfZVDBRGxmplZMs8qGjMhxwMAwPCZNDtLhV1ZR/ZaX+VAQUQs5yyzdJ5V1GdCjgcAgGHTd/YPZdAVddrZ9b7qYYKIWNTMLplrFY3ZkGMCAGC49EP6r4KbPTJt9kp/LQcJImJVt7PLM8xf63wrZsyGHBMAAMPEQ/c5KuAK+25XDhFExAEYGaayraY+I3JcAAAMi3sP2Of3nd0rw62iIzvoqxociIjDcZZlOueKGTMiZkWODQCA4eCf1H9RBVthL3P14EBEHI6RZSrjauqzIscGAMAw8E/pXycDra4fdtXAQEQcopFpKutKGjMjxwcAQH08uM6dD7LSNjvHVzUsEBGH5yzTdN7V9NwcHwAAtfGA/W4RYmXtO3u/r3pYICIO1Mw2mXsl9dmRYwQAoC4ertfKEKtos0+6r/DXclAgIg7WyLbIOJV9BY3ZkWMEAKAmHqrPVwFW1mbv9FUPCUTEoTvLOJ1/FfUZkuMEAKAWh/bbF/bNJjK8ahp/9JkeDoiI6+Ng/pjHmCExS3KsAADUYdrZr6rgKmuzS3xVQwERcX2cZZ3OwYLGLMmxAgBQg2mzb1CBVdjfcvVQQERcPyPzVBaWNGZKjhcAgNXjn8AvVGFV1pG9xlc1DBAR189Z5uk8LGjMlBwvAACrZdzZ96mgqmrf7Dpf9TBARFxTM/tkLlY0ZkuOGQCA1TFpdr0KqYp60D/k1/tyfy0HASLi2urZt52BIhtL6rMlxwwAwGrw0GwyoIo67extvuohgIi45mYGynysaMyYHDcAAHvLPSfbn+g7e1CFU0mb3e2rDH9ExI1xloU6J4sZMyZmTY4dAIC9wz9p/18VTFWddvZ6X3XwIyJuiJmFMicrGrMmxw4AwN4w7uxvqUAq7K2uDH1ExA00MlFlZUlj5uT4AQBYPh48g/oDyCfNzvJVhT0i4uY5y0SdlzW9JMcPAMBy6Zv9oAihyl7r6rBHRNxcIxtVZpY0Zk+OIQCA5eGBc/N8ABX2/kmzl/mqQh4RcXOdZeP9rsrOit6cYwgAYDl4ML5QhE9dm13hqw55RMRNd5aROj8r6jMoxxEAwGIZd/an+2aPyPApaN/Znb7qcEdExG0zK2WOVjNmUMyiHEsAAIvDQ+aU+dCp7LTZ63yVwY6IiDMzK2WOFvWUHEsAAIth0uwZImwqG7+PWIY6IiIe4ZD+24v4LQzPyPEEAHDieLBcfkTQFLVv9qm+szP8tQpzREScMzIzstNfy1wt6OU5ngAATozJyH5YhExZ+y272lcZ5oiIqM3slLlaUp9NOaYAAHbPpNltMmQq2uyQrzLEERHxGM4yVOdrNX025ZgCANgdHiYHjgiX2r7Z1QGOiIjHMjJUZWtVD+S4AgDYGffsty/rO3tcBEtJ+y37mK8quBER8TjNLJU5W82YUTGrcmwBABw/fbPTVbBU1QPvAl9lcCMi4vGZWSpztqIxq3JsAQAcHwebfYcKlLI2u9FXGdqIiLhDZ5mq87agMbNyfAEAHBv/RP92FSYV9Wt9bNrsVf5aBzYiIu7IyNTIVn8tc7eaMbNyfAEAPDV9s3+vgqSq087e46sMa0RE3J2ZrTJ3KxqzK8cYAIDmgwfs903agP5DhGYTX2VIIyLiiZkZK/O3nD67YoblOAMAOJJ+y35OBkhVm73JVxnQiIh4gs4yVudvQWOG5TgDAHgyB5t9tQqOqvbNPuqrDmdERFyImbUyhysasyzHGgDAZ/CAOHM+MIp7niuDGRERF2Zkrcrgqp6ZYw0AYEa/Zf9AhEVlr3dVICMi4uKNzFVZXNKYaTneAADMJs2uVGFR0b7ZI323/ZdZqDBGRMQFG5kb2euvZS6X02dajjcA2HQ8wH5CBkVRp52921cZxoiIuBwze2UuVzRmW445ANhUHt9nT/NPvveokKho32zsqwxhRERcrpnBMp/L6bMtZlyOOwDYRDwMXnxEONT2MlcGMCIiLt3IYJXNVX1xjjsA2DT6ffa1IhTKOm52u68qeBERcY/MLJY5XdGYdTn2AGCTmDQ7R4VCYc91ZfAiIuKeGVmsMrqmPuty7AHApjAZ2TNlIBS17+z9vqrARUTEPTYzWeZ1SX3m5fgDgE3AD/41RwRBUT1QP9k3O81fy8BFRMS9NTI5stlfy9wu6DU5/gBg3Rk3e74IgbKOO3unrzJsERFxNWY2y9yuaMy+HIMAsK4c2m9f6J/EJyoEKurXep+vMmQREXG1ZkbL/K5mzL6YgTkOAWAd6bfsV1UAlLXZJb7KgEVExBU7y2id3wWNGZjjEADWjfuafYM6+FUdN7vNVx2uiIhYwsxqmeMVjVmYYxEA1om+swvVoa/qdGSv8VUGKyIi1jCzWuZ4RWMW5lgEgHVhvGX/TB34qnoQXeerDFVERKxlZrbM84rGTMzxCADrQN/sA+qwl7TZQ4dG9nJ/LQMVERFruZ3Znt3+Wud6MWMm5ngEgKHjn7S31EGvql/v232VYYqIiDXN7Ja5XtGYjTkmAWCoPLDP/rh/yn5AHfKi3u3KEEVExPJGhqtsr6fPxpiROS4BYIj4J9b/Iw94UcedXeyrCk9ERCxuZrjM94rGjMxxCQBDY7zf/qY62GUd2a2+yvBERMSBOMtynfMFjVmZYxMAhsSk2RvUoa7qdGRn+aqDExERB2Fmucz5kvqszLEJAEOh7+xfyANdVL/ea32VoYmIiMMyM13mfUVjZub4BIAh4Af3pvmDXFUPmAf8E/XL/LUMTEREHJie6dvZLjK/qDfl+ASA6viBPXnuAJfWw/CtvuqwRETEQZrZLnO/qCfnGAWAqjz0QvsSP6wPzx3eyt7pypBERMTBGxmvsr+iD8cMzXEKABXJ3wKgDnBJx1t2ka8qHBERceBmxsv8L6nP0BynAFCN+5o9Qx7covad3eyrDEdERFwPM+vlHKhozNIcqwBQCQ+Ty9Whrahf6+PTZmf4axmMiIi4HkbWR+b7azkPqhmzNMcqAFRhvGU/rA5sVT1IrvZVhiIiIq6XmflyHlQ0ZmqOVwCoQN/sNnVYK+rXethXGYaIiLieZvbLuVDNmKk5XgFg1Yw7O6AOamHf7MogRETEtTWyX82EksZszTELAKtius/+vH/yHMzvfZo0+5ivKgAREXHdnc0APR+KGbM1ZmyOWwBYBX4QX6kOaFX7zi7wVQcgIiKutTkD5HyoaMzYHLcAsNdMR/bt6mCWtdmNvsrwQ0TEDXE2C/ScKGjM2hy7ALCX+CfNt6lDWdTH/JP8q3zVwYeIiBthzoLHXDUryhmzNscuAOwV487+nTqQVfWguMpXGXqIiLhZ5kyQ86KiMXNz/ALAsnniWfZ7/eDdMX8QCztxZdghIuLGGrNBzYyK3hGzN8cwACwT/yT838QhrOybXBVyiIi4ucZsUDOjpDF7cwwDwLI4vN++Sh3AqnowfNRXFXCIiLjh5oyQ86OiMYNzHAPAMvBQOEMdvqr69Z7nqww4RETcbHNGyPlR0ZjBOY4BYNEc6uw71cEra7MP+irDDRERcdvZrNBzpKAxi3MsA8Ai8QP27vkDV9hH/JPv6b7qYENERHRzVjziqllS0XfnWAaAReFB8Gxx2Mrq13ulrzLUEBERP9ucGXKeVDRmco5nADhR7t5nT/ODdff8QauqB8DYVxlmiIiIypwdcq4U9O6YzTmmAeBEmIzsReKQ1bXZZb7KIENERJTOZoeeKxX12ZxjGgB2S7/PvlYesKL6J/LbfdUhhoiI+BTmDJHzpaIxo3NcA8Bu8EN/jjpcVe07O9dXGWCIiIhPZc4QOV8qGjM6xzUA7JTJPnumOlhVHW/ZB3yV4YWIiHg85iyRc6akPqtzbAPATvBPitfIQ1XRZp/0T+Kn+WsZXIiIiMfj9izxmeKv9bwpZszqHNsAcLyMO/sP6kAV9p2uDC1ERMQdGjNFzZqSxszO8Q0Ax2L6fPvD/om2V4epov5p9j5fVVAhIiLuypwtcu5UM2Z2zO4c4wDwVPjh/h/qIBX2ElcGFSIi4i6N2aJmTkljducYB4CjMR3ZX1UHqKp+sG/zVQUUIiLiCZkzRs6fisYMz3EOAAo/1BfMH5zK+vX+hq8yoBAREU/EnDFy/lQ0ZniOcwCYZ9rZP1UHp7DXuTKcEBERF2TMGjWDShqzPMc6AHw2fWfvV4emqA/1W3aqryqUEBERF2LOmodcNYvKGbM8xzoAfJq+2T51YKrqB/ntvspQQkREXKQ5c+Q8qmjM9BzvAHD/yfbH/GDcP39QytrsHl9lGCEiIi7F2ezRc6me98dszzEPsNn4J9X/LQ5JZS92dRAhIiIux5g9aiaVNGZ7jnmAzeVQZ9+oDkhV+2Yf8lUFECIi4lLNGSTnU0Vjxue4B9hM/CAM6hPquLOzfZUBhIiIuExzBsn5VNSLc9wDbB6Hmv2AOBR1Hdm1vsrwQURE3BNns0jPqYLGrM+xD7BZTJrdqA5FSZs94J+kT/HXOngQERH3wO1Z5DPJX+t5VU2f9Tn2ATYHP6gnywNR1L6zt/oqQwcREXEvzZkk51VFY+bn+AdYf8YvsC/pmz2sDkNFPVDu8lWGDSIi4irM2STnVjVj5sfszxoAsN6Mm71MHYSqephc5KsMGkRExFWYs0nOrYrG7M8aALC+TEb2LeoAVNU/hd7iqwwZRETEVZozSs6vknoHyDoAsJ74oXyT3PwF9U/Lj087O8Nfy4BBRERcpTGjYlb5aznHqhkdIOsAwPoxafav1cYv7NWuDBdERMQixqxSM6ym3gWyFgCsF/6p87fkpq/pYVcFCiIiYjVjZqlZVs7oAlkLANYH/wT3n9SGr6ofxLf4qsIEERGxlDmz5DwrqXeCrAcAw2c6sj/XN/uU3OwFnTb7mK8yTBARESuas0vOtWpGJ4hukDUBYNj4J83T1Eavql/vhb7KIEFERKxozi451yoa3SBrAsBw8U+Yf0dt8LLO/lpiGSKIiIilHdJfre9GR8i6ADBM/BPbYP6awr7Zb/v1vspf6wBBREQsbMywmGX+Ws65akZHyLoAMDz8k9q/VRu7rCO7ylcZHoiIiINwNsv0nCtodIWsDQDD4YkD9jn+qfKjalNX1K916qsODURExAGZM03Ou2pGV4jOkPUBYBhMO/tZtaGr2nd2ua8yMBAREYdkzjQ57yoanSHrA0B9Djf7SrWRq+qBEP/mWYYFIiLiEM3ZJudeRaM7ZI0AqI0frlerTVxVv97zfZVBgYiIOERztsm5V9HoDlkjAOriG/U71QYua7MP+ipDAhERcdDOZpyefwWNDpF1AqAmfqjepTZvRf1APdo3O91f64BAREQcsDHjYtb5azkHy+kdIusEQD38QD1bbtyqNrvSVxkOiIiIa+Fs1uk5WNDoElkrAOpw57Ps8/xT491q01bUr7X3VYcCIiLiGpkzT87DakaXiE6R9QKgBv6J8UVqw1Z12tllvspAQEREXCdz5sl5WFLvFFkvAFaPf/r6S3KjVrXZ7b7KMEBERFxLZ7NPz8WCRrfImgGwWnwz/obapIU919VBgIiIuJ7G7FMzsaTRLbJmAKwO/4T4j9UGrWrf7AO+qgBARERca3MGyvlYUu8YWTcAVoN/4rpabs6CTpt90tfTXBkAiIiIa+5pOQvlnKxmdIysGwB7z2TLnqc2Zllnf8avOviIiIib4YD+vPttvWtk7QDYOyYj+0N9s7HclBVtdp+v+tAjIiJukrOZqOdlMbe7hneOrB8Ae4Nvvl+Z34zFvcTVBx4REXGzjJmoZmVVfyXrB8DymW7ZXxGbsLK3ueqgIyIibqoxG9XMLGl0j6whAMul7+x8tQkLG3/8mTrkiIiIm+qg/mjQ6B5ZQwCWx3Rk36s2YFX7Zr/pqzrgiIiIG23OSDk/KxodJOsIwHIY2KF4qN+yU32VBxwREXGTzRn5kKtmaDmjg2QdAVg8085OUhuvqn4g3uGrPNyIiIi4/W91Y1bKOVrR6CJZSwAWx/0n2Rf5Bjs8v+EKe48rDzUiIiI+yZiZapZW9HB0kqwnAIth2uzXxGar7MWuOsyIiIj4ZGNmqlla0ugkWU8ATpxxZ9+oNlpV+2Yf8lUdZERERBTm7JRztaLRTbKmAJwYvqEG9UnPPduVBxkRERGlMTvVTK3qxVlTAHaPf8L7AbG5yurX+z5f1QFGRETEpzBnqJyvFY2OknUFYHf4JrpRba6SNnvA11NceYARERHxKT0lZ6mes8WMjpJ1BWDnTLZsv9pYVZ2O7K2+qoOLiIiIx2HOUjlnS+pdJWsLwPFzsNmf8k9Kn5SbqqZ3ufLQIiIi4o6MmapmbTmjq0RnyfoCcHz45omNLjdVRaedXeTr/EFFRETEHZozVc7bor406wvAsem37JvFJqrsLa48rIiIiLgrY7aqmVvS6C5ZYwCemkmzN6pNVNTH3TNddUgRERFxd8ZsjRmrZm89vbtkjQE4OpOR/Su5gep6tasOKCIiIp6YMWPV7K2pd5isMwCafkB/M8q0s8O+qoOJiIiICzBnrZzD1YwOk3UG4Eh8k/zM/KYp7ltceTARERFxIcasVTO4qj+TtQbgM0z22Zf2nf222DBV/birDiQiIiIu1pi5ahaXc7vLeKfJegMwY9LsFWrDVNU38oW+qsOIiIiICzRnrpzHJfVOk/UGwGw6sm+TG6WqzW7yVR5GREREXIKz2avnckGj22TNgU3HN8QV8xukqvF/SfRb9mp/rQ8iIiIiLtyYvQP7LY5XZM2BTWba2Y+KzVHXZlf5Kg8hIiIiLtHZDNbzuaDRcbLuwCZyxQH7HP909hG1OSraN5v6qg8fIiIiLt2cxXJOVzM6TnSdrD2wafRb9rNqYxT2clcePERERNwTYxarGV3S6DpZe2CTuK/ZV6oNUdZmd/iqDhwiIiLupbOZrOd1QaPzZP2BTaHvtv+DLrkhinq+qw8cIiIi7qUxk9WsLml0nqw/sAmMt+zvq41QVd+gN/iqDhoiIiKuwJzNcm5XNLpP1iBYdybN3qU2QUX7Zo9OOzvdX8uDhoiIiHtvzOaY0f5azu9yevfJGgTrjH8C+3G5AYo6bXalr/KQISIi4urMGS3nd0WjA2UdgnXkjhfYH/BPX3eph19R35C9r/JwISIi4urNWS3neDWjA0UXyloE64Y/5F+Yf+ilbfZGX+XBQkRExALOZrWe4zX9haxFsE6M99lfFA+7sre7+lAhIiJiJWNmq1le0uhEWY9gXfBPXK9RD7uszV7rqzpMiIiIWMnZzNbzvKLeibIewTrQd/aP5IMu6rTZB3zVhwkRERHLmbNbzvWKRjfKmgRDxx/oe+cfcFV94z3s62muPEiIiIhY0tNyhsv5XtD3Zk2CIeMP8ifnHmxtZ3/GrzpAiIiIWNkB/Tn96U9mXYIhMj5gX+AP8eDcQy1r37avVR8eRERELG/OcjnnC3owulLWJhga/snql8VDrevILvVVHhxEREQcgLNZrud8Rb0rZW2CIeEb7evlAy2qfwK8zVd9aBAREXEw5kyX876k3pmyPsFQ8Ad33hEPsrB+KM7xVR4YREREHI450+W8L+p5WZ9gCIy37HvFQyzrtLPf9FUeFkRERByeOdvl3K9odKesUVAdf2DXzT/Aqvqnvk/4eqorDwoiIiIO0lNzxsv5X9DrskZBZfrOThIPr6x+CN7hqzogiIiIOGBzxsv5X9HoUFmnoCJ3nmRfNGl2WD28io47u9dXeTgQERFx+Oaslz2gnN6hoktlrYJq+CenX5MPrqjTzi72VR4MREREHL4562UPqGh0qaxVUImD++xvqAdW1b6zD/kqDwUiIiKujznzZR+oaHSqrFdQBf8E8nr1sKrqn/DO9lUeCERERFwfc+bLPlDR6FRZr6AC/knpn6sHVdZm7/NVHgZERERcQ2ezX/eCgka3ypoFq8Y3zw3qIRX1AfcUVx8EREREXEdj9kcHUN2gnt6tsmbBKumbjeQDKqpf79t8VQcAERER19jsALIfVDQ6VtYtWAX3vdD+pD+I4fxhzM3u8lVufkRERNwAZ11A94R6fiK6VtYu2Gt8s/w/8VDKOh3ZRb7qjY+IiIhrb3YB2RNK6l0raxfsJX1n3yQfSFH7Zrf4Kjc9IiIibo7ZCWRfqGh0rqxfsFf4jb9s/kEU90xXbnhERETcKKMTqK5Q1cuyfsFeMGn2Q+IhlNU/CV3jq9roiIiIuIFmN5C9oaTevbKGwbLxG37rEQ+gqs0O+yo3OSIiIm6ws46g+0M9b80aBstkMrKfFje/rH2zK3zVGxwRERE31uwIsj+U1DtY1jFYBnftsy/1Tz+PyZtf04+7cnMjIiIiutEVVIeop3ew6GJZy2DR+CefV8gbX9RpZxf6qjY1IiIi4kuzK8geUdHoYlnLYJEc3Gffpm54VfvObvJVbmpERETET5udQfaJikYny3oGi2JIv49l3OxT/gnt1f5abmhERETETxudIbqDv5a9oprRybKewSIYd/aj6kZX1TfAe32VmxkRERFx3uwOsldUNLpZ1jQ4EZ74fvs9/vA/om5yRfvOpr7KTYyIiIh4NLNDyH5Rzehm0dGyrsFu8Rv5X9UNLuzlrtzAiIiIiE9hdAjVLUoaHS3rGuyGe/fbV6gbW9Zmd/iqNi4iIiLisZ11Cd0zChpdLWsb7BT/pPAqdVPLOrLzfdUbFxEREfFYzrqE7hkFja6WtQ12wrizv6duaFX7zm7wVW9aRERExOM0O4XsGxWNzpb1DY4Xv3HvnL+RhX102tmv+yo3LCIiIuLxmp3iUVd1joq+M+sbHA99s2eJm1jXkV3pq9ysiIiIiDt21i107yhodLescfBUPHHAfr/fsDvnb2BV+856X/UmRURERNyl2TFk/yjondHhss7B0fCH+t/FzSurf4J5o69ygyIiIiLu1uwYsn9UNDpc1jlQ3N/Z16gbV1V/oPEXWcjNiYiIiHiiZteQPaSi0eWy1sE8foPOnr9hpW32Wl/lxkREREQ8YWddQ/eQmp6dtQ4+m77Zd4mbVdZxZ9f7qjclIiIi4oLMziH7SEWj02W9g0/jn1iuUjerqA/7Q3ylr3JDIiIiIi7K7BwPu6qT1NM7XdY7CCYje668UVVt9i5f5WZEREREXLiz7qF7SUW922XN22zGz7Mv8Id3n7xJBe07O+ir3oSIiIiISzI7iOwn5fRuFx0v697mMm72y/IGFdWv91Jf5QZEREREXJbZQWQ/qWh0vKx7m8lkZF+vbkxV+2Yf9lVuPkRERMRlm11E9pSSetfL2rd5+MM6T96UovYjO8dXufEQERERl212EdlTKhpdL2vfZnGw2feoG1LVcbP3+yo3HSIiIuJemZ1E9pWKRufL+rc59J1dp25GRf1aP3Gos1P9tdxwiIiIiHtldJLoJv5a9pZqRufL+rcZ+CeRF6gbUVV/QO/wVW42RERExL02u4nsLRWN7pc1cL05vN/+6KTZIXUTKuob6V5f5SZDREREXJXZUWR/Kad3v+iAWQfXl77Z/5I3oKrN3uCr3GCIiIiIK3PWUXR/KWh0wKyD68mhZn9dvfHCfsjVmwsRERFx9UZXUR2mpNEFsxauH31nF6k3XdVxs9f4qjYVIiIi4srNriJ7TEWjC2YtXC/6Zt+v3nBV/UG8z1e5qRARERGrmJ1F9pmKRifMerg+TJp9UL3Zoj7onuLKDYWIiIhYyOgs0V1Up6mnd8Ksh+uBf9Lo5Bstqn/SeJuvaiMhIiIiljO7i+w1FY1umDVx2Dy4ZV/szf0h9SYr6jf+bl/lJkJERESsanYY2W/K6d0wOmLWxeHib+YlR7y5wo6bvd5XuYEQERERq5odRvabor4k6+IwObzfni7eVF2b3eKr3DyIiIiI5Z11Gd1zChpdMWvj8PCbfal6U1Udj+wsX/XGQURERCxudhnZc0rqXTFr47A42OyH5Bsqat/sGl/lpkFEREQcitlpZN+paHTGrI/Doe/sVvVminq/KzcLIiIi4gCNbqM6TzmjM2Z9HAbjZj+t3khV/QZf4avaJIiIiIiDM7uN7D0Vje6YNbI2k5H92b7ZY+pNVLTfsjt9lZsEERERcahmx5H9p5rb3dE7ZNbJuvgniFPVG6jqtLMLfZUbBBEREXGoZseR/aei0SGzTtZk0uxb1YUX9iZXbg5ERETENTC6jupANfUumbWyHt7E3yIvuqD9ln3Kr/fV/lptCkRERMTBG10nOo+/ln2omtEls1bWYrpl/0ZdcGHf68pNgYiIiLhGRudRXaik0SmzXtbgiQP2u/tmt6uLLerUVRsBERERcR2N7qM6UTmjU0a3zJq5evrO/ou60Kr6DXyzr2oTICIiIq6d2X1kL6podMusmavl0JZ9ubrAwt7hyk2AiIiIuMZGB1LdqKTRMbNurg5v3L+uLq6w57vq4SMiIiKus9GBVDcqaXTMrJur4dB++7vqwsra7AZf1YNHREREXH9nXUj3pIJG18zauff0zd6hLqqifq2P9aPtf/usHzwiIiLimhtdKDqRv5Z9qZrRNbN27i3Tzn5MXVBV/Ua9x1f50BERERE3xexEsi9VNDpn1s+94fHn2ef6N/74/IUUtnflw0ZERETcQKMbqc5U0Y9H98waunz8k8DPi4soa9/Zm3xVDxkRERFx48xuJHtTRaN7Zg1dLuPOvkZdQFX9xnzEV/mQERERETfV7EiyP1U0OmjW0eUxGdlZ6ptX1R/ia32VDxgRERFxU82OJPtTSb2DZh1dDn5Dvkt+47pe78qHi4iIiIjbXUl1qJJGF81aunj8i1+lvmlF+y17xK/3lf5aPVRERETEjTe6UnQmfy37VDWji2YtXSyTLXuu+oZVHXf2bl/lQ0VERETEmdmZZJ8qqXfSrKeL4WCzP+gN+j75zQrad3bQV/kwEREREfHJZneSvaqa0Umjm2ZNPXG86f+S+kZlbXapr/JBIiIiIuKcs+6ke1VBo5tmTT0xJlv2l9U3KOyHXf0QEREREfFoRodS3aqm3lGzru6efmh/9ESzc3xVDw8RERERj+asQ+l+VdDoqFlXd8dkZP9EfWFERERExJXrXTVr687xpvw++UUREREREVdsdNWsrTtj2tl/VF8QEREREbGK0Vmzvh4fh15gf6TvbKq+GCIiIiJiFaOzRnfNGnts+mb/U30hRERERMRqRnfNGvvUHNpvf019AURERETEqkaHzTp7dLwRv079YkRERETEqkaHzTqrmXb2feoXIiIiIiJWN7ps1toj8Z9w/fwvQEREREQciNdnrX0y02ZN/GRERERExMEYnTbr7WfwH7h5/iciIiIiIg7Mm7PezpiM7JniJyEiIiIiDk/vtllzt/+khfPkT0JEREREHJjRbbdL7qEt+3L1ExARERERh2p03PhtC89VP4iIiIiIOFi948Z/hPZLR/wAIiIiIuKAHXvHjd+f+1r1g4iIiIiIA/Zc6zu7VvwAIiIiIuJgjY4b/0Z3on4QEREREXGoRseNf6M7VT+IiIiIiDhUo+PGv9F9n/pBRERERMShGh2X/xgNEREREdfRc23S7BfFDyAiIiIiDlfvuFF0nyN/EBERERFxqHrHtUP77SvkDyIiIiIiDtTouBb4/zhv/gcREREREYdo39n52yU3mOyzZ6qfhIiIiIg4OEf2zKy5M/pmN8mfiIiIiIg4EKPTZr39DNPOttRPRkREREQcitFps94+Gf/BM+d/MiIiIiLiQDwza+2R3L3PnjZp9kHxixARERERy9o3uyG6bNZaTb9lT1e/GBERERGxqtFhs84+NYc6+3H1BRARERERqxndNWvs8TEZ2bdMmt2ovhgiIiIi4sr1rtpv2Tdnfd0Z9z7HPt+/wFnyCyMiIiIirsixd9Toqllbd0/fWedf8Ob5b4CIiIiIuMfeHN00a+rimDT77r7ZBXPfDBERERFxqW53UO+iWUuXx+H99lX+zZ7t3/TF/g3P8VZ9rf/vyfwFISIiIiLuxOiU0S2jY469a0bnPNjsq7OG7gCz/w/rFSSiaAwoOQAAAABJRU5ErkJggg==\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEc4SURBVHhe7d0LvKVXedfxUavVUluBzF7vCQja0tZqFa1apVCtVq1WqW2tVq1Sq9bSUkUrVNFqW1tR2lJbq2IJIYRcIZALIZArM3u9eyYJuZGEJCQ0CbnM7LX35AoEEkIS1/POE5Ps85/JOWfOPvt59/79Pp/vh36YZOac/b7rWc+kJNlFRETb372j47+pDJvXl7Z5W2nTWSWnayY5PWDs/7b/bmo/Vv8Y+2P9TyMiIiIiilkZDb63LrPnTtrmqU2pf479uf7TEBERERHFaDJKb67L6i1yid0M+znqz+U/LRERERHRYprs2f3VdUE9Y93CeuzOsJ/bfxkiIiIiop1rktdePWnTzWJJ3Sb15867X+2/HBERERHR/Jvk5if0cjoH9dfyX5aIiIiIaH5Nhru/XS6k81R/Tf/liYiIiIi2vwNXr31VadNNchmdI/s17df2L4OIiIiIaHub5OY0tYjuiPpr+5dBRERERLR9df8IMbWA7iT+0WNEREREtJ1N9uxu6qL5+XWL5877vH0t/mURERERER1bk5zeIZbOxahfi39ZRERERERbr+wdvEounAtkX5N/eUREREREW6vkdKFaNhfJvib/8oiIiIiINl9pB/9QLZoR2NfmXyYRERER0eYqbbpVLZkR2NfmXyYRERER0cYrufmPasGMxL5G/3KJiIiIiJ6/e4fH/8GS05fUchmJfY32tfqXTURERER09Ca5eZdaLEOqX6t/2URERERER246bP6CXCgDs6/Zv3wiIiIiIl1dHC+bXSR74DL/8omIiIiI1lcXxh+ZWSD75Ef82yAiIiIieqanntr1O+qyeMfM8tgnd9j34N8OEREREdHhJm36ebE89kz6ef92iIiIiIi6fwPa1+nFsX/se/Fvi4iIiIhWvZLTyWpp7CP7XvzbIiIiIqJV7tC+wXephbHP7Hvyb4+IiIiIVrVJm7JaFvstZf/2iIiIiGgVK3nwY3pR7D/73vzbJCIiIqJV6raPvOIrJ226Ry2JR1LEfxdXuse+R/92iYiIiGhVKrl5q14Qj6xfi679Vd3mrf7tEhEREdEqdGDP2h9Ri+FG9G3Zte/Vv20iIiIiWvbKsDlDLYXLyL5X/7aJiIiIaJmbts3fUAvhZtSfQ/73Udn37N8+ERERES1rdfG7YnYR3CxbdKftmvyxoK7wb5+IiIiIlrFJbn5SLIFb0re/qmvfu38MRERERLRMTfbs/uq67E3kErhFvVp27Xuvn4F/HERERES0LJWcfkUugMdiJP67wOwz8I+DiIiIiJahsnfwx9Xit4rss/CPhYiIiIj6XmnTB9TSt4rss/CPhYiIiIj6XBkNvlctfKvMPhP/eIiIiIior5U2XaOWvVVmn4l/PERERETUx6bt4I1q0YP9EyMGb/SPiYiIiIj61EPty144yekBteShqp+NfUb+cRERERFRX5rk5tflgjdHJev/Pqz6GfnHRURERER9aLp/7VvlYrcDivjvIrPPyj82IiIiIopeXeDOm13ocETn+cdGRERERJE7mJsfFMscjsI+M//4iIiIiChqJTc3qmVuJ027fzVwWvffR2WfmX98RERERBSxyTC9WS1yi3B42e2R+tn5x0hEREREkSqXDtIkN5+XSxyeX/3s7DP0j5OIiIiIolTa9H/kAocNs8/QP04iIiIiilBpB39eLW7YPPss/WMlIiIiokVX2vRRtbRh8+yz9I+ViIiIiBZZyYN/oBY2bJ19pv7xEhEREdGiKjl9Si1r2Dr7TP3jJSIiIqJFNM2D/6AWNRw7+2z9YyYiIiKiney+K17y0klOj6klLaTcHOioH4uofrb2GfvHTUREREQ7VV3GTli3nEWWmw911I/FdYJ/3ERERES0E01Ha98hlrKwuv8dcU6/Zfr2vym2z9o/diIiIiKad3UBu3R2IYuqtM0TdcE97elF1/7v7r8Tf2xQl/rHTkRERETzrC5er5tZxEIrOV31rCX36b+qe5X6YwN7nX/8RERERDSvJrm5XSxiIZU2PTS75D6t+zHx54RUP3P/+ImIiIhoHpXc/JxcxKLKzWVqyT2s/pj6c4Kyz94fAxERERFtZ6UdfF1pmyfVEhZRyekeveA+o/tjxJ8bkX329gz8cRARERHRdlWXwpPVAhZWTufOLrbCufLPDcqegT8OIiIiItqOSh58l1q8wsrp5pmF9mhulj9HUPYs/LEQERER0bFWcspq6YqotOnxSZtOEQutVv/Yw3+O/vmisWfhj4WIiIiIjqUyHPxztXCFNWqukAvt0difo36uoOyZ+OMhIiIioq30yffv+j29+hu2hukBuchuQPfnip8zInsm9mz8MRERERHRZhu36b+qRSusnC6ZXWA34RL5cwZlz8YfExERERFtpkOj479JLVhh5XTXzOK6FXfJnzsoe0b+uIiIiIhoo9VF6vTZxSq0nM6eWVq34mz5c8d1uj8uIiIiItpIk9z8dbFUhTVtmxvF0rol3c8lfo2w6rPyx0ZEREREz1ddni6XS1VMj9m/SEEtrVvR/Vz155z5NeKqz8ofGxEREREdrbo4/YRcqKLKzX61sB6b+nOqXyuq+sz88RERERGRavyJ9IK6NBW5TAVUcrpPL6rHrvu5xa8ZUn1m9uz8MRIRERHRbKVtflkuUkHVZfQitaRuh+7nFr9mVPbs/DESERER0bO7f1/6FrVARVXy4E61oG6n7tcQv3ZU9gz9cRIRERHR003bdJZanqKqS+gH1HK6nbpfQ/zaUdkz9MdJRERERNahNr1WLU5R1YXuerWYzkP3a4mvISp7lv5YiYiIiGjSpqvV0hRT+uLBPDhJLaXz0P1a9dfUX0tE6Wp/rERERESrXWkHb9QLU0xlmEZqIZ2n7tcUX0tU9kz98RIRERGtZne1L3thyekBtSxFVBfOqVpEd0L3a4uvKSJ7pvZs/TETERERrV7j3Py6WpSiKm36qFpCd0L3a4uvKSp7tv6YiYiIiFarA8O1b1ULUlTjYXO7WkB3Uvc1iK8tKnvG/riJiIiIVqdxbs5Ty1FYo+Z9avncUfY1qK8tKHvG/riJiIiIVqPJsPk7ajGKato218nFcwG6r0V8jWHVZ+2PnYiIiGj5m+TmBrkURZTTI/Xrfdfswrk43dfyiPxaI6rP2h87ERER0XJXl583rVuGAis55fXL5mJ1X5P4WgN7kz9+IiIiouVsvC8NStt8TixCIZU2jdWiGUH3tYmvOSJ75vbs/TUgIiIiWr7qcva/1SIUVcmDC9SSGUH3tYmvOSp79v4aEBERES1X45z+nFqA4kq3qQUzFPsa5dcek70D/joQERERLU8lp4+o5SeuwRlyuYzEvkb5tcdk74C/DkRERETL0TSnv68Wn7ByumbdUhnXNfJ7CMreBX8tiIiIiPrfpE23qKUnopLtb5ZL7xQLZUz1az38NevvJ550i78WRERERP2uLjZv0QtPUMO0Vy6UkdnXrL6XsNJb/PUgIiIi6mf37X/pS+pS86heduIpuTkgF8ke6L528T3FlB61d8NfEyIiIqL+VZead65fcuIq7eB8tUT2Qfe1i+8psHf6a0JERETUrw7sXfsOsdyEVdr0KbVA9kn3PYjvLSp7R/x1ISIiIupP42FzqVpuIiq5ebIuiqfNLo49dFr3vYjvMSJ7R/x1ISIiIupHdYl53exSE1nJ6SqxNPZS972I7zGw1/lrQ0RERBS/SW5uFwtNSCU3D6uFsc+670l8ryHVd8VfGyIiIqLY1SXr5+RCE9S0bS5Ty2Kfdd+T+F6jsnfGXx8iIiKimI2H6Q/36X8jOmnTPWpRXAr2vcnvOR57Z+zd8deIiIiIKF4lp/eoRSaudK5cEpeBfW/ye47J3h1/jYiIiIhiNR6mv6wWmLjSzXJBXCb2PcrvPSZ7h/x1IiIiIopTyWmolpeY0uPVKXI5XCb2PXbfq/oM4rF3yF8nIiIiohiN2/TP1OISVh5cKRfDpVS/V/UZBGXvkr9WRERERIvtqat3/e7SprvV0hJSTg+sXwaX3gPyswjI3iV7p/z1IiIiIlpckzb9klpYopqO0iViEVxq3fcsPou40i/560VERES0mKb5+G/Ui0pQOd01uwSukLvkZxKUvVv+mhERERHtfJPcnKaWlLByOntm+VslZ8vPJKr6bvlrRkRERLSzTfatfbdcUIIqufmkWP5WSvcZiM8mrPqO+etGREREtHPVRWT/usUkqtw8VnI6WS1/q+TwZ9A8Jj+jmPb760ZERES0M5VR83qxlIQ1zs3lavFbRd1nIT6jqOxd89eOiIiIaL6NL0ovKG0zVktJUPephW+l2WeiP6tw7F2zd85fPyIiIqL5NW2bt6mFJKr69V4kl70V1n0m4rOKyt45f/2IiIiI5tN4T/oWtYjENbhTLXqo7LORn1lM9u75a0hERES0/ZVhOkstIVGVPPiAXPLwW91nIz6zqOzd89eQiIiIaHsbt+m1agGJapzTDWrBwzO6z0h8dlHZO+ivIxEREdH2Vdp0tVo+Iqpf6xdLOzhJLXd4hn1G9lmpzzAiewf9dSQiIiLansY5/Su1eEQ1bdNILXZYr/usxGcYlb2L/loSERERHVsP7vnaP1Byul8tHTGlqVrocBT2mcnPMh57F+2d9NeTiIiIaOvVReh/qIUjqukofXTdIoej6j4z8VmGVd9Jfz2JiIiIttZ07/F/Si4aUQ2b22eXOGyQfXbqMw3K3k1/TYmIiIg2X10ozp1dMCIrbfN+ucTheXWfnfhMAzvXX1MiIiKizVUXiR+YWSxCq4vadWqBw8Z1n6H4bAP7AX9diYiIiDZeXSKun1kq4srpkZKbE2cXN2yOf4aPyM84puv9dSUiIiLaWKVt/q1YKsIqbcqzSxu2pvssxWcclb2r/toSERERHb2DudldcvNZtVQEVdTChmNgn6n+rMOxd9XeWX99iYiIiI5cXRz+l1oowsrpgnWLGo7VBfKzDsreWX99iYiIiHT37U/fphaJqEpOnxZLGrZB99mKzzwqe3f9NSYiIiJa36Tt11/Jm+TBmWpJw3aon636zMNKF/hrTERERPTcpqP0Q3qBiCpdoxc0bBv7jOVnH5O9w/46ExERET1TXWpuVstDROO2+dw4pxPkcoZtY5+xfdbqGcSUbvbXmYiIiOhw42F6i14cYipt2qsWM2y/7rMWzyAqe5f9tSYiIqJV7+5LX/SSktOjammIqC5eB9VChvnpPnPxLCKyd9neaX+9iYiIaJUbD9M71cIQ1+B8tYxhjuwzl88iJnun/fUmIiKiVW3Srr1GLQpRlWG6VS5imLvusxfPJK611/hrTkRERKvYJDeX6CUhnpKbJ6ejdJpawjB/9tnbM1DPJqT6bvtrTkRERKtWXQT+sVwQwkpXqQUMO8iegXw2QdV33F93IiIiWqVKbn5bLgcxPSwXL+w8exb6GYVj77i/7kRERLQq1QXgP6vFIKrSNh+TSxd2XPcsxDOKyt51f+2JiIho2Rtfnv5QvfyfUEtBTOketXBhgeyZyGcVj73r9s77609ERETLXGmbk9RCEFZuzpPLFhaoPhP1rIKyd95ffyIiIlrWDo3SX1KLQFzpZr1oYeF69K+MNvbu+zEgIiKiZaxP/zrX+rV+edqmU+SShYWzZ2PPSD27iOzd92NAREREy1ZdTP6pWgDiGlypFiwEYs9IPruY7Az4cSAiIqJl6ak9u76iLiZ3qcs/pvTguqUKMdmzks8woHoG7Cz4sSAiIqJlqF7wvygv/qDGw3Tpc5YphNU9K/EMw6pnwY8FERER9b3p5cd9g7zwo7K/8iwWKoTWo/9vQfOUnQk/HkRERNTnJm06VV32UY2H6RyxSCGw7pmJZxlXOtWPBxEREfW1A8O179YXfVC5+aRapNAH9dmpZxqUnQ0/JkRERNTHStvsU5d8RCU3Xyo5nayXKERnz86eoXq2EdnZ8GNCREREfasMm9erCz6s3FyuFij0SX2G6tkGZWfEjwsRERH1pQMfWvuqkpuxutwjql/r/XpxQt90z1I844jsjNhZ8WNDREREfai0zdvUxR7VtG0uUksT+qd7luIZR2VnxY8NERERRW/cpj+mLvS4BneqhQk9Zs9UPuuY7Mz48SEiIqLIlbZ5v7rMo5q26QNyWUJvdc9UPOuo7Mz48SEiIqKojXP6W+oijyvdoBYlLAF7tvKZx2Rnx48RERERRazkdJW6xEMapS9O28FJcklC73XPtj5j+ewDsrPjx4iIiIiiVZeLf6ku8KjqYrFvdjnCcumesXj2YdUz5MeJiIiIovTA1S/82npJ3ycv74CmbZo+eyHC8uqetXgHQqpnyM6SHysiIiKK0KRNvyYv7qBKmz46uxBhOXXPWrwDcaVf82NFREREi24y2v0n9YUdVG5uVwsRlll95updiKqeKT9eREREtMgmbTpHXtZBdf/4M7kMYVn17R95Z2fKjxcREREtqtKufb++qGMqOX1CLUJYft2zF+9EVHa2/JgRERHRIiq56dHykB6ZDAcnqiUIK8Cevb0D8t2Ix86WHzMiIiLa6aa5+Wl1QUdVhqmVCxBWRvcOiHcjKjtjftyIiIhop/rs1WvH1Yv44dmLOazcFLX4YBXVd0G9IzE9bGfNjx0RERHtRNNR85viUo4rpwvWLzxYURfIdyQoO2t+7IiIiGjejYfp29SFHFXJzafFsoMV1r0T4l2Jys6cHz8iIiKaZ6Vnf0Vs0g7OVMsOVpi9E/JdicnOnB8/IiIimlfjYfohdRFHVReEa+Wig5XXvRvinYnKzp4fQyIiIppHdTm4WV3CEZW2+VxdaE6YXXAAd0L3joh3JyI7e34MiYiIaLsbt+nfqws4rrRXLDfAM+wdke9OTHYG/TgSERHRdnVo9OLjS5u+qC7fmNJBudgAs+xdke9QPHYG7Sz6sSQiIqLt6PBCoC/fmAbnr1toAMXeFfkOBVW/Zj+WREREdKxN8tqr5YUbVrp13TIDHI29M/JdCqqeST+eREREdCzVReBiednG9OS4TaevW2SAo+jemfruzLxLcdUz6ceTiIiItlrJzT+SF21UOV317AUG2ISr5DsVlJ1NP6ZERES0lfr0b5CqX+vDYnkBNqx7h8S7FZGdTT+mREREtNlK2/wndcGGlZuPqeUF2Lj6Dql3Kyg7o35ciYiIaKM9sK95eb1Ev6wu14hKbu7ViwuwOd27JN6xiOyM2ln1Y0tEREQbado271YXa1i5OU8tLcDm1XdJvWNB2Vn1Y0tERETP16E2fae6UKMqOd2iFxZga7p3SrxrUdmZ9eNLRERER2uSmz3qMo0pfXmc06lqWQG2qnun6rul37mA6pn140tERERHarIv/ai8SKPKgyvVogIcu/puqXcuqnp2/RgTERHRbHv27PqKSZs+Iy/RgEpOD+oFBdge3Tsm3r2Y0mfsDPtxJiIiomc3zukX9QUaVbpULSfAtrF3TL57MdkZ9uNMRERET3fP3uO+QV2cUZWc7paLCbDNundNvINR2Vn2Y01ERERWvdBPVZdmXOmc2YUEmAt71+Q7GFQ9y36siYiIaDJc+2vywgyqtOmmdcsIMEfdOyfexbDqmfbjTUREtNqVnPbJyzKmL9Wv92S1jADz0r1z9d2beRfDsjPtx5uIiGh1K23z4+qiDCs3l6tFBJi/+u6pdzIoO9t+zImIiFavu/e/9PfVy/CguiQjKrm5Xy8gwM7o3kHxbkZkZ9vOuB93IiKi1apehP9dXZBh5XTx7OIB7LCL5bsZlJ1xP+5ERESr08Hc/FF1MQZ2p1g6gJ1n76J+R0Oys+7HnoiIaDUquXmfuhSjKqP0Qbl0ADusexfFOxqVnXU/9kRERMvfdJj+proQw8rphtllA1iwG+S7GpSdeT/+REREy92kTR9Xl2FIOT06bQcnzSwZwEL5O/mofGdDSh/3409ERLS81Qvvp/RFGFNp077ZJQOIoHs3xTsbV/opHwNERETL131XvOhr6mV3SF+C8ZRcv1axYABRdO+oeHdjSodsBvg4ICIiWq7qRfd2fQHGVNp0oVougCi6d1S8u3Glt/s4ICIiWp4m7e5X6osvqFFzu1osgHDsXVXvcFi7X+ljgYiIaDmqF/LZ+tKLqQzTWesWCiCg7l0V73BYdRb4WCAiIup/pV37fnnhBVVy+sTsMgFE1r2z4l2O6tC+te/z8UBERNTvpm26Tl12IeX0hUkenDi7SACxde/sF+Q7HZDNBB8PRERE/a3k5qfVRRdVyaldv0QA8XXvrnino7LZ4GOCiIiofx3Ys3ZcvcweVpdcRPVrnagFAuiL7h0W73ZENhtsRvi4ICIi6lf1IvtNdcHFlS5QywPQG/YOy3c7JpsRPi6IiIj608G9zZ9VF1tUpW0+LRcHoGe6d1m841HZrPCxQURE1I9Kbj6sLrXAzlRLA9A79i7rdzwkmxU+NoiIiOI3bdPfUxdaWDldu25ZAPrtWvmuB2Uzw8cHERFR7EqbblKXWUTTtvncpE0niEUB6K/6Th9+t/V7H43NDB8fREREcauX7L9TF1lcabhuSQCWgb3b8p0Pqs4OHyNERETxmg6PW6uXVW/+ofV1ETj4nMUAWDb2jst3P6A6O2yG+DghIiKKVb2o/q+8wMIanP+cpQBYNvaOy3c/qDpDfJwQERHFabJv97fLiyuo0qZb1y0FwBLq3nVxBsKqs8THChERUYzqZXqRvLQiyvaf6XS1FABLp3vXZ85AYDZLfKwQEREtvjJa+2F1YUVVL9Kr5UIALKnunRdnISqbKT5eiIiIFltpm9vUZRXUw2oRAJaevfv6TIRjM8XHCxER0eKats3PqosqqpKbPXIJAJZc9+6LMxGVzRYfM0RERDvfwcual9cL6fHZCyqwe9UCAKwMOwP6bET0uM0YHzdEREQ7Wxk27xaXU1y5OU9e/sDKqGdAnY2gbMb4uCEiItq5xm36TnUxRVVyukVf/MBq6c6COCNR2azxsUNERLQz9el/7zfO6Yn6n6eqSx9YOfUs+JmQ5yUamzU+doiIiOZfvSR/VF1IUZU8+Li88IEV1Z0JcVaispnj44eIiGh+PfX+Xb+r5PQZdRlFVNr0oLrogVXXnQ1xZiKymWOzx8cQERHRfKoX5H9RF1FU01G6dPaCB5B+qzsb4syEVWePjyEiIqLtb7Jn9yvkBRRWunv2cgfwLHZG5NkJqs4gH0dERETbW70UT5GXT1jpHHm5AzjMzog8O1GlU3wcERERbV+lHfxVffHEVNp0k7zYATxHd1bEGYrKZpGPJSIiou2pXoYjdekE9aX69b5XXeoAnqs7K/XMzJyhsGwW+VgiIiI69kq79i/UhRPWqLlcXegAjsDOjDpLQdlM8vFERES09e7c8/LfW3JzQF02MaX75UUO4Ojs7MgzFY/NJJtNPqaIiIi21jQ3/01dNGHldPG6CxzARlwsz1RQNpt8TBEREW2++y5vvlldMGHZv8hCX+AANqY3/zIYYzPKxxUREdHmqhfJmbMXS2TTnD4oLm4AG9SdIXG2AjvTxxUREdHGm46a7xGXSlglNzeqixvA5nRnSZyxqGxW+dgiIiLaWPUCuXL2QomqtOnRktN71KUNYHPsLNmZUmctqCt9bBERET1/kza9QVwmYdVLeZ+6sAFsTXemxFmLK73BxxcREdGRu+0jL/qaemlM9WUST72QD6mLGsCx6c6WOHMxpanNLh9jREREuvEwvV1fJDGVnC5UlzSAY9OdLXHmorLZ5WOMiIhofZN29yvVBRJWbu5QFzSA7VLPmDp7Ye1+pY8zIiKi51YvtrP15RHTtE1nrb+YAWyX7oyJsxdWnWE+zoiIiJ6p5MH3yYsjqmG6fvZSBjAHdtbUGQzKZpmPNSIiosOVnK5Tl0ZE9Wv9wmQ0OFFeygC2Vz1r3ZkTZzEim2U+1oiIiGzJbf6NujCiKqPUygsZwFx0Z06cxahspvl4IyKiVe7eK49/cb0UHlKXRUi5maiLGMC81bOnzmRANtNstvmYIyKiVa20zf9UF0VUJaeP6EsYwDx1Z0+cyahstvmYIyKiVezQqPkz6oKIato2n1YXMICd0Z1BcTajshnn446IiFatehGcP3sxhJab96nLF8BOqWdQnc24zvdxR0REq9S0bf6uuBQiu1ZfvAB2lJ1FfUZDslnnY4+IiFalSW4+qS6FoD5fL9gT1l24ABbhhO5M6rMaT511PvaIiGgVqhfVz8gLIaiS03DmogWwQN2ZFGc1rDrzfPwREdEyN7lydzNp0yPyMghonNN49pIFsHjd2RRnNqY68+rs8zFIRETLWh3479AXQUwlDz6sLlkAi9WdTXFm40rv8DFIRETLWBkNXqUvgKjSreqCBRCEnVF5dmOyGejjkIiIlq1pmy5Uwz+qMhycIS9XACF0Z1Sc3ahsBvo4JCKiZapeSD+sBn9c6Wp1sQIIxs6qPMMx2Sz0sUhERMtSyek2NfQjKrn5rLxQAYTUnVlxliOyWehjkYiIlqHSNj+rBn5UZdjsUZcpgJi6MyvOclQ2E308EhFRnzvQrr2sDvXH1bCPaDxsDqiLFEBs3dkVZzoim4k2G31MEhFRXyu5OVEN+qimbXOeukQBxNadXXGmo7LZ6GOSiIj62MHc/EU14ONKt6gLFEBP2BmWZzsmm5E+LomIqG+V3HxMDfeISk5PTNt0qrw8AfSCnWE7y+qMR2Qz0sclERH1qckw/RM12OMafFxdnAB6xs6yPONB1VnpY5OIiPrQU0/t+p2T3Nwph3pI6UF5YQLoJzvT8qwHVGelzUwfn0REFL16yfyCHOhBlTy4TF6WAHqpO9PirMeVfsHHJxERRW4y2v31epBHle5WFyWAnrOzLc98UHV2+hglIqKolTa9Vw7xsNI58pIE0G92tuWZj8lmp49RIiKKWGkHf0UN8LjSTfKCBLAc7IzLsx+TzVAfp0REFK2SU6uGd0T2byYqw/ReeTkCWAp2xvv0b2a0GerjlIiIIjXNaz+mBndYw+YKdTECWDJ21tUMCMpmqY9VIiKK0JO3veIrJ226Vw3tkHK6f91lCGCZ3S9nQUjpXpupPl6JiGjRTUfNW/XADmqYLhEXIYBlZWdezYKgbKb6eCUiokV2cG/zzWpQR1Vy+oy8CAEste7si5kQlc1WH7NERLSo6kA+Y3ZAR1ZG6YPqEgSw3LqzL2ZCYGf4mCUiokV0cG/zPWI4h1Vyc6O6AAGshm4GiNkQlc1YH7dERLTT1UvjSjWcIyo5PTbN6T3q8gOwGmwG2CxQMyIim7E+bomIaCcbt+kNajCHldP+2UsPwEraL2dEUDZrfewSEdFOdGj04t9f2jRVQzmknA7NXHQAVtshOSsCsllrM9fHLxERzbt6SfyqGshRTdt04cwlB2CFdTNBzIqw6sz18UtERPOs5MGfkIM4qGnb3DF7yQFANxvEzIjKZq+PYSIimlcl9+sf0VPadJa65ACstm42iJkRlc1eH8NERDSPynDwt9UAjitdry44AOjYjJCzIyabwT6OiYhouyttulYN35By+kK9FN697mIDAOcz4gtyhgRkM9jHMRERbWelXfvXavBGNc2pnb3UAGBWNyvEDInKZrGPZSIi2o4e2v/SF5U2PaiGbki5magLDQC0OjPULAnIZrHNZB/PRER0rNXh+huzwza0UfqIvswAQLCZoWZJXL/h45mIiI6lQ+3anxZDNqySm9+WFxkAHEU3O8RMicpms49pIiLaapPcfEgN2ajqZfU+dYkBwNF0s0PMlLDqbPYxTUREW6kO0h+UAzaocW6uUxcYAGxEN0PEbAmrzmgf10REtNnqIL1x3WCNKg8+X3LzLnV5AcBGHJ4hg8/LGRPTjT6uiYhoM01G6c1iqAY2GKqLCwA2xWaJnDFB1VntY5uIiDbSZM/upg7Q3vxVjdKmsbywAGALupkiZk1Qn7eZ7eObiIierzro3yGGaWCDD89eVACwZTZT5KwJqs5sH99ERHS0yt7Bq+QgDaq06bZ1lxQAHKNutoiZE5XNbh/jRER0pEpOF6ohGlUZDs5QlxQAHItutoiZE5XNbh/jRESkKu3gH6oBGle6Wl1QALAtbMbI2ROTzXAf50RENFtp061qeEZUcvPZyUhcTACwXeqM6WaNmEER2Qz3cU5ERM+uDvP/qAZnWLnZIy8mANhWddaoGRSUzXIf60REZN07PP4Plpy+pIZmRHWQH9AXEgBsv27miFkUkc1ym+k+3omIaGL/NiAxMMMaNR9SlxEAzIXNHDWLoqoz3cc7EdFqNx02f0EOyqhyumXdJQQA83eLnElB2Wz3MU9EtLrVgXjZ7IAMKzdP1MvmtJnLBwB2Qp09dQap2RTTZT7miYhWszoIf2RmMIZW2vRxcfkAwI7oZpCYTYH9iI97IqLV6qmndv2OOgTvmBmKYZWcHlIXDwDspG4WiRkV1B02633sExGtTpM2/bwYioENLlOXDgDsKJtFckZFlX7exz4R0WpU2sHX6YEYU2nTPfLCAYAF6GaSmFVR2cz38U9EtPyVnE5WwzCsnM6dvWgAYIHOlbMqKJv5Pv6JiJa7Q/sG36UGYVzpJnHJAMBi2WySMysmm/1+DRARLW91OGc1BCMqbfP4ZJhOkZcMACxSnU3djBKzK6aU/RogIlrOSh78mB6AYV0hLxgAiMBmlJ5dIdkd4NcBEdFyddtHXvGV9Xf0vfkbKEpOD8iLBQAC6WaVmGExpXvsLvBrgYhoeSq5easefDGNc7pEXSoAEEk3q8QMi8ruAr8WiIiWowN71v6IGnhRlZzuUhcKAETUzSwxy6KyO8GvByKi/leGzRlq2EU1HaUPqssEACLqZpaYZVHZneDXAxFRv5u2zd9Qgy6s3NyoLhIAiK3OLjXTgrK7wa8JIqL+Vgdaf/6u4Nw8Nh2l9+hLBADiOjy7msfkbIvpCr8miIj6WR26PymGW1jTttmvLhAA6INuhonZFla9I/y6ICLqV5M9u7+6DrGJHG4BTdt0SF0cANAn3SwTMy4kuyPqXeHXBhFRfyo5/YocbEGVNl2kLg0A6JNulokZF5XdFX5tEBH1o7J38MfVQAvsDnVhAEAv2UzTsy4kuzP8+iAiil9p0wfUMItq2g7OkpcFAPRQN9PErIvK7gy/PoiIYldGg+9VgyyudL26KACg12y2yZkXk90dfo0QEcWt/s78GjXEYkpfnLaDd8tLAgB6rJttdcbp2ReP3R1+jRARxawO1jeqARZVHawjdUEAwDLoZpyYfVHZHeLXCRFRrB5qX/bCOlgfUMMromnbTGYvBQBYNt2sEzMwpHqH2F3i1woRUZwmufl1ObiCGg/TR2cvBABYNt2sEzMwrHqX+LVCRBSj6f61b5UDK6iSm99WFwIALKNu5olZGJXdKX69EBEtvjqYzpsdVJHVof8+dRkAwDLqZp6YhYGd59cLEdFiO5ibHxRDKqw68K9TFwEALLNu9omZGJXdLX7NEBEtrjo8b1RDKqKSB49MRs271CUAAEutzr5uBorZGJHdLX7NEBEtpskwvVkNqKgOjdJQXgAAsAK6GShmY1j1jvHrhohoZyuXDtIkN5+Xwymg0qaxGvwAsEq6WShmZEj1jrG7xq8dIqKdqw7L/yMHU1iDD6uhDwArxWahnJEx2V3j1w4R0c5U2sGfVwMpqjoob5MDHwBWUDcTxayMyu4cv36IiOZfHZL9+geQt4Mz1LAHgJVkM1HOypjszvHrh4hovpU8+AdqEEVVB+Q1ctADwArrZqOYmVHZ3ePXEBHR/Co5fUoNoaA+O2nTO9WQB4CVZrOxm5FydoZjd49fQ0RE82maB/9BDaCwcrNHDngAQFVnpJqdQdkd5NcREdH2dt8VL3lpHYyPqeETUm4OrB/qAIDnqrNSzdCI6h1kd5FfS0RE21cdMiesGzqR5eZD6wc6AOC56qxUMzSuE/xaIiLanqajte8Qwyas7n9HLAc6AGBWz/7ei6fsTvLriYjo2KuD5dLZQRNVaZsn6uA+bXaQAwCO6LRudoqZGtSlfj0RER1bdaC8bmbAhFZyukoMcQDAUXSzU8zUwF7n1xQR0dab5OZ2MWBCKm16SA1wAMDz62aomK0h1bvJrykioq1VcvNzcsBElZvL1PAGAGxEnaFqtgZld5RfV0REm6u0g68rbfOkGi4RlZzu0YMbALBR3SwVMzYiu6PsrvJri4ho49Vhd7IaLGHldO7swAYAbNq5csYGZXeVX1tERBur5MF3qYESVk43zwxqAMDW3SxnbVB2Z/n1RUT0/NXfIWc1TCIqbXp80qZTxKAGAGxFnamHZ6ueu9HYneXXFxHR0SvDwT9XgySsUXOFHNQAgK2z2apmblB2d/k1RkSk++T7d/2eXv2NCMP0gBzQAIBj1s1YMXsjsrvL7jC/zoiI1jdu039VAySsnC6ZHcwAgG1ziZy9Qdkd5tcZEdFzOzQ6/pvU4Agrp7tmBjIAYPvdJWdwUHaX+bVGRPRMdUCcPjswQsvp7JlhDADYfmfLGRzX6X6tEREdbpKbvy6GRVjTtrlRDGMAwBx0M1fM4rDqnebXGxFRt+heLodFTI/ZPyBcDWMAwPbrZm6dvTOzOK56p/n1RkSrXh0IPyEHRVS52a8GMQBgnursVTM5qnq3+TVHRKva+BPpBXUYFDkkAio53acHMABg3roZLGZzSPVuszvOrzsiWsVK2/yyHBBB1SF7kRq+AID562awmM1R2R3n1x0RrVr370vfogZDVCUP7lSDFwCwc7pZLGZ0VHbX+bVHRKvUtE1nqaEQVR2uH1BDFwCwc7pZLGZ0VHbX+bVHRKvSoTa9Vg2EqOqgul4NXADAzutmspjVUdmd59cfEa1CkzZdrYZBTOmLB/PgJDVsAQA7r5vJdTbrmR1RutqvPyJa9ko7eKMeBDGVYRqpQQsAWJxuNouZHZXdfX4NEtGydlf7sheWnB5QQyCiOkinasACABavm9Fidkdkd5/dgX4dEtEyNs7Nr6sBEFVp00fVcAUALF43o8XsjsruQL8OiWjZOjBc+1Z18KMaD5vb1WAFAMTRzWoxw6Oyu9CvRSJapurvZM9Thz6sUfM+NVQBAIHYrFYzPCi7C/1aJKJlaTJs/o468FFN2+Y6OVABAOF0M1vM8rDqnejXIxEtQ5Pc3CAPe0Q5PVK/3nfNDlIAQFTdzH5EzvSI6p3o1yMR9b16qN+07pAHVnLK64coACCybnaLmR7Ym/yaJKK+Nt6XBqVtPicOeEilTWM1QAEA8XUzXMz2iOxutDvSr0si6mN16PxvdcCjKnlwgRqeAID4uhkuZntUdkf6dUlEfWuc059TBzuudJsanACAHrFZLmd8THZX+rVJRH2q5PQRdajjGpwhhyYAoD9slssZH5PdlX5tElFfmub099WBDiuna9YNSwBAX10jZ31Qdmf69UlEfWjSplvUYY6oZPub5dI7xaAEAPRRnemHZ7ue+/GkW/z6JKLo1QP7Fn2QgxqmvXJQAgD6y2a7mvlhpbf4NUpEUbtv/0tfUg/ro/oQx1N/x39ADkgAQO91M17M/pjSo3aH+nVKRBGrh/Wd6w9vXKUdnK+GIwCg/7oZL2Z/YO/065SIonVg79p3iEMbVmnTp9RgBAAsj27WizsgKrtL/VolokiNh82l6tBGVHLzZB2Ap80ORADA0jmtm/niLojI7lK/VokoSvVwvm72sEZWcrpKDEMAwBLqZr64CwJ7nV+vRBShSW5uFwc1pPo7+4fVIAQALK9u9os7IaR6p/r1SkSLrg6Pn5MHNahp21ymhiAAYHl1s1/cCVHZ3erXLBEtqvEw/eE+/W+fJm26Rw1AAMAKsDtA3g3x2N1qd6xft0S0iEpO71EHNK50rhx+AIDlZ3eAvBtisjvWr1si2unq7zT/sjqYcaWb5eADAKwOuwvkHRGT3bV+7RLRTlZ/pzlUhzKm9Hh1ihx6AIDVYXdBdyeouyIeu2v92iWinWrcpn+mDmRYeXClHHgAgBVU7wR1VwRld65fv0Q07566etfvLm26Wx3GkHJ6YP2QAwCsuAfknRGQ3bl29/o1TETzbNKmX1IHMarpKF0iBhwAYIV1d4O4M+JKv+TXMBHNq2k+/hv1AQwqp7tmhxsAAO4ueXcEZXewX8dENI8muTlNHb6wcjp7ZqgBAPC0s+XdEVW9g/06JqLtbrJv7bvlwQuq5OaTYqgBAPD/dXeFuEPCqnexX8tEtJ3VA7Z/3YGLKjePlZxOVkMNAICnHb4rmsfkXRLTfr+WiWi7KqPm9eKwhTXOzeVqoAEAMKu7M8RdEpXdyX49E9GxNr4ovaC0zVgdtqDuU4MMAIAjsrtD3ynh2J1sd7Nf00R0LE3b5m3qoEVVv96L5BADAOAIurtD3ClR2d3s1zQRbbXxnvQt6oDFNbhTDTAAAJ6X3SHybonJ7mi/roloK5VhOksdrqhKHnxADi8AAJ5Hd4eIuyUqu6P9uiaizTZu02vVwYpqnNMNanABALBR3V0i7pio7K72a5uINlNp09XqUEVUv9YvlnZwkhpaAABslN0ldqeouyYiu6v92iaijVZ/R/uv1IGKatqmkRpYAABsVneniLsmKruz/fomoufrwT1f+wdKTverwxRTmqpBBQDAltndIu+ceOzOtrvbr3EiOlr1gP8PdZCimo7SR9cNKAAAjkF3t4g7J6x6d/s1TkRHarr3+D8lD1BUw+b22eEEAMC2sDtG3T1B2R3u1zkRqepBOXf24ERW2ub9cjgBAHCMujtG3D2BnevXORHNVg/ID8wcmNDqALpODSYAALZLd9eIOyiwH/BrnYieXT0c188clrhyeqTk5sTZgQQAwHbyu+YReRfFdL1f60T0dPV3rP9WHJawSpvy7DACAGAeujtH3EVR2Z3u1zsRHczN7vo71s+qwxJUUYMIAIC5sbtH30nh2J1ud7tf80SrXT0Q/0sdlLByumDdAAIAYL4ukHdSUHa3+zVPtLrdtz99mzogUZWcPi2GDwAAc9fdQeJuisrueL/uiVazSduv36FO8uBMNXwAAJi/egepuymsdIFf90Sr13SUfkgfjKjSNXrwAACwQ+wukndUTHbX+7VPtFrVw3qzOhQRjdvmc+OcTpBDBwCAHWJ3kd1J6q6KKd3s1z7R6jQeprfoAxFTadNeNXAAANhp3Z0k7qqo7M73659o+bv70he9pOT0qDoMEdWBclANGgAAFqW7m8SdFZHd+Xb3+xpAtNzV39m9Ux2EuAbnqyEDAMDC2N0k76yY7O73NYBoeZu0a69RByCqMky3ygEDAMCCdXeUuLviWnuNrwNEy9kkN5folz+ekpsnp6N0mhouAAAsmt1RdlepOyykugP4OkC0fNUX/B/LFz+sdJUaLAAAhGF3lbzDgqq7gK8FRMtV/V3nb8uXPqaH5UABACAau7P0XRaO7QK+FhAtT/XF/s/qhY+qtM3H5DABACCY7s4Sd1lUthP4ekDU/8aXpz9UX+on1MseU7pHDRIAAMKyu0veafHYTmC7ga8JRP2u/k7zJPWih5Wb8+QQAQAgrHp3qTstKNsNfE0g6m+HRukvqRc8rnSzHiAAAATXo3+1vrEdwdcFon5WD11v/jWFpU1fnrbpFDk8AAAIzu4wu8vUHRdT2uvrAlH/qgfun+oXO6rBlWpwAADQG3aXyTsuJtsVfG0g6k9P7dn1FfXA3aVe6pjSg+uGBQAAfWR3mrzrAqq7gu0Mvj4Q9aP64v6ifKGDGg/Tpc8ZEgAA9FR3p4m7Lqy6M/j6QBS/6eXHfYN8kaOyv/IsBgUAAD3Wo/+vavOU7Q6+RhDFbtKmU9VLHFX9ne85YkAAANBb3d0m7ry40qm+RhDF7cBw7bv1CxxUbj6pBgQAAP1X7zh19wVlO4SvE0QxK22zT728EZXcfKnkdLIeDgAA9JvdcXbXqTswItshfJ0gilcZNq9XL25YublcDQYAAJZHvevUHRiU7RK+VhDF6cCH1r6q/q5xrF7aiOrXer8eCAAALJfuzhN3YUS2S9hO4esFUYxK27xNvbBRTdvmIjUMAABYNt2dJ+7CqGyn8PWCaPGN2/TH1Isa1+BONQgAAFhadvfJOzEm2y18zSBabPV3Xu9XL2lU0zZ9QA4BAACWVHf3iTsxKtstfM0gWlzjnP6WekHjSjeoAQAAwNKzO1DejTHZjuHrBtFiKjldpV7OkEbpi9N2cJI8/AAALLnuDqx3obwjA7Idw9cNop2vHpp/qV7MqOqB2Td76AEAWCXdXSjuyLDqruFrB9HO9cDVL/za+vLdJ1/KgKZtmj77oAMAsKq6O1HclSHVXcN2Dl8/iHamSZt+Tb6QQZU2fXT2oAMAsIq6O1HclXGlX/P1g2j+TUa7/6R+EYPKze3qoAMAsLrq3ajuzKjq7uFrCNF8q7+zOke+hEF1//gzecgBAFhNfftHg9ru4WsI0fwq7dr36xcwppLTJ9QBBwBg1XV3pLg7o7IdxNcRovlUctOjQ5EemQwHJ6rDDQDAyrM70u5KeYfGYzuIryNE2980Nz+tXryoyjC18mADAIBOd1eKOzQq20V8LSHavj579dpx9QV7ePaFCys3RR1oAAAwq96Z6i6N6WHbSXw9IdqepqPmN8XLFldOF6w/yAAAQLhA3qVB2U7i6wnRsTcepm9TL1pUJTefFocYAAAcQXd3ijs1KttNfE0hOrZKz36nN2kHZ6pDDAAAjsDuTnmnxmS7ia8pRFuv/o7ph9QLFlV98a+VBxgAABxVd4eKuzUq21F8XSHaWvWlv1m9XBGVtvlcPagnzB5cAACwISd0d6m4YyOyHcXXFaLNN27Tv1cvVlxprzi0AABgo+wulXdsTLar+NpCtPEOjV58fGnTF9VLFVM6KA8sAADYHLtT5V0bj+0qtrP4+kK0sQ6/6Pqlimlw/rqDCgAANs/uVHnXBlW/Zl9fiJ6/SV57tXyRwkq3rjukAABg6+xulXduUHV38TWG6OjVF/xi+RLF9OS4TaevO6AAAGDLuru13rEzd25cdXfxNYboyJXc/CP5AkWV01XPPpgAAGDbXCXv3qBsh/F1hkjXp38zSv1aHxaHEgAAbJPurhV3cES2w/g6Q7S+0jb/Sb04YeXmY+pQAgCA7VLvWnUHB2W7jK81RM/0wL7m5fXl+LJ6aSKqv2u7Vx9IAACwnbo7V9zFEdkuYzuNrzdEh5u2zbvVCxNWbs5ThxEAAGy3euequzgo22l8vSHatetQm75TvShRlZxu0QcRAADMQ3f3ijs5KtttfM2hVa/+Tm2PekliSl8e53SqOoQAAGA+uru33sH6bg6o7ja+5tAqN9mXflS+IFHlwZXqAAIAgHmrd7C6m6OqO46vO7SK7dmz6yvq784+I1+OgEpOD+qDBwAAdkJ3F4s7Oqb0Gdt1fO2hVWuc0y/qFyOqdKk6dAAAYIfYXSzv6Jhs1/G1h1ape/Ye9w3qhYiq/g7ybnngAADAjuruZHFXR2U7j68/tCrVF/VU9TLElc6ZPWgAAGAB7E6Wd3VQdefx9YdWoclw7a/JFyGo0qab1h0yAACwMN3dLO7ssOru42sQLXslp33yJYjpS/XrPVkdMgAAsBjd3Vzv6Jk7OyzbfXwNomWutM2PqxcgrNxcrg4YAABYtHpHq7s7KNuBfB2iZezu/S/9ffUhH1QPP6KSm/v1wQIAABF0d7W4wyOyHch2IV+LaNmqD/i/qwcfVk4Xzx4oAAAQysXyDg/KdiFfi2iZOpibP6oeeGB3isMEAACisTtb3+Uh2U7k6xEtSyU371MPO6oySh+UhwkAAITS3dniLo/KdiJfj2gZmg7T31QPOqycbpg9RAAAILQb5J0elO1GviZR35u06ePqIYeU06PTdnDSzOEBAACB+d39qLzbQ0of9zWJ+lx9kD+lH3BMpU37Zg8PAACIr7vDxd0eV/opX5eoj913xYu+pj7EQ/rhxlNy/VrFwQEAAP3Q3eXijo8pHbJdydcm6lv1Ab5dP9iY6u8EL1SHBgAA9EN3l4s7Pq7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Number: 21FLHILL_WQX-101<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: all<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: all<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: all<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: all<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: all<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: all<br> Category: 130 - 999 (908/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-109<br>Sample Condition: all<br> Category: < 35 (1/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-133<br>Sample Condition: all<br> Category: > 999 (3100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-144<br>Sample Condition: all<br> Category: 130 - 999 (620/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-2<br>Sample Condition: all<br> Category: 130 - 999 (280/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-560<br>Sample Condition: all<br> Category: 130 - 999 (600/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-561<br>Sample Condition: all<br> Category: > 999 (3500/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-594<br>Sample Condition: all<br> Category: 130 - 999 (300/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-595<br>Sample Condition: all<br> Category: > 999 (6100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-596<br>Sample Condition: all<br> Category: 130 - 999 (580/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-597<br>Sample Condition: all<br> Category: > 999 (1350/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-598<br>Sample Condition: all<br> Category: 130 - 999 (525/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-74<br>Sample Condition: all<br> Category: 35 - 129 (85/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-32-03<br>Sample Condition: all<br> Category: < 35 (20/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-44-02<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SC-01<br>Sample Condition: all<br> Category: 130 - 999 (480/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-112<br>Sample Condition: all<br> Category: 130 - 999 (220/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-180<br>Sample Condition: all<br> Category: 35 - 129 (56/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-264<br>Sample Condition: all<br> Category: 35 - 129 (40/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-592<br>Sample Condition: all<br> Category: 130 - 999 (320/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-22<br>Sample Condition: all<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-48-03<br>Sample Condition: all<br> Category: < 35 (31/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-CENTRAL CANAL<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-COSP580<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-NORTH CANAL<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SOUTH CANAL<br>Sample Condition: all<br> Category: 130 - 999 (360/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-01<br>Sample Condition: all<br> Category: 130 - 999 (717/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-05<br>Sample Condition: all<br> Category: 130 - 999 (727/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>All samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.535934301,28.0257081],\"lng\":[-82.74574933,-82.381683]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # wet/dry samples show_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5)  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.535934301,-82.74574933,28.0257081,-82.381683,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide 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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\"],\"index\":[0,1,1,0,0,2,3,0,0,2,3,0,1,0,3,0,3,0,3,0,4,2,5,0,0,5,5,0,2,2,2,2,2,2,5,5,0,0,0]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 21FLHILL_WQX-101<br>Sample Condition: dry<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: wet<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: wet<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: dry<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: dry<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: dry<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: dry<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: dry<br> Category: 130 - 999 (908/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-109<br>Sample Condition: dry<br> Category: < 35 (1/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-133<br>Sample Condition: dry<br> Category: > 999 (3100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-144<br>Sample Condition: dry<br> Category: 130 - 999 (620/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-2<br>Sample Condition: wet<br> Category: 130 - 999 (280/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-560<br>Sample Condition: dry<br> Category: 130 - 999 (600/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-561<br>Sample Condition: dry<br> Category: > 999 (3500/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-594<br>Sample Condition: dry<br> Category: 130 - 999 (300/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-595<br>Sample Condition: dry<br> Category: > 999 (6100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-596<br>Sample Condition: dry<br> Category: 130 - 999 (580/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-597<br>Sample Condition: dry<br> Category: > 999 (1350/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-598<br>Sample Condition: dry<br> Category: 130 - 999 (525/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-74<br>Sample Condition: wet<br> Category: 35 - 129 (85/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-32-03<br>Sample Condition: dry<br> Category: < 35 (20/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-44-02<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SC-01<br>Sample Condition: dry<br> Category: 130 - 999 (480/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-112<br>Sample Condition: dry<br> Category: 130 - 999 (220/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-180<br>Sample Condition: dry<br> Category: 35 - 129 (56/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-264<br>Sample Condition: dry<br> Category: 35 - 129 (40/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-592<br>Sample Condition: dry<br> Category: 130 - 999 (320/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-22<br>Sample Condition: dry<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-48-03<br>Sample Condition: dry<br> Category: < 35 (31/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-CENTRAL CANAL<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-COSP580<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-NORTH CANAL<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SOUTH CANAL<br>Sample Condition: dry<br> Category: 130 - 999 (360/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-01<br>Sample Condition: dry<br> Category: 130 - 999 (717/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-05<br>Sample Condition: dry<br> Category: 130 - 999 (727/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Dry samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Wet samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.535934301,28.0257081],\"lng\":[-82.74574933,-82.381683]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Old Tampa Bay only show_enteromap(enterodata, yrsel = 2020, mosel = 9, areasel = \"Old Tampa Bay\")  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.862940001,-82.74574933,28.0257081,-82.562595273,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addMarkers\",\"args\":[[28.0257081,28.010599,27.997414662,27.981868039,28.020482621,27.928402531,27.923464624,27.912087245,27.862940001],[-82.63164009099999,-82.607803,-82.586513802,-82.562595273,-82.68955061299999,-82.74574933,-82.717654432,-82.70025344,-82.61633],{\"iconUrl\":{\"data\":[\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\"],\"index\":[0,0,0,0,0,1,2,0,0]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 21FLHILL_WQX-101<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: all<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: all<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: all<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: all<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: all<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: all<br> Category: 130 - 999 (908/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>All samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info 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location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"show_fibmap(fibdata, yrsel, mosel, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"fibdata input FIB data.frame returned read_importfib read_importwqp, see details yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"# show selected year, month show_fibmap(fibdata, yrsel = 2023, mosel = 8)  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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAq4AAAK5CAYAAAB+LKwlAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAFpGSURBVHhe7d0NtJ1VfefxdHXUcYaZsY7TaR2dlxrf7tnPjTZw9z4BGmap89I1bae60FYdh9VaX1bV6Yyt08pyDatj7az60o50fCsoSCEFEgIEoqAQgXDPfp4bQCBCBGlARRHFCEoD9W3+/3M3TfKcf5J7c+85z36e8/2t9VlBktyc8zx77/8v18M5awghZNqyftf6J82UJ/zMbNV3vYE/Zbbyr3AxvLGowjvF+4rSn+nK8FEX/Tny7zcVMWyRf3dFUYar5d9dJz83kB9vlp/bLf/+bnGf/NwD8u/2yb97VH78waLhP+/Tn1v8Nf5u/T3D37v4Na7Trzn82vJn6J8l/+4c/bPl3505fCwxvFP+/RtnB/IYq7Bx9sa+08euzyE9HUIIIYQQ0pZs/PHGv/eigX9uUfZ/oVf5lxfRv0FK3h9I6Xu/q/w5Ug6vkPIXF4vjsEj+uAsWn8uwDOtzk+coz1Wfc5TnXvrfGl4LuSZ6bfQapctFCCGEEELGmV51/LOLOHfybAyvk2L2v6SYfkIK6ueEfrfTLHao0Wsl10yvnV5DvZZ6TfXapstMCCGEEEKOlvW71j+jV/VPcGV4ZRHDO6RgfdhF/2n533vkfz9uFjGsHrnGeq31muu113ug90Lvid6bdJsIIYQQQqYnz5oPT123EOakLL2+qML/lR93FKV/6JAShQwN79GOdM9er/dQ72W6rYQQQggh7c66gf/Xs1X4JSk9pxfRXyiF544DRQgdccfivfWn673We55uPyGEEEJIfgnz4amzA++lxLxeSswHxef4Luo0k3u/+PrjD8r/fr2uDV0jabkQQgghhEwuRXXSz/Xi3H+RYvJhKSa3HlpagMO6VdfMcO1Ux/9cWk6EEEIIIauXYj78vIvhLa4MFxSlv9coJMAx8Pe60l+ga0vXWFpuhBBCCCFLy9rta5/Si3P/Vl+zKOXiSikV3xktHMDqk78Y6XvsXqlrT9egrsW0LAkhhBBC1qyZvbH/0y72/7Mr/Z9IYdhZLxNAs/xOXZu6RnWtpmVLCCGEkGlJbyGcWMTwhy760i4LQJ6Ga1bWrq7htJwJIYQQ0qW86OaT/pmr/Gtl4J8ng/9BqxAAbTNcy7qmZW3rGk/LnRBCCCFti75BvBv4d8lw5//+x1TQta5rXtd+2gaEEEIIyTHrbln3tN7Av6qI4eOu9F+1BjswLYZ7QPaC7gndG2mbEEIIIaSpzFZ95wb+92VQX1sf3AAOca3uFd0zafsQQgghZNyZuSmsHZbV6BeM4QzgaGTv6B7SvZS2FSGEEEJWK73q+GcXMfyOK8MN5iAGcEyGe0r2lu6xtN0IIYQQstwM3wmgDG9y0X/GGrgAVpfuNd1zvEMBIYQQsoQ8f+eGf1SU/rQi+m3WYAUwIcM96E/TPZm2JyGEEELW71r/pCLO/bqLYbM5QAE0arg3ZY/qXk3blhBCCJmuFGX/F4rSn11Ev98algAyM9yrsmdl76ZtTAghhHQ3a+PcP3ZleKsMwV0jQxFAm+zSvax7Om1vQgghpBsp4tzJrvRnuei/bwxAAC2le1r3tu7xtN0JIYSQ9kX/ow4Xw1v0PSOtgQegY/T9YWXP8x90EUIIaU1mB/4kF/1fyCB7fGSwAZgGj+sZoGdBOhYIIYSQfDKzY+NxRZz7bVf60hhiAKbU8EyQs0HPiHRcEEIIIc1kptzwIleGjxalf8waWgCwyD+mZ4WeGen4IIQQQiaTouy/pIhhiz2gAOAIhmdH/yXpOCGEEELGExk2pxbRf84cRgCwHMOzpH9qOl4IIYSQ1Yl+frkr/W3m8AGAFdCzRc+YdNwQQgghy8+6WzY+rSj96S76+61hAwCrafGs8afr2ZOOIUIIIeTI6S1seE4Rw/uLyH9wBaABevbIGaRnUTqWCCGEkEMzMx/mXPTnmIMEABqgZ5KeTemYIoQQMu3pDfwpRfTbrKEBAFmQM0rPqnRsEUIImbasWwhzrgybzSEBABnSM0vPrnSMEUII6XqK+VAUMZxnDQUAaAU9w+QsS8caIYSQrmVmPqzVT64xhwCm1X4Xw3fkxwdc6e+Vf97jqvB5+d9R/vf18uOOovTXyI9Xu6r/KSkLV7rYv1z+91axpaj8RW4hbHLRny//+5Pyc/oa6bNnF/ofU/rP6d/Jz/nz9dfq7xn+Xvkaw6+lX1O/tvwZ6c/akf7sqI9l+Jjkscn/fiA91v3Cei6YQnqm6dmWjjlCCCFtz4tv2vBMOdz/zDr00T1S7r4nvi7/fJe4VQpjKQXwOvnnq2bLcFlR9S8U50qJ/KgO/VaSx67PQZ/L8DnJc9PnqM9Vn7M+d70Gei3kn83rhG6Re/1netalY48QQkjbUtxw0k8VMfxxUfofWAc9Wku/4/iglLR7ht+RLMMNYnsR+xe6qn/WIQUPH9VrMrw2co3EDYvfxfX36DVM19K6xmglPev679GzLx2DhBBCcs/au/7DU1zp31VE/137cEcL7Je/dOgHP9zuBmEgZesqV/Y3uxg+cUgpw8oNr6lcW73Gcq31mqdrT6ltKzn79AzUszAdi4QQQnJML879rhzY3zAPc2RJytO3pSh9SQpUpa/1dLF//ki5QjP0XgzvSaiG90jvlXEPkSc9C/VMTMcjIYSQXDIbw+tkqO61Dm9kY7/co/ulBN0urutV/Utcyf+13z79s4b3Tu7h8F7KPdV7W7vXyIjcIz0b/2s6LgkhhDQVV27oF1H/a2z7wEZDYvih/Hi/K/3Nw+/YVXwXtfP0Huu9lnuu9z6tAXt9oClX65mZjk9CCCGTyvN2rX+Gi+H/GQczGiBlZb8r+/pdnSgl5rJW/xf7WB2La0Df8UDWRH+vrpGD1wyao2fnejlD03FKCCFknCkq/9/k4NX3szQPZUzEw64KX3SVv17KycWHFBbg8GStyJqRtaNrqLamMEHDMzTO/U46VgkhhKx23MD/YhHDgnUIY7xkyH1Tfrxdiupnh2+kb5cSYHl0LcmaGq6txTVmrj+MkZypbsH/YjpmCSGErDQvHPjnSmm9wDx0MRZSIv5WisU98uN1vD4VE6PvYqBrbnHt/a21NjEervQXvEjO2nTsEkIIOZYUpT/DOmQxDv6hXpy7tajCFSOFAmiArMsr9AMTdG2OrleMhz8jHb+EEEKWGhlarymi/5J9sGJVRP8DF4efga+fPLXp4MIAZCeGTYtrtb9X1+4haxmrS85eueavSccxIYSQw2X2xv6LpUx9yjxMsWJybfdJAdDXE24XHxspB0Ab6NpdXMOylv0+a61j5fQs1jM5Hc+EEEIOTlH6063DEyvjSimr+t6aMWwxSwDQcotr29+sa93aA1gpf3o6pgkhhPSq/oYi+nn7wMSxkAH+SFGFW2WoX1of8kDHXbq49mUPGHsDx8rfqGd1OrYJIWQ6I8Plj+xDEssWw6Ou8rtd9NuMYQ5MH90Lsid0b5h7BsvmYnh3Or4JIWR6UsyHl8pQucU6GLEM0T9elP7O4ev9rMENYJHsEd0ri3vG2EtYssWzu/+SdJwTQkiHc9GpP+lK/wHrMMQS6WfAR3+3q8JV5oAGcGSyd3QPDfeStcewJHqW65meTndCCOlWZqvwS/I39T3WAYil8A8WZX+n/PPHzWEMYFl0Ly3uKd1b1p7D0eiZrmd7OuYJIaT9mdm98bgi+g9bhx6OTIbrD3ulv3N2IVxWH7oAVo/uMd1r8s98F/ZYyBmvZ3069gkhpJ3pDfyr5ED7snnQ4bDcQD+3vb+zWOC7q8AkDfdc9Dcu7kF7f+Jw/H165qfjnxBC2pN1t2x8miv9ufbhBosb+B/p/+3mYv9ya6ACmDTZi7onZW9aexY2Pft1BqRxQAgheUcO+V+UQ3+vdaBhlIvhm8Pv8FThE6ODE0DjdG/qHpW9au1hjJLrtldnQRoLhBCSZ+Rg/9/WIQaDvjMA310F2kX27PAdCaw9jRE6E9J4IISQfDJbnvA8F/1nrYMLB8g1+lERw+3yz39lDkUAraB7WPfycE8bex0HDGfDzuOfn8YFIYQ0m2LgT5O/VfPJNEfgSv838uMuV/lzrSEIoKVkTxdVWEh73Nz/GH7nVWaEPy2NDUIImXxO/fGpP+kGc/qdB/OgwvA7Dfv03QHcgjHwAHSH7PHhXh/uefs8gP4lPnxUZ0caI4QQMpkUce5kV/rbrIMJogpflx+vGRluADpP934Rh2eAfT5MueHskBmSxgkhhIw3ciC/wzqMMDyQ7+2V/SutYQZgushfYOUs8PdaZwWEzJI0VgghZPXzgoWTf7Yo/VbzAJpyLoYv9qK/xBpeAKbb8GyQM8I6O+C3Pn/nhmemMUMIIauT2YF/hRwyD4weOlPvS2KLNawA4GDprNAzwzpLptkDOmPSuCGEkJXFDfyfGAfNVHPR3+tiuKw+mADgqIZnR58PaanRWZPGDiGELD8zu8PTpaBdbh0w08pV4StFFa4whxEALEM6S75inTXTSmeOzp40hgghZGnpVf0NcqDeZR0s08jpfyEcw6cPHjoAsBqGZwvvQvB35JrcpTMojSNCCDlyXNX/DeswmUYyTL7pov9sfdAAwKrTs0bOHOssmkY6i9JYIoQQO67k9axKBoi+ifgOc7gAwBgNzx4+yGBIZ1IaT4QQciAvKE/4p3JATP3rWeUa6Mc23mANEwCYpMWziI+S1dmkMyqNK0LItKe3EE6Uw4HXs5bh1mIhnG0NEABogp5JRSVnk31mTZO7dFalsUUImdb0YvhN44CYKvK3+XuLyHuxAsjX4hnFp3DpzErjixAybZFD4L31Q2Ga6GvIXNn/jDUkACBPcmbx+tf3pjFGCJmGrN+1/hlF9NuMw2AquIH/kfxY2UMBAPI3PMMWzzLznOs8mWE6y9JYI4R0NTMDf1JR+rvNg2AKuBi+OFuGC6xBAABtMjzL5Eyzzrrp4O/WmZbGGyGka5mt/Mtd6b9vHwAdV4UHihiutA5/AGgzPdvknHtg5NybAjrTdLalMUcI6UpmS/9ma9N3nYthv5RW3t4KQOcNzzo984yzsOt0xqVxRwhpe4rSn2Ft9K6Tv4nvcbF/jnXAA0AnDc88v8c6E7vPn5HGHiGkrSmi/7C9wbtLDu1H5MerzUMdAKbA4hk4PAvNc7KzZOal8UcIaVPW71r/JNnAl5gbu8Nc9Ltd1T/LOsgBYKroWShnonVWdprMPp2BaRwSQnJPEeeeVZR+p7mhO8rF8G05qLePHNwAgO16RlpnZ3fJDJRZmMYiISTXyN801+tbhNgbuZtcFT5vHNQAgIPJWWmdod0ls1BmYhqPhJDcUlT+P8pGnabXND3oot9mHtAAgFGLHz7zYO0s7TCZiTIb05gkhOQS2Zyn2Zu2m1zpbzIPZQDA0UV/k3W2dpc/LY1LQkjTkRL3P+2N2j0uhq/Lj1vNgxgAsGTDs3TxTDXP267RWZnGJiGkqchG/IC1QbuoV4Zd1uELADh2erZaZ24X6cxM45MQMunI35Q/ZG3MDnpY8HGtADAmesams9Y6g7uF93olZPKRvzWeZW7I7rlLfNw6aAEAq0fP2nTmWmdxx/iz0jglhIw7UlrPtTdi59xgHa4AgPHRs7d2FnfTwH8yjVVCyLgih8omcwN2ywOu7G+uH6YAgEnpb9azuHY2d448101pvBJCVjsuhi3WxuuUKtw6eoACAJqgZ7J5VneIztY0Zgkhq5Ifr/kJF/3l1obrCnl+fyM/Xm0dnACA5gzP5sUz2jy/u0BnrM7aNHUJIceamd0zT5YN9Wlro3WFHIx7i7J/Xv2wBADkIZ3Rclbb53gX6KzVmZvGLyFkuZnZsfE4OSiusTZYh8SDD0cAQL70zK6d4Z3iSn+Nzt40hgkhS01x20k/5WKH/8vOGB6VQ3B7/VAEAGRvu57h5tneAfL8rtcZnMYxIeRocQP/z2XjdPlvtffPluGCgw5BAECL6BmuZ3ntbO8MeY5RZ3Eay4SQw6VXHf9sF/3N1kbqiC/UD0AAQDvpmV474ztDZ7HO5DSeCSH1zJQn/IxslNusDdQN/kbr4AMAtJee7faZ3346k3U2pzFNCHkiM7s3HldEP29tnA54tCj7V1oHHgCg/fSMXzzrzRnQbjKbdUancU0I0cjmuHpks3TD/a7qn28ddACADpGzXs/82gzoiqvTuCaEFKXfamyS9qt4PSsATBs9+82Z0Hp+axrbhExvZDOcN7o52s9FXs8KAFNLZoA1GzrgvDS+CZm+yN/ePmJsinaL/tFeGXg9KwBMOZ0FOhPMWdFq/iNpjBMyPSlieJ+9IdrMP+jKuU3WAQYAmEZzm3Q22DOjxWSGp3FOSPcjm/gMcyO0mr+vWAhn2wcXAGBa6WwYzghzdrSZPyONdUK6G/lb2u/ZG6C9XOn3WIcVAAAH+D3WDGk1melpvBPSvcyW/s3mwm+z6G+xDygAAA6lM8OcJS2msz2NeUK6k14Mr7MWfLvxzgEAgOXR2WHPlPbSGZ/GPSHtT6/yL7cWepvNRv9Z60ACAOBodIZYs6XNdNansU9Ie9Nb8KdYC7ytXPT7i+i3WQcRAABLNZwlOlOMWdNWOvPT+CekfZmZD2tlY37NWtzt5B8SF1kHEAAAy6UzZXG2WDOnhWTm6+xPNYCQ9mTt9rVPkb9JlubCbiFX+q+Kc62DBwCAY6ezxX/Vmj1tpLNfO0CqA4S0I7IZN1sLup383aMHDQAAq0dnjT2D2keez+ZUBwjJP/I3xz+1FnI7+TvrhwsAAOOgM8eeRe2jXSDVAkLyjRv4t1sLuKW+YB0sAACMi86e2ixqLe0EqR4Qkl9kw73SWritFMPt9cMEAIBJ0BlkzqYWkufzylQTCMknrtzQd6X/vrVoW+jW+iECAMAk6SyqzaZW0m6gHSHVBUKaTxHnniWb7K+tBds6fIQrACATOpPMWdUy8lz+WrtCqg2ENBtZkNdbC7WFdh18YAAA0DSdTbVZ1UryXK5PtYGQ5uKiP99aoC1U1Q8LAAByoDOqNrNaSTtDqg+ETD5FDP/HWpitE0O0DgoAAHKhs8qcYW0j3SHVCEIml6Lq/7a5INsm+nnrgAAAIDc6s8xZ1jbSIVKdIGT8KebDS82F2DZVuME6GAAAyJXOLnOmtY10iVQrCBlfZm/s/7RsnL3mImwTSisAoKW6UF5d9Pdqp0j1gpDxRBba5dYCbBle0woAaDWdZbXZ1jraKVK9IGT142J4t7Xw2sSV/ibrAAAAoH38TdasaxPtFqlmELJ6kQ3ShY9z5ROxAACdorOtNutaR54HHwtLVi9uV/8FRekfsRZbi9xR3+wAAHSBzrjazGsZ/4h2jVQ7CFlZZEHttBdaS0R/t7XRAQDoCp115gxsDb8z1Q5Cjj0uhg/ZC6wdXOzvtTY4AAAd1O53/anCh1L9IGT5kQ3wJnNhtYSL/qtuwdzYAAB0j848mX3WTGwLeR5vSjWEkKWnV/U3WAuqLVzpvyE/fnxkUwMA0GGLs284A8352AbaQVIdIeTomdm98bgi+jutxdQO/qFeGc6zNjQAAF2nM1BnoT0jW0A6iHaRVEsIOXJkwVxoLqQWkL9lPiKbdlN9EwMAMGVkFrb4HYGki6RaQsjhI39DO91cQK3gf9Cr+pcYmxcAgKmjM1Fnoz0z28CfnuoJIaNxC/5l9sJph14ZrrY2LgAA00pnozUz28IN/MtSTSHkQGZ2zzxZ/mbT3te1Rn+jtWEBAJh2OiPN2dkK+nrXmSenukLIYtxgTv9LRGPBtAIf5QoAwBHorKzNzhbxH0l1hRB9XWt49egiaQcX/T3WBgUAADUyM61Z2hKvTrWFTHPWzYd/UcTwLWOB5K8KD8wu9D9mbk4AAHAInZk6O82ZmjvpKtpZUn0h0xpZCFvMBZK/786W4QJrYwIAAJvOTp2htZnaCk46S6ovZBrjSv82a2G0gWy8y6wNCQAAjkxnqDVb20C7S6oxZJrSi3PrrAXRBrLprqlvQgAAsCzXWDO2DbTDpDpDpiUu+uusxZA7+ZtWaWw+AACwbL60Zm3utMOkOkOmIUUV/tBaCLmThbrb3ngAAOCYyGy1Zm72pMukWkO6nGI+vNRcAPn7srnhAADAiuiMrc3cdpBOk+oN6WLW71r/pCKGO8ybnzHZVN8ryv559Y0GAABWLs1YmbX2HM6WdBrtNqnmkK6liP7D5o3PnGym7QdvMAAAsOq2WzM4e9JtUs0hXcrswP+aecPzF43NBQAAVpnO3NoMbgXtOKnukC5k/a71/6CILXz9SvR3WxsLAACMh85ecybnTDqOdp1Ue0jbU5T+TPNG5yz6h1zVP8vaVAAAYExk9uoMNmdzzqL/YKo9pM0pyv5LzBucuV7Vv8TcUAAAYKx0BluzOX/9l6T6Q9qaIoYF++bmy8VwnbWRAADAhMgstmZ01qTzpPpD2pii9KebNzZnMdxubiAAADBROpPNWZ01f3qqQaRNmb2x7+wbmrX7rY0DAACaobO5Nquzt648sZfqEGlLiui3WTczX/4x2SCb6hsGAAA0apPOaHt2Z0o6UKpDpA2Rm/b6kZuYOVeFq4zNAgAAmiYz2prdWZsPr0+1iOSc9bvWP6OI4VvmTcxVDLeYGwUAAGRBZ7U5w3MlXeh50olSPSK5pij9WeYNzNcD1gYBAAB50Zldm+FZc9KJUj0iOaZX9v+TdeMyt8XaHAAAIC86s2szPHvajVJNIrnFxbDbumm5kk0wqG8KAACQtYE103Ol3SjVJJJT3MD/kXXDcuWiv9fYDAAAIHcyw63Znispr+9OdYnkkF7VP8G6UdmK4XEX++ebmwEAAORNZrjOcnPGZ0q7UqpNpOnI3yS2WzcpV/J4d5gbAQAAtMW11ozPlXalVJtIkynK/qnWDcqXv9NY/AAAoGV0ptuzPlf9U1N9Ik3FRd+mzxF+WJxtLX4AANAuOtPTbLdmfna0M6X6RJqIK/3/sG5MrvTb9NbCBwAALdW2lytKd0o1ikwyM/Ph6bJYvmPdlCzx6VgAAHRSmz5VS7uTdqhUp8ikIn9j+FPrhuRIHus3rIUOAAC6wn/D6gA50g6V6hSZRHpxbp11IzK21V7kAACgC3TW12Z/1rRLpVpFxh1ZIJutm5ClgeclAgAATAGd+WYXyJA83s2pVpFxRj9z17oBOXIDv6++qAEAQIfJ7Lc6QY60U6V6RcYVV/rSuvhZiuHT5qIGAACdpLPf7AQZ0k6V6hUZR3qlf7N14XMki2GPtaABAEDn7bG6QY60W6WaRVYz/2rvxr8vF/hr9QueJ/9YUfXPNRYyAADoOO0Awy5gdoTsfE07VqpbZLUiC+A9xsXOkqvCddZCBgAAU0K6gNUR8uTfk+oWWY286Gb/XPtCZyiG+8wFDAAApor0gvtGekKmtGul2kVWGimD51kXOUeyUC+uL1wAADCVLra6Qpaka6XaRVaSIvr15gXOUfQLxqIFAABTSruB2RlyJJ0r1S9yrHHRn29e3My4GL5pLVgAADDlpCNY3SE32rlS/SLHElduON66sFmqwhXmYgUAAFNNO4LZHTKk3SvVMLLcyM3eZF3U3LjK764vUgAAgL8jXcHqELmRx7op1TCynKxbCHPWBc1ODI+72D9nZIECAAA8QbqCdgazS2RGO1iqY2SpKaK/0LqYuZHFOBhZnAAAAKMGVpfIjnSwVMfIUlLEuWBeyOz4h4xFCQAAYNLuYHeKzEgXS7WMHC1yUy8yL2JmXNn/jLUoAQAAbP3PWJ0iP/6iVMvIkeLKDX37AmYmhi/bCxIAAODwtEOY3SIz2slSPSOHi9zQzdbFy9DW+kIEAAA4Gu0QtU6RJXmsm1M9I1Z6C+FE68JlJ4Y76osQAABgqbRLmB0jM9rNUk0j9RTRX2JdtKzE8EN5nH9pLUIAAICl0C4x7BRW18iJdLNU08jBKeLcyeYFy83AL1gLEAAAYDm0U5hdIzfS0VJdI0+kKH0bXu/xsLXwAAAAjoV2i1rXyJDfmuoa0bTmu61l2GEtOgAAgGOh3aLWNfLEd10PpKj8X5oXKS/3WwsOAABgJbRj1DpHfqSrpdo23ektbHiOeYFyU/lt1mIDAABYCe0YZvfIjHa2VN+mN27g32tdnJy40t9jLTQAAIBVco/VQXKinS3Vt+lMmA9PLUr/iHVxMsOHDQAAgLHRrlHrHhnyj2h3SzVu+lLE8N/tC5MPF/luKwAAmASf/XddtbulGjd9kVK4x7woeeG7rQAAYOy0c9Q6SHa0u6UaN13pDfyrrAuSmS9ZCwsAAGAcihi+ZPSRrGiHS3VueiJP/Nr6hchNr+pfYi0qAACAcdDuYXWSzFyb6tx0pA0fOOBKf7e1oAAAAMbL3211k6xM0wcStOQDB7bYiwkAAGB8ioWwxegleZmWDyRoxQcORL7bCgAAmlO04LuuU/GBBG34wIEi8t1WAADQHO0iZkfJSOc/kKAlHzhwl7WAAAAAJkk7Sa2jZKbjH0jQig8cKPubrcUDAAAwSYV0EqurZKXLH0ggNyHrDxxwVfhifdEAAAA0RrqJ1VlyIY+xmx9IUMS5X7GecE56Zbh6ZMEAAAA0JfrPWJ0lK9LxUt3rTlzpLzafbCZc7O81FwwAAECTpKNY3SUX8hgvTnWvG3n+zg3PtJ5oTuSibz9kkQAAAORhu9VdcqJdL9W+9qeI4R3Wk8xG9A8aiwQAACAL2lXMDpML6Xqp9rU/LvrbzCeZi+g/Zy0SAACAHGhXMTtMJrTrpdrX7vQW/CnWE8yFi+F71gIBAADIinQWq8vkQjtfqn/tTVH6s6wnl43oF8zFAQAAkBHtLGaXycXAn53qXzsz+/nZf1jE8Lj55PLwo6Ly51qLAwAAICfaWYbdxe40zZPOp90v1cD2xcXwRvOJZUIWwRfqiwIAACBjX7A6TS60+6Ua2L7Ixb3BelK5kMd38UELAQAAIHd5vy++dL9UA9uVYj78vPWEcsEHDgAAgFbK/AMJtAOmOtieuNJ/wHwymZAbzwcOAACANsr6Awm0A6Y62J7Ig873jXL5wAEAANBi2mXMjpMB7YCpDrYjs5X/NeuJZIMPHAAAAC2mXcbsOLmIc7+eamH+kQd85cgTyIT8LWC/tQAAAADaxe+3uk4mrky1MO/0FjY8x3jw2ZCbfJt98wEAANok74/U106Y6mG+KWJ4h/XgsxHDFvvmAwAAtId2GrPr5EI6YaqH+UYe5Lz54DPgYvi6deMBAABaSbqN1XmyIJ0w1cM888KBf675wDMhN/j6kRsOAADQXtdbnScXL5JumGpifimq8HvWg85CDD8sFsLZxg0HAABoJe02w45jdZ8c5PxygSL6jF8m4PdYNxwAAKDNitLfaXWfLEg3TDUxr2T/MoHKb7NuNgAAQKtJx7G6Ty60I6a6mE+KmPPLBPxD5o0GAADoAO06ZgfKgXTEVBfzSVH6G80Hm4do3WQAAIAu0K5T6z75yO3lAjPzYa35QDPRK/vnWTcZAACgC7TrWB0oF9oVU21sPjm/TEBu5j31mwsAANA9/h6rC2Uhp5cLFDHnlwn4q+ybCwAA0B3aeewulAHpiqk2Npu8Xybgv2vdWAAAgC7S7mN3ouZl8XKBXjX3u9aDy0IMt1g3FQAAoIu0+5idKAPaGVN9bC55v0wgbLVuKgAAQBdp96l1oXw0/XKB3sKG55gPLAOu9PusGwoAANBtfp/VjXKg3THVyMmnFzN+mUDFywQAAMD00Q5kdqMMaHdMNXLykYtzrfWgMsHLBAAAwNTRDlTrRNmQx3dtqpGTzczujcdZDygHvEwAAABMt3xfLqAdMtXJyUUuyq9aDyYLvJsAAACYYjm/u4A8vl9NdXJycTF8yHowWah4mQAAAJhe2oXMjpQB7ZCpTk4uRfR3Ww+maXIxvmPdQAAAgKkincjqSo2TDpnq5GTSG/gXmg8kB7xMAAAAIO8PI5AumWrl+ONK/zbrQWSClwkAAICpp52o1pGyoV0y1crxp4h+m/UgmsbLBAAAAA6S78sFtqVaOeb8eM1PFKXfbz6IhskN+vzIDQMAAJhen7c6U/P8fu2UqV2OL7049+/sB5AFXiYAAACQaDeqdaVsaKdM9XJ8cQP/XusPbxovEwAAADBk+nIB7ZSpXo4vuX7+rYt+t3mzAAAAppl0JKs7NS6GW1K9HE9mdp34L80/OAdV+LR5swAAAKaYdiSzO2VAu2WqmaufXgy/af2hmTjbulkAAADTTDtSrTNlQ7tlqpmrH/kDNtX/wBy46L9q3SgAAACIKnzF6lAZ2JRq5uqniOFbxh+Yg2jeJAAAAOh3XWOtO+VBumWqmaub3nw40fwDcxDDFusmAQAAYFhct4z0p0xox0x1c/XiBv7t1h/WNBfD96wbBAAAgAOKKnzX6lJNc6V/e6qbqxd5whdbf1jT5HHtOfimAAAAwBDDHqtLNU0e28Wpbq5e5Itm+aJeeVzX/N0NAQAAgEl60zX1HpUD/Y/sU91cnfQWNjzH+oPy0D/XujkAAAA4QDuT3aWaNzMf1qbaufK4gX+t9Ydk4AHrxgAAAGCUdqdal8qCq/xrU+1ceVzp/9z6Q5omj+sm66YAAADA4m+yOlXT5LH9eaqdK4+LeT7J2TJcNnpDAAAAYNHuZHWqpmnXTLVzZZnZvfE46w9onn/MuiEAAAA4PO1QdrdqlnbOVD+PPW7gX2Z98aZJM7/HuhkAAAA4AulQVrdqmnbOVD+PPfJF3mV98cZVYd68GQAAADgs7VBmt2qYK/vvSvXz2ONi2G598QxstW4GAAAADk87VK1TZUE7Z6qfxx5X+m9bX7xhP7BuBAAAAI5Ou1StWzVOO2eqn8eWYiEU1hduXPRfs24CAAAAjk67lNmxGuYGfjbV0OVHntQbrC/auCrcYt0EAAAAHJ12KbNjNa3yb0g1dPlxMXzC/KKN81dZNwEAAABHp13K7ljN0u6ZaujyI0/qTuuLNm4hfNK6CQAAADg67VJmx2qcvzPV0OXlebvWP8P+gs1y0e+zbgAAAACWQTqV1bWaph001dGlpzfwp1hfrGlyofeMXHgAAAAs1x6razVNO2iqo0uPi+Et1hdrmiv99caFBwAAwLL4662u1TTtoKmOLj1F6T9ifbGmuSpcbF98AAAALJl0KqtrNc9/JNXRpUd+0077izXJP2ZeeAAAACybdiu7czXJ70x1dOmRJ/Ow/cUadV/9ggMAAODYaLeqda3GyeN6ONXRpWU2zv0b6ws1LvqF+gUHAADAsdFuZXauhmkXTbX06CkG/petL9K4KlxhXXQAAAAsn3Yrs3M1TbpoqqVHTy+Gd5pfpGlV/1zrogMAAGD5tFuZnath2kVTLT16XOkvsL5Ik9zAP2pdcAAAAKzI96zu1STtoqmWHj0u+tusL9IkeQJfMS40AAAAVsR/xepeTdIummrpUXLRqT9ZxPAj64s0qgq32hcbAAAAx0o7ltm9miRdVDtpaqeHTy/OrTO/QPN2WBcbAAAAx047Vq1zZUE7aaqnh488gddYv7lpvegvqV9oAAAArIx2LKt7NU0e22tSPT18iir8sfWbm+bK/ln1Cw0AAICV6p9lda/GSSdN9fTwKaLfZv7mBrnS77MvNAAAAFbO77M6WKOkk6Z6evjIg99r/uYGyWO659CLCwAAgFV0j9XBmiSPaW+qp3bW7Vj3NOs3ZmBX7eICAABglWjXqnWvLGg3TTV1NBm/o8DV1kUGAADAymnXqnWvLBzxnQWKOPcr1m9q3MBfaF1kAAAArJx2LbODNU26aaqpo3Glf5v5mxokj+n71gUGAADAavLft7pYk7Sbppo6GvnJD1i/qVHRP2hfXAAAAKwW7VxmF2uQdtNUU0cjv2BL/Tc0zcWwx7q4AAAAWEXSuawu1rAtqaaORlrtTcZvaJQ8ptK8uAAAAFhFvrS6WJO0m6aaOpqi9A9Zv6lJs5X/rH1xAQAAsFq0c1ldrFHRP5Rq6qFZv2v9PzF/Q8OkaV9qXVwAAACsJn+p1cWaph011dUDyfU9XHtlOM++uAAAAFgt2rmsLtY0871ci8r/svWLmyTNn7fCAgAAmJj83hJLO2qqqwciDzS/93CNfp99UQEAALDqpHtZnaxJ2lFTXT0Q+ZcZvodr+LJ5UQEAALDqtHuZnaxJVXh/qqsHIg80u/dwFXdYFxUAAACrT7tXrYs1TzpqqqsH4iLv4QoAADDdMnwvV+moqa4eiLTZb1m/uEm8hysAAMDk5PleruFbqa4uhvdwBQAAgHYvq5M17ZD3cnU3+VnrFzWN93AFAACYnFzfy9UN/GyqrWvW9Mr+v7d+UZNc9D+wLigAAADGSDqY1c2apF011dY1a+RfvLr+C5qm7yNmXkwAAACMT4bv5SpenWqrvodreKvxC5rFe7gCAABMnHYws5s1SB7XW1Nt1ZcK+DOsX9Qw3sMVAABgwrSD1TpZBvwZqbbqW2H5D9q/qDmu6t9kXUwAAACMkXQwq5s1y5+ZauvwwwfOt39Rg6owb15MAAAAjI12MLObNciV/oJUW4fF9dPWL2qSq8K11sUEAADAGEkHs7pZw65KtXX4qVkLxi9olKv8p8yLCQAAgPGRDmZ1s0bFsCvVVv2Oa9hr/qImVWGreTEBAAAwNtrBzG7WIO2qqbYO/+OsR6xf1CS3EDZZFxMAAABjJB3M6maNkq46LK0zu2eebP6Chrmqf455MQEAADA+0sGsbta0tdvXPmXNCxZO/lnrJxsV/Y/MCwkAAICx0y5mdrQGvXjnhmeuma36zvrJJrno91sXEQAAABMgXczqaI2aD8UaV4WN5k82SD8j17yIAAAAGD/pYlZHa1Jv4E9ZM1v5l1s/2SQXw9fNiwgAAIDxky5mdbQmzQ78K9YUpf8t6yeb5Mr+XvMiAgAAYPyiv9fqaI2K/g1rXOl/3/zJBknL32NeRAAAAIyfdDGrozVJHtMfrJF/eG/9J5rWi3O3mhcRAAAAY6ddzOpojYrhffpSgTPNn2yQi760LiIAAAAmQLqY1dGa5c9cow/O/snmuCpcN3IBAQAAMBnSxayO1iR9XGukUef46Qg7Ri4gAAAAJkK7WK2bNU47q/7HWRdYP9mk2cp/1rqIAAAAGD/tYlZHa5J2Vn2pwGbrJxt2df0CAgAAYDK0i9W6WePkcW1eU0S/zfrJJrmq/6n6BQQAAMCESBezOlqjpLPq22FdNfITzbvSvIgAAAAYO+1itW6Wg6u0uOb34tuyf7l1EQEAADAJ/cutjtawHfpSgXnjJxrlSn+pfREBAAAwfv5Sq6M1Sjqrfsd118hPNG+LfREBAAAwbtrFat0sB7v0fVxvN36iUXLBLq5fQAAAAEzMxVZHa5J2Vimu4YvWTzbsr4wLCAAAgAnQLlbrZo3Tzqrv47rX+skmzZbhgvoFBAAAwGRoF7M6WpPkce3Vlwp8zfrJJvXK/nn1CwgAAIDJ0C5mdbQmaWddU8TwLesnm+RKf651EQEAADAJ/lyrozVKOuuaovSPmD/ZrI/bFxEAAADjpl2s1s0y4B/R77g+bv9kc1zl/8K6iAAAAJgA6WJWR2uUdFZ9H1f7JxtkXkAAAABMjNXRmsZ3XAEAAHCofL/jymtcAQAAcIB2sVo3y8Dia1x5VwEAAAAcJNN3FcjzfVwD7+MKAADQkGzfx1UeHJ+cBQAAgL+T8SdnhS9aP9mwv6pfQAAAAEyGdrFaN2ucdlZ9qcDt1k82SS7YxfULCAAAgIm52OpoTdLOqu/juqv+ExnYYlxAAAAATIB2sVo3y8GuNUX088ZPNMqV/lLrIgIAAGAS/KVWR2uUdFb9juuOkZ9omCv7l9sXEQAAAOPXv9zqaA3bocX1qtq/zMGV9kUEAADAuGkXq3WzHFylLxXYZvxEo1zV/5R1EQEAADAB0sWsjtYo6az6Pq6bzZ9sUK8MV49cQAAAAEyE9LGr6/2safK4Nktx9dm9wexs5T9bv4AAAACYDO1iVkdrknZWfR/Xc6yfbNgO6yICAABg/LSL1bpZ47Sz6ksF9MGZv6AprgrX1S8gAAAAJkS6mNXRmqSPa01R+jOtn2ySNOpy5AICAABgMqSLWR2tWf5MfTus947+RLN6ce5W8yICAABg7LSLWR2tUTG8T//jrN83f7JBLoY91kUEAADABEgXszpak+Qx/YG+VOC3rJ9skov+XvMiAgAAYAL6e62O1qjo37BmtvIvN3+yQdKov25fRAAAAIyddDGrozVpduBfscZVYaP1k01y0e8zLyIAAADGT7qY1dGa1Bv4U9bMVn1n/WST5GLtNy8iAAAAxk+6mNXRGjUfijUvWDj5Z82fbFL0PzIvIgAAAMZOu5jZ0Rr04p0bnrlmZvfMk62fbJqr+udYFxIAAABjJB3M6mZNW7t97VPWaKRVP2L9gia5hbDJvJgAAAAYH+lgVjdrlHTVYWnVuBjye8uDKmw1LyYAAADGRjuY2c0apF011Vb9jmvYZf2iJrnKf8q6mAAAABgj6WBWN2uUdNVUW6W4luGqkV/QMFeFa82LCQAAgPGRDmZ1s4ZdlWrrGv3Y1wuMX9CsKsybFxMAAABjox3M7GYN0q6aaqt+x9Wfaf2iJrmqf5N1MQEAADBG0sGsbtYsf2aqrcPieob9ixp1h3kxAQAAMDbawWqdLAP+jFRb9aUC4a32L2pQDF+uX0gAAACMl3Yws5s1SB7XW1NtHf7HWa+u/4Km6Wfk1i8kAAAAxkw6mNXNGvbqVFvXrOmV/X9v/IJGyUX7gXkxAQAAMD7Swaxu1iTtqqm2rlnjBn7W+kVN65XhPPOCAgAAYNVp97I6WdO0q6baumbN+l3r/4n1i5rmSn+pdVEBAAAwDv5Sq5M1Tbtqqq2LKWL4lvULmzRb+c/aFxUAAACrTbuX1ckaJR011dUDcdFn955d0vpL66ICAABgHHxpdbImaUdNdfVApM1usX5xw3gvVwAAgAnR7lXrYs2Tjprq6oEUVXi/+YubxHu5AgAATIx2L7OTNUk6aqqrB+JK/zbzFzdI30fMuqgAAAAYgwzfw1U7aqqrB1JU/petX9wkeaDfNy8qAAAAxsB/3+pkjZKOmurqgfTi3DrzFzeM93IFAAAYv1zfw1U7aqqrB8J7uQIAAEyzlryH6xMpon/I+g1N4r1cAQAAxi/P93D1D6WaOhpp2ryXKwAAwFTK8D1cpZummjoa+QXZvZeri2GPfXEBAACwaqRzWV2sYaPv4fpEpNV+wPgNzYr+QfPiAgAAYNVo5zK7WIO0m6aaOhr5yfzey5W3xAIAAJiA/N4KS7tpqqmjKeLcr1i/qXEDf6F9gQEAALBS2rXMDtY06aappo4m1/dyFVdbFxkAAAArp12r1r2yYL6H6xNZt2Pd06zflIFd1kUGAADAymnXqnWvLGg3TTXVjjz4vdZvbJI8pnsOvrgAAABYVfdYHaxJ8pj2pnp6+BTRb7N+c5Nc6ffVLi4AAABWjd9ndbBGSSdN9fTwKarwx+Zvbpgr+2fZFxoAAADHrn+W1b0aJ5001dPDR57Aa8zf3LBe9JeMXmgAAACshHYsq3s1TR7ba1I9PXwyfmeBHfULDQAAgJXRjlXrXFk44jsK/F0uOvUnixh+ZH2BRlXhVutiAwAA4NhpxzK7V5Oki2onTe30yHHR32Z+kQa50n/FutgAAABYCf8Vq3s1SbtoqqVHjzyBC6wv0iS5sN8bvdAAAABYkYF/1OpeTdIummrp0dOL4Z3WF2lc1T/XvOAAAABYNu1WZudqmHbRVEuPnmLgf9n6Io2rwhXWRQcAAMDyabcyO1fTpIumWnr0zMa5f2N+kaZFv2BddAAAACyfdiuzczVMu2iqpUuLPJmHrS/UsPvqFxwAAADHRrtVrWs1Th7Xw6mOLj1F6XdaX6xZ/rH6BQcAAMCx0W5ld64m+Z2pji498ps+Yn+xZrkqXGxdeAAAACyDdCqrazXPfyTV0aXHxfAW+4s1y5X+evPiAwAAYBn89VbXapp20FRHl57ewJ9ifbGmyYXeM3rhAQAAsEx7rK7VNO2gqY4uPc/btf4Z1hdrmot+n3HhAQAAsBzSqayu1TTtoKmOLi9F6e+0vmDjFsInzRsAAACAo9IuZXasxvk7Uw1dflwMn7C/aNP8VdZNAAAAwNFpl7I7VrO0e6YauvwUlX+D9UUbV4VbrJsAAACAo9MuZXaspkX/hlRDlx838LPmF21a9F+zbgIAAACOTruU2bGathCKVEOPLa703za/cLN+YN0EAAAAHJ12qVq3apx2zlQ/jz0uhu3WF8/AVutGAAAA4PC0Q9U6VRa0c6b6eexxZf9d1hdvXBXmrZsBAACAw9MOZXarhrmBf1eqn8ce+SIvs75401z091g3AwAAAEcgHcrqVk3Tzpnq57FnZvfG46wv3jz/mHkzAAAAcFjaoexu1SztnKl+rizSzG+y/oCmzZbhMuuGAAAAYJR2J6tTNU27ZqqdK4880T+3/pCmudLfVL8hAAAAOJw8vxkpj+vPU+1ceVzlX2v9IRl4wL4pAAAAqNPuVOtSWXAD/9pUO1eemfmw1vpD8tA/17oxAAAAOEA7k92lmtdb2PCcVDtXJy76r1p/UAausW4OAAAADnGN0aMaJ4/rK6lurl7ki15s/WFNczHsOeiGAAAAwLbH6lJNk8d1caqbqxdX+rdbf1jjqvDd2k0BAABAXQzfM7tUw9zAvz3VzdVLbz6caP1hmdhi3iAAAAB8tIhhi9GfsqAdM9XN1Y086W9Zf2AGonWTAAAAMHw3gVjrTnmQbplq5upH/oBNI39gBlwVvmLdJAAAAIh8/yP7Talmrn56Mfym8Qfm4mzzRgEAAEwx7Ui1zpQN7ZapZq5+Znad+C+tPzQLVfi0dbMAAACmmXYksztlQLtlqpnjSRHDLdYf3DQX/W7rZgEAAEw16UhWd2qcdMpUL8cXN/DvNf/whrkYvmPeLAAAgGkmHcnqTk3TTpnq5fjSi3P/zvrDM7HVvGEAAABTSLtRrStlQztlqpdjzI/X/ERR+v3WA2ia3KDP128YAADAFPu81Zma5/drp0ztcrwpot9mP4hm8XIBAACAg2T6MgHtkqlWjj+u9G8zH0QeeLkAAACYetqJah0pG9olU60cf3oD/0LrQWQhhlusmwcAADBNcn0nKKVdMtXKyaSI/m7rgTSNlwsAAACIfF8mcHeqk5OLXIwPmQ8mBxUvFwAAANNLu5DZkTKgHTLVyclFLsqvWg8mC7xcAAAATLGcXyYgj+9XU52cXGZ2bzzOejA5cKXfV7+BAAAA08PvszpSDrRDpjo52ciFudZ6QJng5QIAAGDqaAeqdaJsyOO7NtXIyacX537XelBZqHi5AAAAmD7agcxulAHtjqlGTj69hQ3PsR5UDni5AAAAmE75vkxAu2Oqkc2kKP1O64FlgpcLAACAqaHdp9aFMuJ3pvrYXLJ+uQDvLgAAAKZI1h860OTLBJ7IzHxYaz24PPjvWjcVAACgi7T72J2oedoZU31sNkX0N1oPMA/+KuvGAgAAdIl2HrsLZUC6YqqNzWe26mf7cgFX+nusmwsAANAx91hdKAfaFVNtbD55v1wg/LhX9s8zbi4AAEAnaNexOlAusnmZwBMpypxfLhCidZMBAAC6QLtOrftkJKOXCTyRIobfsx9sBqJ/yLrJAAAAXaBdx+xAOZCOmOpiPnnhwD/XfLCZcJXfZt1oAACAVpOOY3WfXGhHTHUxr0jbn7cecB78nebNBgAAaLPo99jdJwPSDVNNzC9FlfPLBcIPi4VwtnnDAQAAWki7zbDjWN0nB9INU03ML9m/XKAM19dvOAAAQItdb3WeXGT7MoEnIq0/25cLuBi+btxwAACAdpJuY3WeLEgnTPUw38iDfIf54HMRwxbzxgMAALSIdhqz6+RCOmGqh/mmt7DhOeaDz4Qr/W3WzQcAAGgXf5vVdXKhnTDVw7wjD/bK+oPPhdzk/fbNBwAAaBO/3+o6mbgy1cL8U8S5XzeeQD6i/5y9AAAAAPKnXcbsOJmYrfyvpVrYjsjfAh60nkgWon/QWgQAAABtoF3G7DgZ0A6Y6mB7Ig/6A9aTyYXc9O31RQAAANAC261ukwvtgKkOtifFfPh568nkwpX9vcZCAAAAyFx/r9VtsiEdMNXBdkUu7g3mE8qEq8LFo4sBAAAgU9JdrE6TC3mMN6Qa2L64GN5oPalcyMX9wiGLAQAAIG9fsDpNLrT7pRrYvsx+fvYfFjE8bj2xLET90Z9rLAoAAICsaGdZ7C6Zks6n3S/VwHamGPizzSeXi+gXrMUBAACQE+0sZpfJhj8r1b/2prfgT7GfXB5cDN+zFgcAAEBWpLNYXSYX2vlS/Wt3XMz7I8mK2OcDCQAAQLa0q5gdJhPa9VLta3+KGN5hPcls8IEEAAAgYzl/4MCQdL1U+9qf5+/c8EzzSWZEFgUfSAAAAHKU9QcOKO16qfZ1I3LRM3/fMT6QAAAA5CjvDxxwpb841b3upIhzv2I92Zz0Sv8Ze8EAAABMnnYTq7NkRTpeqnvdityAPeYTzoSrwhfrCwYAAKAx0k2szpILeYx7Us3rXooY/rv1pPPS3zyyaAAAACauv9nuKhmRbpdqXvcS5sNTi9I/Yj7xfNxlLx4AAIDJ0U5S6yiZ8Y9ot0s1r5txA/9e+8lnJIYt1gICAACYBO0iZkfJiHa6VO+6m97ChudYTz4v/m5rEQEAAExCEf3ddkfJh3a6VO+6naLyf2ldgKws8F1XAAAwedJDsv9uq3a5VOu6nyLOnWxehIw4vusKAAAakf93W7XLpVo3HZEnfe3IRchMr+pfYi8oAACA1afdw+okmbk21bnpSW/gX2VciLzE8CVrUQEAAIyDdg+zk2REO1yqc9MVF33WH0iQbLUWFgAAwGrSzlHrINnR7pZq3PRF37TWuig5caW/x1pcAAAAqyr6e6wukpUuf+DA0dKSDyRQfNcVAACMjXaNWvfI0BR84MDR0oYPJJAFxXddAQDAGOX/3dap+MCBo6UdH0ggKr/NXmgAAADHTjuG2T0yMzUfOHC0tOIDCcpwv7XYAAAAVkI7Rq1z5GeaPnDgaGnDBxIkO6wFBwAAcCy0W9S6Rp6m7QMHjpai9C14UXJ42Fp0AAAAx0K7Ra1rZMhvTXWNPJHWfNd14BeshQcAALAc2inMrpEbvttqp4g+/485i+GH8jj/0lqAAAAAS6FdYtgprK6RE+lmqaaRenoL4UTzouUmhjusRQgAALAU2iXMjpEZ7WapphErcjM3WxcuQ3woAQAAWDbtELVOkSV5rJtTPSOHiys39K2Ll50YvlxfiAAAAEejHcLsFpnRTpbqGTlSitJfZF3A3Liy/xlrQQIAANj6n7E6RX78RamWkaOliHPBvoi58Q/ZixIAAGCUdge7U2RGuliqZWQpKaK/0LyQmZFFOKgvSgAAAMPA6hLZkQ6W6hhZatYthDnzYuYmhsdd7J9jLE4AAIBF0hW0M5hdIjPawVIdI8uJ3OhN1gXNjav87pEFCgAA8ATpClaHyI081k2phpHlxpUbjrcuapaqcMXIIgUAAFNPO4LZHTKk3SvVMHIscdGfb13Y3LgYvmktVgAAMOWkI1jdITfauVL9IseaIvr11sXNUvQL5oIFAABTSbuB2RlyJJ0r1S+ykhQxnGde4AzJIr24vmgBAMBUutjqClmSrpVqF1lpXnSzf655kfN0n7FwAQDAlJEyeJ/RE7KkXSvVLrIaKUr/HutC58hV4TprAQMAgCkhXcDqCHny70l1i6xW/tXejX9fLu7XRi92jvxjRdU/11zIAACg07QDDLuA2RGy8zXtWKlukdVMr/RvNi54lmTh7qkvZAAAMA38Hqsb5Ei7VapZZByRxVBaFz5LMXzaXtAAAKCLdPabnSBD2qlSvSLjSq/s/yfr4ufIDfw+a1EDAICOktlvdYIcaadK9YqMM7IwNls3IEsDf8vIogYAAJ2jM9/sAhmSx7s51Soy7vTi3DrrJmRsa31xAwCA7tBZX5v9WdMulWoVmURc6f/UuhE5ksf6DWuRAwCArvDfsDpAjrRDpTpFJpWZ+fB0F8N3rBuSpRh4yQAAAB2kM96c/RnS7qQdKtUpMsnI3xj+h3VTciWLZbu14AEAQEvJbLdmfq60O6UaRZqIi/5268Zk6mFxtrnwAQBAq+hMT7PdmvnZ0c6U6hNpKkXZP9W6Ofnyd1qLHwAAtIvOdHvW56p/aqpPpMm079v04dr64gcAAC0Sww5rxudKu1KqTaTp9Kr+CdZNylYMj7vYP9/cCAAAIG8yw3WWmzM+U9qVUm0iOUT+JvFu60blykV/r7kZAABA3mSGW7M9V27g/yjVJZJTpLzutm5YrmTxD0Y2AwAAyNnAmum50m6UahLJLfqZu9ZNy9wWY1MAAIDM6MyuzfDsaTdKNYnkGFf6s6wbl7EHrM0BAADyojO7NsMz589K9YjkmuftWv+MIoZv2TcwU3yqFgAAWWvTp2MNSRdaL50o1SOSc4r58HrzJmbMVeEqa6MAAICGyYy2ZnfmXp9qEWlDiui3GTcxY/4x2RybRjYLAABo0iad0fbszpR0oFSHSFuyrjyxZ97MvN1vbBgAANAQnc21WZ292Rv7LtUh0qbI35BOt25o1mK43do4AABgsnQmm7M6a/70VINIGyOLbsG+sflyMVxnbSAAADAhMoutGZ016Typ/pC2pij7LzFvbuZ6Vf8ScyMBAICx0hlszeb89V+S6g9pc4roP2jf4IxF/5Cr+mdZGwoAAIyJzF6dweZszpo/M9Ue0vas37X+HxQxfNm+0RmL/m5zUwEAgLHQ2WvO5JxJx9Guk2oP6UJmB/7XzJudv2htLAAAsLp05tZmcCtox0l1h3Qp8reoD1s3PHeymbbXNxcAAFhV260ZnD3pNqnmkK5l/a71TypiuMO88RmTzfS9ouyfV9tgAABgFaQZK7PWnsPZkk6j3SbVHNLFFPPhpebNz9+X6xsNAACsnM7Y2sxtB+k0qd6QLqeowh+aCyBzLvrd1oYDAADHSGarNXOzJ10m1RoyDZGF2r43Fhau9KW58QAAwDL50pq1udMOk+oMmZb04tw6azG0gWy2a0Y3HwAAWIZrrBnbBtphUp0h0xT5m9bbrAXRBrNluMzYhAAA4Ch0hlqztQ20u6QaQ6YxLoYt1sJoge/KxrvA2pAAAMCms1NnaG2mtoN0llRfyLRm3Xz4F7IQvmUukNxV4YHZhf7HrI0JAAAOpTNTZ6c5U3MnXUU7S6ovZJojC+LVIwukJVz091ibEwAA1MjMtGZpS7w61RZCtLz6jxiLpC1uNTcoAAAY0llZm52t4QZzH011hZDFzOyeebKU1zutBdMK0d9obVQAAKadzkhzdraCv1M7SqorhByIG/iX2YumHXpluNrasAAATCudjdbMbAu34F+Wagoho5G/2ZxuLZx28D/oVf1LrI0LAMC00Zmos9GemW3gT0/1hJDDp4j+QnsB5c+V/hHZrJvqmxcAgCkjs9A/Ys3KVpAukmoJIUfOzO6Nx8mCae/rXUv/UK8M5xmbGACAztMZqLPQnpEtIB1Eu0iqJYQcPb2qv8FcTC0hf8v8hvz4cWtDAwDQVYuzbzgDzfnYBtpBUh0hZOmRDfAma0G1hYv+q27B3tgAAHSOzjyZfdZMbAt5Hm9KNYSQ5aeowoeshdUWsgH2HrKpAQDoqtjfa83CtnAxfCjVD0KOPUXpd1oLrDWiv9vc4AAAdITOOnMGtobfmWoHISuL29V/gSyo9v6XiYvusDY6AABtpzOuNvNaxj+iXSPVDkJWHtkYr7QXW6vw0bAAgE7R2Vabda0jz+OVqW4QsnpxMbzbWnBt4kp/U33TAwDQTv4ma9a1iXaLVDMIWf246C+3Fl7LRPsAAACgHXSW1WZb62inSPWCkPFk9sb+T8tCu9dagK1ShRusgwAAgNzpDDNnW4vI89irnSLVC0LGl2I+vNRahK1DeQUAtEwXSuuQdIlUKwgZf4qq/9vmQmyb6OetgwEAgNzozDJnWdtIh0h1gpDJpYjh/5gLsm0ir3kFAORNZ5U5w9pGukOqEYRMPi76882F2T6VdVAAANA0nVG1mdVK2hlSfSCkucimut5aoC20q35YAADQJJ1NtVnVSvJcrk+1gZBmU8S5Z8mC/GtrobZO9LccfGAAANAUnUnmrGoZeS5/rV0h1QZCmo8rN/Rd6b9vLdgW4hO2AACN0llUm02tpN1AO0KqC4TkE9loXfhY2EUx3F4/RAAAmASdQeZsaiF5PnycK8k3buDfbi3clvpC/TABAGCcdPbUZlFraSdI9YCQfONK/6fWAm4nf6d1sAAAsNp05tizqH20C6RaQEj+kQ242VrI7eTvrh8uAACsJp019gxqH3k+m1MdIKQdWbt97VNc9KW1oNtI/ub4VXFu/aABAGBldLb4r1qzp4109msHSHWAkPZkZj6sLaL/mrWw28k/JC6yDx4AAJZHZ8ribLFmTgvJzNfZn2oAIe1Lb8GfYi7ulpK/Se6XjbnNOoAAAFiq4SzRmWLMmrbSmZ/GPyHtTa/yL7cWeJvNRv9Z6yACAOBodIZYs6XNdNansU9I+9OL4XXWQm83f6N1IAEAcDg6O+yZ0l4649O4J6Q7mS39m60F32p8RCwAYIl0ZpizpMV0tqcxT0j3UsTwe9bCbzNX+j3WAQUAwAF+jzVDWk1mehrvhHQ3RenPMDdAq/n7ioVwtn1YAQCmlc6G4YwwZ0eb+TPSWCek+5G/pb3P3ght5h905dwm6+ACAEyjuU06G+yZ0WIyw9M4J2R6Ipv5I+aGaLPoH+2V4Ur7AAMATAudBToTzFnRav4jaYwTMn2RTXDe6KZoPxd5xwEAmFoyA6zZ0AHnpfFNyPRG/va21dgc7VeFL5gHGgCgs/TsN2dC6/mtaWwTQmRTXD26STrhflf1z7cONwBAh8hZr2d+bQZ0xdVpXBNCNDO7Nx5XRD9vbJYueLQo+7zuFQA6Ss/4xbPenAHtJrNZZ3Qa14SQJzJTnvAzLvrbzI3TCbzuFQC6Rs92+8xvP53JOpvTmCaE1NOrjn+2bJSbrQ3UEbzuFQA6Qs/02hnfGTqLdSan8UwIOVzcwP9zORCitZE64v7ZMlxQPwABAO2gZ7ie5bWzvTPkOUadxWksE0KOluK2k35KNs711obqhBgelee3/YlDEADQGtv1DDfP9g6Q53fDzHx4ehrHhJClZmbHxuNc6a+xNlaHxNqBCADIlJ7ZtTO8U+Q5XqOzN41hQshyM7N75smu8p+yNlhXyEGxtyj75x18OAIA8pHOaDmr7XO8C1z0n9aZm8YvIeSY8+M1PyEb6nJro3WFPL+/kR+vrh+WAIBmDc/mxTPaPL+7wJX+cp21aeoSQlYjcoBstjZcp1Th1vqhCQBohp7J5lndJTFsSWOWELLacTFsMjdetzzgyv5m6xAFAExCX79R8kDtbO6iTWm8EkLGFVf6c43N10U32AcqAGBc9OytncVd9ck0Vgkh446U17OMTdhFd4mPW4crAGD16FmbzlzrLO4Yf1Yap4SQScXF8CF7Q3bOw+JK66AFAKycnrHprLXO4G6J/sNpjBJCJh1X+g+YG7ODemXYZR24AIBjp2erdeZ2kc7MND4JIU1FNuL/tDZoF7kYvi4/brUOXwDA0g3P0sUz1Txvu0ZnZRqbhJCmU5T+NGujdpWL/ibrIAYALIW/yTpbu8uflsYlISSXFJX/j7I5H7E3bSc9KAV2m30oAwBGyJmpZ2ftLO0wmYkyG9OYJITklmIh/Lxs1LvtDdxNrgqfNw9oAMABclZaZ2h3ySyMfn0aj4SQXFPEuWfJht1pb+RucjF8Ww7m7SMHNQBgu56R1tnZXTIDZRamsUgIyT3rd61/kmzeLaObudtc9Ltd1T/LOLgBYLroWShnonVWdlr0l+gMTOOQENKm6PvVmRu7w9zi63yvNg9yAJgCi2fgVP03D4t4j1ZC2p+i9GeYG7zj5NDe42L/HOtQB4BOGp55fo91JnafPyONPUJI29Mr/Zvtjd5tLob9RRVuMA94AOiQ4VmnZ55xFnbdrMy4NO4IIV3JbOVfLn8T/7616afAA0XkY2MBdI+ebVJaHzDOvc7TmaazLY05QkjXMjPwJw3fIsQ4AKaBi+GLs2W4wDr8AaBNhmeZnGnWWTcd/N0609J4I4R0NS8oT/inxeKbUBsHQfe5gf+R/FhZgwAA2mB4hi2eZeY513kyw3SWpbFGCJmGyOZ/78hhMEVc9Ptc2f+MNRQAIE9yZsnZZZ1p00Kuw3vTGCOETFt6MfymdTBME1f6e4sYtowOCADIw+IZJWeVcYZNE51ZaXwRQqY1vYVwohwId9UPiKlThVuLhXC2NTQAoAl6Jsn5dOvIeTVl5Frc1ZsPJ6axRQiZ9uhrheRv85dbB8Y0kWvwN/Ijb58FoHGLZ9HwTDLPq2nhor+c17MSQszIIfkn1sExbdJryHZYwwQAxml49kz561ifoDMpjSdCCLHjqv5vWAfINHIxfFMGyGet4QIAq0rPGjlzrLNoGrnY/400lggh5MjpVf0NcpDyutdEhsnXixg+PTJoAGCFhmeLnjHG2TON9L1pdQalcUQIIUvLzO7wdH1tkXWwTCtXha8UVbjCGj4AsBzpLPmKddZMK7kel83Mh6enMUQIIcuPG/C61zop9Pe6GC47eAgBwJIMz47+XutsmWY6a9LYIYSQlWV24F8hB8tUfhb2UXxJ8B6wAI4qnRV6ZlhnyTR7QGdMGjeEELI6ef7ODc8sSr/VOHSm3vA1WdFfUh9UADA8G+SMsM4O+K0vWDj5Z9OYIYSQ1U8RwzvsAwiu9Pf2ynClNbwATJei0rOAT7s6LJklaawQQsh4U8S5k+VAvs08jKCfwqX/hfA11jAD0G2696WU8S4BhzGcHTJD0jghhJDJ5NQfn/qT6ZA2DycM/yOufUXZ3+kW7AEHoCNkjw/3Oh8ccERuMPdRnR1pjBBCyORTlP40F8Oj1iGFRU4/trEKC67y55pDD0A7yZ4e7m0+mvWIhjNi4E9LY4MQQppNsfP45+unvlgHFg6Qa/SjIobb5Z//yhyCAFpB97Du5eGeNvY6DtDZMFue8Lw0LgghJJ/I36r/t3VwwRD93a7sX24NRQC56l+ue9fc0xihMyGNB0IIyTNu4H9RDnjeXHuJ5GD/piv9ja4KnxgdkgAaN9ybskdlr1p7GKPkuu3VWZDGAiGE5J11t2x8mhz051oHGmxyyP9IrtkevgsL5EL2YpQ9KXvT2rOw6dmvMyCNA0IIaU96A/+qovT3WYcbDm/4Xdg4/A4P34UFJkn3nO69Ad9dXbbov6xnfjr+CSGknZnZvfE4OdA+bB50OCIZpD+U4n/nbKmfbW4MWQCrYnYhXNaTvSb/LHvO3o84Ajnj9axPxz4hhLQ/s1X4Jf2/3cxDD0vxoL5PpPz48frQBbB8upcW95SXvWXuORyFnul6tqdjnhBCOpaL9EML/AesAxBLFMMPh+9IUIWrrGEM4Chk7wzfGUD3krXHsCR6luuZnk53Qgjpboqy/xL5m/ot1mGIZYj+cX0pgYthuzmgASySPaJ7ZXHPGHsJSzY8u+fDS9NxTggh0xMZJu+2DkYcgxgedZXfLUNlmzm4gWmje0H2hO4Nc89g2Vzp/ygd34QQMp3pVf0NRelvtA5JHBsZLo8UVbhVhvelI8Mc6LZLF9e+7AFjb+AYRT+vZ3U6tgkhhEh5Pd08MLEiMsD3iZuLGLYYQx5ovcW17W/WtW7tAayUPz0d04QQQg7O7I39F7voP2Ufnlgpubb73PDz1cN28TGrBADZ07W7uIZlLVNWx0XPYj2T0/FMCCHkcJHh9Joi+i9ZhylWSfQ/cGVfP5r3BikAm0bKAZCXTYtr1d+ra/eQtYzVJWevXO/XpOOYEELIUlOU/gzzYMUY+IdcFT4v/3xFrTAAjSiqcEUvzt2qa3N0vWI8/Bnp+CWEEHIseeHAP9cN/AX2IYtxcDH8rRSHe+TH61zsn18vFMBYVLLWdM0trr2/tdYmxkPPWD1r07FLCCFkpZGD9ReLGBasQxfjJSVCP7f9dlf5z7roKbJYHbqWZE0N19biGjPXH8ZIzlQ9W9MxSwghZLVTVP6/yZD7jnkIY1IedlX4oiv99VJALh4pJIDtYimq1+va0TVUW1OYoOEZKmdpOlYJIYSMM8/btf4ZcvD+P+tAxuRJgd2f/kOvKOXkMrdglhZMk8U1cNnimujv1TVy8JpBc/TsXC9naDpOCSGETCqu3NAvYrjaOpzRoMXPgL9/+N6aVf9Tw9cuWuUG3aH3WO+1vmew3Pu0Buz1gWbIWalnZjo+CSGENJXZGF4nw1O/42cf2MjBfrlH97vF95G9rlf1L3Fl/6xDyg9aoH/W8N4N/8M9uZdaUuXe1u41MiL3SM/G/5qOS0IIIbmkF+d+15X+G/WDG/mSofrtIoYvSQmqht+x410M8qH3YnhPQjW8R3qvjHuIPOlZqGdiOh4JIYTkmLV3/YenyIH9riL671qHOVphvxQl/U7e7W4QBq4KV7myv1kK1CdGyhVWZnhN5drqNZZrrdc8XXu+i9pWcvbpGahnYToWCSGE5J7ihpN+qij77ylKPmWnY7RQPeiiv0c/MEHK1w1iexH7F7qKlx6MkGsyvDZyjcQNw2sm106vYbqW1jVGK8lZF8Mf69mXjkFCCCFty4tv2vBMF8Of2Qc9ukbu9ffE1+Wf7xK3SkkrpaxdJ/981az+V+5V/0Jxbqvf+UAeuz4HfS7D5yTPTZ+jPld9zvrc9RrotZB/Nq8TukXWxZ/pWZeOPUIIIW3PzHxYq0PfOvQxtfZLudP3BH7Alf5e+ec9+h1J+d9R/vf18uOOovTXyI9X62s9ixiudLF/ufzvrWJLUfmLpERu0jfSl//9Sfm5c+THs2cX+h9T+s/p38nP+fP11+rvGf5e+RrDr6VfU7+2/Bnpz9qR/uy4+N1ReUzy2OR/P5AeK98lxd/RM03PtnTMEUII6VqK+VBIWTjPGgIA0Ap6hslZlo41QgghXc+6hTDnyrDZHAoAkCE9s/TsSscYIYSQaUtv4E8pot9mDQkAyIKcUXpWpWOLEELItGdmPsy56PX1iPbgAIAJ0zNJz6Z0TBFCCCGHprew4TlFDO8von/MGiQAMFZ69sgZpGdROpYIIYSQI2fdLRufVpT+dBe9vhm7PWAAYJUsnjX+dD170jFECCGELD+uDG9ypb/NGjYAsBJ6tugZk44bQgghZHVSlP1Ti+g/Zw0fAFiW4VnSPzUdL4QQQsh4IsPmJUUcvom8PZAA4HCGZ0f/Jek4IYQQQiaTmXLDi/STa4qS/5ALwJH4x/Ss0DMjHR+EEEJIM5nZsfG4Is79tiuHnxVvDC0A02h4JsjZoGdEOi4IIYSQfDI78Ce56P9Chtbj9SEGYCo8rmeAngXpWCCEEELyzvN3bvhHLoa3FNEvGIMNQNfIXtc9r3s/HQOEEEJI+1LEuZNd6c9y0X/fHHgAWkn3tO5t3eNpuxNCCCHdyNo4949dGd4qA29XfQACaJVdupd1T6ftTQghhHQ3Rdn/haL0ZxfR7zeGIoDcDPeq7FnZu2kbE0IIIdOV9bvWP6mIc7/uYthsDksAjRruTdmjulfTtiWEEEKI/kcdRelPK6LfZg1QABMy3IP+NP5DK0IIIWQJedHNJ/0z/fxyF/1nzMEKYFXpXtM9p3svbUNCCCGELDe96vhnFzH8jgzVG6yBC+DYDPeU7C3dY2m7EUIIIWS1MnNTWOsG/vf1PSOtQQzgKPT9VmUP6V5K24oQQggh485s1XfDEluGa0eGM4CDXat7RfdM2j6EEEIIaSrrbln3tN7Av6qI4eOu9F81BjcwNYZ7QPaC7gndG2mbEEIIISTHrFsIc27g3+Wi32kNdqBrdK3rmte1n7YBIYQQQtqW4TsUVP61RQznyXB/0Br6QNsM17KuaVnbvBMAIYQQ0tH0FsKJMvD/UAZ/aRUCIFfDNStrV9dwWs6EEEIImZbM3tj/aRf7/9mV/k+KkpcVIDd+p65NXaO6VtOyJYQQQghZs2bt9rVP6cW5fyuF4XQpDle6MuwbLRPA6nMxfEd+vFLXnq5BXYtpWRJCCCGELC3FfPh5KRVvcaW/QErFvfXCARwbf6/8xegCXVu6xtJyI4QQQghZvRTV8T/Xi3P/pYj+w1JAbh0tJIDpVl0zw7VTnfRzaTkRQgghhEwuYT48dXbgvRST10sx+aD4XFH6h2qlBVND7r2uAV0LsiZ0begaScuFEEIIISS/rBv4fz1bhV/S1yxKiblQSswdhxYcdMAdi/fWn673Wu95uv2EEEIIIe3Os+bDU/UN4qXwvL6owv+VH3fw3dk2GN6jHemevV7vod7LdFsJIYQQQqYn63etf0av6p/gyvDKIoZ3FNF/2EX/afnfe+R/P35oicKqk2us11qvuV57vQd6L/Se6L1Jt4kQQgghhBwtver4Zxdx7uTZGF7nYvhfrgqfkIKlr6O8zyxiGKXXSq6ZXju9hnot9ZrqtU2XmRBCCCGEjDMbf7zx771o4J9blP1f6FX+5UXpf0uK2R8UMbzfRX+O/O8r5H9H+fFu+d+deV/axeeiz0mfW7jCVfJc9TlX+tz9GxavRf8X9NroNUqXixBCCCGEtCXrd61/0kx5ws/M3th3UvI2zg78K6T8vVFK3zuLKrxPyuCZrgwf1dIr/36T/PstWn6lHF4t/+46+bmB/Hiz/NxuLY5Cv+v7gBZJ+XePyo8/WDT8Zy3KDyz+mmHJ3D38vYtf4zr9msOvLX+G/lny787RP1v+3ZnDx1KFd8q/f+Ns5V/RG/hTZqu+08euzyE9HUIImZKsWfP/AavTKnLZzH5HAAAAAElFTkSuQmCC\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEb3SURBVHhe7d0LuOVXfdf/qNVqqdVq1WpVtE2BzFm/E8qQs9YOaVNFba1Si5ZWi/aixabFWq2lWou2tYpSWkWptn8ghABhIAm5EBISchlIMnPWb8/kThKSkAuEW4AkJIFyCYH/93tmAZPf+WRyzplz+f72fr+f5/WkT5OZs8/e67e+38OTyzFERLT5dVc/++mpL6ekPr/cnJVqvsb++MCKlf+7nHXoz5VT/K9tv4yIiIiIKGbdcv5BW17P6/ry5fVY+TX2a9tvQ0REREQUo66Wl3R9vlUtsetjv4f9Xu23JSIiIiLamXbtPfkbU1/26KV14/z39N+7fRkiIiIiou1rYX95ji2ltwyX1E10i3+N9uWIiIiIiLa+hT7/rFhMt4R/rfZliYiIiIi2roV9kxPVQrqV/Gu2L09EREREtPntPrj7G2zxvHm4iG6Dm/1rt5dBRERERLS5pZrPEEvotvCv3V4GEREREdHmdehfIaaX0G3Dv3qMiIiIiDazXf0J35r68mm5fG4jfw3+WtrLIiIiIiI6urqaf08tnjvCXkt7WUREREREGy/1J0zkwrmD/DW1l0dEREREtLFSzRerZXMn+WtqL4+IiIiIaP3ZUvljwyUzkB9rL5OIiIiIaH2lWm4TC2YI/trayyQiIiIiWntdn39VLZix5F9tL5eIiIiI6MlbmD77r6RavqCXyzj8NfprbS+biIiIiOjIdX1+rVosY8qvbS+biIiIiOiJ6/rJ9+iFMrLJ97SXT0RERESkS32+XC+Tcflrbi+fiIiIiGh1tjT+xHCJHJGfaN8GEREREdFhffmYP5T6cpdYIEfBX7t/D+27ISIiIiI6VNfnX1cL5LjkX2/fDhERERGRLbnTk75dL44jZN9L+7aIiIiIaN5LfT5dLo0j5N9L+7aIiIiIaJ7r+slz1cI4bpPntm+PiIiIiOa11Jcr9bI4Xv49tW+PiIiIiOaxbjm/SC2KM8G+t/ZtEhEREdE8dexFx3596su9ckmcAf69+ffYvl0iIiIimpe65fwytSDOFPse27dLRERERPNQ2jd5hlwMZ5B/r+3bJiIiIqJZL9WyRy2Fs8i/1/ZtExEREdEs1y3nv6sWwnWZiv9fZPY9t2+fiIiIiGa11Jcql8H1mk70/z8g/57bt09EREREs1i3nH9OLYIbMr7/Vffn2ttARERERLPUrr0nf2Pq831yCdyoES27/r37e9DeDiIiIiKalWzZe8Vw+ZtDr2hvBxERERHNQt2B0omlb3OM7W9hsPeivS1ERERENPZSX86WS98c8veivS1ERERENOa6af5BtfDNNXtP2ttDRERERGMt9fkauexttnH9g2nXtLeHiIiIiMZYN82/oBY9GHtv2ttERERERGOqu/Gkb059fkAuefD/VfcBf4/a20VEREREYyn15ZVqwcPX+HvU3i4iIiIiGkPdgfIstdhBsPeqvW1EREREFL3Ul/PlUodV/L1qbxsRERERRa6rSz+sFjocgb1n7e0jIiIioqilmm+Sy9x2q+L/F5S/Z+3tIyIiIqKI2XL5ErXIYQ3svWtvIxERERFFKi3nv5Bq/rRc4nZIEv+/qPy98/ewvZ1EREREFKVUy/9TCxzWzt/D9nYSERERUYS6ulTU4oYNsPeyva1EREREtNOlmt8plzasm7+X7W0lIiIiop2sq5N/ohY2HAV7T9vbS0REREQ7Var5fXJZw4b5e9reXiIiIiLaibpa/qNa1LAJ7L1tbzMRERERbWddXfrLtox9Xi5pMX24UX8uHn9v7T1ubzcRERERbVep5tfIBS2o1E/e7tSfi8rf4/Z2ExEREdF21NWl71aLWVSpz+9Lffn/DhnZ31Ns73V724mIiIhoq0s1XyaXsoBsuX0s1ckZX110D/3fj6m/NiJ/r9vbTkRERERb2WItP64WsrBqPvDVJbfx/5/8a4Py97y9/URERES0VaVa7lTLWES21H5quOQe5lPq10Tk73l7+4mIiIhoK7KF69fUIhaVLbOXD5bbw12ufk1U/t63j4GIiIiINrPuqmd/uy1cXxouYFHZInvvYLFV7lW/Nqgv+WfQPg4iIiIi2qxSn08Xy1dYabmcJxbbx7O/Rv3aqPwzaB8HEREREW1GXT95rlq8ArtFLraC/7WDXxvc5LntYyEiIiKio80Wwiv10hVP6vOjC31543ChfSKH/tr8qPq9IrLXfGX7WIiIiIjoaLLl6qeHy1ZwdbjMPhn/NYPfI7qfbh8PEREREW2kXe/d9cdsERzNP7C10JcHhkvsWvmvVb9nRPZ67/XPpn1MRERERLTeUp//m1q0okr95NLhArt2k0vV7xmVfzbtYyIiIiKi9dRNT3y6WrDCqvkDeoFdO/895O8dlX1G7eMiIiIiorWW+vxmuVwFtVDzOWp5XQ//PdTvHZV/Ru3jIiIiIqK1tNiX71eLVWA3qcV1I/z3Gvzeofln1T42IiIiInqybOFbVktVSLV8PvX59OHCunH5dP895dcKyF7zcvvYiIiIiOhILfb5Z9VCFVYt+1cvq0fHf0/5tYLyz6x9fERERESkWrx+8Sm2OH1suEiFVfMn1aK6Gfz3ll8zpo/5Z9c+RiIiIiIalvr8W2KJiuwStaRuBv+9B18rNP/s2sdIRERERIe3OJ0ktUCFVcvdakHdTP415NcOyj/D9nESERER0Veyxe4stTxFZa/37MOX0i1ytvraUdnrPat9nERERETkLU7L89TiFNgNg4V0y/jXGnzt0PyzbB8rEREREdmCdHC4MEWVavmsOU0tpVvCv5Z9TfVagjrYPlYiIiKi+W5hOf+CWJYCm1wtF9It5F9Tv5aY/DNtHy8RERHRfNZdddI3p5ofUMtSSDV/XC2i28G/tnxNAa18pvbZto+ZiIiIaP5KtbxSLUpR2QL3TrWEbgv72uo1ReWfbfuYiYiIiOarbn95llqQorJF8065gG4new3qtYVln3H7uImIiIjmp1TL+XI5iurA5K1y+dxG/hrkawvKP+P2cRMRERHNR4vL+R+pxSisablOLZ47wV+LfI1B+WfdPnYiIiKi2S/VfKNaiiKy1/qZ1E9eq5bOnWGvxV6Teq0R+WfdPnYiIiKi2W6hLv2SWoiiStN8pV44d5C9JvVao/LPvH38RERERLPZ4r7Jn+9qfkQtQyFNy0flohmAvzb5miOyz9w/+3YMiIiIiGavVMv/lYtQVLVcqJbMCPy1ydcclH/27RgQERERzVaLyzmrBSisabldLZiR+GuUrz0oPwPtOBARERHNTraYXaSWn6js9e45fKkMao967VHZ672oHQciIiKi2Whxmv+xWnyiSnVyzWChjMteq/oeovKz0I4FERER0fjr+nyrWnpiyo+k6eTVcqmMyF6rv2b9vUSUb23HgoiIiGjcpWn5Fb3wBFXzu+VCGZi/Zvm9BOVnoh0PIiIionF2/HXl27o+f04tOyHV8mG1SI6Bv3b5PYWUP+dnox0TIiIiovGVpuXVetGJKdV8gVoiR8Feu/qeovKz0Y4JERER0bjq6tJ3qwUnqlTL++QCOSb2PajvLSw7I+24EBEREY2nVPNlcrkJyF7rl1KdnCGXxzHx78G+F/U9RuRnpB0XIiIionG0UMuPq8UmrJoPyMVxhPx7kd9jUH5W2rEhIiIiil+q+U611IS0XB5SC+OY+fckv9eA/Ky0Y0NEREQUu1TLr6mFJqo0LZerZXHU7HtS32tUfmba8SEiIiKK2WJd+utdLeP5e0T7cu+qJXF23Ku+55DszPjZaceIiIiIKF6p5tfLRSYoWwbPGyyHs+Q89T1H5WenHSMiIiKiWC3Wpb+pFpjAbhHL4Uzx73HwPYfmZ6gdJyIiIqI4pZrfo5aXiFKfH13oyxvVcjhLDn2P+VH1HkTkZ6gdJyIiIqIYLdTyL9TiEpUtf71aDGdT7tV7EJWfpXasiIiIiHa23Qd3/9Gulg+qpSUiW/4eWL0MzrwH1HsRkp0lP1PteBERERHtXKmW/yoXlqBSP7lULIIzbnKpei+i8jPVjhcRERHRzrTYn/A0tagE9gG9CM4+/94H70VofrbaMSMiIiLa/lLNZ6glJaqF6eQctQTOA//e1XsSlZ+tdsyIiIiItrfFfvJ9akGJyhan96oFcK7Ye6Dem6j8jLXjRkRERLR9dbXsV8tJUJ9P03y6XP7mib0H/l4M3pu47Iy140ZERES0PdnSdIpcTIKy17v8uIVvvi2r9ygqe72ntGNHREREtLUtXrL4lK6Wj6qlJKRaPjlY9OaevyfyvYrIzpqfuXb8iIiIiLau1OeXy4UkqDQtl6hlb67Ze6Leq6j8zLXjR0RERLQ1Le6bJLWIRGVL3d2rljx8xd3qPYvKz147hkRERESbX1rOZ6klJKpUy9liwYOz90a9Z1H52WvHkIiIiGhzW9xfnqcWkKhSn2+UCx4Ok29U711UfgbbcSQiIiLavLpaDqrlI6jPplpO08sdvsreI3+vBu9dXHYG23EkIiIi2pxSn/+1XDzCmlwtFzus4u+Vfg9j8rPYjiURERHR0XX8dcf/6a7P96ulI6b8cbXQ4Yn5e6bfy4jy/X4m2/EkIiIi2nipz/9LLxwxpZrfqZY5HIG9Z+q9jMrPZDueRERERBtrcTr5LrVoRGUL251ykcOTs/dOvadR+dlsx5SIiIho/dkCdJ5aMuLKZ65a4LAm/t7p9zQme83ntWNKREREtL4WpvkfqgUjrFquGy5vWB9/D+V7G5Sf0XZciYiIiNaeLRI3DBeLsGr5jP3xVLW8Ye38PWzvpX6f47mhHVciIiKitZX6/O/EUhGWLWlXDpc2bNiV6j2Oys9qO7ZERERER+6Z157057o+P6yWiqA+JpY1HAV/TwfvcWD5YT+z7fgSERERPXG26PyuXijCunC4qOHo+Hs6eI9Ds9f8u+34EhEREemOP1CW1CIRVs13DJc0bA5/b+V7HpSf3XaMiYiIiFZnC8O4/pe8Wt6iljRsAntv1Xse2IXtGBMRERE9voVp/lGxPISV+sk1ckHDJppco977qPwMt+NMRERE9LVsUbhluDiEVfMjizW/Ri9n2Cz+Hvt7LT+DmG5px5mIiIjoUKku/YpYGuKq+d1qMcPm8/dafgZB+Vlux5qIiIjmveP3l2+zZeZzamkIqeaPqIUMW8ffc/lZRGRn2c90O95EREQ0z6VaXi0XhqDSNF+gljFsIXvP1WcRlZ/pdryJiIhoXltcziepRSEqW2Buk4sYtp699+ozicrPdjvmRERENI+lmi9VS0JINX8pTSdnyCUMW8/ee/8M5GcTkJ/tdsyJiIho3lqoS/9MLQhhTcsBuYBh2/hnID+boPyMt+NORERE81RX8/vVchDUQ2rxwvbzz2Lw2cRlZ7wddyIiIpqXUi3/WS4GQdmCdcVw4cKOuUJ9RlH5WW/HnoiIiGa945fzX+tqeUwtBRGlablXLFvYSfaZqM8qJDvrfubb8SciIqJZLtVymlwIgrLF6vxVixZ22vnqs4rKz3w7/kRERDSrLdSlv6EWgbgmt4glCwH4Z6M/s5j87LfHgIiIiGaxblT/Odf8RVum3qiWLOw8/2wOfUbqswvIzn57DIiIiGjWSnXyz+UCEFTqc68WLESSe/XZReXPQHsciIiIaFY6ee/JX9fV/AE1/CNKNT+oFyuEY5+V+gxDsmfAn4X2WBAREdEslGr5TTn4g7Ll6TK5VCEe+6zUZxiVPwvtsSAiIqKx98xr83eqgR/YB+RChbD8Mxt8hqH5M9EeDyIiIhpz3TS/SQ37qBaWy7lqmUJc/pmpzzIseyba40FERERjbaE/4fvkoA8q1fxetUhhBOyzU59pVP5stMeEiIiIxljX531qyEeUavmCvd7T5RKF8FY+u5XPUH++8eR97TEhIiKisWXLxyl6wMeUlsvycHnCyNhnqD7bqOw1n9IeFyIiIhpLuw/u/oaulo+q4R5SzfevWpowSv5Zys84IntG/Flpjw0RERGNodTnl8vBHlSalkvU0oQRss9SfcZR+bPSHhsiIiKK3vH9CQtqoEeV+sndcmHCiE3uVp91VP7MtMeHiIiIItf1+Uw1zOOanK2XJYzX5Gz9WUeVz2yPDxEREUVtoZ/8fT3IY0p9vlEvShi/fKP6zKPyZ6c9RkRERBSxrpYDaogH9dk0LafpJQmjZ5+tf8aDzzwue3baY0RERETRsuXi5+UADyrVvG/VcoTZYp+x+uyjstf88+1xIiIioijtPrj7T3W1fFIN76A+vmopwkzyz3rw2cdlz5A/S+2xIiIiogilPv9PObiDStPJO9VShBlkn7U6A1H5s9QeKyIiItrpdvUnPlMN7KhSzXfKhQizyz5zdRai8meqPV5ERES0k3V9PlcN67Cm+Uy5DGFm+Wcuz0JY+dz2eBEREdFOZUvE8/Wgjsle7/WHL0CYK9erMxGVvd7nt8eMiIiIdiIbyONZHmr5jP3x1MHygznhn307A/p8xHN9e8yIiIhou0t9/kUxnMOyZeeq4fKDuXOVOhtR+TPWHjciIiLarnYf3P0tNogfGg7mwD4mlh7MIT8Lg7MR2UP+rLXHjoiIiLajrs+vEkM5rIV+cqFaejB//CyoMxJXflV77IiIiGir27W/LOmBHFW+Qy08mF9+JvRZicmfufb4ERER0VbW1TKy/0WsvEUtO5hffiYGZyQ2e+ba40dERERb1cJy/lE5iINKNV+rFh3Az4Y6M1H5s9ceQyIiItqKulpuUUM4qEcWa36NXHIw9/xs+BkZnJm47NlrjyERERFtdmk5/wc5gMOavFstOMBX+BnRZycmfwbb40hERESb1XddfeJf6mr+rBq+MeWPqMUGGPKzos9QQPYM+rPYHksiIiLajNLyyj/Ao4dvRDVfoJYaYMjPijxDQfmz2B5LIiIiOtoWDpTnqIEbVZqW29RCAzwhOzPqLEXlz2R7PImIiOhossH6ruGgDexLi315s1xmgCfgZ8bPzuAsRfau9ngSERHRRkvT/E/FkI2rlgNqkQGejJ8deaaC8mezPaZERES0kUb1X5CalofUAgOslZ8hebZCyne0x5SIiIjWW+rzf9IDNiZbVK4YLi7AOl2hzlZU/oy2x5WIiIjW2nHXTJ5qQ/SLarhGlGr+kFhagPWzs6TOWET+jPqz2h5bIiIiWks2RF83HKqRLfblfLm0AOvkZ0mdscBe1x5bIiIierIWDuTvFcM0rppvVQsLsFF+puRZC8qf2fb4EhER0ZGywbl3OEjDqvmL5k1qWQE2ys/UytlSZy6mve3xJSIioicqTfNPiSEaVuonvVpUgKM36dWZi8qf3fYYExER0bCT9578dV2f71FDNKJU84N6QQE2iZ0xdfZiyvf4M9weZyIiIjq8VMtv6gEaky0hl8nlBNgsdsbU2YvKn+H2OBMREdFXOm45f6canGHV8kG5mACbzM+aPINB+bPcHmsiIiLyVv7hGzE0AztXLSXAZvOzNjh7sdmz3B5rIiIiWqhLf0cOzKDScrlZLSTAlrEzp85iVP5Mt8ebiIhovutq3qeGZUSpli9008npchkBtsjKmfOzJ85kSPZMt8ebiIhofrPh/TNyUAZlS8fycAkBtsmyOpNR+bPdHnMiIqL5q+wvf6Kr+SNqSMaU7xfLB7Bt/AzqsxmQPdv+jLfHnYiIaL7qavkfckDG9S61fADbxc/g4EzGZs94e9yJiIjmp111aZccjEGlfnK3WjyA7Te5W53RqPxZb489ERHRfNTV/FY1FAN7m146gO3lZ3FwNmOzZ7099kRERLNfqkt/Tw7EoFKfb1QLB7Bz8o3qrEblz3x7/ImIiGa7ruapGoYx5c+laTlNLxvADrEz6WdTn9mA7Jlvjz8REdHslmr5V3IQBpX6vE8uGsCOG8+/f9r5s9+uASIiotnr2Lr0TTbsPqGGYET+WvWCAQQxsufJ74B2HRAREc1WXS2/owZgWLVcLJcLIAg/o/LsRmV3QLsOiIiIZqeFunS8HHxBpT7fqRYLIJ58pzrDUfld0K4FIiKi2air+Rw19KJKy+UsvVQAwdhZVWc4LLsL2rVAREQ0/tL+8nw58IJK03K9XCiAqOzMqrMcVaqTH2rXAxER0bjrpuU6NewiSn3+A/vjqXKZAII6dGZXzq481+HYndCuByIiovFmw/cX5aALKtVylVokgPDs7KozHZXfDe2aICIiGl9PO7j7W2wAP6SGXEQ2eO9btTwAo5LvU2c7Inu9D/kd0a4LIiKicdX1+VVqwMU1uXD14gCMh59hfbajyq9q1wUREdF4WphOTtCDLap8h1ocgLHxs6zPeEx+V7Rrg4iIaBzZsH2HGmqBvUUtDcDY+FkenO3g8jvatUFERBQ/G7Y/ogdaTKnma4fLAjBqdqbVWY/KXvOPtOuDiIgodja4bh4OssAeSdP8mlWLAjBmdqb9bA/OemQ3t+uDiIgobqnP/14MsbBSLe+RiwIwdna21ZmPyu+Odo0QERHF6xkHnvUXbViN519aX/NH5IIAzAg/4/LsB+R3h98h7TohIiKKVdfn31cDLKxpuUAtB8Cs8DMuz35Y+ffbdUJERBSnhenkRD24Ykq13KYWA2Dm2FlXz0BUfpe0a4WIiChGNqAuGQ6ssGr58mJf3iyXAmDG+Fn3My+fhZguadcKERHRzmfD9IViWEV2cLgMALPMz/zgGQjNXvML2/VCRES0s9lQul0Nq6AeOnwBAOaFn/3BsxCWvd7b2/VCRES0c3V9fqkaVFGlWvYOFwBgLtjZV89EXPml7ZohIiLa/o7bN3lq6vOjekjFY6/1Q3IBAOZG/pB6NiLyu8XvmHbdEBERbW9dLa9TAyqqxb6cr4c/MB/8GVDPRlh2x7TrhoiIaPtaWM7fKwdTVDXfqgY/MG/8WZDPSFB+17Rrh4iIaHvqxvT3+9XyWDfNb1JDH5g3/iysPBPqWYnI7pp27RAREW19aTn/lBxIQaVapmrgA3PLngn1rETld067foiIiLawM1/wR1LN96hhFFHq84Ny0ANzLz+onpmI/M7xu6fdQkRERFtTV5f+ixpEUS1O82V6yAPzzZ8N9cyEZXdPu4aIiIg2v137y7FyAMX1QTXgARziz8jgmQnN76B2HREREW1uXS1vVMMnrGk5Vw13AIf4MyKfnajsDmrXERER0eaVlvPfloMnKBviNw+HOgDpZvUMReV3UbuWiIiINqeu5qvV0InIBvcX7I9vGAxzAEJ7VvyZkc9TOHYXtWuJiIjo6LPB8i/lwAkqTcvycJgDOAJ7ZtSzFJbdSe16IiIi2nhP3XvyH099/rAcNiHl++UgB3BE/uzoZyoev5P8bmrXFBER0cbqpuW/q0ET2LvUEAdwZP7sDJ6l2OxuatcUERHR+lu4Jh8nB0xQqc/3qAEOYK3G8x+DcX5HteuKiIhofdkgectwsIRWy9v08AawFv4MyWcrrre064qIiGjtpQP5B8RQCSvVcpMa3ADWyZ4l9YxF5XdVu7aIiIjWVupzr4ZKTPlzqU5eL4c2gPWxZ8mfKf2sxeN3Vbu2iIiInrxuOnmxGihh1bxPDmwAG+LPlHzWorI7q11fRERET9yxdembUp8/LodJQKmWT6hBDeAo2bOlnrmI/M7yu6tdY0RERLqult9RgySsWi6WQxrAUfFnSz5zUdnd1a4xIiKi1S3UpePlAAkqLZe71IAGsEnsGVPPXlR+h7XrjIiI6PF1NZ+jhkdUNojPWjWYAWyms9SzF5bdYe06IyIi+lqpLv2QHBxBLdSlG8RQBrDJ/FlTz2BUfpe1a42IiOhQqebr1NCIyF7rH3QHyqlqKAPYXCvPmj9z4lmMyO+ydq0RERGt/ANo/1YNjMCuUgMZwNbwZ27wDMZmd1q73oiIaJ57Rn/Cn021fEoOi4BSn+9TgxjAVsv3qWcyIr/T/G5r1xwREc1rXc3/Rw2KqGzgXrR6AAPYBhepZzIsu9vaNUdERPNY6k94thwQQaU+3yGGL4Btk+9Qz2ZUfse1646IiOatruYL1HAIq07eqocvgO3gz6B8NqOyO65dd0RENE91/eQFcjAElfp8rRq8ALZbvlY9o3FNXtCuPSIimpdSLe/VQyEee62fTtP8Gj10AWwrfxbtmVTPakR+17Vrj4iI5qGull9WAyGqNC3vkQMXwM6wZ1I9q2HZndeuPyIimuV29Sd8a6rlM3IYBGSv9aNy0ALYWfZsqmc2Ir/z/O5r1yAREc1qXc2/pwZBYO+QQxbAjvJnc/CsxmZ3X7sGiYhoFkv9iRM5AIJK03KbGrAAgrBnVD27Ufkd2K5DIiKatVLNF6vLP6rUL+2RwxVAEEt71LMbld+B7TokIqJZKu0vL1QXf2AH9WAFEIk/q4NnNzS/C9u1SEREs1Kq5XZ16UeU+vywGqgAosoPq2c5Ir8L27VIRESzULecX6ou/MD26mEKICJ/ZgfPcGx2J7brkYiIxtyuq57zV1OfH5WXfUCp5g+rQQogOHt21TMdkd+Jfje2a5KIiMZa1+dT1UUf1WJfzpdDFEBo/uyqZzqufGq7JomIaIyl/eVkfcFHlW9VAxTAOPgzrJ/tmPyObNclERGNLRs8V6jLPaRaHuum+U3DwQlgPPwZXnmW1TMekL3mK9p1SUREY6rr80+qiz2sWqbDoQlgfPxZls94WPkn27VJRESj6MvH/GEbOHfrSz2eNC0PDoclgBGzZ1o96xHZ673b78x2exIRUfS6Pv+GutADu3zVoAQwWv5MD57x4PJvtOuTiIgit3DgxO/QF3lQtXxQDUoA4+bPtnzmg/K7s12jREQUNbuw3zC8wIM7Vw1JAOPmz/bgWY/uDe0aJSKiiHXT8rfE5R2WDcObh8MRwEy5WT37Ydkd2q5TIiKKlg2Vq+TlHVCqK/+1tjcMhiKAGbLyjB961uU9EI295qvadUpERJHq+vwidXGHVUsdDkUAs8efdXkHhJVf1K5VIiKK0LG3f//Xpz5/SF/aEeX71UAEMJv8mdd3QTx+l/qd2q5XIiLa6bp+8jJ1YUeVar5UDUMAM8qeeXUXxDV5WbteiYhoJ1tYzsfpizqm1Od75CAEMOPyPepOiMrv1nbNEhHRTmUX8p7hBR3c2/QQBDDL/Nkf3AXR7WnXLBER7URpOf+AuJzjquUmNQABzAe/A+TdEJTfse26JSKi7S7V3KvLOaSaP5+mk9er4QdgTtgd4HeBvCMC8ju2XbdERLSddXXpxepiDqvm/XLwAZgrfhfIOyIqu2vbtUtERNvR068+8U+mmj8uL+WAUi2fUAMPwJyyO0HdFRH5Xet3brt+iYhoq+tq+W11IYc1LRfLYQdgLvmdIO+KqOzObdcvERFtZWk5L8qLOCgbancNhxwAmLvUnRGV373tGiYioq2qq+P6V/SkaTlLDDgA887uBnVnhGV3b7uGiYhoK+rq0j+QF3BcN8gBBwDG74jBnRGb3cHtOiYios0u1XytvHwDSn3+A/vj69RwAwB36I5YuSvkPRKN38HtOiYios2sq+XfqIs3rGm5Sg02ADic3xXyDonK7uJ2LRMR0Wa0a3/5M6nmB+WlG1Dq831qoAGAlu9Td0lEfhf7ndyuZyIiOtq6Wv63unCjssF10epBBgBP6CJ1l4Rld3K7nomI6Gjqat4tL9qgbGC9fzDAAGAt3q/ulLDsbm7XNBERbbTU57fLSzaqOnmrGGAAcER+d8g7JSi/m9s1TUREG6mrSz+sLtiwar5ODTAAWAu/Q+TdEpXd0e26JiKi9Zb6fJO8XAOyIfVpe72vHQ4uAFi7lTvk0+qOicjv6HZdExHReuqm5SXqYo0q1fKe1UMLANbJ7hJ1x4Rld3W7tomIaC3t6k/4Vrvwx/O/atTy0VXDCgA2yu4UdddEZK/3035nt+ubiIierK7m31MXamDvWDWoAGCD/E4Z3DGx2Z3drm8iIjpSqT9hIi/SqOrS7WpQAcDR8LtF3jlB+d3drnEiInqiUs0Xq0s0KhtIe4YDCgA2wR5150Tld3e7xomISGWX5Y8NL8/gDorhBACbwu+YwZ0T3Y+165yIiIalWm4TF2dIqeaH0wE9nABgU/gdY3eNuoMi8ju8XedERHR4XZ9/VV2cge2VgwkANpHfNYO7J7j8q+1aJyIib2H67L+SavmCvjTjsdf6YTWQAGBL2J2j7qKI/C73O71d70RE1PX5terCjCr1k7fLYQQAW2LydnUXxZVf2653IqL5rusn36MvyqjyrXoQAcDW8btH30lRTb6nXfNERPNb6vPl+pIMqJbHUs1nqCEEAFvK7h6/g+TdFJDf7e2aJyKaz+wy/Inh5RjcVA4gANgGfgcN7qTofqJd90REc9aXj/lDdnHfJS7GkFItnxoOHQDYdnYXqTsqInu9d/ld3259IqL5qevzr6uLMSq7sC9/3LABgJ0xnr/da0X+9XbtExHNR930pG/XF2JMqc/3imEDADsk36vuqrDszm/XPxHR7GeX9OnyMgzKXu95etgAwE7I56m7Kiq/89v1T0Q023X95LnqIgzsZj1oAGDn+N00uKuCmzy3jQEiotnNLugr9SUYT+rzowt9eeNwwADATjt0N+VH1d0Vkb3mK9sYICKazbrl/CJ1AQZWh8MFAKLwO2pwZ8VmM6CNAyKi2erYi479eruYR/MPUKRaHhgOFQAIx+4qdYdFZK/3Xp8FbSwQEc1O9pP8y9TFF1XqJ5euGigAEM7kUnWHhWWzoI0FIqLZKO2bPENeeFHV/AE9UAAgHr+z5F0WlM+ENh6IiMZfqmWPuuwCe5saJgAQkd9ZgzssNJ8JbTwQEY27bjn/XXXRBXaTGiQAEJnfXYO7LDabDW1MEBGNN7uAx/RPBX8+1cnrhwMEAMKzu8vvsMGdFpa95trGBBHROLOf2H9OXXBhTcv+VcMDAEbC7zB5t0VlM6KNCyKicbVr78nfmPp8n7zcArIh8Ynh0ACAEfqEuuMi8hnhs6KNDSKi8WSX2CuGl1ps+RIxMABgVPwu03dcWK9oY4OIaBx1B0onLrO4puUuNTAAYIz8TpN3XVQ2M9r4ICKKn120Z8vLLCh7vWcdPiQAYOTOUnddVPZ6z27jg4godt00/6C6yAK7YTAgAGD0/G4b3HWx2exoY4SIKG6pz9fISywge62ftT++Tg0JABizQ3fbyh0n779ofHa0MUJEFDP7ifwX1AUWVs1XqwEBALPA7zh590VlM6SNEyKiWHU3nvTN9hP5A/LyCshe631qMADAbBnTv+bRZojNkjZWiIjiZBfqK9XFFVWq+Z2rBwIAzBi769QdGJW95le2sUJEFKPuQHmWurDCquX9q4YBAMwov/PkXRiVzZQ2XoiIdj67SM+Xl1VU08lbh4MAAGaV33nyLgzKXvP5bbwQEe1sXV36YXVRhVXLdcMhAACzzu8+eSdGZbOljRkiop0r1XyTvKQCSsv5M2k6ea0aAgAw0/zusztQ3Y0R+WxpY4aIaGfqanmJuqCiStPyHjkAAGAe2B2o7sawbMa0cUNEtL2l5fwX7CfuT8vLKaBUy0flxQ8A88TuQnVHRuQzxmdNGztERNuXXZb/T11MYU3LO+SlDwBzxO9CeUcG5bOmjR0iou2pq0tFXUiB3a4ufACYR34nDu7I2GzmtPFDRLT1jfBfQL5neNEDwBzbo+7KqHzmtPFDRLS1dXXyT9RFFFXq8zXikgeAOZevUXdmWDZ72hgiItq67Cfr98lLKCC7yB9O0/JqfckDwBxbuRvzw+rujMhnTxtDRERbU1fLf1QXUGB75QUPAPC/V3fv4M6MzWZQG0dERJtbV5f+sl0yn5eXT0wfVhc7AOBr/K4c3J1x+QyyWdTGEhHR5pVqfo28eIJK/eTt6lIHABxu8nZ1h0bls6iNJSKizcl+gv5udeFElfr8Pn2hAwBWG88/e7HCZlIbT0RER5/9BH2ZvGwCskv7sVQnZ6y+yAEA0qE78zF1p0bkM6mNJyKio2uxlh9XF01YNR9YdYkDAI7I7055pwbls6mNKSKijZdquVNdMhHZZf2p4eUNAFizT6m7NSKfTW1MERFtLLtIfk1dMFHZJX354NIGAKzd5epujcpnVBtXRETrq7vq2d9uF8mXhhdLVHZB3zu4sAEA63evumOD+pLPqja2iIjWXurz6eJSCSstl/PEhQ0AWA+7S9UdG5XPqja2iIjWVtdPnqsulMBukRc2AGDd/E4d3LHBTZ7bxhcR0ZNnF92V+jKJx36af3ShL28cXtQAgI05dKfmR9WdG5G95ivb+CIiOnJ2afz08BIJrg4vaQDA0fG7dXDXRvfTbYwREel2vXfXH7MLbjT/IMJCXx4YXs4AgM3hd6y6eyOy13uvz7A2zoiIVpf6/N/UBRJV6ieXDi9mAMBmmVyq7t6ofIa1cUZE9Pi66YlPVxdHWDV/QF/MAIDN4netvIOjslnWxhoR0deyn4TfLC+NoBZqPkddygCAzeN3rbqDo/JZ1sYaEdGhFvvy/erCCOwmdSEDADaf37mDOzg0n2ltvBERrfzrxJbVZRFSLZ+3n9hPH17EAICtkk/3u1feyQHZa15u442I5r3FPv+suijCqmX/6ksYALCV/O6Vd3JQPtvamCOieW3x+sWn2IXwseEFEVbNn1QXMABg6/kdLO/mmD7mM66NOyKax1Kff0tcDpFdoi5fAMDW8zt4cCeH5jOujTsimrcWp5OkLoawarlbXbwAgO3jd7G8o4PyWdfGHhHNU3ZhnaUuhajs9Z59+GULANgRZ6s7Oip7vWe1sUdE89LitDxPXQiB3TC4aAEAO8Tv5MEdHZrPvDb+iGgesgf/4PAiiCrV8llzmrpsAQA7wO9ku5vVnR3UwTb+iGjWW1jOvyAugcAmV8uLFgCwY/xu1nd2TD772hgkolmtu+qkb041P6AugZBq/ri6YAEAO8/vaHl3B7Qy+2wGtnFIRLNYquWV6gKIyi6md6rLFQAQgN3R6u6OymdgG4dENGt1+8uz1IMflV2gd8qLFQAQh93V6g4Py2ZhG4tENEvZT7Lny4c+qgOTt8pLFQAQht/V8g4PymdhG4tENCstLud/pB74sKblOnWhAgDi8Ttb3uVB+Uxs45GIZqFU843qYY/IXutnUj95rbpMAQAR2Z1td7e60yPymdjGIxGNvYW69EvqQY8qTfOV+iIFAIRld7e606Py2djGJBGNtcV9kz/f1fyIeshDmpaPygsUABCe3+Hybo/IZqPPyDYuiWiMpVr+r3zAo6rlQnV5AgDi8ztc3u1B+Yxs45KIxtbics7qwQ5rWm5XFycAYDz8Lpd3fFA+K9vYJKIxZRfOReqhjspe757DL0sAwCjtUXd8VPZ6L2pjk4jG0uI0/2P1QEeV6uSawUUJABgru9PVXR+Vz8w2PoloDHV9vlU9zDHlR9J08mp5WQIAxsfudL/b9Z0fUb61jU8iil6all/RD3JQNb9bXpQAgNHyu13e+UH57GxjlIiidvx15dvsJ9PPqYc4pFo+rC5IAMD4+R0v7/6Q8ud8hrZxSkQRs59IX60f4JhSzReoyxEAMAPsjld3f1Q+Q9s4JaJodXXpu9WDG1Wq5X3yYgQAzA6769UMCMtmaRurRBQp+8n5MvnQBmSv9UupTs6QlyIAYHb4XW93vpoFEfksbWOViKK0UMuPqwc2rJoPyAsRADBz/M6XsyAon6ltvBJRhOwn0DvVwxrScnlIXYQAgNnld7+cCQH5TG3jlYh2ulTLr6kHNao0LZerSxAAMMPs7lczISqfrW3MEtFOtViX/npXy3j+3qe+3Lvq8gMAzIt71WwIyWarz9g2boloJ0o1v14+oEHZJXfe4NIDAMyP89RsiMpnbBu3RLTd2U+af1M9mIHdIi49AMAc8VkwmA2h+axtY5eItjP7SfM96qGMKPX50YW+vFFdegCA+XFoFuRH1ayIyGdtG7tEtF0t1PIv1AMZlV1qvbrwAADzKPdqVkTlM7eNXyLa6nYf3P1Hu1o+qB7GiOxSe2D1JQcAmHMPqJkRks1cn71tDBPRVpZq+a/yQQwq9ZNLxQUHAJhrk0vVzIjKZ28bw0S0VS32JzxNPYCBfUBfcACAeeczYjAzQvMZ3MYxEW1FqeYz1MMX1cJ0co663AAA8BmhZkdUPoPbOCaizW6xn3yfevCisgvhvepiAwDgq2xWqBkSlc/iNpaJaDPratmvHrqgPp+m+XR5qQEA8BU2K3xmDGZIXDaL21gmos3KLoNT5AMXlL3e5cddZAAAPLFlNUuistd7ShvPRHS0LV6y+BT7CfKj6mELqZZPDi4wAACOyGeHnCkR2Uz22dzGNBEdTanPL5cPWlBpWi5RlxgAAE/IZoeaKVH5bG5jmog22uK+SVIPWFR2Wd296vICAGBt7lazJSqf0W1cE9FGSsv5LPVwRZVqOVtcXAAAPDmbIWq2ROUzuo1rIlpvi/vL89SDFVXq843y4gIAYM3yjWrGROWzuo1tIlpPXS0H1UMV1GftJ/HT9KUFAMAa2SzxmTKYMXHZrG5jm4jWmv1E+6/lAxXW5Gp5YQEAsE4+U/SsiclndhvfRPRkHX/d8X+66/P96mGKKX9cXVQAAGyUzxY9cyLK9/vsbmOciI6U/WT4v/SDFFOq+Z3qkgIAYMNstqiZE5XP7jbGieiJWpxOvks9QFHZRXSnvKAAADhaNmPU7InKZ3gb50Sksgf7PPXwxJXPXHUxAQCwCXzG6NkTk73m89o4J6JhC9P8D9WDE1Yt1w0vJQAANpPPGjmDgvJZ3sY6ER2ePSA3DB+YsGr5jP3xVHUpAQCwWXzWtJmj51E8N7SxTkRfKfX534mHJSy7fK4cXkYAAGyRK9UsispnehvvRPTMa0/6c12fH1YPS1AfE5cQAABbxmfPYBYFlh/22d7GPNF8Zw/w7+oHJawLhxcQAABbyWfPYBaFZq/5d9uYJ5rfjj9QltQDElbNdwwvHwAAtoPPIDmbgvIZ38Y90XxmD8K4fkKt5S3q8gEAYMvZDFKzKbAL27gnmr8WpvlHxUMRVuon18iLBwCAbTO5Rs2oqHzWt7FPNF/ZA3DL8IEIq+ZHFmt+jb50AADYHj6LfCbJWRXTLW3sE81PqS79ingY4qr53erCAQBgu/lMkrMqKJ/5bfwTzX7H7y/fZg/p59TDEFLNH1EXDQAAO8Vnk5xZEdnM99nf1gCi2S7V8mr5IASVpvkCdckAALBjbDapmRWVz/62BhDNbovL+ST1AERlD+Zt8oIBAGCn2YxSsysq3wHaOkA0m6WaL1WHP6Sav5SmkzPk5QIAwE6zGeWzSs6wgHwHaOsA0ey1UJf+mTr4YU3LAXmxAAAQhM8qOcOC8l2grQVEs5X91Pl+deiDekhdKAAAROMzazDD4rJdoK0FRLNTquU/ywMflF0cVwwvEgAAgrpCzbKofCdo6wHR+Dt+Of+1rpbH1GGPKE3LveISAQAgLptdaqaFZDuB7wZtTSAad/aT22nyoAdlF8b5qy4QAABiO1/NtKh8N2hrAtF4W6hLf0Md8Lgmt4jLAwCA8HyG6dkWk+8IbV0gGmfdqP4zhfmLdkm8UV0eAABE5zPs0CxTMy4g2xHaukA0vlKd/HN5sINKfe7VxQEAwHjkXs24qHxXaGsD0Xg6ee/JX2c/qX1AHeqIUs0P6gsDAICRsZmmZl1Itiv4ztDWB6JxlGr5TXmgg7JL4TJ5WQAAMDY209Ssi8p3hrY+EMXvmdfm71QHObAPyIsCAICR8tk2mHWh+e7Q1gii2HXT/CZ1iKNaWC7nqksCAICx8tmmZl5Ytju0NYIobgv9Cd8nD3BQqeb3qgsCAIDRsxmnZl9UvkO0dYIoZl2f96nDG1Gq5Qv2ek+XlwMAACO3MuNWZp2eg/HkfW2dIIqXPVSn6IMbU1ouy8NLAQCAmWKzTs3AqOw1n9LWCqI47T64+xu6Wj6qDm1INd+/6jIAAGAG+cyTszAi2yV8p2jrBVGMUp9fLg9sUGlaLlGXAQAAM8dmnpqFUflO0dYLop3v+P6EBXVQo0r95G55EQAAMLMmd6uZGJXvFm3NINrZuj6fqQ5pXJOz9SUAAMCsmpytZ2JU+cy2ZhDtXAv95O/rAxpT6vON+gIAAGDW5RvVbIzKd4y2bhDtTF0tB9ThDOqzaVpO0w8/AAAzzmagz8LBbIzLdoy2bhBtf/bQ/Lw8mEGlmveteugBAJgnNgvVjIzKXvPPt7WDaPvafXD3n7KftD6pDmVQH1/1sAMAMId8Jg5mZFy2a/jO0dYPou0p9fl/ygMZVJpO3qkedgAA5o7NRDUro/Kdo60fRFvfrv7EZ6qDGFWq+U75oAMAMK9sNqqZGZXvHm0NIdrauj6fqw5hWNN8pnzIAQCYUz4b5cwMK5/b1hCircsejufrAxiTvd7rD3+wAQDAV12vZmdU9nqf39YRoq3JDtp4HopaPmN/PHXwUAMAAOMzss1KPUfjub6tI0SbX+rzL4pDF5Y9xFcNH2oAAPA4V6kZGpXvIm0tIdq8dh/c/S12wB4aHrjAPiYeZgAAMOAzczBDI3vId5K2nhBtTl2fXyUOW1gL/eRC9TADAIDH85mpZmlc+VVtPSE6+nbtL0v6oEWV71APMgAA0Hx26pkak+8mbU0hOrq6Wkb2k155i3qIAQCA5rNzMEtjs92krSlEG29hOf+oPGBBpZqvVQ8wAAB4EjZD1WyNyneUtq4QbSz7iekWdbiCemSx5tfIhxcAAByRz1CfpYPZGpftKG1dIVp/aTn/B3mwwpq8Wz24AABgbXyW6hkbk+8qbW0hWnvfdfWJf6mr+bPqUMWUP6IeWAAAsD4+U/WsDch2Fd9Z2vpCtLbS8srfmK4PVUQ1X6AeVgAAsD4+U+WsDcp3lra+ED15CwfKc9RBiipNy23qQQUAABtks1XN3Kh8d2lrDNGRswPzruEBCuxLi315s3xIAQDAhvhs9Rk7mLmRvautMURPXJrmfyoOT1y1HFAPKAAAODo+Y+XsDcp3mLbOEOlG9V9GmZaH1IMJAAA2h89aOYNDyne0dYZodanP/0kfnJjsAbxi+EACAIBNdYWawVH5LtPWGqKvddw1k6fa4fiiOjQRpZo/JB5GAACw2Wzmqlkcke8yvtO09YboUHY4Xjc8LJEt9uV8+TACAIBN5TNXzeLAXtfWGyL/14nl7xWHJK6ab1UPIgAA2Bo+e+VMDsp3m7bm0LxnB2Lv8ICEVfMXzZvUQwgAALaGz96VGaxmc0x725pD81ya5p8ShyOs1E969QACAICtNunVbI7Kd5y27tA8dvLek7+u6/M96nBElGp+UD94AABgW9gsVjM6pnyP7zpt7aF5K9Xym/pgxGQP12XyoQMAANvDZrGa0VH5rtPWHpqnjlvO36kORFi1fFA+cAAAYFv5TJazOijfedr6Q/PSyt9ULg5DYOeqhw0AAGwvn8mDGR2b7Txt/aF5aKEu/R15EIJKy+Vm9aABAIAdYrNZzeyofPdpaxDNevaTzT51CCJKtXyhm05Olw8ZAADYESuz2We0mN0h2e7T1iCa5exQ/ow8AEHZw7Q8fLgAAEAIy2p2R+U7UFuHaBYr+8ufsJ9oPqI+/Jjy/eKhAgAAQfis1jM8INuBfBdqaxHNWl0t/0N+8HG9Sz1UAAAgBp/Vg9kdm+1CbS2iWWpXXdolP/CgUj+5Wz1QAAAgmsndapZH5TtRW49oVupqfqv6sAN7m36YAABAJD6zBzM8NtuJ2npEs1CqS39PftBBpT7fqB4kAAAQVb5RzfSofDdqaxKNPfvJZao+5Jjy59K0nKYfIgAAEJLNbp/herYHZLtRW5NozKVa/pX8gIOynwj3yQcIAAAEN55/T7/zHamtSzTGjq1L32Qf4ifUhxuRv1b94AAAgFEY2d7hu1Jbm2hsdbX8jvpgw6rlYvnQAACAUfBZLmd8VLYrtbWJxtRCXTpefqBBpT7fqR4YAAAwNvlONeuj8p2prU80lrqaz1EfZlRpuZylHxYAADAqNtPVrA/Ldqa2PtEYSvvL8+UHGVSaluvlgwIAAMbJZrua+VH57tTWKIpeNy3XqQ8xotTnP7A/niofEgAAMEqHZvvKjJfzPxzbndoaRZGzQ/WL8gMMKtVylXpAAADAyNmMV7M/Kt+h2jpFEXvawd3fYgfrIfXhRWQH6r5VDwUAAJgh+T61A0Rkr/ch36XaWkXR6vr8KvXBxTW5cPUDAQAAZoXPer0DRJVf1dYqitTCdHKC/sCiyneoBwIAAMwWn/l6F4jJd6q2XlGU7BC9Q31Ygb1FPQwAAGC2+Mwf7ADB5Xe09YoiZIfoR/QHFVOq+drhQwAAAGaYzX61E0Rlr/lH2ppFO519IDcPP6DAHknT/JpVDwAAAJhdNvt9BxjsBJHd3NYs2slSn/+9+HDCSrW8Rz4AAABgttkOoHaDqHzHausW7UTPOPCsv2gfwnj+Zcw1f0QefAAAMBd8F5A7QkC+Y/mu1dYu2u66Pv+++mDCmpYL1KEHAADzwXcBuSOElX+/rV20nS1MJyfqDySmVMtt6sADAIA5YzuB2hWi8p2rrV+0Xdkbf8nwgwirli8v9uXN8rADAIC54juB7wZyZ4jpkrZ+0XZkh+SF4kOI7ODwkAMAgPnlu8FgVwjNXvML2xpGW5292berDyGohw4/2AAAAM53hMHOEJa93tvbGkZbWdfnl6oPIKpUy97hwQYAAPAdQe0OceWXtnWMtqLj9k2emvr8qH7z47HX+iF5sAEAAFbkD6kdIiLfwXwXa2sZbXZdLa9Tb3xUi305Xx9qAACAlX8w7Xy1Q4Rlu1hby2gzW1jO3yvf8KhqvlUdaAAAgMP5ziB3iaB8J2vrGW1W9hPEeP4+lloe66b5TeowAwAAHM53hpXdQe0UEdlO1tYz2ozScv4p+UYHlWqZqoMMAAAg2e6gdoqofDdraxodVWe+4I+kmu9Rb3JEqc8PygMMAABwRPlBtVtE5LuZ72htW6ON1tWl/6Le4KgWp/kyfXgBAACemO8QarcIy3a0tq7RRtq1vxwr39i4PqgOLgAAwFr4LjHYLULzXa2tbbTeulreqN7UsKblXHVoAQAA1sJ3CbljRGW7WlvbaD2l5fy35RsalB3Om4eHFQAAYANuVrtGVL6ztfWN1lpX89XqzYzIDuQX7I9vGBxSAACAdWs7he8Wcu8Ix3a2tr7RWrI37F/KNzKoNC3Lw0MKAACwYbZbqJ0jLNvd2hpHR+qpe0/+46nPH5ZvYkj5fnlAAQAAjoLvGHr3iMd3N9/h2jpHT1Q3Lf9dvYGBvUsdTgAAgKPhO8Zg54jNdri2zpFq4Zp8nHzjgrKfXu5RBxMAAGBzjOc/muV8l2trHQ2zN+gtwzcstFrepg8lAADA0fNdQ+4gcb2lrXV0eOlA/gHxZoWVarlJHUgAAIBNZTuH2kWi8p2urXf0lVKfe/VmxZQ/l+rk9fIwAgAAbCbbOXz30DtJPL7TtfWOvG46ebF6o8KqeZ88iAAAAFvAdw+5k0Rlu11b8+a7Y+vSN9nm/3H5JgWUavmEOoAAAABbynYQtZtE5Lud73ht3Zvfulp+R71BYdVysTx8AAAAW8h3ELmbRGU7Xlv35rOFunS8fGOCSsvlLnXwAAAAtoXtImpHicp3vbb2zV9dzeeoNyUqO2BnrTpwAAAA2+cstaOEZbteW/vmq1SXfki+IUHZTyQ3iMMGAACwrXwnUbtKVL7ztfVvfko1X6fejIjstf5Bd6Ccqg4bAADAdlrZSXw3ETtLRL7ztfVvPupq+bfqjQjsKnXQAAAAdoLvJoNdJTbb/doaONs9oz/hz6ZaPiXfhIBSn+9TBwwAAGBn5fvU7hKR736+A7Z1cHbrav4/6g2Iyg7SRasPFgAAwI67SO0uYdkO2NbB2Sz1JzxbfuNB2U9Kd4hDBQAAEES+Q+0wUfku2NbC2cs2+QvUNx1WnbxVHyoAAICd57uK3GGisl2wrYWzVddPXiC/4aDsJ6Rr1YECAACIJV+rdpm4Ji9o6+HslGp5r/5m47HX+uk0za/RhwkAACAQ31lsd1E7TUS+E7b1cDbqavll9Y1GlablPfIgAQAARGS7i9ppwrLdsK2J425Xf8K32ub+GflNBmSv9aPyAAEAAERmO4zabSLy3dB3xLYujreu5t9T32Bg75CHBwAAIDDfYQY7TWy2I7Z1cZyl/sSJ/MaCStNymzo4AAAAo2C7jNpxovJdsa2N4yvVfLH6pqJK/dIeeWgAAABGYWmP2nGi8l2xrY3jKu0vL1TfUGAH9YEBAAAYD99pBjtOaL4ztvVxPKVablffTESpzw+rgwIAADBO+WG180TkO2NbH8dRt5xfqr6RwPbqQwIAADA+vtsMdp3YbHdsa2Tsdl31nL9qP0U8Kr+JgFLNH1YHBAAAYNRsx1G7T0S+O/oO2dbJuHV9PlV9A1Et9uV8eTgAAABGzHcctfvElU9t62TM0v5ysn7hUeVb1cEAAACYBb7r6B0oJt8l21oZL3tDr1AvOqRaHuum+U3DAwEAADArfNdZ2XnULhSQveYr2loZK/uJ4SfVCw6rlunwMAAAAMwa33nkLhRW/sm2Xgbpy8f8YXsj79YvNp40LQ8ODwEAAMDMst1H7UQR2eu923fLtmXufLZ5/4Z6oYFdvuoAAAAAzCjffQa7UHD5N9qaubMtHDjxO/QLDKqWD6oDAAAAMMt8B5K7UVC+Y7Z1c+eyF/KG4QsL7lz14QMAAMwy34EGO1F0b2jr5s7UTcvfEi8qLPuQbx5+6AAAAHPkZrUjhWW7Zls7tz97s66SLyqgVFf+a21vGHzYAAAAc2NlFzq0E8l9KRp7zVe1tXN76/r8IvWCwqqlDj9sAACAeeM7kdyVwsovauvn9nTs7d//9anPH9IvJqJ8v/qgAQAA5pHvRnpnisd3Tt892xq69XX95GXqhUSVar5UfcgAAABzyXYjtTPFNXlZW0O3toXlfJx+ATHZTwH3yA8YAABgruV71O4Ule+gbR3duuwL7Rl+4eDepj9cAACA+eU70mBnim5PW0e3prScf0B80bhquUl9sAAAAFj5B9NukjtUUL6LtrV080s19+qLhlTz59N08nr1oQIAAMDYruQ7k9ylAvJdtK2lm1tXl16svmBYNe+XHygAAAC+yncmuUtFZTtpW083p6dffeKftA364/KLBZRq+YT6IAEAACDY7qR2qoh8J/XdtK2pR19Xy2+rLxTWtFwsP0QAAACs4ruT3Kmist20ralHV1rOi/ILBGUf1l3DDw8AAABP6i61W0XlO2pbVzeebcyj+ldPpGk5S3xwAAAAOBLbodRuFZbtqG1d3VhdXfoH8jcGAAAAdprtqm1tXX+p5mvlbwoAAADsMN9V29q6vrpa/o36DQEAAIAwbGdt6+va2rW//BnbkB+UvxkAAAAQhO+svru2NfbJs834f6vfCAAAAAjHdte2xh65rubd8jcAAAAAorIdtq2zT1zq89vlLwYAAACC8h22rbO6ri79sPqFAAAAQHi2y7a1dnW2Cd8kfxEAAAAQnO+yba19fN20vET9AgAAAGA0bKdt6+3XSjW/T/7FAAAAwEj4TtvW20MtTsvz1F8IAAAAjI3vtm3NXflXip2j/iIAAABgdGy3XVlyFw6c+B3yLwAAAABGynfcY7rp5MXqTwIAAACjZTuu/+d+f1v+SQAAAGCsbMc9JtXyNvknAQAAgJFKfTnb/yMR16g/CQAAAIyV77j+7899QP1JAAAAYKx8x/X/RfdB9ScBAACAsfId1/8X3WvVnwQAAADGyndc/mE0AAAAzJyVfxjN/o9XDP8EAAAAMHKvOKZbzj8n/gQAAAAwXrbjHrPrmnKs/JMAAADASPmOe4zX1XyO+gsAAACA8cnnriy53uL+8jz9FwEAAADjsjgtz2tr7qG6mm9VfyEAAAAwGrbTtvX2ay1MJ78k/2IAAABgJHynbevt40t9frP6BQAAAEB0vsu2tXZ1i5csPiXV8l71CwEAAICoUl9u9l22rbW61J84Ub8YAAAAiMp32LbOHrl0oPyM+g0AAACAaHx3bWvs2tq1nE+yX3jL8DcCAAAAgrhl4UB5Tltf19euvSd/Y+rLHvGbAgAAADsm1bLHd9W2tm68rpZfTjW/T30RAAAAYLus7KS2m7Y1dfPqpvkHU1/OU18UAAAA2CorO6jtom0t3boW+xOeZl/slNTn37I/nmWb9TX2fz+gXhQAAACwVr5THtotbcc8tGue0l397Ke3NXQdHXPM/w+LdBQvQyJLdgAAAABJRU5ErkJggg==\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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(2/100mL)<\\/html>\",\"<html>Station Number: 96<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 97<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 101<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (412/100mL)<\\/html>\",\"<html>Station Number: 102<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (327/100mL)<\\/html>\",\"<html>Station Number: 103<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (173/100mL)<\\/html>\",\"<html>Station Number: 104<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1020/100mL)<\\/html>\",\"<html>Station Number: 105<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (50/100mL)<\\/html>\",\"<html>Station Number: 106<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (48/100mL)<\\/html>\",\"<html>Station Number: 107<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (150/100mL)<\\/html>\",\"<html>Station Number: 108<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (123/100mL)<\\/html>\",\"<html>Station Number: 109<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 110<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (4/100mL)<\\/html>\",\"<html>Station Number: 111<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: > 999 (1033/100mL)<\\/html>\",\"<html>Station Number: 112<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 113<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (20/100mL)<\\/html>\",\"<html>Station Number: 114<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (140/100mL)<\\/html>\",\"<html>Station Number: 115<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (100/100mL)<\\/html>\",\"<html>Station Number: 116<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (53/100mL)<\\/html>\",\"<html>Station Number: 118<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (33/100mL)<\\/html>\",\"<html>Station Number: 120<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (73/100mL)<\\/html>\",\"<html>Station Number: 129<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (92/100mL)<\\/html>\",\"<html>Station Number: 132<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (467/100mL)<\\/html>\",\"<html>Station Number: 133<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1500/100mL)<\\/html>\",\"<html>Station Number: 135<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (7/100mL)<\\/html>\",\"<html>Station Number: 137<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (80/100mL)<\\/html>\",\"<html>Station Number: 138<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (333/100mL)<\\/html>\",\"<html>Station Number: 139<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (96/100mL)<\\/html>\",\"<html>Station Number: 140<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (273/100mL)<\\/html>\",\"<html>Station Number: 141<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (287/100mL)<\\/html>\",\"<html>Station Number: 142<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (96/100mL)<\\/html>\",\"<html>Station Number: 143<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 144<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (120/100mL)<\\/html>\",\"<html>Station Number: 145<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (20/100mL)<\\/html>\",\"<html>Station Number: 146<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (10/100mL)<\\/html>\",\"<html>Station Number: 147<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (100/100mL)<\\/html>\",\"<html>Station Number: 148<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (30/100mL)<\\/html>\",\"<html>Station Number: 149<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (56/100mL)<\\/html>\",\"<html>Station Number: 151<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (70/100mL)<\\/html>\",\"<html>Station Number: 152<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (144/100mL)<\\/html>\",\"<html>Station Number: 153<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (700/100mL)<\\/html>\",\"<html>Station Number: 154<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (260/100mL)<\\/html>\",\"<html>Station Number: 155<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (110/100mL)<\\/html>\",\"<html>Station Number: 158<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (220/100mL)<\\/html>\",\"<html>Station Number: 160<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (270/100mL)<\\/html>\",\"<html>Station Number: 161<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (187/100mL)<\\/html>\",\"<html>Station Number: 163<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (180/100mL)<\\/html>\",\"<html>Station Number: 164<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (140/100mL)<\\/html>\",\"<html>Station Number: 165<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (60/100mL)<\\/html>\",\"<html>Station Number: 166<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (107/100mL)<\\/html>\",\"<html>Station Number: 167<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (460/100mL)<\\/html>\",\"<html>Station Number: 168<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (40/100mL)<\\/html>\",\"<html>Station Number: 169<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (575/100mL)<\\/html>\",\"<html>Station Number: 170<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (310/100mL)<\\/html>\",\"<html>Station Number: 171<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (42/100mL)<\\/html>\",\"<html>Station Number: 172<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (280/100mL)<\\/html>\",\"<html>Station Number: 173<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (210/100mL)<\\/html>\",\"<html>Station Number: 174<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (34/100mL)<\\/html>\",\"<html>Station Number: 175<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (980/100mL)<\\/html>\",\"<html>Station Number: 176<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (128/100mL)<\\/html>\",\"<html>Station Number: 177<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 178<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (630/100mL)<\\/html>\",\"<html>Station Number: 179<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (240/100mL)<\\/html>\",\"<html>Station Number: 180<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 181<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (4/100mL)<\\/html>\",\"<html>Station Number: 182<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (32/100mL)<\\/html>\",\"<html>Station Number: 264<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (28/100mL)<\\/html>\",\"<html>Station Number: 265<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 266<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (60/100mL)<\\/html>\",\"<html>Station Number: 267<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (340/100mL)<\\/html>\",\"<html>Station Number: 268<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (560/100mL)<\\/html>\",\"<html>Station Number: 269<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (147/100mL)<\\/html>\",\"<html>Station Number: 270<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (117/100mL)<\\/html>\",\"<html>Station Number: 271<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 1510<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (110/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.53248,28.149932],\"lng\":[-82.783203,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # show selected year, month, and area show_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River')  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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\"],\"index\":[0,1,2,1,1,1,1,3,2,4,4,0,3]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 74<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (168/100mL)<\\/html>\",\"<html>Station Number: 111<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (50/100mL)<\\/html>\",\"<html>Station Number: 114<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (447/100mL)<\\/html>\",\"<html>Station Number: 115<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (80/100mL)<\\/html>\",\"<html>Station Number: 116<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (30/100mL)<\\/html>\",\"<html>Station Number: 139<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (47/100mL)<\\/html>\",\"<html>Station Number: 151<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 153<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (4000/100mL)<\\/html>\",\"<html>Station Number: 154<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (433/100mL)<\\/html>\",\"<html>Station Number: 155<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (170/100mL)<\\/html>\",\"<html>Station Number: 166<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (310/100mL)<\\/html>\",\"<html>Station Number: 178<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (650/100mL)<\\/html>\",\"<html>Station Number: 179<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1010/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,27.937863],\"lng\":[-82.383348,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Manatee County data show_fibmap(mancofibdata, yrsel = 2020, mosel = 7, areasel = 'Little Manatee River')  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\",\"data:image/png;base64,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\"],\"index\":[0,1]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: D3<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (88/100mL)<\\/html>\",\"<html>Station Number: D1<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (365/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.601944401,27.648594001],\"lng\":[-82.294442,-82.2111111]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"Map Fecal Indicator Bacteria matrix results year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"","code":"show_fibmatmap(   fibdata,   yrsel,   areasel,   indic,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   listout = FALSE,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"fibdata input data frame returned read_importfib,  read_importentero, read_importwqp, see details yrsel numeric value indicating year map areasel vector bay segment area names include, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period listout logical return list simple feature objects data used leaflet map, default FALSE warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"leaflet map selected year area showing station matrix scores listout = FALSE (default).  Bay segment scores also shown input data EPCHC. list simple feature objects returned listout = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"Placing mouse cursor item map reveal additional information segment station. input fibdata EPCHC (read_importfib), valid entries areasel include 'Alafia River', 'Hillsborough River', 'Big Bend', 'Cockroach Bay', 'East Lake Outfall', 'Hillsborough Bay', 'Little Manatee River', 'Lower Tampa Bay', 'McKay Bay', 'Middle Tampa Bay', 'Old Tampa Bay', 'Palm River', 'Tampa Bypass Canal', 'Valrico Lake'.  input data EPCHC (read_importentero), valid entries areasel include 'OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR'. Input read_importwqp Manatee County (21FLMANA_WQX) FIB data can also used.  function tested organizations.  Valid entries areasel include 'Big Slough', 'Bowlees Creek', 'Braden River', 'Bud Slough',  'Cedar Creek', 'Clay Gully', 'Cooper Creek', 'Curiosity Creek', 'Frog Creek', 'Gamble Creek', 'Gap Creek', 'Gates Creek', 'Gilley Creek', 'Hickory Hammock Creek', 'Lake Manatee', 'Little Manatee River', 'Lower Manatee River', 'Lower Tampa Bay', 'Manatee River Estuary', 'Mcmullen Creek', 'Mill Creek', 'Mud Lake Slough', 'Myakka River', 'Nonsense Creek', 'Palma Sola Bay', 'Piney Point Creek', 'Rattlesnake Slough', 'Sugarhouse Creek', 'Upper Manatee River', 'Ward Lake', 'Williams Creek' Bay segment matrix categories can shown input data read_importentero).  Stations data chosen specifically downstream endpoints bay segment, whereas datasets appropriate estimating bay segment outcomes.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"","code":"# non-EPCHC, non Manatee County data show_fibmatmap(enterodata, yrsel = 2020, indic = 'entero', areasel = 'OTB') #> Warning: Stations with insufficient data for lagyr: 21FLHILL_WQX-619, 21FLTPA_WQX-G1SW0095  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Number: 2<br>Category: A\",\"<html>Station Number: 74<br>Category: A\",\"<html>Station Number: 105<br>Category: A\",\"<html>Station Number: 106<br>Category: A\",\"<html>Station Number: 108<br>Category: A\",\"<html>Station Number: 114<br>Category: B\",\"<html>Station Number: 115<br>Category: A\",\"<html>Station Number: 116<br>Category: A\",\"<html>Station Number: 137<br>Category: A\",\"<html>Station Number: 139<br>Category: A\",\"<html>Station Number: 152<br>Category: B\",\"<html>Station Number: 153<br>Category: A\",\"<html>Station Number: 165<br>Category: A\",\"<html>Station Number: 166<br>Category: B\",\"<html>Station Number: 176<br>Category: B\",\"<html>Station Number: 178<br>Category: A\",\"<html>Station Number: 179<br>Category: A\",\"<html>Station Number: 548<br>Category: A\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Report card<br/>categories<\\/b><br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_green.png?raw=true' style='width:10px;height:10px;'> A<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_yellow.png?raw=true' style='width:10px;height:10px;'> B<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_orange.png?raw=true' style='width:10px;height:10px;'> C<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_red.png?raw=true' style='width:10px;height:10px;'> D<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_purple.png?raw=true' style='width:10px;height:10px;'> E\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,28.149932],\"lng\":[-82.474942,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Manatee County data show_fibmatmap(mancofibdata, yrsel = 2020, indic = 'fcolif', areasel = 'Lower Manatee River')  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segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"","code":"show_fibmatrix(   fibdata,   yrrng = NULL,   stas = NULL,   bay_segment = NULL,   indic = NULL,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   txtsz = 3,   asreact = FALSE,   nrows = 10,   family = NA,   angle = 90,   size = 10,   hjust = 0,   plotly = FALSE,   width = NULL,   height = NULL,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"fibdata input data frame returned read_importfib, read_importentero, read_importwqp, see details yrrng numeric vector indicating min, max years include, defaults range years data, see details stas optional vector stations include, see details bay_segment optional vector bay segment names include, supercedes stas provided, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period txtsz numeric size text plot, applies tab = FALSE.  Use txtsz = NULL suppress. asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table family optional chr string indicating font family text labels angle numeric angle x-axis text labels size numeric size x-axis text labels hjust numeric horizontal justification x-axis text labels plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"static ggplot object returned default. reactable table returned asreact = TRUE.  interactive plotly object returned plotly = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL Fecal Coliform 130 CFU / 100 mL Enterococcus.  Bay segments used instead stations bay_segment NULL input data read_importentero.  likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3).  Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 document http://publicfiles.dep.state.fl.us/DEAR/BMAP/Tampa/MST%20Report/Fecal%20BMAP%20DST%20Final%20Report%20--%20June%202008.pdf Morrison et al. 2009 BASIS 5 proceedings. default stations fecal coliform data used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins bay_segment NULL input data read_importfib.  include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137).  stations can plotted using stas argument.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"","code":"show_fibmatrix(fibdata)   # change the threshold show_fibmatrix(fibdata, threshold = 200)   # change the indicator show_fibmatrix(fibdata, indic = 'entero')   # show matrix for only dry samples show_fibmatrix(enterodata, indic = 'entero', lagyr = 1, subset_wetdry = \"dry\",                temporal_window = 2, wet_threshold = 0.5) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Show Habitat Master Plan progress report card — show_hmpreport","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"Show Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"show_hmpreport(   acres,   subtacres,   hmptrgs,   typ,   twocol = FALSE,   strata = c(\"Subtidal\", \"Intertidal\", \"Supratidal\"),   ycollapse = FALSE,   text = 2.5,   xang = 25,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals typ character string indicating \"targets\" \"goals\" twocol logical indicating two colors shown target goals met symbols indicate likelihood attaining targets goals, see details strata character string indicating strata plot, one many \"Subtidal\", \"Intertidal\", \"Supratidal\" ycollapse logical indicating y-axis collapsed year data, see details text numeric indicating text size proportion target goal met habitat types shown cell types symbols twocol = T, use NULL suppress xang numeric angle habitat labels x-axis (top) family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"ggplot2 object showing overall progress attaining Habitat Master Plan targets goals.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"twocol = F, colors indicate target/goal met likelihood attaining target/goal 2030/2050.  Red indicates target/goal met likely met 2030/2050 (trending target/goal), yellow indicates target/goal met although likely met 2030/2050 (trending target/goal), light green indicates target/goal met although likely met 2030/2050 (trending target/goal), green indicates target/goal met likely met 2030/2050 (trending target/goal).  Numbers cell show proportion target goal met year data available.  twocol = T, colors indicate goal met (green) met (red) symbols cell indicate goal likely met (arrow) (arrow) 2030/2050.  cases, colors trends relative 2030 targets 2050 goals using typ argument. report card provides information artificial reefs, living shorelines, hard bottom habitats.  habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan. subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District.  years dataset typically match dataset collected approximate 2 3 year intervals.  default, year y-axis shown continuous variable, gaps shown years dataset unavailable.  Use ycollapse = TRUE remove years without data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"# view summarized data for report card, targets show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\")   # view summarized data for report card, goals show_hmpreport(acres, subtacres, hmptrgs, typ = \"goals\")   # remove empty years show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE)   # select only subtidal show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE, strata = 'Subtidal')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for indicator reporting — show_matrix","title":"Create a colorized table for indicator reporting — show_matrix","text":"Create colorized table indicator reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(   epcdata,   txtsz = 3,   trgs = NULL,   yrrng = NULL,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   asreact = FALSE,   nrows = 10,   abbrev = FALSE,   family = NA,   historic = TRUE,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for indicator reporting — show_matrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include, defaults range years epcdata bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for indicator reporting — show_matrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly matrix from any matrix function input — show_matrixplotly","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"Creates plotly matrix matrix function input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"show_matrixplotly(   mat,   family = NA,   tooltip = \"Result\",   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"mat input matrix output show_matrix, show_segmatrix, show_wqmatrix, show_tbnimatrix family optional chr string indicating font family text labels tooltip chr string indicating column name tooltip width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"mat <- show_wqmatrix(epcdata) show_matrixplotly(mat)  {\"x\":{\"data\":[{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 10.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 10.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 10.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 10.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 11, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 11.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 11.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 11.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 11.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 11.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 12, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Below (Average: 12.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 12.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 12.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 12.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 13, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 13.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 13.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 13.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 14.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5],\"text\":\"Result: Below (Average: 14.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 14.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 2.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 2.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 2.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 3.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 3.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 3.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 3.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 3.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1991.5,-1990.5,-1990.5,-1991.5,-1991.5,null,-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 3.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 3.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-1986.5,-1985.5,-1985.5,-1986.5,-1986.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5,null,-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2015.5,-2014.5,-2014.5,-2015.5,-2015.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 3.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 4.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 4.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 4.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 4.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 4.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 4.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 4.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 4.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Below (Average: 4.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 5.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 5.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2016.5,-2015.5,-2015.5,-2016.5,-2016.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 5.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 5.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5,null,-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 6.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 6.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 6.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 6.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 7.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 7.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 7.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5,null,-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 8.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 8.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 8.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 9.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 9.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 9.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 9.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 9.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 10.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 10.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Above (Average: 10.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 11, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 11.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 11.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 11.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Above (Average: 11.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Above (Average: 11.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 12, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Above (Average: 12.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 12.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 13, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 13, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 13.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 13.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 13.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 13.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 14.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 16.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 17.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 17.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 18, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 18.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 18.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 20.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 22, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 22.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 25.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 27.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 29.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 29.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 31.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 32.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 36.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 5.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 5.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 5.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5,null,-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 6.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Above (Average: 6.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5,null,-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 7.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5],\"text\":\"Result: Above (Average: 8.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5],\"text\":\"Result: Above (Average: 8.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Above (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Above (Average: 9.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-2017.5,-2016.5,-2016.5,-2017.5,-2017.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Above (Average: 9.5, Threshold: 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data recent year approximated five year monthly averages parameter outtxt1 optional text NMC action 1, added outcome column outtxt2 optional text NMC action 2, added outcome column outtxt3 optional text NMC action 3, added outcome column outtxt45 optional text NMC actions 4 5, added outcome column txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"flextable object showing reasonable assurance compliance bay segment selected year within five-year period.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Choosing bay_segment = 'RALTB' work epcdata additional data needed use option.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2)    years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years    years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/   necessary due observed water 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1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-88623153{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Bay Segment Reasonable Assurance Assessment StepsDATA USED TO ASSESS ANNUAL REASONABLE ASSURANCEOUTCOMEYear 1 (2022)Year 2 (2023)Year 3 (2024)Year 4 (2025)Year 5 (2026)NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/LNo (7.1)No (6.2)All years below threshold so far, not necessary for NMC Actions 2-5NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive yearsNoNoAll years met threshold, not necessary for NMC Actions 3-5NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/yearN/AN/ANot necessary due to observed water quality and seagrass conditions in the bay segmentNMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation periodNot necessary when chlorophyll-a threshold met"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":null,"dir":"Reference","previous_headings":"","what":"Create reactable table from matrix data — show_reactable","title":"Create reactable table from matrix data — show_reactable","text":"Create reactable table matrix data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create reactable table from matrix data — show_reactable","text":"","code":"show_reactable(totab, colfun, nrows = 10, txtsz = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create reactable table from matrix data — show_reactable","text":"totab data frame wide format summarized results colfun Function specifying colors treated cell background nrows numeric specifying number rows table txtsz numeric indicating text size cells, use txtsz = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create reactable table from matrix data — show_reactable","text":"reactable table","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create reactable table from matrix data — show_reactable","text":"function used internally within show_matrix show_wqmatrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create reactable table from matrix data — show_reactable","text":"","code":"data(targets) data(epcdata)  library(tidyr) library(dplyr) #>  #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #>  #>     filter, lag #> The following objects are masked from ‘package:base’: #>  #>     intersect, setdiff, setequal, union  # data totab <- anlz_avedat(epcdata) %>%   .$ann %>%   filter(var %in% 'mean_chla') %>%   left_join(targets, by = 'bay_segment') %>%   select(bay_segment, yr, val, chla_thresh) %>%   mutate(     bay_segment = factor(bay_segment, levels = c('OTB', 'HB', 'MTB', 'LTB')),      outcome = case_when(       val < chla_thresh ~ 'green',       val >= chla_thresh ~ 'red'     )   ) %>%   select(bay_segment, yr, outcome) %>%   spread(bay_segment, outcome)  # color function colfun <- function(x){    out <- case_when(     x == 'red' ~ '#FF3333',     x == 'green' ~ '#33FF3B'   )    return(out)  }  show_reactable(totab, colfun)  {\"x\":{\"tag\":{\"name\":\"Reactable\",\"attribs\":{\"data\":{\"yr\":[1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"OTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"green\"],\"HB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"MTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"LTB\":[\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"]},\"columns\":[{\"id\":\"yr\",\"name\":\"Year\",\"type\":\"numeric\",\"style\":{\"fontSize\":\"16px\"}},{\"id\":\"OTB\",\"name\":\"OTB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"backgrou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a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"Create barplot seagrass coverage time Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(   seagrass,   maxyr = 2022,   family = NA,   lastlab = \"acres\",   axsbrk = c(0.08, 0.1) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"seagrass input data.frame included package seagrass maxyr numeric maximum year plot family optional chr string indicating font family text labels lastlab chr string text append label last bar barplot axsbrk numeric vector length two indicating x-axis break occurs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"grid object showing acres total seagrass coverage Tampa Bay time.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"function creates flagship seagrass coverage graphic report coverage changes time.  data pre-processed included package seagrass dataset.  Original data Southwest Florida Water Management District available online https://data-swfwmd.opendata.arcgis.com/.  function data used create plot distinct used transect monitoring program.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(seagrass)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot metal concentrations against aluminum — show_sedimentalratio","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Plot metal concentrations aluminum","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot, must metal yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"ggplot object plotly object plotly = TRUE showing ratio selected parameter plotted aluminum concentrations collected site. Black lines show linear fit log-log model 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"plot shows selected contaminant concentration relative aluminum, latter present common metal Earth's crust.  elevated ratio metal parameter relative aluminum suggests higher background concentrations. Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Schropp, S. J., Graham Lewis, F., Windom, H. L., Ryan, J. D., Calder, F. D., & Burney, L. C. 1990. Interpretation metal concentrations estuarine sediments Florida using aluminum reference element. Estuaries. 13:227-235.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(sedimentdata, param = 'Arsenic') #> Warning: log-10 transformation introduced infinite values. #> Warning: log-10 transformation introduced infinite values."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sediment concentration averages by bay segment — show_sedimentave","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Plot sediment concentration averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"ggplot object plotly object plotly = TRUE showing sediment averages 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(sedimentdata, param = 'Arsenic')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"Make map sediment contaminants stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(   sedimentdata,   param,   yrrng = c(1993, 2022),   funding_proj = \"TBEP\",   weight = 1.5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" weight numeric outline width station points map","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"map shows sediment contaminant concentrations selected parameter relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available.  Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend.  TEL PEL thresholds available, map sediment concentrations shown warning returned console.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(sedimentdata, param = 'Arsenic')  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mg/kg\",\"StationNumber: 93LTB39, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93LTB40, Year: 1993, Value: 10.3 mg/kg\",\"StationNumber: 93MTB41, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB42, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB43, Year: 1993, Value: 2.2 mg/kg\",\"StationNumber: 93MTB44, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB45, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93MTB47, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB48, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93MTB49, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93MTB50, Year: 1993, Value: 0.4 mg/kg\",\"StationNumber: 93MTB51, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB52, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB53, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB54, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB55, Year: 1993, Value: 5.4 mg/kg\",\"StationNumber: 93MTB56, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB57, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB58, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB59, Year: 1993, Value: 1.7 mg/kg\",\"StationNumber: 93MTB60, Year: 1993, Value: 2.4 mg/kg\",\"StationNumber: 93MTB61, Year: 1993, Value: 3.6 mg/kg\",\"StationNumber: 93OTB63, Year: 1993, Value: 5.5 mg/kg\",\"StationNumber: 93OTB64, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93OTB65, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB66, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB67, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB68, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB69, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB70, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93OTB71, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB72, Year: 1993, Value: 1.3 mg/kg\",\"StationNumber: 93OTB73, Year: 1993, Value: 0.7 mg/kg\",\"StationNumber: 93OTB76, Year: 1993, Value: 1.8 mg/kg\",\"StationNumber: 93OTB77, Year: 1993, Value: 0.3 mg/kg\",\"StationNumber: 93OTB78, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93OTB79, Year: 1993, Value: 3.7 mg/kg\",\"StationNumber: 93OTB80, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB83, Year: 1993, Value: 0.6 mg/kg\",\"StationNumber: 94HB03, Year: 1994, Value: 11.53 mg/kg\",\"StationNumber: 94HB04, Year: 1994, Value: 8.831 mg/kg\",\"StationNumber: 94HB05, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB06, Year: 1994, Value: 0.469 mg/kg\",\"StationNumber: 94HB07, Year: 1994, Value: 18.34 mg/kg\",\"StationNumber: 94HB08, Year: 1994, Value: 6.249 mg/kg\",\"StationNumber: 94HB09, Year: 1994, Value: 3.867 mg/kg\",\"StationNumber: 94HB10, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB12, Year: 1994, Value: 2.244 mg/kg\",\"StationNumber: 94HB13, Year: 1994, Value: 0.523 mg/kg\",\"StationNumber: 94HB14, Year: 1994, Value: 1.158 mg/kg\",\"StationNumber: 94HB15, Year: 1994, Value: 1.3 mg/kg\",\"StationNumber: 94HB16, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB18, Year: 1994, Value: 0.785 mg/kg\",\"StationNumber: 94HB19, Year: 1994, Value: 2.992 mg/kg\",\"StationNumber: 94HB20, Year: 1994, Value: 6.697 mg/kg\",\"StationNumber: 94HB21, Year: 1994, Value: 4.794 mg/kg\",\"StationNumber: 94HB22, Year: 1994, Value: 0.559 mg/kg\",\"StationNumber: 94HB23, Year: 1994, Value: 5.137 mg/kg\",\"StationNumber: 94LTB24, Year: 1994, Value: 2.557 mg/kg\",\"StationNumber: 94LTB25, Year: 1994, Value: 10.23 mg/kg\",\"StationNumber: 94LTB26, Year: 1994, Value: 0.982 mg/kg\",\"StationNumber: 94LTB27, Year: 1994, Value: 2.211 mg/kg\",\"StationNumber: 94LTB28, Year: 1994, Value: 3.464 mg/kg\",\"StationNumber: 94LTB29, Year: 1994, Value: 2.906 mg/kg\",\"StationNumber: 94LTB30, Year: 1994, Value: 3.515 mg/kg\",\"StationNumber: 94LTB31, Year: 1994, Value: 1.09 mg/kg\",\"StationNumber: 94LTB32, Year: 1994, Value: 0.538 mg/kg\",\"StationNumber: 94LTB33, Year: 1994, Value: 4.454 mg/kg\",\"StationNumber: 94LTB34, Year: 1994, Value: 1.975 mg/kg\",\"StationNumber: 94LTB35, Year: 1994, Value: 0.164 mg/kg\",\"StationNumber: 94LTB36, Year: 1994, Value: 4.695 mg/kg\",\"StationNumber: 94LTB37, Year: 1994, Value: 5.033 mg/kg\",\"StationNumber: 94LTB38, Year: 1994, Value: 2.197 mg/kg\",\"StationNumber: 94LTB39, Year: 1994, Value: 12.93 mg/kg\",\"StationNumber: 94LTB40, Year: 1994, Value: 8.954 mg/kg\",\"StationNumber: 94MR23, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR24, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR26, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR27, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR28, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR29, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR31, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR32, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR34, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR43, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MTB41, Year: 1994, Value: 0.465 mg/kg\",\"StationNumber: 94MTB42, Year: 1994, Value: 0.074 mg/kg\",\"StationNumber: 94MTB43, Year: 1994, Value: 6.242 mg/kg\",\"StationNumber: 94MTB44, Year: 1994, Value: 3.975 mg/kg\",\"StationNumber: 94MTB45, Year: 1994, Value: 0.417 mg/kg\",\"StationNumber: 94MTB47, Year: 1994, Value: 6.591 mg/kg\",\"StationNumber: 94MTB48, Year: 1994, Value: 0.209 mg/kg\",\"StationNumber: 94MTB49, Year: 1994, Value: 9.619 mg/kg\",\"StationNumber: 94MTB50, Year: 1994, Value: 1.634 mg/kg\",\"StationNumber: 94MTB51, Year: 1994, Value: 1.203 mg/kg\",\"StationNumber: 94MTB52, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB53, Year: 1994, Value: 0.173 mg/kg\",\"StationNumber: 94MTB54, Year: 1994, Value: 2.975 mg/kg\",\"StationNumber: 94MTB55, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB56, Year: 1994, Value: 0.028 mg/kg\",\"StationNumber: 94MTB57, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB58, Year: 1994, Value: 11.58 mg/kg\",\"StationNumber: 94MTB59, Year: 1994, Value: 1.603 mg/kg\",\"StationNumber: 94MTB60, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB61, Year: 1994, Value: 2.096 mg/kg\",\"StationNumber: 94OTB63, Year: 1994, Value: 8.811 mg/kg\",\"StationNumber: 94OTB64, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB65, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB66, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB67, Year: 1994, Value: 1.513 mg/kg\",\"StationNumber: 94OTB68, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB69, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB70, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB71, Year: 1994, Value: 1.415 mg/kg\",\"StationNumber: 94OTB72, Year: 1994, Value: 0.159 mg/kg\",\"StationNumber: 94OTB73, Year: 1994, Value: 1.64 mg/kg\",\"StationNumber: 94OTB76, Year: 1994, Value: 0.683 mg/kg\",\"StationNumber: 94OTB77, Year: 1994, Value: 0.111 mg/kg\",\"StationNumber: 94OTB78, Year: 1994, Value: 4.152 mg/kg\",\"StationNumber: 94OTB79, Year: 1994, Value: 0.086 mg/kg\",\"StationNumber: 94OTB80, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB83, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94TCB22, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB37, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB38, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB39, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB40, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB41, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB42, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 95BCB01, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB02, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB03, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB04, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB05, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB06, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB07, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB08, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB09, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB10, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB11, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB12, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB13, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB14, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB15, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB16, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB17, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB18, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB19, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB20, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB21, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95HB14, Year: 1995, Value: 0.565 mg/kg\",\"StationNumber: 95HB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB17, Year: 1995, Value: 0.844 mg/kg\",\"StationNumber: 95HB18, Year: 1995, Value: 2.685 mg/kg\",\"StationNumber: 95HB19, Year: 1995, Value: 0.011 mg/kg\",\"StationNumber: 95HB22, Year: 1995, Value: 0.134 mg/kg\",\"StationNumber: 95HB23, Year: 1995, Value: 2.499 mg/kg\",\"StationNumber: 95HB24, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB25, Year: 1995, Value: 0.258 mg/kg\",\"StationNumber: 95HB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB28, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB37, Year: 1995, Value: 1.482 mg/kg\",\"StationNumber: 95HB38, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB40, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB41, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB42, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB43, Year: 1995, Value: 0.432 mg/kg\",\"StationNumber: 95HB44, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB45, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB46, Year: 1995, Value: 3.023 mg/kg\",\"StationNumber: 95HB48, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB49, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB51, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB52, Year: 1995, Value: 1.696 mg/kg\",\"StationNumber: 95HB54, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB55, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB56, Year: 1995, Value: 4.81 mg/kg\",\"StationNumber: 95LTB01, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB02, Year: 1995, Value: 0.076 mg/kg\",\"StationNumber: 95LTB04, Year: 1995, Value: 1.513 mg/kg\",\"StationNumber: 95LTB05, Year: 1995, Value: 1.347 mg/kg\",\"StationNumber: 95LTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB07, Year: 1995, Value: 0.876 mg/kg\",\"StationNumber: 95LTB08, Year: 1995, Value: 2.389 mg/kg\",\"StationNumber: 95LTB09, Year: 1995, Value: 1.187 mg/kg\",\"StationNumber: 95LTB10, Year: 1995, Value: 1.839 mg/kg\",\"StationNumber: 95LTB11, Year: 1995, Value: 2.845 mg/kg\",\"StationNumber: 95LTB12, Year: 1995, Value: 0.953 mg/kg\",\"StationNumber: 95LTB13, Year: 1995, Value: 1.192 mg/kg\",\"StationNumber: 95LTB15, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB17, Year: 1995, Value: 1.678 mg/kg\",\"StationNumber: 95LTB18, Year: 1995, Value: 1.29 mg/kg\",\"StationNumber: 95LTB19, Year: 1995, Value: 0.872 mg/kg\",\"StationNumber: 95LTB20, Year: 1995, Value: 0.139 mg/kg\",\"StationNumber: 95LTB21, Year: 1995, Value: 0.009 mg/kg\",\"StationNumber: 95LTB23, Year: 1995, Value: 1.475 mg/kg\",\"StationNumber: 95LTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB29, Year: 1995, Value: 0.225 mg/kg\",\"StationNumber: 95MR23, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR24, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR25, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR26, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR27, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR28, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR29, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR31, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR32, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR34, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR43, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MTB03, Year: 1995, Value: 0.098 mg/kg\",\"StationNumber: 95MTB04, Year: 1995, Value: 0.296 mg/kg\",\"StationNumber: 95MTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB07, Year: 1995, Value: 2.145 mg/kg\",\"StationNumber: 95MTB08, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB10, Year: 1995, Value: 0.254 mg/kg\",\"StationNumber: 95MTB15, Year: 1995, Value: 0.107 mg/kg\",\"StationNumber: 95MTB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB17, Year: 1995, Value: 9.688 mg/kg\",\"StationNumber: 95MTB18, Year: 1995, Value: 5.681 mg/kg\",\"StationNumber: 95MTB19, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB21, Year: 1995, Value: 0.19 mg/kg\",\"StationNumber: 95MTB24, Year: 1995, Value: 0.144 mg/kg\",\"StationNumber: 95MTB25, Year: 1995, Value: 0.264 mg/kg\",\"StationNumber: 95MTB26, Year: 1995, Value: 0.067 mg/kg\",\"StationNumber: 95MTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB30, Year: 1995, Value: 0.738 mg/kg\",\"StationNumber: 95MTB31, Year: 1995, Value: 0.483 mg/kg\",\"StationNumber: 95MTB32, Year: 1995, Value: 0.445 mg/kg\",\"StationNumber: 95MTB34, Year: 1995, Value: 1.065 mg/kg\",\"StationNumber: 95MTB35, Year: 1995, Value: 0.129 mg/kg\",\"StationNumber: 95OTB02, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB03, Year: 1995, Value: 0.259 mg/kg\",\"StationNumber: 95OTB05, Year: 1995, Value: 0.772 mg/kg\",\"StationNumber: 95OTB06, Year: 1995, Value: 0.84 mg/kg\",\"StationNumber: 95OTB07, Year: 1995, Value: 0.274 mg/kg\",\"StationNumber: 95OTB08, Year: 1995, Value: 0.087 mg/kg\",\"StationNumber: 95OTB11, Year: 1995, Value: 0.214 mg/kg\",\"StationNumber: 95OTB12, Year: 1995, Value: 0.344 mg/kg\",\"StationNumber: 95OTB13, Year: 1995, Value: 0.269 mg/kg\",\"StationNumber: 95OTB14, Year: 1995, Value: 0.451 mg/kg\",\"StationNumber: 95OTB15, Year: 1995, Value: 7.62 mg/kg\",\"StationNumber: 95OTB17, Year: 1995, Value: 0.59 mg/kg\",\"StationNumber: 95OTB18, Year: 1995, Value: 0.356 mg/kg\",\"StationNumber: 95OTB19, Year: 1995, Value: 3.07 mg/kg\",\"StationNumber: 95OTB20, Year: 1995, Value: 0.314 mg/kg\",\"StationNumber: 95OTB22, Year: 1995, Value: 0.522 mg/kg\",\"StationNumber: 95OTB23, Year: 1995, Value: 0.135 mg/kg\",\"StationNumber: 95OTB24, Year: 1995, Value: 0.476 mg/kg\",\"StationNumber: 95OTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB26, Year: 1995, Value: 0.226 mg/kg\",\"StationNumber: 95OTB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB30, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95TCB22, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB37, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB38, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB39, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB40, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB41, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB42, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 96BCB02, Year: 1996, Value: 1.681 mg/kg\",\"StationNumber: 96BCB04, Year: 1996, Value: 4.387 mg/kg\",\"StationNumber: 96BCB07, Year: 1996, Value: 1.51 mg/kg\",\"StationNumber: 96BCB08, Year: 1996, Value: 2.112 mg/kg\",\"StationNumber: 96BCB12, Year: 1996, Value: 1.308 mg/kg\",\"StationNumber: 96BCB13, Year: 1996, Value: 5.299 mg/kg\",\"StationNumber: 96BCB15, Year: 1996, Value: 3.323 mg/kg\",\"StationNumber: 96BCB19, Year: 1996, Value: 0.7 mg/kg\",\"StationNumber: 96BCB24, Year: 1996, Value: 0.754 mg/kg\",\"StationNumber: 96BCB26, Year: 1996, Value: 0.16 mg/kg\",\"StationNumber: 96BCB27, Year: 1996, Value: 0.783 mg/kg\",\"StationNumber: 96BCB30, Year: 1996, Value: 0.546 mg/kg\",\"StationNumber: 96BCB31, Year: 1996, Value: 0.256 mg/kg\",\"StationNumber: 96BCB34, Year: 1996, Value: 0.29 mg/kg\",\"StationNumber: 96BCB36, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96BCB39, Year: 1996, Value: 0.25 mg/kg\",\"StationNumber: 96BCB40, Year: 1996, Value: 1.148 mg/kg\",\"StationNumber: 96BCB41, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96BCB44, Year: 1996, Value: 0.98 mg/kg\",\"StationNumber: 96BCB46, Year: 1996, Value: 0.339 mg/kg\",\"StationNumber: 96BCB49, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96HB13, Year: 1996, Value: 2.778 mg/kg\",\"StationNumber: 96HB16, Year: 1996, Value: 0.534 mg/kg\",\"StationNumber: 96HB18, Year: 1996, Value: 1.303 mg/kg\",\"StationNumber: 96HB20, Year: 1996, Value: 4.202 mg/kg\",\"StationNumber: 96HB22, Year: 1996, Value: 3.994 mg/kg\",\"StationNumber: 96HB23, Year: 1996, Value: 2.264 mg/kg\",\"StationNumber: 96HB24, Year: 1996, Value: 0.182 mg/kg\",\"StationNumber: 96HB26, Year: 1996, Value: 0.077 mg/kg\",\"StationNumber: 96HB27, Year: 1996, Value: 2.885 mg/kg\",\"StationNumber: 96HB29, Year: 1996, Value: 1.112 mg/kg\",\"StationNumber: 96HB36, Year: 1996, Value: 1.771 mg/kg\",\"StationNumber: 96HB37, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96HB38, Year: 1996, Value: 2.504 mg/kg\",\"StationNumber: 96HB39, Year: 1996, Value: 1.465 mg/kg\",\"StationNumber: 96HB42, Year: 1996, Value: 2.318 mg/kg\",\"StationNumber: 96HB43, Year: 1996, Value: 2.562 mg/kg\",\"StationNumber: 96HB44, Year: 1996, Value: 1.521 mg/kg\",\"StationNumber: 96HB45, Year: 1996, Value: 0.167 mg/kg\",\"StationNumber: 96HB46, Year: 1996, Value: 7.157 mg/kg\",\"StationNumber: 96HB47, Year: 1996, Value: 0.464 mg/kg\",\"StationNumber: 96HB48, Year: 1996, Value: 4.527 mg/kg\",\"StationNumber: 96HB50, Year: 1996, Value: 0.914 mg/kg\",\"StationNumber: 96HB51, Year: 1996, Value: 0.333 mg/kg\",\"StationNumber: 96HB52, Year: 1996, Value: 0.158 mg/kg\",\"StationNumber: 96HB53, Year: 1996, Value: 0.597 mg/kg\",\"StationNumber: 96HB54, Year: 1996, Value: 0.378 mg/kg\",\"StationNumber: 96HB56, Year: 1996, Value: 5.858 mg/kg\",\"StationNumber: 96LTB01, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB02, Year: 1996, Value: 1.027 mg/kg\",\"StationNumber: 96LTB03, Year: 1996, Value: 1.366 mg/kg\",\"StationNumber: 96LTB04, Year: 1996, Value: 2.045 mg/kg\",\"StationNumber: 96LTB05, Year: 1996, Value: 1.675 mg/kg\",\"StationNumber: 96LTB06, Year: 1996, Value: 0.221 mg/kg\",\"StationNumber: 96LTB07, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB08, Year: 1996, Value: 0.48 mg/kg\",\"StationNumber: 96LTB09, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB10, Year: 1996, Value: 11.04 mg/kg\",\"StationNumber: 96LTB11, Year: 1996, Value: 1.949 mg/kg\",\"StationNumber: 96LTB12, Year: 1996, Value: 0.571 mg/kg\",\"StationNumber: 96LTB13, Year: 1996, Value: 2.568 mg/kg\",\"StationNumber: 96LTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB17, Year: 1996, Value: 6.999 mg/kg\",\"StationNumber: 96LTB18, Year: 1996, Value: 2.186 mg/kg\",\"StationNumber: 96LTB19, Year: 1996, Value: 2.416 mg/kg\",\"StationNumber: 96LTB20, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB21, Year: 1996, Value: 0.131 mg/kg\",\"StationNumber: 96LTB23, Year: 1996, Value: 2.988 mg/kg\",\"StationNumber: 96LTB24, Year: 1996, Value: 1.609 mg/kg\",\"StationNumber: 96LTB25, Year: 1996, Value: 0.876 mg/kg\",\"StationNumber: 96LTB26, Year: 1996, Value: 0.241 mg/kg\",\"StationNumber: 96LTB27, Year: 1996, Value: 2.428 mg/kg\",\"StationNumber: 96MR20, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MR21, Year: 1996, Value: 0.319 mg/kg\",\"StationNumber: 96MR23, Year: 1996, Value: 0.042 mg/kg\",\"StationNumber: 96MR24, Year: 1996, Value: 0.449 mg/kg\",\"StationNumber: 96MR25, Year: 1996, Value: 0.192 mg/kg\",\"StationNumber: 96MR26, Year: 1996, Value: 0.486 mg/kg\",\"StationNumber: 96MR27, Year: 1996, Value: 0.302 mg/kg\",\"StationNumber: 96MR28, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR29, Year: 1996, Value: 0.596 mg/kg\",\"StationNumber: 96MR30, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR31, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR32, Year: 1996, Value: 0.716 mg/kg\",\"StationNumber: 96MR43, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB04, Year: 1996, Value: 0.503 mg/kg\",\"StationNumber: 96MTB05, Year: 1996, Value: 0.329 mg/kg\",\"StationNumber: 96MTB07, Year: 1996, Value: 0.458 mg/kg\",\"StationNumber: 96MTB09, Year: 1996, Value: 2.141 mg/kg\",\"StationNumber: 96MTB10, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96MTB11, Year: 1996, Value: 1.049 mg/kg\",\"StationNumber: 96MTB12, Year: 1996, Value: 0.633 mg/kg\",\"StationNumber: 96MTB13, Year: 1996, Value: 0 mg/kg\",\"StationNumber: 96MTB14, Year: 1996, Value: 6.52 mg/kg\",\"StationNumber: 96MTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB16, Year: 1996, Value: 0.063 mg/kg\",\"StationNumber: 96MTB17, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96MTB18, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB19, Year: 1996, Value: 0.119 mg/kg\",\"StationNumber: 96MTB20, Year: 1996, Value: 4.526 mg/kg\",\"StationNumber: 96MTB23, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB24, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MTB25, Year: 1996, Value: 0.756 mg/kg\",\"StationNumber: 96MTB26, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB30, Year: 1996, Value: 0.024 mg/kg\",\"StationNumber: 96MTB31, Year: 1996, Value: 0.827 mg/kg\",\"StationNumber: 96MTB32, Year: 1996, Value: 5.666 mg/kg\",\"StationNumber: 96MTB34, Year: 1996, Value: 0.664 mg/kg\",\"StationNumber: 96MTB35, Year: 1996, Value: 0.206 mg/kg\",\"StationNumber: 96OTB07, Year: 1996, Value: 0.477 mg/kg\",\"StationNumber: 96OTB11, Year: 1996, Value: 0.239 mg/kg\",\"StationNumber: 96OTB12, Year: 1996, Value: 1.951 mg/kg\",\"StationNumber: 96OTB13, Year: 1996, Value: 0.721 mg/kg\",\"StationNumber: 96OTB14, Year: 1996, Value: 1.631 mg/kg\",\"StationNumber: 96OTB17, Year: 1996, Value: 1.716 mg/kg\",\"StationNumber: 96OTB18, Year: 1996, Value: 1.202 mg/kg\",\"StationNumber: 96OTB19, Year: 1996, Value: 1.134 mg/kg\",\"StationNumber: 96OTB20, Year: 1996, Value: 1.832 mg/kg\",\"StationNumber: 96OTB23, Year: 1996, Value: 0.698 mg/kg\",\"StationNumber: 96OTB24, Year: 1996, Value: 0.749 mg/kg\",\"StationNumber: 96OTB26, Year: 1996, Value: 0.526 mg/kg\",\"StationNumber: 96OTB27, Year: 1996, Value: 0.629 mg/kg\",\"StationNumber: 96OTB29, Year: 1996, Value: 0.574 mg/kg\",\"StationNumber: 96OTB30, Year: 1996, Value: 0.106 mg/kg\",\"StationNumber: 96TCB22, Year: 1996, Value: 3.557 mg/kg\",\"StationNumber: 96TCB36, Year: 1996, Value: 1.001 mg/kg\",\"StationNumber: 96TCB37, Year: 1996, Value: 5.738 mg/kg\",\"StationNumber: 96TCB38, Year: 1996, Value: 2.784 mg/kg\",\"StationNumber: 96TCB39, Year: 1996, Value: 1.919 mg/kg\",\"StationNumber: 96TCB40, Year: 1996, Value: 1.242 mg/kg\",\"StationNumber: 96TCB41, Year: 1996, Value: 1.244 mg/kg\",\"StationNumber: 96TCB42, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 97BCB02, Year: 1997, Value: 0.9 mg/kg\",\"StationNumber: 97BCB08, Year: 1997, Value: 3.79 mg/kg\",\"StationNumber: 97BCB10, Year: 1997, Value: 1.504 mg/kg\",\"StationNumber: 97BCB13, Year: 1997, Value: 1.11 mg/kg\",\"StationNumber: 97BCB17, Year: 1997, Value: 3.833 mg/kg\",\"StationNumber: 97BCB18, Year: 1997, Value: 0.053 mg/kg\",\"StationNumber: 97BCB27, Year: 1997, Value: 7.606 mg/kg\",\"StationNumber: 97BCB30, Year: 1997, Value: 1.439 mg/kg\",\"StationNumber: 97BCB31, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97BCB36, Year: 1997, Value: 0.548 mg/kg\",\"StationNumber: 97BCB37, Year: 1997, Value: 0.041 mg/kg\",\"StationNumber: 97BCB40, Year: 1997, Value: 2.312 mg/kg\",\"StationNumber: 97BCB46, Year: 1997, Value: 1.153 mg/kg\",\"StationNumber: 97BCB50, Year: 1997, Value: 3.046 mg/kg\",\"StationNumber: 97BCB57-1, Year: 1997, Value: 4.964 mg/kg\",\"StationNumber: 97BCB58-1, Year: 1997, Value: 8.192 mg/kg\",\"StationNumber: 97BCB58-2, Year: 1997, Value: 1.739 mg/kg\",\"StationNumber: 97BCB59-1, Year: 1997, Value: 1.017 mg/kg\",\"StationNumber: 97BCB59-2, Year: 1997, Value: 1.042 mg/kg\",\"StationNumber: 97BCB60-2, Year: 1997, Value: 0.932 mg/kg\",\"StationNumber: 97BCB60-4, Year: 1997, Value: 1.016 mg/kg\",\"StationNumber: 97HB10, Year: 1997, Value: 2.262 mg/kg\",\"StationNumber: 97HB13, Year: 1997, Value: 3.367 mg/kg\",\"StationNumber: 97HB18, Year: 1997, Value: 0.393 mg/kg\",\"StationNumber: 97HB22, Year: 1997, Value: 1.588 mg/kg\",\"StationNumber: 97HB23, Year: 1997, Value: 0.17 mg/kg\",\"StationNumber: 97HB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB29, Year: 1997, Value: 1.632 mg/kg\",\"StationNumber: 97HB36, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB37, Year: 1997, Value: 1.131 mg/kg\",\"StationNumber: 97HB38, Year: 1997, Value: 0.753 mg/kg\",\"StationNumber: 97HB39, Year: 1997, Value: 1.737 mg/kg\",\"StationNumber: 97HB43, Year: 1997, Value: 0.107 mg/kg\",\"StationNumber: 97HB44, Year: 1997, Value: 0.576 mg/kg\",\"StationNumber: 97HB45, Year: 1997, Value: 0.888 mg/kg\",\"StationNumber: 97HB46, Year: 1997, Value: 0.424 mg/kg\",\"StationNumber: 97HB48, Year: 1997, Value: 0.494 mg/kg\",\"StationNumber: 97HB50, Year: 1997, Value: 2.002 mg/kg\",\"StationNumber: 97HB53, Year: 1997, Value: 0.349 mg/kg\",\"StationNumber: 97HB54, Year: 1997, Value: 0.918 mg/kg\",\"StationNumber: 97HB55, Year: 1997, Value: 0.597 mg/kg\",\"StationNumber: 97HB56, Year: 1997, Value: 0.564 mg/kg\",\"StationNumber: 97LTB01, Year: 1997, Value: 0.364 mg/kg\",\"StationNumber: 97LTB02, Year: 1997, Value: 0.667 mg/kg\",\"StationNumber: 97LTB03, Year: 1997, Value: 1.481 mg/kg\",\"StationNumber: 97LTB06, Year: 1997, Value: 1.145 mg/kg\",\"StationNumber: 97LTB07, Year: 1997, Value: 1.822 mg/kg\",\"StationNumber: 97LTB09, Year: 1997, Value: 5.154 mg/kg\",\"StationNumber: 97LTB10, Year: 1997, Value: 9.854 mg/kg\",\"StationNumber: 97LTB11, Year: 1997, Value: 10.221 mg/kg\",\"StationNumber: 97LTB12, Year: 1997, Value: 2.644 mg/kg\",\"StationNumber: 97LTB13, Year: 1997, Value: 1.991 mg/kg\",\"StationNumber: 97LTB15, Year: 1997, Value: 0.607 mg/kg\",\"StationNumber: 97LTB17, Year: 1997, Value: 3.416 mg/kg\",\"StationNumber: 97LTB18, Year: 1997, Value: 2.814 mg/kg\",\"StationNumber: 97LTB19, Year: 1997, Value: 2.16 mg/kg\",\"StationNumber: 97LTB20, Year: 1997, Value: 0.558 mg/kg\",\"StationNumber: 97LTB21, Year: 1997, Value: 1.584 mg/kg\",\"StationNumber: 97LTB23, Year: 1997, Value: 2.302 mg/kg\",\"StationNumber: 97LTB24, Year: 1997, Value: 0.57 mg/kg\",\"StationNumber: 97LTB25, Year: 1997, Value: 0.538 mg/kg\",\"StationNumber: 97LTB26, Year: 1997, Value: 0.1 mg/kg\",\"StationNumber: 97LTB28, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MR09, Year: 1997, Value: 0.458 mg/kg\",\"StationNumber: 97MR10, Year: 1997, Value: 0.672 mg/kg\",\"StationNumber: 97MR11, Year: 1997, Value: 2.184 mg/kg\",\"StationNumber: 97MR12, Year: 1997, Value: 1.339 mg/kg\",\"StationNumber: 97MR13, Year: 1997, Value: 1.416 mg/kg\",\"StationNumber: 97MR14, Year: 1997, Value: 1.886 mg/kg\",\"StationNumber: 97MR15, Year: 1997, Value: 1.079 mg/kg\",\"StationNumber: 97MR16, Year: 1997, Value: 1.293 mg/kg\",\"StationNumber: 97MR17, Year: 1997, Value: 0.902 mg/kg\",\"StationNumber: 97MR18, Year: 1997, Value: 1.223 mg/kg\",\"StationNumber: 97MR19, Year: 1997, Value: 1.164 mg/kg\",\"StationNumber: 97MR20, Year: 1997, Value: 1.285 mg/kg\",\"StationNumber: 97MR21, Year: 1997, Value: 1.766 mg/kg\",\"StationNumber: 97MTB02, Year: 1997, Value: 0.086 mg/kg\",\"StationNumber: 97MTB03, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB04, Year: 1997, Value: 0.531 mg/kg\",\"StationNumber: 97MTB05, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB07, Year: 1997, Value: 1.425 mg/kg\",\"StationNumber: 97MTB09, Year: 1997, Value: 0.514 mg/kg\",\"StationNumber: 97MTB10, Year: 1997, Value: 1.592 mg/kg\",\"StationNumber: 97MTB12, Year: 1997, Value: 0.718 mg/kg\",\"StationNumber: 97MTB14, Year: 1997, Value: 1.277 mg/kg\",\"StationNumber: 97MTB15, Year: 1997, Value: 0.612 mg/kg\",\"StationNumber: 97MTB16, Year: 1997, Value: 1.06 mg/kg\",\"StationNumber: 97MTB17, Year: 1997, Value: 1.021 mg/kg\",\"StationNumber: 97MTB18, Year: 1997, Value: 0.336 mg/kg\",\"StationNumber: 97MTB19, Year: 1997, Value: 0.112 mg/kg\",\"StationNumber: 97MTB23, Year: 1997, Value: 0.992 mg/kg\",\"StationNumber: 97MTB24, Year: 1997, Value: 6.807 mg/kg\",\"StationNumber: 97MTB25, Year: 1997, Value: 1.392 mg/kg\",\"StationNumber: 97MTB26, Year: 1997, Value: 0.193 mg/kg\",\"StationNumber: 97MTB30, Year: 1997, Value: 0.442 mg/kg\",\"StationNumber: 97MTB31, Year: 1997, Value: 0.756 mg/kg\",\"StationNumber: 97MTB32, Year: 1997, Value: 8.261 mg/kg\",\"StationNumber: 97MTB35, Year: 1997, Value: 0.47 mg/kg\",\"StationNumber: 97OTB03, Year: 1997, Value: 3.828 mg/kg\",\"StationNumber: 97OTB06, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB07, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB11, Year: 1997, Value: 0.142 mg/kg\",\"StationNumber: 97OTB12, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB13, Year: 1997, Value: 0.724 mg/kg\",\"StationNumber: 97OTB17, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB18, Year: 1997, Value: 0.029 mg/kg\",\"StationNumber: 97OTB19, Year: 1997, Value: 0.012 mg/kg\",\"StationNumber: 97OTB20, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB22, Year: 1997, Value: 0.13 mg/kg\",\"StationNumber: 97OTB23, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB26, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB29, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97TCB01, Year: 1997, Value: 2.943 mg/kg\",\"StationNumber: 97TCB02, Year: 1997, Value: 2.221 mg/kg\",\"StationNumber: 97TCB03, Year: 1997, Value: 4.341 mg/kg\",\"StationNumber: 97TCB04, Year: 1997, Value: 3.585 mg/kg\",\"StationNumber: 97TCB05, Year: 1997, Value: 2.998 mg/kg\",\"StationNumber: 97TCB06, Year: 1997, Value: 1.551 mg/kg\",\"StationNumber: 97TCB07, Year: 1997, Value: 3.303 mg/kg\",\"StationNumber: 97TCB08, Year: 1997, Value: 0.787 mg/kg\",\"StationNumber: 98BCB06, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB09, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB11, Year: 1998, Value: 0.445 mg/kg\",\"StationNumber: 98BCB12, Year: 1998, Value: 2.509 mg/kg\",\"StationNumber: 98BCB15, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98BCB17, Year: 1998, Value: 1.517 mg/kg\",\"StationNumber: 98BCB21, Year: 1998, Value: 0.54 mg/kg\",\"StationNumber: 98BCB27, Year: 1998, Value: 0.102 mg/kg\",\"StationNumber: 98BCB28, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB32, Year: 1998, Value: 0.09 mg/kg\",\"StationNumber: 98BCB38, Year: 1998, Value: 0.595 mg/kg\",\"StationNumber: 98BCB40, Year: 1998, Value: 0.392 mg/kg\",\"StationNumber: 98BCB43, Year: 1998, Value: 0.065 mg/kg\",\"StationNumber: 98BCB46, Year: 1998, Value: 1.568 mg/kg\",\"StationNumber: 98BCB57/1, Year: 1998, Value: 4.454 mg/kg\",\"StationNumber: 98BCB58/1, Year: 1998, Value: 4.341 mg/kg\",\"StationNumber: 98BCB58/2, Year: 1998, Value: 3.761 mg/kg\",\"StationNumber: 98BCB59/1, Year: 1998, Value: 0.088 mg/kg\",\"StationNumber: 98BCB59/2, Year: 1998, Value: 1.103 mg/kg\",\"StationNumber: 98BCB60/2, Year: 1998, Value: 0.999 mg/kg\",\"StationNumber: 98BCB60/4, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98HB003, Year: 1998, Value: 0.036 mg/kg\",\"StationNumber: 98HB006, Year: 1998, Value: 3.089 mg/kg\",\"StationNumber: 98HB014, Year: 1998, Value: 2.09 mg/kg\",\"StationNumber: 98HB016, Year: 1998, Value: 1.995 mg/kg\",\"StationNumber: 98HB017, Year: 1998, Value: 0.072 mg/kg\",\"StationNumber: 98HB024, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB030, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB049, Year: 1998, Value: 2.146 mg/kg\",\"StationNumber: 98HB052, Year: 1998, Value: 0.64 mg/kg\",\"StationNumber: 98HB056, Year: 1998, Value: 1.656 mg/kg\",\"StationNumber: 98HB059, Year: 1998, Value: 0.534 mg/kg\",\"StationNumber: 98HB069, Year: 1998, Value: 0.785 mg/kg\",\"StationNumber: 98HB080, Year: 1998, Value: 3.475 mg/kg\",\"StationNumber: 98HB089, Year: 1998, Value: 0.435 mg/kg\",\"StationNumber: 98HB130, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98HB153, Year: 1998, Value: 0.777 mg/kg\",\"StationNumber: 98HB171, Year: 1998, Value: 0.842 mg/kg\",\"StationNumber: 98HB180, Year: 1998, Value: 1.348 mg/kg\",\"StationNumber: 98HB224, Year: 1998, Value: 1.942 mg/kg\",\"StationNumber: 98HB237, Year: 1998, Value: 0.471 mg/kg\",\"StationNumber: 98HB245, Year: 1998, Value: 0.642 mg/kg\",\"StationNumber: 98HB252, Year: 1998, Value: 1.898 mg/kg\",\"StationNumber: 98HB280, Year: 1998, Value: 0.134 mg/kg\",\"StationNumber: 98HB789, Year: 1998, Value: 2.42 mg/kg\",\"StationNumber: 98HBDIcanal, Year: 1998, Value: 0.931 mg/kg\",\"StationNumber: 98HBspark, Year: 1998, Value: 0.258 mg/kg\",\"StationNumber: 98LTB0014, Year: 1998, Value: 2.93 mg/kg\",\"StationNumber: 98LTB0025, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0049, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0095, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0123, Year: 1998, Value: 0.56 mg/kg\",\"StationNumber: 98LTB0144, Year: 1998, Value: 0.476 mg/kg\",\"StationNumber: 98LTB0151, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0168, Year: 1998, Value: 0.441 mg/kg\",\"StationNumber: 98LTB0183, Year: 1998, Value: 0.828 mg/kg\",\"StationNumber: 98LTB0223, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0244, Year: 1998, Value: 0.078 mg/kg\",\"StationNumber: 98LTB0273, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0307, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0364, Year: 1998, Value: 0.105 mg/kg\",\"StationNumber: 98LTB0393, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98LTB0762, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB1057, Year: 1998, Value: 0.673 mg/kg\",\"StationNumber: 98MR09, Year: 1998, Value: 0.125 mg/kg\",\"StationNumber: 98MR10, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR11, Year: 1998, Value: 0.99 mg/kg\",\"StationNumber: 98MR12, Year: 1998, Value: 0.198 mg/kg\",\"StationNumber: 98MR13, Year: 1998, Value: 1.029 mg/kg\",\"StationNumber: 98MR14, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR15, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR16, Year: 1998, Value: 0.352 mg/kg\",\"StationNumber: 98MR17, Year: 1998, Value: 0.36 mg/kg\",\"StationNumber: 98MR18, Year: 1998, Value: 0.322 mg/kg\",\"StationNumber: 98MR19, Year: 1998, Value: 0.176 mg/kg\",\"StationNumber: 98MR20, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR21, Year: 1998, Value: 2.438 mg/kg\",\"StationNumber: 98MTB0032, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0035, Year: 1998, Value: 0.482 mg/kg\",\"StationNumber: 98MTB0052, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0067, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98MTB0090, Year: 1998, Value: 0.747 mg/kg\",\"StationNumber: 98MTB0103, Year: 1998, Value: 0.073 mg/kg\",\"StationNumber: 98MTB0133, Year: 1998, Value: 0.164 mg/kg\",\"StationNumber: 98MTB0187, Year: 1998, Value: 1.46 mg/kg\",\"StationNumber: 98MTB0191, Year: 1998, Value: 0.192 mg/kg\",\"StationNumber: 98MTB0208, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0270, Year: 1998, Value: 0.016 mg/kg\",\"StationNumber: 98MTB0275, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0283, Year: 1998, Value: 0.376 mg/kg\",\"StationNumber: 98MTB0322, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0331, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0416, Year: 1998, Value: 3.312 mg/kg\",\"StationNumber: 98MTB0460, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0688, Year: 1998, Value: 0.769 mg/kg\",\"StationNumber: 98MTB0694, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB1036, Year: 1998, Value: 0.018 mg/kg\",\"StationNumber: 98OTB0036, Year: 1998, Value: 0.256 mg/kg\",\"StationNumber: 98OTB0039, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0048, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0056, Year: 1998, Value: 0.499 mg/kg\",\"StationNumber: 98OTB0125, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0177, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0185, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0199, Year: 1998, Value: 2.325 mg/kg\",\"StationNumber: 98OTB0232, Year: 1998, Value: 0.301 mg/kg\",\"StationNumber: 98OTB0239, Year: 1998, Value: 1.557 mg/kg\",\"StationNumber: 98OTB0274, Year: 1998, Value: 2.028 mg/kg\",\"StationNumber: 98OTB0425, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0596, Year: 1998, Value: 8.041 mg/kg\",\"StationNumber: 98OTB0721, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98OTB1140, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB1227, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB01, Year: 1998, Value: 1.816 mg/kg\",\"StationNumber: 98TCB02, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB04, Year: 1998, Value: 1.3 mg/kg\",\"StationNumber: 98TCB05, Year: 1998, Value: 0.903 mg/kg\",\"StationNumber: 98TCB06, Year: 1998, Value: 1.118 mg/kg\",\"StationNumber: 98TCB07, Year: 1998, Value: 0.966 mg/kg\",\"StationNumber: 98TCB08, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2025, Year: 1999, Value: 0.194 mg/kg\",\"StationNumber: 99BCB2041, Year: 1999, Value: 0.553 mg/kg\",\"StationNumber: 99BCB2063, Year: 1999, Value: 1.16 mg/kg\",\"StationNumber: 99BCB2069, Year: 1999, Value: 0.715 mg/kg\",\"StationNumber: 99BCB2070, Year: 1999, Value: 0.693 mg/kg\",\"StationNumber: 99BCB2086, Year: 1999, Value: 0.348 mg/kg\",\"StationNumber: 99BCB2094, Year: 1999, Value: 1.893 mg/kg\",\"StationNumber: 99BCB2115, Year: 1999, Value: 1.48 mg/kg\",\"StationNumber: 99BCB2132, Year: 1999, Value: 0.09 mg/kg\",\"StationNumber: 99BCB2295, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2358, Year: 1999, Value: 0.627 mg/kg\",\"StationNumber: 99BCB2423, Year: 1999, Value: 0.758 mg/kg\",\"StationNumber: 99BCB2514, Year: 1999, Value: 0.18 mg/kg\",\"StationNumber: 99BCB2585, Year: 1999, Value: 0.374 mg/kg\",\"StationNumber: 99BCB57/1, Year: 1999, Value: 3.215 mg/kg\",\"StationNumber: 99BCB58/1, Year: 1999, Value: 2.112 mg/kg\",\"StationNumber: 99BCB58/2, Year: 1999, Value: 1.224 mg/kg\",\"StationNumber: 99BCB59/1, Year: 1999, Value: 0.044 mg/kg\",\"StationNumber: 99BCB59/2, Year: 1999, Value: 0.787 mg/kg\",\"StationNumber: 99BCB60/2, Year: 1999, Value: 0.589 mg/kg\",\"StationNumber: 99BCB60/4, Year: 1999, Value: 1.162 mg/kg\",\"StationNumber: 99HB2001, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2012, Year: 1999, Value: 1.721 mg/kg\",\"StationNumber: 99HB2013, Year: 1999, Value: 0.197 mg/kg\",\"StationNumber: 99HB2019, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2040, Year: 1999, Value: 0.331 mg/kg\",\"StationNumber: 99HB2041, Year: 1999, Value: 0.988 mg/kg\",\"StationNumber: 99HB2043, Year: 1999, Value: 0.235 mg/kg\",\"StationNumber: 99HB2044, Year: 1999, Value: 0.82 mg/kg\",\"StationNumber: 99HB2051, Year: 1999, Value: 0.847 mg/kg\",\"StationNumber: 99HB2055, Year: 1999, Value: 1.08 mg/kg\",\"StationNumber: 99HB2058, Year: 1999, Value: 3.832 mg/kg\",\"StationNumber: 99HB2061, Year: 1999, Value: 5.185 mg/kg\",\"StationNumber: 99HB2085, Year: 1999, Value: 3.395 mg/kg\",\"StationNumber: 99HB2094, Year: 1999, Value: 0.205 mg/kg\",\"StationNumber: 99HB2124, Year: 1999, Value: 2.804 mg/kg\",\"StationNumber: 99HB2157, Year: 1999, Value: 0.252 mg/kg\",\"StationNumber: 99HB2176, Year: 1999, Value: 0.468 mg/kg\",\"StationNumber: 99HB2207, Year: 1999, Value: 2.127 mg/kg\",\"StationNumber: 99HB2214, Year: 1999, Value: 0.649 mg/kg\",\"StationNumber: 99HB2233, Year: 1999, Value: 2.896 mg/kg\",\"StationNumber: 99HB2393, Year: 1999, Value: 1.265 mg/kg\",\"StationNumber: 99HB2445, Year: 1999, Value: 1.072 mg/kg\",\"StationNumber: 99HB2757, Year: 1999, Value: 1.051 mg/kg\",\"StationNumber: 99LTB2014, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99LTB2021, Year: 1999, Value: 11.552 mg/kg\",\"StationNumber: 99LTB2041, Year: 1999, Value: 4.997 mg/kg\",\"StationNumber: 99LTB2071, Year: 1999, Value: 5.805 mg/kg\",\"StationNumber: 99LTB2112, Year: 1999, Value: 3.993 mg/kg\",\"StationNumber: 99LTB2124, Year: 1999, Value: 0.035 mg/kg\",\"StationNumber: 99LTB2203, Year: 1999, Value: 0.664 mg/kg\",\"StationNumber: 99LTB2214, Year: 1999, Value: 0.098 mg/kg\",\"StationNumber: 99LTB2247, Year: 1999, Value: 0.297 mg/kg\",\"StationNumber: 99LTB2267, Year: 1999, Value: 1.444 mg/kg\",\"StationNumber: 99LTB2277, Year: 1999, Value: 0.692 mg/kg\",\"StationNumber: 99LTB2290, Year: 1999, Value: 1.374 mg/kg\",\"StationNumber: 99LTB2327, Year: 1999, Value: 0.362 mg/kg\",\"StationNumber: 99LTB2546, Year: 1999, Value: 0.994 mg/kg\",\"StationNumber: 99LTB2617, Year: 1999, Value: 3.167 mg/kg\",\"StationNumber: 99LTB3020, Year: 1999, Value: 0.368 mg/kg\",\"StationNumber: 99MR09, Year: 1999, Value: 0.375 mg/kg\",\"StationNumber: 99MR10, Year: 1999, Value: 0.445 mg/kg\",\"StationNumber: 99MR11, Year: 1999, Value: 1.258 mg/kg\",\"StationNumber: 99MR12, Year: 1999, Value: 0.538 mg/kg\",\"StationNumber: 99MR13, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MR14, Year: 1999, Value: 0.402 mg/kg\",\"StationNumber: 99MR15, Year: 1999, Value: 0.668 mg/kg\",\"StationNumber: 99MR16, Year: 1999, Value: 0.087 mg/kg\",\"StationNumber: 99MR17, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR18, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR19, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR20, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR21, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2029, Year: 1999, Value: 1.088 mg/kg\",\"StationNumber: 99MTB2059, Year: 1999, Value: 0.528 mg/kg\",\"StationNumber: 99MTB2060, Year: 1999, Value: 0.709 mg/kg\",\"StationNumber: 99MTB2108, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MTB2109, Year: 1999, Value: 0.25 mg/kg\",\"StationNumber: 99MTB2116, Year: 1999, Value: 0.479 mg/kg\",\"StationNumber: 99MTB2129, Year: 1999, Value: 1.833 mg/kg\",\"StationNumber: 99MTB2149, Year: 1999, Value: 0.968 mg/kg\",\"StationNumber: 99MTB2165, Year: 1999, Value: 0.712 mg/kg\",\"StationNumber: 99MTB2240, Year: 1999, Value: 0.188 mg/kg\",\"StationNumber: 99MTB2243, Year: 1999, Value: 1.994 mg/kg\",\"StationNumber: 99MTB2244, Year: 1999, Value: 2.396 mg/kg\",\"StationNumber: 99MTB2253, Year: 1999, Value: 1.24 mg/kg\",\"StationNumber: 99MTB2268, Year: 1999, Value: 1.218 mg/kg\",\"StationNumber: 99MTB2274, Year: 1999, Value: 2.485 mg/kg\",\"StationNumber: 99MTB2291, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2358, Year: 1999, Value: 0.699 mg/kg\",\"StationNumber: 99MTB2385, Year: 1999, Value: 0.269 mg/kg\",\"StationNumber: 99MTB2554, Year: 1999, Value: 0.524 mg/kg\",\"StationNumber: 99MTB2598, Year: 1999, Value: 1.573 mg/kg\",\"StationNumber: 99MTB2642, Year: 1999, Value: 0.016 mg/kg\",\"StationNumber: 99OTB2002, Year: 1999, Value: 0.452 mg/kg\",\"StationNumber: 99OTB2005, Year: 1999, Value: 0.022 mg/kg\",\"StationNumber: 99OTB2009, Year: 1999, Value: 0.41 mg/kg\",\"StationNumber: 99OTB2010, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2022, Year: 1999, Value: 0.836 mg/kg\",\"StationNumber: 99OTB2045, Year: 1999, Value: 0.166 mg/kg\",\"StationNumber: 99OTB2067, Year: 1999, Value: 0.055 mg/kg\",\"StationNumber: 99OTB2111, Year: 1999, Value: 0.071 mg/kg\",\"StationNumber: 99OTB2121, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2225, Year: 1999, Value: 0.203 mg/kg\",\"StationNumber: 99OTB2296, Year: 1999, Value: 0.839 mg/kg\",\"StationNumber: 99OTB2313, Year: 1999, Value: 0.875 mg/kg\",\"StationNumber: 99OTB2316, Year: 1999, Value: 1.126 mg/kg\",\"StationNumber: 99OTB2331, Year: 1999, Value: 0.353 mg/kg\",\"StationNumber: 99OTB2395, Year: 1999, Value: 0.233 mg/kg\",\"StationNumber: 99OTB2482, Year: 1999, Value: 1.236 mg/kg\",\"StationNumber: 99OTB2908, Year: 1999, Value: 0.307 mg/kg\",\"StationNumber: 99OTB2994, Year: 1999, Value: 0.038 mg/kg\",\"StationNumber: 99OTB3046, Year: 1999, Value: 0.397 mg/kg\",\"StationNumber: 99TCB01, Year: 1999, Value: 1.95 mg/kg\",\"StationNumber: 99TCB02, Year: 1999, Value: 0.225 mg/kg\",\"StationNumber: 99TCB03, Year: 1999, Value: 4.578 mg/kg\",\"StationNumber: 99TCB04, Year: 1999, Value: 2.024 mg/kg\",\"StationNumber: 99TCB05, Year: 1999, Value: 1.134 mg/kg\",\"StationNumber: 99TCB06, Year: 1999, Value: 1.082 mg/kg\",\"StationNumber: 99TCB07, Year: 1999, Value: 1.652 mg/kg\",\"StationNumber: 99TCB08, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 00BCB4000, Year: 2000, Value: 7.05 mg/kg\",\"StationNumber: 00BCB4001, Year: 2000, Value: 8.917 mg/kg\",\"StationNumber: 00BCB4004, Year: 2000, Value: 5.717 mg/kg\",\"StationNumber: 00BCB4033, Year: 2000, Value: 6.44 mg/kg\",\"StationNumber: 00BCB4034, Year: 2000, Value: 6.595 mg/kg\",\"StationNumber: 00BCB4037, Year: 2000, Value: 5.573 mg/kg\",\"StationNumber: 00BCB4038, Year: 2000, Value: 7.398 mg/kg\",\"StationNumber: 00BCB4041, Year: 2000, Value: 8.081 mg/kg\",\"StationNumber: 00BCB4042, Year: 2000, Value: 8.315 mg/kg\",\"StationNumber: 00BCB4046, Year: 2000, Value: 7.3 mg/kg\",\"StationNumber: 00BCB4079, Year: 2000, Value: 5.898 mg/kg\",\"StationNumber: 00BCB4084, Year: 2000, Value: 6.968 mg/kg\",\"StationNumber: 00BCB4090, Year: 2000, Value: 8.108 mg/kg\",\"StationNumber: 00BCB4100, Year: 2000, Value: 7.966 mg/kg\",\"StationNumber: 00BCB4124, Year: 2000, Value: 5.814 mg/kg\",\"StationNumber: 00BCB4165, Year: 2000, Value: 5.405 mg/kg\",\"StationNumber: 00BCB4174, Year: 2000, Value: 8.747 mg/kg\",\"StationNumber: 00BCB4207, Year: 2000, Value: 7.704 mg/kg\",\"StationNumber: 00BCB4268, Year: 2000, Value: 7.855 mg/kg\",\"StationNumber: 00BCB4299, Year: 2000, Value: 8.06 mg/kg\",\"StationNumber: 00BCB4312, Year: 2000, Value: 8.316 mg/kg\",\"StationNumber: 00BCB58/1, Year: 2000, Value: 5.498 mg/kg\",\"StationNumber: 00BCB58/2, Year: 2000, Value: 4.644 mg/kg\",\"StationNumber: 00BCB59/1, Year: 2000, Value: 6.148 mg/kg\",\"StationNumber: 00BCB59/2, Year: 2000, Value: 5.036 mg/kg\",\"StationNumber: 00BCB60/2, Year: 2000, Value: 5.003 mg/kg\",\"StationNumber: 00BCB60/4, Year: 2000, Value: 4.842 mg/kg\",\"StationNumber: 00HB4002, Year: 2000, Value: 5.886 mg/kg\",\"StationNumber: 00HB4006, Year: 2000, Value: 6.219 mg/kg\",\"StationNumber: 00HB4019, Year: 2000, Value: 3.684 mg/kg\",\"StationNumber: 00HB4023, Year: 2000, Value: 5.729 mg/kg\",\"StationNumber: 00HB4032, Year: 2000, Value: 5.767 mg/kg\",\"StationNumber: 00HB4033, Year: 2000, Value: 4.768 mg/kg\",\"StationNumber: 00HB4038, Year: 2000, Value: 6.182 mg/kg\",\"StationNumber: 00HB4047, Year: 2000, Value: 5.84 mg/kg\",\"StationNumber: 00HB4058, Year: 2000, Value: 3.097 mg/kg\",\"StationNumber: 00HB4077, Year: 2000, Value: 6.608 mg/kg\",\"StationNumber: 00HB4082, Year: 2000, Value: 6.717 mg/kg\",\"StationNumber: 00HB4083, Year: 2000, Value: 7.399 mg/kg\",\"StationNumber: 00HB4093, Year: 2000, Value: 1.936 mg/kg\",\"StationNumber: 00HB4094, Year: 2000, Value: 2.189 mg/kg\",\"StationNumber: 00HB4100, Year: 2000, Value: 4.324 mg/kg\",\"StationNumber: 00HB4106, Year: 2000, Value: 2.128 mg/kg\",\"StationNumber: 00HB4144, Year: 2000, Value: 1.909 mg/kg\",\"StationNumber: 00HB4152, Year: 2000, Value: 7.008 mg/kg\",\"StationNumber: 00HB4267, Year: 2000, Value: 4.486 mg/kg\",\"StationNumber: 00HB4291, Year: 2000, Value: 4.846 mg/kg\",\"StationNumber: 00HB4316, Year: 2000, Value: 6.769 mg/kg\",\"StationNumber: 00HB4505, Year: 2000, Value: 4.805 mg/kg\",\"StationNumber: 00LTB4039, Year: 2000, Value: 2.434 mg/kg\",\"StationNumber: 00LTB4051, Year: 2000, Value: 4.039 mg/kg\",\"StationNumber: 00LTB4066, Year: 2000, Value: 1.702 mg/kg\",\"StationNumber: 00LTB4117, Year: 2000, Value: 3.904 mg/kg\",\"StationNumber: 00LTB4151, Year: 2000, Value: 5.587 mg/kg\",\"StationNumber: 00LTB4185, Year: 2000, Value: 3.635 mg/kg\",\"StationNumber: 00LTB4286, Year: 2000, Value: 5.878 mg/kg\",\"StationNumber: 00LTB4340, Year: 2000, Value: 2.792 mg/kg\",\"StationNumber: 00LTB4484, Year: 2000, Value: 2.7 mg/kg\",\"StationNumber: 00LTB4487, Year: 2000, Value: 1.721 mg/kg\",\"StationNumber: 00LTB4513, Year: 2000, Value: 1.915 mg/kg\",\"StationNumber: 00LTB4529, Year: 2000, Value: 5.51 mg/kg\",\"StationNumber: 00LTB4536, Year: 2000, Value: 6.17 mg/kg\",\"StationNumber: 00LTB4637, Year: 2000, Value: 9.27 mg/kg\",\"StationNumber: 00LTB4677, Year: 2000, Value: 1.76 mg/kg\",\"StationNumber: 00LTB4730, Year: 2000, Value: 9.63 mg/kg\",\"StationNumber: 00LTB4749, Year: 2000, Value: 1.727 mg/kg\",\"StationNumber: 00MR09, Year: 2000, Value: 7.262 mg/kg\",\"StationNumber: 00MR10, Year: 2000, Value: 7.28 mg/kg\",\"StationNumber: 00MR11, Year: 2000, Value: 7.022 mg/kg\",\"StationNumber: 00MR12, Year: 2000, Value: 6.682 mg/kg\",\"StationNumber: 00MR13, Year: 2000, Value: 6.746 mg/kg\",\"StationNumber: 00MR14, Year: 2000, Value: 5.791 mg/kg\",\"StationNumber: 00MR15, Year: 2000, Value: 5.559 mg/kg\",\"StationNumber: 00MR16, Year: 2000, Value: 4.961 mg/kg\",\"StationNumber: 00MR17, Year: 2000, Value: 5.02 mg/kg\",\"StationNumber: 00MR18, Year: 2000, Value: 5.104 mg/kg\",\"StationNumber: 00MR19, Year: 2000, Value: 7.434 mg/kg\",\"StationNumber: 00MR20, Year: 2000, Value: 2.837 mg/kg\",\"StationNumber: 00MR21, Year: 2000, Value: 4.022 mg/kg\",\"StationNumber: 00MTB4030, Year: 2000, Value: 4.501 mg/kg\",\"StationNumber: 00MTB4032, Year: 2000, Value: 8.919 mg/kg\",\"StationNumber: 00MTB4041, Year: 2000, Value: 2.068 mg/kg\",\"StationNumber: 00MTB4061, Year: 2000, Value: 2.284 mg/kg\",\"StationNumber: 00MTB4072, Year: 2000, Value: 1.826 mg/kg\",\"StationNumber: 00MTB4086, Year: 2000, Value: 1.935 mg/kg\",\"StationNumber: 00MTB4090, Year: 2000, Value: 9.376 mg/kg\",\"StationNumber: 00MTB4098, Year: 2000, Value: 19.11 mg/kg\",\"StationNumber: 00MTB4100, Year: 2000, Value: 5.523 mg/kg\",\"StationNumber: 00MTB4106, Year: 2000, Value: 2.373 mg/kg\",\"StationNumber: 00MTB4159, Year: 2000, Value: 2.926 mg/kg\",\"StationNumber: 00MTB4181, Year: 2000, Value: 5.332 mg/kg\",\"StationNumber: 00MTB4193, Year: 2000, Value: 2.564 mg/kg\",\"StationNumber: 00MTB4201, Year: 2000, Value: 5.145 mg/kg\",\"StationNumber: 00MTB4249, Year: 2000, Value: 5.123 mg/kg\",\"StationNumber: 00MTB4265, Year: 2000, Value: 18.11 mg/kg\",\"StationNumber: 00MTB4310, Year: 2000, Value: 4.749 mg/kg\",\"StationNumber: 00MTB4363, Year: 2000, Value: 5.988 mg/kg\",\"StationNumber: 00MTB4504, Year: 2000, Value: 1.819 mg/kg\",\"StationNumber: 00MTB4584, Year: 2000, Value: 4.649 mg/kg\",\"StationNumber: 00MTB4653, Year: 2000, Value: 6.862 mg/kg\",\"StationNumber: 00MTB4845, Year: 2000, Value: 6.98 mg/kg\",\"StationNumber: 00MTB5125, Year: 2000, Value: 6.297 mg/kg\",\"StationNumber: 00OTB4011, Year: 2000, Value: 6.398 mg/kg\",\"StationNumber: 00OTB4019, Year: 2000, Value: 5.242 mg/kg\",\"StationNumber: 00OTB4037, Year: 2000, Value: 5.554 mg/kg\",\"StationNumber: 00OTB4040, Year: 2000, Value: 6.998 mg/kg\",\"StationNumber: 00OTB4044, Year: 2000, Value: 6.455 mg/kg\",\"StationNumber: 00OTB4096, Year: 2000, Value: 6.509 mg/kg\",\"StationNumber: 00OTB4105, Year: 2000, Value: 4.904 mg/kg\",\"StationNumber: 00OTB4123, Year: 2000, Value: 6.756 mg/kg\",\"StationNumber: 00OTB4132, Year: 2000, Value: 4.869 mg/kg\",\"StationNumber: 00OTB4138, Year: 2000, Value: 5.793 mg/kg\",\"StationNumber: 00OTB4149, Year: 2000, Value: 6.974 mg/kg\",\"StationNumber: 00OTB4192, Year: 2000, Value: 4.798 mg/kg\",\"StationNumber: 00OTB4217, Year: 2000, Value: 6.639 mg/kg\",\"StationNumber: 00OTB4254, Year: 2000, Value: 8.763 mg/kg\",\"StationNumber: 00OTB4278, Year: 2000, Value: 2.048 mg/kg\",\"StationNumber: 00OTB4402, Year: 2000, Value: 7.662 mg/kg\",\"StationNumber: 00OTB4407, Year: 2000, Value: 8.601 mg/kg\",\"StationNumber: 00OTB4650, Year: 2000, Value: 8.558 mg/kg\",\"StationNumber: 00OTB4946, Year: 2000, Value: 7.083 mg/kg\",\"StationNumber: 00TCB01, Year: 2000, Value: 5.933 mg/kg\",\"StationNumber: 00TCB02, Year: 2000, Value: 3.519 mg/kg\",\"StationNumber: 00TCB03, Year: 2000, Value: 9.862 mg/kg\",\"StationNumber: 00TCB04, Year: 2000, Value: 4.401 mg/kg\",\"StationNumber: 00TCB05, Year: 2000, Value: 6.928 mg/kg\",\"StationNumber: 00TCB06, Year: 2000, Value: 6.186 mg/kg\",\"StationNumber: 00TCB07, Year: 2000, Value: 6.023 mg/kg\",\"StationNumber: 00TCB08, Year: 2000, Value: 5.912 mg/kg\",\"StationNumber: 01BCB57/1, Year: 2001, Value: 2.985 mg/kg\",\"StationNumber: 01BCB58/1, Year: 2001, Value: 4.108 mg/kg\",\"StationNumber: 01BCB58/2, Year: 2001, Value: 4.081 mg/kg\",\"StationNumber: 01BCB59/1, Year: 2001, Value: 2.709 mg/kg\",\"StationNumber: 01BCB59/2, Year: 2001, Value: 2.059 mg/kg\",\"StationNumber: 01BCB60/2, Year: 2001, Value: 3.449 mg/kg\",\"StationNumber: 01BCB60/4, Year: 2001, Value: 0.432 mg/kg\",\"StationNumber: 01BCB6001, Year: 2001, Value: 4.072 mg/kg\",\"StationNumber: 01BCB6009, Year: 2001, Value: 3.178 mg/kg\",\"StationNumber: 01BCB6018, Year: 2001, Value: 2.845 mg/kg\",\"StationNumber: 01BCB6019, Year: 2001, Value: 3.296 mg/kg\",\"StationNumber: 01BCB6031, Year: 2001, Value: 3.409 mg/kg\",\"StationNumber: 01BCB6063, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01BCB6072, Year: 2001, Value: 3.246 mg/kg\",\"StationNumber: 01BCB6089, Year: 2001, Value: 2.207 mg/kg\",\"StationNumber: 01BCB6109, Year: 2001, Value: 2.415 mg/kg\",\"StationNumber: 01BCB6114, Year: 2001, Value: 2.628 mg/kg\",\"StationNumber: 01BCB6152, Year: 2001, Value: 2.854 mg/kg\",\"StationNumber: 01BCB6178, Year: 2001, Value: 2.596 mg/kg\",\"StationNumber: 01BCB6190, Year: 2001, Value: 2.145 mg/kg\",\"StationNumber: 01BCB6230, Year: 2001, Value: 3.755 mg/kg\",\"StationNumber: 01BCB6263, Year: 2001, Value: 1.707 mg/kg\",\"StationNumber: 01BCB6359, Year: 2001, Value: 1.433 mg/kg\",\"StationNumber: 01HB6019, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6022, Year: 2001, Value: 1.909 mg/kg\",\"StationNumber: 01HB6032, Year: 2001, Value: 2.588 mg/kg\",\"StationNumber: 01HB6035, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6045, Year: 2001, Value: 0.325 mg/kg\",\"StationNumber: 01HB6064, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6066, Year: 2001, Value: 1.155 mg/kg\",\"StationNumber: 01HB6087, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6093, Year: 2001, Value: 2.265 mg/kg\",\"StationNumber: 01HB6102, Year: 2001, Value: 2.313 mg/kg\",\"StationNumber: 01HB6108, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6131, Year: 2001, Value: 0.71 mg/kg\",\"StationNumber: 01HB6140, Year: 2001, Value: 2.982 mg/kg\",\"StationNumber: 01HB6145, Year: 2001, Value: 2.677 mg/kg\",\"StationNumber: 01HB6159, Year: 2001, Value: 2.869 mg/kg\",\"StationNumber: 01HB6186, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6187, Year: 2001, Value: 3.434 mg/kg\",\"StationNumber: 01HB6249, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6261, Year: 2001, Value: 3.626 mg/kg\",\"StationNumber: 01HB6264, Year: 2001, Value: 1.742 mg/kg\",\"StationNumber: 01HB6283, Year: 2001, Value: 1.357 mg/kg\",\"StationNumber: 01HB6305, Year: 2001, Value: 2.006 mg/kg\",\"StationNumber: 01HB6374, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6453, Year: 2001, Value: 2.977 mg/kg\",\"StationNumber: 01HB6537, Year: 2001, Value: 3.517 mg/kg\",\"StationNumber: 01LTB6026, Year: 2001, Value: 14.165 mg/kg\",\"StationNumber: 01LTB6027, Year: 2001, Value: 1.328 mg/kg\",\"StationNumber: 01LTB6050, Year: 2001, Value: 0.606 mg/kg\",\"StationNumber: 01LTB6104, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6120, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6122, Year: 2001, Value: 0.66 mg/kg\",\"StationNumber: 01LTB6158, Year: 2001, Value: 5.092 mg/kg\",\"StationNumber: 01LTB6302, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6346, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01LTB6380, Year: 2001, Value: 0.874 mg/kg\",\"StationNumber: 01LTB6595, Year: 2001, Value: 3.852 mg/kg\",\"StationNumber: 01LTB6869, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MR09, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR12, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR13, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR14, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR17, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR18, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR19, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR20, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR21, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MTB6002, Year: 2001, Value: 0.981 mg/kg\",\"StationNumber: 01MTB6011, Year: 2001, Value: 0.416 mg/kg\",\"StationNumber: 01MTB6014, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MTB6049, Year: 2001, Value: 0.168 mg/kg\",\"StationNumber: 01MTB6059, Year: 2001, Value: 5.14 mg/kg\",\"StationNumber: 01MTB6064, Year: 2001, Value: 3.241 mg/kg\",\"StationNumber: 01MTB6068, Year: 2001, Value: 5.837 mg/kg\",\"StationNumber: 01MTB6080, Year: 2001, Value: 3.556 mg/kg\",\"StationNumber: 01MTB6133, Year: 2001, Value: 2.453 mg/kg\",\"StationNumber: 01MTB6154, Year: 2001, Value: 0.963 mg/kg\",\"StationNumber: 01MTB6188, Year: 2001, Value: 0.797 mg/kg\",\"StationNumber: 01MTB6189, Year: 2001, Value: 2.868 mg/kg\",\"StationNumber: 01MTB6196, Year: 2001, Value: 2.703 mg/kg\",\"StationNumber: 01MTB6229, Year: 2001, Value: 2.698 mg/kg\",\"StationNumber: 01MTB6257, Year: 2001, Value: 0.988 mg/kg\",\"StationNumber: 01MTB6265, Year: 2001, Value: 4.324 mg/kg\",\"StationNumber: 01MTB6290, Year: 2001, Value: 3.339 mg/kg\",\"StationNumber: 01MTB6325, Year: 2001, Value: 2.765 mg/kg\",\"StationNumber: 01MTB6327, Year: 2001, Value: 4.862 mg/kg\",\"StationNumber: 01MTB6328, Year: 2001, Value: 3.179 mg/kg\",\"StationNumber: 01MTB6464, Year: 2001, Value: 3.707 mg/kg\",\"StationNumber: 01MTB6495, Year: 2001, Value: 3.297 mg/kg\",\"StationNumber: 01MTB6527, Year: 2001, Value: 3.538 mg/kg\",\"StationNumber: 01MTB6638, Year: 2001, Value: 4.338 mg/kg\",\"StationNumber: 01MTB6699, Year: 2001, Value: 4.171 mg/kg\",\"StationNumber: 01MTB7153, Year: 2001, Value: 3.938 mg/kg\",\"StationNumber: 01OTB6010, Year: 2001, Value: 3.892 mg/kg\",\"StationNumber: 01OTB6017, Year: 2001, Value: 3.183 mg/kg\",\"StationNumber: 01OTB6021, Year: 2001, Value: 2.793 mg/kg\",\"StationNumber: 01OTB6022, Year: 2001, Value: 1.206 mg/kg\",\"StationNumber: 01OTB6025, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6028, Year: 2001, Value: 5.384 mg/kg\",\"StationNumber: 01OTB6078, Year: 2001, Value: 3.845 mg/kg\",\"StationNumber: 01OTB6103, Year: 2001, Value: 5.634 mg/kg\",\"StationNumber: 01OTB6135, Year: 2001, Value: 2.772 mg/kg\",\"StationNumber: 01OTB6152, Year: 2001, Value: 28.868 mg/kg\",\"StationNumber: 01OTB6178, Year: 2001, Value: 9.713 mg/kg\",\"StationNumber: 01OTB6186, Year: 2001, Value: 5.55 mg/kg\",\"StationNumber: 01OTB6234, Year: 2001, Value: 5.199 mg/kg\",\"StationNumber: 01OTB6239, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6441, Year: 2001, Value: 5.652 mg/kg\",\"StationNumber: 01OTB6784, Year: 2001, Value: 10.207 mg/kg\",\"StationNumber: 01OTB6830, Year: 2001, Value: 5.184 mg/kg\",\"StationNumber: 01SAFHAB, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01TCB02, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB03, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB04, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB06, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB07, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 02BCB05, Year: 2002, Value: 5.202 mg/kg\",\"StationNumber: 02BCB20, Year: 2002, Value: 1.257 mg/kg\",\"StationNumber: 02BCB32, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB52, Year: 2002, Value: 0.407 mg/kg\",\"StationNumber: 02BCB62, Year: 2002, Value: 3.401 mg/kg\",\"StationNumber: 02BCB69, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB74, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB83, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB90, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-1, Year: 2002, Value: 0.426 mg/kg\",\"StationNumber: 02DH07-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH09-1, Year: 2002, Value: 2.957 mg/kg\",\"StationNumber: 02DH09-2, Year: 2002, Value: 1.154 mg/kg\",\"StationNumber: 02DH09-3, Year: 2002, Value: 3.812 mg/kg\",\"StationNumber: 02DH11A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH14-1, Year: 2002, Value: 1.74 mg/kg\",\"StationNumber: 02DH14-3, Year: 2002, Value: 1.197 mg/kg\",\"StationNumber: 02DH14-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-3, Year: 2002, Value: 0.146 mg/kg\",\"StationNumber: 02DH20-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-3, Year: 2002, Value: 0.323 mg/kg\",\"StationNumber: 02DH21B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB20, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB21, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB39, Year: 2002, Value: 0.328 mg/kg\",\"StationNumber: 02HB42, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB51, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB55, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB01, Year: 2002, Value: 3.105 mg/kg\",\"StationNumber: 02LTB02, Year: 2002, Value: 4.432 mg/kg\",\"StationNumber: 02LTB03, Year: 2002, Value: 0.925 mg/kg\",\"StationNumber: 02LTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB06, Year: 2002, Value: 0.657 mg/kg\",\"StationNumber: 02LTB07, Year: 2002, Value: 0.376 mg/kg\",\"StationNumber: 02LTB08, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR06, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR08, Year: 2002, Value: 0.022 mg/kg\",\"StationNumber: 02MR10, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR11, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB11, Year: 2002, Value: 0.563 mg/kg\",\"StationNumber: 02MTB12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB18, Year: 2002, Value: 1.634 mg/kg\",\"StationNumber: 02MTB19, Year: 2002, Value: 6.859 mg/kg\",\"StationNumber: 02MTB21, Year: 2002, Value: 0.379 mg/kg\",\"StationNumber: 02MTB23, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB29, Year: 2002, Value: 4.363 mg/kg\",\"StationNumber: 02MTB32, Year: 2002, Value: 0.595 mg/kg\",\"StationNumber: 02MTB34, Year: 2002, Value: 0.126 mg/kg\",\"StationNumber: 02OTB02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB52, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB60, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB66, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB03, Year: 2002, Value: 1.409 mg/kg\",\"StationNumber: 02TCB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB07, Year: 2002, Value: 3.347 mg/kg\",\"StationNumber: 02TCB09, Year: 2002, Value: 0.612 mg/kg\",\"StationNumber: 03BCB107, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB120, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB126, Year: 2003, Value: 0.086 mg/kg\",\"StationNumber: 03BCB190, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB230, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB242, Year: 2003, Value: 2.439 mg/kg\",\"StationNumber: 03BCB278, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB287, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB338, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB439, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB02, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB09, Year: 2003, Value: 5.878 mg/kg\",\"StationNumber: 03HB10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB12, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB14, Year: 2003, Value: 0.176 mg/kg\",\"StationNumber: 03HB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB18, Year: 2003, Value: 1.028 mg/kg\",\"StationNumber: 03HB21, Year: 2003, Value: 3.834 mg/kg\",\"StationNumber: 03HB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB37, Year: 2003, Value: 0.988 mg/kg\",\"StationNumber: 03HB38, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB41, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB42, Year: 2003, Value: 1.908 mg/kg\",\"StationNumber: 03HB44, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB47, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB50, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB51, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB52, Year: 2003, Value: 3.438 mg/kg\",\"StationNumber: 03HB53, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB02, Year: 2003, Value: 7.824 mg/kg\",\"StationNumber: 03LTB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB05, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB08, Year: 2003, Value: 1.746 mg/kg\",\"StationNumber: 03LTB09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB10, Year: 2003, Value: 3.726 mg/kg\",\"StationNumber: 03LTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB12, Year: 2003, Value: 5.634 mg/kg\",\"StationNumber: 03MR02, Year: 2003, Value: 0.283 mg/kg\",\"StationNumber: 03MR04, Year: 2003, Value: 0.17 mg/kg\",\"StationNumber: 03MR06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR08, Year: 2003, Value: 0.608 mg/kg\",\"StationNumber: 03MR09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB03, Year: 2003, Value: 1.161 mg/kg\",\"StationNumber: 03MTB08, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB10, Year: 2003, Value: 1.265 mg/kg\",\"StationNumber: 03MTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB13, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB14, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB15, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB17, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB18, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB19, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB21, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB24, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB25, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB31, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB35, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB157, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB200, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB413, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB414, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB507, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB623, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB706, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB794, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB929, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB05, Year: 2003, Value: 3.05 mg/kg\",\"StationNumber: 04BCB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB03, Year: 2004, Value: 2.501 mg/kg\",\"StationNumber: 04BCB04, Year: 2004, Value: 0.51 mg/kg\",\"StationNumber: 04BCB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB06, Year: 2004, Value: 0.839 mg/kg\",\"StationNumber: 04BCB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB10, Year: 2004, Value: 2.332 mg/kg\",\"StationNumber: 04HB01, Year: 2004, Value: 0.523 mg/kg\",\"StationNumber: 04HB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB03, Year: 2004, Value: 0.552 mg/kg\",\"StationNumber: 04HB04, Year: 2004, Value: 1.214 mg/kg\",\"StationNumber: 04HB05, Year: 2004, Value: 0.346 mg/kg\",\"StationNumber: 04HB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB07, Year: 2004, Value: 1.338 mg/kg\",\"StationNumber: 04HB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB10, Year: 2004, Value: 2.967 mg/kg\",\"StationNumber: 04HB11, Year: 2004, Value: 0.026 mg/kg\",\"StationNumber: 04HB12, Year: 2004, Value: 0.348 mg/kg\",\"StationNumber: 04HB13, Year: 2004, Value: 0.431 mg/kg\",\"StationNumber: 04HB14, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB15, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB16, Year: 2004, Value: 0.477 mg/kg\",\"StationNumber: 04HB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB18, Year: 2004, Value: 2.08 mg/kg\",\"StationNumber: 04HB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB20, Year: 2004, Value: 0.117 mg/kg\",\"StationNumber: 04HB21, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB23, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB24, Year: 2004, Value: 0.37 mg/kg\",\"StationNumber: 04HB25, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB26, Year: 2004, Value: 0.004 mg/kg\",\"StationNumber: 04LTB01, Year: 2004, Value: 3.535 mg/kg\",\"StationNumber: 04LTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB03, Year: 2004, Value: 0.715 mg/kg\",\"StationNumber: 04LTB04, Year: 2004, Value: 2.723 mg/kg\",\"StationNumber: 04LTB05, Year: 2004, Value: 0.562 mg/kg\",\"StationNumber: 04LTB06, Year: 2004, Value: 3.492 mg/kg\",\"StationNumber: 04LTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB08, Year: 2004, Value: 4.848 mg/kg\",\"StationNumber: 04LTB09, Year: 2004, Value: 0.25 mg/kg\",\"StationNumber: 04LTB10, Year: 2004, Value: 1.579 mg/kg\",\"StationNumber: 04LTB11, Year: 2004, Value: 1.156 mg/kg\",\"StationNumber: 04MR01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR10, Year: 2004, Value: 0.32 mg/kg\",\"StationNumber: 04MR11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB01, Year: 2004, Value: 2.748 mg/kg\",\"StationNumber: 04MTB02, Year: 2004, Value: 2.306 mg/kg\",\"StationNumber: 04MTB04, Year: 2004, Value: 0.557 mg/kg\",\"StationNumber: 04MTB05, Year: 2004, Value: 1.049 mg/kg\",\"StationNumber: 04MTB06, Year: 2004, Value: 1.363 mg/kg\",\"StationNumber: 04MTB07, Year: 2004, Value: 0.169 mg/kg\",\"StationNumber: 04MTB08, Year: 2004, Value: 0.219 mg/kg\",\"StationNumber: 04MTB09, Year: 2004, Value: 1.226 mg/kg\",\"StationNumber: 04MTB10, Year: 2004, Value: 1.518 mg/kg\",\"StationNumber: 04MTB11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB12, Year: 2004, Value: 1.075 mg/kg\",\"StationNumber: 04MTB13, Year: 2004, Value: 0.444 mg/kg\",\"StationNumber: 04MTB14, Year: 2004, Value: 0.936 mg/kg\",\"StationNumber: 04MTB15, Year: 2004, Value: 0.83 mg/kg\",\"StationNumber: 04MTB16, Year: 2004, Value: 1.378 mg/kg\",\"StationNumber: 04MTB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB18, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB20, Year: 2004, Value: 0.469 mg/kg\",\"StationNumber: 04MTB21, Year: 2004, Value: 16.571 mg/kg\",\"StationNumber: 04MTB22, Year: 2004, Value: 0.19 mg/kg\",\"StationNumber: 04MTB24, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04TCB07, Year: 2004, Value: 1.789 mg/kg\",\"StationNumber: 05BCB01, Year: 2005, Value: 0.505 mg/kg\",\"StationNumber: 05BCB02, Year: 2005, Value: 0.245 mg/kg\",\"StationNumber: 05BCB03, Year: 2005, Value: 0.638 mg/kg\",\"StationNumber: 05BCB04, Year: 2005, Value: 0.791 mg/kg\",\"StationNumber: 05BCB05, Year: 2005, Value: 6.022 mg/kg\",\"StationNumber: 05BCB06, Year: 2005, Value: 2.432 mg/kg\",\"StationNumber: 05BCB07, Year: 2005, Value: 0.357 mg/kg\",\"StationNumber: 05BCB08, Year: 2005, Value: 1.489 mg/kg\",\"StationNumber: 05BCB09, Year: 2005, Value: 0.987 mg/kg\",\"StationNumber: 05BCB10, Year: 2005, Value: 0.021 mg/kg\",\"StationNumber: 05HB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB06, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB07, Year: 2005, Value: 0.733 mg/kg\",\"StationNumber: 05HB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB10, Year: 2005, Value: 0.598 mg/kg\",\"StationNumber: 05HB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB12, Year: 2005, Value: 3.811 mg/kg\",\"StationNumber: 05HB13, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB14, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB16, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB17, Year: 2005, Value: 0.036 mg/kg\",\"StationNumber: 05HB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB19, Year: 2005, Value: 0.322 mg/kg\",\"StationNumber: 05HB20, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB21, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB22, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB23, Year: 2005, Value: 0.616 mg/kg\",\"StationNumber: 05HB24, Year: 2005, Value: 2.172 mg/kg\",\"StationNumber: 05LTB01, Year: 2005, Value: 5.537 mg/kg\",\"StationNumber: 05LTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05LTB03, Year: 2005, Value: 2.554 mg/kg\",\"StationNumber: 05LTB04, Year: 2005, Value: 2.548 mg/kg\",\"StationNumber: 05LTB05, Year: 2005, Value: 1.008 mg/kg\",\"StationNumber: 05LTB06, Year: 2005, Value: 2.134 mg/kg\",\"StationNumber: 05LTB07, Year: 2005, Value: 3.24 mg/kg\",\"StationNumber: 05LTB08, Year: 2005, Value: 2.144 mg/kg\",\"StationNumber: 05LTB09, Year: 2005, Value: 4.455 mg/kg\",\"StationNumber: 05LTB10, Year: 2005, Value: 0.116 mg/kg\",\"StationNumber: 05LTB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR06, Year: 2005, Value: 1.085 mg/kg\",\"StationNumber: 05MR08, Year: 2005, Value: 0.372 mg/kg\",\"StationNumber: 05MR09, Year: 2005, Value: 0.97 mg/kg\",\"StationNumber: 05MR11, Year: 2005, Value: 0.271 mg/kg\",\"StationNumber: 05MTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB06, Year: 2005, Value: 0.691 mg/kg\",\"StationNumber: 05MTB07, Year: 2005, Value: 0.685 mg/kg\",\"StationNumber: 05MTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB10, Year: 2005, Value: 0.871 mg/kg\",\"StationNumber: 05MTB11, Year: 2005, Value: 0.609 mg/kg\",\"StationNumber: 05MTB12, Year: 2005, Value: 0.585 mg/kg\",\"StationNumber: 05MTB13, Year: 2005, Value: 1.943 mg/kg\",\"StationNumber: 05MTB14, Year: 2005, Value: 8.527 mg/kg\",\"StationNumber: 05MTB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB16, Year: 2005, Value: 0.45 mg/kg\",\"StationNumber: 05MTB17, Year: 2005, Value: 0.043 mg/kg\",\"StationNumber: 05MTB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB19, Year: 2005, Value: 0.177 mg/kg\",\"StationNumber: 05MTB20, Year: 2005, Value: 2.689 mg/kg\",\"StationNumber: 05MTB21, Year: 2005, Value: 0.156 mg/kg\",\"StationNumber: 05MTB22, Year: 2005, Value: 0.31 mg/kg\",\"StationNumber: 05OTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB02, Year: 2005, Value: 0.308 mg/kg\",\"StationNumber: 05OTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB04, Year: 2005, Value: 0.154 mg/kg\",\"StationNumber: 05OTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB06, Year: 2005, Value: 0.727 mg/kg\",\"StationNumber: 05OTB07, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB10, Year: 2005, Value: 0.348 mg/kg\",\"StationNumber: 05TCB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05TCB03, Year: 2005, Value: 1.689 mg/kg\",\"StationNumber: 05TCB05, Year: 2005, Value: 1.313 mg/kg\",\"StationNumber: 05TCB07, Year: 2005, Value: 0.98 mg/kg\",\"StationNumber: 05TCB10, Year: 2005, Value: 2.404 mg/kg\",\"StationNumber: 06BCB01, Year: 2006, Value: 10.76 mg/kg\",\"StationNumber: 06BCB02, Year: 2006, Value: 7.6 mg/kg\",\"StationNumber: 06BCB03, Year: 2006, Value: 6.966 mg/kg\",\"StationNumber: 06BCB04, Year: 2006, Value: 6.49 mg/kg\",\"StationNumber: 06BCB05, Year: 2006, Value: 1.041 mg/kg\",\"StationNumber: 06BCB06, Year: 2006, Value: 5.932 mg/kg\",\"StationNumber: 06BCB07, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06BCB08, Year: 2006, Value: 2.144 mg/kg\",\"StationNumber: 06BCB09, Year: 2006, Value: 6.173 mg/kg\",\"StationNumber: 06HB01, Year: 2006, Value: 0.768 mg/kg\",\"StationNumber: 06HB02, Year: 2006, Value: 6.388 mg/kg\",\"StationNumber: 06HB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB04, Year: 2006, Value: 5.29 mg/kg\",\"StationNumber: 06HB05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB06, Year: 2006, Value: 8.423 mg/kg\",\"StationNumber: 06HB08, Year: 2006, Value: 4.515 mg/kg\",\"StationNumber: 06HB09, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB10, Year: 2006, Value: 9.296 mg/kg\",\"StationNumber: 06HB11, Year: 2006, Value: 9.144 mg/kg\",\"StationNumber: 06HB12, Year: 2006, Value: 1.668 mg/kg\",\"StationNumber: 06HB13, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB14, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB15, Year: 2006, Value: 3.641 mg/kg\",\"StationNumber: 06HB16, Year: 2006, Value: 3.091 mg/kg\",\"StationNumber: 06HB17, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB18, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB19, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB20, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB21, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB22, Year: 2006, Value: 0.958 mg/kg\",\"StationNumber: 06HB23, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB24, Year: 2006, Value: 0.867 mg/kg\",\"StationNumber: 06HB25, Year: 2006, Value: 3.199 mg/kg\",\"StationNumber: 06LTB01, Year: 2006, Value: 5.442 mg/kg\",\"StationNumber: 06LTB02, Year: 2006, Value: 6.614 mg/kg\",\"StationNumber: 06LTB03, Year: 2006, Value: 13.302 mg/kg\",\"StationNumber: 06LTB04, Year: 2006, Value: 9.592 mg/kg\",\"StationNumber: 06LTB05, Year: 2006, Value: 6.313 mg/kg\",\"StationNumber: 06LTB06, Year: 2006, Value: 8.886 mg/kg\",\"StationNumber: 06LTB07, Year: 2006, Value: 7.536 mg/kg\",\"StationNumber: 06LTB08, Year: 2006, Value: 6.973 mg/kg\",\"StationNumber: 06MR05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MR06, Year: 2006, Value: 6.076 mg/kg\",\"StationNumber: 06MR07, Year: 2006, Value: 1.121 mg/kg\",\"StationNumber: 06MR08, Year: 2006, Value: 6.41 mg/kg\",\"StationNumber: 06MR10, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB01, Year: 2006, Value: 21.691 mg/kg\",\"StationNumber: 06MTB02, Year: 2006, Value: 7.887 mg/kg\",\"StationNumber: 06MTB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB04, Year: 2006, Value: 5.141 mg/kg\",\"StationNumber: 06MTB05, Year: 2006, Value: 6.599 mg/kg\",\"StationNumber: 06MTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB07, Year: 2006, Value: 8.465 mg/kg\",\"StationNumber: 06MTB08, Year: 2006, Value: 7.305 mg/kg\",\"StationNumber: 06MTB09, Year: 2006, Value: 9.749 mg/kg\",\"StationNumber: 06MTB10, Year: 2006, Value: 7.082 mg/kg\",\"StationNumber: 06MTB11, Year: 2006, Value: 4.9 mg/kg\",\"StationNumber: 06MTB12, Year: 2006, Value: 5.42 mg/kg\",\"StationNumber: 06MTB13, Year: 2006, Value: 2.843 mg/kg\",\"StationNumber: 06MTB14, Year: 2006, Value: 6.476 mg/kg\",\"StationNumber: 06MTB15, Year: 2006, Value: 6.64 mg/kg\",\"StationNumber: 06MTB16, Year: 2006, Value: 5.146 mg/kg\",\"StationNumber: 06MTB17, Year: 2006, Value: 8.46 mg/kg\",\"StationNumber: 06MTB18, Year: 2006, Value: 1.724 mg/kg\",\"StationNumber: 06MTB19, Year: 2006, Value: 5.701 mg/kg\",\"StationNumber: 06OTB01, Year: 2006, Value: 5.045 mg/kg\",\"StationNumber: 06OTB02, Year: 2006, Value: 6.294 mg/kg\",\"StationNumber: 06OTB03, Year: 2006, Value: 5.32 mg/kg\",\"StationNumber: 06OTB04, Year: 2006, Value: 5.697 mg/kg\",\"StationNumber: 06OTB05, Year: 2006, Value: 2.581 mg/kg\",\"StationNumber: 06OTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06OTB07, Year: 2006, Value: 2.085 mg/kg\",\"StationNumber: 06OTB08, Year: 2006, Value: 5.097 mg/kg\",\"StationNumber: 06TCB01, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB02, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB04, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB09, Year: 2006, Value: 0.189 mg/kg\",\"StationNumber: 07BCB06, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB09, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB15, Year: 2007, Value: 7.27 mg/kg\",\"StationNumber: 07BCB28, Year: 2007, Value: 6.46 mg/kg\",\"StationNumber: 07BCB29, Year: 2007, Value: 0.61 mg/kg\",\"StationNumber: 07BCB30, Year: 2007, Value: 9.62 mg/kg\",\"StationNumber: 07BCB41, Year: 2007, Value: 6.85 mg/kg\",\"StationNumber: 07BCB42, Year: 2007, Value: 11.82 mg/kg\",\"StationNumber: 07BCB44, Year: 2007, Value: 7.13 mg/kg\",\"StationNumber: 07BCB45, Year: 2007, Value: 8.32 mg/kg\",\"StationNumber: 07HB13, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB21, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB34, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB37, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB38, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB41, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB53, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07LTB91, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR09, Year: 2007, Value: 0.11 mg/kg\",\"StationNumber: 07MR28, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR46, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR50, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB34, Year: 2007, Value: 9.44 mg/kg\",\"StationNumber: 07MTB39, Year: 2007, Value: 4.6 mg/kg\",\"StationNumber: 07MTB40, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB43, Year: 2007, Value: 0.51 mg/kg\",\"StationNumber: 07MTB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB47, Year: 2007, Value: 10.84 mg/kg\",\"StationNumber: 07MTB54, Year: 2007, Value: 13.61 mg/kg\",\"StationNumber: 07OTB04, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB08, Year: 2007, Value: 7.25 mg/kg\",\"StationNumber: 07OTB18, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB21, Year: 2007, Value: 2.99 mg/kg\",\"StationNumber: 07OTB24, Year: 2007, Value: 3.72 mg/kg\",\"StationNumber: 07OTB25, Year: 2007, Value: 7.21 mg/kg\",\"StationNumber: 07OTB31, Year: 2007, Value: 10.48 mg/kg\",\"StationNumber: 07TCB14, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB15, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB20, Year: 2007, Value: 8.27 mg/kg\",\"StationNumber: 07TCB22, Year: 2007, Value: 1.55 mg/kg\",\"StationNumber: 08BCB02, Year: 2008, Value: 2.25 mg/kg\",\"StationNumber: 08BCB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB12, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB15, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB16, Year: 2008, Value: 4.4 mg/kg\",\"StationNumber: 08BCB17, Year: 2008, Value: 3.34 mg/kg\",\"StationNumber: 08BCB23, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB26, Year: 2008, Value: 9.9 mg/kg\",\"StationNumber: 08BCB29, Year: 2008, Value: 7.8 mg/kg\",\"StationNumber: 08BCB35, Year: 2008, Value: 7.83 mg/kg\",\"StationNumber: 08BCB38, Year: 2008, Value: 6.95 mg/kg\",\"StationNumber: 08HB13, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB14, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB17, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB21, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB27, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB34, Year: 2008, Value: 4.62 mg/kg\",\"StationNumber: 08HB43, Year: 2008, Value: 4.15 mg/kg\",\"StationNumber: 08HB44, Year: 2008, Value: 6.35 mg/kg\",\"StationNumber: 08HB48, Year: 2008, Value: 7.51 mg/kg\",\"StationNumber: 08LTB69, Year: 2008, Value: 9.07 mg/kg\",\"StationNumber: 08LTB79, Year: 2008, Value: 22.19 mg/kg\",\"StationNumber: 08LTB82, Year: 2008, Value: 9.06 mg/kg\",\"StationNumber: 08MR08, Year: 2008, Value: 11.03 mg/kg\",\"StationNumber: 08MR35, Year: 2008, Value: 6.78 mg/kg\",\"StationNumber: 08MR40, Year: 2008, Value: 2.73 mg/kg\",\"StationNumber: 08MR43, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08MR53, Year: 2008, Value: 4.18 mg/kg\",\"StationNumber: 08MR54, Year: 2008, Value: 5.54 mg/kg\",\"StationNumber: 08MTB37, Year: 2008, Value: 6.6 mg/kg\",\"StationNumber: 08MTB47, Year: 2008, Value: 8.06 mg/kg\",\"StationNumber: 08MTB53, Year: 2008, Value: 0 mg/kg\",\"StationNumber: 08MTB62, Year: 2008, Value: 11.22 mg/kg\",\"StationNumber: 08MTB73, Year: 2008, Value: 4.04 mg/kg\",\"StationNumber: 08OTB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08OTB07, Year: 2008, Value: 0.46 mg/kg\",\"StationNumber: 08OTB13, Year: 2008, Value: 6.98 mg/kg\",\"StationNumber: 08OTB15, Year: 2008, Value: 3.77 mg/kg\",\"StationNumber: 08OTB17, Year: 2008, Value: 8.33 mg/kg\",\"StationNumber: 08OTB23, Year: 2008, Value: 11.18 mg/kg\",\"StationNumber: 08OTB27, Year: 2008, Value: 9.44 mg/kg\",\"StationNumber: 08TCB01, Year: 2008, Value: 1.91 mg/kg\",\"StationNumber: 08TCB07, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08TCB26, Year: 2008, Value: 0.07 mg/kg\",\"StationNumber: 10BCB06, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB11, Year: 2010, Value: 5.82 mg/kg\",\"StationNumber: 10BCB17, Year: 2010, Value: 5.65 mg/kg\",\"StationNumber: 10BCB25, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB28, Year: 2010, Value: 7.31 mg/kg\",\"StationNumber: 10BCB30, Year: 2010, Value: 8.9 mg/kg\",\"StationNumber: 10BCB37, Year: 2010, Value: 5.2 mg/kg\",\"StationNumber: 10BCB41, Year: 2010, Value: 4.55 mg/kg\",\"StationNumber: 10BCB46, Year: 2010, Value: 5.05 mg/kg\",\"StationNumber: 10BCB47, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB49, Year: 2010, Value: 6.65 mg/kg\",\"StationNumber: 10HB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB22, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB25, Year: 2010, Value: 10.85 mg/kg\",\"StationNumber: 10HB26, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB34, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB44, Year: 2010, Value: 6.34 mg/kg\",\"StationNumber: 10HB46, Year: 2010, Value: 5.15 mg/kg\",\"StationNumber: 10HB48, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB54, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB71, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB76, Year: 2010, Value: 4.59 mg/kg\",\"StationNumber: 10LTB89, Year: 2010, Value: 9.22 mg/kg\",\"StationNumber: 10MR25, Year: 2010, Value: 7.48 mg/kg\",\"StationNumber: 10MR29, Year: 2010, Value: 9.82 mg/kg\",\"StationNumber: 10MR33, Year: 2010, Value: 4.36 mg/kg\",\"StationNumber: 10MR40, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MR44, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB30, Year: 2010, Value: 9.2 mg/kg\",\"StationNumber: 10MTB35, Year: 2010, Value: 5.93 mg/kg\",\"StationNumber: 10MTB43, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB53, Year: 2010, Value: 9.06 mg/kg\",\"StationNumber: 10MTB56, Year: 2010, Value: 9.26 mg/kg\",\"StationNumber: 10OTB04, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB05, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB07, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB08, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB09, Year: 2010, Value: 4.65 mg/kg\",\"StationNumber: 10OTB12, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB14, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB15, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB16, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB18, Year: 2010, Value: 8.82 mg/kg\",\"StationNumber: 10OTB19, Year: 2010, Value: 4.94 mg/kg\",\"StationNumber: 10OTB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB24, Year: 2010, Value: 6.72 mg/kg\",\"StationNumber: 10OTB25, Year: 2010, Value: 7.91 mg/kg\",\"StationNumber: 10OTB26, Year: 2010, Value: 8.22 mg/kg\",\"StationNumber: 10OTB28, Year: 2010, Value: 10.09 mg/kg\",\"StationNumber: 10OTB29, Year: 2010, Value: 9.46 mg/kg\",\"StationNumber: 10OTB96, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB97, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB98, Year: 2010, Value: 9.71 mg/kg\",\"StationNumber: 10TCB01, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB11, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 11BCB05, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB20, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB22, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB42, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB48, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB13, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB29, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB31, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB36, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB38, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB40, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB47, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB69, Year: 2011, Value: 4.07 mg/kg\",\"StationNumber: 11LTB75, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB80, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR37, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR45, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR52, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB39, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB46, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB54, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB72, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB08, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB24, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB31, Year: 2011, Value: 4.24 mg/kg\",\"StationNumber: 11OTB32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB10, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 12BCB06, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB23, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB25, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB35, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB44, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB49, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB28, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB31, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB32, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB38, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB45, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB78, Year: 2012, Value: 10.58 mg/kg\",\"StationNumber: 12LTB84, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB93, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR17, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR33, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR36, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR43, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB47, Year: 2012, Value: 4.25 mg/kg\",\"StationNumber: 12MTB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB58, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB63, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB64, Year: 2012, Value: 4.45 mg/kg\",\"StationNumber: 12OTB04, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB18, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB20, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB05, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 13BCB05, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB07, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB10, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB17, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB22, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB30, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB43, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB13, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB25, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB26, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB36, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB79, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB82, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB86, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR24, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR31, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB34, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB55, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB12, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB15, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB16, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB21, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB27, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB28, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB29, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB01, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB14, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 14BCB03, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14BCB12, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB17, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB26, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB43, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB44, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB71, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB81, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB90, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR37, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR38, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14MR47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB39, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB63, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB04, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB08, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB14, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB18, Year: 2014, Value: 463.9 mg/kg\",\"StationNumber: 14OTB19, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB22, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 15BCB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB31, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB34, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB43, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB47, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB14, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB27, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB36, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB37, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB41, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB70, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB76, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB94, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR08, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR33, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR42, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB49, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB55, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB62, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB20, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB24, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB29, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB01, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB11, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 16BCB20, Year: 2016, Value: 3.32 mg/kg\",\"StationNumber: 16BCB22, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB25, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB29, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB34, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB35, Year: 2016, Value: 3.05 mg/kg\",\"StationNumber: 16BCB36, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB41, Year: 2016, Value: 2.42 mg/kg\",\"StationNumber: 16BCB42, Year: 2016, Value: 1.18 mg/kg\",\"StationNumber: 16BCB43, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16DH01-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-4, Year: 2016, Value: 3.25 mg/kg\",\"StationNumber: 16DH03-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-4, Year: 2016, Value: 0.76 mg/kg\",\"StationNumber: 16DH04-1, Year: 2016, Value: 2.53 mg/kg\",\"StationNumber: 16DH04-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-4, Year: 2016, Value: 3.5 mg/kg\",\"StationNumber: 16DH05-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-3, Year: 2016, Value: 1.87 mg/kg\",\"StationNumber: 16DH05-4, Year: 2016, Value: 2.91 mg/kg\",\"StationNumber: 16DH06-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-4, Year: 2016, Value: 1.85 mg/kg\",\"StationNumber: 16DH08-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-2, Year: 2016, Value: 2.25 mg/kg\",\"StationNumber: 16DH10-3, Year: 2016, Value: 1.16 mg/kg\",\"StationNumber: 16DH10-4, Year: 2016, Value: 3.43 mg/kg\",\"StationNumber: 16HB19, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB21, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB27, Year: 2016, Value: 2.44 mg/kg\",\"StationNumber: 16HB28, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB32, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16LTB71, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16LTB79, Year: 2016, Value: 8.12 mg/kg\",\"StationNumber: 16LTB85, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR17, Year: 2016, Value: 2.41 mg/kg\",\"StationNumber: 16MR25, Year: 2016, Value: 1.84 mg/kg\",\"StationNumber: 16MR29, Year: 2016, Value: 0.62 mg/kg\",\"StationNumber: 16MR33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR43, Year: 2016, Value: 2.1 mg/kg\",\"StationNumber: 16MR44, Year: 2016, Value: 0.09 mg/kg\",\"StationNumber: 16MR45, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB41, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB47, Year: 2016, Value: 3.95 mg/kg\",\"StationNumber: 16MTB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB53, Year: 2016, Value: 4.34 mg/kg\",\"StationNumber: 16MTB72, Year: 2016, Value: 1.69 mg/kg\",\"StationNumber: 16OTB08, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB09, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB13, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB18, Year: 2016, Value: 1.78 mg/kg\",\"StationNumber: 16OTB22, Year: 2016, Value: 3.79 mg/kg\",\"StationNumber: 16OTB25, Year: 2016, Value: 1.02 mg/kg\",\"StationNumber: 16TCB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16TCB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 17BCB15, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB27, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB30, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB36, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB40, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB44, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB10, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB15, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 17HB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB34, Year: 2017, Value: 524.32 mg/kg\",\"StationNumber: 17HB36, Year: 2017, Value: 8.91 mg/kg\",\"StationNumber: 17HB41, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB70, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB83, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB89, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR09, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR18, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR24, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR37, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB34, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB46, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB55, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB63, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB04, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB07, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB19, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB28, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP01, Year: 2017, Value: 20.64 mg/kg\",\"StationNumber: 17TCP02, Year: 2017, Value: 17.43 mg/kg\",\"StationNumber: 17TCP03, Year: 2017, Value: 15.42 mg/kg\",\"StationNumber: 17TCP04, Year: 2017, Value: 14.89 mg/kg\",\"StationNumber: 17TCP05, Year: 2017, Value: 9.77 mg/kg\",\"StationNumber: 17TCP06, Year: 2017, Value: 27.33 mg/kg\",\"StationNumber: 17TCP07, Year: 2017, Value: 11.7 mg/kg\",\"StationNumber: 17TCP08, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP09, Year: 2017, Value: 8.06 mg/kg\",\"StationNumber: 17TCP10, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 18BCB11, Year: 2018, Value: 24.7 mg/kg\",\"StationNumber: 18BCB15, Year: 2018, Value: 1.51 mg/kg\",\"StationNumber: 18BCB19, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB20, Year: 2018, Value: 1.19 mg/kg\",\"StationNumber: 18BCB22, Year: 2018, Value: 1.43 mg/kg\",\"StationNumber: 18BCB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB26, Year: 2018, Value: 1.76 mg/kg\",\"StationNumber: 18BCB37, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB42, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB44, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB46, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18HB14, Year: 2018, Value: 2.7 mg/kg\",\"StationNumber: 18HB20, Year: 2018, Value: 4.74 mg/kg\",\"StationNumber: 18HB21, Year: 2018, Value: 1.96 mg/kg\",\"StationNumber: 18HB26, Year: 2018, Value: 2.48 mg/kg\",\"StationNumber: 18HB29, Year: 2018, Value: 1.98 mg/kg\",\"StationNumber: 18HB33, Year: 2018, Value: 3.56 mg/kg\",\"StationNumber: 18HB38, Year: 2018, Value: 3.23 mg/kg\",\"StationNumber: 18HB41, Year: 2018, Value: 1.26 mg/kg\",\"StationNumber: 18HB46, Year: 2018, Value: 1.05 mg/kg\",\"StationNumber: 18LTB75, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB79, Year: 2018, Value: 14.24 mg/kg\",\"StationNumber: 18LTB81, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB82, Year: 2018, Value: 0.1 mg/kg\",\"StationNumber: 18MR25, Year: 2018, Value: 7.31 mg/kg\",\"StationNumber: 18MR37, Year: 2018, Value: 0.78 mg/kg\",\"StationNumber: 18MR46, Year: 2018, Value: 0.07 mg/kg\",\"StationNumber: 18MTB41, Year: 2018, Value: 1.08 mg/kg\",\"StationNumber: 18MTB42, Year: 2018, Value: 2.2 mg/kg\",\"StationNumber: 18MTB48, Year: 2018, Value: 1.01 mg/kg\",\"StationNumber: 18MTB56, Year: 2018, Value: 1.63 mg/kg\",\"StationNumber: 18OTB04, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB08, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB13, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB14, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB15, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB21, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18TCB05, Year: 2018, Value: 9.11 mg/kg\",\"StationNumber: 18TCB11, Year: 2018, Value: 6.79 mg/kg\",\"StationNumber: 18TCB14, Year: 2018, Value: 5.34 mg/kg\",\"StationNumber: 18TCB15, Year: 2018, Value: 6.28 mg/kg\",\"StationNumber: 18TCB21, Year: 2018, Value: 15.39 mg/kg\",\"StationNumber: 18TCB22, Year: 2018, Value: 5.61 mg/kg\",\"StationNumber: 19BCB27, Year: 2019, Value: 5.22 mg/kg\",\"StationNumber: 19BCB29, Year: 2019, Value: 5.87 mg/kg\",\"StationNumber: 19BCB30, Year: 2019, Value: 12.82 mg/kg\",\"StationNumber: 19BCB34, Year: 2019, Value: 0.26 mg/kg\",\"StationNumber: 19BCB35, Year: 2019, Value: 5.29 mg/kg\",\"StationNumber: 19BCB36, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19BCB40, Year: 2019, Value: 0.86 mg/kg\",\"StationNumber: 19BCB41, Year: 2019, Value: 0.61 mg/kg\",\"StationNumber: 19BCB43, Year: 2019, Value: 0.3 mg/kg\",\"StationNumber: 19BCB49, Year: 2019, Value: 1.28 mg/kg\",\"StationNumber: 19BCB50, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19HB09, Year: 2019, Value: 0.5 mg/kg\",\"StationNumber: 19HB16, Year: 2019, Value: 15.28 mg/kg\",\"StationNumber: 19HB25, Year: 2019, Value: 0.59 mg/kg\",\"StationNumber: 19HB27, Year: 2019, Value: 3.02 mg/kg\",\"StationNumber: 19HB32, Year: 2019, Value: 3.82 mg/kg\",\"StationNumber: 19HB37, Year: 2019, Value: 3.57 mg/kg\",\"StationNumber: 19HB39, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19HB40, Year: 2019, Value: 1.14 mg/kg\",\"StationNumber: 19HB47, Year: 2019, Value: 0.06 mg/kg\",\"StationNumber: 19LTB76, Year: 2019, Value: 1.06 mg/kg\",\"StationNumber: 19LTB78, Year: 2019, Value: 0.74 mg/kg\",\"StationNumber: 19LTB88, Year: 2019, Value: 6.12 mg/kg\",\"StationNumber: 19LTB90, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19MR17, Year: 2019, Value: 1.46 mg/kg\",\"StationNumber: 19MR18, Year: 2019, Value: 1.44 mg/kg\",\"StationNumber: 19MR29, Year: 2019, Value: 2.28 mg/kg\",\"StationNumber: 19MR33, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19MR43, Year: 2019, Value: 5.07 mg/kg\",\"StationNumber: 19MR44, Year: 2019, Value: 6.22 mg/kg\",\"StationNumber: 19MR52, Year: 2019, Value: 1.98 mg/kg\",\"StationNumber: 19MTB36, Year: 2019, Value: 2.26 mg/kg\",\"StationNumber: 19MTB47, Year: 2019, Value: 0.31 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 1.61 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 2.2 mg/kg\",\"StationNumber: 19MTB62, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19OTB07, Year: 2019, Value: 1.5 mg/kg\",\"StationNumber: 19OTB18, Year: 2019, Value: 1.2 mg/kg\",\"StationNumber: 19OTB20, Year: 2019, Value: 0.38 mg/kg\",\"StationNumber: 19OTB23, Year: 2019, Value: 0.9 mg/kg\",\"StationNumber: 19OTB25, Year: 2019, Value: 0.94 mg/kg\",\"StationNumber: 19OTB29, Year: 2019, Value: 1.32 mg/kg\",\"StationNumber: 19OTB31, Year: 2019, Value: 2.03 mg/kg\",\"StationNumber: 19TCB01, Year: 2019, Value: 4.92 mg/kg\",\"StationNumber: 19TCB20, Year: 2019, Value: 3.89 mg/kg\",\"StationNumber: 20BCB10, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB17, Year: 2020, Value: 0.92 mg/kg\",\"StationNumber: 20BCB22, Year: 2020, Value: 15.76 mg/kg\",\"StationNumber: 20BCB23, Year: 2020, Value: 0.99 mg/kg\",\"StationNumber: 20BCB35, Year: 2020, Value: 3.19 mg/kg\",\"StationNumber: 20BCB37, Year: 2020, Value: 1.91 mg/kg\",\"StationNumber: 20BCB40, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB43, Year: 2020, Value: 1.81 mg/kg\",\"StationNumber: 20BCB47, Year: 2020, Value: 1.65 mg/kg\",\"StationNumber: 20BCB48, Year: 2020, Value: 0.78 mg/kg\",\"StationNumber: 20BCB49, Year: 2020, Value: 1.3 mg/kg\",\"StationNumber: 20HB09, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB10, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB26, Year: 2020, Value: 8.35 mg/kg\",\"StationNumber: 20HB38, Year: 2020, Value: 3.49 mg/kg\",\"StationNumber: 20HB41, Year: 2020, Value: 3.54 mg/kg\",\"StationNumber: 20HB46, Year: 2020, Value: 1.16 mg/kg\",\"StationNumber: 20HB47, Year: 2020, Value: 0.34 mg/kg\",\"StationNumber: 20HB52, Year: 2020, Value: 2.28 mg/kg\",\"StationNumber: 20LTB70, Year: 2020, Value: 0.79 mg/kg\",\"StationNumber: 20LTB71, Year: 2020, Value: 0.96 mg/kg\",\"StationNumber: 20LTB77, Year: 2020, Value: 2.21 mg/kg\",\"StationNumber: 20LTB85, Year: 2020, Value: 10.94 mg/kg\",\"StationNumber: 20MR08, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR09, Year: 2020, Value: 1.22 mg/kg\",\"StationNumber: 20MR33, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR36, Year: 2020, Value: 1.24 mg/kg\",\"StationNumber: 20MR44, Year: 2020, Value: 6.25 mg/kg\",\"StationNumber: 20MR49, Year: 2020, Value: 0.94 mg/kg\",\"StationNumber: 20MTB35, Year: 2020, Value: 3.65 mg/kg\",\"StationNumber: 20MTB46, Year: 2020, Value: 0.23 mg/kg\",\"StationNumber: 20MTB52, Year: 2020, Value: 1.12 mg/kg\",\"StationNumber: 20MTB63, Year: 2020, Value: 0.48 mg/kg\",\"StationNumber: 20OTB13, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB14, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB15, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB19, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB24, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB32, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20TCB10, Year: 2020, Value: 4.53 mg/kg\",\"StationNumber: 20TCB12, Year: 2020, Value: 3.28 mg/kg\",\"StationNumber: 20TCB20, Year: 2020, Value: 3.03 mg/kg\",\"StationNumber: 21BCB09, Year: 2021, Value: 11.03 mg/kg\",\"StationNumber: 21BCB12, Year: 2021, Value: 4.15 mg/kg\",\"StationNumber: 21BCB15, Year: 2021, Value: 8.58 mg/kg\",\"StationNumber: 21BCB22, Year: 2021, Value: 1.46 mg/kg\",\"StationNumber: 21BCB25, Year: 2021, Value: 3.25 mg/kg\",\"StationNumber: 21BCB26, Year: 2021, Value: 5.19 mg/kg\",\"StationNumber: 21BCB29, Year: 2021, Value: 2.06 mg/kg\",\"StationNumber: 21BCB36, Year: 2021, Value: 0.98 mg/kg\",\"StationNumber: 21BCB41, Year: 2021, Value: 1.48 mg/kg\",\"StationNumber: 21BCB44, Year: 2021, Value: 4.08 mg/kg\",\"StationNumber: 21BCB50, Year: 2021, Value: 0.79 mg/kg\",\"StationNumber: 21HB13, Year: 2021, Value: 3.05 mg/kg\",\"StationNumber: 21HB19, Year: 2021, Value: 3.23 mg/kg\",\"StationNumber: 21HB20, Year: 2021, Value: 0.39 mg/kg\",\"StationNumber: 21HB27, Year: 2021, Value: 2.12 mg/kg\",\"StationNumber: 21HB34, Year: 2021, Value: 0.2 mg/kg\",\"StationNumber: 21HB36, Year: 2021, Value: 1.6 mg/kg\",\"StationNumber: 21HB37, Year: 2021, Value: 2.04 mg/kg\",\"StationNumber: 21HB40, Year: 2021, Value: 1.21 mg/kg\",\"StationNumber: 21HB43, Year: 2021, Value: 1.09 mg/kg\",\"StationNumber: 21LTB78, Year: 2021, Value: 3.26 mg/kg\",\"StationNumber: 21LTB83, Year: 2021, Value: 1.43 mg/kg\",\"StationNumber: 21LTB84, Year: 2021, Value: 5.27 mg/kg\",\"StationNumber: 21LTB89, Year: 2021, Value: 0.38 mg/kg\",\"StationNumber: 21MR24, Year: 2021, Value: 1.29 mg/kg\",\"StationNumber: 21MR29, Year: 2021, Value: 1.72 mg/kg\",\"StationNumber: 21MR45, Year: 2021, Value: 4.29 mg/kg\",\"StationNumber: 21MR47, Year: 2021, Value: 1.64 mg/kg\",\"StationNumber: 21MR52, Year: 2021, Value: 1.92 mg/kg\",\"StationNumber: 21MTB40, Year: 2021, Value: 0.15 mg/kg\",\"StationNumber: 21MTB43, Year: 2021, Value: 3.11 mg/kg\",\"StationNumber: 21MTB48, Year: 2021, Value: 1.12 mg/kg\",\"StationNumber: 21MTB62, Year: 2021, Value: 3.19 mg/kg\",\"StationNumber: 21OTB08, Year: 2021, Value: 0.22 mg/kg\",\"StationNumber: 21OTB12, Year: 2021, Value: 4.8 mg/kg\",\"StationNumber: 21OTB13, Year: 2021, Value: 0.45 mg/kg\",\"StationNumber: 21OTB18, Year: 2021, Value: 2.44 mg/kg\",\"StationNumber: 21OTB21, Year: 2021, Value: 0.24 mg/kg\",\"StationNumber: 21OTB25, Year: 2021, Value: 0.32 mg/kg\",\"StationNumber: 21OTB28, Year: 2021, Value: 0.16 mg/kg\",\"StationNumber: 21TCB02, Year: 2021, Value: 11.5 mg/kg\",\"StationNumber: 21TCB13, Year: 2021, Value: 7.11 mg/kg\",\"StationNumber: 21TCB22, Year: 2021, Value: 4.36 mg/kg\",\"StationNumber: 21TCB26, Year: 2021, Value: 2.49 mg/kg\",\"StationNumber: 22BCB02, Year: 2022, Value: 5.83 mg/kg\",\"StationNumber: 22BCB05, Year: 2022, Value: 1.17 mg/kg\",\"StationNumber: 22BCB11, Year: 2022, Value: 1.49 mg/kg\",\"StationNumber: 22BCB12, Year: 2022, Value: 1.1 mg/kg\",\"StationNumber: 22BCB17, Year: 2022, Value: 2.31 mg/kg\",\"StationNumber: 22BCB27, Year: 2022, Value: 1.33 mg/kg\",\"StationNumber: 22BCB30, Year: 2022, Value: 0.91 mg/kg\",\"StationNumber: 22BCB34, Year: 2022, Value: 0.62 mg/kg\",\"StationNumber: 22BCB35, Year: 2022, Value: 0.48 mg/kg\",\"StationNumber: 22BCB45, Year: 2022, Value: 1.24 mg/kg\",\"StationNumber: 22BCB47, Year: 2022, Value: 3.19 mg/kg\",\"StationNumber: 22HB10, Year: 2022, Value: 0.54 mg/kg\",\"StationNumber: 22HB19, Year: 2022, Value: 0.13 mg/kg\",\"StationNumber: 22HB21, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22HB25, Year: 2022, Value: 1.8 mg/kg\",\"StationNumber: 22HB26, Year: 2022, Value: 4.73 mg/kg\",\"StationNumber: 22HB28, Year: 2022, Value: 0.27 mg/kg\",\"StationNumber: 22HB32, Year: 2022, Value: 3.93 mg/kg\",\"StationNumber: 22HB40, Year: 2022, Value: 0.56 mg/kg\",\"StationNumber: 22HB46, Year: 2022, Value: 0.97 mg/kg\",\"StationNumber: 22LTB70, Year: 2022, Value: 2.91 mg/kg\",\"StationNumber: 22LTB79, Year: 2022, Value: 10.38 mg/kg\",\"StationNumber: 22LTB81, Year: 2022, Value: 0.9 mg/kg\",\"StationNumber: 22LTB90, Year: 2022, Value: 0.01 mg/kg\",\"StationNumber: 22MR17, Year: 2022, Value: 1.62 mg/kg\",\"StationNumber: 22MR25, Year: 2022, Value: 1.11 mg/kg\",\"StationNumber: 22MR32, Year: 2022, Value: 2.35 mg/kg\",\"StationNumber: 22MR37, Year: 2022, Value: 1.94 mg/kg\",\"StationNumber: 22MR42, Year: 2022, Value: 0.87 mg/kg\",\"StationNumber: 22MR44, Year: 2022, Value: 1.16 mg/kg\",\"StationNumber: 22MR46, Year: 2022, Value: 0.24 mg/kg\",\"StationNumber: 22MR52, Year: 2022, Value: 4.05 mg/kg\",\"StationNumber: 22MTB35, Year: 2022, Value: 1.69 mg/kg\",\"StationNumber: 22MTB37, Year: 2022, Value: 0.46 mg/kg\",\"StationNumber: 22MTB41, Year: 2022, Value: 2.4 mg/kg\",\"StationNumber: 22MTB55, Year: 2022, Value: 0.8 mg/kg\",\"StationNumber: 22OTB02, Year: 2022, Value: 1.05 mg/kg\",\"StationNumber: 22OTB07, Year: 2022, Value: 2.48 mg/kg\",\"StationNumber: 22OTB19, Year: 2022, Value: 1.75 mg/kg\",\"StationNumber: 22OTB22, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22OTB28, Year: 2022, Value: 0.25 mg/kg\",\"StationNumber: 22OTB29, Year: 2022, Value: 0.19 mg/kg\",\"StationNumber: 22OTB32, Year: 2022, Value: 0.15 mg/kg\",\"StationNumber: 22TCB20, Year: 2022, Value: 2.86 mg/kg\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.343422]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot summary of PEL averages by bay segment — show_sedimentpelave","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Plot summary PEL averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   alph = 1,   ylim = c(0, 0.4),   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" alph numeric indicating alpha value score category colors ylim numeric y axis limits lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"ggplot object plotly object plotly = TRUE showing PEL averages (average averages) 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Lines grades shown plot. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(sedimentdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"Creates plotly object average PEL plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"show_sedimentpelaveplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"p ggplot object output show_sedimentpelave width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"p <- show_sedimentpelave(sedimentdata) show_sedimentpelaveplotly(p)  {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,0.0075599999999999999,0.0075599999999999999,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.0075599999999999999,0.02052,0.02052,0.0075599999999999999,0.0075599999999999999],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(162,253,122,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.02052,0.085669999999999996,0.085669999999999996,0.02052,0.02052],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.085669999999999996,0.28026000000000001,0.28026000000000001,0.085669999999999996,0.085669999999999996],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(238,118,0,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.28026000000000001,null,null,0.28026000000000001,0.28026000000000001],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: 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C\",\"StationNumber: 94LTB35, Year: 1994, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 94LTB36, Year: 1994, PEL ratio: 0.04666, Grade: C\",\"StationNumber: 94LTB37, Year: 1994, PEL ratio: 0.10165, Grade: D\",\"StationNumber: 94LTB38, Year: 1994, PEL ratio: 0.02221, Grade: C\",\"StationNumber: 94LTB39, Year: 1994, PEL ratio: 0.08637, Grade: D\",\"StationNumber: 94LTB40, Year: 1994, PEL ratio: 0.06117, Grade: C\",\"StationNumber: 94MR23, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR24, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR26, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR27, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR28, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR29, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR31, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR32, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR34, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR43, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MTB41, Year: 1994, PEL ratio: 0.00869, Grade: B\",\"StationNumber: 94MTB42, Year: 1994, PEL ratio: 0.00546, Grade: A\",\"StationNumber: 94MTB43, Year: 1994, PEL ratio: 0.07634, Grade: C\",\"StationNumber: 94MTB44, Year: 1994, PEL ratio: 0.09942, Grade: D\",\"StationNumber: 94MTB45, Year: 1994, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 94MTB47, Year: 1994, PEL ratio: 0.03786, Grade: C\",\"StationNumber: 94MTB48, Year: 1994, PEL ratio: 0.00958, Grade: B\",\"StationNumber: 94MTB49, Year: 1994, PEL ratio: 0.08992, Grade: D\",\"StationNumber: 94MTB50, Year: 1994, PEL ratio: 0.04484, Grade: C\",\"StationNumber: 94MTB51, Year: 1994, PEL ratio: 0.01764, Grade: B\",\"StationNumber: 94MTB52, Year: 1994, PEL ratio: 0.01808, Grade: B\",\"StationNumber: 94MTB53, Year: 1994, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 94MTB54, Year: 1994, PEL ratio: 0.05744, Grade: C\",\"StationNumber: 94MTB55, Year: 1994, PEL ratio: 0.00805, Grade: B\",\"StationNumber: 94MTB56, Year: 1994, PEL ratio: 0.03262, Grade: C\",\"StationNumber: 94MTB57, Year: 1994, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 94MTB58, Year: 1994, PEL ratio: 0.10823, Grade: D\",\"StationNumber: 94MTB59, Year: 1994, PEL ratio: 0.0237, Grade: C\",\"StationNumber: 94MTB60, Year: 1994, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 94MTB61, Year: 1994, PEL ratio: 0.14417, Grade: D\",\"StationNumber: 94OTB63, Year: 1994, PEL ratio: 0.16877, Grade: D\",\"StationNumber: 94OTB64, Year: 1994, PEL ratio: 0.01051, Grade: B\",\"StationNumber: 94OTB65, Year: 1994, PEL ratio: 0.02364, Grade: C\",\"StationNumber: 94OTB66, Year: 1994, PEL ratio: 0.0106, Grade: B\",\"StationNumber: 94OTB67, Year: 1994, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 94OTB68, Year: 1994, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 94OTB69, Year: 1994, PEL ratio: 0.01953, Grade: B\",\"StationNumber: 94OTB70, Year: 1994, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 94OTB71, Year: 1994, PEL ratio: 0.0663, Grade: C\",\"StationNumber: 94OTB72, Year: 1994, PEL ratio: 0.01765, Grade: B\",\"StationNumber: 94OTB73, Year: 1994, PEL ratio: 0.09561, Grade: D\",\"StationNumber: 94OTB76, Year: 1994, PEL ratio: 0.01769, Grade: B\",\"StationNumber: 94OTB77, Year: 1994, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 94OTB78, Year: 1994, PEL ratio: 0.15079, Grade: D\",\"StationNumber: 94OTB79, Year: 1994, PEL ratio: 0.02344, Grade: C\",\"StationNumber: 94OTB80, Year: 1994, PEL ratio: 0.02606, Grade: C\",\"StationNumber: 94OTB83, Year: 1994, PEL ratio: 0.01552, Grade: B\",\"StationNumber: 94TCB22, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB37, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB38, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB39, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB40, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB41, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB42, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB01, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB02, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB03, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB04, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB05, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB06, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB07, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB08, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB09, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB10, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB11, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB12, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB13, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB14, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB15, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB16, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB17, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB18, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB19, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB20, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB21, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95HB14, Year: 1995, PEL ratio: 0.27004, Grade: D\",\"StationNumber: 95HB16, Year: 1995, PEL ratio: 0.46027, Grade: F\",\"StationNumber: 95HB17, Year: 1995, PEL ratio: 0.04182, Grade: C\",\"StationNumber: 95HB18, Year: 1995, PEL ratio: 0.25744, Grade: D\",\"StationNumber: 95HB19, Year: 1995, PEL ratio: 0.02669, Grade: C\",\"StationNumber: 95HB22, Year: 1995, PEL ratio: 0.08766, Grade: D\",\"StationNumber: 95HB23, Year: 1995, PEL ratio: 0.17389, Grade: D\",\"StationNumber: 95HB24, Year: 1995, PEL ratio: 0.00709, Grade: A\",\"StationNumber: 95HB25, Year: 1995, PEL ratio: 0.10295, Grade: D\",\"StationNumber: 95HB26, Year: 1995, PEL ratio: 0.00947, Grade: B\",\"StationNumber: 95HB27, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB28, Year: 1995, PEL ratio: 0.00784, Grade: B\",\"StationNumber: 95HB29, Year: 1995, PEL ratio: 0.06887, Grade: C\",\"StationNumber: 95HB37, Year: 1995, PEL ratio: 0.07591, Grade: C\",\"StationNumber: 95HB38, Year: 1995, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 95HB40, Year: 1995, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 95HB41, Year: 1995, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 95HB42, Year: 1995, PEL ratio: 0.00695, Grade: A\",\"StationNumber: 95HB43, Year: 1995, PEL ratio: 0.07978, Grade: C\",\"StationNumber: 95HB44, Year: 1995, PEL ratio: 0.00487, Grade: A\",\"StationNumber: 95HB45, Year: 1995, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 95HB46, Year: 1995, PEL ratio: 0.11769, Grade: D\",\"StationNumber: 95HB48, Year: 1995, PEL ratio: 0.01232, Grade: B\",\"StationNumber: 95HB49, Year: 1995, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 95HB51, Year: 1995, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 95HB52, Year: 1995, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 95HB54, Year: 1995, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 95HB55, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB56, Year: 1995, PEL ratio: 0.19484, Grade: D\",\"StationNumber: 95LTB01, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95LTB02, Year: 1995, PEL ratio: 0.00483, Grade: A\",\"StationNumber: 95LTB04, Year: 1995, PEL ratio: 0.01579, Grade: B\",\"StationNumber: 95LTB05, Year: 1995, PEL ratio: 0.02646, Grade: C\",\"StationNumber: 95LTB06, Year: 1995, PEL ratio: 0.00405, Grade: A\",\"StationNumber: 95LTB07, Year: 1995, PEL ratio: 0.00392, Grade: A\",\"StationNumber: 95LTB08, Year: 1995, PEL ratio: 0.00633, Grade: A\",\"StationNumber: 95LTB09, Year: 1995, PEL ratio: 0.00764, Grade: B\",\"StationNumber: 95LTB10, Year: 1995, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 95LTB11, Year: 1995, PEL ratio: 0.01854, Grade: B\",\"StationNumber: 95LTB12, Year: 1995, PEL ratio: 0.05258, Grade: C\",\"StationNumber: 95LTB13, Year: 1995, PEL ratio: 0.03364, Grade: C\",\"StationNumber: 95LTB15, Year: 1995, PEL ratio: 0.00223, Grade: A\",\"StationNumber: 95LTB17, Year: 1995, PEL ratio: 0.00912, Grade: B\",\"StationNumber: 95LTB18, Year: 1995, PEL ratio: 0.00937, Grade: B\",\"StationNumber: 95LTB19, Year: 1995, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 95LTB20, Year: 1995, PEL ratio: 0.00586, Grade: A\",\"StationNumber: 95LTB21, Year: 1995, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 95LTB23, Year: 1995, PEL ratio: 0.01403, Grade: B\",\"StationNumber: 95LTB25, Year: 1995, PEL ratio: 0.002, Grade: A\",\"StationNumber: 95LTB26, Year: 1995, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 95LTB29, Year: 1995, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 95MR23, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR24, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR25, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR26, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR27, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR28, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR29, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR31, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR32, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR34, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR43, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MTB03, Year: 1995, PEL ratio: 0.00465, Grade: A\",\"StationNumber: 95MTB04, Year: 1995, PEL ratio: 0.008, Grade: B\",\"StationNumber: 95MTB06, Year: 1995, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 95MTB07, Year: 1995, PEL ratio: 0.12807, Grade: D\",\"StationNumber: 95MTB08, Year: 1995, PEL ratio: 0.00916, Grade: B\",\"StationNumber: 95MTB10, Year: 1995, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 95MTB15, Year: 1995, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 95MTB16, Year: 1995, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 95MTB17, Year: 1995, PEL ratio: 0.01668, Grade: B\",\"StationNumber: 95MTB18, Year: 1995, PEL ratio: 0.03443, Grade: C\",\"StationNumber: 95MTB19, Year: 1995, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 95MTB21, Year: 1995, PEL ratio: 0.02294, Grade: C\",\"StationNumber: 95MTB24, Year: 1995, PEL ratio: 0.00408, Grade: A\",\"StationNumber: 95MTB25, Year: 1995, PEL ratio: 0.0049, Grade: A\",\"StationNumber: 95MTB26, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95MTB29, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB30, Year: 1995, PEL ratio: 0.00748, Grade: A\",\"StationNumber: 95MTB31, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB32, Year: 1995, PEL ratio: 0.00689, Grade: A\",\"StationNumber: 95MTB34, Year: 1995, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 95MTB35, Year: 1995, PEL ratio: 0.00817, Grade: B\",\"StationNumber: 95OTB02, Year: 1995, PEL ratio: 0.01655, Grade: B\",\"StationNumber: 95OTB03, Year: 1995, PEL ratio: 0.00572, Grade: A\",\"StationNumber: 95OTB05, Year: 1995, PEL ratio: 0.02432, Grade: C\",\"StationNumber: 95OTB06, Year: 1995, PEL ratio: 0.00961, Grade: B\",\"StationNumber: 95OTB07, Year: 1995, PEL ratio: 0.00772, Grade: B\",\"StationNumber: 95OTB08, Year: 1995, PEL ratio: 0.00541, Grade: A\",\"StationNumber: 95OTB11, Year: 1995, PEL ratio: 0.01187, Grade: B\",\"StationNumber: 95OTB12, Year: 1995, PEL ratio: 0.01178, Grade: B\",\"StationNumber: 95OTB13, Year: 1995, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 95OTB14, Year: 1995, PEL ratio: 0.00796, Grade: B\",\"StationNumber: 95OTB15, Year: 1995, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 95OTB17, Year: 1995, PEL ratio: 0.00668, Grade: A\",\"StationNumber: 95OTB18, Year: 1995, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 95OTB19, Year: 1995, PEL ratio: 0.04972, Grade: C\",\"StationNumber: 95OTB20, Year: 1995, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 95OTB22, Year: 1995, PEL ratio: 0.01855, Grade: B\",\"StationNumber: 95OTB23, Year: 1995, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 95OTB24, Year: 1995, PEL ratio: 0.00477, Grade: A\",\"StationNumber: 95OTB25, Year: 1995, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 95OTB26, Year: 1995, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 95OTB27, Year: 1995, PEL ratio: 0.0039, Grade: A\",\"StationNumber: 95OTB29, Year: 1995, PEL ratio: 0.00722, Grade: A\",\"StationNumber: 95OTB30, Year: 1995, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 95TCB22, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB37, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB38, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB39, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB40, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB41, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB42, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 96BCB02, Year: 1996, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 96BCB04, Year: 1996, PEL ratio: 0.21792, Grade: D\",\"StationNumber: 96BCB07, Year: 1996, PEL ratio: 0.04432, Grade: C\",\"StationNumber: 96BCB08, Year: 1996, PEL ratio: 0.02026, Grade: B\",\"StationNumber: 96BCB12, Year: 1996, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 96BCB13, Year: 1996, PEL ratio: 0.31368, Grade: F\",\"StationNumber: 96BCB15, Year: 1996, PEL ratio: 0.18237, Grade: D\",\"StationNumber: 96BCB19, Year: 1996, PEL ratio: 0.01925, Grade: B\",\"StationNumber: 96BCB24, Year: 1996, PEL ratio: 0.03429, Grade: C\",\"StationNumber: 96BCB26, Year: 1996, PEL ratio: 0.01638, Grade: B\",\"StationNumber: 96BCB27, Year: 1996, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 96BCB30, Year: 1996, PEL ratio: 0.01775, Grade: B\",\"StationNumber: 96BCB31, Year: 1996, PEL ratio: 0.26305, Grade: D\",\"StationNumber: 96BCB34, Year: 1996, PEL ratio: 0.01272, Grade: B\",\"StationNumber: 96BCB36, Year: 1996, PEL ratio: 0.00987, Grade: B\",\"StationNumber: 96BCB39, Year: 1996, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 96BCB40, Year: 1996, PEL ratio: 0.01665, Grade: B\",\"StationNumber: 96BCB41, Year: 1996, PEL ratio: 0.00563, Grade: A\",\"StationNumber: 96BCB44, Year: 1996, PEL ratio: 0.02696, Grade: C\",\"StationNumber: 96BCB46, Year: 1996, PEL ratio: 0.00262, Grade: A\",\"StationNumber: 96BCB49, Year: 1996, PEL ratio: 0.00173, Grade: A\",\"StationNumber: 96HB13, Year: 1996, PEL ratio: 0.28424, Grade: F\",\"StationNumber: 96HB16, Year: 1996, PEL ratio: 0.01524, Grade: B\",\"StationNumber: 96HB18, Year: 1996, PEL ratio: 0.52049, Grade: F\",\"StationNumber: 96HB20, Year: 1996, PEL ratio: 0.14092, Grade: D\",\"StationNumber: 96HB22, Year: 1996, PEL ratio: 0.16443, Grade: D\",\"StationNumber: 96HB23, Year: 1996, PEL ratio: 0.07935, Grade: C\",\"StationNumber: 96HB24, Year: 1996, PEL ratio: 0.00728, Grade: A\",\"StationNumber: 96HB26, Year: 1996, PEL ratio: 0.00701, Grade: A\",\"StationNumber: 96HB27, Year: 1996, PEL ratio: 0.05771, Grade: C\",\"StationNumber: 96HB29, Year: 1996, PEL ratio: 0.01207, Grade: B\",\"StationNumber: 96HB36, Year: 1996, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 96HB37, Year: 1996, PEL ratio: 0.03752, Grade: C\",\"StationNumber: 96HB38, Year: 1996, PEL ratio: 0.10492, Grade: D\",\"StationNumber: 96HB39, Year: 1996, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 96HB42, Year: 1996, PEL ratio: 0.05108, Grade: C\",\"StationNumber: 96HB43, Year: 1996, PEL ratio: 0.08509, Grade: C\",\"StationNumber: 96HB44, Year: 1996, PEL ratio: 0.02579, Grade: C\",\"StationNumber: 96HB45, Year: 1996, PEL ratio: 0.00593, Grade: A\",\"StationNumber: 96HB46, Year: 1996, PEL ratio: 11.28998, Grade: F\",\"StationNumber: 96HB47, Year: 1996, PEL ratio: 0.01428, Grade: B\",\"StationNumber: 96HB48, Year: 1996, PEL ratio: 0.1139, Grade: D\",\"StationNumber: 96HB50, Year: 1996, PEL ratio: 0.02802, Grade: C\",\"StationNumber: 96HB51, Year: 1996, PEL ratio: 0.00781, Grade: B\",\"StationNumber: 96HB52, Year: 1996, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 96HB53, Year: 1996, PEL ratio: 0.00529, Grade: A\",\"StationNumber: 96HB54, Year: 1996, PEL ratio: 0.00646, Grade: A\",\"StationNumber: 96HB56, Year: 1996, PEL ratio: 0.15168, Grade: D\",\"StationNumber: 96LTB01, Year: 1996, PEL ratio: 0.07215, Grade: C\",\"StationNumber: 96LTB02, Year: 1996, PEL ratio: 0.01176, Grade: B\",\"StationNumber: 96LTB03, Year: 1996, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 96LTB04, Year: 1996, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 96LTB05, Year: 1996, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 96LTB06, Year: 1996, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 96LTB07, Year: 1996, PEL ratio: 0.01085, Grade: B\",\"StationNumber: 96LTB08, Year: 1996, PEL ratio: 0.00503, Grade: A\",\"StationNumber: 96LTB09, Year: 1996, PEL ratio: 0.00497, Grade: A\",\"StationNumber: 96LTB10, Year: 1996, PEL ratio: 0.01922, Grade: B\",\"StationNumber: 96LTB11, Year: 1996, PEL ratio: 0.02443, Grade: C\",\"StationNumber: 96LTB12, Year: 1996, PEL ratio: 0.01365, Grade: B\",\"StationNumber: 96LTB13, Year: 1996, PEL ratio: 0.05548, Grade: C\",\"StationNumber: 96LTB15, Year: 1996, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 96LTB17, Year: 1996, PEL ratio: 0.01376, Grade: B\",\"StationNumber: 96LTB18, Year: 1996, PEL ratio: 0.01093, Grade: B\",\"StationNumber: 96LTB19, Year: 1996, PEL ratio: 0.00533, Grade: A\",\"StationNumber: 96LTB20, Year: 1996, PEL ratio: 0.00274, Grade: A\",\"StationNumber: 96LTB21, Year: 1996, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 96LTB23, Year: 1996, PEL ratio: 0.00883, Grade: B\",\"StationNumber: 96LTB24, Year: 1996, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 96LTB25, Year: 1996, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 96LTB26, Year: 1996, PEL ratio: 0.00167, Grade: A\",\"StationNumber: 96LTB27, Year: 1996, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 96MR20, Year: 1996, PEL ratio: 0.0375, Grade: C\",\"StationNumber: 96MR21, Year: 1996, PEL ratio: 0.01873, Grade: B\",\"StationNumber: 96MR23, Year: 1996, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 96MR24, Year: 1996, PEL ratio: 0.04434, Grade: C\",\"StationNumber: 96MR25, Year: 1996, PEL ratio: 0.0361, Grade: C\",\"StationNumber: 96MR26, Year: 1996, PEL ratio: 0.02689, Grade: C\",\"StationNumber: 96MR27, Year: 1996, PEL ratio: 0.02357, Grade: C\",\"StationNumber: 96MR28, Year: 1996, PEL ratio: 0.00874, Grade: B\",\"StationNumber: 96MR29, Year: 1996, PEL ratio: 0.04221, Grade: C\",\"StationNumber: 96MR30, Year: 1996, PEL ratio: 0.03112, Grade: C\",\"StationNumber: 96MR31, Year: 1996, PEL ratio: 0.01702, Grade: B\",\"StationNumber: 96MR32, Year: 1996, PEL ratio: 0.0686, Grade: C\",\"StationNumber: 96MR43, Year: 1996, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 96MTB04, Year: 1996, PEL ratio: 0.00399, Grade: A\",\"StationNumber: 96MTB05, Year: 1996, PEL ratio: 0.00738, Grade: A\",\"StationNumber: 96MTB07, Year: 1996, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 96MTB09, Year: 1996, PEL ratio: 0.04135, Grade: C\",\"StationNumber: 96MTB10, Year: 1996, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 96MTB11, Year: 1996, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 96MTB12, Year: 1996, PEL ratio: 0.01296, Grade: B\",\"StationNumber: 96MTB13, Year: 1996, PEL ratio: 0.00054, Grade: A\",\"StationNumber: 96MTB14, Year: 1996, PEL ratio: 0.21228, Grade: D\",\"StationNumber: 96MTB15, Year: 1996, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 96MTB16, Year: 1996, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 96MTB17, Year: 1996, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 96MTB18, Year: 1996, PEL ratio: 0.00511, Grade: A\",\"StationNumber: 96MTB19, Year: 1996, PEL ratio: 0.00327, Grade: A\",\"StationNumber: 96MTB20, Year: 1996, PEL ratio: 0.07168, Grade: C\",\"StationNumber: 96MTB23, Year: 1996, PEL ratio: 0.00289, Grade: A\",\"StationNumber: 96MTB24, Year: 1996, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 96MTB25, Year: 1996, PEL ratio: 0.00302, Grade: A\",\"StationNumber: 96MTB26, Year: 1996, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 96MTB30, Year: 1996, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 96MTB31, Year: 1996, PEL ratio: 0.01583, Grade: B\",\"StationNumber: 96MTB32, Year: 1996, PEL ratio: 0.02658, Grade: C\",\"StationNumber: 96MTB34, Year: 1996, PEL ratio: 0.01453, Grade: B\",\"StationNumber: 96MTB35, Year: 1996, PEL ratio: 0.00178, Grade: A\",\"StationNumber: 96OTB07, Year: 1996, PEL ratio: 0.00525, Grade: A\",\"StationNumber: 96OTB11, Year: 1996, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 96OTB12, Year: 1996, PEL ratio: 0.01689, Grade: B\",\"StationNumber: 96OTB13, Year: 1996, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 96OTB14, Year: 1996, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 96OTB17, Year: 1996, PEL ratio: 0.00886, Grade: B\",\"StationNumber: 96OTB18, Year: 1996, PEL ratio: 0.01434, Grade: B\",\"StationNumber: 96OTB19, Year: 1996, PEL ratio: 0.01141, Grade: B\",\"StationNumber: 96OTB20, Year: 1996, PEL ratio: 0.09948, Grade: D\",\"StationNumber: 96OTB23, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB24, Year: 1996, PEL ratio: 0.00798, Grade: B\",\"StationNumber: 96OTB26, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB27, Year: 1996, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 96OTB29, Year: 1996, PEL ratio: 0.00299, Grade: A\",\"StationNumber: 96OTB30, Year: 1996, PEL ratio: 0.01598, Grade: B\",\"StationNumber: 96TCB22, Year: 1996, PEL ratio: 0.03815, Grade: C\",\"StationNumber: 96TCB36, Year: 1996, PEL ratio: 0.0182, Grade: B\",\"StationNumber: 96TCB37, Year: 1996, PEL ratio: 0.06747, Grade: C\",\"StationNumber: 96TCB38, Year: 1996, PEL ratio: 0.04811, Grade: C\",\"StationNumber: 96TCB39, Year: 1996, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 96TCB40, Year: 1996, PEL ratio: 0.02086, Grade: C\",\"StationNumber: 96TCB41, Year: 1996, PEL ratio: 0.02591, Grade: C\",\"StationNumber: 96TCB42, Year: 1996, PEL ratio: 0.01431, Grade: B\",\"StationNumber: 97BCB02, Year: 1997, PEL ratio: 0.02654, Grade: C\",\"StationNumber: 97BCB08, Year: 1997, PEL ratio: 0.06243, Grade: C\",\"StationNumber: 97BCB10, Year: 1997, PEL ratio: 0.07472, Grade: C\",\"StationNumber: 97BCB13, Year: 1997, PEL ratio: 0.02112, Grade: C\",\"StationNumber: 97BCB17, Year: 1997, PEL ratio: 0.06466, Grade: C\",\"StationNumber: 97BCB18, Year: 1997, PEL ratio: 0.03013, Grade: C\",\"StationNumber: 97BCB27, Year: 1997, PEL ratio: 0.25161, Grade: D\",\"StationNumber: 97BCB30, Year: 1997, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 97BCB31, Year: 1997, PEL ratio: 0.00973, Grade: B\",\"StationNumber: 97BCB36, Year: 1997, PEL ratio: 0.01281, Grade: B\",\"StationNumber: 97BCB37, Year: 1997, PEL ratio: 0.01861, Grade: B\",\"StationNumber: 97BCB40, Year: 1997, PEL ratio: 0.03448, Grade: C\",\"StationNumber: 97BCB46, Year: 1997, PEL ratio: 0.01276, Grade: B\",\"StationNumber: 97BCB50, Year: 1997, PEL ratio: 0.0087, Grade: B\",\"StationNumber: 97BCB57-1, Year: 1997, PEL ratio: 0.12797, Grade: D\",\"StationNumber: 97BCB58-1, Year: 1997, PEL ratio: 0.29199, Grade: F\",\"StationNumber: 97BCB58-2, Year: 1997, PEL ratio: 0.04357, Grade: C\",\"StationNumber: 97BCB59-1, Year: 1997, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 97BCB59-2, Year: 1997, PEL ratio: 0.02798, Grade: C\",\"StationNumber: 97BCB60-2, Year: 1997, PEL ratio: 0.00469, Grade: A\",\"StationNumber: 97BCB60-4, Year: 1997, PEL ratio: 0.00523, Grade: A\",\"StationNumber: 97HB10, Year: 1997, PEL ratio: 1.45751, Grade: F\",\"StationNumber: 97HB13, Year: 1997, PEL ratio: 0.20993, Grade: D\",\"StationNumber: 97HB18, Year: 1997, PEL ratio: 0.0395, Grade: C\",\"StationNumber: 97HB22, Year: 1997, PEL ratio: 0.23185, Grade: D\",\"StationNumber: 97HB23, Year: 1997, PEL ratio: 0.01374, Grade: B\",\"StationNumber: 97HB24, Year: 1997, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 97HB27, Year: 1997, PEL ratio: 0.00494, Grade: A\",\"StationNumber: 97HB29, Year: 1997, PEL ratio: 0.18186, Grade: D\",\"StationNumber: 97HB36, Year: 1997, PEL ratio: 0.00827, Grade: B\",\"StationNumber: 97HB37, Year: 1997, PEL ratio: 0.06009, Grade: C\",\"StationNumber: 97HB38, Year: 1997, PEL ratio: 0.04075, Grade: C\",\"StationNumber: 97HB39, Year: 1997, PEL ratio: 0.08084, Grade: C\",\"StationNumber: 97HB43, Year: 1997, PEL ratio: 0.0066, Grade: A\",\"StationNumber: 97HB44, Year: 1997, PEL ratio: 0.01905, Grade: B\",\"StationNumber: 97HB45, Year: 1997, PEL ratio: 0.03887, Grade: C\",\"StationNumber: 97HB46, Year: 1997, PEL ratio: 0.00974, Grade: B\",\"StationNumber: 97HB48, Year: 1997, PEL ratio: 0.00871, Grade: B\",\"StationNumber: 97HB50, Year: 1997, PEL ratio: 0.08114, Grade: C\",\"StationNumber: 97HB53, Year: 1997, PEL ratio: 0.00914, Grade: B\",\"StationNumber: 97HB54, Year: 1997, PEL ratio: 0.01088, Grade: B\",\"StationNumber: 97HB55, Year: 1997, PEL ratio: 0.02004, Grade: B\",\"StationNumber: 97HB56, Year: 1997, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 97LTB01, Year: 1997, PEL ratio: 0.0117, Grade: B\",\"StationNumber: 97LTB02, Year: 1997, PEL ratio: 0.01631, Grade: B\",\"StationNumber: 97LTB03, Year: 1997, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 97LTB06, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97LTB07, Year: 1997, PEL ratio: 0.00826, Grade: B\",\"StationNumber: 97LTB09, Year: 1997, PEL ratio: 0.01935, Grade: B\",\"StationNumber: 97LTB10, Year: 1997, PEL ratio: 0.02574, Grade: C\",\"StationNumber: 97LTB11, Year: 1997, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 97LTB12, Year: 1997, PEL ratio: 0.01318, Grade: B\",\"StationNumber: 97LTB13, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97LTB15, Year: 1997, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 97LTB17, Year: 1997, PEL ratio: 0.00975, Grade: B\",\"StationNumber: 97LTB18, Year: 1997, PEL ratio: 0.00942, Grade: B\",\"StationNumber: 97LTB19, Year: 1997, PEL ratio: 0.00972, Grade: B\",\"StationNumber: 97LTB20, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97LTB21, Year: 1997, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 97LTB23, Year: 1997, PEL ratio: 0.01146, Grade: B\",\"StationNumber: 97LTB24, Year: 1997, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 97LTB25, Year: 1997, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 97LTB26, Year: 1997, PEL ratio: 0.00218, Grade: A\",\"StationNumber: 97LTB28, Year: 1997, PEL ratio: 0.00444, Grade: A\",\"StationNumber: 97MR09, Year: 1997, PEL ratio: 0.01198, Grade: B\",\"StationNumber: 97MR10, Year: 1997, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 97MR11, Year: 1997, PEL ratio: 0.04743, Grade: C\",\"StationNumber: 97MR12, Year: 1997, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 97MR13, Year: 1997, PEL ratio: 0.0476, Grade: C\",\"StationNumber: 97MR14, Year: 1997, PEL ratio: 0.08134, Grade: C\",\"StationNumber: 97MR15, Year: 1997, PEL ratio: 0.02453, Grade: C\",\"StationNumber: 97MR16, Year: 1997, PEL ratio: 0.05074, Grade: C\",\"StationNumber: 97MR17, Year: 1997, PEL ratio: 0.02537, Grade: C\",\"StationNumber: 97MR18, Year: 1997, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 97MR19, Year: 1997, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 97MR20, Year: 1997, PEL ratio: 0.05581, Grade: C\",\"StationNumber: 97MR21, Year: 1997, PEL ratio: 0.04083, Grade: C\",\"StationNumber: 97MTB02, Year: 1997, PEL ratio: 0.02552, Grade: C\",\"StationNumber: 97MTB03, Year: 1997, PEL ratio: 0.00549, Grade: A\",\"StationNumber: 97MTB04, Year: 1997, PEL ratio: 0.0071, Grade: A\",\"StationNumber: 97MTB05, Year: 1997, PEL ratio: 0.00589, Grade: A\",\"StationNumber: 97MTB07, Year: 1997, PEL ratio: 0.01701, Grade: B\",\"StationNumber: 97MTB09, Year: 1997, PEL ratio: 0.01016, Grade: B\",\"StationNumber: 97MTB10, Year: 1997, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 97MTB12, Year: 1997, PEL ratio: 0.01224, Grade: B\",\"StationNumber: 97MTB14, Year: 1997, PEL ratio: 0.04718, Grade: C\",\"StationNumber: 97MTB15, Year: 1997, PEL ratio: 0.00923, Grade: B\",\"StationNumber: 97MTB16, Year: 1997, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 97MTB17, Year: 1997, PEL ratio: 0.01049, Grade: B\",\"StationNumber: 97MTB18, Year: 1997, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 97MTB19, Year: 1997, PEL ratio: 0.00548, Grade: A\",\"StationNumber: 97MTB23, Year: 1997, PEL ratio: 0.01245, Grade: B\",\"StationNumber: 97MTB24, Year: 1997, PEL ratio: 0.01036, Grade: B\",\"StationNumber: 97MTB25, Year: 1997, PEL ratio: 0.0052, Grade: A\",\"StationNumber: 97MTB26, Year: 1997, PEL ratio: 0.00284, Grade: A\",\"StationNumber: 97MTB30, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97MTB31, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97MTB32, Year: 1997, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 97MTB35, Year: 1997, PEL ratio: 0.00417, Grade: A\",\"StationNumber: 97OTB03, Year: 1997, PEL ratio: 0.08428, Grade: C\",\"StationNumber: 97OTB06, Year: 1997, PEL ratio: 0.00508, Grade: A\",\"StationNumber: 97OTB07, Year: 1997, PEL ratio: 0.04147, Grade: C\",\"StationNumber: 97OTB11, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97OTB12, Year: 1997, PEL ratio: 0.00901, Grade: B\",\"StationNumber: 97OTB13, Year: 1997, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 97OTB17, Year: 1997, PEL ratio: 0.02135, Grade: C\",\"StationNumber: 97OTB18, Year: 1997, PEL ratio: 0.01639, Grade: B\",\"StationNumber: 97OTB19, Year: 1997, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 97OTB20, Year: 1997, PEL ratio: 0.0108, Grade: B\",\"StationNumber: 97OTB22, Year: 1997, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 97OTB23, Year: 1997, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 97OTB24, Year: 1997, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 97OTB26, Year: 1997, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 97OTB27, Year: 1997, PEL ratio: 0.0027, Grade: A\",\"StationNumber: 97OTB29, Year: 1997, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 97TCB01, Year: 1997, PEL ratio: 0.03736, Grade: C\",\"StationNumber: 97TCB02, Year: 1997, PEL ratio: 0.05752, Grade: C\",\"StationNumber: 97TCB03, Year: 1997, PEL ratio: 0.07413, Grade: C\",\"StationNumber: 97TCB04, Year: 1997, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 97TCB05, Year: 1997, PEL ratio: 0.03402, Grade: C\",\"StationNumber: 97TCB06, Year: 1997, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 97TCB07, Year: 1997, PEL ratio: 0.06132, Grade: C\",\"StationNumber: 97TCB08, Year: 1997, PEL ratio: 0.0461, Grade: C\",\"StationNumber: 98BCB06, Year: 1998, PEL ratio: 0.00538, Grade: A\",\"StationNumber: 98BCB09, Year: 1998, PEL ratio: 0.00305, Grade: A\",\"StationNumber: 98BCB11, Year: 1998, PEL ratio: 0.00393, Grade: A\",\"StationNumber: 98BCB12, Year: 1998, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 98BCB15, Year: 1998, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 98BCB17, Year: 1998, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 98BCB21, Year: 1998, PEL ratio: 0.0041, Grade: A\",\"StationNumber: 98BCB27, Year: 1998, PEL ratio: 0.01015, Grade: B\",\"StationNumber: 98BCB28, Year: 1998, PEL ratio: 0.0098, Grade: B\",\"StationNumber: 98BCB32, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98BCB38, Year: 1998, PEL ratio: 0.00578, Grade: A\",\"StationNumber: 98BCB40, Year: 1998, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 98BCB43, Year: 1998, PEL ratio: 0.00199, Grade: A\",\"StationNumber: 98BCB46, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98BCB57/1, Year: 1998, PEL ratio: 0.06999, Grade: C\",\"StationNumber: 98BCB58/1, Year: 1998, PEL ratio: 0.1367, Grade: D\",\"StationNumber: 98BCB58/2, Year: 1998, PEL ratio: 0.02526, Grade: C\",\"StationNumber: 98BCB59/1, Year: 1998, PEL ratio: 0.00363, Grade: A\",\"StationNumber: 98BCB59/2, Year: 1998, PEL ratio: 0.02915, Grade: C\",\"StationNumber: 98BCB60/2, Year: 1998, PEL ratio: 0.00939, Grade: B\",\"StationNumber: 98BCB60/4, Year: 1998, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 98HB003, Year: 1998, PEL ratio: 0.0024, Grade: A\",\"StationNumber: 98HB006, Year: 1998, PEL ratio: 0.97324, Grade: F\",\"StationNumber: 98HB014, Year: 1998, PEL ratio: 0.0317, Grade: C\",\"StationNumber: 98HB016, Year: 1998, PEL ratio: 0.11511, Grade: D\",\"StationNumber: 98HB017, Year: 1998, PEL ratio: 0.00283, Grade: A\",\"StationNumber: 98HB024, Year: 1998, PEL ratio: 0.03375, Grade: C\",\"StationNumber: 98HB030, Year: 1998, PEL ratio: 0.00478, Grade: A\",\"StationNumber: 98HB049, Year: 1998, PEL ratio: 0.00685, Grade: A\",\"StationNumber: 98HB052, Year: 1998, PEL ratio: 0.04381, Grade: C\",\"StationNumber: 98HB056, Year: 1998, PEL ratio: 0.00367, Grade: A\",\"StationNumber: 98HB059, Year: 1998, PEL ratio: 0.00786, Grade: B\",\"StationNumber: 98HB069, Year: 1998, PEL ratio: 0.01266, Grade: B\",\"StationNumber: 98HB080, Year: 1998, PEL ratio: 0.10159, Grade: D\",\"StationNumber: 98HB089, Year: 1998, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 98HB130, Year: 1998, PEL ratio: 0.00708, Grade: A\",\"StationNumber: 98HB153, Year: 1998, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 98HB171, Year: 1998, PEL ratio: 0.07363, Grade: C\",\"StationNumber: 98HB180, Year: 1998, PEL ratio: 0.02965, Grade: C\",\"StationNumber: 98HB224, Year: 1998, PEL ratio: 0.0387, Grade: C\",\"StationNumber: 98HB237, Year: 1998, PEL ratio: 0.00906, Grade: B\",\"StationNumber: 98HB245, Year: 1998, PEL ratio: 0.02123, Grade: C\",\"StationNumber: 98HB252, Year: 1998, PEL ratio: 0.04475, Grade: C\",\"StationNumber: 98HB280, Year: 1998, PEL ratio: 0.01676, Grade: B\",\"StationNumber: 98HB789, Year: 1998, PEL ratio: 0.07519, Grade: C\",\"StationNumber: 98HBDIcanal, Year: 1998, PEL ratio: 0.0396, Grade: C\",\"StationNumber: 98HBspark, Year: 1998, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 98LTB0014, Year: 1998, PEL ratio: 0.01019, Grade: B\",\"StationNumber: 98LTB0025, Year: 1998, PEL ratio: 0.00349, Grade: A\",\"StationNumber: 98LTB0049, Year: 1998, PEL ratio: 0.0015, Grade: A\",\"StationNumber: 98LTB0095, Year: 1998, PEL ratio: 0.00272, Grade: A\",\"StationNumber: 98LTB0123, Year: 1998, PEL ratio: 0.0128, Grade: B\",\"StationNumber: 98LTB0144, Year: 1998, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 98LTB0151, Year: 1998, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 98LTB0168, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98LTB0183, Year: 1998, PEL ratio: 0.00534, Grade: A\",\"StationNumber: 98LTB0223, Year: 1998, PEL ratio: 0.00257, Grade: A\",\"StationNumber: 98LTB0244, Year: 1998, PEL ratio: 0.00145, Grade: A\",\"StationNumber: 98LTB0273, Year: 1998, PEL ratio: 0.00217, Grade: A\",\"StationNumber: 98LTB0307, Year: 1998, PEL ratio: 0.00156, Grade: A\",\"StationNumber: 98LTB0364, Year: 1998, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 98LTB0393, Year: 1998, PEL ratio: 0.00144, Grade: A\",\"StationNumber: 98LTB0762, Year: 1998, PEL ratio: 0.00278, Grade: A\",\"StationNumber: 98LTB1057, Year: 1998, PEL ratio: 0.00277, Grade: A\",\"StationNumber: 98MR09, Year: 1998, PEL ratio: 0.00264, Grade: A\",\"StationNumber: 98MR10, Year: 1998, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 98MR11, Year: 1998, PEL ratio: 0.02354, Grade: C\",\"StationNumber: 98MR12, Year: 1998, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 98MR13, Year: 1998, PEL ratio: 0.04647, Grade: C\",\"StationNumber: 98MR14, Year: 1998, PEL ratio: 0.01126, Grade: B\",\"StationNumber: 98MR15, Year: 1998, PEL ratio: 0.01005, Grade: B\",\"StationNumber: 98MR16, Year: 1998, PEL ratio: 0.0221, Grade: C\",\"StationNumber: 98MR17, Year: 1998, PEL ratio: 0.01136, Grade: B\",\"StationNumber: 98MR18, Year: 1998, PEL ratio: 0.00778, Grade: B\",\"StationNumber: 98MR19, Year: 1998, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 98MR20, Year: 1998, PEL ratio: 0.00821, Grade: B\",\"StationNumber: 98MR21, Year: 1998, PEL ratio: 0.18896, Grade: D\",\"StationNumber: 98MTB0032, Year: 1998, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 98MTB0035, Year: 1998, PEL ratio: 0.02315, Grade: C\",\"StationNumber: 98MTB0052, Year: 1998, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 98MTB0067, Year: 1998, PEL ratio: 0.00681, Grade: A\",\"StationNumber: 98MTB0090, Year: 1998, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 98MTB0103, Year: 1998, PEL ratio: 0.00342, Grade: A\",\"StationNumber: 98MTB0133, Year: 1998, PEL ratio: 0.00293, Grade: A\",\"StationNumber: 98MTB0187, Year: 1998, PEL ratio: 0.0175, Grade: B\",\"StationNumber: 98MTB0191, Year: 1998, PEL ratio: 0.29254, Grade: F\",\"StationNumber: 98MTB0208, Year: 1998, PEL ratio: 0.00527, Grade: A\",\"StationNumber: 98MTB0270, Year: 1998, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 98MTB0275, Year: 1998, PEL ratio: 0.00228, Grade: A\",\"StationNumber: 98MTB0283, Year: 1998, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 98MTB0322, Year: 1998, PEL ratio: 0.00756, Grade: B\",\"StationNumber: 98MTB0331, Year: 1998, PEL ratio: 0.00226, Grade: A\",\"StationNumber: 98MTB0416, Year: 1998, PEL ratio: 0.01759, Grade: B\",\"StationNumber: 98MTB0460, Year: 1998, PEL ratio: 0.00109, Grade: A\",\"StationNumber: 98MTB0688, Year: 1998, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 98MTB0694, Year: 1998, PEL ratio: 0.00183, Grade: A\",\"StationNumber: 98MTB1036, Year: 1998, PEL ratio: 0.00193, Grade: A\",\"StationNumber: 98OTB0036, Year: 1998, PEL ratio: 0.0377, Grade: C\",\"StationNumber: 98OTB0039, Year: 1998, PEL ratio: 0.01561, Grade: B\",\"StationNumber: 98OTB0048, Year: 1998, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 98OTB0056, Year: 1998, PEL ratio: 0.01204, Grade: B\",\"StationNumber: 98OTB0125, Year: 1998, PEL ratio: 0.00279, Grade: A\",\"StationNumber: 98OTB0177, Year: 1998, PEL ratio: 0.00429, Grade: A\",\"StationNumber: 98OTB0185, Year: 1998, PEL ratio: 0.00276, Grade: A\",\"StationNumber: 98OTB0199, Year: 1998, PEL ratio: 0.0051, Grade: A\",\"StationNumber: 98OTB0232, Year: 1998, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 98OTB0239, Year: 1998, PEL ratio: 0.00934, Grade: B\",\"StationNumber: 98OTB0274, Year: 1998, PEL ratio: 0.00653, Grade: A\",\"StationNumber: 98OTB0425, Year: 1998, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 98OTB0596, Year: 1998, PEL ratio: 0.13969, Grade: D\",\"StationNumber: 98OTB0721, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98OTB1140, Year: 1998, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 98OTB1227, Year: 1998, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 98TCB01, Year: 1998, PEL ratio: 0.00905, Grade: B\",\"StationNumber: 98TCB02, Year: 1998, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 98TCB04, Year: 1998, PEL ratio: 0.0067, Grade: A\",\"StationNumber: 98TCB05, Year: 1998, PEL ratio: 0.00686, Grade: A\",\"StationNumber: 98TCB06, Year: 1998, PEL ratio: 0.00741, Grade: A\",\"StationNumber: 98TCB07, Year: 1998, PEL ratio: 0.0084, Grade: B\",\"StationNumber: 98TCB08, Year: 1998, PEL ratio: 0.02781, Grade: C\",\"StationNumber: 99BCB2025, Year: 1999, PEL ratio: 0.005, Grade: A\",\"StationNumber: 99BCB2041, Year: 1999, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 99BCB2063, Year: 1999, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 99BCB2069, Year: 1999, PEL ratio: 0.00888, Grade: B\",\"StationNumber: 99BCB2070, Year: 1999, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 99BCB2086, Year: 1999, PEL ratio: 0.00471, Grade: A\",\"StationNumber: 99BCB2094, Year: 1999, PEL ratio: 0.02788, Grade: C\",\"StationNumber: 99BCB2115, Year: 1999, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 99BCB2132, Year: 1999, PEL ratio: 0.00326, Grade: A\",\"StationNumber: 99BCB2295, Year: 1999, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 99BCB2358, Year: 1999, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 99BCB2423, Year: 1999, PEL ratio: 0.00676, Grade: A\",\"StationNumber: 99BCB2514, Year: 1999, PEL ratio: 0.00801, Grade: B\",\"StationNumber: 99BCB2585, Year: 1999, PEL ratio: 0.00657, Grade: A\",\"StationNumber: 99BCB57/1, Year: 1999, PEL ratio: 0.05417, Grade: C\",\"StationNumber: 99BCB58/1, Year: 1999, PEL ratio: 0.09826, Grade: D\",\"StationNumber: 99BCB58/2, Year: 1999, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 99BCB59/1, Year: 1999, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 99BCB59/2, Year: 1999, PEL ratio: 0.02713, Grade: C\",\"StationNumber: 99BCB60/2, Year: 1999, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 99BCB60/4, Year: 1999, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 99HB2001, Year: 1999, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 99HB2012, Year: 1999, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 99HB2013, Year: 1999, PEL ratio: 0.01091, Grade: B\",\"StationNumber: 99HB2019, Year: 1999, PEL ratio: 0.01342, Grade: B\",\"StationNumber: 99HB2040, Year: 1999, PEL ratio: 0.00861, Grade: B\",\"StationNumber: 99HB2041, Year: 1999, PEL ratio: 0.00984, Grade: B\",\"StationNumber: 99HB2043, Year: 1999, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 99HB2044, Year: 1999, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 99HB2051, Year: 1999, PEL ratio: 0.04843, Grade: C\",\"StationNumber: 99HB2055, Year: 1999, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 99HB2058, Year: 1999, PEL ratio: 0.1295, Grade: D\",\"StationNumber: 99HB2061, Year: 1999, PEL ratio: 0.66795, Grade: F\",\"StationNumber: 99HB2085, Year: 1999, PEL ratio: 0.11485, Grade: D\",\"StationNumber: 99HB2094, Year: 1999, PEL ratio: 0.00687, Grade: A\",\"StationNumber: 99HB2124, Year: 1999, PEL ratio: 0.08012, Grade: C\",\"StationNumber: 99HB2157, Year: 1999, PEL ratio: 0.01348, Grade: B\",\"StationNumber: 99HB2176, Year: 1999, PEL ratio: 0.07747, Grade: C\",\"StationNumber: 99HB2207, Year: 1999, PEL ratio: 0.09551, Grade: D\",\"StationNumber: 99HB2214, Year: 1999, PEL ratio: 0.00568, Grade: A\",\"StationNumber: 99HB2233, Year: 1999, PEL ratio: 0.04361, Grade: C\",\"StationNumber: 99HB2393, Year: 1999, PEL ratio: 0.01757, Grade: B\",\"StationNumber: 99HB2445, Year: 1999, PEL ratio: 0.0179, Grade: B\",\"StationNumber: 99HB2757, Year: 1999, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 99LTB2014, Year: 1999, PEL ratio: 0.00357, Grade: A\",\"StationNumber: 99LTB2021, Year: 1999, PEL ratio: 0.02082, Grade: C\",\"StationNumber: 99LTB2041, Year: 1999, PEL ratio: 0.01184, Grade: B\",\"StationNumber: 99LTB2071, Year: 1999, PEL ratio: 0.04983, Grade: C\",\"StationNumber: 99LTB2112, Year: 1999, PEL ratio: 0.01, Grade: B\",\"StationNumber: 99LTB2124, Year: 1999, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 99LTB2203, Year: 1999, PEL ratio: 0.03476, Grade: C\",\"StationNumber: 99LTB2214, Year: 1999, PEL ratio: 0.00338, Grade: A\",\"StationNumber: 99LTB2247, Year: 1999, PEL ratio: 0.00398, Grade: A\",\"StationNumber: 99LTB2267, Year: 1999, PEL ratio: 0.00762, Grade: B\",\"StationNumber: 99LTB2277, Year: 1999, PEL ratio: 0.00489, Grade: A\",\"StationNumber: 99LTB2290, Year: 1999, PEL ratio: 0.00641, Grade: A\",\"StationNumber: 99LTB2327, Year: 1999, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 99LTB2546, Year: 1999, PEL ratio: 0.00355, Grade: A\",\"StationNumber: 99LTB2617, Year: 1999, PEL ratio: 0.0074, Grade: A\",\"StationNumber: 99LTB3020, Year: 1999, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 99MR09, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99MR10, Year: 1999, PEL ratio: 0.00816, Grade: B\",\"StationNumber: 99MR11, Year: 1999, PEL ratio: 0.01449, Grade: B\",\"StationNumber: 99MR12, Year: 1999, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 99MR13, Year: 1999, PEL ratio: 0.00522, Grade: A\",\"StationNumber: 99MR14, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99MR15, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MR16, Year: 1999, PEL ratio: 0.00967, Grade: B\",\"StationNumber: 99MR17, Year: 1999, PEL ratio: 0.00407, Grade: A\",\"StationNumber: 99MR18, Year: 1999, PEL ratio: 0.00432, Grade: A\",\"StationNumber: 99MR19, Year: 1999, PEL ratio: 0.007, Grade: A\",\"StationNumber: 99MR20, Year: 1999, PEL ratio: 0.00696, Grade: A\",\"StationNumber: 99MR21, Year: 1999, PEL ratio: 0.00917, Grade: B\",\"StationNumber: 99MTB2029, Year: 1999, PEL ratio: 0.00978, Grade: B\",\"StationNumber: 99MTB2059, Year: 1999, PEL ratio: 0.00849, Grade: B\",\"StationNumber: 99MTB2060, Year: 1999, PEL ratio: 0.00498, Grade: A\",\"StationNumber: 99MTB2108, Year: 1999, PEL ratio: 0.01361, Grade: B\",\"StationNumber: 99MTB2109, Year: 1999, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 99MTB2116, Year: 1999, PEL ratio: 0.01071, Grade: B\",\"StationNumber: 99MTB2129, Year: 1999, PEL ratio: 0.00543, Grade: A\",\"StationNumber: 99MTB2149, Year: 1999, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 99MTB2165, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MTB2240, Year: 1999, PEL ratio: 0.00258, Grade: A\",\"StationNumber: 99MTB2243, Year: 1999, PEL ratio: 0.00684, Grade: A\",\"StationNumber: 99MTB2244, Year: 1999, PEL ratio: 0.00704, Grade: A\",\"StationNumber: 99MTB2253, Year: 1999, PEL ratio: 0.00506, Grade: A\",\"StationNumber: 99MTB2268, Year: 1999, PEL ratio: 0.00697, Grade: A\",\"StationNumber: 99MTB2274, Year: 1999, PEL ratio: 0.00654, Grade: A\",\"StationNumber: 99MTB2291, Year: 1999, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 99MTB2358, Year: 1999, PEL ratio: 0.02137, Grade: C\",\"StationNumber: 99MTB2385, Year: 1999, PEL ratio: 0.00448, Grade: A\",\"StationNumber: 99MTB2554, Year: 1999, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 99MTB2598, Year: 1999, PEL ratio: 0.00643, Grade: A\",\"StationNumber: 99MTB2642, Year: 1999, PEL ratio: 0.00161, Grade: A\",\"StationNumber: 99OTB2002, Year: 1999, PEL ratio: 0.00876, Grade: B\",\"StationNumber: 99OTB2005, Year: 1999, PEL ratio: 0.00294, Grade: A\",\"StationNumber: 99OTB2009, Year: 1999, PEL ratio: 0.00343, Grade: A\",\"StationNumber: 99OTB2010, Year: 1999, PEL ratio: 0.00216, Grade: A\",\"StationNumber: 99OTB2022, Year: 1999, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 99OTB2045, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99OTB2067, Year: 1999, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 99OTB2111, Year: 1999, PEL ratio: 0.00613, Grade: A\",\"StationNumber: 99OTB2121, Year: 1999, PEL ratio: 0.00637, Grade: A\",\"StationNumber: 99OTB2225, Year: 1999, PEL ratio: 0.00677, Grade: A\",\"StationNumber: 99OTB2296, Year: 1999, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 99OTB2313, Year: 1999, PEL ratio: 0.01389, Grade: B\",\"StationNumber: 99OTB2316, Year: 1999, PEL ratio: 0.02452, Grade: C\",\"StationNumber: 99OTB2331, Year: 1999, PEL ratio: 0.00962, Grade: B\",\"StationNumber: 99OTB2395, Year: 1999, PEL ratio: 0.00307, Grade: A\",\"StationNumber: 99OTB2482, Year: 1999, PEL ratio: 0.02893, Grade: C\",\"StationNumber: 99OTB2908, Year: 1999, PEL ratio: 0.00461, Grade: A\",\"StationNumber: 99OTB2994, Year: 1999, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 99OTB3046, Year: 1999, PEL ratio: 0.01179, Grade: B\",\"StationNumber: 99TCB01, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99TCB02, Year: 1999, PEL ratio: 0.00618, Grade: A\",\"StationNumber: 99TCB03, Year: 1999, PEL ratio: 0.01419, Grade: B\",\"StationNumber: 99TCB04, Year: 1999, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 99TCB05, Year: 1999, PEL ratio: 0.00868, Grade: B\",\"StationNumber: 99TCB06, Year: 1999, PEL ratio: 0.01238, Grade: B\",\"StationNumber: 99TCB07, Year: 1999, PEL ratio: 0.01057, Grade: B\",\"StationNumber: 99TCB08, Year: 1999, PEL ratio: 0.00285, Grade: A\",\"StationNumber: 00BCB4000, Year: 2000, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 00BCB4001, Year: 2000, PEL ratio: 0.03269, Grade: C\",\"StationNumber: 00BCB4004, Year: 2000, PEL ratio: 0.02038, Grade: B\",\"StationNumber: 00BCB4033, Year: 2000, PEL ratio: 0.08678, Grade: D\",\"StationNumber: 00BCB4034, Year: 2000, PEL ratio: 0.03197, Grade: C\",\"StationNumber: 00BCB4037, Year: 2000, PEL ratio: 0.02797, Grade: C\",\"StationNumber: 00BCB4038, Year: 2000, PEL ratio: 0.81297, Grade: F\",\"StationNumber: 00BCB4041, Year: 2000, PEL ratio: 0.03473, Grade: C\",\"StationNumber: 00BCB4042, Year: 2000, PEL ratio: 0.03588, Grade: C\",\"StationNumber: 00BCB4046, Year: 2000, PEL ratio: 0.03579, Grade: C\",\"StationNumber: 00BCB4079, Year: 2000, PEL ratio: 0.02888, Grade: C\",\"StationNumber: 00BCB4084, Year: 2000, PEL ratio: 0.03169, Grade: C\",\"StationNumber: 00BCB4090, Year: 2000, PEL ratio: 0.0329, Grade: C\",\"StationNumber: 00BCB4100, Year: 2000, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 00BCB4124, Year: 2000, PEL ratio: 0.0309, Grade: C\",\"StationNumber: 00BCB4165, Year: 2000, PEL ratio: 0.03378, Grade: C\",\"StationNumber: 00BCB4174, Year: 2000, PEL ratio: 0.03618, Grade: C\",\"StationNumber: 00BCB4207, Year: 2000, PEL ratio: 0.03283, Grade: C\",\"StationNumber: 00BCB4268, Year: 2000, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 00BCB4299, Year: 2000, PEL ratio: 0.04446, Grade: C\",\"StationNumber: 00BCB4312, Year: 2000, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 00BCB58/1, Year: 2000, PEL ratio: 0.18329, Grade: D\",\"StationNumber: 00BCB58/2, Year: 2000, PEL ratio: 0.04382, Grade: C\",\"StationNumber: 00BCB59/1, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00BCB59/2, Year: 2000, PEL ratio: 0.06279, Grade: C\",\"StationNumber: 00BCB60/2, Year: 2000, PEL ratio: 0.04105, Grade: C\",\"StationNumber: 00BCB60/4, Year: 2000, PEL ratio: 0.04149, Grade: C\",\"StationNumber: 00HB4002, Year: 2000, PEL ratio: 0.04724, Grade: C\",\"StationNumber: 00HB4006, Year: 2000, PEL ratio: 0.04834, Grade: C\",\"StationNumber: 00HB4019, Year: 2000, PEL ratio: 0.10805, Grade: D\",\"StationNumber: 00HB4023, Year: 2000, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 00HB4032, Year: 2000, PEL ratio: 0.04776, Grade: C\",\"StationNumber: 00HB4033, Year: 2000, PEL ratio: 0.05791, Grade: C\",\"StationNumber: 00HB4038, Year: 2000, PEL ratio: 0.04416, Grade: C\",\"StationNumber: 00HB4047, Year: 2000, PEL ratio: 0.04742, Grade: C\",\"StationNumber: 00HB4058, Year: 2000, PEL ratio: 0.01604, Grade: B\",\"StationNumber: 00HB4077, Year: 2000, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 00HB4082, Year: 2000, PEL ratio: 0.04468, Grade: C\",\"StationNumber: 00HB4083, Year: 2000, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 00HB4093, Year: 2000, PEL ratio: 0.06406, Grade: C\",\"StationNumber: 00HB4094, Year: 2000, PEL ratio: 0.06062, Grade: C\",\"StationNumber: 00HB4100, Year: 2000, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 00HB4106, Year: 2000, PEL ratio: 0.09251, Grade: D\",\"StationNumber: 00HB4144, Year: 2000, PEL ratio: 0.53451, Grade: F\",\"StationNumber: 00HB4152, Year: 2000, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 00HB4267, Year: 2000, PEL ratio: 0.06204, Grade: C\",\"StationNumber: 00HB4291, Year: 2000, PEL ratio: 0.05424, Grade: C\",\"StationNumber: 00HB4316, Year: 2000, PEL ratio: 0.05501, Grade: C\",\"StationNumber: 00HB4505, Year: 2000, PEL ratio: 0.06045, Grade: C\",\"StationNumber: 00LTB4039, Year: 2000, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 00LTB4051, Year: 2000, PEL ratio: 0.19124, Grade: D\",\"StationNumber: 00LTB4066, Year: 2000, PEL ratio: 0.05414, Grade: C\",\"StationNumber: 00LTB4117, Year: 2000, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 00LTB4151, Year: 2000, PEL ratio: 0.03939, Grade: C\",\"StationNumber: 00LTB4185, Year: 2000, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 00LTB4286, Year: 2000, PEL ratio: 0.05463, Grade: C\",\"StationNumber: 00LTB4340, Year: 2000, PEL ratio: 0.05064, Grade: C\",\"StationNumber: 00LTB4484, Year: 2000, PEL ratio: 0.0517, Grade: C\",\"StationNumber: 00LTB4487, Year: 2000, PEL ratio: 0.04958, Grade: C\",\"StationNumber: 00LTB4513, Year: 2000, PEL ratio: 0.05351, Grade: C\",\"StationNumber: 00LTB4529, Year: 2000, PEL ratio: 0.049, Grade: C\",\"StationNumber: 00LTB4536, Year: 2000, PEL ratio: 0.05145, Grade: C\",\"StationNumber: 00LTB4637, Year: 2000, PEL ratio: 0.04148, Grade: C\",\"StationNumber: 00LTB4677, Year: 2000, PEL ratio: 0.04906, Grade: C\",\"StationNumber: 00LTB4730, Year: 2000, PEL ratio: 0.04835, Grade: C\",\"StationNumber: 00LTB4749, Year: 2000, PEL ratio: 0.04495, Grade: C\",\"StationNumber: 00MR09, Year: 2000, PEL ratio: 0.04919, Grade: C\",\"StationNumber: 00MR10, Year: 2000, PEL ratio: 0.06403, Grade: C\",\"StationNumber: 00MR11, Year: 2000, PEL ratio: 0.05939, Grade: C\",\"StationNumber: 00MR12, Year: 2000, PEL ratio: 0.05823, Grade: C\",\"StationNumber: 00MR13, Year: 2000, PEL ratio: 0.06481, Grade: C\",\"StationNumber: 00MR14, Year: 2000, PEL ratio: 0.0737, Grade: C\",\"StationNumber: 00MR15, Year: 2000, PEL ratio: 0.0527, Grade: C\",\"StationNumber: 00MR16, Year: 2000, PEL ratio: 0.08249, Grade: C\",\"StationNumber: 00MR17, Year: 2000, PEL ratio: 0.08444, Grade: C\",\"StationNumber: 00MR18, Year: 2000, PEL ratio: 0.08809, Grade: D\",\"StationNumber: 00MR19, Year: 2000, PEL ratio: 0.08127, Grade: C\",\"StationNumber: 00MR20, Year: 2000, PEL ratio: 0.11393, Grade: D\",\"StationNumber: 00MR21, Year: 2000, PEL ratio: 0.07841, Grade: C\",\"StationNumber: 00MTB4030, Year: 2000, PEL ratio: 0.07289, Grade: C\",\"StationNumber: 00MTB4032, Year: 2000, PEL ratio: 0.04097, Grade: C\",\"StationNumber: 00MTB4041, Year: 2000, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 00MTB4061, Year: 2000, PEL ratio: 0.05053, Grade: C\",\"StationNumber: 00MTB4072, Year: 2000, PEL ratio: 0.04819, Grade: C\",\"StationNumber: 00MTB4086, Year: 2000, PEL ratio: 0.03955, Grade: C\",\"StationNumber: 00MTB4090, Year: 2000, PEL ratio: 0.33753, Grade: F\",\"StationNumber: 00MTB4098, Year: 2000, PEL ratio: 0.0477, Grade: C\",\"StationNumber: 00MTB4100, Year: 2000, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 00MTB4106, Year: 2000, PEL ratio: 0.04444, Grade: C\",\"StationNumber: 00MTB4159, Year: 2000, PEL ratio: 0.0458, Grade: C\",\"StationNumber: 00MTB4181, Year: 2000, PEL ratio: 0.05132, Grade: C\",\"StationNumber: 00MTB4193, Year: 2000, PEL ratio: 0.03968, Grade: C\",\"StationNumber: 00MTB4201, Year: 2000, PEL ratio: 0.05155, Grade: C\",\"StationNumber: 00MTB4249, Year: 2000, PEL ratio: 0.033, Grade: C\",\"StationNumber: 00MTB4265, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB4310, Year: 2000, PEL ratio: 0.04594, Grade: C\",\"StationNumber: 00MTB4363, Year: 2000, PEL ratio: 0.07539, Grade: C\",\"StationNumber: 00MTB4504, Year: 2000, PEL ratio: 0.04349, Grade: C\",\"StationNumber: 00MTB4584, Year: 2000, PEL ratio: 0.04498, Grade: C\",\"StationNumber: 00MTB4653, Year: 2000, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 00MTB4845, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB5125, Year: 2000, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 00OTB4011, Year: 2000, PEL ratio: 0.03964, Grade: C\",\"StationNumber: 00OTB4019, Year: 2000, PEL ratio: 0.04292, Grade: C\",\"StationNumber: 00OTB4037, Year: 2000, PEL ratio: 0.05343, Grade: C\",\"StationNumber: 00OTB4040, Year: 2000, PEL ratio: 0.04909, Grade: C\",\"StationNumber: 00OTB4044, Year: 2000, PEL ratio: 0.04244, Grade: C\",\"StationNumber: 00OTB4096, Year: 2000, PEL ratio: 0.03974, Grade: C\",\"StationNumber: 00OTB4105, Year: 2000, PEL ratio: 0.04131, Grade: C\",\"StationNumber: 00OTB4123, Year: 2000, PEL ratio: 0.06385, Grade: C\",\"StationNumber: 00OTB4132, Year: 2000, PEL ratio: 0.06645, Grade: C\",\"StationNumber: 00OTB4138, Year: 2000, PEL ratio: 0.05762, Grade: C\",\"StationNumber: 00OTB4149, Year: 2000, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 00OTB4192, Year: 2000, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 00OTB4217, Year: 2000, PEL ratio: 0.05579, Grade: C\",\"StationNumber: 00OTB4254, Year: 2000, PEL ratio: 0.0437, Grade: C\",\"StationNumber: 00OTB4278, Year: 2000, PEL ratio: 0.25534, Grade: D\",\"StationNumber: 00OTB4402, Year: 2000, PEL ratio: 0.0459, Grade: C\",\"StationNumber: 00OTB4407, Year: 2000, PEL ratio: 0.04964, Grade: C\",\"StationNumber: 00OTB4650, Year: 2000, PEL ratio: 0.04792, Grade: C\",\"StationNumber: 00OTB4946, Year: 2000, PEL ratio: 0.05067, Grade: C\",\"StationNumber: 00TCB01, Year: 2000, PEL ratio: 0.04699, Grade: C\",\"StationNumber: 00TCB02, Year: 2000, PEL ratio: 0.04205, Grade: C\",\"StationNumber: 00TCB03, Year: 2000, PEL ratio: 0.03651, Grade: C\",\"StationNumber: 00TCB04, Year: 2000, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 00TCB05, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00TCB06, Year: 2000, PEL ratio: 0.04342, Grade: C\",\"StationNumber: 00TCB07, Year: 2000, PEL ratio: 0.04274, Grade: C\",\"StationNumber: 00TCB08, Year: 2000, PEL ratio: 0.04303, Grade: C\",\"StationNumber: 01BCB57/1, Year: 2001, PEL ratio: 0.05374, Grade: C\",\"StationNumber: 01BCB58/1, Year: 2001, PEL ratio: 0.12193, Grade: D\",\"StationNumber: 01BCB58/2, Year: 2001, PEL ratio: 0.027, Grade: C\",\"StationNumber: 01BCB59/1, Year: 2001, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 01BCB59/2, Year: 2001, PEL ratio: 0.04048, Grade: C\",\"StationNumber: 01BCB60/2, Year: 2001, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 01BCB60/4, Year: 2001, PEL ratio: 0.01424, Grade: B\",\"StationNumber: 01BCB6001, Year: 2001, PEL ratio: 0.0563, Grade: C\",\"StationNumber: 01BCB6009, Year: 2001, PEL ratio: 0.04348, Grade: C\",\"StationNumber: 01BCB6018, Year: 2001, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 01BCB6019, Year: 2001, PEL ratio: 0.01532, Grade: B\",\"StationNumber: 01BCB6031, Year: 2001, PEL ratio: 0.02161, Grade: C\",\"StationNumber: 01BCB6063, Year: 2001, PEL ratio: 0.0077, Grade: B\",\"StationNumber: 01BCB6072, Year: 2001, PEL ratio: 0.03264, Grade: C\",\"StationNumber: 01BCB6089, Year: 2001, PEL ratio: 0.02463, Grade: C\",\"StationNumber: 01BCB6109, Year: 2001, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 01BCB6114, Year: 2001, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 01BCB6152, Year: 2001, PEL ratio: 0.0269, Grade: C\",\"StationNumber: 01BCB6178, Year: 2001, PEL ratio: 0.02377, Grade: C\",\"StationNumber: 01BCB6190, Year: 2001, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 01BCB6230, Year: 2001, PEL ratio: 0.05637, Grade: C\",\"StationNumber: 01BCB6263, Year: 2001, PEL ratio: 0.04428, Grade: C\",\"StationNumber: 01BCB6359, Year: 2001, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 01HB6019, Year: 2001, PEL ratio: 0.13163, Grade: D\",\"StationNumber: 01HB6022, Year: 2001, PEL ratio: 0.07712, Grade: C\",\"StationNumber: 01HB6032, Year: 2001, PEL ratio: 0.03892, Grade: C\",\"StationNumber: 01HB6035, Year: 2001, PEL ratio: 0.06366, Grade: C\",\"StationNumber: 01HB6045, Year: 2001, PEL ratio: 0.04136, Grade: C\",\"StationNumber: 01HB6064, Year: 2001, PEL ratio: 0.08868, Grade: D\",\"StationNumber: 01HB6066, Year: 2001, PEL ratio: 0.04113, Grade: C\",\"StationNumber: 01HB6087, Year: 2001, PEL ratio: 0.07944, Grade: C\",\"StationNumber: 01HB6093, Year: 2001, PEL ratio: 0.0345, Grade: C\",\"StationNumber: 01HB6102, Year: 2001, PEL ratio: 0.04233, Grade: C\",\"StationNumber: 01HB6108, Year: 2001, PEL ratio: 0.07274, Grade: C\",\"StationNumber: 01HB6131, Year: 2001, PEL ratio: 0.03937, Grade: C\",\"StationNumber: 01HB6140, Year: 2001, PEL ratio: 0.03728, Grade: C\",\"StationNumber: 01HB6145, Year: 2001, PEL ratio: 0.03711, Grade: C\",\"StationNumber: 01HB6159, Year: 2001, PEL ratio: 0.05123, Grade: C\",\"StationNumber: 01HB6186, Year: 2001, PEL ratio: 0.11466, Grade: D\",\"StationNumber: 01HB6187, Year: 2001, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 01HB6249, Year: 2001, PEL ratio: 0.02319, Grade: C\",\"StationNumber: 01HB6261, Year: 2001, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 01HB6264, Year: 2001, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 01HB6283, Year: 2001, PEL ratio: 0.03557, Grade: C\",\"StationNumber: 01HB6305, Year: 2001, PEL ratio: 0.0378, Grade: C\",\"StationNumber: 01HB6374, Year: 2001, PEL ratio: 0.09193, Grade: D\",\"StationNumber: 01HB6453, Year: 2001, PEL ratio: 0.05442, Grade: C\",\"StationNumber: 01HB6537, Year: 2001, PEL ratio: 0.03766, Grade: C\",\"StationNumber: 01LTB6026, Year: 2001, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 01LTB6027, Year: 2001, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 01LTB6050, Year: 2001, PEL ratio: 0.04404, Grade: C\",\"StationNumber: 01LTB6104, Year: 2001, PEL ratio: 0.0209, Grade: C\",\"StationNumber: 01LTB6120, Year: 2001, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 01LTB6122, Year: 2001, PEL ratio: 0.05444, Grade: C\",\"StationNumber: 01LTB6158, Year: 2001, PEL ratio: 0.09951, Grade: D\",\"StationNumber: 01LTB6302, Year: 2001, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 01LTB6346, Year: 2001, PEL ratio: 0.00189, Grade: A\",\"StationNumber: 01LTB6380, Year: 2001, PEL ratio: 0.04602, Grade: C\",\"StationNumber: 01LTB6595, Year: 2001, PEL ratio: 0.04587, Grade: C\",\"StationNumber: 01LTB6869, Year: 2001, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 01MR09, Year: 2001, PEL ratio: 0.00085, Grade: A\",\"StationNumber: 01MR12, Year: 2001, PEL ratio: 0.00214, Grade: A\",\"StationNumber: 01MR13, Year: 2001, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 01MR14, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR17, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR18, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR19, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR20, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR21, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MTB6002, Year: 2001, PEL ratio: 0.04429, Grade: C\",\"StationNumber: 01MTB6011, Year: 2001, PEL ratio: 0.03017, Grade: C\",\"StationNumber: 01MTB6014, Year: 2001, PEL ratio: 0.03931, Grade: C\",\"StationNumber: 01MTB6049, Year: 2001, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 01MTB6059, Year: 2001, PEL ratio: 0.03202, Grade: C\",\"StationNumber: 01MTB6064, Year: 2001, PEL ratio: 0.02866, Grade: C\",\"StationNumber: 01MTB6068, Year: 2001, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 01MTB6080, Year: 2001, PEL ratio: 0.03134, Grade: C\",\"StationNumber: 01MTB6133, Year: 2001, PEL ratio: 0.03877, Grade: C\",\"StationNumber: 01MTB6154, Year: 2001, PEL ratio: 0.03081, Grade: C\",\"StationNumber: 01MTB6188, Year: 2001, PEL ratio: 0.04865, Grade: C\",\"StationNumber: 01MTB6189, Year: 2001, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 01MTB6196, Year: 2001, PEL ratio: 0.03661, Grade: C\",\"StationNumber: 01MTB6229, Year: 2001, PEL ratio: 0.03253, Grade: C\",\"StationNumber: 01MTB6257, Year: 2001, PEL ratio: 0.04035, Grade: C\",\"StationNumber: 01MTB6265, Year: 2001, PEL ratio: 0.03247, Grade: C\",\"StationNumber: 01MTB6290, Year: 2001, PEL ratio: 0.03227, Grade: C\",\"StationNumber: 01MTB6325, Year: 2001, PEL ratio: 0.03135, Grade: C\",\"StationNumber: 01MTB6327, Year: 2001, PEL ratio: 0.0343, Grade: C\",\"StationNumber: 01MTB6328, Year: 2001, PEL ratio: 0.0383, Grade: C\",\"StationNumber: 01MTB6464, Year: 2001, PEL ratio: 0.03323, Grade: C\",\"StationNumber: 01MTB6495, Year: 2001, PEL ratio: 0.03374, Grade: C\",\"StationNumber: 01MTB6527, Year: 2001, PEL ratio: 0.0365, Grade: C\",\"StationNumber: 01MTB6638, Year: 2001, PEL ratio: 0.03712, Grade: C\",\"StationNumber: 01MTB6699, Year: 2001, PEL ratio: 0.03196, Grade: C\",\"StationNumber: 01MTB7153, Year: 2001, PEL ratio: 0.02961, Grade: C\",\"StationNumber: 01OTB6010, Year: 2001, PEL ratio: 0.0366, Grade: C\",\"StationNumber: 01OTB6017, Year: 2001, PEL ratio: 0.0392, Grade: C\",\"StationNumber: 01OTB6021, Year: 2001, PEL ratio: 0.035, Grade: C\",\"StationNumber: 01OTB6022, Year: 2001, PEL ratio: 0.03556, Grade: C\",\"StationNumber: 01OTB6025, Year: 2001, PEL ratio: 0.0835, Grade: C\",\"StationNumber: 01OTB6028, Year: 2001, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 01OTB6078, Year: 2001, PEL ratio: 0.03835, Grade: C\",\"StationNumber: 01OTB6103, Year: 2001, PEL ratio: 0.04375, Grade: C\",\"StationNumber: 01OTB6135, Year: 2001, PEL ratio: 0.1479, Grade: D\",\"StationNumber: 01OTB6152, Year: 2001, PEL ratio: 0.17372, Grade: D\",\"StationNumber: 01OTB6178, Year: 2001, PEL ratio: 0.04426, Grade: C\",\"StationNumber: 01OTB6186, Year: 2001, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 01OTB6234, Year: 2001, PEL ratio: 0.03095, Grade: C\",\"StationNumber: 01OTB6239, Year: 2001, PEL ratio: 0.07735, Grade: C\",\"StationNumber: 01OTB6441, Year: 2001, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 01OTB6784, Year: 2001, PEL ratio: 0.03879, Grade: C\",\"StationNumber: 01OTB6830, Year: 2001, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 01SAFHAB, Year: 2001, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 01TCB02, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB03, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB04, Year: 2001, PEL ratio: 0.00149, Grade: A\",\"StationNumber: 01TCB06, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB07, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 02BCB05, Year: 2002, PEL ratio: 0.09921, Grade: D\",\"StationNumber: 02BCB20, Year: 2002, PEL ratio: 0.03895, Grade: C\",\"StationNumber: 02BCB32, Year: 2002, PEL ratio: 0.02428, Grade: C\",\"StationNumber: 02BCB52, Year: 2002, PEL ratio: 0.03041, Grade: C\",\"StationNumber: 02BCB62, Year: 2002, PEL ratio: 0.07542, Grade: C\",\"StationNumber: 02BCB69, Year: 2002, PEL ratio: 0.02783, Grade: C\",\"StationNumber: 02BCB74, Year: 2002, PEL ratio: 0.02301, Grade: C\",\"StationNumber: 02BCB83, Year: 2002, PEL ratio: 0.02746, Grade: C\",\"StationNumber: 02BCB90, Year: 2002, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 02DH09-1, Year: 2002, PEL ratio: 0.19807, Grade: D\",\"StationNumber: 02DH09-2, Year: 2002, PEL ratio: 0.12272, Grade: D\",\"StationNumber: 02DH09-3, Year: 2002, PEL ratio: 0.30626, Grade: F\",\"StationNumber: 02DH11A-1, Year: 2002, PEL ratio: 0.10175, Grade: D\",\"StationNumber: 02DH11A-2, Year: 2002, PEL ratio: 0.11172, Grade: D\",\"StationNumber: 02DH11A-3, Year: 2002, PEL ratio: 0.14465, Grade: D\",\"StationNumber: 02DH11B-1, Year: 2002, PEL ratio: 0.10113, Grade: D\",\"StationNumber: 02DH11B-4, Year: 2002, PEL ratio: 0.12537, Grade: D\",\"StationNumber: 02DH11B-5, Year: 2002, PEL ratio: 0.13789, Grade: D\",\"StationNumber: 02HB09, Year: 2002, PEL ratio: 0.16733, Grade: D\",\"StationNumber: 02HB20, Year: 2002, PEL ratio: 0.02678, Grade: C\",\"StationNumber: 02HB21, Year: 2002, PEL ratio: 0.02244, Grade: C\",\"StationNumber: 02HB27, Year: 2002, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 02HB39, Year: 2002, PEL ratio: 0.21706, Grade: D\",\"StationNumber: 02HB42, Year: 2002, PEL ratio: 0.02683, Grade: C\",\"StationNumber: 02HB49, Year: 2002, PEL ratio: 0.03845, Grade: C\",\"StationNumber: 02HB50, Year: 2002, PEL ratio: 0.32514, Grade: F\",\"StationNumber: 02HB51, Year: 2002, PEL ratio: 0.06603, Grade: C\",\"StationNumber: 02HB55, Year: 2002, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 02LTB01, Year: 2002, PEL ratio: 0.02663, Grade: C\",\"StationNumber: 02LTB02, Year: 2002, PEL ratio: 0.02978, Grade: C\",\"StationNumber: 02LTB03, Year: 2002, PEL ratio: 0.02042, Grade: B\",\"StationNumber: 02LTB04, Year: 2002, PEL ratio: 0.02782, Grade: C\",\"StationNumber: 02LTB05, Year: 2002, PEL ratio: 0.02348, Grade: C\",\"StationNumber: 02LTB06, Year: 2002, PEL ratio: 0.04038, Grade: C\",\"StationNumber: 02LTB07, Year: 2002, PEL ratio: 0.03048, Grade: C\",\"StationNumber: 02LTB08, Year: 2002, PEL ratio: 0.02061, Grade: C\",\"StationNumber: 02LTB09, Year: 2002, PEL ratio: 0.02023, Grade: B\",\"StationNumber: 02MR02, Year: 2002, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 02MR04, Year: 2002, PEL ratio: 0.03337, Grade: C\",\"StationNumber: 02MR06, Year: 2002, PEL ratio: 0.14519, Grade: D\",\"StationNumber: 02MR08, Year: 2002, PEL ratio: 0.02507, Grade: C\",\"StationNumber: 02MR10, Year: 2002, PEL ratio: 0.04251, Grade: C\",\"StationNumber: 02MR11, Year: 2002, PEL ratio: 0.03906, Grade: C\",\"StationNumber: 02MR12, Year: 2002, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 02DH08-1, Year: 2002, PEL ratio: 0.09017, Grade: D\",\"StationNumber: 02DH08-2, Year: 2002, PEL ratio: 0.10363, Grade: D\",\"StationNumber: 02DH08-3, Year: 2002, PEL ratio: 0.08051, Grade: C\",\"StationNumber: 02DH14-1, Year: 2002, PEL ratio: 0.18895, Grade: D\",\"StationNumber: 02DH14-3, Year: 2002, PEL ratio: 0.12398, Grade: D\",\"StationNumber: 02DH14-4, Year: 2002, PEL ratio: 0.13475, Grade: D\",\"StationNumber: 02DH15-1, Year: 2002, PEL ratio: 0.03722, Grade: C\",\"StationNumber: 02DH15-2, Year: 2002, PEL ratio: 0.03193, Grade: C\",\"StationNumber: 02DH15-5, Year: 2002, PEL ratio: 0.10865, Grade: D\",\"StationNumber: 02MTB11, Year: 2002, PEL ratio: 0.03207, Grade: C\",\"StationNumber: 02MTB12, Year: 2002, PEL ratio: 0.03458, Grade: C\",\"StationNumber: 02MTB18, Year: 2002, PEL ratio: 0.06402, Grade: C\",\"StationNumber: 02MTB19, Year: 2002, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 02MTB21, Year: 2002, PEL ratio: 0.07645, Grade: C\",\"StationNumber: 02MTB23, Year: 2002, PEL ratio: 0.04157, Grade: C\",\"StationNumber: 02MTB27, Year: 2002, PEL ratio: 0.03517, Grade: C\",\"StationNumber: 02MTB29, Year: 2002, PEL ratio: 0.03409, Grade: C\",\"StationNumber: 02MTB32, Year: 2002, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 02MTB34, Year: 2002, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 02DH03-2, Year: 2002, PEL ratio: 0.15, Grade: D\",\"StationNumber: 02DH03-4, Year: 2002, PEL ratio: 0.15355, Grade: D\",\"StationNumber: 02DH03-5, Year: 2002, PEL ratio: 0.18194, Grade: D\",\"StationNumber: 02DH05-3, Year: 2002, PEL ratio: 0.02701, Grade: C\",\"StationNumber: 02DH05-4, Year: 2002, PEL ratio: 0.08347, Grade: C\",\"StationNumber: 02DH05-5, Year: 2002, PEL ratio: 0.03648, Grade: C\",\"StationNumber: 02DH07-1, Year: 2002, PEL ratio: 0.08738, Grade: D\",\"StationNumber: 02DH07-2, Year: 2002, PEL ratio: 0.09842, Grade: D\",\"StationNumber: 02DH07-3, Year: 2002, PEL ratio: 0.09265, Grade: D\",\"StationNumber: 02DH18-1, Year: 2002, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 02DH18-2, Year: 2002, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 02DH18-3, Year: 2002, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 02DH20-3, Year: 2002, PEL ratio: 0.09118, Grade: D\",\"StationNumber: 02DH20-4, Year: 2002, PEL ratio: 0.0982, Grade: D\",\"StationNumber: 02DH20-5, Year: 2002, PEL ratio: 0.08451, Grade: C\",\"StationNumber: 02DH21A-1, Year: 2002, PEL ratio: 0.08952, Grade: D\",\"StationNumber: 02DH21A-3, Year: 2002, PEL ratio: 0.10866, Grade: D\",\"StationNumber: 02DH21A-5, Year: 2002, PEL ratio: 0.11684, Grade: D\",\"StationNumber: 02DH21B-1, Year: 2002, PEL ratio: 0.13203, Grade: D\",\"StationNumber: 02DH21B-3, Year: 2002, PEL ratio: 0.12143, Grade: D\",\"StationNumber: 02DH21B-4, Year: 2002, PEL ratio: 0.1119, Grade: D\",\"StationNumber: 02OTB02, Year: 2002, PEL ratio: 0.02894, Grade: C\",\"StationNumber: 02OTB04, Year: 2002, PEL ratio: 0.03118, Grade: C\",\"StationNumber: 02OTB27, Year: 2002, PEL ratio: 0.02515, Grade: C\",\"StationNumber: 02OTB49, Year: 2002, PEL ratio: 0.0374, Grade: C\",\"StationNumber: 02OTB50, Year: 2002, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 02OTB52, Year: 2002, PEL ratio: 0.03468, Grade: C\",\"StationNumber: 02OTB60, Year: 2002, PEL ratio: 0.0399, Grade: C\",\"StationNumber: 02OTB66, Year: 2002, PEL ratio: 0.04346, Grade: C\",\"StationNumber: 02TCB03, Year: 2002, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 02TCB05, Year: 2002, PEL ratio: 0.05723, Grade: C\",\"StationNumber: 02TCB07, Year: 2002, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 02TCB09, Year: 2002, PEL ratio: 0.041, Grade: C\",\"StationNumber: 03BCB107, Year: 2003, PEL ratio: 0.04845, Grade: C\",\"StationNumber: 03BCB120, Year: 2003, PEL ratio: 0.07755, Grade: C\",\"StationNumber: 03BCB126, Year: 2003, PEL ratio: 0.05955, Grade: C\",\"StationNumber: 03BCB190, Year: 2003, PEL ratio: 0.07526, Grade: C\",\"StationNumber: 03BCB230, Year: 2003, PEL ratio: 0.04192, Grade: C\",\"StationNumber: 03BCB242, Year: 2003, PEL ratio: 0.1701, Grade: D\",\"StationNumber: 03BCB278, Year: 2003, PEL ratio: 0.04954, Grade: C\",\"StationNumber: 03BCB287, Year: 2003, PEL ratio: 0.0426, Grade: C\",\"StationNumber: 03BCB338, Year: 2003, PEL ratio: 0.05523, Grade: C\",\"StationNumber: 03BCB439, Year: 2003, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 03HB01, Year: 2003, PEL ratio: 0.05953, Grade: C\",\"StationNumber: 03HB02, Year: 2003, PEL ratio: 0.09513, Grade: D\",\"StationNumber: 03HB04, Year: 2003, PEL ratio: 0.05264, Grade: C\",\"StationNumber: 03HB06, Year: 2003, PEL ratio: 0.2787, Grade: D\",\"StationNumber: 03HB09, Year: 2003, PEL ratio: 2.62709, Grade: F\",\"StationNumber: 03HB10, Year: 2003, PEL ratio: 0.07527, Grade: C\",\"StationNumber: 03HB11, Year: 2003, PEL ratio: 0.05917, Grade: C\",\"StationNumber: 03HB12, Year: 2003, PEL ratio: 0.08962, Grade: D\",\"StationNumber: 03HB14, Year: 2003, PEL ratio: 0.05233, Grade: C\",\"StationNumber: 03HB16, Year: 2003, PEL ratio: 0.08913, Grade: D\",\"StationNumber: 03HB18, Year: 2003, PEL ratio: 0.07056, Grade: C\",\"StationNumber: 03HB21, Year: 2003, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 03HB27, Year: 2003, PEL ratio: 0.11208, Grade: D\",\"StationNumber: 03HB28, Year: 2003, PEL ratio: 0.13538, Grade: D\",\"StationNumber: 03HB30, Year: 2003, PEL ratio: 0.05101, Grade: C\",\"StationNumber: 03HB32, Year: 2003, PEL ratio: 0.08584, Grade: D\",\"StationNumber: 03HB33, Year: 2003, PEL ratio: 0.04992, Grade: C\",\"StationNumber: 03HB34, Year: 2003, PEL ratio: 0.05096, Grade: C\",\"StationNumber: 03HB37, Year: 2003, PEL ratio: 0.17023, Grade: D\",\"StationNumber: 03HB38, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03HB41, Year: 2003, PEL ratio: 0.07016, Grade: C\",\"StationNumber: 03HB42, Year: 2003, PEL ratio: 0.11971, Grade: D\",\"StationNumber: 03HB44, Year: 2003, PEL ratio: 0.04723, Grade: C\",\"StationNumber: 03HB47, Year: 2003, PEL ratio: 0.0484, Grade: C\",\"StationNumber: 03HB50, Year: 2003, PEL ratio: 0.04892, Grade: C\",\"StationNumber: 03HB51, Year: 2003, PEL ratio: 0.07784, Grade: C\",\"StationNumber: 03HB52, Year: 2003, PEL ratio: 0.10156, Grade: D\",\"StationNumber: 03HB53, Year: 2003, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 03LTB01, Year: 2003, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 03LTB02, Year: 2003, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 03LTB03, Year: 2003, PEL ratio: 0.04888, Grade: C\",\"StationNumber: 03LTB04, Year: 2003, PEL ratio: 0.05672, Grade: C\",\"StationNumber: 03LTB05, Year: 2003, PEL ratio: 0.03249, Grade: C\",\"StationNumber: 03LTB06, Year: 2003, PEL ratio: 0.04582, Grade: C\",\"StationNumber: 03LTB07, Year: 2003, PEL ratio: 0.05602, Grade: C\",\"StationNumber: 03LTB08, Year: 2003, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 03LTB09, Year: 2003, PEL ratio: 0.04842, Grade: C\",\"StationNumber: 03LTB10, Year: 2003, PEL ratio: 0.03141, Grade: C\",\"StationNumber: 03LTB11, Year: 2003, PEL ratio: 0.05041, Grade: C\",\"StationNumber: 03LTB12, Year: 2003, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 03MR02, Year: 2003, PEL ratio: 0.07551, Grade: C\",\"StationNumber: 03MR04, Year: 2003, PEL ratio: 0.06186, Grade: C\",\"StationNumber: 03MR06, Year: 2003, PEL ratio: 0.11177, Grade: D\",\"StationNumber: 03MR07, Year: 2003, PEL ratio: 0.04271, Grade: C\",\"StationNumber: 03MR08, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03MR09, Year: 2003, PEL ratio: 0.04126, Grade: C\",\"StationNumber: 03MR10, Year: 2003, PEL ratio: 0.05761, Grade: C\",\"StationNumber: 03MTB03, Year: 2003, PEL ratio: 0.05627, Grade: C\",\"StationNumber: 03MTB08, Year: 2003, PEL ratio: 0.06744, Grade: C\",\"StationNumber: 03MTB10, Year: 2003, PEL ratio: 0.04607, Grade: C\",\"StationNumber: 03MTB11, Year: 2003, PEL ratio: 0.0679, Grade: C\",\"StationNumber: 03MTB13, Year: 2003, PEL ratio: 0.08571, Grade: D\",\"StationNumber: 03MTB14, Year: 2003, PEL ratio: 0.07424, Grade: C\",\"StationNumber: 03MTB15, Year: 2003, PEL ratio: 0.07661, Grade: C\",\"StationNumber: 03MTB16, Year: 2003, PEL ratio: 0.07141, Grade: C\",\"StationNumber: 03MTB17, Year: 2003, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 03MTB18, Year: 2003, PEL ratio: 0.06047, Grade: C\",\"StationNumber: 03MTB19, Year: 2003, PEL ratio: 0.0635, Grade: C\",\"StationNumber: 03MTB21, Year: 2003, PEL ratio: 0.06752, Grade: C\",\"StationNumber: 03MTB24, Year: 2003, PEL ratio: 0.05516, Grade: C\",\"StationNumber: 03MTB25, Year: 2003, PEL ratio: 0.06373, Grade: C\",\"StationNumber: 03MTB27, Year: 2003, PEL ratio: 0.05651, Grade: C\",\"StationNumber: 03MTB28, Year: 2003, PEL ratio: 0.06933, Grade: C\",\"StationNumber: 03MTB30, Year: 2003, PEL ratio: 0.43636, Grade: F\",\"StationNumber: 03MTB31, Year: 2003, PEL ratio: 0.07005, Grade: C\",\"StationNumber: 03MTB32, Year: 2003, PEL ratio: 0.05667, Grade: C\",\"StationNumber: 03MTB33, Year: 2003, PEL ratio: 0.07011, Grade: C\",\"StationNumber: 03MTB34, Year: 2003, PEL ratio: 0.06682, Grade: C\",\"StationNumber: 03MTB35, Year: 2003, PEL ratio: 0.07621, Grade: C\",\"StationNumber: 03OTB157, Year: 2003, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 03OTB200, Year: 2003, PEL ratio: 0.16694, Grade: D\",\"StationNumber: 03OTB413, Year: 2003, PEL ratio: 0.05894, Grade: C\",\"StationNumber: 03OTB414, Year: 2003, PEL ratio: 0.04976, Grade: C\",\"StationNumber: 03OTB507, Year: 2003, PEL ratio: 0.07151, Grade: C\",\"StationNumber: 03OTB623, Year: 2003, PEL ratio: 0.19749, Grade: D\",\"StationNumber: 03OTB706, Year: 2003, PEL ratio: 0.11944, Grade: D\",\"StationNumber: 03OTB794, Year: 2003, PEL ratio: 0.05991, Grade: C\",\"StationNumber: 03OTB929, Year: 2003, PEL ratio: 0.09521, Grade: D\",\"StationNumber: 03TCB01, Year: 2003, PEL ratio: 0.03963, Grade: C\",\"StationNumber: 03TCB03, Year: 2003, PEL ratio: 0.04315, Grade: C\",\"StationNumber: 03TCB05, Year: 2003, PEL ratio: 0.04569, Grade: C\",\"StationNumber: 04BCB01, Year: 2004, PEL ratio: 0.03545, Grade: C\",\"StationNumber: 04BCB02, Year: 2004, PEL ratio: 0.03051, Grade: C\",\"StationNumber: 04BCB03, Year: 2004, PEL ratio: 0.1299, Grade: D\",\"StationNumber: 04BCB04, Year: 2004, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 04BCB05, Year: 2004, PEL ratio: 0.02806, Grade: C\",\"StationNumber: 04BCB06, Year: 2004, PEL ratio: 0.05131, Grade: C\",\"StationNumber: 04BCB07, Year: 2004, PEL ratio: 0.02049, Grade: B\",\"StationNumber: 04BCB08, Year: 2004, PEL ratio: 0.03435, Grade: C\",\"StationNumber: 04BCB09, Year: 2004, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 04BCB10, Year: 2004, PEL ratio: 0.03223, Grade: C\",\"StationNumber: 04HB01, Year: 2004, PEL ratio: 0.01651, Grade: B\",\"StationNumber: 04HB02, Year: 2004, PEL ratio: 0.0358, Grade: C\",\"StationNumber: 04HB03, Year: 2004, PEL ratio: 0.12867, Grade: D\",\"StationNumber: 04HB04, Year: 2004, PEL ratio: 0.08639, Grade: D\",\"StationNumber: 04HB05, Year: 2004, PEL ratio: 0.02012, Grade: B\",\"StationNumber: 04HB06, Year: 2004, PEL ratio: 0.02029, Grade: B\",\"StationNumber: 04HB07, Year: 2004, PEL ratio: 0.02572, Grade: C\",\"StationNumber: 04HB08, Year: 2004, PEL ratio: 0.02404, Grade: C\",\"StationNumber: 04HB09, Year: 2004, PEL ratio: 0.04005, Grade: C\",\"StationNumber: 04HB10, Year: 2004, PEL ratio: 0.18388, Grade: D\",\"StationNumber: 04HB11, Year: 2004, PEL ratio: 0.02011, Grade: B\",\"StationNumber: 04HB12, Year: 2004, PEL ratio: 0.11403, Grade: D\",\"StationNumber: 04HB13, Year: 2004, PEL ratio: 0.14349, Grade: D\",\"StationNumber: 04HB14, Year: 2004, PEL ratio: 0.02109, Grade: C\",\"StationNumber: 04HB15, Year: 2004, PEL ratio: 0.02016, Grade: B\",\"StationNumber: 04HB16, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04HB17, Year: 2004, PEL ratio: 0.18354, Grade: D\",\"StationNumber: 04HB18, Year: 2004, PEL ratio: 0.4013, Grade: F\",\"StationNumber: 04HB19, Year: 2004, PEL ratio: 0.12724, Grade: D\",\"StationNumber: 04HB20, Year: 2004, PEL ratio: 0.02398, Grade: C\",\"StationNumber: 04HB21, Year: 2004, PEL ratio: 0.02873, Grade: C\",\"StationNumber: 04HB23, Year: 2004, PEL ratio: 0.02633, Grade: C\",\"StationNumber: 04HB24, Year: 2004, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 04HB25, Year: 2004, PEL ratio: 0.05102, Grade: C\",\"StationNumber: 04HB26, Year: 2004, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 04LTB01, Year: 2004, PEL ratio: 0.01329, Grade: B\",\"StationNumber: 04LTB02, Year: 2004, PEL ratio: 0.02081, Grade: C\",\"StationNumber: 04LTB03, Year: 2004, PEL ratio: 0.02025, Grade: B\",\"StationNumber: 04LTB04, Year: 2004, PEL ratio: 0.01177, Grade: B\",\"StationNumber: 04LTB05, Year: 2004, PEL ratio: 0.0211, Grade: C\",\"StationNumber: 04LTB06, Year: 2004, PEL ratio: 0.01694, Grade: B\",\"StationNumber: 04LTB07, Year: 2004, PEL ratio: 0.01745, Grade: B\",\"StationNumber: 04LTB08, Year: 2004, PEL ratio: 0.03084, Grade: C\",\"StationNumber: 04LTB09, Year: 2004, PEL ratio: 0.02538, Grade: C\",\"StationNumber: 04LTB10, Year: 2004, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 04LTB11, Year: 2004, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 04MR01, Year: 2004, PEL ratio: 0.08777, Grade: D\",\"StationNumber: 04MR02, Year: 2004, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 04MR03, Year: 2004, PEL ratio: 0.01966, Grade: B\",\"StationNumber: 04MR04, Year: 2004, PEL ratio: 0.04362, Grade: C\",\"StationNumber: 04MR05, Year: 2004, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 04MR06, Year: 2004, PEL ratio: 0.01585, Grade: B\",\"StationNumber: 04MR08, Year: 2004, PEL ratio: 0.06183, Grade: C\",\"StationNumber: 04MR09, Year: 2004, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 04MR10, Year: 2004, PEL ratio: 0.02989, Grade: C\",\"StationNumber: 04MR11, Year: 2004, PEL ratio: 0.04141, Grade: C\",\"StationNumber: 04MTB01, Year: 2004, PEL ratio: 0.0143, Grade: B\",\"StationNumber: 04MTB02, Year: 2004, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 04MTB04, Year: 2004, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 04MTB05, Year: 2004, PEL ratio: 0.02789, Grade: C\",\"StationNumber: 04MTB06, Year: 2004, PEL ratio: 0.01916, Grade: B\",\"StationNumber: 04MTB07, Year: 2004, PEL ratio: 0.01837, Grade: B\",\"StationNumber: 04MTB08, Year: 2004, PEL ratio: 0.02226, Grade: C\",\"StationNumber: 04MTB09, Year: 2004, PEL ratio: 0.0162, Grade: B\",\"StationNumber: 04MTB10, Year: 2004, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 04MTB11, Year: 2004, PEL ratio: 0.02662, Grade: C\",\"StationNumber: 04MTB12, Year: 2004, PEL ratio: 0.0287, Grade: C\",\"StationNumber: 04MTB13, Year: 2004, PEL ratio: 0.03236, Grade: C\",\"StationNumber: 04MTB14, Year: 2004, PEL ratio: 0.03029, Grade: C\",\"StationNumber: 04MTB15, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04MTB16, Year: 2004, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 04MTB17, Year: 2004, PEL ratio: 0.02028, Grade: B\",\"StationNumber: 04MTB18, Year: 2004, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 04MTB19, Year: 2004, PEL ratio: 0.03315, Grade: C\",\"StationNumber: 04MTB20, Year: 2004, PEL ratio: 0.02831, Grade: C\",\"StationNumber: 04MTB21, Year: 2004, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 04MTB22, Year: 2004, PEL ratio: 0.02665, Grade: C\",\"StationNumber: 04MTB24, Year: 2004, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 04OTB01, Year: 2004, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 04OTB02, Year: 2004, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 04OTB03, Year: 2004, PEL ratio: 0.03106, Grade: C\",\"StationNumber: 04OTB04, Year: 2004, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 04OTB05, Year: 2004, PEL ratio: 0.12197, Grade: D\",\"StationNumber: 04OTB06, Year: 2004, PEL ratio: 0.02194, Grade: C\",\"StationNumber: 04OTB07, Year: 2004, PEL ratio: 0.10091, Grade: D\",\"StationNumber: 04OTB08, Year: 2004, PEL ratio: 0.0248, Grade: C\",\"StationNumber: 04OTB09, Year: 2004, PEL ratio: 0.0243, Grade: C\",\"StationNumber: 04TCB07, Year: 2004, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05BCB01, Year: 2005, PEL ratio: 0.02056, Grade: C\",\"StationNumber: 05BCB02, Year: 2005, PEL ratio: 0.01422, Grade: B\",\"StationNumber: 05BCB03, Year: 2005, PEL ratio: 0.0279, Grade: C\",\"StationNumber: 05BCB04, Year: 2005, PEL ratio: 0.01565, Grade: B\",\"StationNumber: 05BCB05, Year: 2005, PEL ratio: 0.94385, Grade: F\",\"StationNumber: 05BCB06, Year: 2005, PEL ratio: 0.03608, Grade: C\",\"StationNumber: 05BCB07, Year: 2005, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 05BCB08, Year: 2005, PEL ratio: 0.0183, Grade: B\",\"StationNumber: 05BCB09, Year: 2005, PEL ratio: 0.02383, Grade: C\",\"StationNumber: 05BCB10, Year: 2005, PEL ratio: 0.01397, Grade: B\",\"StationNumber: 05HB01, Year: 2005, PEL ratio: 0.02071, Grade: C\",\"StationNumber: 05HB02, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05HB03, Year: 2005, PEL ratio: 0.01997, Grade: B\",\"StationNumber: 05HB04, Year: 2005, PEL ratio: 0.0672, Grade: C\",\"StationNumber: 05HB05, Year: 2005, PEL ratio: 0.10587, Grade: D\",\"StationNumber: 05HB06, Year: 2005, PEL ratio: 0.07366, Grade: C\",\"StationNumber: 05HB07, Year: 2005, PEL ratio: 0.01737, Grade: B\",\"StationNumber: 05HB08, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05HB09, Year: 2005, PEL ratio: 0.03392, Grade: C\",\"StationNumber: 05HB10, Year: 2005, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 05HB11, Year: 2005, PEL ratio: 0.01724, Grade: B\",\"StationNumber: 05HB12, Year: 2005, PEL ratio: 1.00876, Grade: F\",\"StationNumber: 05HB13, Year: 2005, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05HB14, Year: 2005, PEL ratio: 0.15213, Grade: D\",\"StationNumber: 05HB15, Year: 2005, PEL ratio: 0.07682, Grade: C\",\"StationNumber: 05HB16, Year: 2005, PEL ratio: 0.11966, Grade: D\",\"StationNumber: 05HB17, Year: 2005, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 05HB18, Year: 2005, PEL ratio: 0.02303, Grade: C\",\"StationNumber: 05HB19, Year: 2005, PEL ratio: 0.01643, Grade: B\",\"StationNumber: 05HB20, Year: 2005, PEL ratio: 0.01686, Grade: B\",\"StationNumber: 05HB21, Year: 2005, PEL ratio: 0.0478, Grade: C\",\"StationNumber: 05HB22, Year: 2005, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 05HB23, Year: 2005, PEL ratio: 0.02946, Grade: C\",\"StationNumber: 05HB24, Year: 2005, PEL ratio: 0.01751, Grade: B\",\"StationNumber: 05LTB01, Year: 2005, PEL ratio: 0.02599, Grade: C\",\"StationNumber: 05LTB02, Year: 2005, PEL ratio: 0.01545, Grade: B\",\"StationNumber: 05LTB03, Year: 2005, PEL ratio: 0.01154, Grade: B\",\"StationNumber: 05LTB04, Year: 2005, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 05LTB05, Year: 2005, PEL ratio: 0.01619, Grade: B\",\"StationNumber: 05LTB06, Year: 2005, PEL ratio: 0.0193, Grade: B\",\"StationNumber: 05LTB07, Year: 2005, PEL ratio: 0.01402, Grade: B\",\"StationNumber: 05LTB08, Year: 2005, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 05LTB09, Year: 2005, PEL ratio: 0.02347, Grade: C\",\"StationNumber: 05LTB10, Year: 2005, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 05LTB11, Year: 2005, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 05MR02, Year: 2005, PEL ratio: 0.01442, Grade: B\",\"StationNumber: 05MR04, Year: 2005, PEL ratio: 0.02173, Grade: C\",\"StationNumber: 05MR06, Year: 2005, PEL ratio: 0.01537, Grade: B\",\"StationNumber: 05MR08, Year: 2005, PEL ratio: 0.01574, Grade: B\",\"StationNumber: 05MR09, Year: 2005, PEL ratio: 0.01971, Grade: B\",\"StationNumber: 05MR11, Year: 2005, PEL ratio: 0.08271, Grade: C\",\"StationNumber: 05MTB01, Year: 2005, PEL ratio: 0.02214, Grade: C\",\"StationNumber: 05MTB02, Year: 2005, PEL ratio: 0.0218, Grade: C\",\"StationNumber: 05MTB03, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05MTB04, Year: 2005, PEL ratio: 0.01475, Grade: B\",\"StationNumber: 05MTB05, Year: 2005, PEL ratio: 0.01741, Grade: B\",\"StationNumber: 05MTB06, Year: 2005, PEL ratio: 0.01714, Grade: B\",\"StationNumber: 05MTB07, Year: 2005, PEL ratio: 0.03643, Grade: C\",\"StationNumber: 05MTB08, Year: 2005, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 05MTB09, Year: 2005, PEL ratio: 0.01427, Grade: B\",\"StationNumber: 05MTB10, Year: 2005, PEL ratio: 0.01804, Grade: B\",\"StationNumber: 05MTB11, Year: 2005, PEL ratio: 0.01786, Grade: B\",\"StationNumber: 05MTB12, Year: 2005, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 05MTB13, Year: 2005, PEL ratio: 0.01404, Grade: B\",\"StationNumber: 05MTB14, Year: 2005, PEL ratio: 0.02263, Grade: C\",\"StationNumber: 05MTB15, Year: 2005, PEL ratio: 0.10298, Grade: D\",\"StationNumber: 05MTB16, Year: 2005, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 05MTB17, Year: 2005, PEL ratio: 0.01324, Grade: B\",\"StationNumber: 05MTB18, Year: 2005, PEL ratio: 0.01423, Grade: B\",\"StationNumber: 05MTB19, Year: 2005, PEL ratio: 0.01217, Grade: B\",\"StationNumber: 05MTB20, Year: 2005, PEL ratio: 0.01481, Grade: B\",\"StationNumber: 05MTB21, Year: 2005, PEL ratio: 0.03798, Grade: C\",\"StationNumber: 05MTB22, Year: 2005, PEL ratio: 0.0196, Grade: B\",\"StationNumber: 05OTB01, Year: 2005, PEL ratio: 0.01507, Grade: B\",\"StationNumber: 05OTB02, Year: 2005, PEL ratio: 0.02508, Grade: C\",\"StationNumber: 05OTB03, Year: 2005, PEL ratio: 0.01587, Grade: B\",\"StationNumber: 05OTB04, Year: 2005, PEL ratio: 0.02237, Grade: C\",\"StationNumber: 05OTB05, Year: 2005, PEL ratio: 0.0268, Grade: C\",\"StationNumber: 05OTB06, Year: 2005, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 05OTB07, Year: 2005, PEL ratio: 0.02997, Grade: C\",\"StationNumber: 05OTB08, Year: 2005, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 05OTB09, Year: 2005, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 05OTB10, Year: 2005, PEL ratio: 0.01673, Grade: B\",\"StationNumber: 05TCB01, Year: 2005, PEL ratio: 0.02249, Grade: C\",\"StationNumber: 05TCB03, Year: 2005, PEL ratio: 0.01896, Grade: B\",\"StationNumber: 05TCB05, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05TCB07, Year: 2005, PEL ratio: 0.11125, Grade: D\",\"StationNumber: 05TCB10, Year: 2005, PEL ratio: 0.01684, Grade: B\",\"StationNumber: 06BCB01, Year: 2006, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 06BCB02, Year: 2006, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 06BCB03, Year: 2006, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 06BCB04, Year: 2006, PEL ratio: 0.04285, Grade: C\",\"StationNumber: 06BCB05, Year: 2006, PEL ratio: 0.02977, Grade: C\",\"StationNumber: 06BCB06, Year: 2006, PEL ratio: 0.03224, Grade: C\",\"StationNumber: 06BCB07, Year: 2006, PEL ratio: 0.05354, Grade: C\",\"StationNumber: 06BCB08, Year: 2006, PEL ratio: 0.03691, Grade: C\",\"StationNumber: 06BCB09, Year: 2006, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 06HB01, Year: 2006, PEL ratio: 0.05456, Grade: C\",\"StationNumber: 06HB02, Year: 2006, PEL ratio: 0.07105, Grade: C\",\"StationNumber: 06HB03, Year: 2006, PEL ratio: 0.09993, Grade: D\",\"StationNumber: 06HB04, Year: 2006, PEL ratio: 0.04056, Grade: C\",\"StationNumber: 06HB05, Year: 2006, PEL ratio: 0.05604, Grade: C\",\"StationNumber: 06HB06, Year: 2006, PEL ratio: 0.05301, Grade: C\",\"StationNumber: 06HB08, Year: 2006, PEL ratio: 0.04385, Grade: C\",\"StationNumber: 06HB09, Year: 2006, PEL ratio: 0.326, Grade: F\",\"StationNumber: 06HB10, Year: 2006, PEL ratio: 0.03664, Grade: C\",\"StationNumber: 06HB11, Year: 2006, PEL ratio: 0.04268, Grade: C\",\"StationNumber: 06HB12, Year: 2006, PEL ratio: 0.04913, Grade: C\",\"StationNumber: 06HB13, Year: 2006, PEL ratio: 0.03765, Grade: C\",\"StationNumber: 06HB14, Year: 2006, PEL ratio: 0.04626, Grade: C\",\"StationNumber: 06HB15, Year: 2006, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 06HB16, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06HB17, Year: 2006, PEL ratio: 0.04712, Grade: C\",\"StationNumber: 06HB18, Year: 2006, PEL ratio: 0.14179, Grade: D\",\"StationNumber: 06HB19, Year: 2006, PEL ratio: 0.05858, Grade: C\",\"StationNumber: 06HB20, Year: 2006, PEL ratio: 0.10134, Grade: D\",\"StationNumber: 06HB21, Year: 2006, PEL ratio: 0.08326, Grade: C\",\"StationNumber: 06HB22, Year: 2006, PEL ratio: 0.033, Grade: C\",\"StationNumber: 06HB23, Year: 2006, PEL ratio: 0.02427, Grade: C\",\"StationNumber: 06HB24, Year: 2006, PEL ratio: 0.04327, Grade: C\",\"StationNumber: 06HB25, Year: 2006, PEL ratio: 0.01783, Grade: B\",\"StationNumber: 06LTB01, Year: 2006, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 06LTB02, Year: 2006, PEL ratio: 0.0323, Grade: C\",\"StationNumber: 06LTB03, Year: 2006, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 06LTB04, Year: 2006, PEL ratio: 0.03755, Grade: C\",\"StationNumber: 06LTB05, Year: 2006, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 06LTB06, Year: 2006, PEL ratio: 0.0252, Grade: C\",\"StationNumber: 06LTB07, Year: 2006, PEL ratio: 0.02677, Grade: C\",\"StationNumber: 06LTB08, Year: 2006, PEL ratio: 0.034, Grade: C\",\"StationNumber: 06MR05, Year: 2006, PEL ratio: 0.06293, Grade: C\",\"StationNumber: 06MR06, Year: 2006, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 06MR07, Year: 2006, PEL ratio: 0.03329, Grade: C\",\"StationNumber: 06MR08, Year: 2006, PEL ratio: 0.02817, Grade: C\",\"StationNumber: 06MR10, Year: 2006, PEL ratio: 0.0606, Grade: C\",\"StationNumber: 06MTB01, Year: 2006, PEL ratio: 0.0429, Grade: C\",\"StationNumber: 06MTB02, Year: 2006, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 06MTB03, Year: 2006, PEL ratio: 0.07411, Grade: C\",\"StationNumber: 06MTB04, Year: 2006, PEL ratio: 0.03457, Grade: C\",\"StationNumber: 06MTB05, Year: 2006, PEL ratio: 0.04597, Grade: C\",\"StationNumber: 06MTB06, Year: 2006, PEL ratio: 0.04758, Grade: C\",\"StationNumber: 06MTB07, Year: 2006, PEL ratio: 0.03733, Grade: C\",\"StationNumber: 06MTB08, Year: 2006, PEL ratio: 0.02422, Grade: C\",\"StationNumber: 06MTB09, Year: 2006, PEL ratio: 0.03151, Grade: C\",\"StationNumber: 06MTB10, Year: 2006, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 06MTB11, Year: 2006, PEL ratio: 0.05121, Grade: C\",\"StationNumber: 06MTB12, Year: 2006, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 06MTB13, Year: 2006, PEL ratio: 0.04635, Grade: C\",\"StationNumber: 06MTB14, Year: 2006, PEL ratio: 0.02936, Grade: C\",\"StationNumber: 06MTB15, Year: 2006, PEL ratio: 0.04074, Grade: C\",\"StationNumber: 06MTB16, Year: 2006, PEL ratio: 0.02985, Grade: C\",\"StationNumber: 06MTB17, Year: 2006, PEL ratio: 0.04129, Grade: C\",\"StationNumber: 06MTB18, Year: 2006, PEL ratio: 0.02464, Grade: C\",\"StationNumber: 06MTB19, Year: 2006, PEL ratio: 0.03277, Grade: C\",\"StationNumber: 06OTB01, Year: 2006, PEL ratio: 0.03793, Grade: C\",\"StationNumber: 06OTB02, Year: 2006, PEL ratio: 0.03026, Grade: C\",\"StationNumber: 06OTB03, Year: 2006, PEL ratio: 0.02375, Grade: C\",\"StationNumber: 06OTB04, Year: 2006, PEL ratio: 0.03499, Grade: C\",\"StationNumber: 06OTB05, Year: 2006, PEL ratio: 0.03108, Grade: C\",\"StationNumber: 06OTB06, Year: 2006, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 06OTB07, Year: 2006, PEL ratio: 0.03414, Grade: C\",\"StationNumber: 06OTB08, Year: 2006, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 06TCB01, Year: 2006, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 06TCB02, Year: 2006, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 06TCB03, Year: 2006, PEL ratio: 0.02258, Grade: C\",\"StationNumber: 06TCB04, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06TCB09, Year: 2006, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 07BCB06, Year: 2007, PEL ratio: 0.03022, Grade: C\",\"StationNumber: 07BCB09, Year: 2007, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 07BCB15, Year: 2007, PEL ratio: 0.03284, Grade: C\",\"StationNumber: 07BCB28, Year: 2007, PEL ratio: 0.0147, Grade: B\",\"StationNumber: 07BCB29, Year: 2007, PEL ratio: 0.03304, Grade: C\",\"StationNumber: 07BCB30, Year: 2007, PEL ratio: 0.02747, Grade: C\",\"StationNumber: 07BCB41, Year: 2007, PEL ratio: 0.02363, Grade: C\",\"StationNumber: 07BCB42, Year: 2007, PEL ratio: 0.03369, Grade: C\",\"StationNumber: 07BCB44, Year: 2007, PEL ratio: 0.02609, Grade: C\",\"StationNumber: 07BCB45, Year: 2007, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 07HB13, Year: 2007, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 07HB21, Year: 2007, PEL ratio: 0.64118, Grade: F\",\"StationNumber: 07HB34, Year: 2007, PEL ratio: 0.02191, Grade: C\",\"StationNumber: 07HB37, Year: 2007, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 07HB38, Year: 2007, PEL ratio: 0.01243, Grade: B\",\"StationNumber: 07HB41, Year: 2007, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 07HB42, Year: 2007, PEL ratio: 0.04791, Grade: C\",\"StationNumber: 07HB44, Year: 2007, PEL ratio: 0.05993, Grade: C\",\"StationNumber: 07HB53, Year: 2007, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 07LTB91, Year: 2007, PEL ratio: 0.01736, Grade: B\",\"StationNumber: 07MR09, Year: 2007, PEL ratio: 0.00426, Grade: A\",\"StationNumber: 07MR28, Year: 2007, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 07MR42, Year: 2007, PEL ratio: 0.01369, Grade: B\",\"StationNumber: 07MR46, Year: 2007, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 07MR50, Year: 2007, PEL ratio: 0.00928, Grade: B\",\"StationNumber: 07MTB34, Year: 2007, PEL ratio: 0.03749, Grade: C\",\"StationNumber: 07MTB39, Year: 2007, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 07MTB40, Year: 2007, PEL ratio: 0.03116, Grade: C\",\"StationNumber: 07MTB43, Year: 2007, PEL ratio: 0.03052, Grade: C\",\"StationNumber: 07MTB44, Year: 2007, PEL ratio: 0.0747, Grade: C\",\"StationNumber: 07MTB47, Year: 2007, PEL ratio: 0.04289, Grade: C\",\"StationNumber: 07MTB54, Year: 2007, PEL ratio: 0.03469, Grade: C\",\"StationNumber: 07OTB04, Year: 2007, PEL ratio: 0.0814, Grade: C\",\"StationNumber: 07OTB08, Year: 2007, PEL ratio: 0.03439, Grade: C\",\"StationNumber: 07OTB18, Year: 2007, PEL ratio: 0.03309, Grade: C\",\"StationNumber: 07OTB21, Year: 2007, PEL ratio: 0.05054, Grade: C\",\"StationNumber: 07OTB24, Year: 2007, PEL ratio: 0.03054, Grade: C\",\"StationNumber: 07OTB25, Year: 2007, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 07OTB31, Year: 2007, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 07TCB14, Year: 2007, PEL ratio: 0.02992, Grade: C\",\"StationNumber: 07TCB15, Year: 2007, PEL ratio: 0.0222, Grade: C\",\"StationNumber: 07TCB20, Year: 2007, PEL ratio: 0.01955, Grade: B\",\"StationNumber: 07TCB22, Year: 2007, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 08BCB02, Year: 2008, PEL ratio: 0.02083, Grade: C\",\"StationNumber: 08BCB05, Year: 2008, PEL ratio: 0.02657, Grade: C\",\"StationNumber: 08BCB12, Year: 2008, PEL ratio: 0.02728, Grade: C\",\"StationNumber: 08BCB15, Year: 2008, PEL ratio: 0.06515, Grade: C\",\"StationNumber: 08BCB16, Year: 2008, PEL ratio: 0.03082, Grade: C\",\"StationNumber: 08BCB17, Year: 2008, PEL ratio: 0.09679, Grade: D\",\"StationNumber: 08BCB23, Year: 2008, PEL ratio: 0.1008, Grade: D\",\"StationNumber: 08BCB26, Year: 2008, PEL ratio: 0.0274, Grade: C\",\"StationNumber: 08BCB29, Year: 2008, PEL ratio: 0.0277, Grade: C\",\"StationNumber: 08BCB35, Year: 2008, PEL ratio: 0.03788, Grade: C\",\"StationNumber: 08BCB38, Year: 2008, PEL ratio: 0.02984, Grade: C\",\"StationNumber: 08HB13, Year: 2008, PEL ratio: 0.07748, Grade: C\",\"StationNumber: 08HB14, Year: 2008, PEL ratio: 0.03813, Grade: C\",\"StationNumber: 08HB17, Year: 2008, PEL ratio: 0.24554, Grade: D\",\"StationNumber: 08HB21, Year: 2008, PEL ratio: 0.15288, Grade: D\",\"StationNumber: 08HB27, Year: 2008, PEL ratio: 0.05295, Grade: C\",\"StationNumber: 08HB34, Year: 2008, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 08HB43, Year: 2008, PEL ratio: 0.02778, Grade: C\",\"StationNumber: 08HB44, Year: 2008, PEL ratio: 0.02327, Grade: C\",\"StationNumber: 08HB48, Year: 2008, PEL ratio: 0.02752, Grade: C\",\"StationNumber: 08LTB69, Year: 2008, PEL ratio: 0.02295, Grade: C\",\"StationNumber: 08LTB79, Year: 2008, PEL ratio: 0.04396, Grade: C\",\"StationNumber: 08LTB82, Year: 2008, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 08MR08, Year: 2008, PEL ratio: 0.03334, Grade: C\",\"StationNumber: 08MR35, Year: 2008, PEL ratio: 0.02726, Grade: C\",\"StationNumber: 08MR40, Year: 2008, PEL ratio: 0.03952, Grade: C\",\"StationNumber: 08MR43, Year: 2008, PEL ratio: 0.08724, Grade: D\",\"StationNumber: 08MR53, Year: 2008, PEL ratio: 0.02561, Grade: C\",\"StationNumber: 08MR54, Year: 2008, PEL ratio: 0.02649, Grade: C\",\"StationNumber: 08MTB37, Year: 2008, PEL ratio: 0.02715, Grade: C\",\"StationNumber: 08MTB47, Year: 2008, PEL ratio: 0.02945, Grade: C\",\"StationNumber: 08MTB53, Year: 2008, PEL ratio: 0, Grade: A\",\"StationNumber: 08MTB62, Year: 2008, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 08MTB73, Year: 2008, PEL ratio: 0.085, Grade: C\",\"StationNumber: 08OTB05, Year: 2008, PEL ratio: 0.02469, Grade: C\",\"StationNumber: 08OTB07, Year: 2008, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 08OTB13, Year: 2008, PEL ratio: 0.02418, Grade: C\",\"StationNumber: 08OTB15, Year: 2008, PEL ratio: 0.03404, Grade: C\",\"StationNumber: 08OTB17, Year: 2008, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 08OTB23, Year: 2008, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 08OTB27, Year: 2008, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 08TCB01, Year: 2008, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 08TCB07, Year: 2008, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 08TCB26, Year: 2008, PEL ratio: 0.03977, Grade: C\",\"StationNumber: 09BCB06, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB07, Year: 2009, PEL ratio: 0.22765, Grade: D\",\"StationNumber: 09BCB10, Year: 2009, PEL ratio: 0.22887, Grade: D\",\"StationNumber: 09BCB18, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09BCB20, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB22, Year: 2009, PEL ratio: 0.22745, Grade: D\",\"StationNumber: 09BCB25, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB31, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB34, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB36, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB43, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB05, Year: 2009, PEL ratio: 0.2648, Grade: D\",\"StationNumber: 09HB11, Year: 2009, PEL ratio: 0.23926, Grade: D\",\"StationNumber: 09HB15, Year: 2009, PEL ratio: 0.2285, Grade: D\",\"StationNumber: 09HB23, Year: 2009, PEL ratio: 0.22717, Grade: D\",\"StationNumber: 09HB24, Year: 2009, PEL ratio: 0.22751, Grade: D\",\"StationNumber: 09HB32, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB35, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB53, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB56, Year: 2009, PEL ratio: 0.24223, Grade: D\",\"StationNumber: 09LTB77, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09LTB90, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR17, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR30, Year: 2009, PEL ratio: 0.22715, Grade: D\",\"StationNumber: 09MR36, Year: 2009, PEL ratio: 0.23016, Grade: D\",\"StationNumber: 09MR46, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR49, Year: 2009, PEL ratio: 0.22727, Grade: D\",\"StationNumber: 09MTB42, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB44, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB48, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB50, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB63, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB72, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB09, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB10, Year: 2009, PEL ratio: 0.23279, Grade: D\",\"StationNumber: 09OTB14, Year: 2009, PEL ratio: 0.22724, Grade: D\",\"StationNumber: 09OTB16, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09OTB20, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09OTB28, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB29, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB10, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB13, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB14, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB22, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 10BCB06, Year: 2010, PEL ratio: 0.05418, Grade: C\",\"StationNumber: 10BCB11, Year: 2010, PEL ratio: 0.06776, Grade: C\",\"StationNumber: 10BCB17, Year: 2010, PEL ratio: 0.05636, Grade: C\",\"StationNumber: 10BCB25, Year: 2010, PEL ratio: 0.04525, Grade: C\",\"StationNumber: 10BCB28, Year: 2010, PEL ratio: 0.058, Grade: C\",\"StationNumber: 10BCB30, Year: 2010, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 10BCB37, Year: 2010, PEL ratio: 0.05759, Grade: C\",\"StationNumber: 10BCB41, Year: 2010, PEL ratio: 0.16956, Grade: D\",\"StationNumber: 10BCB46, Year: 2010, PEL ratio: 0.04398, Grade: C\",\"StationNumber: 10BCB47, Year: 2010, PEL ratio: 0.05076, Grade: C\",\"StationNumber: 10BCB49, Year: 2010, PEL ratio: 0.04946, Grade: C\",\"StationNumber: 10HB21, Year: 2010, PEL ratio: 0.11698, Grade: D\",\"StationNumber: 10HB22, Year: 2010, PEL ratio: 0.1448, Grade: D\",\"StationNumber: 10HB25, Year: 2010, PEL ratio: 0.06694, Grade: C\",\"StationNumber: 10HB26, Year: 2010, PEL ratio: 0.09827, Grade: D\",\"StationNumber: 10HB34, Year: 2010, PEL ratio: 0.05702, Grade: C\",\"StationNumber: 10HB44, Year: 2010, PEL ratio: 0.05266, Grade: C\",\"StationNumber: 10HB46, Year: 2010, PEL ratio: 0.05934, Grade: C\",\"StationNumber: 10HB48, Year: 2010, PEL ratio: 0.05189, Grade: C\",\"StationNumber: 10HB54, Year: 2010, PEL ratio: 0.06254, Grade: C\",\"StationNumber: 10LTB71, Year: 2010, PEL ratio: 0.03978, Grade: C\",\"StationNumber: 10LTB76, Year: 2010, PEL ratio: 0.04208, Grade: C\",\"StationNumber: 10LTB89, Year: 2010, PEL ratio: 0.04389, Grade: C\",\"StationNumber: 10MR25, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR29, Year: 2010, PEL ratio: 0.04883, Grade: C\",\"StationNumber: 10MR33, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR40, Year: 2010, PEL ratio: 0.05975, Grade: C\",\"StationNumber: 10MR44, Year: 2010, PEL ratio: 0.05334, Grade: C\",\"StationNumber: 10MTB30, Year: 2010, PEL ratio: 0.11699, Grade: D\",\"StationNumber: 10MTB35, Year: 2010, PEL ratio: 0.0404, Grade: C\",\"StationNumber: 10MTB43, Year: 2010, PEL ratio: 0.05591, Grade: C\",\"StationNumber: 10MTB53, Year: 2010, PEL ratio: 0.05385, Grade: C\",\"StationNumber: 10MTB56, Year: 2010, PEL ratio: 0.04796, Grade: C\",\"StationNumber: 10OTB04, Year: 2010, PEL ratio: 0.06327, Grade: C\",\"StationNumber: 10OTB05, Year: 2010, PEL ratio: 0.04514, Grade: C\",\"StationNumber: 10OTB07, Year: 2010, PEL ratio: 0.0966, Grade: D\",\"StationNumber: 10OTB08, Year: 2010, PEL ratio: 0.05185, Grade: C\",\"StationNumber: 10OTB09, Year: 2010, PEL ratio: 0.0499, Grade: C\",\"StationNumber: 10OTB12, Year: 2010, PEL ratio: 0.04749, Grade: C\",\"StationNumber: 10OTB13, Year: 2010, PEL ratio: 0.09096, Grade: D\",\"StationNumber: 10OTB14, Year: 2010, PEL ratio: 0.05743, Grade: C\",\"StationNumber: 10OTB15, Year: 2010, PEL ratio: 0.0503, Grade: C\",\"StationNumber: 10OTB16, Year: 2010, PEL ratio: 0.04904, Grade: C\",\"StationNumber: 10OTB18, Year: 2010, PEL ratio: 0.04797, Grade: C\",\"StationNumber: 10OTB19, Year: 2010, PEL ratio: 0.04649, Grade: C\",\"StationNumber: 10OTB20, Year: 2010, PEL ratio: 0.05188, Grade: C\",\"StationNumber: 10OTB21, Year: 2010, PEL ratio: 0.09696, Grade: D\",\"StationNumber: 10OTB24, Year: 2010, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 10OTB25, Year: 2010, PEL ratio: 0.04516, Grade: C\",\"StationNumber: 10OTB26, Year: 2010, PEL ratio: 0.06229, Grade: C\",\"StationNumber: 10OTB28, Year: 2010, PEL ratio: 0.05494, Grade: C\",\"StationNumber: 10OTB29, Year: 2010, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 10OTB96, Year: 2010, PEL ratio: 0.09566, Grade: D\",\"StationNumber: 10OTB97, Year: 2010, PEL ratio: 0.0741, Grade: C\",\"StationNumber: 10OTB98, Year: 2010, PEL ratio: 0.057, Grade: C\",\"StationNumber: 10TCB01, Year: 2010, PEL ratio: 0.03856, Grade: C\",\"StationNumber: 10TCB11, Year: 2010, PEL ratio: 0.04704, Grade: C\",\"StationNumber: 10TCB13, Year: 2010, PEL ratio: 0.04199, Grade: C\",\"StationNumber: 10TCB20, Year: 2010, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 11BCB05, Year: 2011, PEL ratio: 0.03406, Grade: C\",\"StationNumber: 11BCB09, Year: 2011, PEL ratio: 0.07696, Grade: C\",\"StationNumber: 11BCB12, Year: 2011, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 11BCB20, Year: 2011, PEL ratio: 0.0708, Grade: C\",\"StationNumber: 11BCB22, Year: 2011, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 11BCB26, Year: 2011, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 11BCB35, Year: 2011, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 11BCB42, Year: 2011, PEL ratio: 0.05499, Grade: C\",\"StationNumber: 11BCB43, Year: 2011, PEL ratio: 0.03362, Grade: C\",\"StationNumber: 11BCB44, Year: 2011, PEL ratio: 0.03382, Grade: C\",\"StationNumber: 11BCB48, Year: 2011, PEL ratio: 0.03412, Grade: C\",\"StationNumber: 11HB09, Year: 2011, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 11HB13, Year: 2011, PEL ratio: 0.05996, Grade: C\",\"StationNumber: 11HB29, Year: 2011, PEL ratio: 0.0821, Grade: C\",\"StationNumber: 11HB31, Year: 2011, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 11HB35, Year: 2011, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 11HB36, Year: 2011, PEL ratio: 0.04301, Grade: C\",\"StationNumber: 11HB38, Year: 2011, PEL ratio: 0.03229, Grade: C\",\"StationNumber: 11HB40, Year: 2011, PEL ratio: 0.04344, Grade: C\",\"StationNumber: 11HB47, Year: 2011, PEL ratio: 0.07343, Grade: C\",\"StationNumber: 11LTB69, Year: 2011, PEL ratio: 0.03431, Grade: C\",\"StationNumber: 11LTB75, Year: 2011, PEL ratio: 0.03175, Grade: C\",\"StationNumber: 11LTB80, Year: 2011, PEL ratio: 0.02849, Grade: C\",\"StationNumber: 11MR18, Year: 2011, PEL ratio: 0.03158, Grade: C\",\"StationNumber: 11MR32, Year: 2011, PEL ratio: 0.08626, Grade: D\",\"StationNumber: 11MR35, Year: 2011, PEL ratio: 0.2895, Grade: F\",\"StationNumber: 11MR37, Year: 2011, PEL ratio: 0.04922, Grade: C\",\"StationNumber: 11MR43, Year: 2011, PEL ratio: 0.22016, Grade: D\",\"StationNumber: 11MR45, Year: 2011, PEL ratio: 0.05964, Grade: C\",\"StationNumber: 11MR52, Year: 2011, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 11MTB39, Year: 2011, PEL ratio: 0.03658, Grade: C\",\"StationNumber: 11MTB44, Year: 2011, PEL ratio: 0.03276, Grade: C\",\"StationNumber: 11MTB46, Year: 2011, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 11MTB54, Year: 2011, PEL ratio: 0.03421, Grade: C\",\"StationNumber: 11MTB72, Year: 2011, PEL ratio: 0.03547, Grade: C\",\"StationNumber: 11OTB08, Year: 2011, PEL ratio: 0.05594, Grade: C\",\"StationNumber: 11OTB09, Year: 2011, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 11OTB18, Year: 2011, PEL ratio: 0.03456, Grade: C\",\"StationNumber: 11OTB24, Year: 2011, PEL ratio: 0.03411, Grade: C\",\"StationNumber: 11OTB26, Year: 2011, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 11OTB31, Year: 2011, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 11OTB32, Year: 2011, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 11TCB10, Year: 2011, PEL ratio: 0.02871, Grade: C\",\"StationNumber: 11TCB12, Year: 2011, PEL ratio: 0.03385, Grade: C\",\"StationNumber: 12BCB06, Year: 2012, PEL ratio: 0.04452, Grade: C\",\"StationNumber: 12BCB14, Year: 2012, PEL ratio: 0.38368, Grade: F\",\"StationNumber: 12BCB19, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12BCB23, Year: 2012, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 12BCB25, Year: 2012, PEL ratio: 0.03922, Grade: C\",\"StationNumber: 12BCB27, Year: 2012, PEL ratio: 0.07968, Grade: C\",\"StationNumber: 12BCB35, Year: 2012, PEL ratio: 0.04033, Grade: C\",\"StationNumber: 12BCB40, Year: 2012, PEL ratio: 0.04044, Grade: C\",\"StationNumber: 12BCB44, Year: 2012, PEL ratio: 0.03462, Grade: C\",\"StationNumber: 12BCB46, Year: 2012, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 12BCB49, Year: 2012, PEL ratio: 0.04079, Grade: C\",\"StationNumber: 12HB27, Year: 2012, PEL ratio: 0.04713, Grade: C\",\"StationNumber: 12HB28, Year: 2012, PEL ratio: 0.0439, Grade: C\",\"StationNumber: 12HB31, Year: 2012, PEL ratio: 0.13887, Grade: D\",\"StationNumber: 12HB32, Year: 2012, PEL ratio: 0.04521, Grade: C\",\"StationNumber: 12HB38, Year: 2012, PEL ratio: 0.05609, Grade: C\",\"StationNumber: 12HB40, Year: 2012, PEL ratio: 0.03976, Grade: C\",\"StationNumber: 12HB45, Year: 2012, PEL ratio: 0.07001, Grade: C\",\"StationNumber: 12HB53, Year: 2012, PEL ratio: 0.045, Grade: C\",\"StationNumber: 12HB54, Year: 2012, PEL ratio: 0.04384, Grade: C\",\"StationNumber: 12LTB78, Year: 2012, PEL ratio: 0.04261, Grade: C\",\"StationNumber: 12LTB84, Year: 2012, PEL ratio: 0.03384, Grade: C\",\"StationNumber: 12LTB93, Year: 2012, PEL ratio: 0.03901, Grade: C\",\"StationNumber: 12MR08, Year: 2012, PEL ratio: 0.03605, Grade: C\",\"StationNumber: 12MR17, Year: 2012, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 12MR33, Year: 2012, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 12MR36, Year: 2012, PEL ratio: 0.0414, Grade: C\",\"StationNumber: 12MR43, Year: 2012, PEL ratio: 0.04657, Grade: C\",\"StationNumber: 12MR46, Year: 2012, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 12MR54, Year: 2012, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 12MTB47, Year: 2012, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 12MTB53, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12MTB58, Year: 2012, PEL ratio: 0.05309, Grade: C\",\"StationNumber: 12MTB63, Year: 2012, PEL ratio: 0.03957, Grade: C\",\"StationNumber: 12MTB64, Year: 2012, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 12OTB04, Year: 2012, PEL ratio: 0.13065, Grade: D\",\"StationNumber: 12OTB08, Year: 2012, PEL ratio: 0.03843, Grade: C\",\"StationNumber: 12OTB13, Year: 2012, PEL ratio: 0.04154, Grade: C\",\"StationNumber: 12OTB14, Year: 2012, PEL ratio: 0.03612, Grade: C\",\"StationNumber: 12OTB18, Year: 2012, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 12OTB19, Year: 2012, PEL ratio: 0.03486, Grade: C\",\"StationNumber: 12OTB20, Year: 2012, PEL ratio: 0.04146, Grade: C\",\"StationNumber: 12TCB05, Year: 2012, PEL ratio: 0.03318, Grade: C\",\"StationNumber: 12TCB13, Year: 2012, PEL ratio: 0.03331, Grade: C\",\"StationNumber: 13BCB05, Year: 2013, PEL ratio: 0.16727, Grade: D\",\"StationNumber: 13BCB07, Year: 2013, PEL ratio: 0.04534, Grade: C\",\"StationNumber: 13BCB09, Year: 2013, PEL ratio: 0.04449, Grade: C\",\"StationNumber: 13BCB10, Year: 2013, PEL ratio: 0.03598, Grade: C\",\"StationNumber: 13BCB11, Year: 2013, PEL ratio: 0.1881, Grade: D\",\"StationNumber: 13BCB17, Year: 2013, PEL ratio: 0.10487, Grade: D\",\"StationNumber: 13BCB22, Year: 2013, PEL ratio: 0.0432, Grade: C\",\"StationNumber: 13BCB30, Year: 2013, PEL ratio: 0.03594, Grade: C\",\"StationNumber: 13BCB41, Year: 2013, PEL ratio: 0.03671, Grade: C\",\"StationNumber: 13BCB43, Year: 2013, PEL ratio: 0.03609, Grade: C\",\"StationNumber: 13BCB48, Year: 2013, PEL ratio: 0.04681, Grade: C\",\"StationNumber: 13HB09, Year: 2013, PEL ratio: 0.07695, Grade: C\",\"StationNumber: 13HB13, Year: 2013, PEL ratio: 0.0831, Grade: C\",\"StationNumber: 13HB25, Year: 2013, PEL ratio: 0.03306, Grade: C\",\"StationNumber: 13HB26, Year: 2013, PEL ratio: 0.05412, Grade: C\",\"StationNumber: 13HB35, Year: 2013, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 13HB36, Year: 2013, PEL ratio: 0.18861, Grade: D\",\"StationNumber: 13HB41, Year: 2013, PEL ratio: 0.03847, Grade: C\",\"StationNumber: 13HB44, Year: 2013, PEL ratio: 0.09625, Grade: D\",\"StationNumber: 13HB48, Year: 2013, PEL ratio: 0.0373, Grade: C\",\"StationNumber: 13LTB79, Year: 2013, PEL ratio: 0.03872, Grade: C\",\"StationNumber: 13LTB82, Year: 2013, PEL ratio: 0.03513, Grade: C\",\"StationNumber: 13LTB86, Year: 2013, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 13MR09, Year: 2013, PEL ratio: 0.03565, Grade: C\",\"StationNumber: 13MR24, Year: 2013, PEL ratio: 0.03695, Grade: C\",\"StationNumber: 13MR31, Year: 2013, PEL ratio: 0.34066, Grade: F\",\"StationNumber: 13MR44, Year: 2013, PEL ratio: 0.09108, Grade: D\",\"StationNumber: 13MR45, Year: 2013, PEL ratio: 0.06721, Grade: C\",\"StationNumber: 13MR48, Year: 2013, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 13MTB34, Year: 2013, PEL ratio: 0.03171, Grade: C\",\"StationNumber: 13MTB35, Year: 2013, PEL ratio: 0.05215, Grade: C\",\"StationNumber: 13MTB41, Year: 2013, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 13MTB45, Year: 2013, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 13MTB55, Year: 2013, PEL ratio: 0.06478, Grade: C\",\"StationNumber: 13OTB12, Year: 2013, PEL ratio: 0.04515, Grade: C\",\"StationNumber: 13OTB15, Year: 2013, PEL ratio: 0.03702, Grade: C\",\"StationNumber: 13OTB16, Year: 2013, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 13OTB21, Year: 2013, PEL ratio: 0.04235, Grade: C\",\"StationNumber: 13OTB27, Year: 2013, PEL ratio: 0.03527, Grade: C\",\"StationNumber: 13OTB28, Year: 2013, PEL ratio: 0.03653, Grade: C\",\"StationNumber: 13OTB29, Year: 2013, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 13TCB01, Year: 2013, PEL ratio: 0.03209, Grade: C\",\"StationNumber: 13TCB11, Year: 2013, PEL ratio: 0.03349, Grade: C\",\"StationNumber: 13TCB14, Year: 2013, PEL ratio: 0.03452, Grade: C\",\"StationNumber: 14BCB03, Year: 2014, PEL ratio: 0.07223, Grade: C\",\"StationNumber: 14BCB12, Year: 2014, PEL ratio: 0.03971, Grade: C\",\"StationNumber: 14BCB15, Year: 2014, PEL ratio: 0.12267, Grade: D\",\"StationNumber: 14BCB17, Year: 2014, PEL ratio: 0.03495, Grade: C\",\"StationNumber: 14BCB20, Year: 2014, PEL ratio: 0.04709, Grade: C\",\"StationNumber: 14BCB25, Year: 2014, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 14BCB29, Year: 2014, PEL ratio: 0.01869, Grade: B\",\"StationNumber: 14BCB33, Year: 2014, PEL ratio: 0.03039, Grade: C\",\"StationNumber: 14BCB35, Year: 2014, PEL ratio: 0.08684, Grade: D\",\"StationNumber: 14BCB41, Year: 2014, PEL ratio: 0.03173, Grade: C\",\"StationNumber: 14BCB47, Year: 2014, PEL ratio: 0.02445, Grade: C\",\"StationNumber: 14HB20, Year: 2014, PEL ratio: 0.02692, Grade: C\",\"StationNumber: 14HB21, Year: 2014, PEL ratio: 0.11022, Grade: D\",\"StationNumber: 14HB26, Year: 2014, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 14HB33, Year: 2014, PEL ratio: 0.04596, Grade: C\",\"StationNumber: 14HB43, Year: 2014, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 14HB44, Year: 2014, PEL ratio: 0.02425, Grade: C\",\"StationNumber: 14HB46, Year: 2014, PEL ratio: 0.02682, Grade: C\",\"StationNumber: 14HB47, Year: 2014, PEL ratio: 0.02598, Grade: C\",\"StationNumber: 14HB54, Year: 2014, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 14LTB71, Year: 2014, PEL ratio: 0.02041, Grade: B\",\"StationNumber: 14LTB81, Year: 2014, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 14LTB90, Year: 2014, PEL ratio: 0.01877, Grade: B\",\"StationNumber: 14MR29, Year: 2014, PEL ratio: 0.01907, Grade: B\",\"StationNumber: 14MR35, Year: 2014, PEL ratio: 0.0555, Grade: C\",\"StationNumber: 14MR37, Year: 2014, PEL ratio: 0.09494, Grade: D\",\"StationNumber: 14MR38, Year: 2014, PEL ratio: 0.1108, Grade: D\",\"StationNumber: 14MR47, Year: 2014, PEL ratio: 0.01791, Grade: B\",\"StationNumber: 14MTB39, Year: 2014, PEL ratio: 0.02273, Grade: C\",\"StationNumber: 14MTB41, Year: 2014, PEL ratio: 0.03062, Grade: C\",\"StationNumber: 14MTB46, Year: 2014, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 14MTB54, Year: 2014, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 14MTB63, Year: 2014, PEL ratio: 0.02282, Grade: C\",\"StationNumber: 14OTB04, Year: 2014, PEL ratio: 0.02755, Grade: C\",\"StationNumber: 14OTB08, Year: 2014, PEL ratio: 0.03792, Grade: C\",\"StationNumber: 14OTB14, Year: 2014, PEL ratio: 0.04277, Grade: C\",\"StationNumber: 14OTB18, Year: 2014, PEL ratio: 2.41188, Grade: F\",\"StationNumber: 14OTB19, Year: 2014, PEL ratio: 0.01969, Grade: B\",\"StationNumber: 14OTB21, Year: 2014, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 14OTB25, Year: 2014, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 14TCB15, Year: 2014, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 14TCB20, Year: 2014, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 14TCB21, Year: 2014, PEL ratio: 0.0283, Grade: C\",\"StationNumber: 14TCB22, Year: 2014, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 15BCB09, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15BCB12, Year: 2015, PEL ratio: 0.04372, Grade: C\",\"StationNumber: 15BCB15, Year: 2015, PEL ratio: 0.04656, Grade: C\",\"StationNumber: 15BCB26, Year: 2015, PEL ratio: 0.05585, Grade: C\",\"StationNumber: 15BCB30, Year: 2015, PEL ratio: 0.04815, Grade: C\",\"StationNumber: 15BCB31, Year: 2015, PEL ratio: 0.13946, Grade: D\",\"StationNumber: 15BCB34, Year: 2015, PEL ratio: 0.03182, Grade: C\",\"StationNumber: 15BCB39, Year: 2015, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 15BCB43, Year: 2015, PEL ratio: 0.03861, Grade: C\",\"StationNumber: 15BCB47, Year: 2015, PEL ratio: 0.06181, Grade: C\",\"StationNumber: 15BCB48, Year: 2015, PEL ratio: 0.03381, Grade: C\",\"StationNumber: 15HB09, Year: 2015, PEL ratio: 0.15218, Grade: D\",\"StationNumber: 15HB14, Year: 2015, PEL ratio: 0.08241, Grade: C\",\"StationNumber: 15HB27, Year: 2015, PEL ratio: 0.07462, Grade: C\",\"StationNumber: 15HB36, Year: 2015, PEL ratio: 0.04156, Grade: C\",\"StationNumber: 15HB37, Year: 2015, PEL ratio: 0.03697, Grade: C\",\"StationNumber: 15HB39, Year: 2015, PEL ratio: 0.03681, Grade: C\",\"StationNumber: 15HB40, Year: 2015, PEL ratio: 0.03913, Grade: C\",\"StationNumber: 15HB41, Year: 2015, PEL ratio: 0.03531, Grade: C\",\"StationNumber: 15HB48, Year: 2015, PEL ratio: 0.038, Grade: C\",\"StationNumber: 15LTB70, Year: 2015, PEL ratio: 0.03226, Grade: C\",\"StationNumber: 15LTB76, Year: 2015, PEL ratio: 0.03036, Grade: C\",\"StationNumber: 15LTB94, Year: 2015, PEL ratio: 0.03816, Grade: C\",\"StationNumber: 15MR08, Year: 2015, PEL ratio: 0.03832, Grade: C\",\"StationNumber: 15MR28, Year: 2015, PEL ratio: 0.03623, Grade: C\",\"StationNumber: 15MR30, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15MR33, Year: 2015, PEL ratio: 0.15657, Grade: D\",\"StationNumber: 15MR42, Year: 2015, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 15MR52, Year: 2015, PEL ratio: 0.03954, Grade: C\",\"StationNumber: 15MTB40, Year: 2015, PEL ratio: 0.0354, Grade: C\",\"StationNumber: 15MTB49, Year: 2015, PEL ratio: 0.04217, Grade: C\",\"StationNumber: 15MTB52, Year: 2015, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 15MTB55, Year: 2015, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 15MTB62, Year: 2015, PEL ratio: 0.03246, Grade: C\",\"StationNumber: 15OTB12, Year: 2015, PEL ratio: 0.04593, Grade: C\",\"StationNumber: 15OTB15, Year: 2015, PEL ratio: 0.05137, Grade: C\",\"StationNumber: 15OTB20, Year: 2015, PEL ratio: 0.05337, Grade: C\",\"StationNumber: 15OTB24, Year: 2015, PEL ratio: 0.04, Grade: C\",\"StationNumber: 15OTB26, Year: 2015, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 15OTB28, Year: 2015, PEL ratio: 0.03812, Grade: C\",\"StationNumber: 15OTB29, Year: 2015, PEL ratio: 0.05653, Grade: C\",\"StationNumber: 15TCB01, Year: 2015, PEL ratio: 0.02764, Grade: C\",\"StationNumber: 15TCB11, Year: 2015, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 15TCB12, Year: 2015, PEL ratio: 0.04456, Grade: C\",\"StationNumber: 16BCB20, Year: 2016, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 16BCB22, Year: 2016, PEL ratio: 0.01314, Grade: B\",\"StationNumber: 16BCB25, Year: 2016, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 16BCB29, Year: 2016, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 16BCB34, Year: 2016, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 16BCB35, Year: 2016, PEL ratio: 0.01331, Grade: B\",\"StationNumber: 16BCB36, Year: 2016, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 16BCB37, Year: 2016, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 16BCB41, Year: 2016, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 16BCB42, Year: 2016, PEL ratio: 0.01254, Grade: B\",\"StationNumber: 16BCB43, Year: 2016, PEL ratio: 0.0166, Grade: B\",\"StationNumber: 16DH07-1, Year: 2016, PEL ratio: 0.18391, Grade: D\",\"StationNumber: 16DH07-2, Year: 2016, PEL ratio: 0.13524, Grade: D\",\"StationNumber: 16DH07-3, Year: 2016, PEL ratio: 0.20542, Grade: D\",\"StationNumber: 16DH07-4, Year: 2016, PEL ratio: 0.01549, Grade: B\",\"StationNumber: 16HB19, Year: 2016, PEL ratio: 0.05887, Grade: C\",\"StationNumber: 16HB20, Year: 2016, PEL ratio: 0.04907, Grade: C\",\"StationNumber: 16HB21, Year: 2016, PEL ratio: 0.0132, Grade: B\",\"StationNumber: 16HB27, Year: 2016, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 16HB28, Year: 2016, PEL ratio: 0.9678, Grade: F\",\"StationNumber: 16HB32, Year: 2016, PEL ratio: 0.08862, Grade: D\",\"StationNumber: 16HB33, Year: 2016, PEL ratio: 0.01043, Grade: B\",\"StationNumber: 16HB37, Year: 2016, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 16HB48, Year: 2016, PEL ratio: 0.00834, Grade: B\",\"StationNumber: 16DH04-1, Year: 2016, PEL ratio: 0.01392, Grade: B\",\"StationNumber: 16DH04-2, Year: 2016, PEL ratio: 0.01391, Grade: B\",\"StationNumber: 16DH04-3, Year: 2016, PEL ratio: 0.0173, Grade: B\",\"StationNumber: 16DH04-4, Year: 2016, PEL ratio: 0.01483, Grade: B\",\"StationNumber: 16DH08-1, Year: 2016, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 16DH08-2, Year: 2016, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 16DH08-3, Year: 2016, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 16DH08-4, Year: 2016, PEL ratio: 0.0073, Grade: A\",\"StationNumber: 16DH09-1, Year: 2016, PEL ratio: 0.0417, Grade: C\",\"StationNumber: 16DH09-2, Year: 2016, PEL ratio: 0.0163, Grade: B\",\"StationNumber: 16DH09-3, Year: 2016, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 16DH09-4, Year: 2016, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 16LTB71, Year: 2016, PEL ratio: 0.02031, Grade: B\",\"StationNumber: 16LTB79, Year: 2016, PEL ratio: 0.03301, Grade: C\",\"StationNumber: 16LTB85, Year: 2016, PEL ratio: 0.01936, Grade: B\",\"StationNumber: 16MR17, Year: 2016, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 16MR25, Year: 2016, PEL ratio: 0.01518, Grade: B\",\"StationNumber: 16MR29, Year: 2016, PEL ratio: 0.02155, Grade: C\",\"StationNumber: 16MR33, Year: 2016, PEL ratio: 0.04406, Grade: C\",\"StationNumber: 16MR43, Year: 2016, PEL ratio: 0.03343, Grade: C\",\"StationNumber: 16MR44, Year: 2016, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 16MR45, Year: 2016, PEL ratio: 0.09741, Grade: D\",\"StationNumber: 16DH06-1, Year: 2016, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 16DH06-2, Year: 2016, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 16DH06-3, Year: 2016, PEL ratio: 0.0963, Grade: D\",\"StationNumber: 16DH06-4, Year: 2016, PEL ratio: 0.04943, Grade: C\",\"StationNumber: 16DH10-1, Year: 2016, PEL ratio: 0.0172, Grade: B\",\"StationNumber: 16DH10-2, Year: 2016, PEL ratio: 0.0164, Grade: B\",\"StationNumber: 16DH10-3, Year: 2016, PEL ratio: 0.01826, Grade: B\",\"StationNumber: 16DH10-4, Year: 2016, PEL ratio: 0.01494, Grade: B\",\"StationNumber: 16MTB41, Year: 2016, PEL ratio: 0.04661, Grade: C\",\"StationNumber: 16MTB47, Year: 2016, PEL ratio: 0.01915, Grade: B\",\"StationNumber: 16MTB48, Year: 2016, PEL ratio: 0.02853, Grade: C\",\"StationNumber: 16MTB53, Year: 2016, PEL ratio: 0.01875, Grade: B\",\"StationNumber: 16MTB72, Year: 2016, PEL ratio: 0.01874, Grade: B\",\"StationNumber: 16DH01-1, Year: 2016, PEL ratio: 0.12523, Grade: D\",\"StationNumber: 16DH01-2, Year: 2016, PEL ratio: 0.02653, Grade: C\",\"StationNumber: 16DH01-3, Year: 2016, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 16DH01-4, Year: 2016, PEL ratio: 0.02374, Grade: C\",\"StationNumber: 16DH02-1, Year: 2016, PEL ratio: 0.02317, Grade: C\",\"StationNumber: 16DH02-2, Year: 2016, PEL ratio: 0.01762, Grade: B\",\"StationNumber: 16DH02-3, Year: 2016, PEL ratio: 0.14359, Grade: D\",\"StationNumber: 16DH02-4, Year: 2016, PEL ratio: 0.015, Grade: B\",\"StationNumber: 16DH03-1, Year: 2016, PEL ratio: 0.08286, Grade: C\",\"StationNumber: 16DH03-2, Year: 2016, PEL ratio: 0.12405, Grade: D\",\"StationNumber: 16DH03-3, Year: 2016, PEL ratio: 0.08808, Grade: D\",\"StationNumber: 16DH03-4, Year: 2016, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 16DH05-1, Year: 2016, PEL ratio: 0.05878, Grade: C\",\"StationNumber: 16DH05-2, Year: 2016, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 16DH05-3, Year: 2016, PEL ratio: 0.02045, Grade: B\",\"StationNumber: 16DH05-4, Year: 2016, PEL ratio: 0.01988, Grade: B\",\"StationNumber: 16OTB08, Year: 2016, PEL ratio: 0.02621, Grade: C\",\"StationNumber: 16OTB09, Year: 2016, PEL ratio: 0.03233, Grade: C\",\"StationNumber: 16OTB13, Year: 2016, PEL ratio: 0.04697, Grade: C\",\"StationNumber: 16OTB14, Year: 2016, PEL ratio: 0.02479, Grade: C\",\"StationNumber: 16OTB18, Year: 2016, PEL ratio: 0.01902, Grade: B\",\"StationNumber: 16OTB22, Year: 2016, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 16OTB25, Year: 2016, PEL ratio: 0.01921, Grade: B\",\"StationNumber: 16TCB14, Year: 2016, PEL ratio: 0.01957, Grade: B\",\"StationNumber: 16TCB20, Year: 2016, PEL ratio: 0.01605, Grade: B\",\"StationNumber: 17BCB15, Year: 2017, PEL ratio: 0.05574, Grade: C\",\"StationNumber: 17BCB26, Year: 2017, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 17BCB27, Year: 2017, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 17BCB30, Year: 2017, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 17BCB35, Year: 2017, PEL ratio: 0.0452, Grade: C\",\"StationNumber: 17BCB36, Year: 2017, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 17BCB40, Year: 2017, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 17BCB42, Year: 2017, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 17BCB43, Year: 2017, PEL ratio: 0.0479, Grade: C\",\"StationNumber: 17BCB44, Year: 2017, PEL ratio: 0.04568, Grade: C\",\"StationNumber: 17BCB48, Year: 2017, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 17HB10, Year: 2017, PEL ratio: 0.07514, Grade: C\",\"StationNumber: 17HB13, Year: 2017, PEL ratio: 0.09007, Grade: D\",\"StationNumber: 17HB15, Year: 2017, PEL ratio: 0.20221, Grade: D\",\"StationNumber: 17HB26, Year: 2017, PEL ratio: 0.04364, Grade: C\",\"StationNumber: 17HB34, Year: 2017, PEL ratio: 2.58424, Grade: F\",\"StationNumber: 17HB36, Year: 2017, PEL ratio: 0.06844, Grade: C\",\"StationNumber: 17HB41, Year: 2017, PEL ratio: 0.04206, Grade: C\",\"StationNumber: 17HB42, Year: 2017, PEL ratio: 0.04424, Grade: C\",\"StationNumber: 17HB43, Year: 2017, PEL ratio: 0.04021, Grade: C\",\"StationNumber: 17LTB70, Year: 2017, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 17LTB83, Year: 2017, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 17LTB89, Year: 2017, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 17TCP01, Year: 2017, PEL ratio: 0.05508, Grade: C\",\"StationNumber: 17TCP02, Year: 2017, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 17TCP03, Year: 2017, PEL ratio: 0.05051, Grade: C\",\"StationNumber: 17TCP04, Year: 2017, PEL ratio: 0.05089, Grade: C\",\"StationNumber: 17TCP05, Year: 2017, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 17TCP06, Year: 2017, PEL ratio: 0.07589, Grade: C\",\"StationNumber: 17TCP07, Year: 2017, PEL ratio: 0.051, Grade: C\",\"StationNumber: 17TCP08, Year: 2017, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 17TCP09, Year: 2017, PEL ratio: 0.04474, Grade: C\",\"StationNumber: 17TCP10, Year: 2017, PEL ratio: 0.04683, Grade: C\",\"StationNumber: 17MR09, Year: 2017, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 17MR18, Year: 2017, PEL ratio: 0.04076, Grade: C\",\"StationNumber: 17MR24, Year: 2017, PEL ratio: 0.03902, Grade: C\",\"StationNumber: 17MR32, Year: 2017, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 17MR35, Year: 2017, PEL ratio: 0.0913, Grade: D\",\"StationNumber: 17MR37, Year: 2017, PEL ratio: 0.04193, Grade: C\",\"StationNumber: 17MTB34, Year: 2017, PEL ratio: 0.03827, Grade: C\",\"StationNumber: 17MTB35, Year: 2017, PEL ratio: 0.05891, Grade: C\",\"StationNumber: 17MTB46, Year: 2017, PEL ratio: 0.04189, Grade: C\",\"StationNumber: 17MTB55, Year: 2017, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 17MTB63, Year: 2017, PEL ratio: 0.04197, Grade: C\",\"StationNumber: 17OTB04, Year: 2017, PEL ratio: 0.0536, Grade: C\",\"StationNumber: 17OTB07, Year: 2017, PEL ratio: 0.05219, Grade: C\",\"StationNumber: 17OTB12, Year: 2017, PEL ratio: 0.10245, Grade: D\",\"StationNumber: 17OTB19, Year: 2017, PEL ratio: 0.04286, Grade: C\",\"StationNumber: 17OTB21, Year: 2017, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 17OTB28, Year: 2017, PEL ratio: 0.04793, Grade: C\",\"StationNumber: 17OTB32, Year: 2017, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 17TCB12, Year: 2017, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 17TCB13, Year: 2017, PEL ratio: 0.04488, Grade: C\",\"StationNumber: 17TCB21, Year: 2017, PEL ratio: 0.04358, Grade: C\",\"StationNumber: 18BCB11, Year: 2018, PEL ratio: 0.37337, Grade: F\",\"StationNumber: 18BCB15, Year: 2018, PEL ratio: 0.21905, Grade: D\",\"StationNumber: 18BCB19, Year: 2018, PEL ratio: 0.00266, Grade: A\",\"StationNumber: 18BCB20, Year: 2018, PEL ratio: 0.21369, Grade: D\",\"StationNumber: 18BCB22, Year: 2018, PEL ratio: 0.17683, Grade: D\",\"StationNumber: 18BCB24, Year: 2018, PEL ratio: 0.01165, Grade: B\",\"StationNumber: 18BCB26, Year: 2018, PEL ratio: 0.28634, Grade: F\",\"StationNumber: 18BCB37, Year: 2018, PEL ratio: 0.00425, Grade: A\",\"StationNumber: 18BCB42, Year: 2018, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 18BCB44, Year: 2018, PEL ratio: 0.00316, Grade: A\",\"StationNumber: 18BCB46, Year: 2018, PEL ratio: 0.01455, Grade: B\",\"StationNumber: 18HB14, Year: 2018, PEL ratio: 0.04307, Grade: C\",\"StationNumber: 18HB20, Year: 2018, PEL ratio: 0.05365, Grade: C\",\"StationNumber: 18HB21, Year: 2018, PEL ratio: 0.03344, Grade: C\",\"StationNumber: 18HB26, Year: 2018, PEL ratio: 0.03348, Grade: C\",\"StationNumber: 18HB29, Year: 2018, PEL ratio: 0.0738, Grade: C\",\"StationNumber: 18HB33, Year: 2018, PEL ratio: 0.05804, Grade: C\",\"StationNumber: 18HB38, Year: 2018, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 18HB41, Year: 2018, PEL ratio: 0.00774, Grade: B\",\"StationNumber: 18HB46, Year: 2018, PEL ratio: 1.04973, Grade: F\",\"StationNumber: 18LTB75, Year: 2018, PEL ratio: 0.12361, Grade: D\",\"StationNumber: 18LTB79, Year: 2018, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 18LTB81, Year: 2018, PEL ratio: 0.09621, Grade: D\",\"StationNumber: 18LTB82, Year: 2018, PEL ratio: 0.0782, Grade: C\",\"StationNumber: 18MR25, Year: 2018, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 18MR37, Year: 2018, PEL ratio: 0.06345, Grade: C\",\"StationNumber: 18MR46, Year: 2018, PEL ratio: 0.03519, Grade: C\",\"StationNumber: 18MTB41, Year: 2018, PEL ratio: 0.01539, Grade: B\",\"StationNumber: 18MTB42, Year: 2018, PEL ratio: 0.18686, Grade: D\",\"StationNumber: 18MTB48, Year: 2018, PEL ratio: 0.00879, Grade: B\",\"StationNumber: 18MTB56, Year: 2018, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 18OTB04, Year: 2018, PEL ratio: 0.06233, Grade: C\",\"StationNumber: 18OTB08, Year: 2018, PEL ratio: 0.003, Grade: A\",\"StationNumber: 18OTB13, Year: 2018, PEL ratio: 0.01252, Grade: B\",\"StationNumber: 18OTB14, Year: 2018, PEL ratio: 0.04092, Grade: C\",\"StationNumber: 18OTB15, Year: 2018, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 18OTB21, Year: 2018, PEL ratio: 0.00898, Grade: B\",\"StationNumber: 18OTB24, Year: 2018, PEL ratio: 0.00579, Grade: A\",\"StationNumber: 18TCB05, Year: 2018, PEL ratio: 0.03777, Grade: C\",\"StationNumber: 18TCB11, Year: 2018, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 18TCB14, Year: 2018, PEL ratio: 0.05688, Grade: C\",\"StationNumber: 18TCB15, Year: 2018, PEL ratio: 0.05947, Grade: C\",\"StationNumber: 18TCB21, Year: 2018, PEL ratio: 0.11579, Grade: D\",\"StationNumber: 18TCB22, Year: 2018, PEL ratio: 0.02805, Grade: C\",\"StationNumber: 19BCB27, Year: 2019, PEL ratio: 0.04772, Grade: C\",\"StationNumber: 19BCB29, Year: 2019, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 19BCB30, Year: 2019, PEL ratio: 0.1321, Grade: D\",\"StationNumber: 19BCB34, Year: 2019, PEL ratio: 0.51859, Grade: F\",\"StationNumber: 19BCB35, Year: 2019, PEL ratio: 0.05839, Grade: C\",\"StationNumber: 19BCB36, Year: 2019, PEL ratio: 0.11644, Grade: D\",\"StationNumber: 19BCB40, Year: 2019, PEL ratio: 0.00368, Grade: A\",\"StationNumber: 19BCB41, Year: 2019, PEL ratio: 0.0436, Grade: C\",\"StationNumber: 19BCB43, Year: 2019, PEL ratio: 0.09295, Grade: D\",\"StationNumber: 19BCB49, Year: 2019, PEL ratio: 0.05207, Grade: C\",\"StationNumber: 19BCB50, Year: 2019, PEL ratio: 0.0513, Grade: C\",\"StationNumber: 19HB09, Year: 2019, PEL ratio: 0.01191, Grade: B\",\"StationNumber: 19HB16, Year: 2019, PEL ratio: 0.69077, Grade: F\",\"StationNumber: 19HB25, Year: 2019, PEL ratio: 0.0126, Grade: B\",\"StationNumber: 19HB27, Year: 2019, PEL ratio: 0.05811, Grade: C\",\"StationNumber: 19HB32, Year: 2019, PEL ratio: 0.03805, Grade: C\",\"StationNumber: 19HB37, Year: 2019, PEL ratio: 0.06339, Grade: C\",\"StationNumber: 19HB39, Year: 2019, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 19HB40, Year: 2019, PEL ratio: 0.0131, Grade: B\",\"StationNumber: 19HB47, Year: 2019, PEL ratio: 0.00395, Grade: A\",\"StationNumber: 19LTB76, Year: 2019, PEL ratio: 0.00985, Grade: B\",\"StationNumber: 19LTB78, Year: 2019, PEL ratio: 0.01215, Grade: B\",\"StationNumber: 19LTB88, Year: 2019, PEL ratio: 0.11037, Grade: D\",\"StationNumber: 19LTB90, Year: 2019, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 19MR17, Year: 2019, PEL ratio: 0.01119, Grade: B\",\"StationNumber: 19MR18, Year: 2019, PEL ratio: 0.02367, Grade: C\",\"StationNumber: 19MR29, Year: 2019, PEL ratio: 0.02627, Grade: C\",\"StationNumber: 19MR33, Year: 2019, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 19MR43, Year: 2019, PEL ratio: 0.17714, Grade: D\",\"StationNumber: 19MR44, Year: 2019, PEL ratio: 0.15675, Grade: D\",\"StationNumber: 19MR52, Year: 2019, PEL ratio: 0.0116, Grade: B\",\"StationNumber: 19MTB36, Year: 2019, PEL ratio: 0.08261, Grade: C\",\"StationNumber: 19MTB47, Year: 2019, PEL ratio: 0.01131, Grade: B\",\"StationNumber: 19MTB54, Year: 2019, PEL ratio: 0.00976, Grade: B\",\"StationNumber: 19MTB62, Year: 2019, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 19OTB07, Year: 2019, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 19OTB18, Year: 2019, PEL ratio: 0.05206, Grade: C\",\"StationNumber: 19OTB20, Year: 2019, PEL ratio: 0.02767, Grade: C\",\"StationNumber: 19OTB23, Year: 2019, PEL ratio: 0.01054, Grade: B\",\"StationNumber: 19OTB25, Year: 2019, PEL ratio: 0.04412, Grade: C\",\"StationNumber: 19OTB29, Year: 2019, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 19OTB31, Year: 2019, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 19TCB01, Year: 2019, PEL ratio: 0.01901, Grade: B\",\"StationNumber: 19TCB20, Year: 2019, PEL ratio: 0.01996, Grade: B\",\"StationNumber: 20BCB10, Year: 2020, PEL ratio: 0.02055, Grade: C\",\"StationNumber: 20BCB17, Year: 2020, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 20BCB22, Year: 2020, PEL ratio: 0.20992, Grade: D\",\"StationNumber: 20BCB23, Year: 2020, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 20BCB35, Year: 2020, PEL ratio: 0.04529, Grade: C\",\"StationNumber: 20BCB37, Year: 2020, PEL ratio: 0.01213, Grade: B\",\"StationNumber: 20BCB40, Year: 2020, PEL ratio: 0.00479, Grade: A\",\"StationNumber: 20BCB43, Year: 2020, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 20BCB47, Year: 2020, PEL ratio: 0.01811, Grade: B\",\"StationNumber: 20BCB48, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20BCB49, Year: 2020, PEL ratio: 0.01004, Grade: B\",\"StationNumber: 20HB09, Year: 2020, PEL ratio: 0.04899, Grade: C\",\"StationNumber: 20HB10, Year: 2020, PEL ratio: 0.06714, Grade: C\",\"StationNumber: 20HB21, Year: 2020, PEL ratio: 0.1516, Grade: D\",\"StationNumber: 20HB26, Year: 2020, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 20HB38, Year: 2020, PEL ratio: 0.04319, Grade: C\",\"StationNumber: 20HB41, Year: 2020, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 20HB46, Year: 2020, PEL ratio: 0.01143, Grade: B\",\"StationNumber: 20HB47, Year: 2020, PEL ratio: 0.00625, Grade: A\",\"StationNumber: 20HB52, Year: 2020, PEL ratio: 0.0242, Grade: C\",\"StationNumber: 20LTB70, Year: 2020, PEL ratio: 0.01567, Grade: B\",\"StationNumber: 20LTB71, Year: 2020, PEL ratio: 0.03189, Grade: C\",\"StationNumber: 20LTB77, Year: 2020, PEL ratio: 0.01505, Grade: B\",\"StationNumber: 20LTB85, Year: 2020, PEL ratio: 0.02098, Grade: C\",\"StationNumber: 20MR08, Year: 2020, PEL ratio: 0.07608, Grade: C\",\"StationNumber: 20MR09, Year: 2020, PEL ratio: 0.09408, Grade: D\",\"StationNumber: 20MR33, Year: 2020, PEL ratio: 0.18328, Grade: D\",\"StationNumber: 20MR36, Year: 2020, PEL ratio: 0.01558, Grade: B\",\"StationNumber: 20MR44, Year: 2020, PEL ratio: 0.10315, Grade: D\",\"StationNumber: 20MR49, Year: 2020, PEL ratio: 0.12139, Grade: D\",\"StationNumber: 20MTB35, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20MTB46, Year: 2020, PEL ratio: 0.00585, Grade: A\",\"StationNumber: 20MTB52, Year: 2020, PEL ratio: 0.0217, Grade: C\",\"StationNumber: 20MTB63, Year: 2020, PEL ratio: 0.00437, Grade: A\",\"StationNumber: 20OTB13, Year: 2020, PEL ratio: 0.11907, Grade: D\",\"StationNumber: 20OTB14, Year: 2020, PEL ratio: 0.09905, Grade: D\",\"StationNumber: 20OTB15, Year: 2020, PEL ratio: 0.00718, Grade: A\",\"StationNumber: 20OTB19, Year: 2020, PEL ratio: 0.01134, Grade: B\",\"StationNumber: 20OTB21, Year: 2020, PEL ratio: 0.00212, Grade: A\",\"StationNumber: 20OTB24, Year: 2020, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 20OTB32, Year: 2020, PEL ratio: 0.00435, Grade: A\",\"StationNumber: 20TCB10, Year: 2020, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 20TCB12, Year: 2020, PEL ratio: 0.03948, Grade: C\",\"StationNumber: 20TCB20, Year: 2020, PEL ratio: 0.058, Grade: C\",\"StationNumber: 21BCB09, Year: 2021, PEL ratio: 0.11558, Grade: D\",\"StationNumber: 21BCB12, Year: 2021, PEL ratio: 0.01683, Grade: B\",\"StationNumber: 21BCB15, Year: 2021, PEL ratio: 0.05873, Grade: C\",\"StationNumber: 21BCB22, Year: 2021, PEL ratio: 0.01386, Grade: B\",\"StationNumber: 21BCB25, Year: 2021, PEL ratio: 0.00971, Grade: B\",\"StationNumber: 21BCB26, Year: 2021, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 21BCB29, Year: 2021, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 21BCB36, Year: 2021, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 21BCB41, Year: 2021, PEL ratio: 0.00501, Grade: A\",\"StationNumber: 21BCB44, Year: 2021, PEL ratio: 0.01104, Grade: B\",\"StationNumber: 21BCB50, Year: 2021, PEL ratio: 0.00475, Grade: A\",\"StationNumber: 21HB13, Year: 2021, PEL ratio: 0.05335, Grade: C\",\"StationNumber: 21HB19, Year: 2021, PEL ratio: 0.08665, Grade: D\",\"StationNumber: 21HB20, Year: 2021, PEL ratio: 0.02175, Grade: C\",\"StationNumber: 21HB27, Year: 2021, PEL ratio: 0.04735, Grade: C\",\"StationNumber: 21HB34, Year: 2021, PEL ratio: 0.01341, Grade: B\",\"StationNumber: 21HB36, Year: 2021, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 21HB37, Year: 2021, PEL ratio: 0.04959, Grade: C\",\"StationNumber: 21HB40, Year: 2021, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 21HB43, Year: 2021, PEL ratio: 0.03012, Grade: C\",\"StationNumber: 21LTB78, Year: 2021, PEL ratio: 0.02074, Grade: C\",\"StationNumber: 21LTB83, Year: 2021, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 21LTB84, Year: 2021, PEL ratio: 0.01135, Grade: B\",\"StationNumber: 21LTB89, Year: 2021, PEL ratio: 0.01185, Grade: B\",\"StationNumber: 21MR24, Year: 2021, PEL ratio: 0.0078, Grade: B\",\"StationNumber: 21MR29, Year: 2021, PEL ratio: 0.01739, Grade: B\",\"StationNumber: 21MR45, Year: 2021, PEL ratio: 0.06525, Grade: C\",\"StationNumber: 21MR47, Year: 2021, PEL ratio: 0.01081, Grade: B\",\"StationNumber: 21MR52, Year: 2021, PEL ratio: 0.01768, Grade: B\",\"StationNumber: 21MTB40, Year: 2021, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 21MTB43, Year: 2021, PEL ratio: 0.03909, Grade: C\",\"StationNumber: 21MTB48, Year: 2021, PEL ratio: 0.01998, Grade: B\",\"StationNumber: 21MTB62, Year: 2021, PEL ratio: 0.01841, Grade: B\",\"StationNumber: 21OTB08, Year: 2021, PEL ratio: 0.00752, Grade: A\",\"StationNumber: 21OTB12, Year: 2021, PEL ratio: 0.05583, Grade: C\",\"StationNumber: 21OTB13, Year: 2021, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 21OTB18, Year: 2021, PEL ratio: 0.01239, Grade: B\",\"StationNumber: 21OTB21, Year: 2021, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 21OTB25, Year: 2021, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 21OTB28, Year: 2021, PEL ratio: 0.00379, Grade: A\",\"StationNumber: 21TCB02, Year: 2021, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 21TCB13, Year: 2021, PEL ratio: 0.04086, Grade: C\",\"StationNumber: 21TCB22, Year: 2021, PEL ratio: 0.01641, Grade: B\",\"StationNumber: 21TCB26, Year: 2021, PEL ratio: 0.01436, Grade: B\",\"StationNumber: 22BCB02, Year: 2022, PEL ratio: 0.10158, Grade: D\",\"StationNumber: 22BCB05, Year: 2022, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 22BCB11, Year: 2022, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 22BCB12, Year: 2022, PEL ratio: 0.01548, Grade: B\",\"StationNumber: 22BCB17, Year: 2022, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 22BCB27, Year: 2022, PEL ratio: 0.02323, Grade: C\",\"StationNumber: 22BCB30, Year: 2022, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 22BCB34, Year: 2022, PEL ratio: 0.00532, Grade: A\",\"StationNumber: 22BCB35, Year: 2022, PEL ratio: 0.00406, Grade: A\",\"StationNumber: 22BCB45, Year: 2022, PEL ratio: 0.011, Grade: 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data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"Create colorized table water quality outcomes segment includes management action chlorophyll, light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(   epcdata,   txtsz = 3,   trgs = NULL,   yrrng = c(1975, 2023),   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   abbrev = FALSE,   family = NA,   historic = TRUE,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"function provides combined output show_wqmatrix show_matrix functions. one bay segment can plotted function call.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"Plot chlorophyll secchi data together matrix outcomes","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(   epcdata,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   yrrng = c(1975, 2023),   family = NULL,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" yrrng numeric year range plot family optional chr string indicating font family text labels partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"interactive plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"function combines outputs show_thrplot show_segmatrix selected bay segment. plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(epcdata)  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3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1975.5,1976.5,1976.5,1975.5,1975.5,null,1976.5,1977.5,1977.5,1976.5,1976.5,null,1977.5,1978.5,1978.5,1977.5,1977.5,null,1978.5,1979.5,1979.5,1978.5,1978.5,null,1979.5,1980.5,1980.5,1979.5,1979.5,null,1980.5,1981.5,1981.5,1980.5,1980.5,null,1981.5,1982.5,1982.5,1981.5,1981.5,null,1982.5,1983.5,1983.5,1982.5,1982.5,null,1984.5,1985.5,1985.5,1984.5,1984.5,null,1985.5,1986.5,1986.5,1985.5,1985.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: 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3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1988.5,1989.5,1989.5,1988.5,1988.5,null,1989.5,1990.5,1990.5,1989.5,1989.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1997.5,1998.5,1998.5,1997.5,1997.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2010.5,2011.5,2011.5,2010.5,2010.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,1974.5,1975.5,1975.5,1974.5,1974.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: large (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5,null,1975.5,1976.5,1976.5,1975.5,1975.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 3, Exceedance: large (size), NA 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Outcome: 3, Exceedance: large (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1987.5,1988.5,1988.5,1987.5,1987.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1996.5,1997.5,1997.5,1996.5,1996.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1992.5,1993.5,1993.5,1992.5,1992.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998.5,1999.5,1999.5,1998.5,1998.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2015.5,2016.5,2016.5,2015.5,2015.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 1, la: 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1975<br />yval: 0.9780952<br />\",\"yr: 1976<br />yval: 1.1759318<br />\",\"yr: 1977<br />yval: 1.1896016<br />\",\"yr: 1978<br />yval: 1.1682173<br />\",\"yr: 1979<br />yval: 1.7595230<br />\",\"yr: 1980<br />yval: 1.3836268<br />\",\"yr: 1981<br />yval: 1.0469025<br />\",\"yr: 1982<br />yval: 1.0583860<br />\",\"yr: 1983<br />yval: 1.1152678<br />\",\"yr: 1984<br />yval: 1.1617502<br />\",\"yr: 1985<br />yval: 0.9534905<br />\",\"yr: 1986<br />yval: 0.8929313<br />\",\"yr: 1987<br />yval: 0.8536198<br />\",\"yr: 1988<br />yval: 0.8558599<br />\",\"yr: 1989<br />yval: 0.9374651<br />\",\"yr: 1990<br />yval: 0.8353229<br />\",\"yr: 1991<br />yval: 0.8031788<br />\",\"yr: 1992<br />yval: 0.8166729<br />\",\"yr: 1993<br />yval: 0.9133746<br />\",\"yr: 1994<br />yval: 0.7481484<br />\",\"yr: 1995<br />yval: 0.9379637<br />\",\"yr: 1996<br />yval: 0.9202700<br />\",\"yr: 1997<br />yval: 0.8473840<br />\",\"yr: 1998<br />yval: 1.0612729<br />\",\"yr: 1999<br />yval: 0.8801655<br />\",\"yr: 2000<br />yval: 0.7328166<br />\",\"yr: 2001<br />yval: 0.9512714<br />\",\"yr: 2002<br />yval: 0.9272802<br />\",\"yr: 2003<br />yval: 1.0370998<br />\",\"yr: 2004<br />yval: 0.8777406<br />\",\"yr: 2005<br />yval: 0.7693579<br />\",\"yr: 2006<br />yval: 0.6204267<br />\",\"yr: 2007<br />yval: 0.6771304<br />\",\"yr: 2008<br />yval: 0.6962244<br />\",\"yr: 2009<br />yval: 0.8076962<br />\",\"yr: 2010<br />yval: 0.8419635<br />\",\"yr: 2011<br />yval: 0.9122183<br />\",\"yr: 2012<br />yval: 0.6867633<br />\",\"yr: 2013<br />yval: 0.5674502<br />\",\"yr: 2014<br />yval: 0.6056886<br />\",\"yr: 2015<br />yval: 0.5604978<br />\",\"yr: 2016<br />yval: 0.5747356<br />\",\"yr: 2017<br />yval: 0.6821210<br />\",\"yr: 2018<br />yval: 0.6780425<br />\",\"yr: 2019<br />yval: 0.7396049<br />\",\"yr: 2020<br />yval: 0.7686231<br />\",\"yr: 2021<br />yval: 0.7783039<br />\",\"yr: 2022<br />yval: 0.7871073<br />\",\"yr: 2023<br />yval: 0.7344259<br 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Light Atten. 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Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"Map site bay segment attainment categories selected year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(   epcdata,   yrsel,   param = c(\"chla\", \"la\"),   trgs = NULL,   thrs = FALSE,   partialyr = FALSE,   base_size = 12,   family = NA )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"epcdata data frame epc data returned read_importwq yrsel numeric year plot param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation trgs optional data.frame annual bay segment water quality targets, defaults targets thrs logical indicating attainment category relative targets (default) thresholds, passed anlz_attainsite partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter base_size numeric indicating text scaling size plot family optional chr string indicating font family text labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"map similar returned show_sitemap addition polygons bay segment colored annual attainment category site points sized relative selected parameter param.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(epcdata, yrsel = 2023) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Plot matrix Tampa Bay Benthic Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"show_tbbimatrix(   tbbiscr,   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"),   yrrng = c(1993, 2022),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"ggplot object showing trends time TBBI scores bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\").","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) show_tbbimatrix(tbbiscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"Plot matrix Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"show_tbnimatrix(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   perc = c(32, 46),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"ggplot object showing trends time TBNI scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbnimatrix(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"Plot Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"show_tbniscr(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   perc = c(32, 46),   alph = 1,   ylim = c(22, 58),   rev = FALSE,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"tbniscr input dat frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscr(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"Plot Tampa Bay Nekton Index scores time average across bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"show_tbniscrall(   tbniscr,   perc = c(32, 46),   alph = 1,   ylim = c(22, 58),   rev = FALSE,   plotly = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"tbniscr input dat frame returned anlz_tbniscr perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscrall(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"Creates plotly object TBNI score plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"show_tbniscrplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"p ggplot object output show_tbniscr show_tbniscrall width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) p <- show_tbniscrall(tbniscr) show_tbniscrplotly(p)  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2010<br />TBNI_Score - seval: 47.60934<br />TBNI_Score + seval: 50.39066\",\"Year: 2011<br />TBNI_Score - seval: 46.50183<br />TBNI_Score + seval: 49.49817\",\"Year: 2012<br />TBNI_Score - seval: 43.50750<br />TBNI_Score + seval: 46.49250\",\"Year: 2013<br />TBNI_Score - seval: 45.54410<br />TBNI_Score + seval: 48.45590\",\"Year: 2014<br />TBNI_Score - seval: 47.54311<br />TBNI_Score + seval: 50.45689\",\"Year: 2015<br />TBNI_Score - seval: 50.54042<br />TBNI_Score + seval: 53.45958\",\"Year: 2016<br />TBNI_Score - seval: 50.54140<br />TBNI_Score + seval: 53.45860\",\"Year: 2017<br />TBNI_Score - seval: 47.53068<br />TBNI_Score + seval: 50.46932\",\"Year: 2018<br />TBNI_Score - seval: 46.51340<br />TBNI_Score + seval: 49.48660\",\"Year: 2019<br />TBNI_Score - seval: 44.52515<br />TBNI_Score + seval: 47.47485\",\"Year: 2020<br />TBNI_Score - seval: 46.47367<br />TBNI_Score + seval: 49.52633\",\"Year: 2021<br />TBNI_Score - seval: 40.58822<br />TBNI_Score + seval: 43.41178\",\"Year: 2022<br />TBNI_Score - seval: 40.63419<br />TBNI_Score + seval: 43.36581\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2022<br />TBNI_Score - seval: 40.63419<br />TBNI_Score + seval: 43.36581\",\"Year: 2021<br />TBNI_Score - seval: 40.58822<br />TBNI_Score + seval: 43.41178\",\"Year: 2020<br />TBNI_Score - seval: 46.47367<br />TBNI_Score + seval: 49.52633\",\"Year: 2019<br />TBNI_Score - seval: 44.52515<br />TBNI_Score + seval: 47.47485\",\"Year: 2018<br />TBNI_Score - seval: 46.51340<br />TBNI_Score + seval: 49.48660\",\"Year: 2017<br />TBNI_Score - seval: 47.53068<br />TBNI_Score + seval: 50.46932\",\"Year: 2016<br />TBNI_Score - seval: 50.54140<br />TBNI_Score + seval: 53.45860\",\"Year: 2015<br />TBNI_Score - seval: 50.54042<br />TBNI_Score + seval: 53.45958\",\"Year: 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49\",\"Year: 2011<br />TBNI_Score: 48\",\"Year: 2012<br />TBNI_Score: 45\",\"Year: 2013<br />TBNI_Score: 47\",\"Year: 2014<br />TBNI_Score: 49\",\"Year: 2015<br />TBNI_Score: 52\",\"Year: 2016<br />TBNI_Score: 52\",\"Year: 2017<br />TBNI_Score: 49\",\"Year: 2018<br />TBNI_Score: 48\",\"Year: 2019<br />TBNI_Score: 46\",\"Year: 2020<br />TBNI_Score: 48\",\"Year: 2021<br />TBNI_Score: 42\",\"Year: 2022<br />TBNI_Score: 42\",\"Year: 2023<br />TBNI_Score: 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show_tdlcrk","text":"Make map tidal creek report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"show_tdlcrk(dat, weight = 1.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for tidal creek report card — show_tdlcrk","text":"dat input creek score data returned anlz_tdlcrk weight numeric weight polylines, passed addPolylines","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for tidal creek report card — show_tdlcrk","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrk(dat)  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MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addLegend\",\"args\":[{\"colors\":[\"#ADD8E6\",\"#2DC938\",\"#E9C318\",\"#EE7600\",\"#FF4040\"],\"labels\":[\"No Data\",\"Monitor\",\"Caution\",\"Investigate\",\"Prioritize\"],\"na_color\":null,\"na_label\":\"NA\",\"opacity\":1,\"position\":\"topright\",\"type\":\"factor\",\"title\":\"Creek scores\",\"extra\":null,\"layerId\":null,\"className\":\"info 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Monitor\",\"WBID: 2073, JEI: CC110, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2074B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2077, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC15, Name: Rock Creek, Creek score: No Data\",\"WBID: 2045, JEI: CC15, Name: Rock Creek, Creek score: Monitor\",\"WBID: 1991B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2010B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2025, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2043, JEI: CC16, Name: Apollo Waterway, Creek score: Monitor\",\"WBID: 1991A, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC18, Name: Sam Knight Creek, Creek score: Monitor\",\"WBID: 2055, JEI: CC18, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC25, Name: NA, Creek score: Investigate\",\"WBID: 2060A1, JEI: CC26, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC28, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2046, JEI: CC31, Name: NA, Creek score: Monitor\",\"WBID: 2056D, JEI: CC34, Name: Little Alligator Creek, Creek score: No Data\",\"WBID: 2056E, JEI: CC34, Name: Little Alligator Creek, Creek score: Monitor\",\"WBID: 2056D, JEI: CC36, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC36, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC37, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC40, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC41, Name: NA, Creek score: No Data\",\"WBID: 2056B, JEI: CC42, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC42, Name: NA, Creek score: Monitor\",\"WBID: 2056C2, JEI: CC44, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC45, Name: NA, Creek score: Prioritize\",\"WBID: 2056E, JEI: CC45, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC46, Name: NA, Creek score: No Data\",\"WBID: 2056C1, JEI: CC47, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2080, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2087, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC49, Name: NA, Creek score: No Data\",\"WBID: 1991A, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2053, JEI: CC50, Name: NA, Creek score: Monitor\",\"WBID: 2055, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC51, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC52, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC53, Name: Myrtle Slough, Creek score: No Data\",\"WBID: 2054, JEI: CC53, Name: Myrtle Slough, Creek score: Monitor\",\"WBID: 2041A, JEI: CC54, Name: NA, Creek score: No Data\",\"WBID: 2059, JEI: CC55, Name: NA, Creek score: Monitor\",\"WBID: 2059, JEI: CC56, Name: NA, Creek score: Investigate\",\"WBID: 2062, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2063, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2065A, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC62, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2063, JEI: CC64, Name: North Fork Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC64, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2074, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2077, JEI: CC65, Name: Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2074B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2077, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2081, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2081, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2084, JEI: CC67, Name: South Silcox Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2086, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2088, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC70, Name: Pirate Canal, Creek score: No Data\",\"WBID: 2082A, JEI: CC70, Name: Pirate Canal, Creek score: Monitor\",\"WBID: 2065B, JEI: CC71, Name: NA, Creek score: No Data\",\"WBID: 2094, JEI: CC72, Name: Bear Branch, Creek score: No Data\",\"WBID: 2093A, JEI: CC73, Name: Hog Branch, Creek score: No Data\",\"WBID: 2079, JEI: CC74, Name: Whidden Creek, Creek score: Monitor\",\"WBID: 2065B, JEI: CC75, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 1983B, JEI: CC77, Name: Lemon Creek, Creek score: Monitor\",\"WBID: 2076, JEI: CC77, Name: Lemon Creek, Creek score: Prioritize\",\"WBID: 2089, JEI: CC78, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC80, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC81, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC82, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC83, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC84, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC85, Name: NA, Creek score: No Data\",\"WBID: 2065A, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC87, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC88, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC89, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC90, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048C, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC95, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC96, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC97, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC99, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC01, Name: NA, Creek score: No Data\",\"WBID: 2033, JEI: DC01, Name: NA, Creek score: Monitor\",\"WBID: 1623A, JEI: DC02, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC03, Name: NA, Creek score: No Data\",\"WBID: 2028, JEI: DC03, Name: NA, Creek score: Prioritize\",\"WBID: 1623A, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC07, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC08, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2035, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2056C1, JEI: DC11, Name: NA, Creek score: No Data\",\"WBID: 1513E, JEI: HC01, Name: Double Branch Creek, Creek score: Monitor\",\"WBID: 1513F, JEI: HC01, Name: Double Branch Creek, Creek score: No Data\",\"WBID: 1513E, JEI: HC02, Name: NA, Creek score: Monitor\",\"WBID: 1513F, JEI: HC02, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC03, Name: Channel A, Creek score: No Data\",\"WBID: 1507A, JEI: HC03, Name: Channel A, Creek score: Monitor\",\"WBID: 1563, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1581, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1516, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1558I, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1563, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1558I, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1563, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1587A, JEI: HC06, Name: Woods Creek, Creek score: Monitor\",\"WBID: 1558I, JEI: HC07, Name: Peppermound Creek, Creek score: No Data\",\"WBID: 1577A, JEI: HC07, Name: Peppermound Creek, Creek score: Monitor\",\"WBID: 1570, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1570A, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1601A, JEI: HC08, Name: Sweetwater Creek, Creek score: No Data\",\"WBID: 1594, JEI: HC09, Name: Fish Creek, Creek score: Monitor\",\"WBID: 1606, JEI: HC10, Name: Lemon Street Ditch, Creek score: No Data\",\"WBID: 1536E, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1584A1, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1536A, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC16, Name: Ironhead Creek, Creek score: Prioritize\",\"WBID: 1605, JEI: HC17, Name: Delaney Creek, Creek score: Monitor\",\"WBID: 1605D, JEI: HC17, Name: Delaney Creek, Creek score: Investigate\",\"WBID: 1636, JEI: HC18, Name: Port Sutton Ditch, Creek score: Prioritize\",\"WBID: 1637, JEI: HC18, Name: Port Sutton Ditch, Creek score: No Data\",\"WBID: 1636, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1605, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1628, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1632, JEI: HC20, Name: Delaney Creek Popoff, Creek score: Monitor\",\"WBID: 1558E, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628A, JEI: HC21, Name: North Archie Creek, Creek score: Monitor\",\"WBID: 1632, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC22, Name: South Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC22, Name: South Archie Creek, Creek score: Investigate\",\"WBID: 1628A, JEI: HC22, Name: South Archie Creek, Creek score: Monitor\",\"WBID: 1635B, JEI: HC23, Name: Buckhorn Creek, Creek score: Monitor\",\"WBID: 1659, JEI: HC24, Name: Rice Creek, Creek score: Monitor\",\"WBID: 1558D, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1666, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1666A, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1686, JEI: HC25, Name: Bullfrog Creek, Creek score: Prioritize\",\"WBID: 1688, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1693, JEI: HC26, Name: Jackson Branch, Creek score: No Data\",\"WBID: 1693, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1708, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1712, JEI: HC28, Name: Beever Creek, Creek score: No Data\",\"WBID: 1719, JEI: HC29, Name: NA, Creek score: Prioritize\",\"WBID: 1725, JEI: HC30, Name: NA, Creek score: No Data\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1736, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1558C, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1725, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1736, JEI: HC32, Name: Wolf Branch, Creek score: Monitor\",\"WBID: 1742A1, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747A, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747B, JEI: HC33, Name: Marsh Branch, Creek score: Prioritize\",\"WBID: 1742C1, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC34, Name: Curiosity Creek, Creek score: Investigate\",\"WBID: 1798, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC35, Name: NA, Creek score: Caution\",\"WBID: 1779, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1742C1, JEI: HC37, Name: Sun City Slough, Creek score: No Data\",\"WBID: 1771, JEI: HC37, Name: Sun City Slough, Creek score: Caution\",\"WBID: 1778, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1788, JEI: HC38, Name: Cockroach Creek, Creek score: Prioritize\",\"WBID: 1789, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1789, JEI: HC39, Name: Piney Point Creek, Creek score: Prioritize\",\"WBID: 1797B, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1816, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC40, Name: Coon Hammock Creek\\r\\n, Creek score: No Data\",\"WBID: 1621G, JEI: HC41, Name: NA, Creek score: No Data\",\"WBID: 1558I, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1566, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1609, JEI: HC44, Name: Gun Branch, Creek score: No Data\",\"WBID: 1558G, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1609, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1584A1, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1584B, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1664, JEI: HC48, Name: Gibsonton Creek, Creek score: No Data\",\"WBID: 1558D, JEI: HC49, Name: Dug Creek, Creek score: No Data\",\"WBID: 1676A, JEI: HC49, Name: Dug Creek, Creek score: Caution\",\"WBID: 1682, JEI: HC50, Name: Kitchen Branch, Creek score: Monitor\",\"WBID: 1691, JEI: HC51, Name: Sims Branch, Creek score: No Data\",\"WBID: 1778, JEI: HC52, Name: Andrews Creek, Creek score: No Data\",\"WBID: 1682, JEI: HC53, Name: NA, Creek score: Monitor\",\"WBID: 1558C, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 2065D, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2082B, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B1, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2093A, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B, JEI: LC02, Name: Yucca Pen Creek, Creek score: Prioritize\",\"WBID: 2082B2, JEI: LC02, Name: Yucca Pen Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC03, Name: Durden Creek, Creek score: No Data\",\"WBID: 2082C, JEI: LC03, Name: Durden Creek, Creek score: Investigate\",\"WBID: 2082C1, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2082C2, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2082C1, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2065F, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC07, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC08, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC10, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240A1, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240EA, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240E1, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240EB, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240B, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240EA, JEI: LC21, Name: Powell Creek, Creek score: Investigate\",\"WBID: 3240L, JEI: LC21, Name: Powell Creek, Creek score: Monitor\",\"WBID: 2082C, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240B, JEI: LC22, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC23, Name: Daughtrey Creek, Creek score: No Data\",\"WBID: 3240F, JEI: LC23, Name: Daughtrey Creek, Creek score: Monitor\",\"WBID: 3240B1, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240F, JEI: LC24, Name: NA, Creek score: No Data\",\"WBID: 3240B1, JEI: LC25, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC25, Name: NA, Creek score: No Data\",\"WBID: 3240Q, JEI: LC26, Name: Popash Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240M, JEI: LC27, Name: Stroud Creek, Creek score: Monitor\",\"WBID: 3240Q, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240C, JEI: LC28, Name: Palm Creek, Creek score: No Data\",\"WBID: 3240C1, JEI: LC28, Name: Palm Creek, Creek score: Monitor\",\"WBID: 3240G, JEI: LC29, Name: Owl Creek, Creek score: No Data\",\"WBID: 3240N, JEI: LC29, Name: Owl Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC30, Name: Trout Creek, Creek score: No Data\",\"WBID: 3240G, JEI: LC30, Name: Trout Creek, Creek score: Monitor\",\"WBID: 3236A, JEI: LC31, Name: Telegraph Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC33, Name: Orange River, Creek score: No Data\",\"WBID: 3240K, JEI: LC33, Name: Orange River, Creek score: Monitor\",\"WBID: 3240B, JEI: LC35, Name: Billy Creek, Creek score: No Data\",\"WBID: 3240J1, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J2, JEI: LC35, Name: Billy Creek, Creek score: Investigate\",\"WBID: 3240J3, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J4, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC36, Name: Manuel Branch, Creek score: No Data\",\"WBID: 3240V, JEI: LC36, Name: Manuel Branch, Creek score: Monitor\",\"WBID: 3240H1, JEI: LC39, Name: Whiskey Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC40, Name: NA, Creek score: Monitor\",\"WBID: 3240A4, JEI: LC40, Name: NA, Creek score: Caution\",\"WBID: 3240A4, JEI: LC43, Name: NA, Creek score: No Data\",\"WBID: 3240O, JEI: LC44, Name: NA, Creek score: No Data\",\"WBID: 3258A1, JEI: LC45, Name: Cow Creek, Creek score: No Data\",\"WBID: 3258B2, JEI: LC46, Name: Hendry Creek, Creek score: Caution\",\"WBID: 3258X, JEI: LC46, Name: Hendry Creek, Creek score: No Data\",\"WBID: 3258C2, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258C4, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC47, Name: Mullock Creek, Creek score: No Data\",\"WBID: 3258D1, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258H2, JEI: LC49, Name: NA, Creek score: No Data\",\"WBID: 3258H2, JEI: LC50, Name: Spring Creek, Creek score: Caution\",\"WBID: 3258H3, JEI: LC50, Name: Spring Creek, Creek score: Monitor\",\"WBID: 3258EB, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EC, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258ED, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EG, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: No Data\",\"WBID: 3258F, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 2065F, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC54, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC55, Name: Underhill Creek, Creek score: No Data\",\"WBID: 2065F, JEI: LC56, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC58, Name: NA, Creek score: No Data\",\"WBID: 3258C4, JEI: LC59, Name: Mud Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC59, Name: Mud Creek, Creek score: No Data\",\"WBID: 3258C4, JEI: LC60, Name: NA, Creek score: No Data\",\"WBID: 1792, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1823, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1825A, JEI: MC02, Name: Frog Creek, Creek score: Investigate\",\"WBID: 1825B, JEI: MC02, Name: Frog Creek, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC04, Name: McMullen Creek, Creek score: No Data\",\"WBID: 1841, JEI: MC04, Name: McMullen Creek, Creek score: Monitor\",\"WBID: 1797A, JEI: MC05, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC06, Name: Palmetto Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC07, Name: King Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC08, Name: Memphis Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC09, Name: NA, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC09, Name: NA, Creek score: No Data\",\"WBID: 1848A, JEI: MC10, Name: NA, Creek score: Prioritize\",\"WBID: 1848B, JEI: MC10, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1850, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1872B, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1909, JEI: MC13, Name: Mill Creek, Creek score: No Data\",\"WBID: 1872A, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC14, Name: Gates Creek, Creek score: No Data\",\"WBID: 1874, JEI: MC14, Name: Gates Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC15, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC16, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC20, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1875, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1876, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1848B, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC26, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC27, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC28, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1876A, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1899, JEI: MC29, Name: Gap Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D2, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1876, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1887, JEI: MC30, Name: Sugarhouse Creek, Creek score: Monitor\",\"WBID: 1876, JEI: MC31, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848D2, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC33, Name: NA, Creek score: No Data\",\"WBID: 1885A, JEI: MC34, Name: Wares Creek, Creek score: Caution\",\"WBID: 1888A, JEI: MC34, Name: Wares Creek, Creek score: No Data\",\"WBID: 1888B, JEI: MC35, Name: Palma Sola Creek, Creek score: No Data\",\"WBID: 1883, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC37, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC38, Name: Cedar Hammock Creek, Creek score: No Data\",\"WBID: 1896, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1899, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1888A, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC41, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC42, Name: NA, Creek score: No Data\",\"WBID: 1868, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1883, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1901, JEI: MC44, Name: Williams Creek, Creek score: Monitor\",\"WBID: 1797B, JEI: MC45, Name: Little Redfish Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC46, Name: Peterson Creek, Creek score: No Data\",\"WBID: 1888A, JEI: MC47, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1618C, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1618D, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1625, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1641, JEI: PC02, Name: Cross Bayou, Creek score: Caution\",\"WBID: 1662, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1662, JEI: PC03, Name: NA, Creek score: Caution\",\"WBID: 1662A, JEI: PC03, Name: NA, Creek score: Monitor\",\"WBID: 1641, JEI: PC04, Name: Saint Joes Creek, Creek score: No Data\",\"WBID: 1668A, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668B, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668D, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668E, JEI: PC04, Name: Saint Joes Creek, Creek score: Prioritize\",\"WBID: 1701A, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1701B, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1716B, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716D, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716A, JEI: PC07, Name: NA, Creek score: Investigate\",\"WBID: 1716C1, JEI: PC07, Name: NA, Creek score: No Data\",\"WBID: 1716D, JEI: PC07, Name: NA, Creek score: Monitor\",\"WBID: 1731, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1731A, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1716C1, JEI: PC08, Name: NA, Creek score: Caution\",\"WBID: 1716D, JEI: PC08, Name: NA, Creek score: Monitor\",\"WBID: 1709D, JEI: PC09, Name: Bayou Creek, Creek score: Investigate\",\"WBID: 1558B, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1709, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731B, JEI: PC10, Name: Salt Creek, Creek score: Monitor\",\"WBID: 1696, JEI: PC12, Name: Booker Creek, Creek score: Monitor\",\"WBID: 1709B, JEI: PC12, Name: Booker Creek, Creek score: No Data\",\"WBID: 1661B, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661G, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661A, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661H, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661I, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661D, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1625, JEI: PC16, Name: Cross Bayou, Creek score: Monitor\",\"WBID: 1627, JEI: PC17, Name: Long Branch, Creek score: Monitor\",\"WBID: 1627B, JEI: PC17, Name: Long Branch, Creek score: Caution\",\"WBID: 1558H, JEI: PC18, Name: Allen Creek, Creek score: No Data\",\"WBID: 1604, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B1, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B2, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1575, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1575A, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1569, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1569A, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1546, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1558I, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1528B, JEI: PC22, Name: NA, Creek score: No Data\",\"WBID: 1668F, JEI: PC23, Name: NA, Creek score: Monitor\",\"WBID: 1694B, JEI: PC23, Name: NA, Creek score: No Data\",\"WBID: 1530, JEI: PC24, Name: Moccasin Creek, Creek score: Caution\",\"WBID: 1558H, JEI: PC25, Name: Grassy Creek, Creek score: No Data\",\"WBID: 1541A, JEI: PC26, Name: Briar Creek, Creek score: No Data\",\"WBID: 1541C, JEI: PC26, Name: Briar Creek, Creek score: Monitor\",\"WBID: 1479, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 8045G, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 1538, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1538A, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1550, JEI: PC28, Name: Curlew Creek, Creek score: No Data\",\"WBID: 1556, JEI: PC29, Name: Cedar Creek, Creek score: Caution\",\"WBID: 1556A, JEI: PC29, Name: Cedar Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1567C, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1633, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1633E, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1643, JEI: PC32, Name: Church Creek, Creek score: Prioritize\",\"WBID: 1508, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1508A, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1527A, JEI: PC34, Name: Bee Branch, Creek score: No Data\",\"WBID: 1527B, JEI: PC34, Name: Bee Branch, Creek score: Monitor\",\"WBID: 1535, JEI: PC35, Name: Minnow Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC36, Name: Spring Branch, Creek score: No Data\",\"WBID: 1567B, JEI: PC36, Name: Spring Branch, Creek score: Monitor\",\"WBID: 1528, JEI: PC37, Name: Rattlesnake Creek, Creek score: No Data\",\"WBID: 1614, JEI: PC37, Name: Rattlesnake Creek, Creek score: Prioritize\",\"WBID: 1936, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1936A, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1953, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1953A, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1968C, JEI: SC02, Name: Hudson Bayou, Creek score: No Data\",\"WBID: 1937, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1947, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1975D, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975C, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975A, JEI: SC06, Name: Clower Creek, Creek score: Investigate\",\"WBID: 1984A, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984AB, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984B, JEI: SC07, Name: Catfish/North Creek, Creek score: Monitor\",\"WBID: 1982, JEI: SC08, Name: South Creek, Creek score: Investigate\",\"WBID: 1982A, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1982B, JEI: SC08, Name: South Creek, Creek score: Prioritize\",\"WBID: 1985, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1924, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924B, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994B, JEI: SC12, Name: Shakett Creek, Creek score: Monitor\",\"WBID: 2002, JEI: SC12, Name: Shakett Creek, Creek score: Caution\",\"WBID: 2009B, JEI: SC14, Name: Curry Creek, Creek score: Caution\",\"WBID: 2009C, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2016, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2018A, JEI: SC14, Name: Curry Creek, Creek score: Monitor\",\"WBID: 2015, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 2015A, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 1983A1, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: No Data\",\"WBID: 2030, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: Caution\",\"WBID: 1983A1, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2042, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2039, JEI: SC22, Name: Forked Creek, Creek score: Monitor\",\"WBID: 1983B, JEI: SC25, Name: Gottfried Creek, Creek score: No Data\",\"WBID: 2049, JEI: SC25, Name: Gottfried Creek, Creek score: Caution\",\"WBID: 1991C, JEI: SC26, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC27, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 2038, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 2037, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 2036, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 2034, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC32, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC32, Name: NA, Creek score: Investigate\",\"WBID: 1991E, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2029, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 1991G, JEI: SC34, Name: NA, Creek score: No Data\",\"WBID: 2011, JEI: SC34, Name: NA, Creek score: Monitor\",\"WBID: 2006, JEI: SC35, Name: NA, Creek score: No Data\",\"WBID: 1978, JEI: SC36, Name: Deer Prairie Creek, Creek score: Monitor\",\"WBID: 1991E, JEI: SC36, Name: Deer Prairie Creek, Creek score: No Data\",\"WBID: 1991C, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991C, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2014, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2026, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 2026A, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 1991C, JEI: SC39, Name: NA, Creek score: No Data\",\"WBID: 1976B, JEI: SC40, Name: Big Slough Canal, Creek score: Investigate\",\"WBID: 1976C, JEI: SC40, Name: Big Slough Canal, Creek score: Monitor\",\"WBID: 2014, JEI: SC40, Name: Big Slough Canal, Creek score: No Data\",\"WBID: 1991B, JEI: SC41, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC42, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC43, Name: NA, Creek score: No Data\",\"WBID: 2057, JEI: SC43, Name: NA, Creek score: No Data\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[26.32829183658335,28.12975168603929],\"lng\":[-82.83757582032332,-81.68445583408415]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"Plotly barplots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"show_tdlcrkindic(   id,   cntdat,   yr = 2023,   thrsel = FALSE,   pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindic(id, cntdat, thrsel = TRUE)  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empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"Plotly empirical CDF plots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"show_tdlcrkindiccdf(   id,   cntdat,   yr = 2023,   thrsel = FALSE,   pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"function returns several empirical cumulative distribution plots tidal creek context indicators.  Points plot indicate observed values percentiles creek specified id. percentiles CDF values defined \"population\" creeks cntdat.  Points plots color-coded sample year evaluate temporal trends, .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindiccdf(id, cntdat, thrsel = TRUE)  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a line or annotation to a plotly graph — show_tdlcrkline","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"Add line annotation plotly graph tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"show_tdlcrkline(   varin = c(\"CHLAC\", \"TN\", \"chla_tn_ratio\", \"DO\", \"tsi\", \"no23_ratio\"),   thrsel = FALSE,   horiz = TRUE,   annotate = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"varin chr string indicator thrsel logical something returned, otherwise NULL, hack working plotly output horiz logical indicating output horizontal vertical annotate logical indicating output line annotation text","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"list object passed layout argument plotly, either shapes annotate depending user input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"function used internally within show_tdlcrkindic show_tdlcrkindiccdf","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"# code for vertical line output, chloropyll show_tdlcrkline('CHLAC', thrsel = TRUE) #> [[1]] #> [[1]]$type #> [1] \"line\" #>  #> [[1]]$x0 #> [1] 0 #>  #> [[1]]$x1 #> [1] 1 #>  #> [[1]]$xref #> [1] \"paper\" #>  #> [[1]]$y0 #> [1] 11 #>  #> [[1]]$y1 #> [1] 11 #>  #> [[1]]$line #> [[1]]$line$color #> [1] \"red\" #>  #> [[1]]$line$dash #> [1] 10 #>  #>  #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"Plot tidal creek report card matrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"show_tdlcrkmatrix(   dat,   class = c(\"3M\", \"2\"),   score = c(\"Prioritize\", \"Investigate\", \"Caution\", \"Monitor\"),   family = NA,   size = 11 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"dat input creek score data returned anlz_tdlcrk class character vector indicating creek classes show, one many '3M', '2', '3F', '1'.  Defaults marine ('3M', '2'). score character vector score categories include, one many 'Prioritize', 'Investigate', 'Caution', 'Monitor'. Defaults . family optional chr string indicating font family text labels size numeric text line scaling","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"static ggplot object returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"plot shows matrix rows individual creeks columns overall creek score.  columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories.  Number years mapped cell transparency.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkmatrix(dat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":null,"dir":"Reference","previous_headings":"","what":"Radar plots for tidal creek indicators — show_tdlcrkradar","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"Radar plots tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"show_tdlcrkradar(   id,   cntdat,   col = \"#338080E6\",   ptsz = 1,   lbsz = 0.8,   valsz = 1,   brdwd = 5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic col color input polygon line portions ptsz numeric size points lbsz numeric size text labels valsz numeric size numeric value labels brdwd numeric polygon border width","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"radar plot","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"See details anlz_tdlcrkindic explanation indicators Internal code borrowed heavily radarchart function fmsb package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = TRUE)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id, cntdat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"Plot annual water quality values, targets, thresholds bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(   epcdata,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   thr = c(\"chla\", \"la\"),   trgs = NULL,   yrrng = c(1975, 2023),   family = NA,   labelexp = TRUE,   txtlab = TRUE,   thrs = FALSE,   partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" thr chr string indicating water quality value appropriate target/threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets/thresholds, defaults targets yrrng numeric vector indicating min, max years include family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot thrs logical indicating reference lines shown regulatory threshold partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(epcdata, bay_segment = 'OTB', thr = 'chl')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot results for a seagrass transect by time and location — show_transect","title":"Plot results for a seagrass transect by time and location — show_transect","text":"Plot results seagrass transect time location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"show_transect(   transect,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   yrrng = c(1998, 2023),   varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"),   base_size = 12,   facet = FALSE,   ncol = NULL,   plotly = FALSE,   width = NULL,   height = NULL,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot results for a seagrass transect by time and location — show_transect","text":"transect data frame returned read_transect site chr string indicating site results plot species chr string indicating one many species plot yrrng numeric indicating year ranges evaluate varplo chr string indicating variable plot base_size numeric indicating text scaling size plot facet logical indicating plots separated facets species ncol numeric indicating number columns facet = TRUE plotly logical plot created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot results for a seagrass transect by time and location — show_transect","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot results for a seagrass transect by time and location — show_transect","text":"sites along transect surveyed shown plot, including selected species found.  latter colored grey hollow points.  Species options include Halodule, Syringodium, Thalassia, Halophila, Ruppia, Caulerpa (attached macroalgae), /Dapis (cyanobacteria). Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. Note plotly = TRUE, size legend shown.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # }  # one species show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance')   # multiple species, one plot show_transect(transect, site = 'S3T10',   species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia',     'Caulerpa', 'Dapis'),   varplo = 'Abundance')   # multiple species, multiple plots show_transect(transect, site = 'S3T10',   species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia',     'Caulerpa', 'Dapis'),   varplo = 'Abundance', facet = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Show annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"show_transectavespp(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   yrrng = c(1998, 2023),   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   total = TRUE,   alph = 1,   family = NA,   plotly = FALSE,   asreact = FALSE,   width = NULL,   height = NULL,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned, applies asreact = FALSE alph numeric indicating alpha value score category colors family optional chr string indicating font family text labels plotly logical matrix created using plotly asreact logical reactable table returned instead plot width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"asreact = F, ggplot plotly (plotly = T) object returned showing trends time species selected bay segments.  asreact = T, reactable table showing results year, segment, species returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Results based averages across species date transect bay segment. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"plot representation figure 2 Johansson, R. (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida. table representation table 2, p. 163 Yarbro, L. ., P. R. Carlson, Jr., eds. 2016. Seagrass Integrated Mapping Monitoring Program: Mapping Monitoring Report . 2. Fish Wildlife Research Institute Technical Report TR-17 version 2. vi + 281 p.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectavespp(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Show matrix seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"show_transectmatrix(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   total = TRUE,   neutral = FALSE,   yrrng = c(1998, 2023),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments neutral logical indicating neutral continuous color scheme used yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"ggplot object showing trends time bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Results based averages across species date transect bay segment color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence.  necessarily translate ecological breakpoints.  Use neutral = TRUE use neutral continuous color palette.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"plot representation Table 1 R. Johansson (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectmatrix(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"Plot frequency occurrence seagrass transect time species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"show_transectsum(   transectocc,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   yrrng = c(1998, 2023),   abund = FALSE,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"transectocc data frame returned anlz_transectocc site chr string indicating site results plot species chr string indicating species plot yrrng numeric indicating year ranges evaluate abund logical indicating abundance averages plotted instead frequency occurrence sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10')  {\"x\":{\"visdat\":{\"1b1965e8e3db\":[\"function () 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a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"Create colorized table chlorophyll light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(   epcdata,   param = c(\"chla\", \"la\"),   txtsz = 3,   trgs = NULL,   yrrng = c(1975, 2023),   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   asreact = FALSE,   nrows = 10,   abbrev = FALSE,   family = NA,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay stations by segment — stations","title":"Bay stations by segment — stations","text":"Bay stations segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay stations by segment — stations","text":"","code":"stations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay stations by segment — stations","text":"data frame 45 rows 4 variables: bay_segment chr epchc_station num Latitude num Longitude num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay subtidal cover — subtacres","title":"Tampa Bay subtidal cover — subtacres","text":"Tampa Bay subtidal cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"subtacres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay subtidal cover — subtacres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"if (FALSE) { # \\dontrun{ load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/subtacres.RData\"))  save(subtacres, file = 'data/subtacres.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"Spatial data object SWFWMD Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"swfwmdtbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"simple features sf object (MULTIPOLYGON) 7 features 1 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  levs <- c('oldTampaBay', 'hillsboroughBay', 'middleTampaBay',   'lowerTampaBay', 'bocaCiegaBay', 'terraCieaBay', 'manateeRiver') labs <- c('Old Tampa Bay', 'Hillsborough Bay', 'Middle Tampa Bay',   'Lower Tampa Bay', 'Boca Ciega Bay', 'Terra Ceia Bay', 'Manatee River')  swfwmdtbseg <- st_read(     dsn = 'T:/05_GIS/SWFWMD/Seagrass/2022_Seagrass/DraftMaps2022_1130.gdb',     layer = 'suncoastSeagrassSegments'   ) %>%   filter(waterbodyName %in% levs) %>%   mutate(     waterbodyName = factor(waterbodyName, levels = levs, labels = labs)   ) %>%   select(segment = waterbodyName) %>%   st_transform(crs = 4326)  save(swfwmdtbseg, file = 'data/swfwmdtbseg.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay segment targets — targets","title":"Bay segment targets — targets","text":"Bay segment specific management targets including low high magnitude exceedance thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay segment targets — targets","text":"","code":"targets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay segment targets — targets","text":"data frame 4 rows 8 variables: bay_segment chr name chr chla_target num chla_smallex num chla_thresh num la_target num la_smallex num la_thresh num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bay segment targets — targets","text":"","code":"if (FALSE) { # \\dontrun{  targets <- structure(list(    bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCBN\", \"BCBS\", \"TCB\", \"MR\", \"RALTB\"),    name = c(\"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\",       \"Boca Ciega Bay North\", \"Boca Ciega Bay South\", \"Terra Ceia Bay\", \"Manatee River\",       \"Remainder Lower Tampa Bay\"),    chla_target = c(8.5, 13.2, 7.4, 4.6, 7.7, 6.1, 7.5, 7.3, NaN),    chla_smallex = c(8.9, 14.1, 7.9, 4.8, NaN, NaN, NaN, NaN, NaN),    chla_thresh = c(9.3, 15, 8.5, 5.1, 8.3, 6.3, 8.7, 8.8, 5.1),    la_target = c(0.83, 1.58, 0.83, 0.63, NaN, NaN, NaN, NaN, NaN),    la_smallex = c(0.86, 1.63, 0.87, 0.66, NaN, NaN, NaN, NaN, NaN),    la_thresh = c(0.88, 1.67, 0.91, 0.68, NaN, NaN, NaN, NaN, NaN)),    class = \"data.frame\", row.names = c(NA, -9L)    )  save(targets, file = 'data/targets.RData') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"Reference conditions Tampa Bay Nekton Index metrics","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"tbniref"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"data frame 16 rows 12 variables: bay_segment chr Season chr NumTaxa_P5 num NumTaxa_P95 num BenthicTaxa_P5 num BenthicTaxa_P95 num TaxaSelect_P5 num TaxaSelect_P95 num NumGuilds_P5 num NumGuilds_P95 num Shannon_P5 num Shannon_P95 num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"if (FALSE) { # \\dontrun{  library(tbeptools)  tbniref <- anlz_tbnimet(fimdata) %>%   dplyr::filter(between(Year, 1998, 2015)) %>%   dplyr::select(Season, bay_segment, NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon) %>%   dplyr::group_by(bay_segment, Season) %>%   dplyr::summarize(NumTaxa_P5 = round(quantile(NumTaxa, probs = 0.05)),                    NumTaxa_P95 = round(quantile(NumTaxa, probs = 0.95)),                    BenthicTaxa_P5 = round(quantile(BenthicTaxa, probs = 0.05)),                    BenthicTaxa_P95 = round(quantile(BenthicTaxa, probs = 0.95)),                    TaxaSelect_P5 = round(quantile(TaxaSelect, probs = 0.05)),                    TaxaSelect_P95 = round(quantile(TaxaSelect, probs = 0.95)),                    NumGuilds_P5 = round(quantile(NumGuilds, probs = 0.05)),                    NumGuilds_P95 = round(quantile(NumGuilds, probs = 0.95)),                    Shannon_P5 = quantile(Shannon, probs = 0.05),                    Shannon_P95 = quantile(Shannon, probs = 0.95))  save(tbniref, file = 'data/tbniref.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"Reference table Tampa Bay Nekton Index species classifications","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"tbnispp"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"data frame 196 rows 10 variables: TSN int NODCCODE chr ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  # import and clean tbnispp <- read.csv('../tbni-proc/data/TBIndex_spp_codes.csv',     header = TRUE, stringsAsFactors = FALSE) %>%   mutate(     NODCCODE = as.character(NODCCODE),     NODCCODE = case_when(NODCCODE == \"9.998e+09\" ~ \"9998000000\",                              TRUE ~ NODCCODE)   )  save(tbnispp, file = 'data/tbnispp.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments — tbseg","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Note boundaries used formal analysis used visual aids mapping.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"tbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments — tbseg","text":"simple features sf object (POLYGON) 4 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Spatial data object Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE plot(st_geometry(tbseg))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"Note boundaries used formal analysis used visual aids mapping. data object differs tbseg including Boca Ciega Bay, Terra Ceia Bay, Manatee River. boundaries also detailed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"","code":"tbsegdetail"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"Spatial data object detailed Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"","code":"library(sf) plot(st_geometry(tbsegdetail))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"Spatial data object lines defining major Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"tbseglines"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"simple features sf object (LINESTRING) 3 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"library(sf) plot(st_geometry(tbseglines))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"Spatial data object Tampa Bay segments plus waterhseds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"tbsegshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"library(sf) plot(st_geometry(tbsegshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay watershed — tbshed","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"Spatial data object Tampa Bay watershed, includes bay proper","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"tbshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"simple features sf object (POLYGON) 1 feature 0 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"library(sf) if (FALSE) { # \\dontrun{ library(dplyr) tbshed <- st_read('T:/05_GIS/BOUNDARIES/TBEP_Watershed_Correct_Projection.shp') %>%   select(-Id, -Name, -Area_m, -Hectares) %>%   st_transform(crs = 4326)  save(tbshed, file = 'data/tbshed.RData', compress = 'xz') } # } plot(st_geometry(tbshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"tidalcreeks"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"simple features sf object (MULTILINESTRING) 615 features  fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs id num wbid chr JEI chr class chr name chr Creek_Length_m num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"File created using workflow <https://tbep-tech.github.io/tidalcreek-stats/Creek_select_tbeptools>, example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  prj <- 4326  # create sf object of creek population, join with creek length data tidalcreeks <- st_read(   dsn = '../../02_DOCUMENTS/tidal_creeks/TidalCreek_ALL_Line_WBID61.shp',   drivers = 'ESRI Shapefile'   ) %>%   st_transform(crs = prj) %>%   mutate(     id = 1:nrow(.)   ) %>%   select(id, name = Name, JEI = CreekID, wbid = WBID, class = CLASS, Creek_Length_m = Total_m)  # save save(tidalcreeks, file = 'data/tidalcreeks.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidal creek nitrogen targets — tidaltargets","title":"Tidal creek nitrogen targets — tidaltargets","text":"Tidal creek nitrogen targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidal creek nitrogen targets — tidaltargets","text":"","code":"tidaltargets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tidal creek nitrogen targets — tidaltargets","text":"data frame 2 rows 4 variables: region chr prioritize num investigate num caution num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"Seagrass transect data Tampa Bay current 04122024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"transect"},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"data frame 152580 rows 11 variables: Crew chr MonitoringAgency chr Date Date Transect chr Site chr Depth int Savspecies chr SeagrassEdge num var chr aveval num sdval num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"if (FALSE) { # \\dontrun{  transect <- read_transect()  save(transect, file = 'data/transect.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect locations — trnlns","title":"Seagrass transect locations — trnlns","text":"Seagrass transect locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect locations — trnlns","text":"","code":"trnlns"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect locations — trnlns","text":"sf LINESTRING object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect locations — trnlns","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  trnlns <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/transect_routes.shp') %>%    st_transform(crs = 4326) %>%    dplyr::filter(!as.character(Site) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) %>%    dplyr::mutate_if(is.factor, as.character) %>%    dplyr::filter(Site %in% trnpts$TRAN_ID)  # add bearing, positive counter-clockwise from east bearing <- lapply(trnlns$geometry, function(x) geosphere::bearing(x[, c(1:2)])[[1]]) %>%   unlist()  trnlns$bearing <- bearing  save(trnlns, file = 'data/trnlns.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect starting locations — trnpts","title":"Seagrass transect starting locations — trnpts","text":"Seagrass transect starting locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect starting locations — trnpts","text":"","code":"trnpts"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect starting locations — trnpts","text":"sf POINT object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect starting locations — trnpts","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tbeptools)  trnpts <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/TransectBasics2019.shp') %>%    st_transform(crs = 4326) %>%    dplyr::rename(MonAgency = 'MON_AGENCY') %>%    dplyr::filter(!as.character(TRAN_ID) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2'))  # s4t10 is slightly outside boundary for lower tampa bay s4t10 <- trnpts %>%    dplyr::filter(TRAN_ID %in% 'S4T10') %>%    dplyr::mutate(bay_segment = 'LTB')  trnpts <- trnpts %>%    sf::st_intersection(sf::st_make_valid(tbsegshed)) %>%    dplyr::select(-long_name) %>%    dplyr::mutate_if(is.factor, as.character) %>%    dplyr::bind_rows(s4t10)  save(trnpts, file = 'data/trnpts.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":null,"dir":"Reference","previous_headings":"","what":"Return leaflet icon set for FIB maps — util_fibicons","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"Return leaflet icon set FIB maps","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"","code":"util_fibicons(indic)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"indic character indicating \"entero\", \"fcolif\", \"fibmat\" Enterococcus, Fecal Coliform, FIB matrix maps, respectively","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"leaflet icon set returned iconList.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"Used internally show_enteromap wet/dry icons Enterococcus, show_fibmap E. Coli/Enterococcus icons (EPCHC data), show_fibmatmap matrix annual score category icons EPCHC non-EPCHC data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"","code":"util_fibicons(indic = 'entero') #> $entero_green_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_green_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\" util_fibicons(indic = 'fcolif') #> $ecoli_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\" util_fibicons(indic = 'fibmat') #> $fibmat_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_purple #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_purple.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":null,"dir":"Reference","previous_headings":"","what":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"list Fecal Indicator Bacteria (FIB) factor levels labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"","code":"util_fiblevs()"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"list levels (often cutpoints) labels FIB categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"","code":"util_fiblevs() #> $ecolilev #> [1] -Inf  126  410 1000  Inf #>  #> $ecolilbs #> [1] \"< 126\"     \"126 - 409\" \"410 - 999\" \"> 999\"     #>  #> $enterolev #> [1] -Inf   35  130 1000  Inf #>  #> $enterolbs #> [1] \"< 35\"      \"35 - 129\"  \"130 - 999\" \"> 999\"     #>  #> $fibmatlev #> [1] \"A\" \"B\" \"C\" \"D\" \"E\" #>  #> $fibmatlbs #> [1] \"A\" \"B\" \"C\" \"D\" \"E\" #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert character string to html class — util_html","title":"Convert character string to html class — util_html","text":"Convert character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert character string to html class — util_html","text":"","code":"util_html(text)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert character string to html class — util_html","text":"text character string input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert character string to html class — util_html","text":"input character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert character string to html class — util_html","text":"Adapted HTML","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert character string to html class — util_html","text":"","code":"util_html('abd') #> abd"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an empty leaflet map from sf input — util_map","title":"Create an empty leaflet map from sf input — util_map","text":"Create empty leaflet map sf input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"util_map(tomap, minimap = \"bottomleft\")"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an empty leaflet map from sf input — util_map","text":"tomap sf input object minimap character string indicating location minimap, use minimap = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an empty leaflet map from sf input — util_map","text":"leaflet object optional minimap ESRI provider tiles","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"tomap <- tibble::tibble(   lon = -82.6365,   lat = 27.75822   ) tomap <- sf::st_as_sf(tomap, coords = c('lon', 'lat'), crs = 4326) util_map(tomap)  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.75822,-82.6365,27.75822,-82.6365,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]}]},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":null,"dir":"Reference","previous_headings":"","what":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"Get organization name organization identifier USEPA Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin(org, stanm = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"org chr string indicating organization identifier, see read_importwqp valid entries stanm logical indicating character string column name specific organization returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"character string organization name corresponds organization identifier column name station identifier specific organization stanm = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin('21FLHILL_WQX') #> [1] \"Hillsborough\" util_orgin('21FLPASC_WQX', stanm = TRUE) #> [1] \"pasco_station\""}]
+[{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to tbeptools","title":"Contributing to tbeptools","text":"outlines propose change tbeptools. detailed info contributing , please see development contributing guide.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to tbeptools","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES: edit roxygen comment .R file R/. : edit .Rd file man/.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"Contributing to tbeptools","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"Contributing to tbeptools","text":"recommend create Git branch pull request (PR). Look Travis AppVeyor build status making changes. README contain badges continuous integration services used package. New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to tbeptools","text":"Please note tbeptools project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"see-tidyverse-development-contributing-guide","dir":"","previous_headings":"","what":"See tidyverse development contributing guide","title":"Contributing to tbeptools","text":"details.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/ISSUE_TEMPLATE.html","id":null,"dir":"","previous_headings":"","what":"Issues reporting guide","title":"Issues reporting guide","text":"Please briefly describe problem output expect. question, please don’t use form. Instead, ask https://stackoverflow.com/ https://community.rstudio.com/. Please include minimal reproducible example (AKA reprex). ’ve never heard reprex , start reading https://www.tidyverse.org/help/#reprex. Brief description problem","code":"# insert reprex here"},{"path":"https://tbep-tech.github.io/tbeptools/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 tbeptools authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Fecal Indicator Bacteria","text":"Fecal Indicator Bacteria (FIB) used track concentrations pathogens surface waters may detrimental human health environment. Exposure risk commonly measured select indicators present human gut can enter environment wastewater discharges, stormwater, illicit sources. Common indicators include concentrations E. coli, Enterococcus, Fecal Coliform number colony forming units (CFU) per 100 mL water. Many monitoring programs routinely measure FIB concentrations select locations. tbeptools package several functions importing reporting data. Two workflows available: Functions use data exclusively Environmental Protection Commission (EPC) Hillsborough County Functions use data several monitoring programs baywide reporting focusing exclusively Enterococcus vignette organized around two workflows. , assessments meant inform progress remediating fecal impairments support prioritization areas investigation. meant support beach monitoring efforts closures recreational uses - alternative reporting products available purpose (see FLDOH Healthy Beaches).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"epc-reporting","dir":"Articles","previous_headings":"","what":"EPC reporting","title":"Fecal Indicator Bacteria","text":"Environmental Protection Commission (EPC) Hillsborough County tracking FIB indicators several decades part long-term monitoring. Functions tbeptools can used download EPC FIB data, analyze results, create summary maps plots. sections describes use functions. functions focused reporting Hillsborough River fecal coliform impairment associated Basin Management Action Plan (BMAP). tools can used track long-term changes FIBs basin assess progress reducing fecal coliform levels. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx available direct download viewable . data include observations stations parameters throughout period record. FIB data collected stations additional water quality data collected. dataset used reporting water quality indicators Tampa Bay (see water quality data vignette). functions tbeptools can used import analyze data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read","dir":"Articles","previous_headings":"EPC reporting","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing FIB data read_importfib(). function downloads latest file one already available location specified xlsx input argument. function operates similarly read_importwq() importing water quality data. Please refer water quality data vignette additional details import function. FIB data can downloaded follows: data object called fibdata also provided package, although may contain current data available EPC. View help file download date. fibdata object includes monthly samples FIB data select stations Hillsborough River basin. stations include samples beginning 1972. default output read_importfib() returns stations FIB data EPC. = F read_importfib(), stations AreaName Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta returned. Values returned E. coli (ecoli), Enterococcus (entero), Fecal Coliform (fcolif), Total Coliform (totcol). Units # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Consult source spreadsheet interpretation codes. Concentrations noted < (detection) > (detection) raw data reported detection limit. fibdata object can used remaining FIB functions.","code":"fibdata <- read_importfib('vignettes/current_data.xlsx', download_latest = T) fibdata #> # A tibble: 77,526 × 18 #>    area   epchc_station class SampleTime             yr    mo Latitude Longitude #>    <chr>          <dbl> <chr> <dttm>              <dbl> <dbl>    <dbl>     <dbl> #>  1 Hills…             2 3M    2024-06-10 14:51:00  2024     6     27.9     -82.5 #>  2 Hills…             6 3M    2024-06-17 09:25:00  2024     6     27.9     -82.5 #>  3 Hills…             7 3M    2024-06-17 09:42:00  2024     6     27.9     -82.5 #>  4 Hills…             8 3M    2024-06-17 12:39:00  2024     6     27.9     -82.4 #>  5 Middl…             9 2     2024-06-17 11:47:00  2024     6     27.8     -82.4 #>  6 Middl…            11 2     2024-06-17 10:04:00  2024     6     27.8     -82.5 #>  7 Middl…            13 2     2024-06-17 10:18:00  2024     6     27.8     -82.5 #>  8 Middl…            14 2     2024-06-17 11:14:00  2024     6     27.8     -82.5 #>  9 Middl…            16 2     2024-06-25 09:37:00  2024     6     27.7     -82.5 #> 10 Middl…            19 2     2024-06-25 09:52:00  2024     6     27.7     -82.6 #> # ℹ 77,516 more rows #> # ℹ 10 more variables: Total_Depth_m <dbl>, Sample_Depth_m <dbl>, ecoli <dbl>, #> #   ecoli_q <chr>, entero <dbl>, entero_q <chr>, fcolif <dbl>, fcolif_q <chr>, #> #   totcol <dbl>, totcol_q <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze","dir":"Articles","previous_headings":"EPC reporting","what":"Analyze","title":"Fecal Indicator Bacteria","text":"Several analysis functions provided working EPC data. functions used internally show functions described , presented explanation data processed. anlz_fibmap() function assigns categories observation fibdata selected month year. results mapped using anlz_fibmap() (see ). categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. ranges (number samples / 100 mL) EPC follows E. coli Enterococcus. yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. areasel argument can indicate either \"Alafia\" \"Hillsborough\" select data corresponding river basins, rows fibdata filtered based selection. stations returned argument NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdata \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection yrsel mosel. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". anlz_fibmatrix() function creates summary FIB categories station year output show_fibmatrix() function described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood fecal coliform concentrations exceed 400 CFU / 100 mL. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat). indic argument must set explicitly 'fcolif' indicate indicator fecal coliform EPC data.","code":"anlz_fibmap(fibdata) #> # A tibble: 77,526 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 77,516 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmap(fibdata, yrsel = 2023, mosel = 7) #> # A tibble: 207 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2023     7     27.9     -82.5    NA    800 Ente… 130 … #>  2 Hillsb…       6 3M     2023     7     27.9     -82.5    NA      2 Ente… < 35  #>  3 Hillsb…       7 3M     2023     7     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2023     7     27.9     -82.4    NA      2 Ente… < 35  #>  5 Middle…       9 2      2023     7     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2023     7     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2023     7     27.7     -82.5    NA      2 Ente… < 35  #> 10 Middle…      19 2      2023     7     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 197 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 47 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2023     7     27.9     -82.5    NA    800 Ente… 130 … #>  2 Hillsb…     105 3M     2023     7     28.0     -82.4    NA    128 Ente… 35 -… #>  3 Hillsb…     106 1      2023     7     28.1     -82.4   144    232 E. c… 126 … #>  4 Lake T…     107 3F     2023     7     28.0     -82.3   570   1550 E. c… 410 … #>  5 Hillsb…     108 3F     2023     7     28.1     -82.2   187    276 E. c… 126 … #>  6 Lake T…     118 3F     2023     7     28.1     -82.3     4      7 E. c… < 126 #>  7 Hillsb…     120 3F     2023     7     28.1     -82.4   100    410 E. c… < 126 #>  8 Lake T…     135 3F     2023     7     28.1     -82.3     4      4 E. c… < 126 #>  9 Hillsb…     137 3M     2023     7     28.0     -82.5    NA    680 Ente… 130 … #> 10 Hillsb…     143 3F     2023     7     28.1     -82.1   800   1333 E. c… 410 … #> # ℹ 37 more rows #> # ℹ 1 more variable: col <chr> anlz_fibmatrix(fibdata, indic = 'fcolif') #> # A tibble: 459 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1974 143     NA      NA        NA   NA    #>  2  1974 108    247.     28.1     -82.2 NA    #>  3  1974 107    269.     28.0     -82.3 NA    #>  4  1974 135     NA      NA        NA   NA    #>  5  1974 118    136.     28.1     -82.3 NA    #>  6  1974 148     NA      NA        NA   NA    #>  7  1974 105    258.     28.0     -82.4 NA    #>  8  1974 152     NA      NA        NA   NA    #>  9  1974 137     NA      NA        NA   NA    #> 10  1975 143     NA      NA        NA   NA    #> # ℹ 449 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show","dir":"Articles","previous_headings":"EPC reporting","what":"Show","title":"Fecal Indicator Bacteria","text":"show_fibmap() function creates map FIB sites thresholds based output anlz_fibmap(). arguments apply anlz_fibmap() also apply show_fibmap() freshwater marine stations categorized relevant thresholds plotted selected year, month, area. Unlike anlz_fibmap(), yrsel mosel arguments required. Sites Hillsborough Alafia river basins can shown using areasel argument. Additional information site can seen placing cursor location. map inset can also seen clicking arrow bottom left map. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data [1]. matrix colors based likelihood fecal indicator bacteria concentrations exceed 400 CFU / 100 mL (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1].  default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year.  default stations used TBEP report #05-13 [3] Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument.  yrrng argument can also used select year range, default 1985 current year data fibdata.  preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) object can returned setting plotly argument TRUE. Finally, map station categories given year can plotted using show_fibmatrixmap(). yrsel argument required, areasel argument can used select specific area. values shown map respective year show_fibmatrix() function.","code":"show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Alafia River') show_fibmatrix(fibdata) show_fibmatrix(fibdata, lagyr = 1) show_fibmatrix(fibdata, stas = c(115, 116)) show_fibmatrix(fibdata, yrrng = c(1990, 2020)) show_fibmatrix(fibdata, asreact = TRUE) show_fibmatrix(fibdata, plotly = TRUE) show_fibmatmap(fibdata, indic = 'fcolif', yrsel = 2020, areasel = c('Hillsborough River', 'Alafia River'))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"manatee-county-reporting","dir":"Articles","previous_headings":"","what":"Manatee County reporting","title":"Fecal Indicator Bacteria","text":"FIB data Manatee County Natural Resources Department can also used functions. data can downloaded follows: convenience, data object name included tbeptools use FIB functions. Note read_importwqp() can used download FIB data organizations, although FIB functions work data Manatee County. Similar workflows EPCHC data can used. Examples functions using Manatee County data:","code":"mancofibdata <- read_importwqp('21FLMANA_WQX', type = 'fib') show_fibmap(mancofibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmatrix(mancofibdata, plotly = TRUE) show_fibmatmap(mancofibdata, yrsel = 2020, indic = 'fcolif', areasel = 'Lower Manatee River')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"baywide-reporting","dir":"Articles","previous_headings":"","what":"Baywide reporting","title":"Fecal Indicator Bacteria","text":"second workflow uses baywide approach summarize FIB data. Select stations identified downstream locations drain Tampa Bay considered important watershed endpoints FIB monitoring. Enterococcus primary indicator stations located terminal downstream locations tidally influenced. functions organized similarly EPC reporting workflow, unique functions working data locations functions repeated EPC workflow differ output depending data inputs.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing Enterococcus data read_importentero(). function retrieves data USEPA water quality portal using API. three arguments stas, startDate, endDate. stas argument can left NULL (default) retrieve data stations based catchprecip data object, described . startDate endDate arguments specify date ranges retrieving data, input format character string 'YYYY-MM-DD'. data request can take time enterodata data object provided package use downstream functions. dataset includes data 53 selected stations 1995-2023. downstream functions also require precipitation data obtained using read_importrain() function. function downloads daily precipitation data Southwest Florida Water Management District (SWFWMD) rainfall FTP website. station, daily cumulative rainfall summarized upstream catchment, catchments site defined pixel locations used describe SWFWMD rainfall data. information available catchpixels data object. Rainfall data downloaded defining years months interest. enterodata data object, catchprecip object provided package use downstream functions. dataset includes daily rainfall data (inches) 53 selected stations 1995-2023. rainfall data used define Enterococcus samples “wet” “dry” based default user-defined thresholds described .","code":"read_importentero(startDate = '1995-01-01', endDate = '2023-12-31') head(enterodata) #>            date   yr mo time time_zone     long_name bay_segment #> 1901 2001-01-16 2001  1                Old Tampa Bay         OTB #> 1902 2001-02-20 2001  2                Old Tampa Bay         OTB #> 1903 2001-03-20 2001  3                Old Tampa Bay         OTB #> 1904 2001-04-17 2001  4                Old Tampa Bay         OTB #> 1905 2001-05-15 2001  5                Old Tampa Bay         OTB #> 1906 2001-06-19 2001  6                Old Tampa Bay         OTB #>               station entero entero_censored MDL entero_units qualifier #> 1901 21FLHILL_WQX-101     80           FALSE  NA      #/100mL        NA #> 1902 21FLHILL_WQX-101    360           FALSE  NA      #/100mL        NA #> 1903 21FLHILL_WQX-101   3900           FALSE  NA      #/100mL        NA #> 1904 21FLHILL_WQX-101     20           FALSE  NA      #/100mL        NA #> 1905 21FLHILL_WQX-101     NA           FALSE  20                     NA #> 1906 21FLHILL_WQX-101     NA           FALSE  20                     NA #>      LabComments Latitude Longitude #> 1901          NA  28.0248  -82.6316 #> 1902          NA  28.0248  -82.6316 #> 1903          NA  28.0248  -82.6316 #> 1904          NA  28.0248  -82.6316 #> 1905          NA  28.0248  -82.6316 #> 1906          NA  28.0248  -82.6316 read_importrain(2021, catchpixels, mos = 1:12, quiet = F) head(catchprecip) #> # A tibble: 6 × 3 #>   station            date        rain #>   <chr>              <date>     <dbl> #> 1 21FLCOSP_WQX-32-03 1995-01-01 0     #> 2 21FLCOSP_WQX-32-03 1995-01-02 0     #> 3 21FLCOSP_WQX-32-03 1995-01-03 0     #> 4 21FLCOSP_WQX-32-03 1995-01-04 0.389 #> 5 21FLCOSP_WQX-32-03 1995-01-05 0     #> 6 21FLCOSP_WQX-32-03 1995-01-06 0.106"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Analyze","title":"Fecal Indicator Bacteria","text":"Several analysis functions provided working Enterococcus data. functions used internally show functions described , presented explanation data processed. function uses Enterococcus precipitation data provided enterodata catchprecip data objects. latter dataset used define “wet” “dry” samples premise Enterococcus concentrations higher wet weather may useful distinguish samples assess progress achieving water quality restoration goals, .e., rainfall may confound assessment management efforts reduce fecal contamination. anlz function optional arguments define temporal_window wet_threshold defining “wet” “dry” samples, passed anlz_fibwetdry() function. arguments define period time preceding sample date cumulative rainfall threshold within time period must met define sample “wet”. arguments default two days half inch, samples defined “wet” greater half inch cumulative rainfall two days preceding including sample date. time rainfall thresholds can changed user. Additionally, anlz functions can also treat samples equally ignoring rainfall data setting wetdry = FALSE, default behavior. anlz_fibwetdry() function defines “wet” “dry” samples described returns original input dataset three additional columns describing total rain (inches) day sampling (rain_sampleDay), total rain period defined temporal_window argument (rain_total), whether sample “wet” logical value (wet_sample). remaining anlz functions anlz_enteromap() prepare data mapping anlz_fibmatrix() prepare data score card. can optionally use anlz_fibwetdry() plot “wet” “dry” samples, described show section. anlz_enteromap() function Enterococcus-specific analogue anlz_fibmap() fecal coliform function described EPC section . function assigns categories observation Enterococcus data frame, can viewed given month year using show_enteromap() (analagous show_fibmap()). categories specific Enterococcus marine waters, noted cat column output. Corresponding colors col column output. ranges (number samples / 100 mL) EPC follows Enterococcus: yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. wetdry argument can used determine whether sample taken rain event (logical wet_sample column output), based user-specified thresholds provided precipitation data object (catchprecip). shows identify wet samples based least 0.5 inches rain occurring two days prior including sample date. areasel argument can indicate one major subwatersheds Tampa Bay (excluding Terra Ceia Bay data exist). example, use Old Tampa Bay stations subwatershed Old Tampa Bay, rows enterodata filtered based selection. stations returned argument set NULL (default). valid options areasel include \"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay\", \"Manatee River\". anlz_fibmatrix() function used show_fibmatrix() function used similarly EPC workflow described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood Enterococcus concentrations exceed 130 CFU / 100 mL. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat). indic argument must set explicitly 'entero' select indicator Enterococcus.","code":"anlz_fibwetdry(enterodata, catchprecip, temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 6,266 × 19 #>    date          yr    mo time  time_zone long_name   bay_segment station entero #>    <date>     <dbl> <dbl> <chr> <chr>     <chr>       <chr>       <chr>    <dbl> #>  1 2001-01-16  2001     1 \"\"    \"\"        Old Tampa … OTB         21FLHI…     80 #>  2 2001-02-20  2001     2 \"\"    \"\"        Old Tampa … OTB         21FLHI…    360 #>  3 2001-03-20  2001     3 \"\"    \"\"        Old Tampa … OTB         21FLHI…   3900 #>  4 2001-04-17  2001     4 \"\"    \"\"        Old Tampa … OTB         21FLHI…     20 #>  5 2001-05-15  2001     5 \"\"    \"\"        Old Tampa … OTB         21FLHI…     NA #>  6 2001-06-19  2001     6 \"\"    \"\"        Old Tampa … OTB         21FLHI…     NA #>  7 2001-07-24  2001     7 \"\"    \"\"        Old Tampa … OTB         21FLHI…   1300 #>  8 2001-08-21  2001     8 \"\"    \"\"        Old Tampa … OTB         21FLHI…    260 #>  9 2001-09-18  2001     9 \"\"    \"\"        Old Tampa … OTB         21FLHI…    420 #> 10 2001-10-16  2001    10 \"\"    \"\"        Old Tampa … OTB         21FLHI…    520 #> # ℹ 6,256 more rows #> # ℹ 10 more variables: entero_censored <lgl>, MDL <int>, entero_units <chr>, #> #   qualifier <lgl>, LabComments <lgl>, Latitude <dbl>, Longitude <dbl>, #> #   rain_sampleDay <dbl>, rain_total <dbl>, wet_sample <lgl> anlz_enteromap(enterodata) #> # A tibble: 6,266 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     5     28.0     -82.6     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2001     6     28.0     -82.6     NA NA    NA    Ente… #>  7 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  8 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #> # ℹ 6,256 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_enteromap(enterodata, yrsel = 2020, mosel = 8) #> # A tibble: 27 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6    220 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     40 35 -… #E9C… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     70 35 -… #E9C… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     8     28.0     -82.6     50 35 -… #E9C… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     8     27.9     -82.7     20 < 35  #2DC… Ente… #>  6 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4      8 < 35  #2DC… Ente… #>  7 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4   1200 > 999 #CC3… Ente… #>  8 21FLHILL_W… Hillsbor…  2020     8     27.8     -82.4    520 130 … #EE7… Ente… #>  9 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.5    190 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     8     27.9     -82.4     90 35 -… #E9C… Ente… #> # ℹ 17 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_enteromap(enterodata, wetdry = TRUE, precipdata = catchprecip,                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 6,266 × 13 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     5     28.0     -82.6     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2001     6     28.0     -82.6     NA NA    NA    Ente… #>  7 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  8 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #> # ℹ 6,256 more rows #> # ℹ 3 more variables: indnm <chr>, conc <dbl>, wet_sample <lgl> anlz_enteromap(enterodata, yrsel = 2023, mosel = 7, areasel = 'Old Tampa Bay') #> # A tibble: 12 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6      5 < 35  #2DC… Ente… #>  2 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6     30 < 35  #2DC… Ente… #>  3 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6     70 35 -… #E9C… Ente… #>  4 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6    220 130 … #EE7… Ente… #>  5 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.5     NA NA    NA    Ente… #>  6 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6    467 130 … #EE7… Ente… #>  7 21FLHILL_W… Old Tamp…  2023     7     28.0     -82.6   3900 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2023     7     28.0     -82.7    798 130 … #EE7… Ente… #>  9 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7    457 130 … #EE7… Ente… #> 10 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7   1860 > 999 #CC3… Ente… #> 11 21FLPDEM_W… Old Tamp…  2023     7     27.9     -82.7     75 35 -… #E9C… Ente… #> 12 21FLTPA_WQ… Old Tamp…  2023     7     28.0     -82.7   2613 > 999 #CC3… Ente… #> # ℹ 2 more variables: indnm <chr>, conc <dbl> anlz_fibmatrix(enterodata, indic = 'entero') #> # A tibble: 1,200 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 NA    #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show-1","dir":"Articles","previous_headings":"Baywide reporting","what":"Show","title":"Fecal Indicator Bacteria","text":"show_enteromap() function creates map Enterococcus sites thresholds based output anlz_enteromap(). arguments apply anlz_enteromap() also apply show_enteromap(), including classification samples ‘wet’ depending specified thresholds. Wet dry samples differentiated map shapes. Unlike anlz_enteromap(), yrsel mosel arguments required. Additional information site can seen placing cursor location. map inset can also seen clicking arrow bottom left map. Sites specific areas can shown using areasel argument. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data. function primarily designed fecal coliform data, adapted work Enterococcus data. matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 130 CFU / 100 mL Enterococcus (entero fibdata enterodata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1]. stations shown default.  default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year.  Individual stations can selectd using stas argument.  yrrng argument can also used select year range, default date range contained data.  Note subset_wetdry argument can used show_fibmatrix() show wet dry samples based thresholds provided temporal_window wet_threshold. However, recommended scores probability-based comparisons wet dry samples may misleading due different sample sizes, therefore, power detect likelihood exceeding threshold. Specifically, far fewer wet samples dry samples generally receive higher grades due lower power statistical tests. EPC data, HTML table can returned show_fibmatrix() using asreact = TRUE plotly object can returned using plotly = TRUE. See section examples outputs. show_fibmatrix() function also supports baywide reporting bay segment, unlike EPC data. stations baywide reporting selected specifically endpoints drain directly bay segment aggregate summary stations bay segment can indicate MWQA category. calculations station, data aggregated bay segment.  Finally, map station bay segment categories given year can plotted using show_fibmatrixmap(). yrsel argument required, areasel argument can used select specific area. values shown map respective year show_fibmatrix() function.","code":"show_enteromap(enterodata, yrsel = 2020, mosel = 9) show_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5) show_enteromap(enterodata, yrsel = 2023, mosel = 7, areasel = 'Old Tampa Bay') show_fibmatrix(enterodata, indic = 'entero') show_fibmatrix(enterodata, indic = 'entero', lagyr = 1) show_fibmatrix(enterodata,                indic = 'entero',                stas = c('21FLHILL_WQX-101', '21FLHILL_WQX-102', '21FLHILL_WQX-103')) show_fibmatrix(enterodata, indic = 'entero', yrrng = c(2015, 2020)) show_fibmatrix(enterodata, indic = 'entero', bay_segment = c('OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR')) show_fibmatmap(enterodata, indic = 'entero', yrsel = 2020, areasel = c('OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR'))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"retrieving-additional-fib-data","dir":"Articles","previous_headings":"","what":"Retrieving additional FIB data","title":"Fecal Indicator Bacteria","text":"read_importwqp() function can used retrieve data USEPA Water Quality Portal using organization identifier. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'fib', trace = T)  # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Habitat Master Plan","text":"Dashboard: https://shiny.tbep.org/landuse-change/ habitats Tampa Bay provide food, shelter, important services support birds, fish, mammals, invertebrates. Significant habitat alteration loss occurred development activities. address challenges, Habitat Master Plan (2020 Update) [1] provides set targets goals , achieved, provide healthy balanced coverage native habitats Tampa Bay watershed. update builds previous Habitat Master Plan [2] several ways. target goal setting approach informed past changes forty years habitat restoration experience region. approach also identifies possible today rather replicating past ecological conditions accounts potential future effects sea-level rise, climate change, development. Habitat Master Plan defines 10-year (2030) habitat protection restoration targets 30-year (2050) goals. Maps habitat protection restoration opportunity areas targets goals can attained additional products available new plan. Please visit https://tbep.org/habitat-master-plan-update/ additional information.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"datasets","dir":"Articles","previous_headings":"","what":"Datasets","title":"Habitat Master Plan","text":"Three internal datasets tbeptools provide necessary information create Habitat Master Plan report card. Summary annual acreage estimates major habitat type intertidal supratidal strata. Summary annual acreage estimates major habitat type subtidal stratam. table targets goals major habitat type, developed Habitat Master Plan 2020 update [1] (select columns shown). datasets created repository https://github.com/tbep-tech/hmpu-workflow require updates land use cover datasets produced every two three years Southwest Florida Water Management District.","code":"acres #> # A tibble: 90 × 3 #> # Groups:   name [9] #>    name  HMPU_TARGETS                       Acres #>    <chr> <chr>                              <dbl> #>  1 1990  Coastal Uplands                    5078. #>  2 1990  Developed                        372438. #>  3 1990  Forested Freshwater Wetlands     159561. #>  4 1990  Mangrove Forests                  13522. #>  5 1990  Native Uplands                   229990. #>  6 1990  Non-Forested Freshwater Wetlands  54454. #>  7 1990  Open Water                        38357. #>  8 1990  Restorable                       571513. #>  9 1990  Salt Barrens                        468  #> 10 1990  Salt Marshes                       4482. #> # ℹ 80 more rows subtacres #> # A tibble: 65 × 3 #>    name  HMPU_TARGETS    Acres #>    <chr> <chr>           <dbl> #>  1 1988  Open Water   197802.  #>  2 1988  Restorable       72.9 #>  3 1988  Seagrasses    23279.  #>  4 1988  Tidal Flats   21686.  #>  5 1990  Open Water   197058.  #>  6 1990  Restorable       67.0 #>  7 1990  Seagrasses    25218.  #>  8 1990  Tidal Flats   20433.  #>  9 1992  Open Water   195908.  #> 10 1992  Restorable       86.0 #> # ℹ 55 more rows hmptrgs[, c(\"Category\", \"HMPU_TARGETS\", \"Target2030\", \"Goal2050\")] #>      Category                     HMPU_TARGETS Target2030 Goal2050 #> 1    Subtidal                      Hard Bottom      423.0    423.0 #> 2    Subtidal                 Artificial Reefs      166.0    166.0 #> 3    Subtidal                      Tidal Flats    16220.0  16220.0 #> 4    Subtidal                       Seagrasses    40000.0  40000.0 #> 5    Subtidal                      Oyster Bars      221.0    471.0 #> 6  Intertidal                Living Shorelines       21.3     56.3 #> 7  Intertidal                 Total Intertidal    21353.0  23803.0 #> 8  Intertidal                 Mangrove Forests    15300.0  15300.0 #> 9  Intertidal                     Salt Barrens      546.0    796.0 #> 10 Intertidal                     Salt Marshes     4807.0   5457.0 #> 11 Intertidal                Tidal Tributaries        4.0     18.0 #> 12 Supratidal                  Coastal Uplands     3769.0   4219.0 #> 13 Supratidal Non-Forested Freshwater Wetlands    68937.0  71787.0 #> 14 Supratidal     Forested Freshwater Wetlands   152282.0 152732.0 #> 15 Supratidal                   Native Uplands   141050.0 142100.0"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-summary","dir":"Articles","previous_headings":"","what":"Report card summary","title":"Habitat Master Plan","text":"important reporting product Habitat Master Plan report card summarizes attainment targets goals evaluates prior trends identify coverages trending targets goals. Two functions provided tbeptools create report card. anlz_hmpreport() summarizes datasets provide necessary information creating report card. show_hmpreport() generates plot report card. latter can used former provided need view data behind report card. Using anlz_hmpreport() function summarizes acreage coverage estimates habitat type, compares targets goals year data, assesses coverage trend year pairs determine changes trending targets goals. columns follows: year: Year assessment metric: Habitat type assessed Acres: Coverage estimate year lacres: Coverage estimate previous set available data lyr: Year previous set available data category: Strata habitat type Target: 2030 target habitat type Habitat Master Plan Goal: 2050 goal habitat type Habitat Master Plan acresdiff: Difference acres current year previous set available data yeardiff: Difference years current year previous set available data changerate: Acreage change per year current year relative previous set available data targetrate: Annual rate required achieve 2030 target goalrate: Annual rate required achieve 2050 goal targetprop: Proportion target met current year goalprop: Proportion goal met current year targeteval: number indicating target status current year report card goaleval: number indicating goal status current year report card important columns output targetprop, goalprop, targeteval, goaleval. targetprop goalprop columns indicate proportion target goal met habitat type current assessment year. targeteval goaleval columns one four values, -1, 0, 0.5, 1, habitat type year. numbers define habitat status assessment year: -1: target goal met, trending 0: target goal met, trending 0.5: target goal met, trending 1: target goal met, trending ","code":"anlz_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs) #> # A tibble: 150 × 17 #>     year metric      Acres lacres   lyr category Target  Goal acresdiff yeardiff #>    <dbl> <chr>       <dbl>  <dbl> <dbl> <fct>     <dbl> <dbl>     <dbl>    <dbl> #>  1  1990 Seagrasses 25218. 23279.  1988 Subtidal  40000 40000     1939.        2 #>  2  1990 Tidal Fla… 20433. 21686.  1988 Subtidal  16220 16220    -1253.        2 #>  3  1992 Seagrasses 25746. 25218.  1990 Subtidal  40000 40000      528.        2 #>  4  1992 Tidal Fla… 20594. 20433.  1990 Subtidal  16220 16220      161.        2 #>  5  1994 Seagrasses 26524. 25746.  1992 Subtidal  40000 40000      778.        2 #>  6  1994 Tidal Fla… 20244. 20594.  1992 Subtidal  16220 16220     -349.        2 #>  7  1996 Seagrasses 26924. 26524.  1994 Subtidal  40000 40000      400.        2 #>  8  1996 Tidal Fla… 20443. 20244.  1994 Subtidal  16220 16220      199.        2 #>  9  1999 Seagrasses 24840. 26924.  1996 Subtidal  40000 40000    -2083.        3 #> 10  1999 Tidal Fla… 27085. 20443.  1996 Subtidal  16220 16220     6642.        3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate <dbl>, targetrate <dbl>, goalrate <dbl>, #> #   targetprop <dbl>, goalprop <dbl>, targeteval <dbl>, goaleval <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-plot","dir":"Articles","previous_headings":"","what":"Report card plot","title":"Habitat Master Plan","text":"show_hmpreport() can used create Habitat Master Plan report card. anlz_hmpreport() function used internally need used separately. input files . plot shows report card 2030 targets, using typ = \"targets\". colors cell correspond numbers targeteval column (goaleval typ = \"goals\") returned anlz_hmpreport(). numbers cell indicate proportion target targetprop (goal goalprop typ = \"goals\") met habitat type assessment year. Note creation datasets generate summaries continuous year varies subtidal inter/supratidal habitat.  2050 goals report card can shown using typ = \"goals\".  subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data.  Different strata can also selected using strata argument. Note use ycollapse = T remove years without data.  strata can combined single plot collapsed years using patchwork library.  text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5).  alternative form report card can returned attainment targets goals likelihood attainment shown differently using colors shapes, respectively. plotted using twocol = T, red shows target goal met, green shows target goal met, arrow shows target goal likely met, arrow shows target goal likely met.  report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan.","code":"show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'goals') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', ycollapse = T) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = c('Intertidal', 'Supratidal'), ycollapse = T) library(patchwork) library(ggplot2)   p1 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = 'Subtidal', ycollapse = T) p2 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets',                 strata = c('Intertidal', 'Supratidal'), ycollapse = T) + labs(title = NULL)  p1 + p2 + plot_layout(ncol = 2, guides = 'collect') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', text = NULL) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', twocol = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Water Quality Data","text":"Dashboard: https://shiny.tbep.org/wq-dash vignette provides overview functions tbeptools can used work water quality data Tampa Bay. View vignettes topical introductions reporting products (e.g., seagrasess, tidal creeks, etc.). environmental recovery Tampa Bay exceptional success story coastal water quality management. Nitrogen loads mid 1970s estimated 8.2 million kg/yr, approximately 5.5 million kg/yr entering upper Bay alone [2]. Reduced water clarity associated phytoplankton biomass contributed dramatic reduction areal coverage seagrass [3] development hypoxic events, causing decline benthic faunal production [4]. Extensive efforts reduce nutrient loads Bay occurred late 1970s, notable improvements infrastructure wastewater treatment 1979. Improvements water clarity decreases chlorophyll concentrations observed Bay-wide 1980s, conditions generally remaining constant present day [5]. Tracking changes environmental condition past present day possible without long-term monitoring dataset. Data collected monthly Environmental Protection Commission Hillsborough County since 1974 [6,7]. Samples taken forty-five stations water collection monitoring sonde bottom, mid- surface depths, depending parameter. locations monitoring stations fixed cover entire Bay uppermost mesohaline sections lowermost euhaline portions direct interaction Gulf Mexico. 515 observations available different parameters station, e.g., nitrogen, chlorophyll-, secchi depth. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. date, systematic tools importing, analyzing, reporting information data. tbeptools package provides developed address need. Locations long-term monitoring stations Tampa Bay. Bay separated four segments defined chemical, physical, geopolitical boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Water Quality Data","text":"main function importing water quality data read_importwq(). function downloads latest file one already available location specified xlsx input argument. First, create character path location file. one exist, specify desired location name downloaded file. , want put file vignettes folder name current_results.xls. Note file path relative root working directly current R session. can view working directory getwd(). Now pass xlsx object read_importwq() function. get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get message, indication file server downloaded. ’ll data downloaded saved epcdata object finishes downloading. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work monitoring data, read_importwq() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: argument na indicates fields downloaded spreadsheet treated blank values assigned NA. number strings can added function replace fields NA values. data successfully imported, can view assigned object: data include bay segment name, station number, sample time, year, month, latitude, longitude, station depth, sample depth, total nitrogen, secchi depth, chlorophyll, salinity, water temperature, turbidity, water color. parameters can included setting = TRUE read_importwq(). import function also available download format phytoplankton cell count data. read_importphyto() function works similarly import function water quality data. Start specifying path data downloaded set download_latest TRUE. function download summarize data file PlanktonDataList_ThroughCurrentReportMonth.xlsx EPC website. phytoplankton data successfully imported, can view assigned object: data highly summarized raw data file available online. Cell counts (number cells per 0.1mL) selected taxa summed station quarters (.e., Jan/Feb/Mar, Apr/May/Jun, etc.). quarter indicated yrqrt column specified starting date quarter (e.g., 1975-07-01 quarter Jul/Aug/Sep 1975). data primarily used support analyses water quality dashboard: https://shiny.tbep.org/wq-dash/","code":"xlsx <- 'vignettes/current_results.xlsx' epcdata <- read_importwq(xlsx) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File vignettes/current_results.xlsx does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1'  length 24562051 bytes (23.4 MB) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File is current... #> Replacing local file with current... epcdata #> # A tibble: 27,961 × 26 #>    bay_segment epchc_station SampleTime             yr    mo Latitude Longitude #>    <chr>               <dbl> <dttm>              <dbl> <dbl>    <dbl>     <dbl> #>  1 HB                      6 2023-12-19 10:01:00  2023    12     27.9     -82.5 #>  2 HB                      7 2023-12-19 10:12:00  2023    12     27.9     -82.5 #>  3 HB                      8 2023-12-19 12:39:00  2023    12     27.9     -82.4 #>  4 MTB                     9 2023-12-19 11:54:00  2023    12     27.8     -82.4 #>  5 MTB                    11 2023-12-19 10:25:00  2023    12     27.8     -82.5 #>  6 MTB                    13 2023-12-19 10:38:00  2023    12     27.8     -82.5 #>  7 MTB                    14 2023-12-19 11:24:00  2023    12     27.8     -82.5 #>  8 MTB                    16 2023-12-20 09:35:00  2023    12     27.7     -82.5 #>  9 MTB                    19 2023-12-20 09:49:00  2023    12     27.7     -82.6 #> 10 LTB                    23 2023-12-20 13:16:00  2023    12     27.7     -82.6 #> # ℹ 27,951 more rows #> # ℹ 19 more variables: Total_Depth_m <dbl>, Sample_Depth_m <dbl>, tn <dbl>, #> #   tn_q <chr>, sd_m <dbl>, sd_raw_m <dbl>, sd_q <chr>, chla <dbl>, #> #   chla_q <chr>, Sal_Top_ppth <dbl>, Sal_Mid_ppth <dbl>, #> #   Sal_Bottom_ppth <dbl>, Temp_Water_Top_degC <dbl>, #> #   Temp_Water_Mid_degC <dbl>, Temp_Water_Bottom_degC <dbl>, #> #   `Turbidity_JTU-NTU` <chr>, Turbidity_Q <chr>, Color_345_F45_PCU <chr>, … xlsx <- 'phyto_data.xlsx' phytodata <- read_importphyto(xlsx, download_latest = T) #> File vignettes/phyto_data.xlsx does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1'  length 12319508 bytes (11.7 MB) phytodata #> # A tibble: 21,143 × 8 #>    epchc_station Date       name           units  count yrqrt         yr mo    #>    <chr>         <date>     <chr>          <chr>  <dbl> <date>     <dbl> <ord> #>  1 11            1975-07-23 other          /0.1mL     0 1975-07-01  1975 Jul   #>  2 11            1976-01-07 other          /0.1mL     1 1976-01-01  1976 Jan   #>  3 11            1977-01-05 other          /0.1mL     1 1977-01-01  1977 Jan   #>  4 11            1977-04-20 Tripos hircus  /0.1mL     1 1977-04-01  1977 Apr   #>  5 11            1977-04-20 other          /0.1mL     1 1977-04-01  1977 Apr   #>  6 11            1977-07-13 other          /0.1mL    12 1977-07-01  1977 Jul   #>  7 11            1978-01-11 other          /0.1mL    16 1978-01-01  1978 Jan   #>  8 11            1979-02-08 other          /0.1mL     1 1979-01-01  1979 Feb   #>  9 11            1979-05-02 Karenia brevis /0.1mL     1 1979-04-01  1979 May   #> 10 11            1979-05-30 other          /0.1mL     1 1979-04-01  1979 May   #> # ℹ 21,133 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"retrieving-additional-water-quality-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional water quality data","title":"Water Quality Data","text":"water quality functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description water quality. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored organization type = 'wq'. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T)  # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'wq', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Water Quality Data","text":"functions anlz_avedat() anlz_avedatsite() summarize station data bay segments sites, respectively. functions return annual means chlorophyll light attenuation (based Secchi depth measurements) monthly means year chlorophyll light attenuation. summaries used determine bay segment targets water quality met using anlz_attain() anlz_attainsite() function. use anlz_avedat() summarize data bay segment estimate annual monthly means chlorophyll light attenuation. output two-element list annual (ann) monthly (mos) means segment. output can analyzed anlz_attain() determine bay segment outcomes met year. results used plotting functions described . short, chl_la column indicates categorical outcome chlorophyll light attenuation segment. outcomes integer values zero three. relative exceedances water quality thresholds segment, duration magnitude, indicated higher integer values. Similar information can obtained individual sites using anlz_avedatsite() anlz_attainsite(). main difference yes/column metis added indicates target segment threshold site.","code":"avedat <- anlz_avedat(epcdata) avedat #> $ann #> # A tibble: 608 × 4 #>       yr bay_segment var         val #>    <dbl> <chr>       <chr>     <dbl> #>  1  1974 HB          mean_chla 22.4  #>  2  1974 LTB         mean_chla  4.24 #>  3  1974 MTB         mean_chla  9.66 #>  4  1974 OTB         mean_chla 10.2  #>  5  1975 HB          mean_chla 27.9  #>  6  1975 LTB         mean_chla  4.93 #>  7  1975 MTB         mean_chla 11.4  #>  8  1975 OTB         mean_chla 13.2  #>  9  1976 HB          mean_chla 29.5  #> 10  1976 LTB         mean_chla  5.08 #> # ℹ 598 more rows #>  #> $mos #> # A tibble: 4,724 × 5 #>    bay_segment    yr    mo var         val #>    <chr>       <dbl> <dbl> <chr>     <dbl> #>  1 HB           1974     1 mean_chla 36.2  #>  2 LTB          1974     1 mean_chla  1.75 #>  3 MTB          1974     1 mean_chla 11.5  #>  4 OTB          1974     1 mean_chla  4.4  #>  5 HB           1974     2 mean_chla 42.4  #>  6 LTB          1974     2 mean_chla  5.5  #>  7 MTB          1974     2 mean_chla  9.35 #>  8 OTB          1974     2 mean_chla  4.07 #>  9 HB           1974     3 mean_chla 14.9  #> 10 LTB          1974     3 mean_chla  5.88 #> # ℹ 4,714 more rows anlz_attain(avedat) #> # A tibble: 200 × 4 #>    bay_segment    yr chl_la outcome #>    <chr>       <dbl> <chr>  <chr>   #>  1 HB           1974 3_0    yellow  #>  2 HB           1975 3_2    red     #>  3 HB           1976 3_2    red     #>  4 HB           1977 3_2    red     #>  5 HB           1978 3_3    red     #>  6 HB           1979 3_3    red     #>  7 HB           1980 3_3    red     #>  8 HB           1981 3_3    red     #>  9 HB           1982 3_3    red     #> 10 HB           1983 3_0    yellow  #> # ℹ 190 more rows anlz_avedatsite(epcdata) %>% anlz_attainsite #> # A tibble: 2,250 × 9 #>       yr bay_segment epchc_station var     val target smallex thresh met   #>    <dbl> <chr>               <dbl> <chr> <dbl>  <dbl>   <dbl>  <dbl> <chr> #>  1  1974 HB                      6 chla   25.6   13.2    14.1     15 no    #>  2  1974 HB                      7 chla   21.6   13.2    14.1     15 no    #>  3  1974 HB                      8 chla   22.6   13.2    14.1     15 no    #>  4  1974 HB                     44 chla   23.4   13.2    14.1     15 no    #>  5  1974 HB                     52 chla   23.5   13.2    14.1     15 no    #>  6  1974 HB                     55 chla   20.2   13.2    14.1     15 no    #>  7  1974 HB                     70 chla   33.1   13.2    14.1     15 no    #>  8  1974 HB                     71 chla   25.8   13.2    14.1     15 no    #>  9  1974 HB                     73 chla   17.6   13.2    14.1     15 no    #> 10  1974 HB                     80 chla   10.5   13.2    14.1     15 yes   #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Water Quality Data","text":"External package libraries R can used plot time series data. ’s example using popular ggplot2 package. data wrangling dplyr done first filter data want plot.  show_thrplot() function provides descriptive assessment annual trends chosen bay segment relative defined targets thresholds. plot show annual averages across stations Old Tampa bay (bay_segment = \"OTB\") chlorophyll (thr = \"chla\"). red line shows annual trends horizontal blue lines indicate thresholds targets chlorophyll-specific Old Tampa Bay. dashed dotted blue lines indicate +1 +2 standard errors management target shown filled line. target standard errors considered identifying annual segment outcome chlorophyll.  can show plot light attenuation changing thr = \"chla\" thr = \"la\". Note change horizontal reference lines light attenuation target.  year range plot can also specified using yrrng argument, default year range epcdata.  show_thrplot() function uses results anlz_avedat() function. example, can retrieve values plot follows: Similarly, show_boxplot() function provides assessment seasonal changes chlorophyll light attenuation values bay segment. recent year highlighted red default. allows simple evaluation recent year compared historical averages. large exceedance value shown blue text dotted line. corresponds “large” magnitude change +2 standard errors bay segment threshold dotted line shown show_thrplot().   different subset years selected year interest can also viewed changing yrrng yrsel arguments. show 1980 compared monthly averages 2008 2018.  show_thrplot() function useful understand annual variation chlorophyll light attenuation relative management targets bay segment. information plots can provide understanding annual reporting outcomes determined. noted , outcome integer zero three assigned bay segment annual estimate chlorophyll light attenuation. outcomes based exceedance annual estimate threshold target (blue lines show_thrplot()) duration exceedance years prior. following graphic describes logic [8]. Outcomes annual estimates water quality assigned integer value zero three depending magnitude duration exceedence. outcomes assigned chlorophyll light attenuation. duration criteria determined based whether exceedance observed years prior current year. exceedance criteria chlorophyll light-attenuation specific segment. tbeptools package contains targets data file reference determining annual outcomes. file loaded automatically package can viewed command line. final plotting function show_matrix(), creates annual reporting matrix reflects combined outcomes chlorophyll light attenuation. Tracking attainment bay segment specific targets indicators provides framework bay management actions developed initiated. year segment, color-coded management action assigned: Stay Course: Continue planned projects. Report data via annual progress reports Baywide Environmental Monitoring Report. Caution: Review monitoring data nitrogen loading estimates. Begin/continue TAC Management Board development specific management recommendations. Alert: Finalize development implement appropriate management actions get back track. management category action based combination outcomes chlorophyll light attenuation [8]. Management action categories assigned bay segment year based chlorophyll light attenuation outcomes. results can viewed show_matrix().  matrix also ggplot object layout can changed using ggplot elements. Note use txtsz = NULL remove color labels.  preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. Results can also obtained selected year. Outcomes can returned tabular format anlz_yrattain(). table also shows segment averages chlorophyll light attenuation, including associated targets. map showing individual sites achieved chlorophyll targets can obtained show_sitemap(). station averages chlorophyll selected year shown next point. Stations red failed meet segment target.  show_sitemap() function also includes argument specify particular monthly range selected year. option chosen, averages shown continuous values station.  Another map can created show_sitesegmap() similar show_sitemap(), except bay segments shown colored annual outcome. map useful understand site data correspond bay segment.  Bay segment exceedances can also viewed matrix using show_wqmatrix(). thresholds values correspond Florida DEP criteria (large exceedance defined +2 standard errors segment target).  default, show_wqmatrix() function returns chlorophyll exceedances segment. Light attenuation exceedances can viewed changing param argument.  results show_matrix() show_wqmatrix() can combined individual segment using show_segmatrix() function. useful understand water quality parameter driving management outcome given year. plot shows light attenuation chlorophyll outcomes show_wqmatrix() next segment management outcomes show_matrix(). one segment can plotted function call.  Finally, segment plots can shown together using show_segplotly() function combines chlorophyll secchi data given segment. function combines outputs show_thrplot() show_segmatrix(). final plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot. plots, can quickly view summary environmental history water quality Tampa Bay. Degraded conditions common early period record, particularly Old Tampa Bay Hillsborough Bay. Conditions began improve late 1980s early 1990s, good conditions persisting present day. However, recent trends Old Tampa Bay shown conditions changing “stay course” “caution”.","code":"toplo <- epcdata %>%    filter(epchc_station == '52')  ggplot(toplo, aes(x = SampleTime, y = chla)) +    geom_line() +    geom_point() +    scale_y_log10() +    labs(     y = 'Chlorophyll-a concentration (ug/L)',      x = NULL,      title = 'Chlorophyll trends',     subtitle = 'Hillsborough Bay station 52, all dates'     ) +    theme_bw() show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"chla\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\", yrrng = c(2000, 2018)) epcdata %>%    anlz_avedat %>%    .[['ann']] %>%    filter(bay_segment == 'OTB') %>%    filter(var == 'mean_la') %>%    filter(yr >= 2000 & yr <= 2018) #> # A tibble: 19 × 4 #>       yr bay_segment var       val #>    <dbl> <chr>       <chr>   <dbl> #>  1  2000 OTB         mean_la 0.733 #>  2  2001 OTB         mean_la 0.951 #>  3  2002 OTB         mean_la 0.927 #>  4  2003 OTB         mean_la 1.04  #>  5  2004 OTB         mean_la 0.878 #>  6  2005 OTB         mean_la 0.769 #>  7  2006 OTB         mean_la 0.620 #>  8  2007 OTB         mean_la 0.677 #>  9  2008 OTB         mean_la 0.696 #> 10  2009 OTB         mean_la 0.808 #> 11  2010 OTB         mean_la 0.842 #> 12  2011 OTB         mean_la 0.912 #> 13  2012 OTB         mean_la 0.687 #> 14  2013 OTB         mean_la 0.567 #> 15  2014 OTB         mean_la 0.606 #> 16  2015 OTB         mean_la 0.560 #> 17  2016 OTB         mean_la 0.575 #> 18  2017 OTB         mean_la 0.682 #> 19  2018 OTB         mean_la 0.678 show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\") show_boxplot(epcdata, param = 'la', bay_segment = \"HB\") show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\", yrrng = c(2008, 2018), yrsel = 1980) targets #>   bay_segment                      name chla_target chla_smallex chla_thresh #> 1         OTB             Old Tampa Bay         8.5          8.9         9.3 #> 2          HB          Hillsborough Bay        13.2         14.1        15.0 #> 3         MTB          Middle Tampa Bay         7.4          7.9         8.5 #> 4         LTB           Lower Tampa Bay         4.6          4.8         5.1 #> 5        BCBN      Boca Ciega Bay North         7.7          NaN         8.3 #> 6        BCBS      Boca Ciega Bay South         6.1          NaN         6.3 #> 7         TCB            Terra Ceia Bay         7.5          NaN         8.7 #> 8          MR             Manatee River         7.3          NaN         8.8 #> 9       RALTB Remainder Lower Tampa Bay         NaN          NaN         5.1 #>   la_target la_smallex la_thresh #> 1      0.83       0.86      0.88 #> 2      1.58       1.63      1.67 #> 3      0.83       0.87      0.91 #> 4      0.63       0.66      0.68 #> 5       NaN        NaN       NaN #> 6       NaN        NaN       NaN #> 7       NaN        NaN       NaN #> 8       NaN        NaN       NaN #> 9       NaN        NaN       NaN show_matrix(epcdata) show_matrix(epcdata, txtsz = NULL) +   scale_y_continuous(expand = c(0,0), breaks = sort(unique(epcdata$yr))) +    coord_flip() +   theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 7)) show_matrix(epcdata, asreact = TRUE) show_matrix(epcdata, plotly = TRUE) anlz_yrattain(epcdata, yrsel = 2018) #> # A tibble: 4 × 6 #>   bay_segment chla_val chla_target la_val la_target outcome #>   <fct>          <dbl>       <dbl>  <dbl>     <dbl> <chr>   #> 1 OTB             9.22         8.5  0.678      0.83 yellow  #> 2 HB             13.9         13.2  1.09       1.58 green   #> 3 MTB             7.05         7.4  0.570      0.83 green   #> 4 LTB             4.65         4.6  0.593      0.63 green show_sitemap(epcdata, yrsel = 2018) show_sitemap(epcdata, yrsel = 2018, mosel = c(7, 9)) show_sitesegmap(epcdata, yrsel = 2018) show_wqmatrix(epcdata) show_wqmatrix(epcdata, param = 'la') show_segmatrix(epcdata, bay_segment = 'OTB') show_segplotly(epcdata, width = 1000, height = 600)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"reasonable-assurance-reporting","dir":"Articles","previous_headings":"Show","what":"Reasonable Assurance reporting","title":"Water Quality Data","text":"TBEP collaboration Tampa Bay Nitrogen Management Consortium (NMC) reports annually water quality conditions Tampa Bay Reasonable Assurance (RA) plan Florida Department Environmental Protection (FDEP). plan comprehensive approach managing nitrogen pollution Tampa Bay provides “reasonable assurance” designated uses waterbody segments bay maintained restored response potential nutrient impairments. Annual reports FDEP critical part plan tbeptools package includes functions facilitate reporting. functions previously described (e.g., show_wqmatrix()). First, show_annualassess() function can create simple table annual management outcome assessments chlorophyll-light attenuation bay segment. provides summary results given year, including segment-averaged chlorophyll-light attenuation bay segment names colored management outcome. required inputs EPC dataset selected year. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Second, show_ratab() function provides table annual water quality outcomes relative five-year RA reporting period. table includes associated NMC actions followed based water quality outcomes, actions provide reasonable assurance water quality maintained restored following outcomes. results specific four bay segments. Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2)    years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years    years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/   necessary due observed water quality seagrass conditions bay segment NMC Actions 4-5: Determine entity/source/facility specific exceedences 5-yr average allocation occurred implementation period necessary chlorophyll-threshold met show_ratab() function developed 2022-2026 RA period currently work previous RA periods. function may updated future accommodate different periods.","code":"show_annualassess(epcdata, yrsel = 2023) show_annualassess(epcdata, yrsel = 2023, caption = TRUE) show_ratab(epcdata, yrsel = 2023, bay_segment = 'OTB')"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Seagrass Transect Data","text":"two datasets included tbeptools show actively monitored transect locations Tampa Bay. trnpts dataset point object starting location transect trnlns dataset line object showing approximate direction length transect beginning point trnpts. dataset also includes MonAgency column indicates monitoring agency collects data transect. two datasets sf() (simple features) objects easily mapped mapview() view locations. transect data can downloaded Water Atlas using read_transect() function. required argument function training, indicates want download training data complete dataset, .e., training = TRUE training = FALSE (default). former case, small dataset downloaded includes data collected annual training event. primarily used internally TBEP staff assess precision among different training crews. data downloaded JSON object formatted internally using read_formtransect() function. Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates blade length cm. Change training argument FALSE download entire transect database. may take seconds. columns complete transect database describe crew (Crew), monitoring agency (MonitoringAgency), sample date (Date), transect name (Transect), meter location quadrat along transect (Site, m), depth site (Depth, cm), Seagrass species (Savspecies), distance seagrass edge transect (SeagrassEdge, m), seagrass variable (var), average value variable (aveval), standard deviation variable appropriate (sdval). raw, unformatted transect data preferred, use raw = TRUE argument read_transect().","code":"trnpts #> Simple feature collection with 66 features and 11 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.8089 ymin: 27.49925 xmax: -82.39305 ymax: 28.0001 #> Geodetic CRS:  WGS 84 #> First 10 features: #>    SEGMENT TRANSECT TRAN_ID Metermark    ID   LAT_DD   LONG_DD MonAgency STATUS #> 1        1        1    S1T1         0 START 27.99498 -82.68325     EPCHC ACTIVE #> 2        1        3    S1T3         0 START 28.00010 -82.66417     EPCHC ACTIVE #> 3        1        5    S1T5         0 START 27.95788 -82.54663      FDEP ACTIVE #> 4        1        6    S1T6         0 START 27.91348 -82.53282     EPCHC ACTIVE #> 5        1        8    S1T8         0 START 27.86233 -82.56867     EPCHC ACTIVE #> 6        1       13   S1T13         0 START 27.92428 -82.70232     EPCHC ACTIVE #> 7        1       14   S1T14         0 START 27.85533 -82.59738     EPCHC ACTIVE #> 8        1       15   S1T15         0 START 27.87408 -82.53098     EPCHC ACTIVE #> 9        1       16   S1T16         0 START 27.88228 -82.62015     PCDEM ACTIVE #> 10       1       17   S1T17         0 START 27.90498 -82.64793     PCDEM ACTIVE #>    Comments bay_segment                   geometry #> 1      <NA>         OTB POINT (-82.68325 27.99498) #> 2      <NA>         OTB  POINT (-82.66417 28.0001) #> 3      <NA>         OTB POINT (-82.54663 27.95788) #> 4      <NA>         OTB POINT (-82.53282 27.91348) #> 5      <NA>         OTB POINT (-82.56867 27.86233) #> 6      <NA>         OTB POINT (-82.70232 27.92428) #> 7      <NA>         OTB POINT (-82.59738 27.85533) #> 8      <NA>         OTB POINT (-82.53098 27.87408) #> 9      <NA>         OTB POINT (-82.62015 27.88228) #> 10     <NA>         OTB POINT (-82.64793 27.90498) trnlns #> Simple feature collection with 61 features and 7 fields #> Geometry type: LINESTRING #> Dimension:     XYM #> Bounding box:  xmin: -82.8118 ymin: 27.49807 xmax: -82.39306 ymax: 28.0001 #> m_range:       mmin: 0 mmax: 2700 #> Geodetic CRS:  WGS 84 #> First 10 features: #>    OBJECTID  Site Shape_Leng MonAgency ActiveYN Comments #> 1         1  S1T1   300.1400     EPCHC      YES     <NA> #> 2         5 S1T13  1102.6182     EPCHC      YES     <NA> #> 3         6 S1T14   800.4500     EPCHC      YES     <NA> #> 4         7 S1T15   701.0075     EPCHC      YES     <NA> #> 5         8 S1T16   998.9961     PCDEM      YES     <NA> #> 6         9 S1T17  2698.5773     PCDEM      YES     <NA> #> 7        10 S1T18   997.5451     EPCHC      YES     <NA> #> 8        12  S1T3   401.5991     EPCHC      YES     <NA> #> 9        14  S1T5   457.5927      FDEP      YES     <NA> #> 10       15  S1T6   398.6606     EPCHC      YES     <NA> #>                          geometry     bearing #> 1  LINESTRING M (-82.68325 27....  116.533756 #> 2  LINESTRING M (-82.70232 27....   -4.689701 #> 3  LINESTRING M (-82.59738 27....  109.402541 #> 4  LINESTRING M (-82.53098 27....  -85.765142 #> 5  LINESTRING M (-82.62015 27....   13.913960 #> 6  LINESTRING M (-82.64791 27....  -21.165576 #> 7  LINESTRING M (-82.61143 27.... -123.050914 #> 8  LINESTRING M (-82.66417 28.... -128.034327 #> 9  LINESTRING M (-82.54663 27.... -121.861907 #> 10 LINESTRING M (-82.53282 27....  -89.362036 cols <- c(\"#E16A86\", \"#CB7F2F\", \"#9F9400\", \"#50A315\", \"#00AC79\", \"#00AAB7\", \"#009ADE\", \"#A87BE4\", \"#DA65C3\")  mapview(trnpts, zcol = 'MonAgency', lwd = 0, legend = F, homebutton = F, col.regions = cols) +    mapview(trnlns, zcol = 'MonAgency', homebutton = F, layer.name = 'Monitoring Agency', lwd = 4, color = cols) # import training data traindat <- read_transect(training = TRUE)  # view the data traindat #> # A tibble: 1,428 × 11 #>       yr grp   grpact    Crew  MonitoringAgency Site  Depth Species var   aveval #>    <int> <chr> <chr>     <chr> <chr>            <chr> <int> <chr>   <chr>  <dbl> #>  1  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Abun…    3   #>  2  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Blad…    0   #>  3  2020 A     2020: MC… K. H… MCNRD            1       -50 Halodu… Shor…    0   #>  4  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Abun…    0   #>  5  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Blad…    0   #>  6  2020 A     2020: MC… K. H… MCNRD            2       -40 No Cov… Shor…    0   #>  7  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Abun…    5   #>  8  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Blad…   22   #>  9  2020 A     2020: MC… K. H… MCNRD            3       -60 Halodu… Shor…   27.3 #> 10  2020 A     2020: MC… K. H… MCNRD            3       -60 Thalas… Abun…    1   #> # ℹ 1,418 more rows #> # ℹ 1 more variable: sdval <dbl> # import entire transct dataset as JSON transect <- read_transect(training = FALSE)  # view the data transect #> # A tibble: 154,476 × 11 #>    Crew              MonitoringAgency Date       Transect Site  Depth Savspecies #>    <chr>             <chr>            <date>     <chr>    <chr> <int> <chr>      #>  1 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  2 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  3 A. McClory, A. I… MCNRD            2024-08-13 S4T2     0       -10 No Cover   #>  4 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  5 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  6 A. McClory, A. I… MCNRD            2024-08-13 S4T2     100     -40 Thalassia  #>  7 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #>  8 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #>  9 A. McClory, A. I… MCNRD            2024-08-13 S4T2     125     -25 Thalassia  #> 10 A. McClory, A. I… MCNRD            2024-08-13 S4T2     150      -5 Halodule   #> # ℹ 154,466 more rows #> # ℹ 4 more variables: SeagrassEdge <dbl>, var <chr>, aveval <dbl>, sdval <dbl> # raw transect data transectraw <- read_transect(training = FALSE, raw = TRUE)  # view the data transectraw #> # A tibble: 51,806 × 46 #>    IDall AssessmentYear CreatedAt   Crew  CountingTech SeagrassEdge Secchi Sonde #>    <int>          <int> <chr>       <chr> <chr>               <dbl>  <dbl> <lgl> #>  1     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  2     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  3     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  4     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  5     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  6     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  7     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  8     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #>  9     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #> 10     2           1998 1998-10-15… NA    NA                     NA     NA FALSE #> # ℹ 51,796 more rows #> # ℹ 38 more variables: Weather <chr>, Hidden <lgl>, HiddenReason <lgl>, #> #   IsComplete <lgl>, QASubmittedAt <chr>, ReadyForQA <lgl>, #> #   QACompletedAt <chr>, MonitoringAgency <chr>, Transect <chr>, #> #   BaySegment <chr>, ID <int>, ObservationDate <chr>, Site <int>, #> #   Species <chr>, SpeciesAbundance <chr>, Appearance <chr>, #> #   BladeLength_1 <int>, BladeLength_2 <int>, BladeLength_3 <int>, …"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"calculating-seagrass-frequency-occurrence","dir":"Articles","previous_headings":"","what":"Calculating seagrass frequency occurrence","title":"Seagrass Transect Data","text":"rest seagrass functions tbeptools developed work complete database. show_complot() function (see ) developed training data. rest functions can used estimate plot frequency occurrence data. anlz_transectocc() function summarizes frequency occurrence transects dates collapsing species results across quadrats within transect. Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2 [1]. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species, including Caulerpa spp. (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. second function, anlz_transectave(), takes results anlz_transectocc() estimates annual results across major bay segments seagrass species averaging frequency occurrence across transects. function used internally within show_transectmatrix() function create summary plots. frequency occurrence estimates also binned categories simple trend assessments, e.g., red < 25%, orange 25-50%, yellow 50-75%, green > 75%. Results specific bay segments annual ranges can filtered bay_segment yrrng arguments. third function, anlz_transectavespp(), takes results anlz_transectocc() estimates annual averages across major bay segments last function, results retained individual species. function used internally within show_transectavespp() function create summary plots. summaries aggregated across selected bay segments, .e., default average species/year across segments. Results individual bay segment can returned appropriate argument, e.g., using bay_segment = 'OTB' select Old Tampa Bay. Results can also filtered specific species using species argument, default return . Caulerpa spp. Dapis spp. also included. Results individual bay segments anlz_transectavespp() can retained setting by_seg argument TRUE. Note totals returned case.","code":"transectocc <- anlz_transectocc(transect) transectocc #> # A tibble: 39,546 × 6 #> # Groups:   Date, Transect [1,521] #>    Date       Transect Savspecies              nsites foest bbest #>    <date>     <chr>    <chr>                    <int> <dbl> <dbl> #>  1 1997-10-11 S2T3     \"AA\"                        41     0     0 #>  2 1997-10-11 S2T3     \"Caulerpa\"                  41     0     0 #>  3 1997-10-11 S2T3     \"DA\"                        41     0     0 #>  4 1997-10-11 S2T3     \"DB: Dictyota\\r\\n\"          41     0     0 #>  5 1997-10-11 S2T3     \"DB: Drift Brown\\r\\n\"       41     0     0 #>  6 1997-10-11 S2T3     \"DG: Chaetomorpha\\r\\n\"      41     0     0 #>  7 1997-10-11 S2T3     \"DG: Drift Green\"           41     0     0 #>  8 1997-10-11 S2T3     \"DG: Ulva\"                  41     0     0 #>  9 1997-10-11 S2T3     \"DG: Ulva fasciata\\r\\n\"     41     0     0 #> 10 1997-10-11 S2T3     \"DR: Acanthophora\"          41     0     0 #> # ℹ 39,536 more rows transectave <- anlz_transectave(transectocc) transectave #> # A tibble: 156 × 4 #> # Groups:   bay_segment [6] #>    bay_segment    yr foest focat   #>    <fct>       <dbl> <dbl> <fct>   #>  1 Tampa Bay    1998  58.0 #E9C318 #>  2 OTB          1998  65.5 #E9C318 #>  3 HB           1998  15.0 #CC3231 #>  4 MTB          1998  53.7 #E9C318 #>  5 LTB          1998  80.8 #2DC938 #>  6 BCB          1998  81.0 #2DC938 #>  7 Tampa Bay    1999  51.5 #E9C318 #>  8 OTB          1999  64.7 #E9C318 #>  9 HB           1999  10.1 #CC3231 #> 10 MTB          1999  51.8 #E9C318 #> # ℹ 146 more rows transectavespp <- anlz_transectavespp(transectocc) transectavespp #> # A tibble: 208 × 3 #>       yr Savspecies   foest #>    <dbl> <fct>        <dbl> #>  1  1998 Caulerpa    0.0166 #>  2  1998 Dapis       0      #>  3  1998 Halodule    0.361  #>  4  1998 Halophila   0      #>  5  1998 Ruppia      0.0112 #>  6  1998 Syringodium 0.0451 #>  7  1998 Thalassia   0.254  #>  8  1998 total       0.580  #>  9  1999 Caulerpa    0.0277 #> 10  1999 Dapis       0      #> # ℹ 198 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,170 × 5 #>       yr bay_segment Savspecies  foest nsites #>    <dbl> <fct>       <fct>       <dbl>  <int> #>  1  1998 BCB         Caulerpa    0         96 #>  2  1998 BCB         Dapis       0         96 #>  3  1998 BCB         Halodule    0.613     96 #>  4  1998 BCB         Halophila   0         96 #>  5  1998 BCB         No Cover    0.190     96 #>  6  1998 BCB         Ruppia      0         96 #>  7  1998 BCB         Syringodium 0         96 #>  8  1998 BCB         Thalassia   0.304     96 #>  9  1998 BCB         total       0.810     96 #> 10  1998 HB          Caulerpa    0        285 #> # ℹ 1,160 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Seagrass Transect Data","text":"one plotting function training data. show_compplot() function used compare training data crews selected species (species argument) variable (varplo argument).  rest plotting functions work complete transect data. Data individual transect can viewed show_transect() function entering transect (site) number, species (one many), variable plot. plot shows relative values selected species variable distance along transect (x-axis) year sampling (y-axis). plots provide overall summary temporal spatial changes selected seagrass metric individual location.  plot can also produced plotly interactive plot setting plotly = TRUE inside function. Note size legend merged species legend, point size average abundance species. sizes can viewed mouseover point. show_transect() function can also used plot multiple species. One many species can provided species argument.  plots can also separated facets species using facet = TRUE. useful reduce overplotting multiple species found location.  show_transectsum() function provides alternative summary data individual transect. plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Unlike show_transect(), plot shows aggregated results across quadrats along transect uses summarized data anlz_transectocc() function input. summary matrix frequency occurrence estimates across species can plotted show_transectmatrix(). uses results anlz_transectocc() anlz_transectave() functions estimate annual averages bay segment. continuous frequency occurrence estimates binned color categories described , Table 1 [2].  default color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. don’t necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette.  matrix can also produced plotly interactive plot setting plotly = TRUE inside function. Time series plots annual averages frequency occurrence estimates species can shown show_transectavespp() function. default, estimates averaged across bay segments species. plot representation Figure 2 [2].  Results individual segments species can returned bay_segment species arguments. Use argument total = FALSE omit total frequency occurrence plot.  plot can also produced plotly interactive plot setting plotly = TRUE inside function. alternative plotting species averages time show_transectavespp(), table can created setting asreact = TRUE. Filtering options apply plot also apply table, e.g., filtering four major bay segments specific year ranges. Also note totals returned table. describes methods tbeptools working transect monitoring data. Seagrass coverage maps also created approximately biennially Southwest Florida Water Management District, available https://data-swfwmd.opendata.arcgis.com/. seagrass data object included package shows Tampa Bay coverage total year available data, including 1950s reference estimate. show_seagrasscoverage() function creates flagship seagrass coverage graphic report changes time data.","code":"show_compplot(traindat, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance', base_size = 14) show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance', plotly = T) show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance', facet = TRUE) show_transectsum(transectocc, site = 'S3T10') show_transectmatrix(transectocc) show_transectmatrix(transectocc, neutral = T) show_transectmatrix(transectocc, plotly = T) show_transectavespp(transectocc) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), total = FALSE) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), plotly = T) show_transectavespp(transectocc, asreact = T, bay_segment = c('HB', 'OTB', 'MTB', 'LTB'), yrrng = c(2006, 2012)) show_seagrasscoverage(seagrass)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Benthic Index","text":"Tampa Bay Benthic Index (TBBI) [1,2]) assessment method quantifies ecological health benthic community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available region (e.g., water quality report card, nekton index, etc.). tbeptools package includes several functions described import data required index plot results view trends time. functions described detail . TBBI uses data Tampa Bay Benthic Monitoring Program part Environmental Protection Commission (EPC) Hillsborough Country. data updated annually public site maintained EPC, typically December Summer/Fall sampling. website hosts water quality data used water quality report card. required data TBBI extensive water quality report card data made available zipped folder csv files, available . process downloading working data similar functions tbeptools.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Benthic Index","text":"Data calculating TBBI scores can imported current R session using read_importbenthic() function. function downloads zipped folder base tables used TBBI EPC site data already downloaded location specified input arguments. download data tbeptools, first create character path location want download zipped files. one exist, specify location name downloaded file. , name folder benthic.zip download desktop. Running code return following error: get error message function indicating file found. makes sense file exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved benthicdata object current R session. try run function downloading data, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work benthic data, read_importbenthic() used import data. always receive message File current... local file matches one server. However, data periodically updated posted server. download_latest = TRUE local file date, receive following message:","code":"path <- '~/Desktop/benthic.zip' benthicdata <- read_importbenthic(path) #> Error in read_importbenthic() : File at path does not exist, use download_latest = TRUE benthicdata <- read_importbenthic(path, download_latest = T) #> File ~/Desktop/benthic.zip does not exist, replacing with downloaded file...  #> trying URL 'https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1' length 37122877 bytes (35.4 MB) benthicdata <- read_importbenthic(path, download_latest = T) #> File is current.. #> Replacing local file with current..."},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"calculating-tbbi-scores","dir":"Articles","previous_headings":"","what":"Calculating TBBI scores","title":"Tampa Bay Benthic Index","text":"data imported, can view assigned object. data provided nested tibble includes three different datasets: station information, field sample data (salinity), detailed taxa information. individual datasets can viewed extracting parent object using deframe() function tibble package. anlz_tbbiscr() function uses nested benthicdata estimate TBBI scores site. TBBI scores typically range 0 100 grouped categories describe general condition benthic community. Scores less 73 considered “degraded”, scores 73 87 “intermediate”, scores greater 87 “healthy”. Locations sampled organisms found assigned score zero category “empty sample”. total abundance (TotalAbundance, organisms/m2), species richness (SpeciesRichness) bottom salinity (Salinity, psu) also provided. metrics TBBI corrected salinity bottom measurements taken time sampling required accurate calculation TBBI.","code":"benthicdata #> # A tibble: 3 × 2 #>   name         value                  #>   <chr>        <list>                 #> 1 stations     <tibble [4,787 × 10]>  #> 2 fieldsamples <tibble [5,197 × 3]>   #> 3 taxacounts   <tibble [149,657 × 7]> # see all deframe(benthicdata) #> $stations #> # A tibble: 4,787 × 10 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl> #>  #> $fieldsamples #> # A tibble: 5,197 × 3 #>    StationID date       Salinity #>        <int> <date>        <dbl> #>  1       448 2002-05-21     30.5 #>  2       449 2002-05-20     30.8 #>  3       450 2002-05-21     30.5 #>  4       451 2002-05-21     30.6 #>  5       452 2002-05-20     30   #>  6       453 2002-05-21     30.6 #>  7       454 2002-05-21     30.5 #>  8       455 2002-05-21     30.3 #>  9       456 2002-05-20     30.0 #> 10       457 2002-05-20     29.9 #> # ℹ 5,187 more rows #>  #> $taxacounts #> # A tibble: 149,657 × 7 #>    StationID TaxaCountID TaxaListID FAMILY           NAME     TaxaCount AdjCount #>        <int>       <int>      <int> <chr>            <chr>        <dbl>    <dbl> #>  1     11321      152055       1198 Anomiidae        Anomia …         1       25 #>  2     11321      152056       1224 Carditidae       Cardite…         1       25 #>  3       584      233277        624 Cirratulidae     Chaetoz…         1       25 #>  4     11321      152057       1306 Veneridae        Chione …         3       75 #>  5      3132      239443        352 Pilargidae       Sigambr…        14      350 #>  6     11321      152058       1088 Pyramidellidae   Turboni…         6      150 #>  7      2541      140530        258 NULL             NEMERTEA         8      200 #>  8      2542      140531        258 NULL             NEMERTEA         2       50 #>  9      2992      140631        262 NULL             Palaeon…         4      100 #> 10      3003      140635        285 Tetrastemmatidae Tetrast…         2       50 #> # ℹ 149,647 more rows  # get only station dat deframe(benthicdata)[['stations']] #> # A tibble: 4,787 × 10 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl> tbbiscr <- anlz_tbbiscr(benthicdata) tbbiscr #> # A tibble: 4,787 × 15 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl>, #> #   TotalAbundance <dbl>, SpeciesRichness <dbl>, TBBI <dbl>, TBBICat <chr>, #> #   Salinity <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Benthic Index","text":"TBBI scores can viewed annual averages bay segment using show_tbbimatrix() function. show_tbbimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. baywide estimate also returned, one based samples across locations (“”) another weighted relative surface areas bay segment (“(wt)”). input show_tbbimatrix() function output anlz_tbbiscr() function.  matrix can also produced plotly interactive plot setting plotly = TRUE inside function.","code":"show_tbbimatrix(tbbiscr) show_tbbimatrix(tbbiscr, plotly = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"additional-sediment-data","dir":"Articles","previous_headings":"","what":"Additional sediment data","title":"Tampa Bay Benthic Index","text":"addition biological data, sediment contaminant concentrations measured sites within Tampa Bay. include 100 different constituents grouped broadly metals, organics, physical, . concentrations constituents can compared relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available, relative indications likelihood concentrations toxic effects invertebrates inhabit sediments. functions tbeptools can used retrieve sediment data provide indication concentrations relative TEL PEL thresholds. read_importsediment() function retrieve sediment data Tampa Bay collected annually Environmental Protection Commission Hillsborough County. data retrieved location biological data used calculate TBBI. data imported, can view assigned object. show_sedimentmap() function can used create maps selected parameters relative TEL PEL values. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. selected stations sampled years within yrrng argument. single year data can shown well. map showing concentrations returned TEL PEL values available parameter. Maps total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned. Although totals included sedimentdata object, calculated tbeptools using anlz_sedimentaddtot() function. Simply entering name total parameter show_sedimentmap() function produce summary map. PEL ratio can also used assess relative sediment quality given measured contaminants. show_sedimentpelmap() function creates map average PEL ratios graded F benthic stations monitored Tampa Bay. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station. average PEL ratios grades used create map can also returned data frame using anlz_sedimentpel(). Plots bay segment averages sediment concentrations selected parameters can created show_sedimentave(). plot includes appropriate lines TEL PEL values, well grand mean across segments. former omitted plot unavailable selected parameter.  plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentave(). , total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned even though included sedimentdata object. anlz_sedimentaddtot() function used calculate totals within anlz_sedimentave(). similar plot bay segment averages average PEL ratios can created show_sedimentpelave(). colors indicate grades (green) F (red).  plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentpelave(). show_sedimentalratio() function creates plot selected metal parameter Aluminum. plot provides information concentration parameter relative background levels, Aluminum present common metal Earth’s crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations [3]. linear fit log-log model shown solid black line, 95% prediction intervals. TEL/PEL values, available, also shown horizontal red lines.  plot can returned interactive plotly object using plotly = T.","code":"path <- '~/Desktop/sediment.zip' sedimentdata <- read_importsediment(path, download_latest = T) sedimentdata #> # A tibble: 221,597 × 24 #>    ProgramId ProgramName   FundingProject    yr AreaAbbr StationID StationNumber #>        <int> <chr>         <chr>          <int> <chr>        <int> <chr>         #>  1         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  2         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  3         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  4         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  5         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  6         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  7         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  8         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  9         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> 10         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> # ℹ 221,587 more rows #> # ℹ 17 more variables: Latitude <dbl>, Longitude <dbl>, Replicate <chr>, #> #   SedResultsType <chr>, Parameter <chr>, ValueAdjusted <dbl>, Units <chr>, #> #   Qualifier <chr>, MDLnum <dbl>, PQLnum <dbl>, TEL <dbl>, PEL <dbl>, #> #   BetweenTELPEL <chr>, ExceedsPEL <chr>, PELRatio <dbl>, #> #   PreparationDate <chr>, AnalysisTimeMerge <chr> show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = 2022) show_sedimentmap(sedimentdata, param = 'Selenium', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) show_sedimentpelmap(sedimentdata, yrrng = c(1993, 2022)) anlz_sedimentpel(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 2,233 × 7 #>       yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #>    <int> <chr>    <chr>            <dbl>     <dbl>    <dbl> <fct> #>  1  1993 HB       93HB15            27.8     -82.4  0.0157  B     #>  2  1993 HB       93HB16            27.8     -82.5  0.0261  C     #>  3  1993 HB       93HB23            27.9     -82.4  0.0174  B     #>  4  1993 LTB      93LTB24           27.7     -82.6  0.0124  B     #>  5  1993 LTB      93LTB25           27.6     -82.6  0.0189  B     #>  6  1993 LTB      93LTB26           27.6     -82.7  0.00997 B     #>  7  1993 LTB      93LTB27           27.6     -82.7  0.0125  B     #>  8  1993 LTB      93LTB28           27.6     -82.7  0.0887  D     #>  9  1993 LTB      93LTB29           27.6     -82.6  0.0350  C     #> 10  1993 LTB      93LTB30           27.6     -82.6  0.0496  C     #> # ℹ 2,223 more rows show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022), plotly = T) anlz_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       7.24  41.6 mg/kg  2.64 2.34   2.94     2.57 #> 2 HB        7.24  41.6 mg/kg  2.93 0.665  5.20     2.57 #> 3 LTB       7.24  41.6 mg/kg  2.93 2.47   3.40     2.57 #> 4 MR        7.24  41.6 mg/kg  1.66 1.37   1.95     2.57 #> 5 MTB       7.24  41.6 mg/kg  2.17 1.86   2.48     2.57 #> 6 OTB       7.24  41.6 mg/kg  3.24 0.707  5.78     2.57 #> 7 TCB       7.24  41.6 mg/kg  2.40 1.92   2.88     2.57 anlz_sedimentave(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       3.89  51.7 ug/kg 0.570 0.382 0.757    0.700 #> 2 HB        3.89  51.7 ug/kg 1.77  0.870 2.67     0.700 #> 3 LTB       3.89  51.7 ug/kg 0.218 0.105 0.332    0.700 #> 4 MR        3.89  51.7 ug/kg 0.838 0.517 1.16     0.700 #> 5 MTB       3.89  51.7 ug/kg 0.434 0.285 0.582    0.700 #> 6 OTB       3.89  51.7 ug/kg 0.490 0.274 0.706    0.700 #> 7 TCB       3.89  51.7 ug/kg 0.582 0.202 0.962    0.700 show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022), plotly = T) anlz_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 7 × 5 #>   AreaAbbr    ave    lov    hiv grandave #>   <fct>     <dbl>  <dbl>  <dbl>    <dbl> #> 1 BCB      0.0535 0.0445 0.0625   0.0522 #> 2 HB       0.118  0.0663 0.169    0.0522 #> 3 LTB      0.0281 0.0247 0.0315   0.0522 #> 4 MR       0.0446 0.0375 0.0516   0.0522 #> 5 MTB      0.0374 0.0327 0.0421   0.0522 #> 6 OTB      0.0506 0.0371 0.0642   0.0522 #> 7 TCB      0.0337 0.0265 0.0409   0.0522 show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB')) show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Nekton Index","text":"Tampa Bay Nekton Index (TBNI) [1,2]) multimetric assessment method quantifies ecological health nekton community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available Tampa Bay (e.g., water quality report card, Benthic index, etc.). tbeptools package includes several functions described import data required index, analyze data calculate metrics index scores, plot results view trends time. functions described detail . TBNI uses catch data Florida Fish Wildlife Conservation Commission (FWC) Fish Wildlife Research Institute’s (FWRI) Fisheries-Independent Monitoring (FIM) program. Catch results center-bag seine longest consistent record FIM database used develop TBNI. include counts taxa identification individuals caught near shore areas, generally early recruits, juveniles, smaller-bodied nekton. fish selected invertebrates identified lowest possible taxon (usually species), counted, subset measured. Current protocols established 1998 TBNI estimates unavailable prior date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Nekton Index","text":"Data required calculating TBNI scores can imported current R session using read_importfim() function. function downloads latest FIM file FTP site data already downloaded location specified input arguments. download data, first create character path location file. one exist, specify desired location name downloaded file. , want put file desktop home directory name fimdata.csv. Running code return following error: get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved fimdata object current R session. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current matches file server. Every time tbeptools used work FIM data, read_importfim() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: data successfully imported, can view assigned object: imported data formatted calculating TBNI. columns include Reference FIM sampling site, sampling date, sampling Zone, sampling Grid, NODCCODE unique identifier species, sample year, sample month, total catch Total_N, scientific name, column indicating species included index, several columns indicating species-specific information required metrics. final columns, separate lookup table provided package merged imported FIM data. file, tbnispp, can viewed anytime package loaded: read_importfim() function can also return simple features object sampled stations raw FIM data setting . data matched appropriate bay segments tabulating TBNI scores. resulting dataset indicates sampling occurred can mapped mapview() function. ease use, dataset named fimstations included tbeptools. read_importfim() function processes observed data needed TBNI, including merging rows tbnispp fimstations data. imported, metrics scores can calculated.","code":"csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv) #> Error in read_importfim(csv) : file.exists(csv) is not TRUE fimdata <- read_importfim(csv, download_latest = T) #> File ~/Desktop/fimdata.csv does not exist, replacing with downloaded file...  #> trying URL 'ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv' length 11083878 bytes (10.6 MB) fimdata <- read_importfim(csv, download_latest = T) #> File is current.. #> Replacing local file with current... head(fimdata) #> # A tibble: 6 × 19 #>   Reference    Sampling_Date Latitude Longitude Zone   Grid NODCCODE  Year Month #>   <chr>        <date>           <dbl>     <dbl> <chr> <int> <chr>    <dbl> <dbl> #> 1 TBM19980109… 1998-01-09        28.0     -82.7 A        31 8747020…  1998     1 #> 2 TBM19980109… 1998-01-09        28.0     -82.7 A        31 8805030…  1998     1 #> 3 TBM19980109… 1998-01-09        27.9     -82.7 A        62 6177010…  1998     1 #> 4 TBM19980109… 1998-01-09        27.9     -82.7 A        63 9998000…  1998     1 #> 5 TBM19980109… 1998-01-09        27.9     -82.6 A        65 8820020…  1998     1 #> 6 TBM19980109… 1998-01-09        27.9     -82.6 A        65 8826020…  1998     1 #> # ℹ 10 more variables: Total_N <dbl>, ScientificName <chr>, #> #   Include_TB_Index <chr>, Hab_Cat <chr>, Est_Cat <chr>, Est_Use <chr>, #> #   Feeding_Cat <chr>, Feeding_Guild <chr>, Selected_Taxa <chr>, #> #   bay_segment <chr> head(tbnispp) #>      TSN   NODCCODE               ScientificName Include_TB_Index Hab_Cat #> 1 173245 8860030201 Acanthostracion quadricornis                Y       B #> 2 172986 8858030202             Achirus lineatus                Y       B #> 3 160978 8713070101           Aetobatus narinari                Y       B #> 4 161121 8739010101                Albula vulpes                Y       P #> 5  96600 6179140000               Alpheidae spp.                N       B #> 6 173131 8860020101           Aluterus schoepfii                Y       B #>   Est_Cat Est_Use Feeding_Cat Feeding_Guild Selected_Taxa #> 1      MS       O          TS            ZB             N #> 2      ES       O          TS            ZB             N #> 3      MS       F          TS            ZB             N #> 4      MS       S          TS            ZB             Y #> 5                          DV            DV             N #> 6      MS       F          TS            HV             N fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) mapview(fimstations, zcol = 'bay_segment')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"calculating-metrics-and-tbni-scores","dir":"Articles","previous_headings":"","what":"Calculating metrics and TBNI scores","title":"Tampa Bay Nekton Index","text":"Metrics scores Tampa Bay Nekton Index can calculated using two functions. anlz_tbnimet() function calculates raw metrics anlz_tbniscr() function calculates scored metrics final TBNI score. functions use imported formatted FIM data input. TBNI includes five metrics sensitive stressor gradients provide unique information Nekton community response environmental conditions. metrics include: NumTaxa: Species richness BenthicTaxa: Species richness benthic taxa TaxaSelect: Number “selected” species (.e., commercially /recreationally important) NumGuilds: Number trophic guilds Shannon: Shannon Diversity (H) Raw metrics first calculated observed data scaled standard score 0 - 10 accounting expected relationships environmental gradients 5th/95th percentiles distributions. final TBNI score summed average scores ranging 0 - 100. raw metrics, scored metrics, final TBNI score returned anlz_tbniscr() function. five metrics chosen TBNI appropriate Tampa Bay dataset selected larger pool candidate metrics. potential metrics can calculated using anlz_tbnimet() function. metrics can used standalone assessments developing Nekton index outside Tampa Bay. argument = TRUE must used return metrics, otherwise selected five TBNI returned.","code":"tbniscr <- anlz_tbniscr(fimdata) head(tbniscr) #> # A tibble: 6 × 16 #>   Reference      Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #>   <chr>         <dbl> <dbl> <chr>  <chr>            <dbl>   <dbl>        <dbl> #> 1 TBM1998010906  1998     1 Winter OTB                 18       2            2 #> 2 TBM1998010910  1998     1 Winter OTB                 14       1            1 #> 3 TBM1998010912  1998     1 Winter OTB                  0       0            0 #> 4 TBM1998010914  1998     1 Winter OTB                 20       2            2 #> 5 TBM1998010915  1998     1 Winter MTB                 46       4            4 #> 6 TBM1998010917  1998     1 Winter MTB                 24       2            2 #> # ℹ 8 more variables: BenthicTaxa <dbl>, ScoreBenthicTaxa <dbl>, #> #   TaxaSelect <dbl>, ScoreTaxaSelect <dbl>, NumGuilds <dbl>, #> #   ScoreNumGuilds <dbl>, Shannon <dbl>, ScoreShannon <dbl> tbnimet <- anlz_tbnimet(fimdata, all = T) head(tbnimet) #> # A tibble: 6 × 37 #>   Reference      Year Month Season bay_segment NumTaxa NumIndiv Shannon Simpson #>   <chr>         <dbl> <dbl> <chr>  <chr>         <dbl>    <dbl>   <dbl>   <dbl> #> 1 TBM1998010906  1998     1 Winter OTB               2       17   0.362    1.26 #> 2 TBM1998010910  1998     1 Winter OTB               1        1   0        1    #> 3 TBM1998010912  1998     1 Winter OTB               0        0   0        0    #> 4 TBM1998010914  1998     1 Winter OTB               2        2   0.693    2    #> 5 TBM1998010915  1998     1 Winter MTB               4       11   1.16     2.81 #> 6 TBM1998010917  1998     1 Winter MTB               2        5   0.500    1.47 #> # ℹ 28 more variables: Pielou <dbl>, TaxaSelect <dbl>, NumGuilds <dbl>, #> #   TSTaxa <dbl>, TGTaxa <dbl>, BenthicTaxa <dbl>, PelagicTaxa <dbl>, #> #   OblTaxa <dbl>, MSTaxa <dbl>, ESTaxa <dbl>, SelectIndiv <dbl>, Taxa90 <dbl>, #> #   TSAbund <dbl>, TGAbund <dbl>, BenthicAbund <dbl>, PelagicAbund <dbl>, #> #   OblAbund <dbl>, ESAbund <dbl>, MSAbund <dbl>, Num_LR <dbl>, PropTG <dbl>, #> #   PropTS <dbl>, PropBenthic <dbl>, PropPelagic <dbl>, PropObl <dbl>, #> #   PropMS <dbl>, PropES <dbl>, PropSelect <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Nekton Index","text":"TBNI scores can viewed annual averages using show_tbniscr(), show_tbniscrall() show_tbnimatrix() functions. show_tbniscr() creates line graph values time bay segment, whereas show_tbniscrall() function plots overall average across bay segments time. show_tbnimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. input function output anlz_tbniscr() function.    plots can also produced plotly interactive plots setting plotly = TRUE inside function. breakpoints categorical outcomes TBNI scores shown colors graph based 33rd 50th percentiles distribution TBNI scores calculated Tampa Bay. plotting option provided consistency existing TBEP reporting tools, e.g., water quality report card returned show_matrix(). categorical outcomes serve management guidelines year activities support environmental resources Bay: Stay Course, Caution, Alert [3]. graphs returned plotting functions ggplot objects can modified. can combined using patchwork single graphic showing trends time categorical outcomes matrix continuous scores bottom plot.","code":"show_tbniscr(tbniscr) show_tbniscrall(tbniscr) show_tbnimatrix(tbniscr) show_tbniscr(tbniscr, plotly = T) show_tbniscrall(tbniscr, plotly = T) show_tbnimatrix(tbniscr, plotly = T) p1 <- show_tbnimatrix(tbniscr, txtsz = NULL, rev = TRUE, position = 'bottom') +   scale_y_continuous(expand = c(0,0), breaks = c(1998:2020)) +   coord_flip() +   theme(axis.text.x = element_blank())  p2 <- show_tbniscr(tbniscr)  p1 + p2 + plot_layout(ncol = 1, heights = c(0.3, 1))"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tidal Creek Assessment","text":"Dashboard: https://shiny.tbep.org/tidalcreek-dash/ Tidal creeks (aka tributaries) essential habitats Tampa Bay Estuary serve important focal points understanding watershed inputs affect water quality. fundamental goal Tampa Bay Estuary Program develop effective nutrient management strategies support ecological function tidal creeks. partnership Sarasota Bay NEP, Coastal & Heartland NEP, local government agency stakeholders, open science framework developed assessing tidal creek condition based host commonly collected water quality data [1–3]. assessments can support tracking water quality management goals can help refine restoration management plans priority tributaries, including need hydrologic restoration can support critical nursery habitats sportfishes. tbeptools package includes simple features spatial data object population tidal creeks southwest Florida, called tidalcreeks(). includes 615 polyline features designated water body ID (WBID), creek id (JEI), FDEP class (class, 1 potable water, 2 shellfish harvesting propagation, 3F/3M freshwater/marine fish consumption, recreation, propagation maintenance healthy, well-balanced population fish wildlife). tidal creek assessment framework established based data FDEP Impaired Waters Rule database run 56 available includes data collected January 10th 2019. However, framework intends link future IWR databases refresh site new data becomes available. Raw updated data IWR database required assessment provided tbeptools package iwrraw() data object.","code":"mapview(tidalcreeks, homebutton = F, legend = F)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"assessment","dir":"Articles","previous_headings":"","what":"Assessment","title":"Tidal Creek Assessment","text":"tidal creek assessment framework includes “report card” “indicators” assessment provided separate tabs dashboard. report card provides assessment total nitrogen concentrations (limiting nutrient creeks) based annual geometric average concentrations relative standards developed contributing freshwater streams. indicators based several water quality metrics derived outcomes study describe tidal creek condition provide insights site specific attributes creeks may govern overall creek health.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card","dir":"Articles","previous_headings":"","what":"Report card","title":"Tidal Creek Assessment","text":"report card similar TBEP water quality report card tidal creeks assigned categories within assessment framework intended serve mechanism evaluating data relative need management action, identify stewardship goals , properly pursued, may preclude need regulatory actions. categories established based principally fish biological response indicator. Tidal creeks assigned one five categories: Data: Data unavailable evaluation. Monitor: Creek nitrogen concentrations protect individual creek types within larger population creeks. Caution: Creek nutrients showing signs elevated nutrient concentrations may increase risk eutrophic condition. Investigate: Creek nutrient concentrations margin safety protect creek potential impairment. Prioritize: Creek nutrient concentrations exceeded regulatory standard associated freshwater portion tributary indicating actions needed identify remediative measures reduce nutrients creek. Conceptually, thresholds appear figure . Scoring rubrik tidal creeks based nitrogen thresholds. Prioritize category defined based Florida’s freshwater stream numeric nutrient criteria (NNC).Two different freshwater stream NNC applicable region; West Central NNC 1.65 mg/l Peninsular region NNC 1.54 mg/l. histograms figure represent range annual geometric mean (AGM) nitrogen concentrations associated Prioritize Investigate categories based NNC. example , maximum expected distribution AGMs exceed 1.65 mg/l 1:3 exceedence probability (defined F..C. 62-303) generated using monte carlo simulation highest observed standard deviation data collected first creeks study. Investigate category defined explicit margin safety adjusting distribution find grand geometric average result 1:20 chance exceeding 1.65 mg/l. Assignment creek Caution category depended creek length adjustment described protect smaller creeks elevated nutrient concentrations. tidaltargets() data object included tbeptools includes thresholds. Note “Caution” category function creek length. scoring algorithm derived define final report card outcome creek using entire ten year record available data based following criteria. single exceedance Prioritize Investigate categories year ten year record result classification creek respective category unless least three years data threshold level category. Creeks assigned next lower category one AGM TN given level multiple years (.e., two) given levels defining cutoff points category. example, creek least 4 years data single exceedance Prioritize threshold assigned Investigate category. Outcomes exemplified .","code":"tidaltargets #>         region prioritize investigate #> 1 West Central       1.65        1.38 #> 2    Peninsula       1.54        1.30 #>                                             caution #> 1 1.38 - 0.0174 * (23.78 - (Creek_Length_m / 1000)) #> 2 1.30 - 0.0174 * (23.78 - (Creek_Length_m / 1000))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card-functions","dir":"Articles","previous_headings":"Report card","what":"Report card functions","title":"Tidal Creek Assessment","text":"two primary functions tidal creek assessments anlz_tdlcrk() obtain scores show_tdlcrk() view interactive map results. anlz_tdlcrk() function uses included tidalcreeks() iwrraw() datasets estimate scores: results include unique creek identifier (id, based wbid JEI fields), waterbody id (wbid), creek ID (JEI), FDEP class (class), results assessment remaining columns. columns monitor, caution, investigate, prioritize indicate number years 2012 2021 nitrogen values within ranges appropriate creek type specified within tidaltargets(). score column indicates overall category assigned creek period record. Note many creeks assigned Data value sufficient data unavailable. summation four component columns (monitor, caution, investigate, prioritize) provides number years data available creek. show_tdlcrk() function can used output anlz_tdlcrk() view interactive map results. Creeks color-coded exceedance categories, “Data” creeks shown light blue. report card style matrix can plotted using show_tdlcrkmatrix() function shows overall creek score number years data used estimate overall score. plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency. default, plot shows creeks marine WBID (water body identifier) designation 3M 2. can changed class argument (.e., class c('3M', '2', '3F', '1') marine freshwater WBIDs).","code":"results <- anlz_tdlcrk(tidalcreeks, iwrraw) results #> # A tibble: 615 × 10 #>       id wbid  JEI   name     class monitor caution investigate prioritize score #>    <int> <chr> <chr> <chr>    <chr>   <dbl>   <dbl>       <dbl>      <dbl> <chr> #>  1     1 1983B CC01  Rock Cr… 2          NA      NA          NA         NA No D… #>  2     2 2052  CC01  Rock Cr… 3M         10      NA          NA         NA Moni… #>  3     3 1983B CC02  Oyster … 2          NA      NA          NA         NA No D… #>  4     4 2067  CC02  Oyster … 3M         10      NA          NA         NA Moni… #>  5     5 1983B CC03  Buck Cr… 2          NA      NA          NA         NA No D… #>  6     6 2068  CC03  Buck Cr… 3M          9       1          NA         NA Moni… #>  7     7 2078A CC04  Buck Cr… 2          NA      NA           1         NA Inve… #>  8     8 2078A CC05  Coral C… 2          NA      NA          NA         NA No D… #>  9     9 2078B CC05  Coral C… 2           4       1          NA         NA Moni… #> 10    10 2065C CC06  Catfish… 2          NA      NA          NA         NA No D… #> # ℹ 605 more rows show_tdlcrk(results) show_tdlcrkmatrix(results)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"indicator-functions","dir":"Articles","previous_headings":"Report card","what":"Indicator functions","title":"Tidal Creek Assessment","text":"Water quality Indicators developed provide context interpreting report card outcomes described detail Wessel et al. 2021 include thresholds total nitrogen (>1.1 mg/l), chlorophyll (>11 ug/l), dissolved oxygen (< 42 % saturation), trophic state index score (>55), chlorophyll/nitrogen ratio (>15) ratio nitrates tidal freshwater portion creek (>1) (data available). results indicator relative established thresholds calculated annual basis synthesized 10 year period calculating percentage annual outcomes exceeding identified threshold indicator values total number years available data. integrative summary indicators presented using standardized polar coordinate system Radar Charts provide single multi-metric summary plot results across indicators. anlz_tdlcrkindic() function generates annual outcomes wbid/JEI combination. Individual creek indicators summarized using multivariate response plot called “radar plot” indicates percentage years indicator exceeded respective threshold value. plots created using radar = TRUE argument anlz_tdlcrkindic() function using results show_tdlcrkradar() function. radar plots apply marine WBIDs tidal creeks (Florida DEP class 2, 3M). Indicators without data creek point plot.  General descriptive plots annual outcomes provided interactive plotly graphics using show_tdlcrkindic() show_tdlcrkindiccdf() functions. show_tdlcrindic() function produces bar plots annual outcomes selected creek. creek plot selected id argument integer used filter results anlz_tdlcrkindic() function, latter passed cntdat argument. thrsel argument plots dotted red lines based threshold values. year unique color. show_tdlcrkindiccdf() function similar except empirical cumulative distribution functions (CDF) plotted evaluate outcomes specific creek relative entire distribution creeks southwest Florida. indicator year selected creek plotted CDF curves. Location points indicate comparison population trajectory indicators time (.e., brown older observations blue recent). Holding mouse cursor point shows year holding cursor line shows percentile value CDF.","code":"results <- anlz_tdlcrkindic(tidalcreeks, iwrraw) head(results) #>   id       name  JEI wbid class year    CHLAC    COLOR COND       DO    DOSAT #> 1  2 Rock Creek CC01 2052    3M 2014 2.380249 14.69473   NA 3.308289 60.31523 #> 2  2 Rock Creek CC01 2052    3M 2015 2.647817 21.91113   NA 4.034172 55.41609 #> 3  2 Rock Creek CC01 2052    3M 2016 2.265462 19.13080   NA 3.980251 55.96637 #> 4  2 Rock Creek CC01 2052    3M 2017 2.851726 15.39576   NA 4.157777 60.18017 #> 5  2 Rock Creek CC01 2052    3M 2018 1.934899 11.65500   NA 4.219790 63.32630 #> 6  2 Rock Creek CC01 2052    3M 2019 2.071003  7.21425   NA 3.015847 44.90322 #>          NO23 ORGN    SALIN       TKN        TN         TP TSS     TURB #> 1 0.007575792   NA 26.63714 0.6161702 0.6228782 0.06938150  NA 2.044623 #> 2 0.009361504   NA 19.10494 0.6465161 0.5678241 0.07602770  NA 1.814818 #> 3 0.008532522   NA 25.84531 0.5813818 0.5408161 0.08330509  NA 2.082253 #> 4 0.007447260   NA 24.86909 0.6255197 0.6326848 0.07566682  NA 1.802161 #> 5 0.006994714   NA 31.32419 0.5668727 0.5734574 0.07432007  NA 2.454007 #> 6 0.007047106   NA 31.63214 0.5053022 0.4577485 0.06300538  NA 1.831953 #>   chla_tn_ratio tn_tp_ratio chla_tsi   tn_tsi  tn2_tsi   tp_tsi  tp2_tsi #> 1      3.821371    8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2      4.663093    7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3      4.188970    6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4      4.507341    8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5      3.374095    7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6      4.524324    7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #>    nut_tsi      tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651          NA         NA         NA       0       1 #> 2 47.43600 39.12890          NA         NA         NA       0       1 #> 3 46.38844 37.48223          NA         NA         NA       0       1 #> 4 49.76107 40.82559          NA         NA         NA       0       0 #> 5 47.64821 36.97650          NA         NA         NA       0       1 #> 6 42.80384 35.04375          NA         NA         NA       1       1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = T)  # get random creek id set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id = id, cntdat = cntdat) cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkindic(id = id, cntdat = cntdat, thrsel = TRUE) show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Marcus Beck. Author, maintainer. Meagan Schrandt. Author. Mike Wessel. Author. Ed Sherwood. Author. Gary Raulerson. Author. Adhokshaja Achar Budihal Prasad. Author. Benjamin Best. Author. Kim Cressman. Author.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beck, M.W., Schrandt, M.N., Wessel, M.R., Sherwood, E.T., Raulerson, G.E., Budihal Prasad, .., Best, B.D., (2021). tbeptools: R package synthesizing estuarine data environmental research. Journal Open Source Software, 6(65), 3485, https://doi.org/10.21105/joss.03485","code":"@Article{,   title = {{t}beptools: An {R} package for synthesizing estuarine data for environmental research},   author = {Marcus Beck and Meagan Schrandt and Mike Wessel and Ed Sherwood and Gary Raulerson and Adhokshaja Achar {Budihal Prasad} and Benjamin Best},   journal = {Journal of Open Source Software},   year = {2021},   volume = {6},   number = {65},   pages = {3485},   doi = {10.21105/joss.03485}, }"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"tbeptools","dir":"","previous_headings":"","what":"Data and Indicators for the Tampa Bay Estuary Program","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"R package Tampa Bay Estuary Program functions. Please see vignettes full description.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"package can installed r-universe. source code available tbep-tech GitHub group web page: https://github.com/tbep-tech/tbeptools. Note tbeptools needs installed , needs loaded every new R session (.e., library(tbeptools)). package loaded, can view help files function typing question mark followed function name, e.g., ?read_importwq, console. help files provide brief description function required arguments needed run function.","code":"# enable repos options(repos = c(     tbeptech = 'https://tbep-tech.r-universe.dev',     CRAN = 'https://cloud.r-project.org'))  # install tbeptools install.packages('tbeptools')  # load tbeptools library(tbeptools)"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"vignettes organized topic excellent place start understanding use package. Currently, six vignettes available tbeptools: Water Quality Data: Overview functions working water quality data water quality report card Tampa Bay Nekton Index: Overview functions import, analyze, plot results Tampa Bay Nekton Index Tampa Bay Benthic Index: Overview functions import data Tampa Bay Benthic Index, development Tidal Creeks Assessment: Overview functions import, analyze, plot results assessment tidal creeks southwest Florida Seagrass Transect Data: Overview functions import, analyze, plot results seagrass transect data collected Tampa Bay Habitat Master Plan: Overview functions analyze create report card Tampa Bay Habitat Master Plan 2020 update Fecal Indicator Bacteria: Overview functions import, analyze, plot results Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"core functions tbeptools three categories based mode use. function named using prefix mode use, followed function . prefixes : read: Import current data main site. anlz: Analyze summarize imported data. show: Create plot analyzed data. functions can easily found RStudio loading package typing prefix command line. autofill dialog box pop showing functions apply prefix. eliminates need searching individual functions know category function need (e.g., read, anlz, show). function also includes semi-descriptive suffix generally describes category applies (e.g, water quality, seagrass) (e.g., imports, formats). follow loose convention attempts strike balance description brevity. optimal balance often hard achieve. aid understanding, provide brief description suffixes used . Suffix descriptions: attain: Analyze functions summarize data relative attainment categories specific bay segments ave, med: Analyze functions summarize data averages medians benthic: Applies benthic monitoring data used Tampa Bay Benthic Index entero: Applies Enterococcus, specific type Fecal Indicator Bacteria, fib functions applicable fib: Applies generally Fecal Indicator Bacteria fim: Applies data Fisheries Independent Monitoring program used Tampa Bay Nekton Index form: intermediate function formatting imported data downstream analysis hmp: Functions work Habitat Master Plan data import: function used import data source external package indic: function analyzes plots individual tidal creek indicator values, opposed integrated creek scores iwr: Functions data apply Impaired Waters Rule (IWR) data maintained Florida Department Environmental Protection used source data tidal creek functions matrix: plotting function creates report card style matrix met: function analyses plots individual metrics integrated indices, e.g., TBBI, TBNI phyto: Applies phytoplankton data Hillsborough County Environmental Protection Commission plotly: plotting function returns interactive plotly object scr: function analyses plots summary scores integrated indices, e.g., TBBI, TBNI seg, site: Functions analyze plot results relative bay segments individual monitoring sites tbbi: Applies Tampa Bay Benthic Index (TBBI) tbni: Applies Tampa Bay Nekton Index (TBNI) tdlcrk: Applies tidal creeks transect: Applies seagrass transect data wq: Applies water quality function reference page can also viewed complete list functions organized category, description , links help files. following example demonstrates use subset functions water quality data read file Hillsborough County Environmental Protection Commission long-term monitoring dataset (available https://www.tampabay.wateratlas.usf.edu/), analyze monthly annual averages major bay segments Tampa Bay, plot annual time series one bay segments.  Functions tbeptools also support creation content interactive, online dashboards can facilitate informed decisions without requiring intimate understanding R programming language methods analysis. dashboards include assessments water quality, seagrasses, nekton communities, tidal creeks.","code":"# load the package library(tbeptools)  # read current data wqdat <- read_importwq(xlsx = \"wqdata.xlsx\", download_latest = TRUE) wqdat ## # A tibble: 26,611 x 22 ##   bay_segment epchc_station SampleTime             yr    mo ##   <chr>               <dbl> <dttm>              <dbl> <dbl> ## 1 HB                      6 2021-06-08 10:59:00  2021     6 ## 2 HB                      7 2021-06-08 11:13:00  2021     6 ## 3 HB                      8 2021-06-08 14:15:00  2021     6 ## 4 MTB                     9 2021-06-08 13:14:00  2021     6 ## 5 MTB                    11 2021-06-08 11:30:00  2021     6 ## # ... with 26,606 more rows, and 17 more variables: ## #   Latitude <dbl>, Longitude <dbl>, Total_Depth_m <dbl>, ## #   Sample_Depth_m <dbl>, tn <dbl>, tn_q <chr>, sd_m <dbl>, ## #   sd_raw_m <dbl>, sd_q <chr>, chla <dbl>, chla_q <chr>, ## #   Sal_Top_ppth <dbl>, Sal_Mid_ppth <dbl>, ## #   Sal_Bottom_ppth <dbl>, Temp_Water_Top_degC <dbl>, ## #   Temp_Water_Mid_degC <dbl>, ... # analyze monthly and annual means by bay segment avedat <- anlz_avedat(wqdat) avedat ## $ann ## # A tibble: 584 x 4 ##      yr bay_segment var         val ##   <dbl> <chr>       <chr>     <dbl> ## 1  1974 HB          mean_chla 22.4 ## 2  1974 LTB         mean_chla  4.24 ## 3  1974 MTB         mean_chla  9.66 ## 4  1974 OTB         mean_chla 10.2 ## 5  1975 HB          mean_chla 27.9 ## # ... with 579 more rows ## ## $mos ## # A tibble: 4,484 x 5 ##   bay_segment    yr    mo var         val ##   <chr>       <dbl> <dbl> <chr>     <dbl> ## 1 HB           1974     1 mean_chla 36.2 ## 2 LTB          1974     1 mean_chla  1.75 ## 3 MTB          1974     1 mean_chla 11.5 ## 4 OTB          1974     1 mean_chla  4.4 ## 5 HB           1974     2 mean_chla 42.4 ## # ... with 4,479 more rows # show annual time series of chlorophyll for Hillsborough bay segment show_thrplot(wqdat, bay_segment = \"HB\", yrrng = c(1975, 2020))"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"issues-and-suggestions","dir":"","previous_headings":"","what":"Issues and suggestions","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please report issues suggestions issues link repository. guide posting issues can found .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"contributing","dir":"","previous_headings":"","what":"Contributing","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please view contributing guidelines changes pull requests.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay intertidal and supratidal land use and cover — acres","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"Tampa Bay intertidal supratidal land use cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"acres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"if (FALSE) { # \\dontrun{ load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/acres.RData\"))  save(acres, file = 'data/acres.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories — anlz_attain","title":"Get attainment categories — anlz_attain","text":"Get attainment categories year bay segment using chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories — anlz_attain","text":"","code":"anlz_attain(avedat, magdurout = FALSE, trgs = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories — anlz_attain","text":"avedat result returned anlz_avedat magdurout logical indicating separate magnitude duration estimates returned trgs optional data.frame annual bay segment water quality targets, defaults targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories — anlz_attain","text":"data.frame year bay segment showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories — anlz_attain","text":"","code":"avedat <- anlz_avedat(epcdata) anlz_attain(avedat) #> # A tibble: 200 × 4 #>    bay_segment    yr chl_la outcome #>    <chr>       <dbl> <chr>  <chr>   #>  1 HB           1974 3_0    yellow  #>  2 HB           1975 3_2    red     #>  3 HB           1976 3_2    red     #>  4 HB           1977 3_2    red     #>  5 HB           1978 3_3    red     #>  6 HB           1979 3_3    red     #>  7 HB           1980 3_3    red     #>  8 HB           1981 3_3    red     #>  9 HB           1982 3_3    red     #> 10 HB           1983 3_0    yellow  #> # ℹ 190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Get site attainments — anlz_attainsite","title":"Get site attainments — anlz_attainsite","text":"Get site attainment categories chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get site attainments — anlz_attainsite","text":"","code":"anlz_attainsite(   avedatsite,   thr = c(\"chla\", \"la\"),   trgs = NULL,   yrrng = NULL,   thrs = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get site attainments — anlz_attainsite","text":"avedatsite result returned anlz_avedatsite thr chr string indicating water quality value appropriate threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng optional numeric value year return, defaults thrs logical indicating attainment category relative targets (default) thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get site attainments — anlz_attainsite","text":"data.frame year site showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get site attainments — anlz_attainsite","text":"function simplication attainment categories returned anlz_attain.  Sites compared targets/thresholds apply separately chlorophyll light attenuation.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get site attainments — anlz_attainsite","text":"","code":"avedatsite <- anlz_avedatsite(epcdata) anlz_attainsite(avedatsite) #> # A tibble: 2,250 × 9 #>       yr bay_segment epchc_station var     val target smallex thresh met   #>    <dbl> <chr>               <dbl> <chr> <dbl>  <dbl>   <dbl>  <dbl> <chr> #>  1  1974 HB                      6 chla   25.6   13.2    14.1     15 no    #>  2  1974 HB                      7 chla   21.6   13.2    14.1     15 no    #>  3  1974 HB                      8 chla   22.6   13.2    14.1     15 no    #>  4  1974 HB                     44 chla   23.4   13.2    14.1     15 no    #>  5  1974 HB                     52 chla   23.5   13.2    14.1     15 no    #>  6  1974 HB                     55 chla   20.2   13.2    14.1     15 no    #>  7  1974 HB                     70 chla   33.1   13.2    14.1     15 no    #>  8  1974 HB                     71 chla   25.8   13.2    14.1     15 no    #>  9  1974 HB                     73 chla   17.6   13.2    14.1     15 no    #> 10  1974 HB                     80 chla   10.5   13.2    14.1     15 yes   #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means — anlz_avedat","title":"Estimate annual means — anlz_avedat","text":"Estimate annual means chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means — anlz_avedat","text":"","code":"anlz_avedat(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means — anlz_avedat","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means — anlz_avedat","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means — anlz_avedat","text":"","code":"# view average estimates anlz_avedat(epcdata) #> $ann #> # A tibble: 608 × 4 #>       yr bay_segment var         val #>    <dbl> <chr>       <chr>     <dbl> #>  1  1974 HB          mean_chla 22.4  #>  2  1974 LTB         mean_chla  4.24 #>  3  1974 MTB         mean_chla  9.66 #>  4  1974 OTB         mean_chla 10.2  #>  5  1975 HB          mean_chla 27.9  #>  6  1975 LTB         mean_chla  4.93 #>  7  1975 MTB         mean_chla 11.4  #>  8  1975 OTB         mean_chla 13.2  #>  9  1976 HB          mean_chla 29.5  #> 10  1976 LTB         mean_chla  5.08 #> # ℹ 598 more rows #>  #> $mos #> # A tibble: 4,724 × 5 #>    bay_segment    yr    mo var         val #>    <chr>       <dbl> <dbl> <chr>     <dbl> #>  1 HB           1974     1 mean_chla 36.2  #>  2 LTB          1974     1 mean_chla  1.75 #>  3 MTB          1974     1 mean_chla 11.5  #>  4 OTB          1974     1 mean_chla  4.4  #>  5 HB           1974     2 mean_chla 42.4  #>  6 LTB          1974     2 mean_chla  5.5  #>  7 MTB          1974     2 mean_chla  9.35 #>  8 OTB          1974     2 mean_chla  4.07 #>  9 HB           1974     3 mean_chla 14.9  #> 10 LTB          1974     3 mean_chla  5.88 #> # ℹ 4,714 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means by site — anlz_avedatsite","title":"Estimate annual means by site — anlz_avedatsite","text":"Estimate annual means site chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"anlz_avedatsite(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means by site — anlz_avedatsite","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means by site — anlz_avedatsite","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"# view average estimates anlz_avedatsite(epcdata) #> $ann #> # A tibble: 6,838 × 5 #>       yr bay_segment epchc_station var         val #>    <dbl> <chr>               <dbl> <chr>     <dbl> #>  1  1974 HB                      6 mean_chla  25.6 #>  2  1974 HB                      7 mean_chla  21.6 #>  3  1974 HB                      8 mean_chla  22.6 #>  4  1974 HB                     44 mean_chla  23.4 #>  5  1974 HB                     52 mean_chla  23.5 #>  6  1974 HB                     55 mean_chla  20.2 #>  7  1974 HB                     70 mean_chla  33.1 #>  8  1974 HB                     71 mean_chla  25.8 #>  9  1974 HB                     73 mean_chla  17.6 #> 10  1974 HB                     80 mean_chla  10.5 #> # ℹ 6,828 more rows #>  #> $mos #> # A tibble: 48,727 × 6 #>    bay_segment epchc_station    yr    mo var         val #>    <chr>               <dbl> <dbl> <dbl> <chr>     <dbl> #>  1 HB                      6  1974     1 mean_chla    53 #>  2 HB                      7  1974     1 mean_chla    19 #>  3 HB                      8  1974     1 mean_chla    46 #>  4 HB                     44  1974     1 mean_chla    24 #>  5 HB                     52  1974     1 mean_chla    28 #>  6 HB                     55  1974     1 mean_chla    33 #>  7 HB                     70  1974     1 mean_chla    58 #>  8 HB                     71  1974     1 mean_chla    73 #>  9 HB                     73  1974     1 mean_chla    17 #> 10 HB                     80  1974     1 mean_chla    11 #> # ℹ 48,717 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Enterococcus data — anlz_enteromap","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"Assign threshold categories Enterococcus data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"","code":"anlz_enteromap(   fibdata,   yrsel = NULL,   mosel = NULL,   areasel = NULL,   wetdry = FALSE,   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   assf = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"fibdata data frame Enterococcus sample data returned enterodata anlz_fibwetdry yrsel optional numeric filter data year mosel optional numeric filter data month areasel optional character string filter output stations long_name column enterodata, see details wetdry logical; TRUE, incorporate wet/dry differences (result call anlz_fibwetdry, case temporal_window wet_threshold required). FALSE (default), differentiate wet dry samples. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required wetdry TRUE. number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required wetdry TRUE. inches accumulated defined temporal window, sample defined 'wet' time period assf logical indicating data processed simple features object additional columns show_enteromap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"data.frame similar fibdata assf = FALSE additional columns describing station categories optionally filtered arguments passed function. sf object assf = TRUE additional columns show_enteromap.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"function based anlz_fibmap, specific Enterococcus data downloaded via read_importentero. creates categories mapping using show_enteromap. Optionally, samples defined 'wet' via anlz_fibwetdry, can represented via symbols map.  Categories based relevant thresholds assigned observation.  categories specific Enterococcus marine waters (class 2 3M). station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. areasel argument can indicate valid entries long_name column enterodata.  example, use \"Old Tampa Bay\" stations subwatershed Old Tampa Bay, rows  enterodata filtered based selection.  stations returned argument set NULL (default). valid options areasel include \"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay\", \"Manatee River\".  One options can used.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_enteromap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Enterococcus data — anlz_enteromap","text":"","code":"anlz_enteromap(enterodata, yrsel = 2020, mosel = 9) #> # A tibble: 39 × 12 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    490 130 … #EE7… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    725 130 … #EE7… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     9     28.0     -82.7    703 130 … #EE7… Ente… #>  6 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7     10 < 35  #2DC… Ente… #>  7 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7   1990 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7    171 130 … #EE7… Ente… #>  9 21FLTPA_WQ… Old Tamp…  2020     9     27.9     -82.6    908 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     9     27.9     -82.4      1 < 35  #2DC… Ente… #> # ℹ 29 more rows #> # ℹ 2 more variables: indnm <chr>, conc <dbl>  # differentiate wet/dry samples in that time frame anlz_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 39 × 13 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  2 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    380 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    490 130 … #EE7… Ente… #>  4 21FLHILL_W… Old Tamp…  2020     9     28.0     -82.6    725 130 … #EE7… Ente… #>  5 21FLPDEM_W… Old Tamp…  2020     9     28.0     -82.7    703 130 … #EE7… Ente… #>  6 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7     10 < 35  #2DC… Ente… #>  7 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7   1990 > 999 #CC3… Ente… #>  8 21FLPDEM_W… Old Tamp…  2020     9     27.9     -82.7    171 130 … #EE7… Ente… #>  9 21FLTPA_WQ… Old Tamp…  2020     9     27.9     -82.6    908 130 … #EE7… Ente… #> 10 21FLHILL_W… Hillsbor…  2020     9     27.9     -82.4      1 < 35  #2DC… Ente… #> # ℹ 29 more rows #> # ℹ 3 more variables: indnm <chr>, conc <dbl>, wet_sample <lgl>  # as sf object anlz_enteromap(enterodata, assf = TRUE) #> Simple feature collection with 5596 features and 14 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.74598 ymin: 27.49433 xmax: -82.38168 ymax: 28.02571 #> Geodetic CRS:  WGS 84 #> # A tibble: 5,596 × 15 #>    station     long_name    yr    mo Latitude Longitude entero cat   col   ind   #>    <chr>       <chr>     <dbl> <dbl>    <dbl>     <dbl>  <dbl> <fct> <chr> <chr> #>  1 21FLHILL_W… Old Tamp…  2001     1     28.0     -82.6     80 35 -… #E9C… Ente… #>  2 21FLHILL_W… Old Tamp…  2001     2     28.0     -82.6    360 130 … #EE7… Ente… #>  3 21FLHILL_W… Old Tamp…  2001     3     28.0     -82.6   3900 > 999 #CC3… Ente… #>  4 21FLHILL_W… Old Tamp…  2001     4     28.0     -82.6     20 < 35  #2DC… Ente… #>  5 21FLHILL_W… Old Tamp…  2001     7     28.0     -82.6   1300 > 999 #CC3… Ente… #>  6 21FLHILL_W… Old Tamp…  2001     8     28.0     -82.6    260 130 … #EE7… Ente… #>  7 21FLHILL_W… Old Tamp…  2001     9     28.0     -82.6    420 130 … #EE7… Ente… #>  8 21FLHILL_W… Old Tamp…  2001    10     28.0     -82.6    520 130 … #EE7… Ente… #>  9 21FLHILL_W… Old Tamp…  2001    11     28.0     -82.6     60 35 -… #E9C… Ente… #> 10 21FLHILL_W… Old Tamp…  2001    12     28.0     -82.6    340 130 … #EE7… Ente… #> # ℹ 5,586 more rows #> # ℹ 5 more variables: grp <fct>, conc <dbl>, wet_sample <fct>, #> #   geometry <POINT [°]>, lab <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"Assign threshold categories Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"anlz_fibmap(fibdata, yrsel = NULL, mosel = NULL, areasel = NULL, assf = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"fibdata input FIB data.frame returned read_importfib read_importwqp, see details yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details assf logical indicating data processed simple features object additional columns show_fibmap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"data.frame similar fibdata mancofibdata assf = FALSE additional columns describing station categories optionally filtered arguments passed function.  sf object assf = TRUE additional columns show_fibmap.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"function used create FIB categories mapping using show_fibmap.  Categories based relevant thresholds assigned observation.  categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively.  station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. Data Manatee County (21FLMANA_WQX) returned read_importwqp can used function.  Data organizations returned function tested. areasel argument can indicate valid entries area column fibdata (read_importfib) mancofibdata (read_importwqp).  example, use either \"Alafia River\" \"Hillsborough River\" corresponding river basins, rows  fibdata filtered based selection.  stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\".  Hillsborough River basin includes values area column fibdata \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\".  areas may present based selection. valid options areasel fibdata include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". One options can used. Valid entries areasel mancofibdata include 'Big Slough', 'Bowlees Creek', 'Braden River', 'Bud Slough',  'Cedar Creek', 'Clay Gully', 'Cooper Creek', 'Curiosity Creek', 'Frog Creek', 'Gamble Creek', 'Gap Creek', 'Gates Creek', 'Gilley Creek', 'Hickory Hammock Creek', 'Lake Manatee', 'Little Manatee River', 'Lower Manatee River', 'Lower Tampa Bay', 'Manatee River Estuary', 'Mcmullen Creek', 'Mill Creek', 'Mud Lake Slough', 'Myakka River', 'Nonsense Creek', 'Palma Sola Bay', 'Piney Point Creek', 'Rattlesnake Slough', 'Sugarhouse Creek', 'Upper Manatee River', 'Ward Lake', 'Williams Creek'. One options can used.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"# assign categories to all anlz_fibmap(fibdata) #> # A tibble: 77,526 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 77,516 more rows #> # ℹ 1 more variable: col <chr>  # filter by year, month, and area anlz_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') #> # A tibble: 24 × 12 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Alafia…      74 3M     2020     7     27.9     -82.4    NA    168 Ente… 130 … #>  2 Alafia…     111 3F     2020     7     27.9     -82.2    50   7000 E. c… < 126 #>  3 Alafia…     114 3F     2020     7     27.9     -82.3   447   1560 E. c… 410 … #>  4 Alafia…     115 3F     2020     7     27.9     -82.1    80    260 E. c… < 126 #>  5 Alafia…     116 3F     2020     7     27.9     -82.1    30    367 E. c… < 126 #>  6 Alafia…     139 3F     2020     7     27.7     -82.1    47    100 E. c… < 126 #>  7 Alafia…     151 3F     2020     7     27.9     -82.2    90     25 E. c… < 126 #>  8 Alafia…     153 3M     2020     7     27.9     -82.3    NA   4000 Ente… > 999 #>  9 Alafia…     154 3F     2020     7     27.9     -82.1   433   1367 E. c… 410 … #> 10 Alafia…     155 3F     2020     7     27.9     -82.2   170    233 E. c… 126 … #> # ℹ 14 more rows #> # ℹ 1 more variable: col <chr>  # as sf object anlz_fibmap(fibdata, assf = TRUE) #> Simple feature collection with 28287 features and 16 fields #> Geometry type: POINT #> Dimension:     XY #> Bounding box:  xmin: -82.7832 ymin: 27.53248 xmax: -82.05604 ymax: 28.16544 #> Geodetic CRS:  WGS 84 #> # A tibble: 28,287 × 17 #>    area    station class    yr    mo Latitude Longitude ecoli entero ind   cat   #>    <chr>     <dbl> <chr> <dbl> <dbl>    <dbl>     <dbl> <dbl>  <dbl> <chr> <fct> #>  1 Hillsb…       2 3M     2024     6     27.9     -82.5    NA      3 Ente… < 35  #>  2 Hillsb…       6 3M     2024     6     27.9     -82.5    NA      8 Ente… < 35  #>  3 Hillsb…       7 3M     2024     6     27.9     -82.5    NA      2 Ente… < 35  #>  4 Hillsb…       8 3M     2024     6     27.9     -82.4    NA      4 Ente… < 35  #>  5 Middle…       9 2      2024     6     27.8     -82.4    NA      2 Ente… < 35  #>  6 Middle…      11 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  7 Middle…      13 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  8 Middle…      14 2      2024     6     27.8     -82.5    NA      2 Ente… < 35  #>  9 Middle…      16 2      2024     6     27.7     -82.5    NA      4 Ente… < 35  #> 10 Middle…      19 2      2024     6     27.7     -82.6    NA      2 Ente… < 35  #> # ℹ 28,277 more rows #> # ℹ 6 more variables: col <chr>, geometry <POINT [°]>, grp <fct>, conc <dbl>, #> #   cls <chr>, lab <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"Analyze Fecal Indicator Bacteria categories time station bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(   fibdata,   yrrng = NULL,   stas = NULL,   bay_segment = NULL,   indic,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"fibdata input data frame returned read_importfib, read_importentero, read_importwqp, see details yrrng numeric vector indicating min, max years include, defaults range years data, see details stas optional vector stations include, see details bay_segment optional vector bay segment names include, supercedes stas provided, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"tibble object FIB summaries year station including columns estimated geometric mean fecal coliform Enterococcus concentrations (gmean), proportion samples exceeding 400 CFU / 100 mL (fecal coliform) 130 CFU / 100 mL (Enterococcus) (exced), count samples (cnt), category indicating letter outcome based proportion exceedences (cat).  Results can summarized bay segment bay_segment NULL input data read_importentero.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"function used create output plotting matrix stoplight graphic FIB categories station.  output can also summarized bay segment bay_segment NULL input data read_importentero. latter case, stas argument ignored stations within subsegment watershed used evaluate FIB categories. station (bay segment) year combination categorized based likelihood fecal indicator bacteria concentrations exceeding threshold given year.  fecal coliform, default threshold 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata).  Enterococcus, default threshold 130 CFU / 100 mL.  proportions categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed).  default, results year based right-centered window uses previous two years current year calculate probabilities using monthly samples (lagyr = 3). See show_fibmatrix additional details. yrrng can specified several ways.  yrrng = NULL, year range data selected changes chosen.  User-defined values minimum maximum years can also used, minimum maximum can specified, e.g., yrrng = c(2000, 2010) yrrng = c(2000, NA).  latter case, maximum year defined data. default stations fecal coliform data used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins bay_segment NULL input data read_importfib.  include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137).  stations can plotted using stas argument. Input read_importwqp Manatee County (21FLMANA_WQX) FIB data can also used.  function tested organizations.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze Fecal Indicator Bacteria categories over time by station or bay segment — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata, indic = 'fcolif') #> # A tibble: 459 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1974 143     NA      NA        NA   NA    #>  2  1974 108    247.     28.1     -82.2 NA    #>  3  1974 107    269.     28.0     -82.3 NA    #>  4  1974 135     NA      NA        NA   NA    #>  5  1974 118    136.     28.1     -82.3 NA    #>  6  1974 148     NA      NA        NA   NA    #>  7  1974 105    258.     28.0     -82.4 NA    #>  8  1974 152     NA      NA        NA   NA    #>  9  1974 137     NA      NA        NA   NA    #> 10  1975 143     NA      NA        NA   NA    #> # ℹ 449 more rows  # use different indicator anlz_fibmatrix(fibdata, indic = 'entero') #> # A tibble: 216 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  2001 143     NA      NA        NA   NA    #>  2  2001 108     NA      NA        NA   NA    #>  3  2001 107     NA      NA        NA   NA    #>  4  2001 135     NA      NA        NA   NA    #>  5  2001 118     NA      NA        NA   NA    #>  6  2001 148     NA      NA        NA   NA    #>  7  2001 105    165.     28.0     -82.4 NA    #>  8  2001 152    207.     28.0     -82.5 NA    #>  9  2001 137    103.     28.0     -82.5 NA    #> 10  2002 143    320.     28.1     -82.1 NA    #> # ℹ 206 more rows  # use different dataset anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06 #> # A tibble: 1,224 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 A     #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,214 more rows  # same entero data; lower threshold - changes 'cat' scores anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1, threshold = 30) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06 #> # A tibble: 1,224 × 6 #>       yr grp                        gmean Latitude Longitude cat   #>    <dbl> <fct>                      <dbl>    <dbl>     <dbl> <chr> #>  1  2000 21FLCOSP_WQX-32-03          NA       NA        NA   NA    #>  2  2000 21FLCOSP_WQX-44-02          NA       NA        NA   NA    #>  3  2000 21FLCOSP_WQX-48-03          NA       NA        NA   NA    #>  4  2000 21FLCOSP_WQX-CENTRAL CANAL  NA       NA        NA   NA    #>  5  2000 21FLCOSP_WQX-COSP580        NA       NA        NA   NA    #>  6  2000 21FLCOSP_WQX-NORTH CANAL    NA       NA        NA   NA    #>  7  2000 21FLCOSP_WQX-SC-01          NA       NA        NA   NA    #>  8  2000 21FLCOSP_WQX-SOUTH CANAL    NA       NA        NA   NA    #>  9  2000 21FLDOH_WQX-MANATEE152      10.7     27.5     -82.7 A     #> 10  2000 21FLHILL_WQX-101            NA       NA        NA   NA    #> # ℹ 1,214 more rows  # subset to only wet samples anlz_fibmatrix(enterodata, indic = 'entero', lagyr = 1, subset_wetdry = \"wet\",                temporal_window = 2, wet_threshold = 0.5) #> # A tibble: 1,150 × 6 #>       yr grp                         gmean Latitude Longitude cat   #>    <dbl> <fct>                       <dbl>    <dbl>     <dbl> <chr> #>  1  2001 21FLCOSP_WQX-32-03           NA       NA        NA   NA    #>  2  2001 21FLCOSP_WQX-44-02           NA       NA        NA   NA    #>  3  2001 21FLCOSP_WQX-48-03           NA       NA        NA   NA    #>  4  2001 21FLCOSP_WQX-CENTRAL CANAL   NA       NA        NA   NA    #>  5  2001 21FLCOSP_WQX-COSP580         NA       NA        NA   NA    #>  6  2001 21FLCOSP_WQX-NORTH CANAL     NA       NA        NA   NA    #>  7  2001 21FLCOSP_WQX-SC-01           NA       NA        NA   NA    #>  8  2001 21FLCOSP_WQX-SOUTH CANAL     NA       NA        NA   NA    #>  9  2001 21FLDOH_WQX-MANATEE152       31.6     27.5     -82.7 A     #> 10  2001 21FLHILL_WQX-101           2252.      28.0     -82.6 C     #> # ℹ 1,140 more rows  # Manatee County data anlz_fibmatrix(mancofibdata, indic = 'fcolif', lagyr = 1) #> # A tibble: 1,350 × 6 #>       yr grp   gmean Latitude Longitude cat   #>    <dbl> <fct> <dbl>    <dbl>     <dbl> <chr> #>  1  1995 396    NA       NA        NA   NA    #>  2  1995 BC1    NA       NA        NA   NA    #>  3  1995 BC2    NA       NA        NA   NA    #>  4  1995 BC41   NA       NA        NA   NA    #>  5  1995 BL01   NA       NA        NA   NA    #>  6  1995 BL201  NA       NA        NA   NA    #>  7  1995 BR1    14.8     27.4     -82.5 A     #>  8  1995 BR2    41.1     27.4     -82.5 A     #>  9  1995 BR3    62.4     27.4     -82.5 A     #> 10  1995 BU01A  NA       NA        NA   NA    #> # ℹ 1,340 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"Identify Fecal Indicator Bacteria samples coming 'wet' 'dry' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"","code":"anlz_fibwetdry(fibdata, precipdata, temporal_window = 2, wet_threshold = 0.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"fibdata input data frame precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select stations. temporal_window numeric, number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric, inches accumulated defined temporal window, sample defined 'wet' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"data frame; original fibdata data frame three additional columns. rain_sampleDay total rain (inches) day sampling, rain_total total rain (inches) period time defined temporal_window, wet_sample logical, indicating whether rainfall station's catchment exceeded amount time period specified args.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"function allows user specify threshold declaring sample taken important amount rain important amount days, declaring 'wet'. interest samples taken significant precipitation (definitions vary, user can specify desired thresholds) likely exceed relevant bacterial thresholds. Identifying samples 'wet' allows calculation indices wet dry subsets samples.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibwetdry.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify Fecal Indicator Bacteria samples as coming from a 'wet' or 'dry' time period — anlz_fibwetdry","text":"","code":"entero_wetdry <- anlz_fibwetdry(enterodata, catchprecip) head(entero_wetdry) #> # A tibble: 6 × 19 #>   date          yr    mo time  time_zone long_name    bay_segment station entero #>   <date>     <dbl> <dbl> <chr> <chr>     <chr>        <chr>       <chr>    <dbl> #> 1 2001-01-16  2001     1 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     80 #> 2 2001-02-20  2001     2 \"\"    \"\"        Old Tampa B… OTB         21FLHI…    360 #> 3 2001-03-20  2001     3 \"\"    \"\"        Old Tampa B… OTB         21FLHI…   3900 #> 4 2001-04-17  2001     4 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     20 #> 5 2001-05-15  2001     5 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     NA #> 6 2001-06-19  2001     6 \"\"    \"\"        Old Tampa B… OTB         21FLHI…     NA #> # ℹ 10 more variables: entero_censored <lgl>, MDL <int>, entero_units <chr>, #> #   qualifier <lgl>, LabComments <lgl>, Latitude <dbl>, Longitude <dbl>, #> #   rain_sampleDay <dbl>, rain_total <dbl>, wet_sample <lgl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"Evaluate Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"anlz_hmpreport(acres, subtacres, hmptrgs)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"summarized data.frame appropriate creating report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"relevant output columns targeteval goaleval indicate numeric values -1 (target met, trending ), 0 (target met, trending ), 0.5 (target met, trending ), 1 (target met, trending ). Columns output follows: year Year assessment metric Habitat type assessed Acres Coverage estimate year lacres Coverage estimate previous set available data lyr Year previous set available data category Strata habitat type Target 2030 target habitat type Habitat Master Plan Goal 2050 goal habitat type Habitat Master Plan acresdiff Difference acres current year previous set available data yeardiff Difference years current year previous set available data changerate Acreage change per year current year relative previous set available data targetrate Annual rate required achieve 2030 target goalrate Annual rate required achieve 2050 goal targetprop Proportion target met current year goalprop Proportion goal met current year targeteval number indicating target status current year report card goaleval number indicating goal status current year report card numbers targeteval goaleval one four values -1, 0, 0.5, 1. numbers define status assessment year: -1 target goal met, trending 0 target goal met, trending 0.5 target goal met, trending 1 target goal met, trending ","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"# view summarized data for report card anlz_hmpreport(acres, subtacres, hmptrgs) #> # A tibble: 150 × 17 #>     year metric      Acres lacres   lyr category Target  Goal acresdiff yeardiff #>    <dbl> <chr>       <dbl>  <dbl> <dbl> <fct>     <dbl> <dbl>     <dbl>    <dbl> #>  1  1990 Seagrasses 25218. 23279.  1988 Subtidal  40000 40000     1939.        2 #>  2  1990 Tidal Fla… 20433. 21686.  1988 Subtidal  16220 16220    -1253.        2 #>  3  1992 Seagrasses 25746. 25218.  1990 Subtidal  40000 40000      528.        2 #>  4  1992 Tidal Fla… 20594. 20433.  1990 Subtidal  16220 16220      161.        2 #>  5  1994 Seagrasses 26524. 25746.  1992 Subtidal  40000 40000      778.        2 #>  6  1994 Tidal Fla… 20244. 20594.  1992 Subtidal  16220 16220     -349.        2 #>  7  1996 Seagrasses 26924. 26524.  1994 Subtidal  40000 40000      400.        2 #>  8  1996 Tidal Fla… 20443. 20244.  1994 Subtidal  16220 16220      199.        2 #>  9  1999 Seagrasses 24840. 26924.  1996 Subtidal  40000 40000    -2083.        3 #> 10  1999 Tidal Fla… 27085. 20443.  1996 Subtidal  16220 16220     6642.        3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate <dbl>, targetrate <dbl>, goalrate <dbl>, #> #   targetprop <dbl>, goalprop <dbl>, targeteval <dbl>, goaleval <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"Estimate hydrological estimates adjustment factors bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"anlz_hydroload(yrs, noaa_key = NULL, trace = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"yrs numeric vector indicating years return noaa_key user-supplied NOAA key, see details trace logical indicating function progress printed consol","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"data frame hydrological load estimates bay segments requested years","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"function uses rainfall streamflow data NOAA USGS requires API key.  See \"Authentication\" section help file ncdc defunct rnoaa package.  key can added R environment file called later use, see examples. estimates used annual compliance assessment reports produced Tampa Bay Nitrogen Management Consortium. Load estimates adjustment factors based regression models https://drive.google.com/file/d/11NT0NQ2WbPO6pVZaD7P7Z6qjcwO1jxHw/view?usp=drivesdk","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"if (FALSE) { # \\dontrun{ # this function requires an API key # save it to the R environment file (only once) # save the key, do only once cat(\"NOAA_KEY=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX\\n\",    file=file.path(normalizePath(\"~/\"), \".Renviron\"),    append=TRUE)  # retrieve the key after saving, may need to restart R noaa_key <- Sys.getenv('NOAA_key')  # get estimates for 2021 anlz_hydroload(2021, noaa_key)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"Format raw IWR data — anlz_iwrraw","title":"Format raw IWR data — anlz_iwrraw","text":"Format raw IWR data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format raw IWR data — anlz_iwrraw","text":"iwrraw FDEP impaired waters rule data base data.frame tidalcreeks sf object population tidal creeks yr numeric reference year evaluate, scores based ten years data using yr last year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format raw IWR data — anlz_iwrraw","text":"data.frame formatted data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format raw IWR data — anlz_iwrraw","text":"function subsets raw IWR data ten years starting value yr subsets creek population tidalcreeks. Select water quality parameters masterCode filtered names combined continuity.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023) #>        wbid class   JEI year       date masterCode        result rCode #> 1      2052    3M  CC01 2014 2014-03-03      CHLAC  0.5877866649  <NA> #> 2      2052    3M  CC01 2014 2014-03-03      COLOR  0.9162907319     U #> 3      2052    3M  CC01 2014 2014-03-03      DOSAT  4.1835756960     + #> 4      2052    3M  CC01 2014 2014-03-03       NO23 -5.5214609179     U #> 5      2052    3M  CC01 2014 2014-03-03      SALIN  3.5292973843  <NA> #> 6      2052    3M  CC01 2014 2014-03-03        TKN -0.6733445533  <NA> #> 7      2052    3M  CC01 2014 2014-03-03         TN -0.6694306539     + #> 8      2052    3M  CC01 2014 2014-03-03         TP -2.7968814148  <NA> #> 9      2052    3M  CC01 2014 2014-03-03       TURB  1.2527629685  <NA> #> 10     2052    3M  CC01 2014 2014-04-07      CHLAC  0.2623642645     I #> 11     2052    3M  CC01 2014 2014-04-07      COLOR  0.9162907319     U #> 12     2052    3M  CC01 2014 2014-04-07         DO  1.3862943611  <NA> #> 13     2052    3M  CC01 2014 2014-04-07      DOSAT  4.0656020934     + #> 14     2052    3M  CC01 2014 2014-04-07       NO23 -5.2983173665     I #> 15     2052    3M  CC01 2014 2014-04-07      SALIN  3.5582011305  <NA> #> 16     2052    3M  CC01 2014 2014-04-07        TKN -0.6733445533  <NA> #> 17     2052    3M  CC01 2014 2014-04-07         TN -0.6655320135     + #> 18     2052    3M  CC01 2014 2014-04-07         TP -2.6882475738  <NA> #> 19     2052    3M  CC01 2014 2014-04-07       TURB  0.7884573604  <NA> #> 20     2052    3M  CC01 2014 2014-05-05      CHLAC  0.8754687374  <NA> #> 21     2052    3M  CC01 2014 2014-05-05      COLOR  3.4011973817  <NA> #> 22     2052    3M  CC01 2014 2014-05-05         DO  1.5040773968  <NA> #> 23     2052    3M  CC01 2014 2014-05-05      DOSAT  4.1399550735     + #> 24     2052    3M  CC01 2014 2014-05-05       NO23 -4.7105307016     I #> 25     2052    3M  CC01 2014 2014-05-05      SALIN  3.3032169733  <NA> #> 26     2052    3M  CC01 2014 2014-05-05        TKN -0.3856624808  <NA> #> 27     2052    3M  CC01 2014 2014-05-05         TN -0.3797973614     + #> 28     2052    3M  CC01 2014 2014-05-05         TP -2.2072749132  <NA> #> 29     2052    3M  CC01 2014 2014-05-05       TURB  1.2237754316     A #> 30     2052    3M  CC01 2014 2014-06-02      CHLAC  0.8754687374  <NA> #> 31     2052    3M  CC01 2014 2014-06-02      COLOR  2.7080502011  <NA> #> 32     2052    3M  CC01 2014 2014-06-02         DO  0.9555114450  <NA> #> 33     2052    3M  CC01 2014 2014-06-02      DOSAT  3.6635616461     + #> 34     2052    3M  CC01 2014 2014-06-02       NO23 -4.9618451299     I #> 35     2052    3M  CC01 2014 2014-06-02      SALIN  3.4719664526  <NA> #> 36     2052    3M  CC01 2014 2014-06-02        TKN -0.6348782724  <NA> #> 37     2052    3M  CC01 2014 2014-06-02         TN -0.6273594400     + #> 38     2052    3M  CC01 2014 2014-06-02         TP -2.6592600369  <NA> #> 39     2052    3M  CC01 2014 2014-06-02       TURB  0.7419373447  <NA> #> 40     2052    3M  CC01 2014 2014-07-07      CHLAC  1.0986122887  <NA> #> 41     2052    3M  CC01 2014 2014-07-07      COLOR  2.2512917986  <NA> #> 42     2052    3M  CC01 2014 2014-07-07         DO  1.4350845253  <NA> #> 43     2052    3M  CC01 2014 2014-07-07       NO23 -5.5214609179     U #> 44     2052    3M  CC01 2014 2014-07-07        TKN -0.5621189182  <NA> #> 45     2052    3M  CC01 2014 2014-07-07         TN -0.5586162876     + #> 46     2052    3M  CC01 2014 2014-07-07         TP -2.9565115604  <NA> #> 47     2052    3M  CC01 2014 2014-07-07       TURB  1.0986122887  <NA> #> 48     2052    3M  CC01 2014 2014-08-04      CHLAC  1.0296194172  <NA> #> 49     2052    3M  CC01 2014 2014-08-04      COLOR  2.3025850930  <NA> #> 50     2052    3M  CC01 2014 2014-08-04         DO  1.0647107370  <NA> #> 51     2052    3M  CC01 2014 2014-08-04      DOSAT  3.8543938926     + #> 52     2052    3M  CC01 2014 2014-08-04       NO23 -5.5214609179     U #> 53     2052    3M  CC01 2014 2014-08-04      SALIN  3.5292973843  <NA> #> 54     2052    3M  CC01 2014 2014-08-04         TN -0.4748151862     + #> 55     2052    3M  CC01 2014 2014-08-04       TURB  0.5877866649  <NA> #> 56     2052    3M  CC01 2014 2014-09-08      CHLAC  1.4350845253  <NA> #> 57     2052    3M  CC01 2014 2014-09-08      COLOR  2.8332133441  <NA> #> 58     2052    3M  CC01 2014 2014-09-08         DO  0.8329091229  <NA> #> 59     2052    3M  CC01 2014 2014-09-08      DOSAT  3.5779478934     + #> 60     2052    3M  CC01 2014 2014-09-08       NO23 -4.7105307016     I #> 61     2052    3M  CC01 2014 2014-09-08      SALIN  3.4965075615  <NA> #> 62     2052    3M  CC01 2014 2014-09-08        TKN -0.3424903089  <NA> #> 63     2052    3M  CC01 2014 2014-09-08         TN -0.3368723166     + #> 64     2052    3M  CC01 2014 2014-09-08         TP -2.7030626596  <NA> #> 65     2052    3M  CC01 2014 2014-09-08       TURB  0.4700036292  <NA> #> 66     2052    3M  CC01 2014 2014-10-06      CHLAC  1.1314021115  <NA> #> 67     2052    3M  CC01 2014 2014-10-06      COLOR  5.2470240722  <NA> #> 68     2052    3M  CC01 2014 2014-10-06      DOSAT  4.1141471895     + #> 69     2052    3M  CC01 2014 2014-10-06       NO23 -3.8167128256  <NA> #> 70     2052    3M  CC01 2014 2014-10-06      SALIN  2.0918640617  <NA> #> 71     2052    3M  CC01 2014 2014-10-06        TKN  0.0953101798  <NA> #> 72     2052    3M  CC01 2014 2014-10-06         TN  0.1151128071     + #> 73     2052    3M  CC01 2014 2014-10-06         TP -2.3025850930  <NA> #> 74     2052    3M  CC01 2014 2014-10-06       TURB  0.3364722366  <NA> #> 75     2052    3M  CC01 2014 2014-11-03      CHLAC  0.7884573604     A #> 76     2052    3M  CC01 2014 2014-11-03      COLOR  3.5263605246     A #> 77     2052    3M  CC01 2014 2014-11-03      DOSAT  4.8698394841     + #> 78     2052    3M  CC01 2014 2014-11-03       NO23 -4.4228486292  <NA> #> 79     2052    3M  CC01 2014 2014-11-03      SALIN  3.2425923515  <NA> #> 80     2052    3M  CC01 2014 2014-11-03        TKN -0.5276327421  <NA> #> 81     2052    3M  CC01 2014 2014-11-03         TN -0.5074978337     + #> 82     2052    3M  CC01 2014 2014-11-03         TP -2.7806208939  <NA> #> 83     2052    3M  CC01 2014 2014-11-03       TURB  0.1823215568  <NA> #> 84     2052    3M  CC01 2014 2014-12-01      CHLAC  0.5877866649  <NA> #> 85     2052    3M  CC01 2014 2014-12-01      COLOR  2.7725887222     A #> 86     2052    3M  CC01 2014 2014-12-01      DOSAT  4.4272389775     + #> 87     2052    3M  CC01 2014 2014-12-01       NO23 -4.3428059215  <NA> #> 88     2052    3M  CC01 2014 2014-12-01      SALIN  3.3178157727  <NA> #> 89     2052    3M  CC01 2014 2014-12-01        TKN -0.6539264674  <NA> #> 90     2052    3M  CC01 2014 2014-12-01         TN -0.6292338548     + #> 91     2052    3M  CC01 2014 2014-12-01         TP -2.9187712324  <NA> #> 92     2052    3M  CC01 2014 2014-12-01       TURB  0.4700036292  <NA> #> 93     2052    3M  CC01 2015 2015-01-05      CHLAC  0.9932517730  <NA> #> 94     2052    3M  CC01 2015 2015-01-05      COLOR  1.8405496334  <NA> #> 95     2052    3M  CC01 2015 2015-01-05         DO  1.5260563035  <NA> #> 96     2052    3M  CC01 2015 2015-01-05      DOSAT  4.1835756960     + #> 97     2052    3M  CC01 2015 2015-01-05       NO23 -4.9618451299     I #> 98     2052    3M  CC01 2015 2015-01-05      SALIN  3.5438536821  <NA> #> 99     2052    3M  CC01 2015 2015-01-05        TKN -0.8675005677  <NA> #> 100    2052    3M  CC01 2015 2015-01-05         TN -0.8580218238     + #> 101    2052    3M  CC01 2015 2015-01-05         TP -2.6310891600  <NA> #> 102    2052    3M  CC01 2015 2015-01-05       TURB  0.7419373447  <NA> #> 103    2052    3M  CC01 2015 2015-02-02      CHLAC  0.4700036292     I #> 104    2052    3M  CC01 2015 2015-02-02      COLOR  0.9162907319     U #> 105    2052    3M  CC01 2015 2015-02-02         DO  1.7578579176  <NA> #> 106    2052    3M  CC01 2015 2015-02-02      DOSAT  4.3333614627     + #> 107    2052    3M  CC01 2015 2015-02-02       NO23 -5.2983173665     I #> 108    2052    3M  CC01 2015 2015-02-02      SALIN  3.5055573970  <NA> #> 109    2052    3M  CC01 2015 2015-02-02        TKN -1.4696759701     I #> 110    2052    3M  CC01 2015 2015-02-02         TN -1.8078888512     + #> 111    2052    3M  CC01 2015 2015-02-02         TP -3.0365542681  <NA> #> 112    2052    3M  CC01 2015 2015-02-02       TURB  0.6418538862  <NA> #> 113    2052    3M  CC01 2015 2015-04-06      CHLAC  0.8329091229  <NA> #> 114    2052    3M  CC01 2015 2015-04-06      COLOR  2.1162555148  <NA> #> 115    2052    3M  CC01 2015 2015-04-06         DO  1.2237754316  <NA> #> 116    2052    3M  CC01 2015 2015-04-06      DOSAT  3.9180050771     + #> 117    2052    3M  CC01 2015 2015-04-06       NO23 -5.5214609179     U #> 118    2052    3M  CC01 2015 2015-04-06      SALIN  3.5582011305  <NA> #> 119    2052    3M  CC01 2015 2015-04-06        TKN -0.6733445533  <NA> #> 120    2052    3M  CC01 2015 2015-04-06         TN -0.6694306539     + #> 121    2052    3M  CC01 2015 2015-04-06         TP -2.8134107168  <NA> #> 122    2052    3M  CC01 2015 2015-04-06       TURB  0.6931471806  <NA> #> 123    2052    3M  CC01 2015 2015-05-04      CHLAC  0.7884573604  <NA> #> 124    2052    3M  CC01 2015 2015-05-04      COLOR  2.1041341543  <NA> #> 125    2052    3M  CC01 2015 2015-05-04         DO  1.4586150227  <NA> #> 126    2052    3M  CC01 2015 2015-05-04      DOSAT  4.1157798429     + #> 127    2052    3M  CC01 2015 2015-05-04       NO23 -5.5214609179     U #> 128    2052    3M  CC01 2015 2015-05-04      SALIN  3.5292973843  <NA> #> 129    2052    3M  CC01 2015 2015-05-04        TKN -1.0216512475     I #> 130    2052    3M  CC01 2015 2015-05-04         TN -1.8201589437     + #> 131    2052    3M  CC01 2015 2015-05-04         TP -3.0159349809  <NA> #> 132    2052    3M  CC01 2015 2015-05-04       TURB  0.8754687374  <NA> #> 133    2052    3M  CC01 2015 2015-08-03      CHLAC  1.4586150227  <NA> #> 134    2052    3M  CC01 2015 2015-08-03      COLOR  5.3936275464  <NA> #> 135    2052    3M  CC01 2015 2015-08-03         DO  1.0647107370  <NA> #> 136    2052    3M  CC01 2015 2015-08-03      DOSAT  3.6506582413     + #> 137    2052    3M  CC01 2015 2015-08-03       NO23 -4.4228486292  <NA> #> 138    2052    3M  CC01 2015 2015-08-03      SALIN  2.2617630985  <NA> #> 139    2052    3M  CC01 2015 2015-08-03        TKN  1.2809338455  <NA> #> 140    2052    3M  CC01 2015 2015-08-03         TN  1.2842616356     + #> 141    2052    3M  CC01 2015 2015-08-03         TP -2.2072749132  <NA> #> 142    2052    3M  CC01 2015 2015-08-03       TURB  0.4700036292  <NA> #> 143    2052    3M  CC01 2015 2015-09-08      CHLAC  1.6292405397  <NA> #> 144    2052    3M  CC01 2015 2015-09-08      COLOR  4.4773368145  <NA> #> 145    2052    3M  CC01 2015 2015-09-08         DO  1.3350010667  <NA> #> 146    2052    3M  CC01 2015 2015-09-08      DOSAT  3.9454577815     + #> 147    2052    3M  CC01 2015 2015-09-08       NO23 -4.2686979494  <NA> #> 148    2052    3M  CC01 2015 2015-09-08      SALIN  1.7227665977  <NA> #> 149    2052    3M  CC01 2015 2015-09-08        TKN -0.1984509387  <NA> #> 150    2052    3M  CC01 2015 2015-09-08         TN -0.1815218766     + #> 151    2052    3M  CC01 2015 2015-09-08         TP -2.4418471603  <NA> #> 152    2052    3M  CC01 2015 2015-09-08       TURB  0.6931471806  <NA> #> 153    2052    3M  CC01 2015 2015-10-05      CHLAC  0.5877866649  <NA> #> 154    2052    3M  CC01 2015 2015-10-05      COLOR  5.0751738152  <NA> #> 155    2052    3M  CC01 2015 2015-10-05         DO  1.2237754316  <NA> #> 156    2052    3M  CC01 2015 2015-10-05      DOSAT  3.7977338590     + #> 157    2052    3M  CC01 2015 2015-10-05       NO23 -3.4112477175  <NA> #> 158    2052    3M  CC01 2015 2015-10-05      SALIN  2.1282317058  <NA> #> 159    2052    3M  CC01 2015 2015-10-05        TKN  0.0953101798  <NA> #> 160    2052    3M  CC01 2015 2015-10-05         TN  0.1248689820     + #> 161    2052    3M  CC01 2015 2015-10-05         TP -1.9661128564  <NA> #> 162    2052    3M  CC01 2015 2015-10-05       TURB  0.1823215568  <NA> #> 163    2052    3M  CC01 2015 2015-12-07      CHLAC  1.0296194172  <NA> #> 164    2052    3M  CC01 2015 2015-12-07      COLOR  2.7725887222  <NA> #> 165    2052    3M  CC01 2015 2015-12-07         DO  1.5686159179  <NA> #> 166    2052    3M  CC01 2015 2015-12-07      DOSAT  4.1743872699     + #> 167    2052    3M  CC01 2015 2015-12-07       NO23 -3.9633162998  <NA> #> 168    2052    3M  CC01 2015 2015-12-07      SALIN  3.3499040873  <NA> #> 169    2052    3M  CC01 2015 2015-12-07        TKN -0.6348782724  <NA> #> 170    2052    3M  CC01 2015 2015-12-07         TN -0.5996568375     + #> 171    2052    3M  CC01 2015 2015-12-07         TP -2.5010360317  <NA> #> 172    2052    3M  CC01 2015 2015-12-07       TURB  0.4700036292  <NA> #> 173    2052    3M  CC01 2016 2016-02-01      CHLAC  0.5306282511  <NA> #> 174    2052    3M  CC01 2016 2016-02-01      COLOR  4.6051701860  <NA> #> 175    2052    3M  CC01 2016 2016-02-01         DO  1.6863989536  <NA> #> 176    2052    3M  CC01 2016 2016-02-01      DOSAT  4.1383614476     + #> 177    2052    3M  CC01 2016 2016-02-01       NO23 -3.5755507688  <NA> #> 178    2052    3M  CC01 2016 2016-02-01      SALIN  2.6100697927  <NA> #> 179    2052    3M  CC01 2016 2016-02-01        TKN -0.2357223335  <NA> #> 180    2052    3M  CC01 2016 2016-02-01         TN -0.2008929424     + #> 181    2052    3M  CC01 2016 2016-02-01         TP -2.3751557858  <NA> #> 182    2052    3M  CC01 2016 2016-02-01       TURB  0.7419373447  <NA> #> 183    2052    3M  CC01 2016 2016-03-07      CHLAC  0.7419373447  <NA> #> 184    2052    3M  CC01 2016 2016-03-07      COLOR  3.5263605246  <NA> #> 185    2052    3M  CC01 2016 2016-03-07         DO  1.6486586256  <NA> #> 186    2052    3M  CC01 2016 2016-03-07      DOSAT  4.1588830834     + #> 187    2052    3M  CC01 2016 2016-03-07       NO23 -4.9618451299     I #> 188    2052    3M  CC01 2016 2016-03-07      SALIN  2.9957322736  <NA> #> 189    2052    3M  CC01 2016 2016-03-07        TKN -0.5108256238  <NA> #> 190    2052    3M  CC01 2016 2016-03-07         TN -0.5041810810     + #> 191    2052    3M  CC01 2016 2016-03-07         TP -2.4418471603  <NA> #> 192    2052    3M  CC01 2016 2016-03-07       TURB  1.1939224685  <NA> #> 193    2052    3M  CC01 2016 2016-04-04      CHLAC  0.9162907319  <NA> #> 194    2052    3M  CC01 2016 2016-04-04      COLOR  2.5649493575  <NA> #> 195    2052    3M  CC01 2016 2016-04-04         DO  1.4109869737  <NA> #> 196    2052    3M  CC01 2016 2016-04-04      DOSAT  4.0289167569     + #> 197    2052    3M  CC01 2016 2016-04-04       NO23 -4.3428059215  <NA> #> 198    2052    3M  CC01 2016 2016-04-04      SALIN  3.3068867022  <NA> #> 199    2052    3M  CC01 2016 2016-04-04        TKN -0.5108256238  <NA> #> 200    2052    3M  CC01 2016 2016-04-04         TN -0.4893903430     + #> 201    2052    3M  CC01 2016 2016-04-04         TP -2.4534079827  <NA> #> 202    2052    3M  CC01 2016 2016-04-04       TURB  0.9162907319  <NA> #> 203    2052    3M  CC01 2016 2016-05-02      CHLAC  0.4054651081     I #> 204    2052    3M  CC01 2016 2016-05-02      COLOR  2.0149030205  <NA> #> 205    2052    3M  CC01 2016 2016-05-02         DO  1.1939224685  <NA> #> 206    2052    3M  CC01 2016 2016-05-02      DOSAT  3.9298629236     + #> 207    2052    3M  CC01 2016 2016-05-02       NO23 -5.5214609179     U #> 208    2052    3M  CC01 2016 2016-05-02      SALIN  3.5085559000  <NA> #> 209    2052    3M  CC01 2016 2016-05-02        TKN -1.0498221245     I #> 210    2052    3M  CC01 2016 2016-05-02         TN -1.8201589437     + #> 211    2052    3M  CC01 2016 2016-05-02         TP -2.4534079827  <NA> #> 212    2052    3M  CC01 2016 2016-05-02       TURB  0.3364722366  <NA> #> 213    2052    3M  CC01 2016 2016-07-05      CHLAC  0.7419373447  <NA> #> 214    2052    3M  CC01 2016 2016-07-05      COLOR  3.1780538303  <NA> #> 215    2052    3M  CC01 2016 2016-07-05         DO  0.9555114450  <NA> #> 216    2052    3M  CC01 2016 2016-07-05      DOSAT  3.7013019741     + #> 217    2052    3M  CC01 2016 2016-07-05       NO23 -5.5214609179     I #> 218    2052    3M  CC01 2016 2016-07-05      SALIN  3.4078419244  <NA> #> 219    2052    3M  CC01 2016 2016-07-05        TKN -0.5621189182  <NA> #> 220    2052    3M  CC01 2016 2016-07-05         TN -0.5551258827     + #> 221    2052    3M  CC01 2016 2016-07-05         TP -2.3434070875  <NA> #> 222    2052    3M  CC01 2016 2016-07-05       TURB  0.5306282511  <NA> #> 223    2052    3M  CC01 2016 2016-08-01      CHLAC  0.9555114450  <NA> #> 224    2052    3M  CC01 2016 2016-08-01      COLOR  3.1354942159  <NA> #> 225    2052    3M  CC01 2016 2016-08-01         DO  1.2527629685  <NA> #> 226    2052    3M  CC01 2016 2016-08-01      DOSAT  3.9926809084     + #> 227    2052    3M  CC01 2016 2016-08-01       NO23 -4.4228486292  <NA> #> 228    2052    3M  CC01 2016 2016-08-01      SALIN  3.3178157727  <NA> #> 229    2052    3M  CC01 2016 2016-08-01        TKN -0.5276327421  <NA> #> 230    2052    3M  CC01 2016 2016-08-01         TN -0.5074978337     + #> 231    2052    3M  CC01 2016 2016-08-01         TP -2.5510464523  <NA> #> 232    2052    3M  CC01 2016 2016-08-01       TURB  0.2623642645  <NA> #> 233    2052    3M  CC01 2016 2016-10-03      CHLAC  1.5686159179  <NA> #> 234    2052    3M  CC01 2016 2016-10-03      COLOR  3.7135720667  <NA> #> 235    2052    3M  CC01 2016 2016-10-03         DO  1.3083328197  <NA> #> 236    2052    3M  CC01 2016 2016-10-03      DOSAT  3.9982007017     + #> 237    2052    3M  CC01 2016 2016-10-03       NO23 -4.9618451299     I #> 238    2052    3M  CC01 2016 2016-10-03      SALIN  3.1223649245  <NA> #> 239    2052    3M  CC01 2016 2016-10-03        TKN -0.2613647641  <NA> #> 240    2052    3M  CC01 2016 2016-10-03         TN -0.2561834054     + #> 241    2052    3M  CC01 2016 2016-10-03         TP -2.3025850930  <NA> #> 242    2052    3M  CC01 2016 2016-10-03       TURB  0.9555114450  <NA> #> 243    2052    3M  CC01 2016 2016-11-07      CHLAC  1.0296194172  <NA> #> 244    2052    3M  CC01 2016 2016-11-07      COLOR  1.8082887712  <NA> #> 245    2052    3M  CC01 2016 2016-11-07         DO  1.3862943611  <NA> #> 246    2052    3M  CC01 2016 2016-11-07      DOSAT  4.0289167569     + #> 247    2052    3M  CC01 2016 2016-11-07       NO23 -4.6051701860  <NA> #> 248    2052    3M  CC01 2016 2016-11-07      SALIN  3.4531571206  <NA> #> 249    2052    3M  CC01 2016 2016-11-07        TKN -0.4462871026  <NA> #> 250    2052    3M  CC01 2016 2016-11-07         TN -0.4307829161     + #> 251    2052    3M  CC01 2016 2016-11-07         TP -2.5639498571  <NA> #> 252    2052    3M  CC01 2016 2016-11-07       TURB  0.8754687374  <NA> #> 253    2052    3M  CC01 2016 2016-12-05      CHLAC  0.4700036292     I #> 254    2052    3M  CC01 2016 2016-12-05      COLOR  2.0149030205     U #> 255    2052    3M  CC01 2016 2016-12-05         DO  1.5892352051  <NA> #> 256    2052    3M  CC01 2016 2016-12-05      DOSAT  4.2456340098     + #> 257    2052    3M  CC01 2016 2016-12-05       NO23 -4.9618451299     I #> 258    2052    3M  CC01 2016 2016-12-05      SALIN  3.5467396870  <NA> #> 259    2052    3M  CC01 2016 2016-12-05        TKN -0.7765287895  <NA> #> 260    2052    3M  CC01 2016 2016-12-05         TN -0.7678707268     + #> 261    2052    3M  CC01 2016 2016-12-05         TP -2.8824035882  <NA> #> 262    2052    3M  CC01 2016 2016-12-05       TURB  0.7884573604  <NA> #> 263    2052    3M  CC01 2017 2017-02-06      CHLAC  0.7419373447  <NA> #> 264    2052    3M  CC01 2017 2017-02-06      COLOR  1.3609765531     I #> 265    2052    3M  CC01 2017 2017-02-06         DO  1.3862943611  <NA> #> 266    2052    3M  CC01 2017 2017-02-06      DOSAT  3.9889840466     + #> 267    2052    3M  CC01 2017 2017-02-06       NO23 -4.1997050779  <NA> #> 268    2052    3M  CC01 2017 2017-02-06      SALIN  3.5204608025  <NA> #> 269    2052    3M  CC01 2017 2017-02-06        TKN -0.6539264674  <NA> #> 270    2052    3M  CC01 2017 2017-02-06         TN -0.6254885321     + #> 271    2052    3M  CC01 2017 2017-02-06         TP -2.8473122684  <NA> #> 272    2052    3M  CC01 2017 2017-02-06       TURB  0.7419373447  <NA> #> 273    2052    3M  CC01 2017 2017-04-03      CHLAC  0.3364722366     I #> 274    2052    3M  CC01 2017 2017-04-03      COLOR  0.9162907319     U #> 275    2052    3M  CC01 2017 2017-04-03         DO  1.2237754316  <NA> #> 276    2052    3M  CC01 2017 2017-04-03      DOSAT  3.9357395320     + #> 277    2052    3M  CC01 2017 2017-04-03       NO23 -5.5214609179     U #> 278    2052    3M  CC01 2017 2017-04-03      SALIN  3.5610460826  <NA> #> 279    2052    3M  CC01 2017 2017-04-03        TKN -0.5978370008  <NA> #> 280    2052    3M  CC01 2017 2017-04-03         TN -0.5942072327     + #> 281    2052    3M  CC01 2017 2017-04-03         TP -2.7181005370  <NA> #> 282    2052    3M  CC01 2017 2017-04-03       TURB  0.7419373447  <NA> #> 283    2052    3M  CC01 2017 2017-06-05      SALIN  3.4242626546  <NA> #> 284    2052    3M  CC01 2017 2017-06-05         DO  0.8241754430  <NA> #> 285    2052    3M  CC01 2017 2017-06-05      DOSAT  3.4210000090     + #> 286    2052    3M  CC01 2017 2017-06-05      SALIN  2.2533948488  <NA> #> 287    2052    3M  CC01 2017 2017-06-05      CHLAC  0.4054651081     I #> 288    2052    3M  CC01 2017 2017-06-05      COLOR  1.9878743482  <NA> #> 289    2052    3M  CC01 2017 2017-06-05         DO  1.2527629685  <NA> #> 290    2052    3M  CC01 2017 2017-06-05      DOSAT  4.0360089852     + #> 291    2052    3M  CC01 2017 2017-06-05       NO23 -4.9618451299     I #> 292    2052    3M  CC01 2017 2017-06-05      SALIN  3.6506582413  <NA> #> 293    2052    3M  CC01 2017 2017-06-05        TKN -0.6539264674  <NA> #> 294    2052    3M  CC01 2017 2017-06-05         TN -0.6462635947     + #> 295    2052    3M  CC01 2017 2017-06-05         TP -2.8473122684  <NA> #> 296    2052    3M  CC01 2017 2017-06-05       TURB  0.2623642645  <NA> #> 297    2052    3M  CC01 2017 2017-06-05         DO  1.4655675420  <NA> #> 298    2052    3M  CC01 2017 2017-06-05      DOSAT  4.1866198383     + #> 299    2052    3M  CC01 2017 2017-06-05      SALIN  3.5115454388  <NA> #> 300    2052    3M  CC01 2017 2017-07-10      CHLAC  0.9162907319  <NA> #> 301    2052    3M  CC01 2017 2017-07-10      COLOR  3.7376696183     A #> 302    2052    3M  CC01 2017 2017-07-10         DO  1.9021075264  <NA> #> 303    2052    3M  CC01 2017 2017-07-10      DOSAT  4.6482296754     + #> 304    2052    3M  CC01 2017 2017-07-10       NO23 -5.5214609179     I #> 305    2052    3M  CC01 2017 2017-07-10      SALIN  3.3214324132  <NA> #> 306    2052    3M  CC01 2017 2017-07-10        TKN -0.3566749439  <NA> #> 307    2052    3M  CC01 2017 2017-07-10         TN -0.3509769228     + #> 308    2052    3M  CC01 2017 2017-07-10         TP -2.4418471603  <NA> #> 309    2052    3M  CC01 2017 2017-07-10       TURB  0.4700036292  <NA> #> 310    2052    3M  CC01 2017 2017-09-05      CHLAC  2.7725887222  <NA> #> 311    2052    3M  CC01 2017 2017-09-05      COLOR  5.2470240722  <NA> #> 312    2052    3M  CC01 2017 2017-09-05         DO  1.4350845253  <NA> #> 313    2052    3M  CC01 2017 2017-09-05      DOSAT  4.0517849478     + #> 314    2052    3M  CC01 2017 2017-09-05       NO23 -4.1351665567  <NA> #> 315    2052    3M  CC01 2017 2017-09-05      SALIN  2.1282317058  <NA> #> 316    2052    3M  CC01 2017 2017-09-05        TKN  0.1823215568  <NA> #> 317    2052    3M  CC01 2017 2017-09-05         TN  0.1955667835     + #> 318    2052    3M  CC01 2017 2017-09-05         TP -2.1202635362  <NA> #> 319    2052    3M  CC01 2017 2017-09-05       TURB  0.6418538862     A #> 320    2052    3M  CC01 2017 2017-10-02      CHLAC  2.1633230257  <NA> #> 321    2052    3M  CC01 2017 2017-10-02      COLOR  3.8066624898  <NA> #> 322    2052    3M  CC01 2017 2017-10-02       NO23 -4.8283137373     I #> 323    2052    3M  CC01 2017 2017-10-02        TKN -0.5276327421  <NA> #> 324    2052    3M  CC01 2017 2017-10-02         TN -0.5208759596     + #> 325    2052    3M  CC01 2017 2017-10-02         TP -2.3025850930  <NA> #> 326    2052    3M  CC01 2017 2017-10-02       TURB  0.6418538862  <NA> #> 327    2052    3M  CC01 2017 2017-11-06      CHLAC  0.6418538862  <NA> #> 328    2052    3M  CC01 2017 2017-11-06      COLOR  2.5649493575  <NA> #> 329    2052    3M  CC01 2017 2017-11-06         DO  1.6863989536  <NA> #> 330    2052    3M  CC01 2017 2017-11-06      DOSAT  4.3241326563     + #> 331    2052    3M  CC01 2017 2017-11-06       NO23 -4.5098600062  <NA> #> 332    2052    3M  CC01 2017 2017-11-06      SALIN  3.2809112158  <NA> #> 333    2052    3M  CC01 2017 2017-11-06        TKN -0.5108256238  <NA> #> 334    2052    3M  CC01 2017 2017-11-06         TN -0.4926583198     + #> 335    2052    3M  CC01 2017 2017-11-06         TP -2.5770219387  <NA> #> 336    2052    3M  CC01 2017 2017-11-06       TURB  0.4700036292  <NA> #> 337    2052    3M  CC01 2017 2017-12-04      CHLAC  0.4054651081     I #> 338    2052    3M  CC01 2017 2017-12-04      COLOR  2.2512917986  <NA> #> 339    2052    3M  CC01 2017 2017-12-04         DO  1.6486586256  <NA> #> 340    2052    3M  CC01 2017 2017-12-04      DOSAT  4.2835865619     + #> 341    2052    3M  CC01 2017 2017-12-04       NO23 -5.5214609179     I #> 342    2052    3M  CC01 2017 2017-12-04      SALIN  3.4843122884  <NA> #> 343    2052    3M  CC01 2017 2017-12-04        TKN -0.6348782724  <NA> #> 344    2052    3M  CC01 2017 2017-12-04         TN -0.6273594400     + #> 345    2052    3M  CC01 2017 2017-12-04         TP -2.7968814148  <NA> #> 346    2052    3M  CC01 2017 2017-12-04       TURB  0.7419373447  <NA> #> 347    2052    3M  CC01 2018 2018-01-02      CHLAC  0.3364722366     I #> 348    2052    3M  CC01 2018 2018-01-02      COLOR  2.3025850930  <NA> #> 349    2052    3M  CC01 2018 2018-01-02         DO  1.8718021769  <NA> #> 350    2052    3M  CC01 2018 2018-01-02      DOSAT  4.3214801348     + #> 351    2052    3M  CC01 2018 2018-01-02       NO23 -4.6051701860  <NA> #> 352    2052    3M  CC01 2018 2018-01-02      SALIN  3.3214324132  <NA> #> 353    2052    3M  CC01 2018 2018-01-02        TKN -0.7765287895  <NA> #> 354    2052    3M  CC01 2018 2018-01-02         TN -0.7550225843     + #> 355    2052    3M  CC01 2018 2018-01-02         TP -2.6450754019  <NA> #> 356    2052    3M  CC01 2018 2018-01-02       TURB  0.7884573604  <NA> #> 357    2052    3M  CC01 2018 2018-02-05      CHLAC  0.6418538862  <NA> #> 358    2052    3M  CC01 2018 2018-02-05      COLOR  2.1633230257  <NA> #> 359    2052    3M  CC01 2018 2018-02-05         DO  1.9600947840  <NA> #> 360    2052    3M  CC01 2018 2018-02-05      DOSAT  4.5358201079     + #> 361    2052    3M  CC01 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 362    2052    3M  CC01 2018 2018-02-05      SALIN  3.3877743613  <NA> #> 363    2052    3M  CC01 2018 2018-02-05        TKN -0.6348782724  <NA> #> 364    2052    3M  CC01 2018 2018-02-05         TN -0.6051363032     + #> 365    2052    3M  CC01 2018 2018-02-05         TP -2.4304184645  <NA> #> 366    2052    3M  CC01 2018 2018-02-05       TURB  1.8405496334     A #> 367    2052    3M  CC01 2018 2018-03-05      CHLAC  0.3364722366     I #> 368    2052    3M  CC01 2018 2018-03-05      COLOR  1.9459101491  <NA> #> 369    2052    3M  CC01 2018 2018-03-05         DO  2.0412203289  <NA> #> 370    2052    3M  CC01 2018 2018-03-05      DOSAT  4.5890408041     + #> 371    2052    3M  CC01 2018 2018-03-05       NO23 -5.5214609179     U #> 372    2052    3M  CC01 2018 2018-03-05      SALIN  3.4372078192  <NA> #> 373    2052    3M  CC01 2018 2018-03-05        TKN -0.7985076962  <NA> #> 374    2052    3M  CC01 2018 2018-03-05         TN -0.7940730991     + #> 375    2052    3M  CC01 2018 2018-03-05         TP -2.8134107168  <NA> #> 376    2052    3M  CC01 2018 2018-03-05       TURB  0.9932517730  <NA> #> 377    2052    3M  CC01 2018 2018-04-02      CHLAC  0.5306282511     I #> 378    2052    3M  CC01 2018 2018-04-02      COLOR  1.0986122887     I #> 379    2052    3M  CC01 2018 2018-04-02      DOSAT  4.5538768916     + #> 380    2052    3M  CC01 2018 2018-04-02       NO23 -5.5214609179     U #> 381    2052    3M  CC01 2018 2018-04-02      SALIN  3.5025498759  <NA> #> 382    2052    3M  CC01 2018 2018-04-02        TKN -0.7550225843  <NA> #> 383    2052    3M  CC01 2018 2018-04-02         TN -0.7507762934     + #> 384    2052    3M  CC01 2018 2018-04-02         TP -2.8473122684  <NA> #> 385    2052    3M  CC01 2018 2018-04-02       TURB  1.1314021115  <NA> #> 386    2052    3M  CC01 2018 2018-05-07      CHLAC  0.5877866649  <NA> #> 387    2052    3M  CC01 2018 2018-05-07      COLOR  2.1041341543  <NA> #> 388    2052    3M  CC01 2018 2018-05-07         DO  0.8285518176  <NA> #> 389    2052    3M  CC01 2018 2018-05-07      DOSAT  3.5292973843  <NA> #> 390    2052    3M  CC01 2018 2018-05-07       NO23 -5.5214609179     U #> 391    2052    3M  CC01 2018 2018-05-07      SALIN  3.5743099994  <NA> #> 392    2052    3M  CC01 2018 2018-05-07        TKN -0.5621189182  <NA> #> 393    2052    3M  CC01 2018 2018-05-07         TN -0.5586162876     + #> 394    2052    3M  CC01 2018 2018-05-07         TP -2.6310891600  <NA> #> 395    2052    3M  CC01 2018 2018-05-07       TURB  0.7884573604  <NA> #> 396    2052    3M  CC01 2018 2018-07-09      CHLAC  0.9932517730  <NA> #> 397    2052    3M  CC01 2018 2018-07-09      COLOR  4.1743872699  <NA> #> 398    2052    3M  CC01 2018 2018-07-09         DO  1.1216775616  <NA> #> 399    2052    3M  CC01 2018 2018-07-09      DOSAT  3.9140210081  <NA> #> 400    2052    3M  CC01 2018 2018-07-09       NO23 -4.6051701860  <NA> #> 401    2052    3M  CC01 2018 2018-07-09      SALIN  3.4339872045  <NA> #> 402    2052    3M  CC01 2018 2018-07-09        TKN -0.2231435513  <NA> #> 403    2052    3M  CC01 2018 2018-07-09         TN -0.2107210313     + #> 404    2052    3M  CC01 2018 2018-07-09         TP -2.3025850930  <NA> #> 405    2052    3M  CC01 2018 2018-07-09       TURB  0.4054651081  <NA> #> 406    2052    3M  CC01 2018 2018-08-06      CHLAC  1.1939224685  <NA> #> 407    2052    3M  CC01 2018 2018-08-06      COLOR  3.4011973817  <NA> #> 408    2052    3M  CC01 2018 2018-08-06         DO  0.8153648133  <NA> #> 409    2052    3M  CC01 2018 2018-08-06      DOSAT  3.5945687746  <NA> #> 410    2052    3M  CC01 2018 2018-08-06       NO23 -4.8283137373     I #> 411    2052    3M  CC01 2018 2018-08-06      SALIN  3.4534735262  <NA> #> 412    2052    3M  CC01 2018 2018-08-06        TKN -0.2231435513  <NA> #> 413    2052    3M  CC01 2018 2018-08-06         TN -0.2181560098     + #> 414    2052    3M  CC01 2018 2018-08-06         TP -2.5257286443  <NA> #> 415    2052    3M  CC01 2018 2018-08-06       TURB  0.3364722366  <NA> #> 416    2052    3M  CC01 2019 2019-02-04      CHLAC -0.3285040670     I #> 417    2052    3M  CC01 2019 2019-02-04      COLOR  3.4339872045  <NA> #> 418    2052    3M  CC01 2019 2019-02-04         DO  1.6213664833  <NA> #> 419    2052    3M  CC01 2019 2019-02-04      DOSAT  4.1431347264  <NA> #> 420    2052    3M  CC01 2019 2019-02-04       NO23 -3.7297014486  <NA> #> 421    2052    3M  CC01 2019 2019-02-04      SALIN  3.1805507105  <NA> #> 422    2052    3M  CC01 2019 2019-02-04        TKN -0.5978370008  <NA> #> 423    2052    3M  CC01 2019 2019-02-04         TN -0.5551258827     + #> 424    2052    3M  CC01 2019 2019-02-04         TP -2.5902671654  <NA> #> 425    2052    3M  CC01 2019 2019-02-04       TURB  0.5306282511  <NA> #> 426    2052    3M  CC01 2019 2019-03-04      CHLAC  0.4054651081     I #> 427    2052    3M  CC01 2019 2019-03-04      COLOR  2.7080502011  <NA> #> 428    2052    3M  CC01 2019 2019-03-04         DO  1.2781522025  <NA> #> 429    2052    3M  CC01 2019 2019-03-04      DOSAT  3.9531649488  <NA> #> 430    2052    3M  CC01 2019 2019-03-04       NO23 -4.8283137373     I #> 431    2052    3M  CC01 2019 2019-03-04        TKN -0.7985076962  <NA> #> 432    2052    3M  CC01 2019 2019-03-04         TN -0.7896580809     + #> 433    2052    3M  CC01 2019 2019-03-04         TP -2.6172958378  <NA> #> 434    2052    3M  CC01 2019 2019-03-04       TURB  0.4700036292  <NA> #> 435    2052    3M  CC01 2019 2019-04-01      CHLAC  0.9162907319  <NA> #> 436    2052    3M  CC01 2019 2019-04-01      COLOR  2.0014800002  <NA> #> 437    2052    3M  CC01 2019 2019-04-01         DO  1.4883995841  <NA> #> 438    2052    3M  CC01 2019 2019-04-01      DOSAT  4.1620032107  <NA> #> 439    2052    3M  CC01 2019 2019-04-01       NO23 -5.5214609179     I #> 440    2052    3M  CC01 2019 2019-04-01      SALIN  3.4094961845  <NA> #> 441    2052    3M  CC01 2019 2019-04-01        TKN -0.9162907319     I #> 442    2052    3M  CC01 2019 2019-04-01         TN -1.8078888512     + #> 443    2052    3M  CC01 2019 2019-04-01         TP -2.5510464523  <NA> #> 444    2052    3M  CC01 2019 2019-04-01       TURB  0.2623642645  <NA> #> 445    2052    3M  CC01 2019 2019-06-03      CHLAC  0.4700036292     I #> 446    2052    3M  CC01 2019 2019-06-03      COLOR  1.4586150227     I #> 447    2052    3M  CC01 2019 2019-06-03         DO  0.3001045925  <NA> #> 448    2052    3M  CC01 2019 2019-06-03      DOSAT  3.1267605360  <NA> #> 449    2052    3M  CC01 2019 2019-06-03       NO23 -5.5214609179     I #> 450    2052    3M  CC01 2019 2019-06-03      SALIN  3.5871235452  <NA> #> 451    2052    3M  CC01 2019 2019-06-03        TKN -0.7133498879  <NA> #> 452    2052    3M  CC01 2019 2019-06-03         TN -0.7052197618     + #> 453    2052    3M  CC01 2019 2019-06-03         TP -3.1700856607  <NA> #> 454    2052    3M  CC01 2019 2019-06-03       TURB  0.3364722366  <NA> #> 455    2052    3M  CC01 2019 2019-07-01      CHLAC  0.5306282511     I #> 456    2052    3M  CC01 2019 2019-07-01      COLOR  2.2823823857  <NA> #> 457    2052    3M  CC01 2019 2019-07-01         DO  0.9593502213  <NA> #> 458    2052    3M  CC01 2019 2019-07-01      DOSAT  3.7208625000  <NA> #> 459    2052    3M  CC01 2019 2019-07-01       NO23 -5.1159958098     I #> 460    2052    3M  CC01 2019 2019-07-01      SALIN  3.5237099561  <NA> #> 461    2052    3M  CC01 2019 2019-07-01        TKN -0.5978370008  <NA> #> 462    2052    3M  CC01 2019 2019-07-01         TN -0.5905905922     + #> 463    2052    3M  CC01 2019 2019-07-01         TP -2.9957322736  <NA> #> 464    2052    3M  CC01 2019 2019-07-01       TURB  0.4700036292  <NA> #> 465    2052    3M  CC01 2019 2019-10-07      CHLAC  1.8562979904  <NA> #> 466    2052    3M  CC01 2019 2019-10-07      COLOR  1.5260563035     I #> 467    2052    3M  CC01 2019 2019-10-07         DO  1.1755733298  <NA> #> 468    2052    3M  CC01 2019 2019-10-07      DOSAT  3.9120230054  <NA> #> 469    2052    3M  CC01 2019 2019-10-07       NO23 -5.2983173665     I #> 470    2052    3M  CC01 2019 2019-10-07      SALIN  3.5231199856  <NA> #> 471    2052    3M  CC01 2019 2019-10-07        TKN -0.5108256238  <NA> #> 472    2052    3M  CC01 2019 2019-10-07         TN -0.5041810810     + #> 473    2052    3M  CC01 2019 2019-10-07         TP -2.5510464523  <NA> #> 474    2052    3M  CC01 2019 2019-10-07       TURB  0.9555114450  <NA> #> 475    2052    3M  CC01 2019 2019-11-04      CHLAC  1.0986122887  <NA> #> 476    2052    3M  CC01 2019 2019-11-04      COLOR  1.4816045409     I #> 477    2052    3M  CC01 2019 2019-11-04         DO  0.9042181506  <NA> #> 478    2052    3M  CC01 2019 2019-11-04      DOSAT  3.6136169696  <NA> #> 479    2052    3M  CC01 2019 2019-11-04       NO23 -4.5098600062  <NA> #> 480    2052    3M  CC01 2019 2019-11-04      SALIN  3.5010427166  <NA> #> 481    2052    3M  CC01 2019 2019-11-04        TKN -0.5276327421  <NA> #> 482    2052    3M  CC01 2019 2019-11-04         TN -0.5091603444     + #> 483    2052    3M  CC01 2019 2019-11-04         TP -2.6450754019  <NA> #> 484    2052    3M  CC01 2019 2019-11-04       TURB  0.7884573604  <NA> #> 485    2052    3M  CC01 2019 2019-12-02      CHLAC  0.8754687374     I #> 486    2052    3M  CC01 2019 2019-12-02      COLOR  0.9162907319     U #> 487    2052    3M  CC01 2019 2019-12-02       NO23 -5.1159958098     I #> 488    2052    3M  CC01 2019 2019-12-02        TKN -0.7985076962  <NA> #> 489    2052    3M  CC01 2019 2019-12-02         TN -0.7896580809     + #> 490    2052    3M  CC01 2019 2019-12-02         TP -2.9957322736  <NA> #> 491    2052    3M  CC01 2019 2019-12-02       TURB  1.0296194172  <NA> #> 492    2052    3M  CC01 2020 2020-01-06      CHLAC  0.1823215568     I #> 493    2052    3M  CC01 2020 2020-01-06      COLOR  2.3978952728  <NA> #> 494    2052    3M  CC01 2020 2020-01-06         DO  1.8196988379  <NA> #> 495    2052    3M  CC01 2020 2020-01-06      DOSAT  4.3554259529  <NA> #> 496    2052    3M  CC01 2020 2020-01-06       NO23 -3.9120230054  <NA> #> 497    2052    3M  CC01 2020 2020-01-06      SALIN  3.4075107437  <NA> #> 498    2052    3M  CC01 2020 2020-01-06        TKN -0.4942963218  <NA> #> 499    2052    3M  CC01 2020 2020-01-06         TN -0.4620354596     + #> 500    2052    3M  CC01 2020 2020-01-06         TP -2.4889146712  <NA> #> 501    2052    3M  CC01 2020 2020-01-06       TURB  0.5877866649  <NA> #> 502    2052    3M  CC01 2020 2020-02-03      CHLAC  0.4700036292     U #> 503    2052    3M  CC01 2020 2020-02-03      COLOR  1.6677068206     I #> 504    2052    3M  CC01 2020 2020-02-03         DO  1.7647307968  <NA> #> 505    2052    3M  CC01 2020 2020-02-03      DOSAT  4.2959239356  <NA> #> 506    2052    3M  CC01 2020 2020-02-03       NO23 -4.5098600062  <NA> #> 507    2052    3M  CC01 2020 2020-02-03      SALIN  3.4992311219  <NA> #> 508    2052    3M  CC01 2020 2020-02-03        TKN -0.7985076962  <NA> #> 509    2052    3M  CC01 2020 2020-02-03         TN -0.7743572360     + #> 510    2052    3M  CC01 2020 2020-02-03         TP -2.7488721956  <NA> #> 511    2052    3M  CC01 2020 2020-02-03       TURB  0.6931471806  <NA> #> 512    2052    3M  CC01 2020 2020-03-02      CHLAC  0.0953101798     I #> 513    2052    3M  CC01 2020 2020-03-02      COLOR  1.5040773968     I #> 514    2052    3M  CC01 2020 2020-03-02         DO  1.7191887764  <NA> #> 515    2052    3M  CC01 2020 2020-03-02      DOSAT  4.3000027992  <NA> #> 516    2052    3M  CC01 2020 2020-03-02       NO23 -5.5214609179     U #> 517    2052    3M  CC01 2020 2020-03-02      SALIN  3.6730041050  <NA> #> 518    2052    3M  CC01 2020 2020-03-02        TKN -0.9942522733     I #> 519    2052    3M  CC01 2020 2020-03-02         TN -1.8201589437     + #> 520    2052    3M  CC01 2020 2020-03-02         TP -2.8647040111  <NA> #> 521    2052    3M  CC01 2020 2020-03-02       TURB  1.0647107370  <NA> #> 522    2052    3M  CC01 2021 2021-01-04      CHLAC  0.5877866649     I #> 523    2052    3M  CC01 2021 2021-01-04      COLOR  1.6094379124     I #> 524    2052    3M  CC01 2021 2021-01-04       NO23 -4.1997050779  <NA> #> 525    2052    3M  CC01 2021 2021-01-04      SALIN  3.4200191359  <NA> #> 526    2052    3M  CC01 2021 2021-01-04        TKN -0.7339691751  <NA> #> 527    2052    3M  CC01 2021 2021-01-04         TN -0.7031975164     + #> 528    2052    3M  CC01 2021 2021-01-04         TP -2.6882475738  <NA> #> 529    2052    3M  CC01 2021 2021-01-04       TURB  1.0296194172     A #> 530    2052    3M  CC01 2021 2021-04-05      CHLAC  0.4054651081     I #> 531    2052    3M  CC01 2021 2021-04-05      COLOR  1.7227665977     I #> 532    2052    3M  CC01 2021 2021-04-05         DO  2.0605135318  <NA> #> 533    2052    3M  CC01 2021 2021-04-05      DOSAT  4.6784206477  <NA> #> 534    2052    3M  CC01 2021 2021-04-05       NO23 -5.5214609179     U #> 535    2052    3M  CC01 2021 2021-04-05      SALIN  3.5579161896  <NA> #> 536    2052    3M  CC01 2021 2021-04-05        TKN -1.0498221245     I #> 537    2052    3M  CC01 2021 2021-04-05         TN -1.8201589437     + #> 538    2052    3M  CC01 2021 2021-04-05         TP -2.6172958378  <NA> #> 539    2052    3M  CC01 2021 2021-04-05       TURB  0.7419373447  <NA> #> 540    2052    3M  CC01 2021 2021-06-07      CHLAC  1.5040773968  <NA> #> 541    2052    3M  CC01 2021 2021-06-07      COLOR  1.0296194172     I #> 542    2052    3M  CC01 2021 2021-06-07         DO  0.6678293726  <NA> #> 543    2052    3M  CC01 2021 2021-06-07      DOSAT  3.5055573970  <NA> #> 544    2052    3M  CC01 2021 2021-06-07       NO23 -5.5214609179     U #> 545    2052    3M  CC01 2021 2021-06-07      SALIN  3.6301904578  <NA> #> 546    2052    3M  CC01 2021 2021-06-07        TKN -0.6733445533  <NA> #> 547    2052    3M  CC01 2021 2021-06-07         TN -0.6694306539     + #> 548    2052    3M  CC01 2021 2021-06-07         TP 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3M  CC01 2021 2021-09-07         DO  0.3364722366  <NA> #> 563    2052    3M  CC01 2021 2021-09-07      DOSAT  2.9652730661  <NA> #> 564    2052    3M  CC01 2021 2021-09-07       NO23 -4.6051701860  <NA> #> 565    2052    3M  CC01 2021 2021-09-07      SALIN  2.9391619221  <NA> #> 566    2052    3M  CC01 2021 2021-09-07        TKN -0.1392620673  <NA> #> 567    2052    3M  CC01 2021 2021-09-07         TN -0.1278333715     + #> 568    2052    3M  CC01 2021 2021-09-07         TP -2.3227878003  <NA> #> 569    2052    3M  CC01 2021 2021-09-07       TURB  0.4054651081  <NA> #> 570    2052    3M  CC01 2021 2021-10-04      CHLAC  3.3672958300  <NA> #> 571    2052    3M  CC01 2021 2021-10-04      COLOR  3.8286413965  <NA> #> 572    2052    3M  CC01 2021 2021-10-04         DO  0.6626879731  <NA> #> 573    2052    3M  CC01 2021 2021-10-04      DOSAT  3.3638415951  <NA> #> 574    2052    3M  CC01 2021 2021-10-04       NO23 -5.5214609179     U #> 575    2052    3M  CC01 2021 2021-10-04      SALIN  3.3304171996  <NA> #> 576    2052    3M  CC01 2021 2021-10-04        TKN -0.2357223335  <NA> #> 577    2052    3M  CC01 2021 2021-10-04         TN -0.2331938872     + #> 578    2052    3M  CC01 2021 2021-10-04         TP -2.3025850930  <NA> #> 579    2052    3M  CC01 2021 2021-10-04       TURB  0.9932517730  <NA> #> 580    2052    3M  CC01 2021 2021-11-01      CHLAC  1.1314021115  <NA> #> 581    2052    3M  CC01 2021 2021-11-01      COLOR  2.7080502011  <NA> #> 582    2052    3M  CC01 2021 2021-11-01         DO  1.2208299214  <NA> #> 583    2052    3M  CC01 2021 2021-11-01      DOSAT  3.8329797981  <NA> #> 584    2052    3M  CC01 2021 2021-11-01       NO23 -3.6888794541  <NA> #> 585    2052    3M  CC01 2021 2021-11-01      SALIN  3.4604092413  <NA> #> 586    2052    3M  CC01 2021 2021-11-01        TKN -0.4942963218  <NA> #> 587    2052    3M  CC01 2021 2021-11-01         TN -0.4541302801     + #> 588    2052    3M  CC01 2021 2021-11-01         TP -2.3025850930  <NA> #> 589    2052    3M  CC01 2021 2021-11-01       TURB  0.4700036292  <NA> #> 590    2052    3M  CC01 2021 2021-12-06      CHLAC  0.9932517730     I #> 591    2052    3M  CC01 2021 2021-12-06      COLOR  0.9162907319     U #> 592    2052    3M  CC01 2021 2021-12-06         DO  1.6752256530  <NA> #> 593    2052    3M  CC01 2021 2021-12-06      DOSAT  4.3027128280  <NA> #> 594    2052    3M  CC01 2021 2021-12-06       NO23 -4.8283137373     I #> 595    2052    3M  CC01 2021 2021-12-06      SALIN  3.4889029621  <NA> #> 596    2052    3M  CC01 2021 2021-12-06        TKN -0.6931471806  <NA> #> 597    2052    3M  CC01 2021 2021-12-06         TN -0.6851790109     + #> 598    2052    3M  CC01 2021 2021-12-06         TP -2.9374633654  <NA> #> 599    2052    3M  CC01 2021 2021-12-06       TURB  1.0647107370  <NA> #> 600    2052    3M  CC01 2022 2022-01-03      CHLAC  0.7419373447     I #> 601    2052    3M  CC01 2022 2022-01-03      COLOR  0.9162907319     U #> 602    2052    3M  CC01 2022 2022-01-03         DO  1.3137236683  <NA> #> 603    2052    3M  CC01 2022 2022-01-03      DOSAT  3.9815490681  <NA> #> 604    2052    3M  CC01 2022 2022-01-03       NO23 -4.8283137373     I #> 605    2052    3M  CC01 2022 2022-01-03      SALIN  3.5207566167  <NA> #> 606    2052    3M  CC01 2022 2022-01-03        TKN -0.9675840263     I #> 607    2052    3M  CC01 2022 2022-01-03         TN -1.8078888512     + #> 608    2052    3M  CC01 2022 2022-01-03         TP -2.5770219387  <NA> #> 609    2052    3M  CC01 2022 2022-01-03       TURB  1.0296194172     A #> 610    2052    3M  CC01 2022 2022-02-07      CHLAC  0.0953101798     I #> 611    2052    3M  CC01 2022 2022-02-07      COLOR  0.9162907319     U #> 612    2052    3M  CC01 2022 2022-02-07         DO  1.5085119938  <NA> #> 613    2052    3M  CC01 2022 2022-02-07      DOSAT  4.0758410907  <NA> #> 614    2052    3M  CC01 2022 2022-02-07       NO23 -4.8283137373     I #> 615    2052    3M  CC01 2022 2022-02-07      SALIN  3.4840054928  <NA> #> 616    2052    3M  CC01 2022 2022-02-07        TKN -0.9162907319  <NA> #> 617    2052    3M  CC01 2022 2022-02-07         TN -0.9063404010     + #> 618    2052    3M  CC01 2022 2022-02-07         TP -2.6036901858  <NA> #> 619    2052    3M  CC01 2022 2022-02-07       TURB  1.2237754316  <NA> #> 620    2052    3M  CC01 2022 2022-03-07      CHLAC  0.0953101798     I #> 621    2052    3M  CC01 2022 2022-03-07      COLOR  0.9162907319     U #> 622    2052    3M  CC01 2022 2022-03-07         DO  0.8109302162  <NA> #> 623    2052    3M  CC01 2022 2022-03-07      DOSAT  3.4657359028  <NA> #> 624    2052    3M  CC01 2022 2022-03-07       NO23 -5.5214609179     U #> 625    2052    3M  CC01 2022 2022-03-07      SALIN  3.5412491371  <NA> #> 626    2052    3M  CC01 2022 2022-03-07         TN -0.4910229965     + #> 627    2052    3M  CC01 2022 2022-03-07         TP -2.9759296463  <NA> #> 628    2052    3M  CC01 2022 2022-03-07       TURB  0.5877866649  <NA> #> 629    2052    3M  CC01 2022 2022-04-04      CHLAC  0.6418538862     I #> 630    2052    3M  CC01 2022 2022-04-04      COLOR  0.9162907319     U #> 631    2052    3M  CC01 2022 2022-04-04         DO  0.6097655716  <NA> #> 632    2052    3M  CC01 2022 2022-04-04      DOSAT  3.2809112158  <NA> #> 633    2052    3M  CC01 2022 2022-04-04       NO23 -5.5214609179     U #> 634    2052    3M  CC01 2022 2022-04-04      SALIN  3.5672766324  <NA> #> 635    2052    3M  CC01 2022 2022-04-04        TKN -0.8915981193  <NA> #> 636    2052    3M  CC01 2022 2022-04-04         TN -0.8867319296     + #> 637    2052    3M  CC01 2022 2022-04-04         TP -2.6736487744  <NA> #> 638    2052    3M  CC01 2022 2022-04-04       TURB  1.0986122887  <NA> #> 639    2052    3M  CC01 2022 2022-05-02      CHLAC  0.8329091229     I #> 640    2052    3M  CC01 2022 2022-05-02      COLOR  0.9162907319     U #> 641    2052    3M  CC01 2022 2022-05-02         DO  0.7178397932  <NA> #> 642    2052    3M  CC01 2022 2022-05-02      DOSAT  3.4242626546  <NA> #> 643    2052    3M  CC01 2022 2022-05-02       NO23 -5.5214609179     U #> 644    2052    3M  CC01 2022 2022-05-02      SALIN  3.6003214271  <NA> #> 645    2052    3M  CC01 2022 2022-05-02        TKN -0.8209805521  <NA> #> 646    2052    3M  CC01 2022 2022-05-02         TN -0.8164453969     + #> 647    2052    3M  CC01 2022 2022-05-02         TP -2.8473122684  <NA> #> 648    2052    3M  CC01 2022 2022-05-02       TURB  0.8329091229  <NA> #> 649    2052    3M  CC01 2022 2022-06-06      CHLAC  1.0986122887  <NA> #> 650    2052    3M  CC01 2022 2022-06-06      COLOR  2.2300144002  <NA> #> 651    2052    3M  CC01 2022 2022-06-06         DO  0.5538851132  <NA> #> 652    2052    3M  CC01 2022 2022-06-06      DOSAT  3.2695689392  <NA> #> 653    2052    3M  CC01 2022 2022-06-06       NO23 -5.5214609179     U #> 654    2052    3M  CC01 2022 2022-06-06      SALIN  3.5195728344  <NA> #> 655    2052    3M  CC01 2022 2022-06-06        TKN -0.7550225843  <NA> #> 656    2052    3M  CC01 2022 2022-06-06         TN -0.7507762934     + #> 657    2052    3M  CC01 2022 2022-06-06         TP -3.1465551633  <NA> #> 658    2052    3M  CC01 2022 2022-06-06       TURB  0.8754687374  <NA> #> 659    2052    3M  CC01 2022 2022-07-05      CHLAC  1.9021075264  <NA> #> 660    2052    3M  CC01 2022 2022-07-05      COLOR  2.7725887222  <NA> #> 661    2052    3M  CC01 2022 2022-07-05         DO  1.3428648032  <NA> #> 662    2052    3M  CC01 2022 2022-07-05      DOSAT  4.1287459889  <NA> #> 663    2052    3M  CC01 2022 2022-07-05       NO23 -4.8283137373     I #> 664    2052    3M  CC01 2022 2022-07-05      SALIN  3.5313480661  <NA> #> 665    2052    3M  CC01 2022 2022-07-05        TKN -0.4942963218  <NA> #> 666    2052    3M  CC01 2022 2022-07-05         TN -0.4877603508     + #> 667    2052    3M  CC01 2022 2022-07-05         TP -2.5010360317  <NA> #> 668    2052    3M  CC01 2022 2022-07-05       TURB  1.2237754316  <NA> #> 669    2052    3M  CC01 2022 2022-08-01      CHLAC  0.9162907319  <NA> #> 670    2052    3M  CC01 2022 2022-08-01      COLOR  1.9021075264  <NA> #> 671    2052    3M  CC01 2022 2022-08-01         DO -0.0943106795  <NA> #> 672    2052    3M  CC01 2022 2022-08-01      DOSAT  2.6946271808  <NA> #> 673    2052    3M  CC01 2022 2022-08-01       NO23 -4.9618451299     I #> 674    2052    3M  CC01 2022 2022-08-01      SALIN  3.5242995788  <NA> #> 675    2052    3M  CC01 2022 2022-08-01        TKN -0.6348782724  <NA> #> 676    2052    3M  CC01 2022 2022-08-01         TN -0.6273594400     + #> 677    2052    3M  CC01 2022 2022-08-01         TP -2.7181005370  <NA> #> 678    2052    3M  CC01 2022 2022-08-01       TURB  0.2623642645  <NA> #> 679    2052    3M  CC01 2022 2022-09-06      CHLAC  1.2809338455  <NA> #> 680    2052    3M  CC01 2022 2022-09-06      COLOR  1.3609765531     I #> 681    2052    3M  CC01 2022 2022-09-06         DO  0.8109302162  <NA> #> 682    2052    3M  CC01 2022 2022-09-06      DOSAT  3.6027767551  <NA> #> 683    2052    3M  CC01 2022 2022-09-06       NO23 -5.1159958098     I #> 684    2052    3M  CC01 2022 2022-09-06      SALIN  3.5040547671  <NA> #> 685    2052    3M  CC01 2022 2022-09-06        TKN -0.6733445533  <NA> #> 686    2052    3M  CC01 2022 2022-09-06         TN -0.6655320135     + #> 687    2052    3M  CC01 2022 2022-09-06         TP -2.5257286443  <NA> #> 688    2052    3M  CC01 2022 2022-09-06       TURB  0.4054651081  <NA> #> 689    2052    3M  CC01 2022 2022-12-05      CHLAC  1.2809338455  <NA> #> 690    2052    3M  CC01 2022 2022-12-05      COLOR  3.7376696183  <NA> #> 691    2052    3M  CC01 2022 2022-12-05         DO  0.9321640810  <NA> #> 692    2052    3M  CC01 2022 2022-12-05      DOSAT  3.5322256441  <NA> #> 693    2052    3M  CC01 2022 2022-12-05       NO23 -3.5755507688  <NA> #> 694    2052    3M  CC01 2022 2022-12-05      SALIN  3.2778991653  <NA> #> 695    2052    3M  CC01 2022 2022-12-05        TKN -0.3011050928  <NA> #> 696    2052    3M  CC01 2022 2022-12-05         TN -0.2639655458     + #> 697    2052    3M  CC01 2022 2022-12-05         TP -2.0402208285  <NA> #> 698    2052    3M  CC01 2022 2022-12-05       TURB  0.6931471806  <NA> #> 699    2052    3M  CC01 2023 2023-01-03      CHLAC  1.2809338455  <NA> #> 700    2052    3M  CC01 2023 2023-01-03      COLOR  2.5649493575  <NA> #> 701    2052    3M  CC01 2023 2023-01-03         DO  1.2641267271  <NA> #> 702    2052    3M  CC01 2023 2023-01-03      DOSAT  3.8897773965  <NA> #> 703    2052    3M  CC01 2023 2023-01-03       NO23 -5.2983173665     I #> 704    2052    3M  CC01 2023 2023-01-03      SALIN  3.3442742343  <NA> #> 705    2052    3M  CC01 2023 2023-01-03        TKN -0.7339691751  <NA> #> 706    2052    3M  CC01 2023 2023-01-03         TN -0.7256703723     + #> 707    2052    3M  CC01 2023 2023-01-03         TP -2.3025850930  <NA> #> 708    2052    3M  CC01 2023 2023-01-03       TURB  0.5306282511  <NA> #> 709    2052    3M  CC01 2023 2023-02-06      CHLAC  0.2623642645     I #> 710    2052    3M  CC01 2023 2023-02-06      COLOR  0.9162907319     U #> 711    2052    3M  CC01 2023 2023-02-06         DO  1.0577902941  <NA> #> 712    2052    3M  CC01 2023 2023-02-06      DOSAT  3.6788291183  <NA> #> 713    2052    3M  CC01 2023 2023-02-06       NO23 -5.2983173665     I #> 714    2052    3M  CC01 2023 2023-02-06      SALIN  3.5237099561  <NA> #> 715    2052    3M  CC01 2023 2023-02-06        TKN -1.1394342832     I #> 716    2052    3M  CC01 2023 2023-02-06         TN -1.8078888512     + #> 717    2052    3M  CC01 2023 2023-02-06         TP -1.8325814637  <NA> #> 718    2052    3M  CC01 2023 2023-02-06       TURB  0.9162907319  <NA> #> 719    2052    3M  CC01 2023 2023-03-06      CHLAC  0.9555114450  <NA> #> 720    2052    3M  CC01 2023 2023-03-06      COLOR  1.5892352051     I #> 721    2052    3M  CC01 2023 2023-03-06       NO23 -5.5214609179     U #> 722    2052    3M  CC01 2023 2023-03-06      SALIN  3.5458747597  <NA> #> 723    2052    3M  CC01 2023 2023-03-06        TKN -0.7765287895  <NA> #> 724    2052    3M  CC01 2023 2023-03-06         TN -0.7721903879     + #> 725    2052    3M  CC01 2023 2023-03-06         TP -2.4079456087  <NA> #> 726    2052    3M  CC01 2023 2023-03-06       TURB  0.4054651081  <NA> #> 727    2067    3M  CC02 2014 2014-02-03      CHLAC  0.5877866649  <NA> #> 728    2067    3M  CC02 2014 2014-02-03      COLOR  2.3978952728     A #> 729    2067    3M  CC02 2014 2014-02-03         DO  1.5892352051  <NA> #> 730    2067    3M  CC02 2014 2014-02-03      DOSAT  4.1478853292     + #> 731    2067    3M  CC02 2014 2014-02-03       NO23 -3.7297014486  <NA> #> 732    2067    3M  CC02 2014 2014-02-03      SALIN  3.3032169733  <NA> #> 733    2067    3M  CC02 2014 2014-02-03        TKN -0.5108256238  <NA> #> 734    2067    3M  CC02 2014 2014-02-03         TN -0.4716049106     + #> 735    2067    3M  CC02 2014 2014-02-03         TP -2.4079456087  <NA> #> 736    2067    3M  CC02 2014 2014-02-03       TURB  1.0647107370  <NA> #> 737    2067    3M  CC02 2014 2014-03-03      CHLAC  1.4109869737  <NA> #> 738    2067    3M  CC02 2014 2014-03-03      COLOR  1.3862943611     I #> 739    2067    3M  CC02 2014 2014-03-03         DO  1.6486586256  <NA> #> 740    2067    3M  CC02 2014 2014-03-03       NO23 -4.7105307016     I #> 741    2067    3M  CC02 2014 2014-03-03      SALIN  3.5292973843  <NA> #> 742    2067    3M  CC02 2014 2014-03-03        TKN -0.6161861394  <NA> #> 743    2067    3M  CC02 2014 2014-03-03         TN -0.6088060321     + #> 744    2067    3M  CC02 2014 2014-03-03         TP -2.6592600369  <NA> #> 745    2067    3M  CC02 2014 2014-03-03       TURB  1.5040773968  <NA> #> 746    2067    3M  CC02 2014 2014-04-07      CHLAC  0.7884573604  <NA> #> 747    2067    3M  CC02 2014 2014-04-07      COLOR  0.9555114450     I #> 748    2067    3M  CC02 2014 2014-04-07         DO  1.5260563035  <NA> #> 749    2067    3M  CC02 2014 2014-04-07      DOSAT  4.2224445648     + #> 750    2067    3M  CC02 2014 2014-04-07       NO23 -4.8283137373     I #> 751    2067    3M  CC02 2014 2014-04-07      SALIN  3.5695326965  <NA> #> 752    2067    3M  CC02 2014 2014-04-07        TKN -0.6931471806  <NA> #> 753    2067    3M  CC02 2014 2014-04-07         TN -0.6851790109     + #> 754    2067    3M  CC02 2014 2014-04-07         TP -2.6882475738  <NA> #> 755    2067    3M  CC02 2014 2014-04-07       TURB  1.3862943611  <NA> #> 756    2067    3M  CC02 2014 2014-05-05      CHLAC  1.3609765531  <NA> #> 757    2067    3M  CC02 2014 2014-05-05      COLOR  2.0412203289  <NA> #> 758    2067    3M  CC02 2014 2014-05-05      DOSAT  4.0775374439     + #> 759    2067    3M  CC02 2014 2014-05-05       NO23 -5.5214609179     I #> 760    2067    3M  CC02 2014 2014-05-05      SALIN  3.5582011305  <NA> #> 761    2067    3M  CC02 2014 2014-05-05        TKN -0.7985076962  <NA> #> 762    2067    3M  CC02 2014 2014-05-05         TN -0.7896580809     + #> 763    2067    3M  CC02 2014 2014-05-05         TP -2.4418471603  <NA> #> 764    2067    3M  CC02 2014 2014-05-05       TURB  1.1939224685  <NA> #> 765    2067    3M  CC02 2014 2014-08-04      CHLAC  1.0296194172  <NA> #> 766    2067    3M  CC02 2014 2014-08-04      COLOR  2.3978952728  <NA> #> 767    2067    3M  CC02 2014 2014-08-04         DO  1.1631508098  <NA> #> 768    2067    3M  CC02 2014 2014-08-04      DOSAT  3.9531649488     + #> 769    2067    3M  CC02 2014 2014-08-04       NO23 -5.2983173665     I #> 770    2067    3M  CC02 2014 2014-08-04      SALIN  3.6163087613  <NA> #> 771    2067    3M  CC02 2014 2014-08-04        TKN -0.5276327421  <NA> #> 772    2067    3M  CC02 2014 2014-08-04         TN -0.5208759596     + #> 773    2067    3M  CC02 2014 2014-08-04         TP -2.3025850930  <NA> #> 774    2067    3M  CC02 2014 2014-08-04       TURB  1.1631508098  <NA> #> 775    2067    3M  CC02 2014 2014-10-06      CHLAC  1.7404661748  <NA> #> 776    2067    3M  CC02 2014 2014-10-06      COLOR  3.3322045102  <NA> #> 777    2067    3M  CC02 2014 2014-10-06      DOSAT  3.9852734672     + #> 778    2067    3M  CC02 2014 2014-10-06       NO23 -4.3428059215  <NA> #> 779    2067    3M  CC02 2014 2014-10-06      SALIN  3.4499875458  <NA> #> 780    2067    3M  CC02 2014 2014-10-06        TKN -0.5276327421  <NA> #> 781    2067    3M  CC02 2014 2014-10-06         TN -0.5058380823     + #> 782    2067    3M  CC02 2014 2014-10-06         TP -1.9661128564  <NA> #> 783    2067    3M  CC02 2014 2014-10-06       TURB  1.0986122887  <NA> #> 784    2067    3M  CC02 2014 2014-11-03      CHLAC  0.4054651081     I #> 785    2067    3M  CC02 2014 2014-11-03      COLOR  2.5649493575  <NA> #> 786    2067    3M  CC02 2014 2014-11-03      DOSAT  4.0724397268     + #> 787    2067    3M  CC02 2014 2014-11-03       NO23 -4.6051701860  <NA> #> 788    2067    3M  CC02 2014 2014-11-03      SALIN  3.4531571206  <NA> #> 789    2067    3M  CC02 2014 2014-11-03        TKN -0.7133498879  <NA> #> 790    2067    3M  CC02 2014 2014-11-03         TN -0.6931471806     + #> 791    2067    3M  CC02 2014 2014-11-03         TP -2.0402208285  <NA> #> 792    2067    3M  CC02 2014 2014-11-03       TURB  1.0647107370  <NA> #> 793    2067    3M  CC02 2014 2014-12-01      CHLAC  0.2623642645     I #> 794    2067    3M  CC02 2014 2014-12-01      COLOR  1.3083328197     I #> 795    2067    3M  CC02 2014 2014-12-01         DO  1.8245492921  <NA> #> 796    2067    3M  CC02 2014 2014-12-01       NO23 -5.2983173665     I #> 797    2067    3M  CC02 2014 2014-12-01      SALIN  3.4626060098  <NA> #> 798    2067    3M  CC02 2014 2014-12-01        TKN -1.2378743560     I #> 799    2067    3M  CC02 2014 2014-12-01         TN -1.8078888512     + #> 800    2067    3M  CC02 2014 2014-12-01         TP -3.0576076773  <NA> #> 801    2067    3M  CC02 2014 2014-12-01       TURB  1.2809338455  <NA> #> 802    2067    3M  CC02 2015 2015-01-05      CHLAC  0.6418538862  <NA> #> 803    2067    3M  CC02 2015 2015-01-05      COLOR  2.1747517215  <NA> #> 804    2067    3M  CC02 2015 2015-01-05         DO  0.9932517730  <NA> #> 805    2067    3M  CC02 2015 2015-01-05      DOSAT  3.6375861597     + #> 806    2067    3M  CC02 2015 2015-01-05       NO23 -4.3428059215  <NA> #> 807    2067    3M  CC02 2015 2015-01-05      SALIN  3.5438536821  <NA> #> 808    2067    3M  CC02 2015 2015-01-05        TKN -0.7765287895  <NA> #> 809    2067    3M  CC02 2015 2015-01-05         TN -0.7486598905     + #> 810    2067    3M  CC02 2015 2015-01-05         TP -2.3025850930  <NA> #> 811    2067    3M  CC02 2015 2015-01-05       TURB  1.3083328197  <NA> #> 812    2067    3M  CC02 2015 2015-03-02      CHLAC  0.5306282511  <NA> #> 813    2067    3M  CC02 2015 2015-03-02      COLOR  2.4849066498  <NA> #> 814    2067    3M  CC02 2015 2015-03-02         DO  1.1939224685  <NA> #> 815    2067    3M  CC02 2015 2015-03-02       NO23 -3.6888794541  <NA> #> 816    2067    3M  CC02 2015 2015-03-02      SALIN  3.4563166809  <NA> #> 817    2067    3M  CC02 2015 2015-03-02        TKN -0.6161861394  <NA> #> 818    2067    3M  CC02 2015 2015-03-02         TN -0.5709295478     + #> 819    2067    3M  CC02 2015 2015-03-02         TP -2.3538783874  <NA> #> 820    2067    3M  CC02 2015 2015-03-02       TURB  1.1314021115  <NA> #> 821    2067    3M  CC02 2015 2015-04-06      CHLAC  1.3350010667  <NA> #> 822    2067    3M  CC02 2015 2015-04-06      COLOR  2.0541237337  <NA> #> 823    2067    3M  CC02 2015 2015-04-06      DOSAT  3.7184382564     + #> 824    2067    3M  CC02 2015 2015-04-06       NO23 -4.6051701860  <NA> #> 825    2067    3M  CC02 2015 2015-04-06      SALIN  3.5695326965  <NA> #> 826    2067    3M  CC02 2015 2015-04-06        TKN -0.3285040670  <NA> #> 827    2067    3M  CC02 2015 2015-04-06         TN -0.3147107448     + #> 828    2067    3M  CC02 2015 2015-04-06         TP -0.7765287895  <NA> #> 829    2067    3M  CC02 2015 2015-04-06       TURB  1.6292405397  <NA> #> 830    2067    3M  CC02 2015 2015-05-04      CHLAC  0.9162907319  <NA> #> 831    2067    3M  CC02 2015 2015-05-04      COLOR  2.0149030205  <NA> #> 832    2067    3M  CC02 2015 2015-05-04       NO23 -4.6051701860     I #> 833    2067    3M  CC02 2015 2015-05-04      SALIN  3.5835189385  <NA> #> 834    2067    3M  CC02 2015 2015-05-04        TKN -0.8209805521  <NA> #> 835    2067    3M  CC02 2015 2015-05-04         TN -0.8119307165     + #> 836    2067    3M  CC02 2015 2015-05-04         TP -2.6310891600  <NA> #> 837    2067    3M  CC02 2015 2015-05-04       TURB  1.3609765531     A #> 838    2067    3M  CC02 2015 2015-06-01      CHLAC  0.4700036292     I #> 839    2067    3M  CC02 2015 2015-06-01      COLOR  2.1860512767  <NA> #> 840    2067    3M  CC02 2015 2015-06-01         DO  1.2237754316  <NA> #> 841    2067    3M  CC02 2015 2015-06-01       NO23 -4.1997050779  <NA> #> 842    2067    3M  CC02 2015 2015-06-01      SALIN  3.5945687746  <NA> #> 843    2067    3M  CC02 2015 2015-06-01        TKN -0.7133498879  <NA> #> 844    2067    3M  CC02 2015 2015-06-01         TN -0.6831968497     + #> 845    2067    3M  CC02 2015 2015-06-01         TP -2.8134107168  <NA> #> 846    2067    3M  CC02 2015 2015-06-01       TURB  0.9555114450  <NA> #> 847    2067    3M  CC02 2015 2015-09-08      CHLAC  1.1631508098  <NA> #> 848    2067    3M  CC02 2015 2015-09-08      COLOR  3.3672958300     A #> 849    2067    3M  CC02 2015 2015-09-08         DO  1.1631508098  <NA> #> 850    2067    3M  CC02 2015 2015-09-08      DOSAT  3.8877303129     + #> 851    2067    3M  CC02 2015 2015-09-08       NO23 -5.1159958098     I #> 852    2067    3M  CC02 2015 2015-09-08      SALIN  3.4078419244  <NA> #> 853    2067    3M  CC02 2015 2015-09-08        TKN -0.3424903089  <NA> #> 854    2067    3M  CC02 2015 2015-09-08         TN -0.3368723166     + #> 855    2067    3M  CC02 2015 2015-09-08         TP -1.3862943611  <NA> #> 856    2067    3M  CC02 2015 2015-09-08       TURB  1.0296194172  <NA> #> 857    2067    3M  CC02 2016 2016-02-01      CHLAC  0.6931471806  <NA> #> 858    2067    3M  CC02 2016 2016-02-01      COLOR  3.2188758249  <NA> #> 859    2067    3M  CC02 2016 2016-02-01         DO  1.4350845253  <NA> #> 860    2067    3M  CC02 2016 2016-02-01      DOSAT  3.9665111907     + #> 861    2067    3M  CC02 2016 2016-02-01       NO23 -3.7297014486  <NA> #> 862    2067    3M  CC02 2016 2016-02-01      SALIN  3.3286266888  <NA> #> 863    2067    3M  CC02 2016 2016-02-01        TKN -0.4942963218  <NA> #> 864    2067    3M  CC02 2016 2016-02-01         TN -0.4557063245     + #> 865    2067    3M  CC02 2016 2016-02-01         TP -2.3227878003  <NA> #> 866    2067    3M  CC02 2016 2016-02-01       TURB  0.8754687374  <NA> #> 867    2067    3M  CC02 2016 2016-03-07      CHLAC  0.8754687374  <NA> #> 868    2067    3M  CC02 2016 2016-03-07      COLOR  3.2188758249  <NA> #> 869    2067    3M  CC02 2016 2016-03-07       NO23 -4.1351665567  <NA> #> 870    2067    3M  CC02 2016 2016-03-07      SALIN  3.3357695763  <NA> #> 871    2067    3M  CC02 2016 2016-03-07        TKN -0.2357223335  <NA> #> 872    2067    3M  CC02 2016 2016-03-07         TN -0.2156715365     + #> 873    2067    3M  CC02 2016 2016-03-07         TP -2.3025850930  <NA> #> 874    2067    3M  CC02 2016 2016-03-07       TURB  1.9315214116  <NA> #> 875    2067    3M  CC02 2016 2016-04-04      CHLAC  0.3364722366     I #> 876    2067    3M  CC02 2016 2016-04-04      COLOR  2.6390573296  <NA> #> 877    2067    3M  CC02 2016 2016-04-04         DO  1.1314021115  <NA> #> 878    2067    3M  CC02 2016 2016-04-04      DOSAT  3.7400477407     + #> 879    2067    3M  CC02 2016 2016-04-04       NO23 -3.9120230054  <NA> #> 880    2067    3M  CC02 2016 2016-04-04      SALIN  3.3809946743  <NA> #> 881    2067    3M  CC02 2016 2016-04-04        TKN -0.7133498879  <NA> #> 882    2067    3M  CC02 2016 2016-04-04         TN -0.6733445533     + #> 883    2067    3M  CC02 2016 2016-04-04         TP -2.3434070875  <NA> #> 884    2067    3M  CC02 2016 2016-04-04       TURB  1.1939224685     A #> 885    2067    3M  CC02 2016 2016-05-02      CHLAC  0.0953101798     I #> 886    2067    3M  CC02 2016 2016-05-02      COLOR  2.4849066498  <NA> #> 887    2067    3M  CC02 2016 2016-05-02         DO  0.7419373447  <NA> #> 888    2067    3M  CC02 2016 2016-05-02      DOSAT  3.4812400893     + #> 889    2067    3M  CC02 2016 2016-05-02       NO23 -4.9618451299     I #> 890    2067    3M  CC02 2016 2016-05-02      SALIN  3.5582011305  <NA> #> 891    2067    3M  CC02 2016 2016-05-02        TKN -0.7339691751  <NA> #> 892    2067    3M  CC02 2016 2016-05-02         TN -0.7256703723     + #> 893    2067    3M  CC02 2016 2016-05-02         TP -2.5257286443  <NA> #> 894    2067    3M  CC02 2016 2016-05-02       TURB  0.9555114450  <NA> #> 895    2067    3M  CC02 2016 2016-06-06      CHLAC  0.2623642645     I #> 896    2067    3M  CC02 2016 2016-06-06      COLOR  3.3672958300  <NA> #> 897    2067    3M  CC02 2016 2016-06-06         DO  0.7884573604  <NA> #> 898    2067    3M  CC02 2016 2016-06-06      DOSAT  3.5351453542     + #> 899    2067    3M  CC02 2016 2016-06-06       NO23 -4.8283137373     I #> 900    2067    3M  CC02 2016 2016-06-06      SALIN  3.4934726578  <NA> #> 901    2067    3M  CC02 2016 2016-06-06        TKN -0.7339691751  <NA> #> 902    2067    3M  CC02 2016 2016-06-06         TN -0.7256703723     + #> 903    2067    3M  CC02 2016 2016-06-06         TP -1.0788096614  <NA> #> 904    2067    3M  CC02 2016 2016-06-06       TURB  0.4700036292  <NA> #> 905    2067    3M  CC02 2016 2016-07-05      CHLAC  1.7047480922  <NA> #> 906    2067    3M  CC02 2016 2016-07-05      COLOR  2.8332133441  <NA> #> 907    2067    3M  CC02 2016 2016-07-05         DO  0.0000000000  <NA> #> 908    2067    3M  CC02 2016 2016-07-05      DOSAT  2.7788192720     + #> 909    2067    3M  CC02 2016 2016-07-05       NO23 -4.7105307016     I #> 910    2067    3M  CC02 2016 2016-07-05      SALIN  3.5174978374  <NA> #> 911    2067    3M  CC02 2016 2016-07-05        TKN  0.6418538862  <NA> #> 912    2067    3M  CC02 2016 2016-07-05         TN  0.6439569364     + #> 913    2067    3M  CC02 2016 2016-07-05         TP -1.7147984281  <NA> #> 914    2067    3M  CC02 2016 2016-07-05       TURB  2.9957322736  <NA> #> 915    2067    3M  CC02 2016 2016-08-01      CHLAC  0.8754687374  <NA> #> 916    2067    3M  CC02 2016 2016-08-01      COLOR  2.7080502011  <NA> #> 917    2067    3M  CC02 2016 2016-08-01         DO  0.4054651081  <NA> #> 918    2067    3M  CC02 2016 2016-08-01      DOSAT  3.1696855807     + #> 919    2067    3M  CC02 2016 2016-08-01       NO23 -4.3428059215  <NA> #> 920    2067    3M  CC02 2016 2016-08-01      SALIN  3.4688560301  <NA> #> 921    2067    3M  CC02 2016 2016-08-01        TKN -0.6161861394  <NA> #> 922    2067    3M  CC02 2016 2016-08-01         TN -0.5923972775     + #> 923    2067    3M  CC02 2016 2016-08-01         TP -2.6310891600  <NA> #> 924    2067    3M  CC02 2016 2016-08-01       TURB  0.9932517730  <NA> #> 925    2067    3M  CC02 2016 2016-10-03      CHLAC  1.1631508098  <NA> #> 926    2067    3M  CC02 2016 2016-10-03      COLOR  4.1271343850  <NA> #> 927    2067    3M  CC02 2016 2016-10-03         DO  0.8754687374  <NA> #> 928    2067    3M  CC02 2016 2016-10-03      DOSAT  3.5174978374     + #> 929    2067    3M  CC02 2016 2016-10-03       NO23 -4.6051701860  <NA> #> 930    2067    3M  CC02 2016 2016-10-03      SALIN  2.7343675094  <NA> #> 931    2067    3M  CC02 2016 2016-10-03        TKN -0.1392620673  <NA> #> 932    2067    3M  CC02 2016 2016-10-03         TN -0.1278333715     + #> 933    2067    3M  CC02 2016 2016-10-03         TP -2.4304184645  <NA> #> 934    2067    3M  CC02 2016 2016-10-03       TURB  0.7419373447  <NA> #> 935    2067    3M  CC02 2016 2016-12-05      CHLAC  0.6418538862     I #> 936    2067    3M  CC02 2016 2016-12-05      COLOR  0.9162907319     U #> 937    2067    3M  CC02 2016 2016-12-05         DO  1.3862943611  <NA> #> 938    2067    3M  CC02 2016 2016-12-05      DOSAT  4.0289167569     + #> 939    2067    3M  CC02 2016 2016-12-05       NO23 -4.1351665567  <NA> #> 940    2067    3M  CC02 2016 2016-12-05      SALIN  3.5438536821  <NA> #> 941    2067    3M  CC02 2016 2016-12-05        TKN -0.3424903089  <NA> #> 942    2067    3M  CC02 2016 2016-12-05         TN -0.3202052642     + #> 943    2067    3M  CC02 2016 2016-12-05         TP -2.5770219387  <NA> #> 944    2067    3M  CC02 2016 2016-12-05       TURB  1.8870696490     A #> 945    2067    3M  CC02 2017 2017-01-03      CHLAC  1.0986122887  <NA> #> 946    2067    3M  CC02 2017 2017-01-03      COLOR  1.5686159179     I #> 947    2067    3M  CC02 2017 2017-01-03         DO  1.3083328197  <NA> #> 948    2067    3M  CC02 2017 2017-01-03      DOSAT  3.9512437186     + #> 949    2067    3M  CC02 2017 2017-01-03       NO23 -3.9633162998  <NA> #> 950    2067    3M  CC02 2017 2017-01-03      SALIN  3.5438536821  <NA> #> 951    2067    3M  CC02 2017 2017-01-03        TKN -0.4780358009  <NA> #> 952    2067    3M  CC02 2017 2017-01-03         TN -0.4478508246     + #> 953    2067    3M  CC02 2017 2017-01-03         TP 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3M  CC02 2017 2017-03-06         DO  1.3862943611  <NA> #> 968    2067    3M  CC02 2017 2017-03-06      DOSAT  3.9778107460     + #> 969    2067    3M  CC02 2017 2017-03-06       NO23 -4.9618451299     I #> 970    2067    3M  CC02 2017 2017-03-06      SALIN  3.5174978374  <NA> #> 971    2067    3M  CC02 2017 2017-03-06        TKN -0.5798184953  <NA> #> 972    2067    3M  CC02 2017 2017-03-06         TN -0.5727010275     + #> 973    2067    3M  CC02 2017 2017-03-06         TP -2.6882475738  <NA> #> 974    2067    3M  CC02 2017 2017-03-06       TURB  1.3083328197  <NA> #> 975    2067    3M  CC02 2017 2017-04-03      CHLAC  0.6931471806  <NA> #> 976    2067    3M  CC02 2017 2017-04-03      COLOR  2.3978952728  <NA> #> 977    2067    3M  CC02 2017 2017-04-03         DO  1.2809338455  <NA> #> 978    2067    3M  CC02 2017 2017-04-03      DOSAT  4.0000338828     + #> 979    2067    3M  CC02 2017 2017-04-03       NO23 -4.9618451299     I #> 980    2067    3M  CC02 2017 2017-04-03      SALIN  3.5835189385  <NA> #> 981    2067    3M  CC02 2017 2017-04-03        TKN -0.4155154440  <NA> #> 982    2067    3M  CC02 2017 2017-04-03         TN -0.4094731295     + #> 983    2067    3M  CC02 2017 2017-04-03         TP -2.6592600369  <NA> #> 984    2067    3M  CC02 2017 2017-04-03       TURB  1.3862943611  <NA> #> 985    2067    3M  CC02 2017 2017-05-01      CHLAC  0.7884573604  <NA> #> 986    2067    3M  CC02 2017 2017-05-01      COLOR  1.5040773968     I #> 987    2067    3M  CC02 2017 2017-05-01         DO  1.2527629685  <NA> #> 988    2067    3M  CC02 2017 2017-05-01      DOSAT  3.9852734672     + #> 989    2067    3M  CC02 2017 2017-05-01       NO23 -5.5214609179     U #> 990    2067    3M  CC02 2017 2017-05-01      SALIN  3.5918177413  <NA> #> 991    2067    3M  CC02 2017 2017-05-01        TKN -0.4462871026  <NA> #> 992    2067    3M  CC02 2017 2017-05-01         TN -0.4431669753     + #> 993    2067    3M  CC02 2017 2017-05-01         TP -3.1010927892  <NA> #> 994    2067    3M  CC02 2017 2017-05-01       TURB  0.8754687374  <NA> #> 995    2067    3M  CC02 2017 2017-07-10      CHLAC  1.0296194172  <NA> #> 996    2067    3M  CC02 2017 2017-07-10      COLOR  3.1354942159  <NA> #> 997    2067    3M  CC02 2017 2017-07-10         DO  1.1314021115  <NA> #> 998    2067    3M  CC02 2017 2017-07-10      DOSAT  3.8938590348     + #> 999    2067    3M  CC02 2017 2017-07-10       NO23 -4.4228486292  <NA> #> 1000   2067    3M  CC02 2017 2017-07-10      SALIN  3.3978584804  <NA> #> 1001   2067    3M  CC02 2017 2017-07-10        TKN -0.4620354596  <NA> #> 1002   2067    3M  CC02 2017 2017-07-10         TN -0.4431669753     + #> 1003   2067    3M  CC02 2017 2017-07-10         TP -2.7181005370  <NA> #> 1004   2067    3M  CC02 2017 2017-07-10       TURB  1.4586150227  <NA> #> 1005   2067    3M  CC02 2017 2017-08-07      CHLAC  1.1631508098  <NA> #> 1006   2067    3M  CC02 2017 2017-08-07      COLOR  3.8712010109  <NA> #> 1007   2067    3M  CC02 2017 2017-08-07         DO  0.8754687374  <NA> #> 1008   2067    3M  CC02 2017 2017-08-07      DOSAT  3.6216707044     + #> 1009   2067    3M  CC02 2017 2017-08-07       NO23 -4.5098600062  <NA> #> 1010   2067    3M  CC02 2017 2017-08-07      SALIN  3.2542429687  <NA> #> 1011   2067    3M  CC02 2017 2017-08-07        TKN -0.4307829161  <NA> #> 1012   2067    3M  CC02 2017 2017-08-07         TN -0.4140014391     + #> 1013   2067    3M  CC02 2017 2017-08-07         TP -2.5639498571  <NA> #> 1014   2067    3M  CC02 2017 2017-08-07       TURB  0.5306282511  <NA> #> 1015   2067    3M  CC02 2017 2017-10-02      CHLAC  1.0986122887  <NA> #> 1016   2067    3M  CC02 2017 2017-10-02      COLOR  3.6888794541  <NA> #> 1017   2067    3M  CC02 2017 2017-10-02       NO23 -5.2983173665     I #> 1018   2067    3M  CC02 2017 2017-10-02        TKN -0.5276327421  <NA> #> 1019   2067    3M  CC02 2017 2017-10-02         TN -0.5208759596     + #> 1020   2067    3M  CC02 2017 2017-10-02         TP -2.3025850930  <NA> #> 1021   2067    3M  CC02 2017 2017-10-02       TURB  1.0296194172  <NA> #> 1022   2067    3M  CC02 2017 2017-11-06      CHLAC  0.9162907319  <NA> #> 1023   2067    3M  CC02 2017 2017-11-06      COLOR  3.2188758249  <NA> #> 1024   2067    3M  CC02 2017 2017-11-06         DO  1.2527629685  <NA> #> 1025   2067    3M  CC02 2017 2017-11-06      DOSAT  3.8938590348     + #> 1026   2067    3M  CC02 2017 2017-11-06       NO23 -4.6051701860  <NA> #> 1027   2067    3M  CC02 2017 2017-11-06      SALIN  3.3499040873  <NA> #> 1028   2067    3M  CC02 2017 2017-11-06        TKN -0.4620354596  <NA> #> 1029   2067    3M  CC02 2017 2017-11-06         TN -0.4462871026     + #> 1030   2067    3M  CC02 2017 2017-11-06         TP -2.6036901858  <NA> #> 1031   2067    3M  CC02 2017 2017-11-06       TURB  0.8754687374     A #> 1032   2067    3M  CC02 2017 2017-12-04      CHLAC  0.7884573604  <NA> #> 1033   2067    3M  CC02 2017 2017-12-04      COLOR  2.5649493575  <NA> #> 1034   2067    3M  CC02 2017 2017-12-04         DO  1.3862943611  <NA> #> 1035   2067    3M  CC02 2017 2017-12-04      DOSAT  4.0181832013     + #> 1036   2067    3M  CC02 2017 2017-12-04       NO23 -4.9618451299     I #> 1037   2067    3M  CC02 2017 2017-12-04      SALIN  3.5025498759  <NA> #> 1038   2067    3M  CC02 2017 2017-12-04        TKN -0.4780358009  <NA> #> 1039   2067    3M  CC02 2017 2017-12-04         TN -0.4716049106     + #> 1040   2067    3M  CC02 2017 2017-12-04         TP -2.6882475738  <NA> #> 1041   2067    3M  CC02 2017 2017-12-04       TURB  1.3862943611     A #> 1042   2067    3M  CC02 2018 2018-01-02      CHLAC  0.9932517730  <NA> #> 1043   2067    3M  CC02 2018 2018-01-02      COLOR  2.5649493575  <NA> #> 1044   2067    3M  CC02 2018 2018-01-02         DO  0.7884573604  <NA> #> 1045   2067    3M  CC02 2018 2018-01-02      DOSAT  3.2580965380     + #> 1046   2067    3M  CC02 2018 2018-01-02       NO23 -4.2686979494  <NA> #> 1047   2067    3M  CC02 2018 2018-01-02      SALIN  3.4688560301  <NA> #> 1048   2067    3M  CC02 2018 2018-01-02        TKN -0.6348782724  <NA> #> 1049   2067    3M  CC02 2018 2018-01-02         TN -0.6088060321     + #> 1050   2067    3M  CC02 2018 2018-01-02         TP -2.3434070875  <NA> #> 1051   2067    3M  CC02 2018 2018-01-02       TURB  1.5260563035  <NA> #> 1052   2067    3M  CC02 2018 2018-02-05      CHLAC  0.0953101798     I #> 1053   2067    3M  CC02 2018 2018-02-05      COLOR  2.6390573296  <NA> #> 1054   2067    3M  CC02 2018 2018-02-05         DO  1.5040773968  <NA> #> 1055   2067    3M  CC02 2018 2018-02-05      DOSAT  4.0724397268     + #> 1056   2067    3M  CC02 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 1057   2067    3M  CC02 2018 2018-02-05      SALIN  3.3877743613  <NA> #> 1058   2067    3M  CC02 2018 2018-02-05        TKN -0.7339691751  <NA> #> 1059   2067    3M  CC02 2018 2018-02-05         TN -0.7011793523     + #> 1060   2067    3M  CC02 2018 2018-02-05         TP -2.7030626596  <NA> #> 1061   2067    3M  CC02 2018 2018-02-05       TURB  1.2809338455  <NA> #> 1062   2067    3M  CC02 2018 2018-03-05      CHLAC  0.6931471806  <NA> #> 1063   2067    3M  CC02 2018 2018-03-05      COLOR  2.0014800002  <NA> #> 1064   2067    3M  CC02 2018 2018-03-05         DO  1.5475625087  <NA> #> 1065   2067    3M  CC02 2018 2018-03-05      DOSAT  4.1351665567     + #> 1066   2067    3M  CC02 2018 2018-03-05       NO23 -5.1159958098     I #> 1067   2067    3M  CC02 2018 2018-03-05      SALIN  3.5835189385  <NA> #> 1068   2067    3M  CC02 2018 2018-03-05        TKN -0.7339691751  <NA> #> 1069   2067    3M  CC02 2018 2018-03-05         TN -0.7256703723     + #> 1070   2067    3M  CC02 2018 2018-03-05         TP -2.7333680091  <NA> #> 1071   2067    3M  CC02 2018 2018-03-05       TURB  1.5892352051     A #> 1072   2067    3M  CC02 2018 2018-04-02      CHLAC  0.6931471806  <NA> #> 1073   2067    3M  CC02 2018 2018-04-02      COLOR  1.2527629685     I #> 1074   2067    3M  CC02 2018 2018-04-02         DO  1.4109869737  <NA> #> 1075   2067    3M  CC02 2018 2018-04-02      DOSAT  4.0926765051     + #> 1076   2067    3M  CC02 2018 2018-04-02       NO23 -4.7105307016     I #> 1077   2067    3M  CC02 2018 2018-04-02      SALIN  3.5945687746  <NA> #> 1078   2067    3M  CC02 2018 2018-04-02        TKN -0.6539264674  <NA> #> 1079   2067    3M  CC02 2018 2018-04-02         TN -0.6462635947     + #> 1080   2067    3M  CC02 2018 2018-04-02         TP -2.5510464523  <NA> #> 1081   2067    3M  CC02 2018 2018-04-02       TURB  1.7227665977  <NA> #> 1082   2067    3M  CC02 2018 2018-05-07      CHLAC  0.5306282511  <NA> #> 1083   2067    3M  CC02 2018 2018-05-07      COLOR  1.8245492921  <NA> #> 1084   2067    3M  CC02 2018 2018-05-07         DO  1.3609765531  <NA> #> 1085   2067    3M  CC02 2018 2018-05-07      DOSAT  3.9608131696  <NA> #> 1086   2067    3M  CC02 2018 2018-05-07       NO23 -5.2983173665     I #> 1087   2067    3M  CC02 2018 2018-05-07      SALIN  3.6027767551  <NA> #> 1088   2067    3M  CC02 2018 2018-05-07        TKN -0.3147107448  <NA> #> 1089   2067    3M  CC02 2018 2018-05-07         TN -0.3092462504     + #> 1090   2067    3M  CC02 2018 2018-05-07         TP -2.7488721956  <NA> #> 1091   2067    3M  CC02 2018 2018-05-07       TURB  1.3083328197  <NA> #> 1092   2067    3M  CC02 2018 2018-07-09      CHLAC  1.6094379124  <NA> #> 1093   2067    3M  CC02 2018 2018-07-09      COLOR  2.7725887222  <NA> #> 1094   2067    3M  CC02 2018 2018-07-09         DO  1.0818051704  <NA> #> 1095   2067    3M  CC02 2018 2018-07-09      DOSAT  3.8308129500  <NA> #> 1096   2067    3M  CC02 2018 2018-07-09       NO23 -5.2983173665     I #> 1097   2067    3M  CC02 2018 2018-07-09      SALIN  3.4741380061  <NA> #> 1098   2067    3M  CC02 2018 2018-07-09        TKN -0.5276327421  <NA> #> 1099   2067    3M  CC02 2018 2018-07-09         TN -0.5208759596     + #> 1100   2067    3M  CC02 2018 2018-07-09       TURB  0.9932517730  <NA> #> 1101   2067    3M  CC02 2018 2018-08-06      CHLAC  1.8562979904  <NA> #> 1102   2067    3M  CC02 2018 2018-08-06      COLOR  3.5263605246     A #> 1103   2067    3M  CC02 2018 2018-08-06         DO  0.8586616190  <NA> #> 1104   2067    3M  CC02 2018 2018-08-06      DOSAT  3.6270040504  <NA> #> 1105   2067    3M  CC02 2018 2018-08-06       NO23 -5.1159958098     I #> 1106   2067    3M  CC02 2018 2018-08-06      SALIN  3.4968105459  <NA> #> 1107   2067    3M  CC02 2018 2018-08-06        TKN -0.2107210313  <NA> #> 1108   2067    3M  CC02 2018 2018-08-06         TN -0.2057949130     + #> 1109   2067    3M  CC02 2018 2018-08-06         TP -2.3968957725  <NA> #> 1110   2067    3M  CC02 2018 2018-08-06       TURB  1.0296194172     A #> 1111   2067    3M  CC02 2019 2019-02-04      CHLAC -0.1984509387     I #> 1112   2067    3M  CC02 2019 2019-02-04      COLOR  3.1354942159  <NA> #> 1113   2067    3M  CC02 2019 2019-02-04         DO  1.3323660191  <NA> #> 1114   2067    3M  CC02 2019 2019-02-04      DOSAT  3.8999504242  <NA> #> 1115   2067    3M  CC02 2019 2019-02-04       NO23 -4.1997050779  <NA> #> 1116   2067    3M  CC02 2019 2019-02-04      SALIN  3.2669037939  <NA> #> 1117   2067    3M  CC02 2019 2019-02-04        TKN -0.6931471806  <NA> #> 1118   2067    3M  CC02 2019 2019-02-04         TN -0.6635883783     + #> 1119   2067    3M  CC02 2019 2019-02-04         TP -2.7181005370  <NA> #> 1120   2067    3M  CC02 2019 2019-02-04       TURB  0.9932517730  <NA> #> 1121   2067    3M  CC02 2019 2019-03-04      CHLAC  0.2623642645     I #> 1122   2067    3M  CC02 2019 2019-03-04      COLOR  3.0445224377  <NA> #> 1123   2067    3M  CC02 2019 2019-03-04       NO23 -5.2983173665     I #> 1124   2067    3M  CC02 2019 2019-03-04      SALIN  3.4381719845  <NA> #> 1125   2067    3M  CC02 2019 2019-03-04        TKN -0.7550225843  <NA> #> 1126   2067    3M  CC02 2019 2019-03-04         TN -0.7465479573     + #> 1127   2067    3M  CC02 2019 2019-03-04         TP -2.7968814148  <NA> #> 1128   2067    3M  CC02 2019 2019-03-04       TURB  0.5877866649  <NA> #> 1129   2067    3M  CC02 2019 2019-04-01      CHLAC -0.2107210313     I #> 1130   2067    3M  CC02 2019 2019-04-01      COLOR  2.0794415417  <NA> #> 1131   2067    3M  CC02 2019 2019-04-01       NO23 -5.5214609179     U #> 1132   2067    3M  CC02 2019 2019-04-01        TKN -0.6161861394  <NA> #> 1133   2067    3M  CC02 2019 2019-04-01         TN -0.6124892775     + #> 1134   2067    3M  CC02 2019 2019-04-01         TP -2.9759296463  <NA> #> 1135   2067    3M  CC02 2019 2019-04-01       TURB  0.4700036292  <NA> #> 1136   2067    3M  CC02 2019 2019-05-06      CHLAC  0.5877866649     I #> 1137   2067    3M  CC02 2019 2019-05-06      COLOR  2.2617630985  <NA> #> 1138   2067    3M  CC02 2019 2019-05-06         DO  0.5877866649  <NA> #> 1139   2067    3M  CC02 2019 2019-05-06      DOSAT  3.3250360207  <NA> #> 1140   2067    3M  CC02 2019 2019-05-06       NO23 -4.8283137373     I #> 1141   2067    3M  CC02 2019 2019-05-06      SALIN  3.5522002552  <NA> #> 1142   2067    3M  CC02 2019 2019-05-06        TKN -0.5108256238  <NA> #> 1143   2067    3M  CC02 2019 2019-05-06         TN -0.5041810810     + #> 1144   2067    3M  CC02 2019 2019-05-06         TP -2.7030626596  <NA> #> 1145   2067    3M  CC02 2019 2019-05-06       TURB  1.0647107370  <NA> #> 1146   2067    3M  CC02 2019 2019-06-03      CHLAC  0.6418538862     I #> 1147   2067    3M  CC02 2019 2019-06-03      COLOR  1.3350010667     I #> 1148   2067    3M  CC02 2019 2019-06-03         DO  0.4700036292  <NA> #> 1149   2067    3M  CC02 2019 2019-06-03      DOSAT  3.2771447330  <NA> #> 1150   2067    3M  CC02 2019 2019-06-03       NO23 -4.3428059215  <NA> #> 1151   2067    3M  CC02 2019 2019-06-03      SALIN  3.5882300460  <NA> #> 1152   2067    3M  CC02 2019 2019-06-03        TKN -0.5447271754  <NA> #> 1153   2067    3M  CC02 2019 2019-06-03         TN -0.5225608800     + #> 1154   2067    3M  CC02 2019 2019-06-03         TP -2.6172958378  <NA> #> 1155   2067    3M  CC02 2019 2019-06-03       TURB  0.6931471806  <NA> #> 1156   2067    3M  CC02 2019 2019-07-01      CHLAC  0.7419373447     I #> 1157   2067    3M  CC02 2019 2019-07-01      COLOR  1.9315214116  <NA> #> 1158   2067    3M  CC02 2019 2019-07-01       NO23 -4.8283137373     I #> 1159   2067    3M  CC02 2019 2019-07-01      SALIN  3.5424075502  <NA> #> 1160   2067    3M  CC02 2019 2019-07-01        TKN -0.5621189182  <NA> #> 1161   2067    3M  CC02 2019 2019-07-01         TN -0.5551258827     + #> 1162   2067    3M  CC02 2019 2019-07-01         TP -3.1941832123  <NA> #> 1163   2067    3M  CC02 2019 2019-07-01       TURB  0.8329091229  <NA> #> 1164   2067    3M  CC02 2019 2019-08-05      CHLAC  0.6418538862     I #> 1165   2067    3M  CC02 2019 2019-08-05      COLOR  3.7841896339     A #> 1166   2067    3M  CC02 2019 2019-08-05         DO  0.6312717768  <NA> #> 1167   2067    3M  CC02 2019 2019-08-05      DOSAT  3.3775875160  <NA> #> 1168   2067    3M  CC02 2019 2019-08-05       NO23 -4.7105307016     I #> 1169   2067    3M  CC02 2019 2019-08-05      SALIN  3.3617633124  <NA> #> 1170   2067    3M  CC02 2019 2019-08-05        TKN -0.4780358009  <NA> #> 1171   2067    3M  CC02 2019 2019-08-05         TN -0.4716049106     + #> 1172   2067    3M  CC02 2019 2019-08-05         TP -3.1010927892  <NA> #> 1173   2067    3M  CC02 2019 2019-08-05       TURB  0.4054651081  <NA> #> 1174   2067    3M  CC02 2019 2019-10-07      CHLAC  1.3350010667  <NA> #> 1175   2067    3M  CC02 2019 2019-10-07      COLOR  1.2809338455     I #> 1176   2067    3M  CC02 2019 2019-10-07         DO  1.0508216248  <NA> #> 1177   2067    3M  CC02 2019 2019-10-07      DOSAT  3.7750571504  <NA> #> 1178   2067    3M  CC02 2019 2019-10-07       NO23 -5.2983173665     I #> 1179   2067    3M  CC02 2019 2019-10-07      SALIN  3.5389282774  <NA> #> 1180   2067    3M  CC02 2019 2019-10-07        TKN -0.6733445533  <NA> #> 1181   2067    3M  CC02 2019 2019-10-07         TN -0.6655320135     + #> 1182   2067    3M  CC02 2019 2019-10-07         TP -2.9759296463  <NA> #> 1183   2067    3M  CC02 2019 2019-10-07       TURB  1.1314021115  <NA> #> 1184   2067    3M  CC02 2019 2019-11-04      CHLAC  1.6292405397  <NA> #> 1185   2067    3M  CC02 2019 2019-11-04      COLOR  1.4816045409     I #> 1186   2067    3M  CC02 2019 2019-11-04         DO  0.4762341790  <NA> #> 1187   2067    3M  CC02 2019 2019-11-04      DOSAT  3.2464909919  <NA> #> 1188   2067    3M  CC02 2019 2019-11-04       NO23 -4.4228486292  <NA> #> 1189   2067    3M  CC02 2019 2019-11-04      SALIN  3.5177945292  <NA> #> 1190   2067    3M  CC02 2019 2019-11-04        TKN -0.4307829161  <NA> #> 1191   2067    3M  CC02 2019 2019-11-04         TN -0.4124897230     + #> 1192   2067    3M  CC02 2019 2019-11-04         TP -2.5257286443  <NA> #> 1193   2067    3M  CC02 2019 2019-11-04       TURB  1.2809338455  <NA> #> 1194   2067    3M  CC02 2019 2019-12-02      CHLAC  0.0953101798     I #> 1195   2067    3M  CC02 2019 2019-12-02      COLOR  0.9162907319     U #> 1196   2067    3M  CC02 2019 2019-12-02         DO  0.9932517730  <NA> #> 1197   2067    3M  CC02 2019 2019-12-02      DOSAT  3.6454498962  <NA> #> 1198   2067    3M  CC02 2019 2019-12-02       NO23 -4.4228486292  <NA> #> 1199   2067    3M  CC02 2019 2019-12-02      SALIN  3.5133348816  <NA> #> 1200   2067    3M  CC02 2019 2019-12-02        TKN -0.7765287895  <NA> #> 1201   2067    3M  CC02 2019 2019-12-02         TN -0.7507762934     + #> 1202   2067    3M  CC02 2019 2019-12-02         TP -2.9374633654  <NA> #> 1203   2067    3M  CC02 2019 2019-12-02       TURB  0.7419373447  <NA> #> 1204   2067    3M  CC02 2020 2020-01-06      CHLAC  0.6931471806     I #> 1205   2067    3M  CC02 2020 2020-01-06      COLOR  2.5649493575  <NA> #> 1206   2067    3M  CC02 2020 2020-01-06       NO23 -4.2686979494  <NA> #> 1207   2067    3M  CC02 2020 2020-01-06      SALIN  3.4775409482  <NA> #> 1208   2067    3M  CC02 2020 2020-01-06        TKN -0.4620354596  <NA> #> 1209   2067    3M  CC02 2020 2020-01-06         TN -0.4400565529     + #> 1210   2067    3M  CC02 2020 2020-01-06         TP -2.3859667019  <NA> #> 1211   2067    3M  CC02 2020 2020-01-06       TURB  1.2809338455  <NA> #> 1212   2067    3M  CC02 2020 2020-02-03      CHLAC  0.9555114450     I #> 1213   2067    3M  CC02 2020 2020-02-03      COLOR  2.2721258855  <NA> #> 1214   2067    3M  CC02 2020 2020-02-03         DO  1.4929040962  <NA> #> 1215   2067    3M  CC02 2020 2020-02-03      DOSAT  4.0360089852  <NA> #> 1216   2067    3M  CC02 2020 2020-02-03       NO23 -4.3428059215  <NA> #> 1217   2067    3M  CC02 2020 2020-02-03      SALIN  3.4691675081  <NA> #> 1218   2067    3M  CC02 2020 2020-02-03        TKN -0.6931471806  <NA> #> 1219   2067    3M  CC02 2020 2020-02-03         TN -0.6674794338     + #> 1220   2067    3M  CC02 2020 2020-02-03         TP -2.5902671654  <NA> #> 1221   2067    3M  CC02 2020 2020-02-03       TURB  0.9932517730  <NA> #> 1222   2067    3M  CC02 2020 2020-03-02      CHLAC  0.5306282511     I #> 1223   2067    3M  CC02 2020 2020-03-02      COLOR  0.9162907319     U #> 1224   2067    3M  CC02 2020 2020-03-02         DO  1.8437192082  <NA> #> 1225   2067    3M  CC02 2020 2020-03-02      DOSAT  4.4067192473  <NA> #> 1226   2067    3M  CC02 2020 2020-03-02       NO23 -5.2983173665     I #> 1227   2067    3M  CC02 2020 2020-03-02      SALIN  3.5222343767  <NA> #> 1228   2067    3M  CC02 2020 2020-03-02         TN -0.8347107449     + #> 1229   2067    3M  CC02 2020 2020-03-02         TP -2.6736487744  <NA> #> 1230   2067    3M  CC02 2020 2020-03-02       TURB  1.7749523509     A #> 1231   2067    3M  CC02 2020 2020-09-08      CHLAC  1.4350845253  <NA> #> 1232   2067    3M  CC02 2020 2020-09-08      COLOR  3.9318256327     A #> 1233   2067    3M  CC02 2020 2020-09-08         DO  0.6259384309  <NA> #> 1234   2067    3M  CC02 2020 2020-09-08      DOSAT  3.3214324132  <NA> #> 1235   2067    3M  CC02 2020 2020-09-08       NO23 -4.2686979494  <NA> #> 1236   2067    3M  CC02 2020 2020-09-08      SALIN  3.2268439945  <NA> #> 1237   2067    3M  CC02 2020 2020-09-08        TKN -0.3856624808  <NA> #> 1238   2067    3M  CC02 2020 2020-09-08         TN -0.3652833185     + #> 1239   2067    3M  CC02 2020 2020-09-08         TP -2.5639498571  <NA> #> 1240   2067    3M  CC02 2020 2020-09-08       TURB  0.7419373447  <NA> #> 1241   2067    3M  CC02 2020 2020-10-05      CHLAC  0.8754687374     I #> 1242   2067    3M  CC02 2020 2020-10-05      COLOR  3.4339872045     A #> 1243   2067    3M  CC02 2020 2020-10-05         DO  0.7793248768  <NA> #> 1244   2067    3M  CC02 2020 2020-10-05      DOSAT  3.4038604991  <NA> #> 1245   2067    3M  CC02 2020 2020-10-05       NO23 -3.6496587410  <NA> #> 1246   2067    3M  CC02 2020 2020-10-05      SALIN  3.3769046891  <NA> #> 1247   2067    3M  CC02 2020 2020-10-05        TKN -0.5447271754  <NA> #> 1248   2067    3M  CC02 2020 2020-10-05         TN -0.5008752929     + #> 1249   2067    3M  CC02 2020 2020-10-05         TP -2.5510464523  <NA> #> 1250   2067    3M  CC02 2020 2020-10-05       TURB  0.8329091229     A #> 1251   2067    3M  CC02 2020 2020-11-02         TN -0.7256703723     + #> 1252   2067    3M  CC02 2020 2020-11-02      CHLAC  1.0647107370  <NA> #> 1253   2067    3M  CC02 2020 2020-11-02      COLOR  3.1354942159  <NA> #> 1254   2067    3M  CC02 2020 2020-11-02         DO  0.7654678421  <NA> #> 1255   2067    3M  CC02 2020 2020-11-02      DOSAT  3.4594662898  <NA> #> 1256   2067    3M  CC02 2020 2020-11-02       NO23 -4.2686979494  <NA> #> 1257   2067    3M  CC02 2020 2020-11-02      SALIN  3.3813347526  <NA> #> 1258   2067    3M  CC02 2020 2020-11-02        TKN -0.7550225843  <NA> #> 1259   2067    3M  CC02 2020 2020-11-02         TP -2.5639498571  <NA> #> 1260   2067    3M  CC02 2020 2020-11-02       TURB  1.3350010667  <NA> #> 1261   2067    3M  CC02 2020 2020-12-07      CHLAC -0.1984509387     U #> 1262   2067    3M  CC02 2020 2020-12-07      COLOR  2.0149030205  <NA> #> 1263   2067    3M  CC02 2020 2020-12-07         DO  1.2919836816  <NA> #> 1264   2067    3M  CC02 2020 2020-12-07      DOSAT  4.0656020934  <NA> #> 1265   2067    3M  CC02 2020 2020-12-07       NO23 -3.6119184130  <NA> #> 1266   2067    3M  CC02 2020 2020-12-07        TKN -0.8439700703  <NA> #> 1267   2067    3M  CC02 2020 2020-12-07         TN -0.7830718881     + #> 1268   2067    3M  CC02 2020 2020-12-07         TP -2.7646205526  <NA> #> 1269   2067    3M  CC02 2020 2020-12-07       TURB  0.6418538862  <NA> #> 1270   2067    3M  CC02 2021 2021-02-01      CHLAC  0.1823215568     I #> 1271   2067    3M  CC02 2021 2021-02-01      COLOR  0.9162907319     U #> 1272   2067    3M  CC02 2021 2021-02-01         DO  1.5953389881  <NA> #> 1273   2067    3M  CC02 2021 2021-02-01      DOSAT  4.1820501426  <NA> #> 1274   2067    3M  CC02 2021 2021-02-01       NO23 -4.9618451299     I #> 1275   2067    3M  CC02 2021 2021-02-01      SALIN  3.4882920885  <NA> #> 1276   2067    3M  CC02 2021 2021-02-01        TKN -0.7133498879  <NA> #> 1277   2067    3M  CC02 2021 2021-02-01         TN -0.7052197618     + #> 1278   2067    3M  CC02 2021 2021-02-01         TP -3.0159349809  <NA> #> 1279   2067    3M  CC02 2021 2021-02-01       TURB  0.7884573604  <NA> #> 1280   2067    3M  CC02 2021 2021-03-01      CHLAC  0.6418538862     I #> 1281   2067    3M  CC02 2021 2021-03-01      COLOR  1.5686159179     I #> 1282   2067    3M  CC02 2021 2021-03-01         DO  1.4327007339  <NA> #> 1283   2067    3M  CC02 2021 2021-03-01      DOSAT  4.1271343850  <NA> #> 1284   2067    3M  CC02 2021 2021-03-01       NO23 -5.1159958098     I #> 1285   2067    3M  CC02 2021 2021-03-01      SALIN  3.5331024525  <NA> #> 1286   2067    3M  CC02 2021 2021-03-01        TKN -0.8209805521  <NA> #> 1287   2067    3M  CC02 2021 2021-03-01         TN -0.8119307165     + #> 1288   2067    3M  CC02 2021 2021-03-01         TP -2.6450754019  <NA> #> 1289   2067    3M  CC02 2021 2021-03-01       TURB  1.5040773968  <NA> #> 1290   2067    3M  CC02 2021 2021-04-05         TN -1.8078888512     + #> 1291   2067    3M  CC02 2021 2021-04-05      CHLAC  0.4054651081     I #> 1292   2067    3M  CC02 2021 2021-04-05      COLOR  1.9021075264  <NA> #> 1293   2067    3M  CC02 2021 2021-04-05         DO  1.1631508098  <NA> #> 1294   2067    3M  CC02 2021 2021-04-05      DOSAT  3.7977338590  <NA> #> 1295   2067    3M  CC02 2021 2021-04-05       NO23 -4.9618451299     I #> 1296   2067    3M  CC02 2021 2021-04-05      SALIN  3.5325179990  <NA> #> 1297   2067    3M  CC02 2021 2021-04-05        TKN -0.9416085399     I #> 1298   2067    3M  CC02 2021 2021-04-05         TP -2.7030626596  <NA> #> 1299   2067    3M  CC02 2021 2021-04-05       TURB  1.1939224685  <NA> #> 1300   2067    3M  CC02 2021 2021-05-03      CHLAC  0.2623642645     I #> 1301   2067    3M  CC02 2021 2021-05-03      COLOR  1.9021075264  <NA> #> 1302   2067    3M  CC02 2021 2021-05-03         DO  0.8064758659  <NA> #> 1303   2067    3M  CC02 2021 2021-05-03      DOSAT  3.5553480615  <NA> #> 1304   2067    3M  CC02 2021 2021-05-03       NO23 -5.5214609179     I #> 1305   2067    3M  CC02 2021 2021-05-03      SALIN  3.5487549460  <NA> #> 1306   2067    3M  CC02 2021 2021-05-03        TKN -0.8439700703  <NA> #> 1307   2067    3M  CC02 2021 2021-05-03         TN -0.8347107449     + #> 1308   2067    3M  CC02 2021 2021-05-03         TP -2.8134107168  <NA> #> 1309   2067    3M  CC02 2021 2021-05-03       TURB  1.2527629685  <NA> #> 1310   2067    3M  CC02 2021 2021-06-07      CHLAC  0.5306282511     I #> 1311   2067    3M  CC02 2021 2021-06-07      COLOR  1.7749523509     I #> 1312   2067    3M  CC02 2021 2021-06-07         DO  1.1999647829  <NA> #> 1313   2067    3M  CC02 2021 2021-06-07      DOSAT  3.9852734672  <NA> #> 1314   2067    3M  CC02 2021 2021-06-07       NO23 -4.8283137373     I #> 1315   2067    3M  CC02 2021 2021-06-07      SALIN  3.6103772260  <NA> #> 1316   2067    3M  CC02 2021 2021-06-07        TKN -0.6733445533  <NA> #> 1317   2067    3M  CC02 2021 2021-06-07         TN -0.6655320135     + #> 1318   2067    3M  CC02 2021 2021-06-07         TP -3.0159349809  <NA> #> 1319   2067    3M  CC02 2021 2021-06-07       TURB  0.6418538862  <NA> #> 1320   2067    3M  CC02 2021 2021-08-02      CHLAC  2.0668627595  <NA> #> 1321   2067    3M  CC02 2021 2021-08-02      COLOR  4.2626798770  <NA> #> 1322   2067    3M  CC02 2021 2021-08-02         DO  0.5128236264  <NA> #> 1323   2067    3M  CC02 2021 2021-08-02      DOSAT  3.2657594108  <NA> #> 1324   2067    3M  CC02 2021 2021-08-02       NO23 -5.5214609179     U #> 1325   2067    3M  CC02 2021 2021-08-02      SALIN  3.2846635654  <NA> #> 1326   2067    3M  CC02 2021 2021-08-02        TKN -0.1984509387  <NA> #> 1327   2067    3M  CC02 2021 2021-08-02         TN -0.1960148839     + #> 1328   2067    3M  CC02 2021 2021-08-02         TP -2.5639498571  <NA> #> 1329   2067    3M  CC02 2021 2021-08-02       TURB  0.9555114450  <NA> #> 1330   2067    3M  CC02 2021 2021-09-07      CHLAC  2.1633230257  <NA> #> 1331   2067    3M  CC02 2021 2021-09-07      COLOR  3.7841896339  <NA> #> 1332   2067    3M  CC02 2021 2021-09-07         DO  1.6863989536  <NA> #> 1333   2067    3M  CC02 2021 2021-09-07      DOSAT  4.4236483094  <NA> #> 1334   2067    3M  CC02 2021 2021-09-07       NO23 -5.2983173665     I #> 1335   2067    3M  CC02 2021 2021-09-07      SALIN  3.2771447330  <NA> #> 1336   2067    3M  CC02 2021 2021-09-07        TKN -0.1863295782  <NA> #> 1337   2067    3M  CC02 2021 2021-09-07         TN -0.1815218766     + #> 1338   2067    3M  CC02 2021 2021-09-07         TP -2.6310891600  <NA> #> 1339   2067    3M  CC02 2021 2021-09-07       TURB  0.9932517730  <NA> #> 1340   2067    3M  CC02 2021 2021-10-04      CHLAC  1.8718021769  <NA> #> 1341   2067    3M  CC02 2021 2021-10-04      COLOR  2.9444389792  <NA> #> 1342   2067    3M  CC02 2021 2021-10-04         DO  1.2354714714  <NA> #> 1343   2067    3M  CC02 2021 2021-10-04      DOSAT  3.9512437186  <NA> #> 1344   2067    3M  CC02 2021 2021-10-04       NO23 -5.5214609179     I #> 1345   2067    3M  CC02 2021 2021-10-04      SALIN  3.4525240088  <NA> #> 1346   2067    3M  CC02 2021 2021-10-04        TKN -0.5798184953  <NA> #> 1347   2067    3M  CC02 2021 2021-10-04         TN -0.5727010275     + #> 1348   2067    3M  CC02 2021 2021-10-04         TP -2.6882475738  <NA> #> 1349   2067    3M  CC02 2021 2021-10-04       TURB  0.8754687374     A #> 1350   2067    3M  CC02 2021 2021-11-01      CHLAC  1.1939224685  <NA> #> 1351   2067    3M  CC02 2021 2021-11-01      COLOR  2.7080502011  <NA> #> 1352   2067    3M  CC02 2021 2021-11-01         DO  1.4678743481  <NA> #> 1353   2067    3M  CC02 2021 2021-11-01      DOSAT  4.1287459889  <NA> #> 1354   2067    3M  CC02 2021 2021-11-01       NO23 -3.9633162998  <NA> #> 1355   2067    3M  CC02 2021 2021-11-01      SALIN  3.4992311219  <NA> #> 1356   2067    3M  CC02 2021 2021-11-01        TKN -0.5447271754  <NA> #> 1357   2067    3M  CC02 2021 2021-11-01         TN -0.5124936809     + #> 1358   2067    3M  CC02 2021 2021-11-01         TP -2.5010360317  <NA> #> 1359   2067    3M  CC02 2021 2021-11-01       TURB  0.9932517730  <NA> #> 1360   2067    3M  CC02 2021 2021-12-06      CHLAC  0.5877866649     I #> 1361   2067    3M  CC02 2021 2021-12-06      COLOR  0.9162907319     U #> 1362   2067    3M  CC02 2021 2021-12-06         DO  1.4350845253  <NA> #> 1363   2067    3M  CC02 2021 2021-12-06      DOSAT  4.0430512678  <NA> #> 1364   2067    3M  CC02 2021 2021-12-06       NO23 -4.7105307016     I #> 1365   2067    3M  CC02 2021 2021-12-06      SALIN  3.4925603877  <NA> #> 1366   2067    3M  CC02 2021 2021-12-06        TKN -0.6348782724  <NA> #> 1367   2067    3M  CC02 2021 2021-12-06         TN -0.6273594400     + #> 1368   2067    3M  CC02 2021 2021-12-06         TP -2.9759296463  <NA> #> 1369   2067    3M  CC02 2021 2021-12-06       TURB  0.5306282511  <NA> #> 1370   2067    3M  CC02 2022 2022-01-03      CHLAC  0.5877866649     I #> 1371   2067    3M  CC02 2022 2022-01-03      COLOR  1.4109869737     I #> 1372   2067    3M  CC02 2022 2022-01-03         DO  1.7578579176  <NA> #> 1373   2067    3M  CC02 2022 2022-01-03      DOSAT  4.4224485492  <NA> #> 1374   2067    3M  CC02 2022 2022-01-03       NO23 -4.5098600062  <NA> #> 1375   2067    3M  CC02 2022 2022-01-03      SALIN  3.5174978374  <NA> #> 1376   2067    3M  CC02 2022 2022-01-03        TKN -0.8675005677  <NA> #> 1377   2067    3M  CC02 2022 2022-01-03         TN -0.8416471889     + #> 1378   2067    3M  CC02 2022 2022-01-03         TP -2.6882475738  <NA> #> 1379   2067    3M  CC02 2022 2022-01-03       TURB  0.7419373447  <NA> #> 1380   2067    3M  CC02 2022 2022-02-07      CHLAC  0.2623642645     I #> 1381   2067    3M  CC02 2022 2022-02-07      COLOR  0.9162907319     U #> 1382   2067    3M  CC02 2022 2022-02-07         DO  1.4996230464  <NA> #> 1383   2067    3M  CC02 2022 2022-02-07      DOSAT  4.0826093060  <NA> #> 1384   2067    3M  CC02 2022 2022-02-07       NO23 -4.5098600062  <NA> #> 1385   2067    3M  CC02 2022 2022-02-07      SALIN  3.5421180727  <NA> #> 1386   2067    3M  CC02 2022 2022-02-07        TKN -0.7985076962  <NA> #> 1387   2067    3M  CC02 2022 2022-02-07         TN -0.7743572360     + #> 1388   2067    3M  CC02 2022 2022-02-07         TP -2.8134107168  <NA> #> 1389   2067    3M  CC02 2022 2022-02-07       TURB  0.5877866649  <NA> #> 1390   2067    3M  CC02 2022 2022-03-07      CHLAC  0.4054651081     I #> 1391   2067    3M  CC02 2022 2022-03-07      COLOR  0.9162907319     U #> 1392   2067    3M  CC02 2022 2022-03-07         DO  1.4206957878  <NA> #> 1393   2067    3M  CC02 2022 2022-03-07      DOSAT  4.1059436981  <NA> #> 1394   2067    3M  CC02 2022 2022-03-07       NO23 -5.5214609179     U #> 1395   2067    3M  CC02 2022 2022-03-07      SALIN  3.5412491371  <NA> #> 1396   2067    3M  CC02 2022 2022-03-07        TKN -0.9162907319     I #> 1397   2067    3M  CC02 2022 2022-03-07         TN -1.8201589437     + #> 1398   2067    3M  CC02 2022 2022-03-07         TP -2.9004220937  <NA> #> 1399   2067    3M  CC02 2022 2022-03-07       TURB  0.9162907319  <NA> #> 1400   2067    3M  CC02 2022 2022-04-04      CHLAC  0.5877866649     I #> 1401   2067    3M  CC02 2022 2022-04-04      COLOR  0.9162907319     U #> 1402   2067    3M  CC02 2022 2022-04-04         DO  1.9430489168  <NA> #> 1403   2067    3M  CC02 2022 2022-04-04      DOSAT  4.6131383556  <NA> #> 1404   2067    3M  CC02 2022 2022-04-04       NO23 -4.7105307016     I #> 1405   2067    3M  CC02 2022 2022-04-04      SALIN  3.5599090728  <NA> #> 1406   2067    3M  CC02 2022 2022-04-04        TKN -1.2729656758     I #> 1407   2067    3M  CC02 2022 2022-04-04         TN -1.8078888512     + #> 1408   2067    3M  CC02 2022 2022-04-04         TP -2.7488721956  <NA> #> 1409   2067    3M  CC02 2022 2022-04-04       TURB  1.0296194172     A #> 1410   2067    3M  CC02 2022 2022-05-02      CHLAC  0.1823215568     I #> 1411   2067    3M  CC02 2022 2022-05-02      COLOR  0.9162907319     U #> 1412   2067    3M  CC02 2022 2022-05-02         DO  1.3244189574  <NA> #> 1413   2067    3M  CC02 2022 2022-05-02      DOSAT  4.0430512678  <NA> #> 1414   2067    3M  CC02 2022 2022-05-02       NO23 -4.7105307016     I #> 1415   2067    3M  CC02 2022 2022-05-02      SALIN  3.5768299503  <NA> #> 1416   2067    3M  CC02 2022 2022-05-02        TKN -0.7339691751  <NA> #> 1417   2067    3M  CC02 2022 2022-05-02         TN -0.7256703723     + #> 1418   2067    3M  CC02 2022 2022-05-02         TP -2.3025850930  <NA> #> 1419   2067    3M  CC02 2022 2022-05-02       TURB  0.4054651081  <NA> #> 1420   2067    3M  CC02 2022 2022-06-06      CHLAC  0.8754687374     I #> 1421   2067    3M  CC02 2022 2022-06-06      COLOR  2.5649493575  <NA> #> 1422   2067    3M  CC02 2022 2022-06-06         DO  1.0296194172  <NA> #> 1423   2067    3M  CC02 2022 2022-06-06      DOSAT  3.7887247891  <NA> #> 1424   2067    3M  CC02 2022 2022-06-06       NO23 -4.7105307016     I #> 1425   2067    3M  CC02 2022 2022-06-06      SALIN  3.5421180727  <NA> #> 1426   2067    3M  CC02 2022 2022-06-06        TKN -0.5621189182  <NA> #> 1427   2067    3M  CC02 2022 2022-06-06         TN -0.5551258827     + #> 1428   2067    3M  CC02 2022 2022-06-06         TP -3.0365542681  <NA> #> 1429   2067    3M  CC02 2022 2022-06-06       TURB  0.9555114450  <NA> #> 1430   2067    3M  CC02 2022 2022-07-05      CHLAC  1.8082887712  <NA> #> 1431   2067    3M  CC02 2022 2022-07-05      COLOR  1.0647107370     I #> 1432   2067    3M  CC02 2022 2022-07-05         DO  1.4255150743  <NA> #> 1433   2067    3M  CC02 2022 2022-07-05      DOSAT  4.2268337453  <NA> #> 1434   2067    3M  CC02 2022 2022-07-05       NO23 -5.2983173665     I #> 1435   2067    3M  CC02 2022 2022-07-05      SALIN  3.5519135990  <NA> #> 1436   2067    3M  CC02 2022 2022-07-05        TKN -0.5108256238  <NA> #> 1437   2067    3M  CC02 2022 2022-07-05         TN -0.5041810810     + #> 1438   2067    3M  CC02 2022 2022-07-05         TP -3.1235656451  <NA> #> 1439   2067    3M  CC02 2022 2022-07-05       TURB  1.3862943611     A #> 1440   2067    3M  CC02 2022 2022-08-01      CHLAC  0.8329091229     I #> 1441   2067    3M  CC02 2022 2022-08-01      COLOR  1.7404661748     I #> 1442   2067    3M  CC02 2022 2022-08-01         DO  1.6370530795  <NA> #> 1443   2067    3M  CC02 2022 2022-08-01      DOSAT  4.4248466319  <NA> #> 1444   2067    3M  CC02 2022 2022-08-01       NO23 -4.6051701860  <NA> #> 1445   2067    3M  CC02 2022 2022-08-01      SALIN  3.5478917608  <NA> #> 1446   2067    3M  CC02 2022 2022-08-01        TKN -0.5108256238  <NA> #> 1447   2067    3M  CC02 2022 2022-08-01         TN -0.4942963218     + #> 1448   2067    3M  CC02 2022 2022-08-01         TP -3.0576076773  <NA> #> 1449   2067    3M  CC02 2022 2022-08-01       TURB  0.8754687374  <NA> #> 1450   2067    3M  CC02 2022 2022-09-06      CHLAC  1.3609765531  <NA> #> 1451   2067    3M  CC02 2022 2022-09-06      COLOR  2.7080502011  <NA> #> 1452   2067    3M  CC02 2022 2022-09-06       NO23 -4.8283137373     I #> 1453   2067    3M  CC02 2022 2022-09-06      SALIN  3.5157158351  <NA> #> 1454   2067    3M  CC02 2022 2022-09-06        TKN -0.7985076962  <NA> #> 1455   2067    3M  CC02 2022 2022-09-06         TN -0.7896580809     + #> 1456   2067    3M  CC02 2022 2022-09-06         TP -3.2441936329  <NA> #> 1457   2067    3M  CC02 2022 2022-09-06       TURB  0.7884573604  <NA> #> 1458   2067    3M  CC02 2022 2022-11-07      CHLAC  2.3978952728  <NA> #> 1459   2067    3M  CC02 2022 2022-11-07      COLOR  3.5553480615     A #> 1460   2067    3M  CC02 2022 2022-11-07         DO  1.4011829736  <NA> #> 1461   2067    3M  CC02 2022 2022-11-07      DOSAT  4.0724397268  <NA> #> 1462   2067    3M  CC02 2022 2022-11-07       NO23 -5.5214609179     U #> 1463   2067    3M  CC02 2022 2022-11-07      SALIN  3.3714252233  <NA> #> 1464   2067    3M  CC02 2022 2022-11-07        TKN -0.3710636814  <NA> #> 1465   2067    3M  CC02 2022 2022-11-07         TN -0.3681693234     + #> 1466   2067    3M  CC02 2022 2022-11-07         TP -2.4079456087  <NA> #> 1467   2067    3M  CC02 2022 2022-11-07       TURB  1.0647107370     A #> 1468   2067    3M  CC02 2022 2022-12-05      CHLAC  2.1747517215  <NA> #> 1469   2067    3M  CC02 2022 2022-12-05      COLOR  3.3672958300     A #> 1470   2067    3M  CC02 2022 2022-12-05       NO23 -4.7105307016     I #> 1471   2067    3M  CC02 2022 2022-12-05      SALIN  3.3961848398  <NA> #> 1472   2067    3M  CC02 2022 2022-12-05        TKN -0.4620354596  <NA> #> 1473   2067    3M  CC02 2022 2022-12-05         TN -0.4557063245     + #> 1474   2067    3M  CC02 2022 2022-12-05         TP -2.4418471603  <NA> #> 1475   2067    3M  CC02 2022 2022-12-05       TURB  1.2527629685  <NA> #> 1476   2067    3M  CC02 2023 2023-01-03      CHLAC  2.2925347571  <NA> #> 1477   2067    3M  CC02 2023 2023-01-03      COLOR  2.7725887222  <NA> #> 1478   2067    3M  CC02 2023 2023-01-03         DO  1.6582280766  <NA> #> 1479   2067    3M  CC02 2023 2023-01-03      DOSAT  4.2904594411  <NA> #> 1480   2067    3M  CC02 2023 2023-01-03       NO23 -5.5214609179     U #> 1481   2067    3M  CC02 2023 2023-01-03      SALIN  3.4249139083  <NA> #> 1482   2067    3M  CC02 2023 2023-01-03        TKN -0.5798184953  <NA> #> 1483   2067    3M  CC02 2023 2023-01-03         TN -0.5762534291     + #> 1484   2067    3M  CC02 2023 2023-01-03         TP -2.5383074265  <NA> #> 1485   2067    3M  CC02 2023 2023-01-03       TURB  1.0296194172  <NA> #> 1486   2067    3M  CC02 2023 2023-02-06      CHLAC  0.8754687374     I #> 1487   2067    3M  CC02 2023 2023-02-06      COLOR  2.1747517215  <NA> #> 1488   2067    3M  CC02 2023 2023-02-06         DO  1.8017098001  <NA> #> 1489   2067    3M  CC02 2023 2023-02-06      DOSAT  4.4260435201  <NA> #> 1490   2067    3M  CC02 2023 2023-02-06       NO23 -5.1159958098     I #> 1491   2067    3M  CC02 2023 2023-02-06      SALIN  3.4895134627  <NA> #> 1492   2067    3M  CC02 2023 2023-02-06        TKN -0.7765287895  <NA> #> 1493   2067    3M  CC02 2023 2023-02-06         TN -0.7678707268     + #> 1494   2067    3M  CC02 2023 2023-02-06         TP -2.6882475738  <NA> #> 1495   2067    3M  CC02 2023 2023-02-06       TURB  0.9932517730  <NA> #> 1496   2067    3M  CC02 2023 2023-03-06         DO  1.7369512327  <NA> #> 1497   2067    3M  CC02 2023 2023-03-06      DOSAT  4.4555094114  <NA> #> 1498   2067    3M  CC02 2023 2023-03-06      SALIN  3.5342703359  <NA> #> 1499   2067    3M  CC02 2018 2018-03-13      CHLAC  1.2809338455  <NA> #> 1500   2067    3M  CC02 2018 2018-03-13       COND 10.7870277941  <NA> #> 1501   2067    3M  CC02 2018 2018-03-13         DO  1.6505798558  <NA> #> 1502   2067    3M  CC02 2018 2018-03-13      DOSAT  4.2282925347  <NA> #> 1503   2067    3M  CC02 2018 2018-03-13       NO23 -5.5214609179     U #> 1504   2067    3M  CC02 2018 2018-03-13      SALIN  3.5751506888     + #> 1505   2067    3M  CC02 2018 2018-03-13        TKN -0.9416085399     I #> 1506   2067    3M  CC02 2018 2018-03-13         TN -1.8201589437     + #> 1507   2067    3M  CC02 2018 2018-03-13         TP -3.1465551633  <NA> #> 1508   2067    3M  CC02 2018 2018-03-13        TSS  2.4849066498  <NA> #> 1509   2067    3M  CC02 2018 2018-03-13       TURB  1.0296194172  <NA> #> 1510   2067    3M  CC02 2018 2018-05-08      CHLAC  1.3083328197  <NA> #> 1511   2067    3M  CC02 2018 2018-05-08       COND 10.9059926772  <NA> #> 1512   2067    3M  CC02 2018 2018-05-08         DO  1.5953389881  <NA> #> 1513   2067    3M  CC02 2018 2018-05-08      DOSAT  4.2904594411  <NA> #> 1514   2067    3M  CC02 2018 2018-05-08       NO23 -5.5214609179     U #> 1515   2067    3M  CC02 2018 2018-05-08      SALIN  3.5481795720     + #> 1516   2067    3M  CC02 2018 2018-05-08        TKN -0.4462871026  <NA> #> 1517   2067    3M  CC02 2018 2018-05-08         TN -0.4431669753     + #> 1518   2067    3M  CC02 2018 2018-05-08         TP -2.7181005370  <NA> #> 1519   2067    3M  CC02 2018 2018-05-08        TSS  1.6094379124     I #> 1520   2067    3M  CC02 2018 2018-05-08       TURB  1.2237754316  <NA> #> 1521   2067    3M  CC02 2018 2018-06-26      CHLAC  2.5649493575  <NA> #> 1522   2067    3M  CC02 2018 2018-06-26       COND 10.6878456131  <NA> #> 1523   2067    3M  CC02 2018 2018-06-26         DO  1.2947271676  <NA> #> 1524   2067    3M  CC02 2018 2018-06-26      DOSAT  4.0395363257  <NA> #> 1525   2067    3M  CC02 2018 2018-06-26       NO23 -4.9618451299     I #> 1526   2067    3M  CC02 2018 2018-06-26        TKN -0.3566749439  <NA> #> 1527   2067    3M  CC02 2018 2018-06-26         TN -0.3509769228     + #> 1528   2067    3M  CC02 2018 2018-06-26         TP -2.3025850930  <NA> #> 1529   2067    3M  CC02 2018 2018-06-26        TSS  2.0794415417     I #> 1530   2067    3M  CC02 2018 2018-06-26       TURB  1.0647107370     A #> 1531   2067    3M  CC02 2018 2018-09-18      CHLAC  2.3978952728  <NA> #> 1532   2067    3M  CC02 2018 2018-09-18       COND 10.2632925926  <NA> #> 1533   2067    3M  CC02 2018 2018-09-18         DO  0.9745596400  <NA> #> 1534   2067    3M  CC02 2018 2018-09-18      DOSAT  3.6963514690  <NA> #> 1535   2067    3M  CC02 2018 2018-09-18       NO23 -3.2188758249  <NA> #> 1536   2067    3M  CC02 2018 2018-09-18        TKN -0.2231435513  <NA> #> 1537   2067    3M  CC02 2018 2018-09-18         TN -0.1743533871     + #> 1538   2067    3M  CC02 2018 2018-09-18         TP -2.0402208285  <NA> #> 1539   2067    3M  CC02 2018 2018-09-18        TSS  1.3862943611     I #> 1540   2067    3M  CC02 2018 2018-09-18       TURB  0.7884573604  <NA> #> 1541   2067    3M  CC02 2018 2018-12-04      CHLAC  1.2809338455  <NA> #> 1542   2067    3M  CC02 2018 2018-12-04       COND 10.8257007122  <NA> #> 1543   2067    3M  CC02 2018 2018-12-04         DO  1.6272778306  <NA> #> 1544   2067    3M  CC02 2018 2018-12-04      DOSAT  4.3107991254  <NA> #> 1545   2067    3M  CC02 2018 2018-12-04       NO23 -1.9661128564     G #> 1546   2067    3M  CC02 2018 2018-12-04      SALIN  3.4949912609  <NA> #> 1547   2067    3M  CC02 2018 2018-12-04        TKN -0.4155154440  <NA> #> 1548   2067    3M  CC02 2018 2018-12-04         TN -0.2231435513     + #> 1549   2067    3M  CC02 2018 2018-12-04         TP -2.5010360317  <NA> #> 1550   2067    3M  CC02 2018 2018-12-04        TSS  2.3025850930     I #> 1551   2067    3M  CC02 2018 2018-12-04       TURB  0.4054651081  <NA> #> 1552   2068    3M  CC03 2014 2014-01-06      CHLAC  0.3364722366     I #> 1553   2068    3M  CC03 2014 2014-01-06      COLOR  2.5649493575  <NA> #> 1554   2068    3M  CC03 2014 2014-01-06         DO  1.3862943611  <NA> #> 1555   2068    3M  CC03 2014 2014-01-06      DOSAT  3.9963641539     + #> 1556   2068    3M  CC03 2014 2014-01-06       NO23 -4.7105307016     I #> 1557   2068    3M  CC03 2014 2014-01-06      SALIN  3.4904285154  <NA> #> 1558   2068    3M  CC03 2014 2014-01-06        TKN -0.6161861394  <NA> #> 1559   2068    3M  CC03 2014 2014-01-06         TN -0.6088060321     + #> 1560   2068    3M  CC03 2014 2014-01-06         TP -3.1010927892  <NA> #> 1561   2068    3M  CC03 2014 2014-01-06       TURB  0.4054651081  <NA> #> 1562   2068    3M  CC03 2014 2014-02-03      CHLAC  1.8870696490  <NA> #> 1563   2068    3M  CC03 2014 2014-02-03      COLOR  3.5263605246  <NA> #> 1564   2068    3M  CC03 2014 2014-02-03         DO  0.7884573604  <NA> #> 1565   2068    3M  CC03 2014 2014-02-03      DOSAT  3.2921262866     + #> 1566   2068    3M  CC03 2014 2014-02-03       NO23 -3.6888794541  <NA> #> 1567   2068    3M  CC03 2014 2014-02-03      SALIN  2.6602595373  <NA> #> 1568   2068    3M  CC03 2014 2014-02-03        TKN  0.0000000000  <NA> #> 1569   2068    3M  CC03 2014 2014-02-03         TN  0.0246926126     + #> 1570   2068    3M  CC03 2014 2014-02-03         TP -2.3025850930  <NA> #> 1571   2068    3M  CC03 2014 2014-02-03       TURB  0.8329091229  <NA> #> 1572   2068    3M  CC03 2014 2014-03-03      CHLAC  1.0986122887  <NA> #> 1573   2068    3M  CC03 2014 2014-03-03      COLOR  2.8332133441  <NA> #> 1574   2068    3M  CC03 2014 2014-03-03         DO  0.7884573604  <NA> #> 1575   2068    3M  CC03 2014 2014-03-03      DOSAT  3.3638415951     + #> 1576   2068    3M  CC03 2014 2014-03-03       NO23 -5.5214609179     I #> 1577   2068    3M  CC03 2014 2014-03-03      SALIN  3.2657594108  <NA> #> 1578   2068    3M  CC03 2014 2014-03-03        TKN -0.4462871026  <NA> #> 1579   2068    3M  CC03 2014 2014-03-03         TN -0.4400565529     + #> 1580   2068    3M  CC03 2014 2014-03-03         TP -2.6592600369  <NA> #> 1581   2068    3M  CC03 2014 2014-03-03       TURB  0.7884573604  <NA> #> 1582   2068    3M  CC03 2014 2014-04-07      CHLAC  1.2237754316  <NA> #> 1583   2068    3M  CC03 2014 2014-04-07      COLOR  3.4011973817     A #> 1584   2068    3M  CC03 2014 2014-04-07         DO  0.6418538862  <NA> #> 1585   2068    3M  CC03 2014 2014-04-07      DOSAT  3.2580965380     + #> 1586   2068    3M  CC03 2014 2014-04-07       NO23 -4.3428059215  <NA> #> 1587   2068    3M  CC03 2014 2014-04-07      SALIN  3.1000922889  <NA> #> 1588   2068    3M  CC03 2014 2014-04-07        TKN -0.1392620673  <NA> #> 1589   2068    3M  CC03 2014 2014-04-07         TN -0.1244300784     + #> 1590   2068    3M  CC03 2014 2014-04-07         TP -2.3968957725  <NA> #> 1591   2068    3M  CC03 2014 2014-04-07       TURB  0.3364722366     A #> 1592   2068    3M  CC03 2014 2014-05-05      CHLAC  2.3978952728  <NA> #> 1593   2068    3M  CC03 2014 2014-05-05      COLOR  3.9120230054  <NA> #> 1594   2068    3M  CC03 2014 2014-05-05         DO  0.0000000000  <NA> #> 1595   2068    3M  CC03 2014 2014-05-05      DOSAT  2.5649493575     + #> 1596   2068    3M  CC03 2014 2014-05-05       NO23 -3.4112477175  <NA> #> 1597   2068    3M  CC03 2014 2014-05-05      SALIN  2.8622008809  <NA> #> 1598   2068    3M  CC03 2014 2014-05-05        TKN -0.0512932944  <NA> #> 1599   2068    3M  CC03 2014 2014-05-05         TN -0.0171461588     + #> 1600   2068    3M  CC03 2014 2014-05-05         TP -2.3025850930  <NA> #> 1601   2068    3M  CC03 2014 2014-05-05       TURB  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3M  CC03 2014 2014-07-07      DOSAT  1.8562979904     + #> 1616   2068    3M  CC03 2014 2014-07-07       NO23 -5.5214609179     I #> 1617   2068    3M  CC03 2014 2014-07-07      SALIN  3.5438536821  <NA> #> 1618   2068    3M  CC03 2014 2014-07-07        TKN -0.2357223335  <NA> #> 1619   2068    3M  CC03 2014 2014-07-07         TN -0.2306718177     + #> 1620   2068    3M  CC03 2014 2014-07-07         TP -3.1235656451  <NA> #> 1621   2068    3M  CC03 2014 2014-07-07       TURB  1.8082887712  <NA> #> 1622   2068    3M  CC03 2014 2014-08-04      CHLAC  1.6292405397  <NA> #> 1623   2068    3M  CC03 2014 2014-08-04      COLOR  3.6375861597  <NA> #> 1624   2068    3M  CC03 2014 2014-08-04         DO -0.3566749439  <NA> #> 1625   2068    3M  CC03 2014 2014-08-04      DOSAT  2.3887627892     + #> 1626   2068    3M  CC03 2014 2014-08-04       NO23 -5.5214609179     I #> 1627   2068    3M  CC03 2014 2014-08-04      SALIN  3.4242626546  <NA> #> 1628   2068    3M  CC03 2014 2014-08-04        TKN 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3M  CC03 2014 2014-10-06      CHLAC  2.3025850930  <NA> #> 1643   2068    3M  CC03 2014 2014-10-06      COLOR  4.1588830834  <NA> #> 1644   2068    3M  CC03 2014 2014-10-06         DO  0.6931471806  <NA> #> 1645   2068    3M  CC03 2014 2014-10-06      DOSAT  3.2464909919     + #> 1646   2068    3M  CC03 2014 2014-10-06       NO23 -4.7105307016     I #> 1647   2068    3M  CC03 2014 2014-10-06      SALIN  2.7080502011  <NA> #> 1648   2068    3M  CC03 2014 2014-10-06        TKN -0.1165338163  <NA> #> 1649   2068    3M  CC03 2014 2014-10-06         TN -0.1120495038     + #> 1650   2068    3M  CC03 2014 2014-10-06         TP -1.9661128564  <NA> #> 1651   2068    3M  CC03 2014 2014-10-06       TURB  1.1631508098  <NA> #> 1652   2068    3M  CC03 2014 2014-11-03      CHLAC  2.3978952728  <NA> #> 1653   2068    3M  CC03 2014 2014-11-03      COLOR  3.5835189385  <NA> #> 1654   2068    3M  CC03 2014 2014-11-03         DO  1.3862943611  <NA> #> 1655   2068    3M  CC03 2014 2014-11-03      DOSAT  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3M  CC03 2015 2015-01-05         TN -0.0387408283     + #> 1670   2068    3M  CC03 2015 2015-01-05         TP -2.5383074265  <NA> #> 1671   2068    3M  CC03 2015 2015-01-05       TURB  0.6418538862  <NA> #> 1672   2068    3M  CC03 2015 2015-02-02      CHLAC  0.6418538862  <NA> #> 1673   2068    3M  CC03 2015 2015-02-02      COLOR  2.3025850930  <NA> #> 1674   2068    3M  CC03 2015 2015-02-02         DO  1.4109869737  <NA> #> 1675   2068    3M  CC03 2015 2015-02-02      DOSAT  3.9778107460     + #> 1676   2068    3M  CC03 2015 2015-02-02       NO23 -5.1159958098     I #> 1677   2068    3M  CC03 2015 2015-02-02      SALIN  3.3911470458  <NA> #> 1678   2068    3M  CC03 2015 2015-02-02        TKN -0.7765287895  <NA> #> 1679   2068    3M  CC03 2015 2015-02-02         TN -0.7678707268     + #> 1680   2068    3M  CC03 2015 2015-02-02         TP -2.9957322736  <NA> #> 1681   2068    3M  CC03 2015 2015-02-02       TURB  0.3364722366  <NA> #> 1682   2068    3M  CC03 2015 2015-03-02      CHLAC  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3M  CC03 2015 2015-04-06       NO23 -5.5214609179     U #> 1697   2068    3M  CC03 2015 2015-04-06      SALIN  3.4011973817  <NA> #> 1698   2068    3M  CC03 2015 2015-04-06        TKN -0.3566749439  <NA> #> 1699   2068    3M  CC03 2015 2015-04-06         TN -0.3538218750     + #> 1700   2068    3M  CC03 2015 2015-04-06         TP -3.2188758249  <NA> #> 1701   2068    3M  CC03 2015 2015-04-06       TURB  0.4700036292  <NA> #> 1702   2068    3M  CC03 2015 2015-05-04      CHLAC  0.9932517730  <NA> #> 1703   2068    3M  CC03 2015 2015-05-04      COLOR  3.2188758249  <NA> #> 1704   2068    3M  CC03 2015 2015-05-04         DO  0.1823215568  <NA> #> 1705   2068    3M  CC03 2015 2015-05-04      DOSAT  2.8622008809     + #> 1706   2068    3M  CC03 2015 2015-05-04       NO23 -4.8283137373     I #> 1707   2068    3M  CC03 2015 2015-05-04      SALIN  3.4904285154  <NA> #> 1708   2068    3M  CC03 2015 2015-05-04        TKN -0.3856624808  <NA> #> 1709   2068    3M  CC03 2015 2015-05-04         TN 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3M  CC03 2015 2015-08-03      COLOR  4.1108738642  <NA> #> 1724   2068    3M  CC03 2015 2015-08-03         DO -0.6931471806  <NA> #> 1725   2068    3M  CC03 2015 2015-08-03      DOSAT  1.9021075264     + #> 1726   2068    3M  CC03 2015 2015-08-03       NO23 -4.6051701860     I #> 1727   2068    3M  CC03 2015 2015-08-03      SALIN  2.3887627892  <NA> #> 1728   2068    3M  CC03 2015 2015-08-03        TKN  0.3364722366  <NA> #> 1729   2068    3M  CC03 2015 2015-08-03         TN  0.3393253056     + #> 1730   2068    3M  CC03 2015 2015-08-03         TP -2.4418471603  <NA> #> 1731   2068    3M  CC03 2015 2015-08-03       TURB  1.5892352051  <NA> #> 1732   2068    3M  CC03 2015 2015-09-08      CHLAC  1.7227665977  <NA> #> 1733   2068    3M  CC03 2015 2015-09-08      COLOR  3.8286413965  <NA> #> 1734   2068    3M  CC03 2015 2015-09-08         DO  0.0000000000  <NA> #> 1735   2068    3M  CC03 2015 2015-09-08      DOSAT  2.6602595373     + #> 1736   2068    3M  CC03 2015 2015-09-08       NO23 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3M  CC03 2015 2015-10-05         TP -3.0576076773  <NA> #> 1751   2068    3M  CC03 2015 2015-10-05       TURB  0.8754687374  <NA> #> 1752   2068    3M  CC03 2015 2015-12-07      CHLAC  1.3609765531  <NA> #> 1753   2068    3M  CC03 2015 2015-12-07      COLOR  3.2188758249  <NA> #> 1754   2068    3M  CC03 2015 2015-12-07         DO  1.1314021115  <NA> #> 1755   2068    3M  CC03 2015 2015-12-07      DOSAT  3.7447870861     + #> 1756   2068    3M  CC03 2015 2015-12-07       NO23 -4.5098600062  <NA> #> 1757   2068    3M  CC03 2015 2015-12-07      SALIN  3.4144426084  <NA> #> 1758   2068    3M  CC03 2015 2015-12-07        TKN -0.4462871026  <NA> #> 1759   2068    3M  CC03 2015 2015-12-07         TN -0.4292456368     + #> 1760   2068    3M  CC03 2015 2015-12-07         TP -2.8473122684  <NA> #> 1761   2068    3M  CC03 2015 2015-12-07       TURB  1.1939224685  <NA> #> 1762   2068    3M  CC03 2016 2016-01-04      CHLAC  1.3083328197  <NA> #> 1763   2068    3M  CC03 2016 2016-01-04      COLOR  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3M  CC03 2016 2016-02-01        TKN -0.2357223335  <NA> #> 1778   2068    3M  CC03 2016 2016-02-01         TN -0.1543173604     + #> 1779   2068    3M  CC03 2016 2016-02-01         TP -2.0402208285  <NA> #> 1780   2068    3M  CC03 2016 2016-02-01       TURB  0.6418538862  <NA> #> 1781   2068    3M  CC03 2016 2016-03-07      CHLAC  1.7227665977  <NA> #> 1782   2068    3M  CC03 2016 2016-03-07      COLOR  3.5835189385  <NA> #> 1783   2068    3M  CC03 2016 2016-03-07         DO  0.8329091229  <NA> #> 1784   2068    3M  CC03 2016 2016-03-07      DOSAT  3.2995337279     + #> 1785   2068    3M  CC03 2016 2016-03-07       NO23 -4.7105307016     I #> 1786   2068    3M  CC03 2016 2016-03-07      SALIN  2.7080502011  <NA> #> 1787   2068    3M  CC03 2016 2016-03-07        TKN -0.3011050928  <NA> #> 1788   2068    3M  CC03 2016 2016-03-07         TN -0.2957142441     + #> 1789   2068    3M  CC03 2016 2016-03-07         TP -2.3025850930  <NA> #> 1790   2068    3M  CC03 2016 2016-03-07       TURB  1.1631508098     A #> 1791   2068    3M  CC03 2016 2016-04-04      CHLAC  0.9932517730  <NA> #> 1792   2068    3M  CC03 2016 2016-04-04      COLOR  3.5263605246  <NA> #> 1793   2068    3M  CC03 2016 2016-04-04         DO  0.9555114450  <NA> #> 1794   2068    3M  CC03 2016 2016-04-04      DOSAT  3.5263605246     + #> 1795   2068    3M  CC03 2016 2016-04-04       NO23 -4.5098600062  <NA> #> 1796   2068    3M  CC03 2016 2016-04-04      SALIN  3.0007198151  <NA> #> 1797   2068    3M  CC03 2016 2016-04-04        TKN -0.3566749439  <NA> #> 1798   2068    3M  CC03 2016 2016-04-04         TN -0.3410828492     + #> 1799   2068    3M  CC03 2016 2016-04-04         TP -2.3859667019  <NA> #> 1800   2068    3M  CC03 2016 2016-04-04       TURB  1.0296194172  <NA> #> 1801   2068    3M  CC03 2016 2016-05-02      CHLAC  0.3364722366     I #> 1802   2068    3M  CC03 2016 2016-05-02      COLOR  3.2580965380  <NA> #> 1803   2068    3M  CC03 2016 2016-05-02         DO  0.7884573604  <NA> #> 1804   2068    3M  CC03 2016 2016-05-02      DOSAT  3.5234150144     + #> 1805   2068    3M  CC03 2016 2016-05-02       NO23 -5.5214609179     U #> 1806   2068    3M  CC03 2016 2016-05-02      SALIN  3.6270040504  <NA> #> 1807   2068    3M  CC03 2016 2016-05-02        TKN -0.3566749439  <NA> #> 1808   2068    3M  CC03 2016 2016-05-02         TN -0.3538218750     + #> 1809   2068    3M  CC03 2016 2016-05-02         TP -2.5639498571  <NA> #> 1810   2068    3M  CC03 2016 2016-05-02       TURB  0.0953101798  <NA> #> 1811   2068    3M  CC03 2017 2017-08-07      CHLAC  2.3978952728  <NA> #> 1812   2068    3M  CC03 2017 2017-08-07      COLOR  4.2195077052  <NA> #> 1813   2068    3M  CC03 2017 2017-08-07      DOSAT  2.3513752572     + #> 1814   2068    3M  CC03 2017 2017-08-07       NO23 -5.5214609179     U #> 1815   2068    3M  CC03 2017 2017-08-07      SALIN  1.4350845253  <NA> #> 1816   2068    3M  CC03 2017 2017-08-07        TKN  0.5306282511  <NA> #> 1817   2068    3M  CC03 2017 2017-08-07         TN  0.5318040302     + #> 1818   2068    3M  CC03 2017 2017-08-07         TP -2.7030626596  <NA> #> 1819   2068    3M  CC03 2017 2017-08-07       TURB  0.9162907319  <NA> #> 1820   2068    3M  CC03 2017 2017-09-05      CHLAC  2.7080502011  <NA> #> 1821   2068    3M  CC03 2017 2017-09-05      COLOR  5.0106352941  <NA> #> 1822   2068    3M  CC03 2017 2017-09-05         DO  0.6931471806  <NA> #> 1823   2068    3M  CC03 2017 2017-09-05      DOSAT  3.2884018875     + #> 1824   2068    3M  CC03 2017 2017-09-05       NO23 -4.4228486292  <NA> #> 1825   2068    3M  CC03 2017 2017-09-05      SALIN  2.2721258855  <NA> #> 1826   2068    3M  CC03 2017 2017-09-05        TKN  0.1823215568  <NA> #> 1827   2068    3M  CC03 2017 2017-09-05         TN  0.1922718876     + #> 1828   2068    3M  CC03 2017 2017-09-05         TP -1.7719568419  <NA> #> 1829   2068    3M  CC03 2017 2017-09-05       TURB  1.3350010667  <NA> #> 1830   2068    3M  CC03 2017 2017-10-02      CHLAC  2.5649493575  <NA> #> 1831   2068    3M  CC03 2017 2017-10-02      COLOR  4.0943445622     A #> 1832   2068    3M  CC03 2017 2017-10-02       NO23 -5.5214609179     U #> 1833   2068    3M  CC03 2017 2017-10-02        TKN -0.0725706928  <NA> #> 1834   2068    3M  CC03 2017 2017-10-02         TN -0.0704224643     + #> 1835   2068    3M  CC03 2017 2017-10-02         TP -2.3025850930  <NA> #> 1836   2068    3M  CC03 2017 2017-10-02       TURB  1.8870696490  <NA> #> 1837   2068    3M  CC03 2017 2017-11-06      CHLAC  1.1631508098  <NA> #> 1838   2068    3M  CC03 2017 2017-11-06      COLOR  3.5835189385  <NA> #> 1839   2068    3M  CC03 2017 2017-11-06         DO  1.3083328197  <NA> #> 1840   2068    3M  CC03 2017 2017-11-06      DOSAT  3.9080149840     + #> 1841   2068    3M  CC03 2017 2017-11-06       NO23 -5.2983173665     I #> 1842   2068    3M  CC03 2017 2017-11-06      SALIN  3.1354942159  <NA> #> 1843   2068    3M  CC03 2017 2017-11-06        TKN -0.2744368457  <NA> #> 1844   2068    3M  CC03 2017 2017-11-06         TN -0.2691874898     + #> 1845   2068    3M  CC03 2017 2017-11-06         TP -2.4418471603  <NA> #> 1846   2068    3M  CC03 2017 2017-11-06       TURB  1.2237754316  <NA> #> 1847   2068    3M  CC03 2018 2018-01-02      CHLAC  1.0647107370  <NA> #> 1848   2068    3M  CC03 2018 2018-01-02      COLOR  3.0445224377  <NA> #> 1849   2068    3M  CC03 2018 2018-01-02       NO23 -4.9618451299     I #> 1850   2068    3M  CC03 2018 2018-01-02      SALIN  3.4563166809  <NA> #> 1851   2068    3M  CC03 2018 2018-01-02        TKN -0.4780358009  <NA> #> 1852   2068    3M  CC03 2018 2018-01-02         TN -0.4716049106     + #> 1853   2068    3M  CC03 2018 2018-01-02         TP -2.4079456087  <NA> #> 1854   2068    3M  CC03 2018 2018-01-02       TURB  1.1314021115  <NA> #> 1855   2068    3M  CC03 2018 2018-02-05      CHLAC  0.9932517730     A #> 1856   2068    3M  CC03 2018 2018-02-05      COLOR  3.2188758249  <NA> #> 1857   2068    3M  CC03 2018 2018-02-05         DO  1.3609765531  <NA> #> 1858   2068    3M  CC03 2018 2018-02-05      DOSAT  3.8979240810     + #> 1859   2068    3M  CC03 2018 2018-02-05       NO23 -4.3428059215  <NA> #> 1860   2068    3M  CC03 2018 2018-02-05      SALIN  3.0587070727  <NA> #> 1861   2068    3M  CC03 2018 2018-02-05        TKN -0.4780358009  <NA> #> 1862   2068    3M  CC03 2018 2018-02-05         TN -0.4572848568     + #> 1863   2068    3M  CC03 2018 2018-02-05         TP -2.6310891600  <NA> #> 1864   2068    3M  CC03 2018 2018-02-05       TURB  0.8754687374  <NA> #> 1865   2068    3M  CC03 2018 2018-03-05      CHLAC  0.6418538862  <NA> #> 1866   2068    3M  CC03 2018 2018-03-05      COLOR  2.5649493575  <NA> #> 1867   2068    3M  CC03 2018 2018-03-05         DO  1.5686159179  <NA> #> 1868   2068    3M  CC03 2018 2018-03-05      DOSAT  4.0517849478     + #> 1869   2068    3M  CC03 2018 2018-03-05       NO23 -5.2983173665     I #> 1870   2068    3M  CC03 2018 2018-03-05      SALIN  3.4781584228  <NA> #> 1871   2068    3M  CC03 2018 2018-03-05        TKN -0.5798184953  <NA> #> 1872   2068    3M  CC03 2018 2018-03-05         TN -0.5727010275     + #> 1873   2068    3M  CC03 2018 2018-03-05         TP -2.7488721956  <NA> #> 1874   2068    3M  CC03 2018 2018-03-05       TURB  2.2407096893  <NA> #> 1875   2068    3M  CC03 2018 2018-04-02      CHLAC -0.5978370008     U #> 1876   2068    3M  CC03 2018 2018-04-02      COLOR  0.9162907319     U #> 1877   2068    3M  CC03 2018 2018-04-02         DO  1.2237754316  <NA> #> 1878   2068    3M  CC03 2018 2018-04-02      DOSAT  3.8877303129     + #> 1879   2068    3M  CC03 2018 2018-04-02       NO23 -3.7297014486  <NA> #> 1880   2068    3M  CC03 2018 2018-04-02      SALIN  3.5553480615  <NA> #> 1881   2068    3M  CC03 2018 2018-04-02        TKN  1.0296194172  <NA> #> 1882   2068    3M  CC03 2018 2018-04-02         TN  1.0381543196     + #> 1883   2068    3M  CC03 2018 2018-04-02         TP -1.7719568419  <NA> #> 1884   2068    3M  CC03 2018 2018-04-02       TURB  1.3862943611  <NA> #> 1885   2068    3M  CC03 2018 2018-05-07      CHLAC  0.4054651081     I #> 1886   2068    3M  CC03 2018 2018-05-07      COLOR  2.6390573296  <NA> #> 1887   2068    3M  CC03 2018 2018-05-07         DO -0.1984509387  <NA> #> 1888   2068    3M  CC03 2018 2018-05-07      DOSAT  2.5416019935  <NA> #> 1889   2068    3M  CC03 2018 2018-05-07       NO23 -5.5214609179     U #> 1890   2068    3M  CC03 2018 2018-05-07      SALIN  3.6109179126  <NA> #> 1891   2068    3M  CC03 2018 2018-05-07        TKN -0.6161861394  <NA> #> 1892   2068    3M  CC03 2018 2018-05-07         TN -0.6124892775     + #> 1893   2068    3M  CC03 2018 2018-05-07         TP -2.8824035882  <NA> #> 1894   2068    3M  CC03 2018 2018-05-07       TURB  0.8754687374  <NA> #> 1895   2068    3M  CC03 2018 2018-08-06      CHLAC  1.5475625087  <NA> #> 1896   2068    3M  CC03 2018 2018-08-06      COLOR  3.8918202981  <NA> #> 1897   2068    3M  CC03 2018 2018-08-06         DO -0.9162907319  <NA> #> 1898   2068    3M  CC03 2018 2018-08-06      DOSAT  1.8245492921  <NA> #> 1899   2068    3M  CC03 2018 2018-08-06       NO23 -5.5214609179     I #> 1900   2068    3M  CC03 2018 2018-08-06      SALIN  3.3332753652  <NA> #> 1901   2068    3M  CC03 2018 2018-08-06        TKN  0.2623642645  <NA> #> 1902   2068    3M  CC03 2018 2018-08-06         TN  0.2654364635     + #> 1903   2068    3M  CC03 2018 2018-08-06         TP -2.4191189092  <NA> #> 1904   2068    3M  CC03 2018 2018-08-06       TURB  1.6486586256  <NA> #> 1905   2068    3M  CC03 2019 2019-03-04      CHLAC  0.2623642645     I #> 1906   2068    3M  CC03 2019 2019-03-04      COLOR  3.6635616461  <NA> #> 1907   2068    3M  CC03 2019 2019-03-04         DO  1.0919233005  <NA> #> 1908   2068    3M  CC03 2019 2019-03-04      DOSAT  3.6506582413  <NA> #> 1909   2068    3M  CC03 2019 2019-03-04       NO23 -5.5214609179     U #> 1910   2068    3M  CC03 2019 2019-03-04      SALIN  2.3105532626  <NA> #> 1911   2068    3M  CC03 2019 2019-03-04        TKN -0.3147107448  <NA> #> 1912   2068    3M  CC03 2019 2019-03-04         TN -0.3119747650     + #> 1913   2068    3M  CC03 2019 2019-03-04         TP -2.3025850930  <NA> #> 1914   2068    3M  CC03 2019 2019-03-04       TURB  0.8754687374  <NA> #> 1915   2068    3M  CC03 2019 2019-05-06      CHLAC  1.3862943611  <NA> #> 1916   2068    3M  CC03 2019 2019-05-06      COLOR  3.4965075615  <NA> #> 1917   2068    3M  CC03 2019 2019-05-06         DO -1.8325814637  <NA> #> 1918   2068    3M  CC03 2019 2019-05-06      DOSAT  0.9932517730  <NA> #> 1919   2068    3M  CC03 2019 2019-05-06       NO23 -5.5214609179     U #> 1920   2068    3M  CC03 2019 2019-05-06      SALIN  3.3809946743  <NA> #> 1921   2068    3M  CC03 2019 2019-05-06        TKN -0.3566749439  <NA> #> 1922   2068    3M  CC03 2019 2019-05-06         TN -0.3538218750     + #> 1923   2068    3M  CC03 2019 2019-05-06         TP -3.0159349809  <NA> #> 1924   2068    3M  CC03 2019 2019-05-06       TURB  0.6418538862  <NA> #> 1925   2068    3M  CC03 2019 2019-06-03      CHLAC  1.0986122887  <NA> #> 1926   2068    3M  CC03 2019 2019-06-03      COLOR  2.9957322736  <NA> #> 1927   2068    3M  CC03 2019 2019-06-03         DO -0.8675005677  <NA> #> 1928   2068    3M  CC03 2019 2019-06-03      DOSAT  1.8870696490  <NA> #> 1929   2068    3M  CC03 2019 2019-06-03       NO23 -5.5214609179     U #> 1930   2068    3M  CC03 2019 2019-06-03      SALIN  3.6068556186  <NA> #> 1931   2068    3M  CC03 2019 2019-06-03        TKN -0.3424903089  <NA> #> 1932   2068    3M  CC03 2019 2019-06-03         TN -0.3396773676     + #> 1933   2068    3M  CC03 2019 2019-06-03         TP -3.0791138825  <NA> #> 1934   2068    3M  CC03 2019 2019-06-03       TURB  0.9555114450  <NA> #> 1935   2068    3M  CC03 2019 2019-07-01      CHLAC  1.9740810260  <NA> #> 1936   2068    3M  CC03 2019 2019-07-01      COLOR  3.2958368660     A #> 1937   2068    3M  CC03 2019 2019-07-01         DO -0.5978370008  <NA> #> 1938   2068    3M  CC03 2019 2019-07-01      DOSAT  2.1517622033  <NA> #> 1939   2068    3M  CC03 2019 2019-07-01       NO23 -5.5214609179     U #> 1940   2068    3M  CC03 2019 2019-07-01      SALIN  3.5160130561  <NA> #> 1941   2068    3M  CC03 2019 2019-07-01        TKN -0.2613647641  <NA> #> 1942   2068    3M  CC03 2019 2019-07-01         TN -0.2587707290     + #> 1943   2068    3M  CC03 2019 2019-07-01         TP -3.0159349809  <NA> #> 1944   2068    3M  CC03 2019 2019-07-01       TURB  1.6486586256     A #> 1945   2068    3M  CC03 2019 2019-10-07         TN -0.6462635947     + #> 1946   2068    3M  CC03 2019 2019-10-07      CHLAC  1.0647107370     I #> 1947   2068    3M  CC03 2019 2019-10-07      COLOR  1.9169226122  <NA> #> 1948   2068    3M  CC03 2019 2019-10-07         DO  0.6931471806  <NA> #> 1949   2068    3M  CC03 2019 2019-10-07      DOSAT  3.4436180975  <NA> #> 1950   2068    3M  CC03 2019 2019-10-07       NO23 -5.1159958098     I #> 1951   2068    3M  CC03 2019 2019-10-07      SALIN  3.5392186796  <NA> #> 1952   2068    3M  CC03 2019 2019-10-07        TKN -0.6539264674  <NA> #> 1953   2068    3M  CC03 2019 2019-10-07         TP -2.5902671654  <NA> #> 1954   2068    3M  CC03 2019 2019-10-07       TURB  0.7884573604  <NA> #> 1955   2068    3M  CC03 2019 2019-11-04      CHLAC  1.7227665977  <NA> #> 1956   2068    3M  CC03 2019 2019-11-04      COLOR  2.8903717579  <NA> #> 1957   2068    3M  CC03 2019 2019-11-04         DO  0.3646431136  <NA> #> 1958   2068    3M  CC03 2019 2019-11-04      DOSAT  3.0349529867  <NA> #> 1959   2068    3M  CC03 2019 2019-11-04       NO23 -4.3428059215  <NA> #> 1960   2068    3M  CC03 2019 2019-11-04      SALIN  3.6030491975  <NA> #> 1961   2068    3M  CC03 2019 2019-11-04        TKN -0.3566749439  <NA> #> 1962   2068    3M  CC03 2019 2019-11-04         TN -0.3382738586     + #> 1963   2068    3M  CC03 2019 2019-11-04         TP -2.7488721956  <NA> #> 1964   2068    3M  CC03 2019 2019-11-04       TURB  1.1631508098  <NA> #> 1965   2068    3M  CC03 2019 2019-12-02      CHLAC  0.8754687374     I #> 1966   2068    3M  CC03 2019 2019-12-02      COLOR  2.1860512767  <NA> #> 1967   2068    3M  CC03 2019 2019-12-02         DO  1.0367368850  <NA> #> 1968   2068    3M  CC03 2019 2019-12-02      DOSAT  3.6988297850  <NA> #> 1969   2068    3M  CC03 2019 2019-12-02       NO23 -4.1997050779  <NA> #> 1970   2068    3M  CC03 2019 2019-12-02      SALIN  3.4977189487  <NA> #> 1971   2068    3M  CC03 2019 2019-12-02        TKN -0.4620354596  <NA> #> 1972   2068    3M  CC03 2019 2019-12-02         TN -0.4385049622     + #> 1973   2068    3M  CC03 2019 2019-12-02         TP -2.9187712324  <NA> #> 1974   2068    3M  CC03 2019 2019-12-02       TURB  0.6418538862  <NA> #> 1975   2068    3M  CC03 2020 2020-01-06      CHLAC  1.2237754316  <NA> #> 1976   2068    3M  CC03 2020 2020-01-06      COLOR  3.5263605246     A #> 1977   2068    3M  CC03 2020 2020-01-06         DO  1.1184149160  <NA> #> 1978   2068    3M  CC03 2020 2020-01-06      DOSAT  3.5862928653  <NA> #> 1979   2068    3M  CC03 2020 2020-01-06       NO23 -4.1997050779  <NA> #> 1980   2068    3M  CC03 2020 2020-01-06      SALIN  2.7491921444  <NA> #> 1981   2068    3M  CC03 2020 2020-01-06        TKN  0.0953101798  <NA> #> 1982   2068    3M  CC03 2020 2020-01-06         TN  0.1088544049     + #> 1983   2068    3M  CC03 2020 2020-01-06         TP -2.5510464523  <NA> #> 1984   2068    3M  CC03 2020 2020-01-06       TURB  1.4350845253  <NA> #> 1985   2068    3M  CC03 2020 2020-02-03      CHLAC  0.5877866649     I #> 1986   2068    3M  CC03 2020 2020-02-03      COLOR  3.3672958300  <NA> #> 1987   2068    3M  CC03 2020 2020-02-03         DO  1.4011829736  <NA> #> 1988   2068    3M  CC03 2020 2020-02-03      DOSAT  3.7909846771  <NA> #> 1989   2068    3M  CC03 2020 2020-02-03       NO23 -4.9618451299     I #> 1990   2068    3M  CC03 2020 2020-02-03      SALIN  3.0819099698  <NA> #> 1991   2068    3M  CC03 2020 2020-02-03        TKN -0.2107210313  <NA> #> 1992   2068    3M  CC03 2020 2020-02-03         TN -0.2057949130     + #> 1993   2068    3M  CC03 2020 2020-02-03         TP -2.7968814148  <NA> #> 1994   2068    3M  CC03 2020 2020-02-03       TURB  0.5877866649  <NA> #> 1995   2068    3M  CC03 2020 2020-03-02      CHLAC  0.6931471806     I #> 1996   2068    3M  CC03 2020 2020-03-02      COLOR  2.6390573296  <NA> #> 1997   2068    3M  CC03 2020 2020-03-02         DO  1.4951487660  <NA> #> 1998   2068    3M  CC03 2020 2020-03-02      DOSAT  4.0360089852  <NA> #> 1999   2068    3M  CC03 2020 2020-03-02       NO23 -5.2983173665     I #> 2000   2068    3M  CC03 2020 2020-03-02      SALIN  3.4600950229  <NA> #> 2001   2068    3M  CC03 2020 2020-03-02        TKN -0.5108256238  <NA> #> 2002   2068    3M  CC03 2020 2020-03-02         TN -0.5041810810     + #> 2003   2068    3M  CC03 2020 2020-03-02         TP -2.6450754019  <NA> #> 2004   2068    3M  CC03 2020 2020-03-02       TURB  1.5040773968  <NA> #> 2005   2068    3M  CC03 2020 2020-09-08      CHLAC  2.7725887222  <NA> #> 2006   2068    3M  CC03 2020 2020-09-08      COLOR  4.8675344505  <NA> #> 2007   2068    3M  CC03 2020 2020-09-08         DO  0.4510756194  <NA> #> 2008   2068    3M  CC03 2020 2020-09-08      DOSAT  3.0155349009  <NA> #> 2009   2068    3M  CC03 2020 2020-09-08       NO23 -5.5214609179     U #> 2010   2068    3M  CC03 2020 2020-09-08      SALIN  1.5151272330  <NA> #> 2011   2068    3M  CC03 2020 2020-09-08        TKN  0.0953101798  <NA> #> 2012   2068    3M  CC03 2020 2020-09-08         TN  0.0971267107     + #> 2013   2068    3M  CC03 2020 2020-09-08         TP -2.2072749132  <NA> #> 2014   2068    3M  CC03 2020 2020-09-08       TURB  1.3862943611  <NA> #> 2015   2068    3M  CC03 2020 2020-10-05      CHLAC  2.0918640617  <NA> #> 2016   2068    3M  CC03 2020 2020-10-05      COLOR  4.2046926194  <NA> #> 2017   2068    3M  CC03 2020 2020-10-05         DO  0.4121096508  <NA> #> 2018   2068    3M  CC03 2020 2020-10-05      DOSAT  3.0587070727  <NA> #> 2019   2068    3M  CC03 2020 2020-10-05       NO23 -4.7105307016     I #> 2020   2068    3M  CC03 2020 2020-10-05      SALIN  3.2027464429  <NA> #> 2021   2068    3M  CC03 2020 2020-10-05        TKN -0.3147107448  <NA> #> 2022   2068    3M  CC03 2020 2020-10-05         TN -0.3092462504     + #> 2023   2068    3M  CC03 2020 2020-10-05         TP -2.5133061243  <NA> #> 2024   2068    3M  CC03 2020 2020-10-05       TURB  1.3350010667  <NA> #> 2025   2068    3M  CC03 2020 2020-11-02      CHLAC  1.4816045409  <NA> #> 2026   2068    3M  CC03 2020 2020-11-02      COLOR  3.6888794541  <NA> #> 2027   2068    3M  CC03 2020 2020-11-02         DO  0.6523251860  <NA> #> 2028   2068    3M  CC03 2020 2020-11-02      DOSAT  3.3428618046  <NA> #> 2029   2068    3M  CC03 2020 2020-11-02       NO23 -4.7105307016     I #> 2030   2068    3M  CC03 2020 2020-11-02      SALIN  3.3721118008  <NA> #> 2031   2068    3M  CC03 2020 2020-11-02        TKN -0.1984509387  <NA> #> 2032   2068    3M  CC03 2020 2020-11-02         TN -0.1935847491     + #> 2033   2068    3M  CC03 2020 2020-11-02         TP 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3M  CC03 2021 2021-01-04         DO  0.7701082217  <NA> #> 2048   2068    3M  CC03 2021 2021-01-04      DOSAT  3.3393219779  <NA> #> 2049   2068    3M  CC03 2021 2021-01-04       NO23 -4.3428059215  <NA> #> 2050   2068    3M  CC03 2021 2021-01-04      SALIN  3.2638491905  <NA> #> 2051   2068    3M  CC03 2021 2021-01-04        TKN -0.4780358009  <NA> #> 2052   2068    3M  CC03 2021 2021-01-04         TN -0.4572848568     + #> 2053   2068    3M  CC03 2021 2021-01-04         TP -2.3025850930  <NA> #> 2054   2068    3M  CC03 2021 2021-01-04       TURB  0.8329091229  <NA> #> 2055   2068    3M  CC03 2021 2021-02-01      CHLAC  0.3364722366     I #> 2056   2068    3M  CC03 2021 2021-02-01      COLOR  1.9878743482  <NA> #> 2057   2068    3M  CC03 2021 2021-02-01         DO  1.3454723666  <NA> #> 2058   2068    3M  CC03 2021 2021-02-01      DOSAT  3.9156165409  <NA> #> 2059   2068    3M  CC03 2021 2021-02-01       NO23 -4.4228486292  <NA> #> 2060   2068    3M  CC03 2021 2021-02-01      SALIN  3.4937765630  <NA> #> 2061   2068    3M  CC03 2021 2021-02-01        TKN -0.7133498879  <NA> #> 2062   2068    3M  CC03 2021 2021-02-01         TN -0.6891551593     + #> 2063   2068    3M  CC03 2021 2021-02-01         TP -2.7646205526  <NA> #> 2064   2068    3M  CC03 2021 2021-02-01       TURB  1.0647107370  <NA> #> 2065   2068    3M  CC03 2021 2021-04-05      CHLAC  0.5877866649     I #> 2066   2068    3M  CC03 2021 2021-04-05      COLOR  2.5649493575  <NA> #> 2067   2068    3M  CC03 2021 2021-04-05         DO  0.9932517730  <NA> #> 2068   2068    3M  CC03 2021 2021-04-05      DOSAT  3.6323091026  <NA> #> 2069   2068    3M  CC03 2021 2021-04-05       NO23 -5.5214609179     U #> 2070   2068    3M  CC03 2021 2021-04-05      SALIN  3.5984075509  <NA> #> 2071   2068    3M  CC03 2021 2021-04-05        TKN -0.6348782724  <NA> #> 2072   2068    3M  CC03 2021 2021-04-05         TN -0.6311117896     + #> 2073   2068    3M  CC03 2021 2021-04-05         TP -2.9374633654  <NA> #> 2074   2068    3M  CC03 2021 2021-04-05       TURB  0.9162907319  <NA> #> 2075   2068    3M  CC03 2021 2021-05-03      CHLAC  0.4054651081     I #> 2076   2068    3M  CC03 2021 2021-05-03      COLOR  3.0910424534     A #> 2077   2068    3M  CC03 2021 2021-05-03         DO -0.4307829161  <NA> #> 2078   2068    3M  CC03 2021 2021-05-03      DOSAT  2.3125354238  <NA> #> 2079   2068    3M  CC03 2021 2021-05-03       NO23 -5.5214609179     U #> 2080   2068    3M  CC03 2021 2021-05-03      SALIN  3.5931942040  <NA> #> 2081   2068    3M  CC03 2021 2021-05-03        TKN -0.6348782724  <NA> #> 2082   2068    3M  CC03 2021 2021-05-03         TN -0.6311117896     + #> 2083   2068    3M  CC03 2021 2021-05-03         TP -3.1010927892  <NA> #> 2084   2068    3M  CC03 2021 2021-05-03       TURB  1.6094379124     A #> 2085   2068    3M  CC03 2021 2021-06-07      CHLAC  0.8754687374     I #> 2086   2068    3M  CC03 2021 2021-06-07      COLOR  2.9444389792  <NA> #> 2087   2068    3M  CC03 2021 2021-06-07         DO -0.4462871026  <NA> #> 2088   2068    3M  CC03 2021 2021-06-07      DOSAT  2.3418058061  <NA> #> 2089   2068    3M  CC03 2021 2021-06-07       NO23 -5.5214609179     U #> 2090   2068    3M  CC03 2021 2021-06-07      SALIN  3.6444049640  <NA> #> 2091   2068    3M  CC03 2021 2021-06-07        TKN -0.4462871026  <NA> #> 2092   2068    3M  CC03 2021 2021-06-07         TN -0.4431669753     + #> 2093   2068    3M  CC03 2021 2021-06-07         TP -3.1941832123  <NA> #> 2094   2068    3M  CC03 2021 2021-06-07       TURB  0.8754687374  <NA> #> 2095   2068    3M  CC03 2021 2021-08-02      CHLAC  3.2188758249  <NA> #> 2096   2068    3M  CC03 2021 2021-08-02      COLOR  4.4308167988  <NA> #> 2097   2068    3M  CC03 2021 2021-08-02         DO -0.5108256238  <NA> #> 2098   2068    3M  CC03 2021 2021-08-02      DOSAT -0.9162907319  <NA> #> 2099   2068    3M  CC03 2021 2021-08-02       NO23 -5.5214609179     U #> 2100   2068    3M  CC03 2021 2021-08-02      SALIN  2.5733752978  <NA> #> 2101   2068    3M  CC03 2021 2021-08-02        TKN  0.2623642645  <NA> #> 2102   2068    3M  CC03 2021 2021-08-02         TN  0.2639015438     + #> 2103   2068    3M  CC03 2021 2021-08-02         TP -1.9661128564  <NA> #> 2104   2068    3M  CC03 2021 2021-08-02       TURB  1.3862943611  <NA> #> 2105   2068    3M  CC03 2021 2021-09-07      CHLAC  3.6375861597  <NA> #> 2106   2068    3M  CC03 2021 2021-09-07      COLOR  4.4308167988  <NA> #> 2107   2068    3M  CC03 2021 2021-09-07         DO  1.9473377010  <NA> #> 2108   2068    3M  CC03 2021 2021-09-07      DOSAT  4.5119578043  <NA> #> 2109   2068    3M  CC03 2021 2021-09-07       NO23 -5.5214609179     U #> 2110   2068    3M  CC03 2021 2021-09-07      SALIN -3.2188758249  <NA> #> 2111   2068    3M  CC03 2021 2021-09-07        TKN  0.1823215568  <NA> #> 2112   2068    3M  CC03 2021 2021-09-07         TN  0.1839868361     + #> 2113   2068    3M  CC03 2021 2021-09-07         TP -2.2072749132  <NA> #> 2114   2068    3M  CC03 2021 2021-09-07       TURB  1.7047480922  <NA> #> 2115   2068    3M  CC03 2021 2021-10-04      CHLAC  1.8082887712  <NA> #> 2116   2068    3M  CC03 2021 2021-10-04      COLOR  3.8712010109     A #> 2117   2068    3M  CC03 2021 2021-10-04         DO  0.1043600153  <NA> #> 2118   2068    3M  CC03 2021 2021-10-04      DOSAT  2.7472709143  <NA> #> 2119   2068    3M  CC03 2021 2021-10-04       NO23 -4.9618451299     I #> 2120   2068    3M  CC03 2021 2021-10-04      SALIN  3.1527360224  <NA> #> 2121   2068    3M  CC03 2021 2021-10-04        TKN -0.2484613593  <NA> #> 2122   2068    3M  CC03 2021 2021-10-04         TN -0.2433462586     + #> 2123   2068    3M  CC03 2021 2021-10-04         TP -2.4079456087  <NA> #> 2124   2068    3M  CC03 2021 2021-10-04       TURB  0.7419373447  <NA> #> 2125   2068    3M  CC03 2021 2021-11-01      CHLAC  1.3350010667     I #> 2126   2068    3M  CC03 2021 2021-11-01      COLOR  3.7612001157  <NA> #> 2127   2068    3M  CC03 2021 2021-11-01         DO  0.4824261492  <NA> #> 2128   2068    3M  CC03 2021 2021-11-01      DOSAT  3.0726933147  <NA> #> 2129   2068    3M  CC03 2021 2021-11-01       NO23 -4.6051701860     I #> 2130   2068    3M  CC03 2021 2021-11-01      SALIN  3.1797191097  <NA> #> 2131   2068    3M  CC03 2021 2021-11-01        TKN -0.3856624808  <NA> #> 2132   2068    3M  CC03 2021 2021-11-01         TN -0.3797973614     + #> 2133   2068    3M  CC03 2021 2021-11-01         TP -2.4418471603  <NA> #> 2134   2068    3M  CC03 2021 2021-11-01       TURB  0.4054651081     A #> 2135   2068    3M  CC03 2021 2021-12-06      CHLAC  0.7419373447     I #> 2136   2068    3M  CC03 2021 2021-12-06      COLOR  2.7725887222  <NA> #> 2137   2068    3M  CC03 2021 2021-12-06         DO  1.1249295970  <NA> #> 2138   2068    3M  CC03 2021 2021-12-06      DOSAT  3.7495040759  <NA> #> 2139   2068    3M  CC03 2021 2021-12-06       NO23 -4.4228486292  <NA> #> 2140   2068    3M  CC03 2021 2021-12-06      SALIN  3.3931652100  <NA> #> 2141   2068    3M  CC03 2021 2021-12-06        TKN 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3M  CC03 2022 2022-02-07      CHLAC -0.1165338163     U #> 2156   2068    3M  CC03 2022 2022-02-07      COLOR  2.3978952728     A #> 2157   2068    3M  CC03 2022 2022-02-07         DO  1.4929040962  <NA> #> 2158   2068    3M  CC03 2022 2022-02-07      DOSAT  4.0517849478  <NA> #> 2159   2068    3M  CC03 2022 2022-02-07       NO23 -5.1159958098     I #> 2160   2068    3M  CC03 2022 2022-02-07      SALIN  3.4651107074  <NA> #> 2161   2068    3M  CC03 2022 2022-02-07        TKN -0.8915981193  <NA> #> 2162   2068    3M  CC03 2022 2022-02-07         TN -0.8818893052     + #> 2163   2068    3M  CC03 2022 2022-02-07         TP -2.6736487744  <NA> #> 2164   2068    3M  CC03 2022 2022-02-07       TURB  0.4054651081  <NA> #> 2165   2068    3M  CC03 2022 2022-03-07      CHLAC  0.7419373447     I #> 2166   2068    3M  CC03 2022 2022-03-07      COLOR  2.3025850930     A #> 2167   2068    3M  CC03 2022 2022-03-07         DO  0.5306282511  <NA> #> 2168   2068    3M  CC03 2022 2022-03-07      DOSAT  3.1863526332  <NA> #> 2169   2068    3M  CC03 2022 2022-03-07       NO23 -5.1159958098     I #> 2170   2068    3M  CC03 2022 2022-03-07      SALIN  3.5331024525  <NA> #> 2171   2068    3M  CC03 2022 2022-03-07        TKN -0.4307829161  <NA> #> 2172   2068    3M  CC03 2022 2022-03-07         TN -0.4246479275     + #> 2173   2068    3M  CC03 2022 2022-03-07         TP -2.8647040111  <NA> #> 2174   2068    3M  CC03 2022 2022-03-07       TURB  0.9555114450  <NA> #> 2175   2068    3M  CC03 2022 2022-04-04      CHLAC  0.0000000000     I #> 2176   2068    3M  CC03 2022 2022-04-04      COLOR  2.5649493575  <NA> #> 2177   2068    3M  CC03 2022 2022-04-04         DO -0.2107210313  <NA> #> 2178   2068    3M  CC03 2022 2022-04-04      DOSAT  2.5416019935  <NA> #> 2179   2068    3M  CC03 2022 2022-04-04       NO23 -5.1159958098     I #> 2180   2068    3M  CC03 2022 2022-04-04        TKN -0.6161861394  <NA> #> 2181   2068    3M  CC03 2022 2022-04-04         TN -0.6088060321     + #> 2182   2068    3M  CC03 2022 2022-04-04         TP -2.9957322736  <NA> #> 2183   2068    3M  CC03 2022 2022-04-04       TURB  1.0986122887  <NA> #> 2184   2068    3M  CC03 2022 2022-05-02      CHLAC  0.3364722366     U #> 2185   2068    3M  CC03 2022 2022-05-02         DO -0.5108256238  <NA> #> 2186   2068    3M  CC03 2022 2022-05-02      DOSAT  2.2082744135  <NA> #> 2187   2068    3M  CC03 2022 2022-05-02       NO23 -5.5214609179     U #> 2188   2068    3M  CC03 2022 2022-05-02      SALIN  3.5366020187  <NA> #> 2189   2068    3M  CC03 2022 2022-05-02         TN -0.5762534291     + #> 2190   2068    3M  CC03 2022 2022-06-06      CHLAC  1.7047480922  <NA> #> 2191   2068    3M  CC03 2022 2022-06-06      COLOR  4.0430512678  <NA> #> 2192   2068    3M  CC03 2022 2022-06-06         DO -0.4462871026  <NA> #> 2193   2068    3M  CC03 2022 2022-06-06      DOSAT  2.1972245773  <NA> #> 2194   2068    3M  CC03 2022 2022-06-06       NO23 -4.6051701860     I #> 2195   2068    3M  CC03 2022 2022-06-06      SALIN  2.9210087274  <NA> #> 2196   2068    3M  CC03 2022 2022-06-06        TKN  0.1823215568  <NA> #> 2197   2068    3M  CC03 2022 2022-06-06         TN  0.1856493469     + #> 2198   2068    3M  CC03 2022 2022-06-06         TP -2.9374633654  <NA> #> 2199   2068    3M  CC03 2022 2022-06-06       TURB  1.3609765531  <NA> #> 2200   2068    3M  CC03 2022 2022-07-05      CHLAC  2.0541237337  <NA> #> 2201   2068    3M  CC03 2022 2022-07-05      COLOR  3.8501476017     A #> 2202   2068    3M  CC03 2022 2022-07-05         DO -0.5447271754  <NA> #> 2203   2068    3M  CC03 2022 2022-07-05      DOSAT  2.1860512767  <NA> #> 2204   2068    3M  CC03 2022 2022-07-05       NO23 -3.9120230054  <NA> #> 2205   2068    3M  CC03 2022 2022-07-05      SALIN  3.2327787300  <NA> #> 2206   2068    3M  CC03 2022 2022-07-05        TKN  0.0953101798  <NA> #> 2207   2068    3M  CC03 2022 2022-07-05         TN  0.1133286853     + #> 2208   2068    3M  CC03 2022 2022-07-05         TP -2.6036901858  <NA> #> 2209   2068    3M  CC03 2022 2022-07-05       TURB  2.0149030205  <NA> #> 2210   2068    3M  CC03 2022 2022-08-01      CHLAC  1.8082887712  <NA> #> 2211   2068    3M  CC03 2022 2022-08-01      COLOR  3.5553480615     A #> 2212   2068    3M  CC03 2022 2022-08-01         DO -0.8209805521  <NA> #> 2213   2068    3M  CC03 2022 2022-08-01      DOSAT  1.9315214116  <NA> #> 2214   2068    3M  CC03 2022 2022-08-01       NO23 -5.2983173665     I #> 2215   2068    3M  CC03 2022 2022-08-01      SALIN  3.3904734183  <NA> #> 2216   2068    3M  CC03 2022 2022-08-01        TKN -0.3011050928  <NA> #> 2217   2068    3M  CC03 2022 2022-08-01         TN -0.2957142441     + #> 2218   2068    3M  CC03 2022 2022-08-01         TP -2.9004220937  <NA> #> 2219   2068    3M  CC03 2022 2022-08-01       TURB  1.0296194172  <NA> #> 2220   2068    3M  CC03 2022 2022-11-07      CHLAC  2.7725887222  <NA> #> 2221   2068    3M  CC03 2022 2022-11-07      COLOR  3.9889840466     A #> 2222   2068    3M  CC03 2022 2022-11-07         DO -0.4462871026  <NA> #> 2223   2068    3M  CC03 2022 2022-11-07      DOSAT  2.2192034841  <NA> #> 2224   2068    3M  CC03 2022 2022-11-07       NO23 -5.5214609179     I #> 2225   2068    3M  CC03 2022 2022-11-07      SALIN  3.1945831323  <NA> #> 2226   2068    3M  CC03 2022 2022-11-07        TKN  0.0000000000  <NA> #> 2227   2068    3M  CC03 2022 2022-11-07         TN  0.0039920213     + #> 2228   2068    3M  CC03 2022 2022-11-07         TP -1.5606477483  <NA> #> 2229   2068    3M  CC03 2022 2022-11-07       TURB  2.7725887222  <NA> #> 2230   2068    3M  CC03 2022 2022-12-05      CHLAC  2.7725887222  <NA> #> 2231   2068    3M  CC03 2022 2022-12-05      COLOR  4.0430512678  <NA> #> 2232   2068    3M  CC03 2022 2022-12-05         DO  0.5766133643  <NA> #> 2233   2068    3M  CC03 2022 2022-12-05      DOSAT  3.1863526332  <NA> #> 2234   2068    3M  CC03 2022 2022-12-05       NO23 -5.5214609179     U #> 2235   2068    3M  CC03 2022 2022-12-05      SALIN  3.0223742045  <NA> #> 2236   2068    3M  CC03 2022 2022-12-05        TKN -0.1625189295  <NA> #> 2237   2068    3M  CC03 2022 2022-12-05         TN -0.1601687522     + #> 2238   2068    3M  CC03 2022 2022-12-05         TP -1.1394342832  <NA> #> 2239   2068    3M  CC03 2022 2022-12-05       TURB  1.5040773968  <NA> #> 2240   2068    3M  CC03 2023 2023-01-03      CHLAC  1.6486586256  <NA> #> 2241   2068    3M  CC03 2023 2023-01-03      COLOR  4.0604430105  <NA> #> 2242   2068    3M  CC03 2023 2023-01-03         DO  0.7080357931  <NA> #> 2243   2068    3M  CC03 2023 2023-01-03      DOSAT  3.2884018875  <NA> #> 2244   2068    3M  CC03 2023 2023-01-03       NO23 -4.2686979494  <NA> #> 2245   2068    3M  CC03 2023 2023-01-03        TKN -0.0512932944  <NA> #> 2246   2068    3M  CC03 2023 2023-01-03         TN -0.0366639844     + #> 2247   2068    3M  CC03 2023 2023-01-03         TP -0.7133498879  <NA> #> 2248   2068    3M  CC03 2023 2023-01-03       TURB  0.3364722366  <NA> #> 2249   2068    3M  CC03 2023 2023-02-06      CHLAC  1.6292405397  <NA> #> 2250   2068    3M  CC03 2023 2023-02-06      COLOR  2.7080502011     A #> 2251   2068    3M  CC03 2023 2023-02-06         DO  1.2781522025  <NA> #> 2252   2068    3M  CC03 2023 2023-02-06      DOSAT  3.8958936235  <NA> #> 2253   2068    3M  CC03 2023 2023-02-06       NO23 -4.6051701860     I #> 2254   2068    3M  CC03 2023 2023-02-06      SALIN  3.4404180948  <NA> #> 2255   2068    3M  CC03 2023 2023-02-06        TKN -0.3566749439  <NA> #> 2256   2068    3M  CC03 2023 2023-02-06         TN -0.3509769228     + #> 2257   2068    3M  CC03 2023 2023-02-06         TP -2.2072749132  <NA> #> 2258   2068    3M  CC03 2023 2023-02-06       TURB  1.1314021115  <NA> #> 2259   2068    3M  CC03 2023 2023-03-06         DO  0.1570037488  <NA> #> 2260   2068    3M  CC03 2023 2023-03-06      DOSAT  2.8791984573  <NA> #> 2261   2068    3M  CC03 2023 2023-03-06      SALIN  3.5962157693  <NA> #> 2262   2068    3M  CC03 2018 2018-03-13      CHLAC  0.9555114450  <NA> #> 2263   2068    3M  CC03 2018 2018-03-13       COND 10.8817948782  <NA> #> 2264   2068    3M  CC03 2018 2018-03-13         DO  2.0794415417  <NA> #> 2265   2068    3M  CC03 2018 2018-03-13      DOSAT  4.6812048723  <NA> #> 2266   2068    3M  CC03 2018 2018-03-13       NO23 -4.7105307016     I #> 2267   2068    3M  CC03 2018 2018-03-13      SALIN  3.6778185068     + #> 2268   2068    3M  CC03 2018 2018-03-13        TKN -0.4942963218  <NA> #> 2269   2068    3M  CC03 2018 2018-03-13         TN -0.4877603508     + #> 2270   2068    3M  CC03 2018 2018-03-13         TP -2.4191189092  <NA> #> 2271   2068    3M  CC03 2018 2018-03-13        TSS  1.3862943611     I #> 2272   2068    3M  CC03 2018 2018-03-13       TURB  1.0647107370  <NA> #> 2273   2068    3M  CC03 2018 2018-05-08      CHLAC  1.1631508098  <NA> #> 2274   2068    3M  CC03 2018 2018-05-08       COND 10.9254527508  <NA> #> 2275   2068    3M  CC03 2018 2018-05-08         DO  1.4973884086  <NA> #> 2276   2068    3M  CC03 2018 2018-05-08      DOSAT  4.2091602367  <NA> #> 2277   2068    3M  CC03 2018 2018-05-08       NO23 -5.5214609179     U #> 2278   2068    3M  CC03 2018 2018-05-08      SALIN  3.5973122606     + #> 2279   2068    3M  CC03 2018 2018-05-08        TKN -0.5108256238  <NA> #> 2280   2068    3M  CC03 2018 2018-05-08         TN -0.5074978337     + #> 2281   2068    3M  CC03 2018 2018-05-08         TP -3.2441936329  <NA> #> 2282   2068    3M  CC03 2018 2018-05-08        TSS  2.0794415417     I #> 2283   2068    3M  CC03 2018 2018-05-08       TURB  1.3083328197  <NA> #> 2284   2068    3M  CC03 2018 2018-06-26      CHLAC  2.4849066498  <NA> #> 2285   2068    3M  CC03 2018 2018-06-26       COND 10.7823463704  <NA> #> 2286   2068    3M  CC03 2018 2018-06-26         DO  1.1118575154  <NA> #> 2287   2068    3M  CC03 2018 2018-06-26      DOSAT  3.8628327612  <NA> #> 2288   2068    3M  CC03 2018 2018-06-26       NO23 -5.5214609179     U #> 2289   2068    3M  CC03 2018 2018-06-26      SALIN  3.3414473773     + #> 2290   2068    3M  CC03 2018 2018-06-26        TKN -0.4155154440  <NA> #> 2291   2068    3M  CC03 2018 2018-06-26         TN -0.4124897230     + #> 2292   2068    3M  CC03 2018 2018-06-26        TSS  2.0794415417     I #> 2293   2068    3M  CC03 2018 2018-06-26       TURB  1.4816045409  <NA> #> 2294   2068    3M  CC03 2018 2018-09-18      CHLAC  2.2617630985  <NA> #> 2295   2068    3M  CC03 2018 2018-09-18       COND  9.9966590834  <NA> #> 2296   2068    3M  CC03 2018 2018-09-18         DO  0.8020015855  <NA> #> 2297   2068    3M  CC03 2018 2018-09-18      DOSAT  3.4812400893  <NA> #> 2298   2068    3M  CC03 2018 2018-09-18       NO23 -4.7105307016     I #> 2299   2068    3M  CC03 2018 2018-09-18        TKN -0.0833816089  <NA> #> 2300   2068    3M  CC03 2018 2018-09-18         TN -0.0790432073     + #> 2301   2068    3M  CC03 2018 2018-09-18         TP -2.3227878003  <NA> #> 2302   2068    3M  CC03 2018 2018-09-18        TSS  1.0986122887     U #> 2303   2068    3M  CC03 2018 2018-09-18       TURB  1.2809338455     A #> 2304   2068    3M  CC03 2018 2018-12-04      CHLAC  1.6486586256  <NA> #> 2305   2068    3M  CC03 2018 2018-12-04       COND 10.7489265434  <NA> #> 2306   2068    3M  CC03 2018 2018-12-04         DO  1.5644405465  <NA> #> 2307   2068    3M  CC03 2018 2018-12-04      DOSAT  4.2239097666  <NA> #> 2308   2068    3M  CC03 2018 2018-12-04       NO23 -1.8971199849     G #> 2309   2068    3M  CC03 2018 2018-12-04      SALIN  3.4094961845  <NA> #> 2310   2068    3M  CC03 2018 2018-12-04        TKN -0.3285040670  <NA> #> 2311   2068    3M  CC03 2018 2018-12-04         TN -0.1392620673     + #> 2312   2068    3M  CC03 2018 2018-12-04         TP -2.6450754019  <NA> #> 2313   2068    3M  CC03 2018 2018-12-04        TSS  2.1972245773     I #> 2314   2068    3M  CC03 2018 2018-12-04       TURB  0.5306282511  <NA> #> 2315  2078A     2  CC04 2019 2019-08-13      CHLAC  3.1780538303  <NA> #> 2316  2078A     2  CC04 2019 2019-08-13       COND  9.8642788393  <NA> #> 2317  2078A     2  CC04 2019 2019-08-13         DO  1.7647307968  <NA> #> 2318  2078A     2  CC04 2019 2019-08-13      DOSAT  4.4176350621  <NA> #> 2319  2078A     2  CC04 2019 2019-08-13       NO23 -5.2983173665     I #> 2320  2078A     2  CC04 2019 2019-08-13      SALIN  2.4274540750  <NA> #> 2321  2078A     2  CC04 2019 2019-08-13        TKN  0.3364722366  <NA> #> 2322  2078A     2  CC04 2019 2019-08-13         TN  0.3393253056     + #> 2323  2078A     2  CC04 2019 2019-08-13         TP -2.9759296463  <NA> #> 2324  2078A     2  CC04 2019 2019-08-13        TSS  1.6094379124     I #> 2325  2078A     2  CC04 2019 2019-08-13       TURB  0.7419373447  <NA> #> 2326  2078B     2  CC05 2019 2019-01-17       COND 10.7433722892  <NA> #> 2327  2078B     2  CC05 2019 2019-01-17         DO  1.9065751437  <NA> #> 2328  2078B     2  CC05 2019 2019-01-17      DOSAT  4.4030540019  <NA> #> 2329  2078B     2  CC05 2019 2019-01-17      SALIN  3.4045251718  <NA> #> 2330  2078B     2  CC05 2019 2019-01-17         TN -0.3827256211     + #> 2331  2078B     2  CC05 2019 2019-01-24      CHLAC  0.2623642645     I #> 2332  2078B     2  CC05 2019 2019-01-24       COND 10.7763069502  <NA> #> 2333  2078B     2  CC05 2019 2019-01-24         DO  1.8702625307  <NA> #> 2334  2078B     2  CC05 2019 2019-01-24      DOSAT  4.4531838290  <NA> #> 2335  2078B     2  CC05 2019 2019-01-24       NO23 -5.1159958098     I #> 2336  2078B     2  CC05 2019 2019-01-24      SALIN  3.4413791713  <NA> #> 2337  2078B     2  CC05 2019 2019-01-24        TKN -0.7985076962  <NA> #> 2338  2078B     2  CC05 2019 2019-01-24         TN -0.7896580809     + #> 2339  2078B     2  CC05 2019 2019-01-24         TP -3.5065578973  <NA> #> 2340  2078B     2  CC05 2019 2019-01-24        TSS  1.0986122887     I #> 2341  2078B     2  CC05 2019 2019-01-24       TURB  0.2623642645  <NA> #> 2342  2078B     2  CC05 2019 2019-03-12      CHLAC  1.2809338455  <NA> #> 2343  2078B     2  CC05 2019 2019-03-12       COND 10.4768935315  <NA> #> 2344  2078B     2  CC05 2019 2019-03-12         DO  1.6992786164  <NA> #> 2345  2078B     2  CC05 2019 2019-03-12      DOSAT  4.3412046402  <NA> #> 2346  2078B     2  CC05 2019 2019-03-12       NO23 -5.5214609179     U #> 2347  2078B     2  CC05 2019 2019-03-12      SALIN  3.1059310659  <NA> #> 2348  2078B     2  CC05 2019 2019-03-12        TKN -0.3424903089  <NA> #> 2349  2078B     2  CC05 2019 2019-03-12         TN -0.3396773676     + #> 2350  2078B     2  CC05 2019 2019-03-12         TP -3.2441936329  <NA> #> 2351  2078B     2  CC05 2019 2019-03-12        TSS  2.1972245773     I #> 2352  2078B     2  CC05 2019 2019-03-12       TURB  0.6931471806  <NA> #> 2353  2078B     2  CC05 2019 2019-04-16      CHLAC  1.4816045409  <NA> #> 2354  2078B     2  CC05 2019 2019-04-16       COND 10.7360705353  <NA> #> 2355  2078B     2  CC05 2019 2019-04-16         DO  1.6505798558  <NA> #> 2356  2078B     2  CC05 2019 2019-04-16      DOSAT  4.3094559418  <NA> #> 2357  2078B     2  CC05 2019 2019-04-16       NO23 -5.5214609179     U #> 2358  2078B     2  CC05 2019 2019-04-16      SALIN  3.3951793093  <NA> #> 2359  2078B     2  CC05 2019 2019-04-16        TKN -0.2484613593  <NA> #> 2360  2078B     2  CC05 2019 2019-04-16         TN -0.2459005384     + #> 2361  2078B     2  CC05 2019 2019-04-16         TP -3.7722610631  <NA> #> 2362  2078B     2  CC05 2019 2019-04-16        TSS  1.6094379124     I #> 2363  2078B     2  CC05 2019 2019-04-16       TURB  0.6418538862  <NA> #> 2364  2078B     2  CC05 2019 2019-06-11      CHLAC  1.1314021115  <NA> #> 2365  2078B     2  CC05 2019 2019-06-11       COND 10.8909447918  <NA> #> 2366  2078B     2  CC05 2019 2019-06-11         DO  1.2059708070  <NA> #> 2367  2078B     2  CC05 2019 2019-06-11      DOSAT  4.0127729085  <NA> #> 2368  2078B     2  CC05 2019 2019-06-11       NO23 -5.5214609179     I #> 2369  2078B     2  CC05 2019 2019-06-11      SALIN  3.5635996377  <NA> #> 2370  2078B     2  CC05 2019 2019-06-11        TKN -0.3285040670  <NA> #> 2371  2078B     2  CC05 2019 2019-06-11         TN -0.3229638866     + #> 2372  2078B     2  CC05 2019 2019-06-11         TP -3.3242363405  <NA> #> 2373  2078B     2  CC05 2019 2019-06-11        TSS  1.0986122887     U #> 2374  2078B     2  CC05 2019 2019-06-11       TURB  0.3364722366  <NA> #> 2375  2078B     2  CC05 2019 2019-08-13      CHLAC  2.8332133441  <NA> #> 2376  2078B     2  CC05 2019 2019-08-13       COND 10.2219412837  <NA> #> 2377  2078B     2  CC05 2019 2019-08-13         DO  1.4036429995  <NA> #> 2378  2078B     2  CC05 2019 2019-08-13      DOSAT  4.0926765051  <NA> #> 2379  2078B     2  CC05 2019 2019-08-13       NO23 -4.6051701860     I #> 2380  2078B     2  CC05 2019 2019-08-13      SALIN  2.8195915758  <NA> #> 2381  2078B     2  CC05 2019 2019-08-13        TKN  0.6418538862  <NA> #> 2382  2078B     2  CC05 2019 2019-08-13         TN  0.6439569364     + #> 2383  2078B     2  CC05 2019 2019-08-13         TP -2.9759296463  <NA> #> 2384  2078B     2  CC05 2019 2019-08-13        TSS  1.7917594692     I #> 2385  2078B     2  CC05 2019 2019-08-13       TURB  0.7884573604  <NA> #> 2386  2078B     2  CC05 2019 2019-08-13       COND 10.3244650523  <NA> #> 2387  2078B     2  CC05 2019 2019-08-13         DO  1.0543120298  <NA> #> 2388  2078B     2  CC05 2019 2019-08-13      DOSAT  3.7541989202  <NA> #> 2389  2078B     2  CC05 2019 2019-08-13      SALIN  2.9322598506  <NA> #> 2390  2078B     2  CC05 2019 2019-10-01       COND 10.7304660807  <NA> #> 2391  2078B     2  CC05 2019 2019-10-01         DO  1.5644405465  <NA> #> 2392  2078B     2  CC05 2019 2019-10-01      DOSAT  4.2724907476  <NA> #> 2393  2078B     2  CC05 2019 2019-10-01      SALIN  3.3864220961  <NA> #> 2394  2078B     2  CC05 2019 2019-11-04       COND 10.7792062586  <NA> #> 2395  2078B     2  CC05 2019 2019-11-04         DO  1.5151272330  <NA> #> 2396  2078B     2  CC05 2019 2019-11-04      DOSAT  4.2061840440  <NA> #> 2397  2078B     2  CC05 2019 2019-11-04      SALIN  3.4423393250  <NA> #> 2398  2078B     2  CC05 2019 2019-11-19      CHLAC  2.6390573296  <NA> #> 2399  2078B     2  CC05 2019 2019-11-19       COND 10.8493565039  <NA> #> 2400  2078B     2  CC05 2019 2019-11-19         DO  2.0135687975  <NA> #> 2401  2078B     2  CC05 2019 2019-11-19      DOSAT  4.6298627986  <NA> #> 2402  2078B     2  CC05 2019 2019-11-19       NO23 -5.5214609179     U #> 2403  2078B     2  CC05 2019 2019-11-19      SALIN  3.5234150144  <NA> #> 2404  2078B     2  CC05 2019 2019-11-19        TKN -0.3011050928  <NA> #> 2405  2078B     2  CC05 2019 2019-11-19         TN -0.2984060358     + #> 2406  2078B     2  CC05 2019 2019-11-19         TP -2.8302178351  <NA> #> 2407  2078B     2  CC05 2019 2019-11-19        TSS  2.0794415417     I #> 2408  2078B     2  CC05 2019 2019-11-19       TURB  1.0296194172     A #> 2409  2078B     2  CC05 2020 2020-02-13      CHLAC  2.1400661635     A #> 2410  2078B     2  CC05 2020 2020-02-13       COND 10.7287588860  <NA> #> 2411  2078B     2  CC05 2020 2020-02-13         DO  1.8961194846  <NA> #> 2412  2078B     2  CC05 2020 2020-02-13      DOSAT  4.5747109785  <NA> #> 2413  2078B     2  CC05 2020 2020-02-13       NO23 -5.5214609179     U #> 2414  2078B     2  CC05 2020 2020-02-13      SALIN  3.3857452771  <NA> #> 2415  2078B     2  CC05 2020 2020-02-13        TKN -0.3424903089  <NA> #> 2416  2078B     2  CC05 2020 2020-02-13         TN -0.3396773676     + #> 2417  2078B     2  CC05 2020 2020-02-13         TP -3.3242363405  <NA> #> 2418  2078B     2  CC05 2020 2020-02-13        TSS  2.2617630985     I #> 2419  2078B     2  CC05 2020 2020-02-13       TURB  1.0296194172  <NA> #> 2420  2078B     2  CC05 2020 2020-03-24      CHLAC  2.2617630985  <NA> #> 2421  2078B     2  CC05 2020 2020-03-24       COND 10.9026109427  <NA> #> 2422  2078B     2  CC05 2020 2020-03-24         DO  1.8357763546  <NA> #> 2423  2078B     2  CC05 2020 2020-03-24      DOSAT  4.5900565482  <NA> #> 2424  2078B     2  CC05 2020 2020-03-24       NO23 -5.5214609179     U #> 2425  2078B     2  CC05 2020 2020-03-24      SALIN  3.5787855313  <NA> #> 2426  2078B     2  CC05 2020 2020-03-24        TKN -0.6161861394  <NA> #> 2427  2078B     2  CC05 2020 2020-03-24         TN -0.6124892775     + #> 2428  2078B     2  CC05 2020 2020-03-24         TP -2.5902671654  <NA> #> 2429  2078B     2  CC05 2020 2020-03-24        TSS  2.4849066498     A #> 2430  2078B     2  CC05 2020 2020-03-24       TURB  1.0647107370  <NA> #> 2431  2078B     2  CC05 2020 2020-06-15      CHLAC  2.8332133441  <NA> #> 2432  2078B     2  CC05 2020 2020-06-15       COND 10.3780433051  <NA> #> 2433  2078B     2  CC05 2020 2020-06-15         DO  1.2325602612  <NA> #> 2434  2078B     2  CC05 2020 2020-06-15      DOSAT  3.9199911751  <NA> #> 2435  2078B     2  CC05 2020 2020-06-15       NO23 -5.5214609179     I #> 2436  2078B     2  CC05 2020 2020-06-15      SALIN  2.9907197317  <NA> #> 2437  2078B     2  CC05 2020 2020-06-15        TKN  0.1823215568  <NA> #> 2438  2078B     2  CC05 2020 2020-06-15         TN  0.1856493469     + #> 2439  2078B     2  CC05 2020 2020-06-15         TP -3.0159349809  <NA> #> 2440  2078B     2  CC05 2020 2020-06-15        TSS  1.6094379124     I #> 2441  2078B     2  CC05 2020 2020-06-15       TURB  0.9932517730  <NA> #> 2442  2078B     2  CC05 2020 2020-07-27      CHLAC  2.5649493575     A #> 2443  2078B     2  CC05 2020 2020-07-27       COND 10.7499993898  <NA> #> 2444  2078B     2  CC05 2020 2020-07-27         DO  1.4422019931  <NA> #> 2445  2078B     2  CC05 2020 2020-07-27      DOSAT  4.2150861799  <NA> #> 2446  2078B     2  CC05 2020 2020-07-27       NO23 -5.5214609179     U #> 2447  2078B     2  CC05 2020 2020-07-27      SALIN  3.4041928906  <NA> #> 2448  2078B     2  CC05 2020 2020-07-27        TKN -0.3424903089  <NA> #> 2449  2078B     2  CC05 2020 2020-07-27         TN -0.3396773676     + #> 2450  2078B     2  CC05 2020 2020-07-27         TP -3.1010927892  <NA> #> 2451  2078B     2  CC05 2020 2020-07-27        TSS  1.6094379124     I #> 2452  2078B     2  CC05 2020 2020-07-27       TURB  1.1631508098  <NA> #> 2453  2078B     2  CC05 2020 2020-08-26      CHLAC  2.8903717579  <NA> #> 2454  2078B     2  CC05 2020 2020-08-26       COND 10.1730947543  <NA> #> 2455  2078B     2  CC05 2020 2020-08-26         DO  1.5062971535  <NA> #> 2456  2078B     2  CC05 2020 2020-08-26      DOSAT  4.1972019477  <NA> #> 2457  2078B     2  CC05 2020 2020-08-26       NO23 -5.5214609179     U #> 2458  2078B     2  CC05 2020 2020-08-26      SALIN  2.7625383864  <NA> #> 2459  2078B     2  CC05 2020 2020-08-26        TKN -0.0618754037  <NA> #> 2460  2078B     2  CC05 2020 2020-08-26         TN -0.0597500044     + #> 2461  2078B     2  CC05 2020 2020-08-26         TP -2.9565115604  <NA> #> 2462  2078B     2  CC05 2020 2020-08-26        TSS  1.7917594692     I #> 2463  2078B     2  CC05 2020 2020-08-26       TURB  1.0647107370  <NA> #> 2464  2078B     2  CC05 2021 2021-01-14      CHLAC  0.9162907319  <NA> #> 2465  2078B     2  CC05 2021 2021-01-14       COND 10.6789517756  <NA> #> 2466  2078B     2  CC05 2021 2021-01-14         DO  1.7422190237  <NA> #> 2467  2078B     2  CC05 2021 2021-01-14      DOSAT  4.2427645673  <NA> #> 2468  2078B     2  CC05 2021 2021-01-14       NO23 -4.6051701860  <NA> #> 2469  2078B     2  CC05 2021 2021-01-14      SALIN  3.3339886320  <NA> #> 2470  2078B     2  CC05 2021 2021-01-14        TKN -0.6348782724  <NA> #> 2471  2078B     2  CC05 2021 2021-01-14         TN -0.6161861394     + #> 2472  2078B     2  CC05 2021 2021-01-14         TP -3.4420193762  <NA> #> 2473  2078B     2  CC05 2021 2021-01-14        TSS  1.0986122887     I #> 2474  2078B     2  CC05 2021 2021-01-14       TURB  0.5306282511  <NA> #> 2475  2078B     2  CC05 2021 2021-02-24       COND 10.7448823096  <NA> #> 2476  2078B     2  CC05 2021 2021-02-24         DO  1.5518087996  <NA> #> 2477  2078B     2  CC05 2021 2021-02-24      DOSAT  4.1987045775  <NA> #> 2478  2078B     2  CC05 2021 2021-02-24       NO23 -4.6051701860     I #> 2479  2078B     2  CC05 2021 2021-02-24      SALIN  3.4061849232  <NA> #> 2480  2078B     2  CC05 2021 2021-02-24        TKN -0.8915981193  <NA> #> 2481  2078B     2  CC05 2021 2021-02-24         TN -0.8818893052     + #> 2482  2078B     2  CC05 2021 2021-02-24         TP -3.2441936329  <NA> #> 2483  2078B     2  CC05 2021 2021-02-24        TSS  1.0986122887     I #> 2484  2078B     2  CC05 2021 2021-03-23      CHLAC  1.1939224685  <NA> #> 2485  2078B     2  CC05 2021 2021-03-23       COND 10.8800451952  <NA> #> 2486  2078B     2  CC05 2021 2021-03-23         DO  1.7783364489  <NA> #> 2487  2078B     2  CC05 2021 2021-03-23      DOSAT  4.4042772436  <NA> #> 2488  2078B     2  CC05 2021 2021-03-23       NO23 -4.9618451299     I #> 2489  2078B     2  CC05 2021 2021-03-23      SALIN  3.5579161896  <NA> #> 2490  2078B     2  CC05 2021 2021-03-23        TKN -0.5447271754  <NA> #> 2491  2078B     2  CC05 2021 2021-03-23         TN -0.5378542962     + #> 2492  2078B     2  CC05 2021 2021-03-23         TP -2.8134107168  <NA> #> 2493  2078B     2  CC05 2021 2021-03-23        TSS  2.4849066498  <NA> #> 2494  2078B     2  CC05 2021 2021-03-23       TURB  1.6863989536  <NA> #> 2495  2078B     2  CC05 2021 2021-07-28      CHLAC  2.5649493575  <NA> #> 2496  2078B     2  CC05 2021 2021-07-28       COND 10.0731881321  <NA> #> 2497  2078B     2  CC05 2021 2021-07-28         DO  0.9001613499  <NA> #> 2498  2078B     2  CC05 2021 2021-07-28      DOSAT  3.6027767551  <NA> #> 2499  2078B     2  CC05 2021 2021-07-28       NO23 -5.5214609179     U #> 2500  2078B     2  CC05 2021 2021-07-28      SALIN  2.6665335209  <NA> #> 2501  2078B     2  CC05 2021 2021-07-28        TKN  0.0000000000  <NA> #> 2502  2078B     2  CC05 2021 2021-07-28         TN  0.0019980027     + #> 2503  2078B     2  CC05 2021 2021-07-28         TP -3.1010927892  <NA> #> 2504  2078B     2  CC05 2021 2021-07-28        TSS  1.3862943611     I #> 2505  2078B     2  CC05 2021 2021-07-28       TURB  1.0296194172  <NA> #> 2506  2078B     2  CC05 2021 2021-08-26      CHLAC  2.4849066498  <NA> #> 2507  2078B     2  CC05 2021 2021-08-26       COND 10.2519942268  <NA> #> 2508  2078B     2  CC05 2021 2021-08-26         DO  1.3737155789  <NA> #> 2509  2078B     2  CC05 2021 2021-08-26      DOSAT  4.0324691585  <NA> #> 2510  2078B     2  CC05 2021 2021-08-26       NO23 -5.5214609179     U #> 2511  2078B     2  CC05 2021 2021-08-26      SALIN  2.8553201198  <NA> #> 2512  2078B     2  CC05 2021 2021-08-26        TKN -0.2231435513  <NA> #> 2513  2078B     2  CC05 2021 2021-08-26         TN -0.2206466711     + #> 2514  2078B     2  CC05 2021 2021-08-26         TP -2.8134107168  <NA> #> 2515  2078B     2  CC05 2021 2021-08-26        TSS  1.9459101491     I #> 2516  2078B     2  CC05 2021 2021-08-26       TURB  0.8754687374  <NA> #> 2517  2078B     2  CC05 2021 2021-09-13      CHLAC  2.5649493575  <NA> #> 2518  2078B     2  CC05 2021 2021-09-13       COND 10.4619312252  <NA> #> 2519  2078B     2  CC05 2021 2021-09-13         DO  1.4929040962  <NA> #> 2520  2078B     2  CC05 2021 2021-09-13      DOSAT  4.2091602367  <NA> #> 2521  2078B     2  CC05 2021 2021-09-13       NO23 -5.5214609179     U #> 2522  2078B     2  CC05 2021 2021-09-13      SALIN  3.0842009215  <NA> #> 2523  2078B     2  CC05 2021 2021-09-13        TKN -0.0943106795  <NA> #> 2524  2078B     2  CC05 2021 2021-09-13         TN -0.0921152889     + #> 2525  2078B     2  CC05 2021 2021-09-13         TP -2.9565115604  <NA> #> 2526  2078B     2  CC05 2021 2021-09-13        TSS  2.0794415417     I #> 2527  2078B     2  CC05 2021 2021-09-13       TURB  1.0986122887     A #> 2528  2078B     2  CC05 2022 2022-04-19      CHLAC  2.3978952728  <NA> #> 2529  2078B     2  CC05 2022 2022-04-19       COND 10.9594532665  <NA> #> 2530  2078B     2  CC05 2022 2022-04-19         DO  1.6486586256  <NA> #> 2531  2078B     2  CC05 2022 2022-04-19      DOSAT  4.3845235149  <NA> #> 2532  2078B     2  CC05 2022 2022-04-19       NO23 -5.5214609179     U #> 2533  2078B     2  CC05 2022 2022-04-19      SALIN  3.6449275666  <NA> #> 2534  2078B     2  CC05 2022 2022-04-19        TKN -0.4462871026  <NA> #> 2535  2078B     2  CC05 2022 2022-04-19         TN -0.4431669753     + #> 2536  2078B     2  CC05 2022 2022-04-19         TP -2.6592600369  <NA> #> 2537  2078B     2  CC05 2022 2022-04-19        TSS  3.0910424534  <NA> #> 2538  2078B     2  CC05 2022 2022-04-19       TURB  1.5892352051     A #> 2539  2078B     2  CC05 2022 2022-05-10      CHLAC  1.9021075264  <NA> #> 2540  2078B     2  CC05 2022 2022-05-10       COND 10.8257603561  <NA> #> 2541  2078B     2  CC05 2022 2022-05-10         DO  1.6114359151  <NA> #> 2542  2078B     2  CC05 2022 2022-05-10      DOSAT  4.3148178850  <NA> #> 2543  2078B     2  CC05 2022 2022-05-10       NO23 -5.5214609179     U #> 2544  2078B     2  CC05 2022 2022-05-10      SALIN  3.4943840964  <NA> #> 2545  2078B     2  CC05 2022 2022-05-10        TKN -0.1984509387  <NA> #> 2546  2078B     2  CC05 2022 2022-05-10         TN -0.1960148839     + #> 2547  2078B     2  CC05 2022 2022-05-10         TP -2.6450754019  <NA> #> 2548  2078B     2  CC05 2022 2022-05-10        TSS  2.1972245773     I #> 2549  2078B     2  CC05 2022 2022-05-10       TURB  1.6486586256  <NA> #> 2550  2078B     2  CC05 2022 2022-09-20      CHLAC  2.2082744135  <NA> #> 2551  2078B     2  CC05 2022 2022-09-20       COND 10.0045990539  <NA> #> 2552  2078B     2  CC05 2022 2022-09-20         DO  0.9001613499  <NA> #> 2553  2078B     2  CC05 2022 2022-09-20      DOSAT  3.5695326965  <NA> #> 2554  2078B     2  CC05 2022 2022-09-20       NO23 -5.5214609179     U #> 2555  2078B     2  CC05 2022 2022-09-20      SALIN  2.5832425505  <NA> #> 2556  2078B     2  CC05 2022 2022-09-20        TKN  0.0953101798  <NA> #> 2557  2078B     2  CC05 2022 2022-09-20         TN  0.0971267107     + #> 2558  2078B     2  CC05 2022 2022-09-20         TP -2.7333680091  <NA> #> 2559  2078B     2  CC05 2022 2022-09-20        TSS  1.3862943611     I #> 2560  2078B     2  CC05 2022 2022-09-20       TURB  0.4054651081     A #> 2561  2078B     2  CC05 2022 2022-10-31      CHLAC  2.7725887222  <NA> #> 2562  2078B     2  CC05 2022 2022-10-31       COND 10.6157508503  <NA> #> 2563  2078B     2  CC05 2022 2022-10-31         DO  1.1505720276  <NA> #> 2564  2078B     2  CC05 2022 2022-10-31      DOSAT  3.8329797981  <NA> #> 2565  2078B     2  CC05 2022 2022-10-31       NO23 -5.5214609179     U #> 2566  2078B     2  CC05 2022 2022-10-31      SALIN  3.2584810795  <NA> #> 2567  2078B     2  CC05 2022 2022-10-31        TKN -1.8325814637     U #> 2568  2078B     2  CC05 2022 2022-10-31         TN -2.5010360317     + #> 2569  2078B     2  CC05 2022 2022-10-31         TP -2.9374633654  <NA> #> 2570  2078B     2  CC05 2022 2022-10-31        TSS  1.7917594692     I #> 2571  2078B     2  CC05 2022 2022-10-31       TURB  1.2237754316  <NA> #> 2572  2078B     2  CC05 2021 2021-03-23      CHLAC  1.5892352051  <NA> #> 2573  2078B     2  CC05 2021 2021-03-23       COND 10.8660128047  <NA> #> 2574  2078B     2  CC05 2021 2021-03-23         DO  2.0162354658  <NA> #> 2575  2078B     2  CC05 2021 2021-03-23      DOSAT  4.6802776585  <NA> #> 2576  2078B     2  CC05 2021 2021-03-23       NO23 -5.5214609179     U #> 2577  2078B     2  CC05 2021 2021-03-23      SALIN  3.5415388662  <NA> #> 2578  2078B     2  CC05 2021 2021-03-23        TKN  0.0953101798  <NA> #> 2579  2078B     2  CC05 2021 2021-03-23         TN  0.0971267107     + #> 2580  2078B     2  CC05 2021 2021-03-23         TP -3.2968373663  <NA> #> 2581  2078B     2  CC05 2021 2021-03-23        TSS  1.0986122887     I #> 2582  2078B     2  CC05 2021 2021-03-23       TURB  0.7884573604  <NA> #> 2583  2078B     2  CC05 2021 2021-07-28      CHLAC  1.5686159179     I #> 2584  2078B     2  CC05 2021 2021-07-28       COND  9.6616070559  <NA> #> 2585  2078B     2  CC05 2021 2021-07-28         DO -0.3566749439  <NA> #> 2586  2078B     2  CC05 2021 2021-07-28      DOSAT  2.3418058061  <NA> #> 2587  2078B     2  CC05 2021 2021-07-28       NO23 -5.5214609179     U #> 2588  2078B     2  CC05 2021 2021-07-28      SALIN  2.2049722641  <NA> #> 2589  2078B     2  CC05 2021 2021-07-28        TKN  0.0953101798  <NA> #> 2590  2078B     2  CC05 2021 2021-07-28         TN  0.0971267107     + #> 2591  2078B     2  CC05 2021 2021-07-28         TP -3.3242363405  <NA> #> 2592  2078B     2  CC05 2021 2021-07-28        TSS  1.0986122887     U #> 2593  2078B     2  CC05 2021 2021-07-28       TURB  0.5306282511  <NA> #> 2594  2078B     2  CC05 2021 2021-08-26      CHLAC  2.5649493575  <NA> #> 2595  2078B     2  CC05 2021 2021-08-26       COND  9.7645702533  <NA> #> 2596  2078B     2  CC05 2021 2021-08-26         DO  0.7030975114  <NA> #> 2597  2078B     2  CC05 2021 2021-08-26      DOSAT  3.3141860047  <NA> #> 2598  2078B     2  CC05 2021 2021-08-26       NO23 -5.5214609179     U #> 2599  2078B     2  CC05 2021 2021-08-26      SALIN  2.3223877203  <NA> #> 2600  2078B     2  CC05 2021 2021-08-26        TKN  0.2623642645  <NA> #> 2601  2078B     2  CC05 2021 2021-08-26         TN  0.2639015438     + #> 2602  2078B     2  CC05 2021 2021-08-26         TP -2.9565115604  <NA> #> 2603  2078B     2  CC05 2021 2021-08-26        TSS  2.3025850930     I #> 2604  2078B     2  CC05 2021 2021-08-26       TURB  2.3978952728  <NA> #> 2605  2078B     2  CC05 2021 2021-09-13      CHLAC  2.8332133441     A #> 2606  2078B     2  CC05 2021 2021-09-13       COND 10.1916695000  <NA> #> 2607  2078B     2  CC05 2021 2021-09-13         DO  1.2296405511  <NA> #> 2608  2078B     2  CC05 2021 2021-09-13      DOSAT  3.9239515763  <NA> #> 2609  2078B     2  CC05 2021 2021-09-13       NO23 -5.5214609179     U #> 2610  2078B     2  CC05 2021 2021-09-13      SALIN  2.7868613815  <NA> #> 2611  2078B     2  CC05 2021 2021-09-13        TKN  0.0953101798  <NA> #> 2612  2078B     2  CC05 2021 2021-09-13         TN  0.0971267107     + #> 2613  2078B     2  CC05 2021 2021-09-13         TP -2.9957322736  <NA> #> 2614  2078B     2  CC05 2021 2021-09-13        TSS  1.6094379124     I #> 2615  2078B     2  CC05 2021 2021-09-13       TURB  1.7578579176  <NA> #> 2616  2078B     2  CC05 2021 2021-10-20      CHLAC  2.7725887222  <NA> #> 2617  2078B     2  CC05 2021 2021-10-20       COND 10.4756810512  <NA> #> 2618  2078B     2  CC05 2021 2021-10-20         DO  0.2700271372  <NA> #> 2619  2078B     2  CC05 2021 2021-10-20      DOSAT  2.9391619221  <NA> #> 2620  2078B     2  CC05 2021 2021-10-20       NO23 -5.5214609179     U #> 2621  2078B     2  CC05 2021 2021-10-20      SALIN  3.1099534176  <NA> #> 2622  2078B     2  CC05 2021 2021-10-20        TKN  0.0953101798  <NA> #> 2623  2078B     2  CC05 2021 2021-10-20         TN  0.0971267107     + #> 2624  2078B     2  CC05 2021 2021-10-20         TP -3.1235656451  <NA> #> 2625  2078B     2  CC05 2021 2021-10-20        TSS  1.9459101491     I #> 2626  2078B     2  CC05 2021 2021-10-20       TURB  1.4109869737  <NA> #> 2627  2078B     2  CC05 2022 2022-04-06      CHLAC  1.8718021769  <NA> #> 2628  2078B     2  CC05 2022 2022-04-06       COND 11.0061250625  <NA> #> 2629  2078B     2  CC05 2022 2022-04-06         DO  0.6365768291  <NA> #> 2630  2078B     2  CC05 2022 2022-04-06      DOSAT  3.3911470458  <NA> #> 2631  2078B     2  CC05 2022 2022-04-06       NO23 -5.5214609179     U #> 2632  2078B     2  CC05 2022 2022-04-06      SALIN  3.6980869349  <NA> #> 2633  2078B     2  CC05 2022 2022-04-06        TKN -0.0512932944  <NA> #> 2634  2078B     2  CC05 2022 2022-04-06         TN -0.0491902442     + #> 2635  2078B     2  CC05 2022 2022-04-06         TP -3.1700856607  <NA> #> 2636  2078B     2  CC05 2022 2022-04-06        TSS  1.3862943611     I #> 2637  2078B     2  CC05 2022 2022-04-06       TURB  0.0953101798  <NA> #> 2638  2078B     2  CC05 2022 2022-05-10      CHLAC  2.5649493575  <NA> #> 2639  2078B     2  CC05 2022 2022-05-10       COND 10.7027274806  <NA> #> 2640  2078B     2  CC05 2022 2022-05-10         DO  1.1281710909  <NA> #> 2641  2078B     2  CC05 2022 2022-05-10      DOSAT  3.7841896339  <NA> #> 2642  2078B     2  CC05 2022 2022-05-10       NO23 -5.5214609179     U #> 2643  2078B     2  CC05 2022 2022-05-10      SALIN  3.3579418730  <NA> #> 2644  2078B     2  CC05 2022 2022-05-10        TKN -0.0512932944  <NA> #> 2645  2078B     2  CC05 2022 2022-05-10         TN -0.0491902442     + #> 2646  2078B     2  CC05 2022 2022-05-10         TP -3.1010927892  <NA> #> 2647  2078B     2  CC05 2022 2022-05-10        TSS  2.1972245773     I #> 2648  2078B     2  CC05 2022 2022-05-10       TURB  1.2237754316  <NA> #> 2649  2078B     2  CC05 2022 2022-09-20      CHLAC  0.8754687374     I #> 2650  2078B     2  CC05 2022 2022-09-20       COND  8.7041705597  <NA> #> 2651  2078B     2  CC05 2022 2022-09-20         DO  0.6830968447  <NA> #> 2652  2078B     2  CC05 2022 2022-09-20      DOSAT  3.2503744919  <NA> #> 2653  2078B     2  CC05 2022 2022-09-20       NO23 -5.5214609179     U #> 2654  2078B     2  CC05 2022 2022-09-20      SALIN  1.1817271954  <NA> #> 2655  2078B     2  CC05 2022 2022-09-20        TKN -0.0100503359  <NA> #> 2656  2078B     2  CC05 2022 2022-09-20         TN -0.0080321717     + #> 2657  2078B     2  CC05 2022 2022-09-20         TP -3.4737680745  <NA> #> 2658  2078B     2  CC05 2022 2022-09-20        TSS  0.6931471806     I #> 2659  2078B     2  CC05 2022 2022-09-20       TURB -0.1053605157     I #> 2660  2078B     2  CC05 2022 2022-10-31      CHLAC  3.1780538303     A #> 2661  2078B     2  CC05 2022 2022-10-31       COND 10.3516289349  <NA> #> 2662  2078B     2  CC05 2022 2022-10-31         DO  0.2231435513  <NA> #> 2663  2078B     2  CC05 2022 2022-10-31      DOSAT  2.8678989020  <NA> #> 2664  2078B     2  CC05 2022 2022-10-31       NO23 -5.5214609179     U #> 2665  2078B     2  CC05 2022 2022-10-31      SALIN  2.9663034629  <NA> #> 2666  2078B     2  CC05 2022 2022-10-31        TKN  0.1823215568  <NA> #> 2667  2078B     2  CC05 2022 2022-10-31         TN  0.1839868361     + #> 2668  2078B     2  CC05 2022 2022-10-31         TP -2.5902671654  <NA> #> 2669  2078B     2  CC05 2022 2022-10-31        TSS  1.9459101491     I #> 2670  2078B     2  CC05 2022 2022-10-31       TURB  3.0910424534  <NA> #> 2671  2078B     2  CC05 2023 2023-02-13      CHLAC  2.4849066498  <NA> #> 2672  2078B     2  CC05 2023 2023-02-13       COND 10.7464115759  <NA> #> 2673  2078B     2  CC05 2023 2023-02-13         DO  1.2892326483  <NA> #> 2674  2078B     2  CC05 2023 2023-02-13      DOSAT  3.8836235309  <NA> #> 2675  2078B     2  CC05 2023 2023-02-13       NO23 -5.5214609179     U #> 2676  2078B     2  CC05 2023 2023-02-13      SALIN  3.4085039568  <NA> #> 2677  2078B     2  CC05 2023 2023-02-13        TKN  0.1823215568  <NA> #> 2678  2078B     2  CC05 2023 2023-02-13         TN  0.1839868361     + #> 2679  2078B     2  CC05 2023 2023-02-13         TP -3.0791138825  <NA> #> 2680  2078B     2  CC05 2023 2023-02-13        TSS  2.6390573296  <NA> #> 2681  2078B     2  CC05 2023 2023-02-13       TURB  1.2237754316  <NA> #> 2682  2078B     2  CC05 2023 2023-04-10       COND 11.0888889713  <NA> #> 2683  2078B     2  CC05 2023 2023-04-10         DO  0.4762341790  <NA> #> 2684  2078B     2  CC05 2023 2023-04-10      DOSAT  3.2188758249  <NA> #> 2685  2078B     2  CC05 2023 2023-04-10       NO23 -3.9120230054     U #> 2686  2078B     2  CC05 2023 2023-04-10      SALIN  3.7934646693  <NA> #> 2687  2078B     2  CC05 2023 2023-04-10        TKN  0.1823215568  <NA> #> 2688  2078B     2  CC05 2023 2023-04-10         TN  0.1906203596     + #> 2689  2078B     2  CC05 2023 2023-04-10         TP -2.9004220937  <NA> #> 2690  2078B     2  CC05 2023 2023-04-10        TSS  1.3862943611     I #> 2691  2078B     2  CC05 2019 2019-06-06      CHLAC  0.7419373447     I #> 2692  2078B     2  CC05 2019 2019-06-06       NO23 -5.2983173665     I #> 2693  2078B     2  CC05 2019 2019-06-06        TKN -0.4004775666  <NA> #> 2694  2078B     2  CC05 2019 2019-06-06         TN -0.3945251681     + #> 2695  2078B     2  CC05 2019 2019-06-06         TP -3.4420193762  <NA> #> 2696   2035    3F CC104 2015 2015-06-04       COND  7.8336002237  <NA> #> 2697   2035    3F CC104 2015 2015-06-04         DO  1.6292405397  <NA> #> 2698   2035    3F CC104 2015 2015-06-04      DOSAT  4.1108738642  <NA> #> 2699   2035    3F CC104 2015 2015-06-04      SALIN  0.2926696140     + #> 2700   2035    3F CC104 2015 2015-08-06       COND  6.3868793194  <NA> #> 2701   2035    3F CC104 2015 2015-08-06         DO  1.7047480922  <NA> #> 2702   2035    3F CC104 2015 2015-08-06      DOSAT  4.2046926194  <NA> #> 2703   2035    3F CC104 2015 2015-08-06      SALIN -1.2729656758     + #> 2704   2035    3F CC104 2015 2015-08-19       COND  6.8351845861  <NA> #> 2705   2035    3F CC104 2015 2015-08-19         DO  1.4109869737  <NA> #> 2706   2035    3F CC104 2015 2015-08-19      DOSAT  3.9318256327  <NA> #> 2707   2035    3F CC104 2015 2015-08-19      SALIN -0.7985076962     + #> 2708   2035    3F CC104 2015 2015-09-15       COND  6.4583382833  <NA> #> 2709   2035    3F CC104 2015 2015-09-15         DO  1.6677068206  <NA> #> 2710   2035    3F CC104 2015 2015-09-15      DOSAT  4.1896547420  <NA> #> 2711   2035    3F CC104 2015 2015-09-15      SALIN -1.2039728043     + #> 2712   2035    3F CC104 2015 2015-11-25       COND  7.2584121506  <NA> #> 2713   2035    3F CC104 2015 2015-11-25         DO  1.8082887712  <NA> #> 2714   2035    3F CC104 2015 2015-11-25      DOSAT  4.2046926194  <NA> #> 2715   2035    3F CC104 2015 2015-11-25      SALIN -0.2231435513     + #> 2716   2035    3F CC104 2015 2015-12-30       COND  7.6563371664  <NA> #> 2717   2035    3F CC104 2015 2015-12-30         DO  1.8562979904  <NA> #> 2718   2035    3F CC104 2015 2015-12-30      DOSAT  4.3040650932  <NA> #> 2719   2035    3F CC104 2015 2015-12-30      SALIN  0.1310282624     + #> 2720   2035    3F CC104 2015 2015-05-21       COND  8.9299648747  <NA> #> 2721   2035    3F CC104 2015 2015-05-21         DO  1.6292405397  <NA> #> 2722   2035    3F CC104 2015 2015-05-21      DOSAT  4.1743872699  <NA> #> 2723   2035    3F CC104 2015 2015-05-21      SALIN  1.3787660947     + #> 2724   2035    3F CC104 2015 2015-06-04       COND  9.1162494486  <NA> #> 2725   2035    3F CC104 2015 2015-06-04         DO  1.5686159179  <NA> #> 2726   2035    3F CC104 2015 2015-06-04      DOSAT  4.1108738642  <NA> #> 2727   2035    3F CC104 2015 2015-06-04      SALIN  1.6054298910     + #> 2728   2035    3F CC104 2015 2015-07-15       COND  7.5559050936  <NA> #> 2729   2035    3F CC104 2015 2015-07-15      SALIN -0.0833816089     + #> 2730   2035    3F CC104 2015 2015-08-06       COND  6.8057225534  <NA> #> 2731   2035    3F CC104 2015 2015-08-06         DO  1.6486586256  <NA> #> 2732   2035    3F CC104 2015 2015-08-06      DOSAT  4.1431347264  <NA> #> 2733   2035    3F CC104 2015 2015-08-06      SALIN -0.8209805521     + #> 2734   2035    3F CC104 2015 2015-08-19       COND  6.6200732065  <NA> #> 2735   2035    3F CC104 2015 2015-08-19         DO  1.4586150227  <NA> #> 2736   2035    3F CC104 2015 2015-08-19      DOSAT  3.9889840466  <NA> #> 2737   2035    3F CC104 2015 2015-08-19      SALIN -1.0216512475     + #> 2738   2035    3F CC104 2015 2015-09-15       COND  6.3315018499  <NA> #> 2739   2035    3F CC104 2015 2015-09-15         DO  1.6677068206  <NA> #> 2740   2035    3F CC104 2015 2015-09-15      DOSAT  4.1588830834  <NA> #> 2741   2035    3F CC104 2015 2015-09-15      SALIN -1.3470736480     + #> 2742   2035    3F CC104 2015 2015-11-25       COND  6.9147308927  <NA> #> 2743   2035    3F CC104 2015 2015-11-25         DO  2.0281482473  <NA> #> 2744   2035    3F CC104 2015 2015-11-25      DOSAT  4.4188406078  <NA> #> 2745   2035    3F CC104 2015 2015-11-25      SALIN -0.5798184953     + #> 2746   2035    3F CC104 2015 2015-12-30       COND  7.5267175614  <NA> #> 2747   2035    3F CC104 2015 2015-12-30         DO  1.8245492921  <NA> #> 2748   2035    3F CC104 2015 2015-12-30      DOSAT  4.2766661190  <NA> #> 2749   2035    3F CC104 2015 2015-12-30      SALIN  0.0000000000     + #> 2750   2035    3F CC104 2015 2015-05-21       COND  9.3336193881  <NA> #> 2751   2035    3F CC104 2015 2015-05-21         DO  1.4109869737  <NA> #> 2752   2035    3F CC104 2015 2015-05-21      DOSAT  4.0073331852  <NA> #> 2753   2035    3F CC104 2015 2015-05-21      SALIN  1.7664416612     + #> 2754   2035    3F CC104 2015 2015-06-04       COND  9.1775072149  <NA> #> 2755   2035    3F CC104 2015 2015-06-04         DO  1.3350010667  <NA> #> 2756   2035    3F CC104 2015 2015-06-04      DOSAT  3.8712010109  <NA> #> 2757   2035    3F CC104 2015 2015-06-04      SALIN  1.6677068206     + #> 2758   2035    3F CC104 2015 2015-07-15       COND  7.9024874372  <NA> #> 2759   2035    3F CC104 2015 2015-07-15      SALIN  0.2546422184     + #> 2760   2035    3F CC104 2015 2015-08-06       COND  6.7765069924  <NA> #> 2761   2035    3F CC104 2015 2015-08-06         DO  1.3350010667  <NA> #> 2762   2035    3F CC104 2015 2015-08-06      DOSAT  3.8918202981  <NA> #> 2763   2035    3F CC104 2015 2015-08-06      SALIN -0.8915981193     + #> 2764   2035    3F CC104 2015 2015-08-19       COND  6.4846352356  <NA> #> 2765   2035    3F CC104 2015 2015-08-19         DO  1.3862943611  <NA> #> 2766   2035    3F CC104 2015 2015-08-19      DOSAT  3.9318256327  <NA> #> 2767   2035    3F CC104 2015 2015-08-19      SALIN -1.2039728043     + #> 2768   2035    3F CC104 2015 2015-09-15       COND  6.2934192788  <NA> #> 2769   2035    3F CC104 2015 2015-09-15         DO  1.6486586256  <NA> #> 2770   2035    3F CC104 2015 2015-09-15      DOSAT  4.1588830834  <NA> #> 2771   2035    3F CC104 2015 2015-09-15      SALIN -1.3862943611     + #> 2772   2035    3F CC104 2015 2015-11-25       COND  6.8101424501  <NA> #> 2773   2035    3F CC104 2015 2015-11-25         DO  1.8870696490  <NA> #> 2774   2035    3F CC104 2015 2015-11-25      DOSAT  4.2766661190  <NA> #> 2775   2035    3F CC104 2015 2015-11-25      SALIN -0.6931471806     + #> 2776   2035    3F CC104 2015 2015-12-30       COND  7.6847839435  <NA> #> 2777   2035    3F CC104 2015 2015-12-30         DO  1.5686159179  <NA> #> 2778   2035    3F CC104 2015 2015-12-30      DOSAT  4.0430512678  <NA> #> 2779   2035    3F CC104 2015 2015-12-30      SALIN  0.1484200051     + #> 2780   2035    3F CC104 2022 2022-01-24       COND  7.5234813126  <NA> #> 2781   2035    3F CC104 2022 2022-01-24         DO  2.2257040487  <NA> #> 2782   2035    3F CC104 2022 2022-01-24      DOSAT  4.4636066217  <NA> #> 2783   2035    3F CC104 2022 2022-01-24      SALIN -0.0512932944  <NA> #> 2784   2035    3F CC104 2022 2022-03-03       COND  7.6722924556  <NA> #> 2785   2035    3F CC104 2022 2022-03-03         DO  2.0108949991  <NA> #> 2786   2035    3F CC104 2022 2022-03-03      DOSAT  4.3870141762  <NA> #> 2787   2035    3F CC104 2022 2022-03-03      SALIN  0.0953101798  <NA> #> 2788   2035    3F CC104 2022 2022-05-23       COND  7.7981126288  <NA> #> 2789   2035    3F CC104 2022 2022-05-23         DO  1.9837562915  <NA> #> 2790   2035    3F CC104 2022 2022-05-23      DOSAT  4.4920014879  <NA> #> 2791   2035    3F CC104 2022 2022-05-23      SALIN  0.2231435513  <NA> #> 2792   2035    3F CC104 2022 2022-06-27       COND  7.0475172214  <NA> #> 2793   2035    3F CC104 2022 2022-06-27         DO  1.8099267732  <NA> #> 2794   2035    3F CC104 2022 2022-06-27      DOSAT  4.3000027992  <NA> #> 2795   2035    3F CC104 2022 2022-06-27      SALIN -0.5621189182  <NA> #> 2796   2035    3F CC104 2023 2023-01-09       COND  6.8232861224  <NA> #> 2797   2035    3F CC104 2023 2023-01-09         DO  1.8991179875  <NA> #> 2798   2035    3F CC104 2023 2023-01-09      DOSAT  4.2696974497  <NA> #> 2799   2035    3F CC104 2023 2023-01-09      SALIN -0.7985076962  <NA> #> 2800   2035    3F CC104 2023 2023-03-14       COND  7.5060421785  <NA> #> 2801   2035    3F CC104 2023 2023-03-14         DO  1.7334238922  <NA> #> 2802   2035    3F CC104 2023 2023-03-14      DOSAT  4.1635596312  <NA> #> 2803   2035    3F CC104 2023 2023-03-14      SALIN -0.0725706928  <NA> #> 2804   2035    3F CC104 2023 2023-05-10       COND  7.6177595766  <NA> #> 2805   2035    3F CC104 2023 2023-05-10         DO  1.6331544391  <NA> #> 2806   2035    3F CC104 2023 2023-05-10      DOSAT  4.0876555741  <NA> #> 2807   2035    3F CC104 2023 2023-05-10      SALIN  0.0392207132  <NA> #> 2808   2035    3F CC104 2022 2022-01-24      CHLAC  0.1823215568     I #> 2809   2035    3F CC104 2022 2022-01-24      COLOR  3.4965075615  <NA> #> 2810   2035    3F CC104 2022 2022-01-24       COND  7.4336665402  <NA> #> 2811   2035    3F CC104 2022 2022-01-24         DO  2.1905355892  <NA> #> 2812   2035    3F CC104 2022 2022-01-24      DOSAT  4.4473461008  <NA> #> 2813   2035    3F CC104 2022 2022-01-24       NO23 -2.3025850930  <NA> #> 2814   2035    3F CC104 2022 2022-01-24      SALIN -0.1508228897  <NA> #> 2815   2035    3F CC104 2022 2022-01-24        TKN -0.4155154440  <NA> #> 2816   2035    3F CC104 2022 2022-01-24         TN -0.2744368457     + #> 2817   2035    3F CC104 2022 2022-01-24         TP -1.0788096614  <NA> #> 2818   2035    3F CC104 2022 2022-01-24        TSS  1.3862943611     I #> 2819   2035    3F CC104 2022 2022-01-24       TURB  2.0541237337  <NA> #> 2820   2035    3F CC104 2022 2022-03-03      CHLAC  0.6418538862     I #> 2821   2035    3F CC104 2022 2022-03-03      COLOR  3.4657359028     A #> 2822   2035    3F CC104 2022 2022-03-03       COND  7.7336835708  <NA> #> 2823   2035    3F CC104 2022 2022-03-03         DO  1.8991179875  <NA> #> 2824   2035    3F CC104 2022 2022-03-03      DOSAT  4.2918283668  <NA> #> 2825   2035    3F CC104 2022 2022-03-03       NO23 -2.3538783874  <NA> #> 2826   2035    3F CC104 2022 2022-03-03      SALIN  0.1655144385  <NA> #> 2827   2035    3F CC104 2022 2022-03-03        TKN -0.4307829161  <NA> #> 2828   2035    3F CC104 2022 2022-03-03         TN -0.2943710606     + #> 2829   2035    3F CC104 2022 2022-03-03         TP -0.9416085399  <NA> #> 2830   2035    3F CC104 2022 2022-03-03        TSS  1.3862943611     I #> 2831   2035    3F CC104 2022 2022-03-03       TURB  2.2407096893     A #> 2832   2035    3F CC104 2022 2022-05-23      CHLAC  3.6109179126  <NA> #> 2833   2035    3F CC104 2022 2022-05-23      COLOR  4.1431347264     A #> 2834   2035    3F CC104 2022 2022-05-23       COND  9.7291936874  <NA> #> 2835   2035    3F CC104 2022 2022-05-23         DO  1.3987168811  <NA> #> 2836   2035    3F CC104 2022 2022-05-23      DOSAT  4.0217738694  <NA> #> 2837   2035    3F CC104 2022 2022-05-23       NO23 -3.1941832123  <NA> #> 2838   2035    3F CC104 2022 2022-05-23      SALIN  2.2854389342  <NA> #> 2839   2035    3F CC104 2022 2022-05-23        TKN  0.0953101798  <NA> #> 2840   2035    3F CC104 2022 2022-05-23         TN  0.1319050709     + #> 2841   2035    3F CC104 2022 2022-05-23         TP -0.3566749439  <NA> #> 2842   2035    3F CC104 2022 2022-05-23        TSS  1.9459101491     I #> 2843   2035    3F CC104 2022 2022-05-23       TURB  2.1633230257     A #> 2844   2035    3F CC104 2022 2022-06-27      CHLAC  1.2527629685     I #> 2845   2035    3F CC104 2022 2022-06-27      COLOR  4.0943445622     A #> 2846   2035    3F CC104 2022 2022-06-27       COND  6.9440872082  <NA> #> 2847   2035    3F CC104 2022 2022-06-27         DO  1.5706970841  <NA> #> 2848   2035    3F CC104 2022 2022-06-27      DOSAT  4.0724397268  <NA> #> 2849   2035    3F CC104 2022 2022-06-27       NO23 -1.5606477483  <NA> #> 2850   2035    3F CC104 2022 2022-06-27      SALIN -0.6733445533  <NA> #> 2851   2035    3F CC104 2022 2022-06-27        TKN  0.0953101798  <NA> #> 2852   2035    3F CC104 2022 2022-06-27         TN  0.2700271372     + #> 2853   2035    3F CC104 2022 2022-06-27         TP -0.3424903089  <NA> #> 2854   2035    3F CC104 2022 2022-06-27        TSS  2.3978952728  <NA> #> 2855   2035    3F CC104 2022 2022-06-27       TURB  2.7080502011  <NA> #> 2856   2035    3F CC104 2023 2023-01-09      CHLAC  2.2512917986  <NA> #> 2857   2035    3F CC104 2023 2023-01-09       COND  6.5666724298  <NA> #> 2858   2035    3F CC104 2023 2023-01-09         DO  1.7647307968  <NA> #> 2859   2035    3F CC104 2023 2023-01-09      DOSAT  4.1239033645  <NA> #> 2860   2035    3F CC104 2023 2023-01-09       NO23 -1.6094379124  <NA> #> 2861   2035    3F CC104 2023 2023-01-09      SALIN -1.0498221245  <NA> #> 2862   2035    3F CC104 2023 2023-01-09        TKN -0.2613647641  <NA> #> 2863   2035    3F CC104 2023 2023-01-09         TN -0.0304592075     + #> 2864   2035    3F CC104 2023 2023-01-09         TP -0.5621189182  <NA> #> 2865   2035    3F CC104 2023 2023-01-09        TSS  1.3862943611     I #> 2866   2035    3F CC104 2023 2023-01-09       TURB  2.5649493575  <NA> #> 2867   2035    3F CC104 2023 2023-03-14      CHLAC  2.8332133441  <NA> #> 2868   2035    3F CC104 2023 2023-03-14       COND  8.7237194369  <NA> #> 2869   2035    3F CC104 2023 2023-03-14         DO  1.0818051704  <NA> #> 2870   2035    3F CC104 2023 2023-03-14      DOSAT  3.5553480615  <NA> #> 2871   2035    3F CC104 2023 2023-03-14       NO23 -2.7646205526  <NA> #> 2872   2035    3F CC104 2023 2023-03-14      SALIN  1.2089603458  <NA> #> 2873   2035    3F CC104 2023 2023-03-14        TKN -0.1392620673  <NA> #> 2874   2035    3F CC104 2023 2023-03-14         TN -0.0693500781     + #> 2875   2035    3F CC104 2023 2023-03-14         TP -0.6733445533  <NA> #> 2876   2035    3F CC104 2023 2023-03-14        TSS  1.7917594692     I #> 2877   2035    3F CC104 2023 2023-03-14       TURB  2.0918640617  <NA> #> 2878   2035    3F CC104 2023 2023-05-10      CHLAC  4.2626798770  <NA> #> 2879   2035    3F CC104 2023 2023-05-10       COND  9.5445958677  <NA> #> 2880   2035    3F CC104 2023 2023-05-10         DO  0.7371640660  <NA> #> 2881   2035    3F CC104 2023 2023-05-10      DOSAT  3.2809112158  <NA> #> 2882   2035    3F CC104 2023 2023-05-10       NO23 -4.1351665567  <NA> #> 2883   2035    3F CC104 2023 2023-05-10      SALIN  2.0881534823  <NA> #> 2884   2035    3F CC104 2023 2023-05-10        TKN  0.1823215568  <NA> #> 2885   2035    3F CC104 2023 2023-05-10         TN  0.1955667835     + #> 2886   2035    3F CC104 2023 2023-05-10         TP -0.4155154440  <NA> #> 2887   2035    3F CC104 2023 2023-05-10        TSS  1.9459101491     I #> 2888   2035    3F CC104 2023 2023-05-10       TURB  2.0541237337  <NA> #> 2889   2035    3F CC104 2022 2022-01-24       COND  9.4453334396  <NA> #> 2890   2035    3F CC104 2022 2022-01-24         DO  2.3832429960  <NA> #> 2891   2035    3F CC104 2022 2022-01-24      DOSAT  4.7949637576  <NA> #> 2892   2035    3F CC104 2022 2022-01-24      SALIN  1.9865035460  <NA> #> 2893   2035    3F CC104 2022 2022-03-03       COND  8.9523465432  <NA> #> 2894   2035    3F CC104 2022 2022-03-03         DO  1.7544036827  <NA> #> 2895   2035    3F CC104 2022 2022-03-03      DOSAT  4.2224445648  <NA> #> 2896   2035    3F CC104 2022 2022-03-03      SALIN  1.4770487244  <NA> #> 2897   2035    3F CC104 2022 2022-05-23       COND  9.9213274707  <NA> #> 2898   2035    3F CC104 2022 2022-05-23         DO  1.2383742310  <NA> #> 2899   2035    3F CC104 2022 2022-05-23      DOSAT  3.8877303129  <NA> #> 2900   2035    3F CC104 2022 2022-05-23      SALIN  2.4923786646  <NA> #> 2901   2035    3F CC104 2022 2022-06-27       COND  7.7948231522  <NA> #> 2902   2035    3F CC104 2022 2022-06-27         DO  1.3660916538  <NA> #> 2903   2035    3F CC104 2022 2022-06-27      DOSAT  3.9019726696  <NA> #> 2904   2035    3F CC104 2022 2022-06-27      SALIN  0.2151113796  <NA> #> 2905   2035    3F CC104 2023 2023-01-09       COND  6.5042881735  <NA> #> 2906   2035    3F CC104 2023 2023-01-09         DO  1.9629077254  <NA> #> 2907   2035    3F CC104 2023 2023-01-09      DOSAT  4.3346729383  <NA> #> 2908   2035    3F CC104 2023 2023-01-09      SALIN -1.1086626245  <NA> #> 2909   2035    3F CC104 2023 2023-03-14       COND  9.1129480260  <NA> #> 2910   2035    3F CC104 2023 2023-03-14         DO  1.4134230285  <NA> #> 2911   2035    3F CC104 2023 2023-03-14      DOSAT  3.9100210028  <NA> #> 2912   2035    3F CC104 2023 2023-03-14      SALIN  1.6253112616  <NA> #> 2913   2035    3F CC104 2023 2023-05-10       COND  9.6875057942  <NA> #> 2914   2035    3F CC104 2023 2023-05-10         DO  1.1216775616  <NA> #> 2915   2035    3F CC104 2023 2023-05-10      DOSAT  3.6913763343  <NA> #> 2916   2035    3F CC104 2023 2023-05-10      SALIN  2.2417729536  <NA> #> 2917   2035    3F CC104 2022 2022-01-24       COND  8.4487001950  <NA> #> 2918   2035    3F CC104 2022 2022-01-24         DO  2.1447610078  <NA> #> 2919   2035    3F CC104 2022 2022-01-24      DOSAT  4.4624538838  <NA> #> 2920   2035    3F CC104 2022 2022-01-24      SALIN  0.9202827531  <NA> #> 2921   2035    3F CC104 2022 2022-03-03       COND  9.6867608690  <NA> #> 2922   2035    3F CC104 2022 2022-03-03         DO  1.4516138272  <NA> #> 2923   2035    3F CC104 2022 2022-03-03      DOSAT  3.9608131696  <NA> #> 2924   2035    3F CC104 2022 2022-03-03      SALIN  2.2449559802  <NA> #> 2925   2035    3F CC104 2022 2022-05-23       COND 10.0031066176  <NA> #> 2926   2035    3F CC104 2022 2022-05-23         DO  1.0986122887  <NA> #> 2927   2035    3F CC104 2022 2022-05-23      DOSAT  3.7518542533  <NA> #> 2928   2035    3F CC104 2022 2022-05-23      SALIN  2.9019708937  <NA> #> 2929   2035    3F CC104 2022 2022-06-27       COND  7.9745328441  <NA> #> 2930   2035    3F CC104 2022 2022-06-27         DO  1.6544112781  <NA> #> 2931   2035    3F CC104 2022 2022-06-27      DOSAT  4.2150861799  <NA> #> 2932   2035    3F CC104 2022 2022-06-27      SALIN  0.4054651081  <NA> #> 2933   2035    3F CC104 2023 2023-01-09       COND  7.0958932211  <NA> #> 2934   2035    3F CC104 2023 2023-01-09         DO  2.1575593209  <NA> #> 2935   2035    3F CC104 2023 2023-01-09      DOSAT  4.5464811896  <NA> #> 2936   2035    3F CC104 2023 2023-01-09      SALIN -0.5108256238  <NA> #> 2937   2035    3F CC104 2023 2023-03-14       COND  9.4841009891  <NA> #> 2938   2035    3F CC104 2023 2023-03-14         DO  0.9820784724  <NA> #> 2939   2035    3F CC104 2023 2023-03-14      DOSAT  3.5292973843  <NA> #> 2940   2035    3F CC104 2023 2023-03-14      SALIN  2.0215475633  <NA> #> 2941   2035    3F CC104 2023 2023-05-10       COND  9.8215722593  <NA> #> 2942   2035    3F CC104 2023 2023-05-10         DO  1.3660916538  <NA> #> 2943   2035    3F CC104 2023 2023-05-10      DOSAT  3.9627161197  <NA> #> 2944   2035    3F CC104 2023 2023-05-10      SALIN  2.3860067011  <NA> #> 2945   2035    3F CC104 2014 2014-05-28       COND  7.0817085861  <NA> #> 2946   2035    3F CC104 2014 2014-05-28         DO  1.5560371357  <NA> #> 2947   2035    3F CC104 2014 2014-05-28      DOSAT  4.0145795938     + #> 2948   2035    3F CC104 2014 2014-05-28      SALIN -0.5276327421  <NA> #> 2949   2035    3F CC104 2014 2014-10-02       COND  5.9506425526  <NA> #> 2950   2035    3F CC104 2014 2014-10-02         DO  1.6770965609  <NA> #> 2951   2035    3F CC104 2014 2014-10-02      DOSAT  4.2061840440     + #> 2952   2035    3F CC104 2014 2014-10-02      SALIN -1.7147984281  <NA> #> 2953   2035    3F CC104 2016 2016-06-02       COND  6.8068293604  <NA> #> 2954   2035    3F CC104 2016 2016-06-02         DO  1.3837912309  <NA> #> 2955   2035    3F CC104 2016 2016-06-02      DOSAT  3.8501476017     + #> 2956   2035    3F CC104 2016 2016-06-02      SALIN -0.8209805521  <NA> #> 2957   2035    3F CC104 2016 2016-09-21       COND  6.3664704477  <NA> #> 2958   2035    3F CC104 2016 2016-09-21         DO  1.6389967147  <NA> #> 2959   2035    3F CC104 2016 2016-09-21      DOSAT  4.1697612015     + #> 2960   2035    3F CC104 2016 2016-09-21      SALIN -1.2729656758  <NA> #> 2961   2035    3F CC104 2017 2017-05-09       COND  6.9791452751  <NA> #> 2962   2035    3F CC104 2017 2017-05-09         DO  1.4134230285  <NA> #> 2963   2035    3F CC104 2017 2017-05-09      DOSAT  3.8220982979     + #> 2964   2035    3F CC104 2017 2017-05-09      SALIN -0.6348782724  <NA> #> 2965   2035    3F CC104 2017 2017-09-27       COND  6.1654178542  <NA> #> 2966   2035    3F CC104 2017 2017-09-27         DO  1.6937790609  <NA> #> 2967   2035    3F CC104 2017 2017-09-27      DOSAT  4.2195077052     + #> 2968   2035    3F CC104 2017 2017-09-27      SALIN -1.4696759701  <NA> #> 2969   2035    3F CC104 2018 2018-06-04       COND  6.2672005485  <NA> #> 2970   2035    3F CC104 2018 2018-06-04         DO  1.6808279085  <NA> #> 2971   2035    3F CC104 2018 2018-06-04      DOSAT  4.2209772132     + #> 2972   2035    3F CC104 2018 2018-06-04      SALIN -1.3862943611  <NA> #> 2973   2035    3F CC104 2018 2018-09-12       COND  6.2265366693  <NA> #> 2974   2035    3F CC104 2018 2018-09-12         DO  1.7749523509  <NA> #> 2975   2035    3F CC104 2018 2018-09-12      DOSAT  4.3040650932     + #> 2976   2035    3F CC104 2018 2018-09-12      SALIN -1.4271163556  <NA> #> 2977   2045    3M  CC15 2018 2018-03-07      CHLAC  2.2617630985  <NA> #> 2978   2045    3M  CC15 2018 2018-03-07       COND 10.0150289273  <NA> #> 2979   2045    3M  CC15 2018 2018-03-07         DO  2.0281482473  <NA> #> 2980   2045    3M  CC15 2018 2018-03-07      DOSAT  4.5475410732  <NA> #> 2981   2045    3M  CC15 2018 2018-03-07       NO23 -5.5214609179     U #> 2982   2045    3M  CC15 2018 2018-03-07      SALIN  2.6595599919     + #> 2983   2045    3M  CC15 2018 2018-03-07        TKN -0.1743533871  <NA> #> 2984   2045    3M  CC15 2018 2018-03-07         TN -0.1719752647     + #> 2985   2045    3M  CC15 2018 2018-03-07         TP -1.8325814637  <NA> #> 2986   2045    3M  CC15 2018 2018-03-07        TSS  1.0986122887     U #> 2987   2045    3M  CC15 2018 2018-03-07       TURB  1.2809338455  <NA> #> 2988   2045    3M  CC15 2018 2018-04-09      CHLAC  1.8870696490  <NA> #> 2989   2045    3M  CC15 2018 2018-04-09       COND 10.4012279368  <NA> #> 2990   2045    3M  CC15 2018 2018-04-09         DO  1.7227665977  <NA> #> 2991   2045    3M  CC15 2018 2018-04-09      DOSAT  4.3438054219  <NA> #> 2992   2045    3M  CC15 2018 2018-04-09       NO23 -5.5214609179     I #> 2993   2045    3M  CC15 2018 2018-04-09      SALIN  3.0017143452     + #> 2994   2045    3M  CC15 2018 2018-04-09        TKN -0.2357223335  <NA> #> 2995   2045    3M  CC15 2018 2018-04-09         TN -0.2306718177     + #> 2996   2045    3M  CC15 2018 2018-04-09         TP -1.5606477483  <NA> #> 2997   2045    3M  CC15 2018 2018-04-09        TSS  2.7080502011  <NA> #> 2998   2045    3M  CC15 2018 2018-04-09       TURB  1.8718021769     A #> 2999   2045    3M  CC15 2018 2018-05-24      CHLAC  2.3978952728  <NA> #> 3000   2045    3M  CC15 2018 2018-05-24       COND  9.3056505518  <NA> #> 3001   2045    3M  CC15 2018 2018-05-24         DO  1.9198594719  <NA> #> 3002   2045    3M  CC15 2018 2018-05-24      DOSAT  4.4589876758  <NA> #> 3003   2045    3M  CC15 2018 2018-05-24       NO23 -3.3524072175  <NA> #> 3004   2045    3M  CC15 2018 2018-05-24      SALIN  1.7833912196     + #> 3005   2045    3M  CC15 2018 2018-05-24        TKN -0.1392620673  <NA> #> 3006   2045    3M  CC15 2018 2018-05-24         TN -0.0998203353     + #> 3007   2045    3M  CC15 2018 2018-05-24         TP -1.6094379124  <NA> #> 3008   2045    3M  CC15 2018 2018-05-24        TSS  1.7917594692     I #> 3009   2045    3M  CC15 2018 2018-05-24       TURB  1.3350010667  <NA> #> 3010   2045    3M  CC15 2018 2018-05-24      SALIN  1.8991179875     + #> 3011   2045    3M  CC15 2018 2018-05-24       COND  9.4091912307  <NA> #> 3012   2045    3M  CC15 2018 2018-05-24         DO  1.7833912196  <NA> #> 3013   2045    3M  CC15 2018 2018-05-24      DOSAT  4.3630986248  <NA> #> 3014   2045    3M  CC15 2018 2018-05-24       COND  9.3056505518  <NA> #> 3015   2045    3M  CC15 2018 2018-05-24         DO  1.9198594719  <NA> #> 3016   2045    3M  CC15 2018 2018-05-24      DOSAT  4.4589876758  <NA> #> 3017   2045    3M  CC15 2018 2018-05-24      SALIN  1.7833912196     + #> 3018   2045    3M  CC15 2018 2018-07-23      CHLAC  2.0149030205  <NA> #> 3019   2045    3M  CC15 2018 2018-07-23       COND  6.5087691370  <NA> #> 3020   2045    3M  CC15 2018 2018-07-23         DO  1.7800242130  <NA> #> 3021   2045    3M  CC15 2018 2018-07-23      DOSAT  4.3567088267  <NA> #> 3022   2045    3M  CC15 2018 2018-07-23       NO23 -1.9661128564  <NA> #> 3023   2045    3M  CC15 2018 2018-07-23      SALIN -1.1394342832  <NA> #> 3024   2045    3M  CC15 2018 2018-07-23        TKN  0.1823215568  <NA> #> 3025   2045    3M  CC15 2018 2018-07-23         TN  0.2926696140     + #> 3026   2045    3M  CC15 2018 2018-07-23         TP -1.1394342832  <NA> #> 3027   2045    3M  CC15 2018 2018-07-23        TSS  1.3862943611     I #> 3028   2045    3M  CC15 2018 2018-07-23       TURB  1.3083328197  <NA> #> 3029   2045    3M  CC15 2018 2018-08-21      CHLAC  2.0794415417  <NA> #> 3030   2045    3M  CC15 2018 2018-08-21       COND  6.4393503711  <NA> #> 3031   2045    3M  CC15 2018 2018-08-21         DO  1.6601310267  <NA> #> 3032   2045    3M  CC15 2018 2018-08-21      DOSAT  4.2341065046  <NA> #> 3033   2045    3M  CC15 2018 2018-08-21       NO23 -2.6736487744  <NA> #> 3034   2045    3M  CC15 2018 2018-08-21      SALIN -1.2039728043  <NA> #> 3035   2045    3M  CC15 2018 2018-08-21        TKN  0.0953101798  <NA> #> 3036   2045    3M  CC15 2018 2018-08-21         TN  0.1561486825     + #> 3037   2045    3M  CC15 2018 2018-08-21         TP -1.2378743560  <NA> #> 3038   2045    3M  CC15 2018 2018-08-21        TSS  1.0986122887     I #> 3039   2045    3M  CC15 2018 2018-08-21       TURB  1.0986122887  <NA> #> 3040   2045    3M  CC15 2018 2018-08-21       COND  6.4264884575  <NA> #> 3041   2045    3M  CC15 2018 2018-08-21         DO  1.6114359151  <NA> #> 3042   2045    3M  CC15 2018 2018-08-21      DOSAT  4.1774594689  <NA> #> 3043   2045    3M  CC15 2018 2018-08-21      SALIN -1.2039728043  <NA> #> 3044   2045    3M  CC15 2019 2019-02-07      CHLAC  3.2188758249     A #> 3045   2045    3M  CC15 2019 2019-02-07       COND  8.6916505732  <NA> #> 3046   2045    3M  CC15 2019 2019-02-07       NO23 -5.1159958098     I #> 3047   2045    3M  CC15 2019 2019-02-07      SALIN  1.1755733298  <NA> #> 3048   2045    3M  CC15 2019 2019-02-07        TKN  0.0953101798  <NA> #> 3049   2045    3M  CC15 2019 2019-02-07         TN  0.0989399479     + #> 3050   2045    3M  CC15 2019 2019-02-07         TP -1.6607312068  <NA> #> 3051   2045    3M  CC15 2019 2019-02-07        TSS  2.3025850930     I #> 3052   2045    3M  CC15 2019 2019-02-07       TURB  2.0281482473  <NA> #> 3053   2045    3M  CC15 2019 2019-03-13      CHLAC  1.8870696490  <NA> #> 3054   2045    3M  CC15 2019 2019-03-13       COND  9.4304392931  <NA> #> 3055   2045    3M  CC15 2019 2019-03-13         DO  1.8961194846  <NA> #> 3056   2045    3M  CC15 2019 2019-03-13      DOSAT  4.4188406078  <NA> #> 3057   2045    3M  CC15 2019 2019-03-13       NO23 -5.2983173665     I #> 3058   2045    3M  CC15 2019 2019-03-13      SALIN  1.9657127764  <NA> #> 3059   2045    3M  CC15 2019 2019-03-13        TKN -0.1625189295  <NA> #> 3060   2045    3M  CC15 2019 2019-03-13         TN -0.1578240852     + #> 3061   2045    3M  CC15 2019 2019-03-13         TP -1.8325814637  <NA> #> 3062   2045    3M  CC15 2019 2019-03-13        TSS  2.0794415417     I #> 3063   2045    3M  CC15 2019 2019-03-13       TURB  1.5892352051  <NA> #> 3064   2045    3M  CC15 2019 2019-04-23      CHLAC  1.7749523509  <NA> #> 3065   2045    3M  CC15 2019 2019-04-23       COND  9.9110588180  <NA> #> 3066   2045    3M  CC15 2019 2019-04-23         DO  1.8562979904  <NA> #> 3067   2045    3M  CC15 2019 2019-04-23      DOSAT  4.3845235149  <NA> #> 3068   2045    3M  CC15 2019 2019-04-23       NO23 -5.5214609179     U #> 3069   2045    3M  CC15 2019 2019-04-23      SALIN  2.4882344399  <NA> #> 3070   2045    3M  CC15 2019 2019-04-23        TKN -0.2744368457  <NA> #> 3071   2045    3M  CC15 2019 2019-04-23         TN -0.2718087233     + #> 3072   2045    3M  CC15 2019 2019-04-23         TP -1.6607312068  <NA> #> 3073   2045    3M  CC15 2019 2019-04-23        TSS  2.0794415417     I #> 3074   2045    3M  CC15 2019 2019-04-23       TURB  1.4586150227  <NA> #> 3075   2045    3M  CC15 2019 2019-07-22      CHLAC  2.4849066498  <NA> #> 3076   2045    3M  CC15 2019 2019-07-22       COND  8.5083542427  <NA> #> 3077   2045    3M  CC15 2019 2019-07-22         DO  1.7227665977  <NA> #> 3078   2045    3M  CC15 2019 2019-07-22      DOSAT  4.3174881135  <NA> #> 3079   2045    3M  CC15 2019 2019-07-22       NO23 -3.5065578973  <NA> #> 3080   2045    3M  CC15 2019 2019-07-22      SALIN  0.9707789172  <NA> #> 3081   2045    3M  CC15 2019 2019-07-22        TKN -0.0512932944  <NA> #> 3082   2045    3M  CC15 2019 2019-07-22         TN -0.0202027073     + #> 3083   2045    3M  CC15 2019 2019-07-22         TP -1.1086626245  <NA> #> 3084   2045    3M  CC15 2019 2019-07-22        TSS  1.6094379124     I #> 3085   2045    3M  CC15 2019 2019-07-22       TURB  1.3862943611  <NA> #> 3086   2045    3M  CC15 2019 2019-09-04       COND  7.2896105215  <NA> #> 3087   2045    3M  CC15 2019 2019-09-04         DO  1.6213664833  <NA> #> 3088   2045    3M  CC15 2019 2019-09-04      DOSAT  4.2061840440  <NA> #> 3089   2045    3M  CC15 2019 2019-09-04       NO23 -2.4191189092  <NA> #> 3090   2045    3M  CC15 2019 2019-09-04      SALIN -0.3147107448  <NA> #> 3091   2045    3M  CC15 2019 2019-09-04        TKN  0.1823215568  <NA> #> 3092   2045    3M  CC15 2019 2019-09-04         TN  0.2538667240     + #> 3093   2045    3M  CC15 2019 2019-09-04         TP -0.9675840263  <NA> #> 3094   2045    3M  CC15 2019 2019-09-04        TSS  1.0986122887     I #> 3095   2045    3M  CC15 2019 2019-09-04       TURB  1.0986122887  <NA> #> 3096   2045    3M  CC15 2020 2020-02-18      CHLAC  2.7080502011  <NA> #> 3097   2045    3M  CC15 2020 2020-02-18       COND 10.0136863448  <NA> #> 3098   2045    3M  CC15 2020 2020-02-18         DO  1.9358598132  <NA> #> 3099   2045    3M  CC15 2020 2020-02-18      DOSAT  4.5272086445  <NA> #> 3100   2045    3M  CC15 2020 2020-02-18       NO23 -4.8283137373     I #> 3101   2045    3M  CC15 2020 2020-02-18      SALIN  2.5967461315  <NA> #> 3102   2045    3M  CC15 2020 2020-02-18        TKN -0.1165338163  <NA> #> 3103   2045    3M  CC15 2020 2020-02-18         TN -0.1120495038     + #> 3104   2045    3M  CC15 2020 2020-02-18         TP -1.6094379124  <NA> #> 3105   2045    3M  CC15 2020 2020-02-18        TSS  2.7080502011  <NA> #> 3106   2045    3M  CC15 2020 2020-02-18       TURB  1.7227665977  <NA> #> 3107   2045    3M  CC15 2020 2020-02-18       COND 10.0120728629  <NA> #> 3108   2045    3M  CC15 2020 2020-02-18         DO  1.9227877316  <NA> #> 3109   2045    3M  CC15 2020 2020-02-18      DOSAT  4.5086592856  <NA> #> 3110   2045    3M  CC15 2020 2020-02-18      SALIN  2.5952547070  <NA> #> 3111   2045    3M  CC15 2020 2020-06-09      CHLAC  2.4849066498  <NA> #> 3112   2045    3M  CC15 2020 2020-06-09       COND  9.2513863414  <NA> #> 3113   2045    3M  CC15 2020 2020-06-09         DO  1.9315214116  <NA> #> 3114   2045    3M  CC15 2020 2020-06-09      DOSAT  4.5239601306  <NA> #> 3115   2045    3M  CC15 2020 2020-06-09       NO23 -3.3813947544  <NA> #> 3116   2045    3M  CC15 2020 2020-06-09      SALIN  1.7664416612  <NA> #> 3117   2045    3M  CC15 2020 2020-06-09        TKN -0.0304592075  <NA> #> 3118   2045    3M  CC15 2020 2020-06-09         TN  0.0039920213     + #> 3119   2045    3M  CC15 2020 2020-06-09         TP -1.4696759701  <NA> #> 3120   2045    3M  CC15 2020 2020-06-09        TSS  1.0986122887     I #> 3121   2045    3M  CC15 2020 2020-06-09       TURB  0.9162907319  <NA> #> 3122   2045    3M  CC15 2020 2020-06-09       COND  9.5815590414  <NA> #> 3123   2045    3M  CC15 2020 2020-06-09         DO  1.6544112781  <NA> #> 3124   2045    3M  CC15 2020 2020-06-09      DOSAT  4.2076732475  <NA> #> 3125   2045    3M  CC15 2020 2020-06-09      SALIN  2.1552445051  <NA> #> 3126   2045    3M  CC15 2020 2020-08-10       COND  9.2688922589  <NA> #> 3127   2045    3M  CC15 2020 2020-08-10         DO  1.6370530795  <NA> #> 3128   2045    3M  CC15 2020 2020-08-10      DOSAT  4.2710950740  <NA> #> 3129   2045    3M  CC15 2020 2020-08-10      SALIN -1.4567168254  <NA> #> 3130   2045    3M  CC15 2020 2020-08-10       COND  9.4812068515  <NA> #> 3131   2045    3M  CC15 2020 2020-08-10         DO  1.4398351280  <NA> #> 3132   2045    3M  CC15 2020 2020-08-10      DOSAT  4.0758410907  <NA> #> 3133   2045    3M  CC15 2020 2020-08-10      SALIN  0.2207406667  <NA> #> 3134   2045    3M  CC15 2020 2020-09-22      CHLAC  2.2192034841  <NA> #> 3135   2045    3M  CC15 2020 2020-09-22       COND  6.5750758406  <NA> #> 3136   2045    3M  CC15 2020 2020-09-22         DO  1.7934247485  <NA> #> 3137   2045    3M  CC15 2020 2020-09-22      DOSAT  4.3359826962  <NA> #> 3138   2045    3M  CC15 2020 2020-09-22       NO23 -2.7968814148  <NA> #> 3139   2045    3M  CC15 2020 2020-09-22      SALIN -1.0498221245  <NA> #> 3140   2045    3M  CC15 2020 2020-09-22        TKN  0.2623642645  <NA> #> 3141   2045    3M  CC15 2020 2020-09-22         TN  0.3082197237     + #> 3142   2045    3M  CC15 2020 2020-09-22         TP -0.9942522733  <NA> #> 3143   2045    3M  CC15 2020 2020-09-22        TSS  1.3862943611     I #> 3144   2045    3M  CC15 2020 2020-09-22       TURB  1.2809338455  <NA> #> 3145   2045    3M  CC15 2020 2020-10-20      CHLAC  3.0445224377  <NA> #> 3146   2045    3M  CC15 2020 2020-10-20       COND  8.3209349689  <NA> #> 3147   2045    3M  CC15 2020 2020-10-20         DO  1.7119945008  <NA> #> 3148   2045    3M  CC15 2020 2020-10-20      DOSAT  4.2640873368  <NA> #> 3149   2045    3M  CC15 2020 2020-10-20       NO23 -2.5010360317  <NA> #> 3150   2045    3M  CC15 2020 2020-10-20      SALIN  0.7747271676  <NA> #> 3151   2045    3M  CC15 2020 2020-10-20        TKN  0.2623642645  <NA> #> 3152   2045    3M  CC15 2020 2020-10-20         TN  0.3235317253     + #> 3153   2045    3M  CC15 2020 2020-10-20         TP -0.9942522733  <NA> #> 3154   2045    3M  CC15 2020 2020-10-20        TSS  1.6094379124     I #> 3155   2045    3M  CC15 2020 2020-10-20       TURB  1.2809338455  <NA> #> 3156   2045    3M  CC15 2020 2020-12-14      CHLAC  2.6390573296  <NA> #> 3157   2045    3M  CC15 2020 2020-12-14       COND  9.2314166976  <NA> #> 3158   2045    3M  CC15 2020 2020-12-14         DO  2.0930978681  <NA> #> 3159   2045    3M  CC15 2020 2020-12-14      DOSAT  4.5695430083  <NA> #> 3160   2045    3M  CC15 2020 2020-12-14       NO23 -4.9618451299     I #> 3161   2045    3M  CC15 2020 2020-12-14      SALIN  1.7526720805  <NA> #> 3162   2045    3M  CC15 2020 2020-12-14        TKN  0.0000000000  <NA> #> 3163   2045    3M  CC15 2020 2020-12-14         TN  0.0039920213     + #> 3164   2045    3M  CC15 2020 2020-12-14         TP -1.4696759701  <NA> #> 3165   2045    3M  CC15 2020 2020-12-14        TSS  1.6094379124     I #> 3166   2045    3M  CC15 2020 2020-12-14       TURB  1.3609765531     A #> 3167   2045    3M  CC15 2021 2021-02-03      CHLAC  1.7404661748  <NA> #> 3168   2045    3M  CC15 2021 2021-02-03       COND  9.8506140629  <NA> #> 3169   2045    3M  CC15 2021 2021-02-03         DO  2.1424163408  <NA> #> 3170   2045    3M  CC15 2021 2021-02-03      DOSAT  4.5528237056  <NA> #> 3171   2045    3M  CC15 2021 2021-02-03       NO23 -5.5214609179     U #> 3172   2045    3M  CC15 2021 2021-02-03      SALIN  2.4248027257  <NA> #> 3173   2045    3M  CC15 2021 2021-02-03        TKN -0.3424903089  <NA> #> 3174   2045    3M  CC15 2021 2021-02-03         TN -0.3396773676     + #> 3175   2045    3M  CC15 2021 2021-02-03         TP -1.9661128564  <NA> #> 3176   2045    3M  CC15 2021 2021-02-03        TSS  1.3862943611     I #> 3177   2045    3M  CC15 2021 2021-02-03       TURB  1.0296194172  <NA> #> 3178   2045    3M  CC15 2021 2021-03-09      CHLAC  2.4849066498  <NA> #> 3179   2045    3M  CC15 2021 2021-03-09       COND  9.8787336881  <NA> #> 3180   2045    3M  CC15 2021 2021-03-09         DO  2.1690537004  <NA> #> 3181   2045    3M  CC15 2021 2021-03-09      DOSAT  4.6510991179  <NA> #> 3182   2045    3M  CC15 2021 2021-03-09       NO23 -5.5214609179     I #> 3183   2045    3M  CC15 2021 2021-03-09      SALIN  2.4544474423  <NA> #> 3184   2045    3M  CC15 2021 2021-03-09        TKN  0.0000000000  <NA> #> 3185   2045    3M  CC15 2021 2021-03-09         TN  0.0039920213     + #> 3186   2045    3M  CC15 2021 2021-03-09         TP -1.4696759701  <NA> #> 3187   2045    3M  CC15 2021 2021-03-09        TSS  3.2958368660  <NA> #> 3188   2045    3M  CC15 2021 2021-03-09       TURB  2.3978952728     A #> 3189   2045    3M  CC15 2021 2021-05-05      CHLAC  1.8082887712  <NA> #> 3190   2045    3M  CC15 2021 2021-05-05       COND 10.2487071336  <NA> #> 3191   2045    3M  CC15 2021 2021-05-05         DO  1.8082887712  <NA> #> 3192   2045    3M  CC15 2021 2021-05-05      DOSAT  4.4986979415  <NA> #> 3193   2045    3M  CC15 2021 2021-05-05       NO23 -5.5214609179     U #> 3194   2045    3M  CC15 2021 2021-05-05      SALIN  2.8489708922  <NA> #> 3195   2045    3M  CC15 2021 2021-05-05        TKN -0.2231435513  <NA> #> 3196   2045    3M  CC15 2021 2021-05-05         TN -0.2206466711     + #> 3197   2045    3M  CC15 2021 2021-05-05         TP -1.6094379124  <NA> #> 3198   2045    3M  CC15 2021 2021-05-05        TSS  1.9459101491     I #> 3199   2045    3M  CC15 2021 2021-05-05       TURB  1.3350010667  <NA> #> 3200   2045    3M  CC15 2021 2021-06-03      CHLAC  1.8245492921  <NA> #> 3201   2045    3M  CC15 2021 2021-06-03       COND 10.3770473511  <NA> #> 3202   2045    3M  CC15 2021 2021-06-03         DO  1.7715567619  <NA> #> 3203   2045    3M  CC15 2021 2021-06-03      DOSAT  4.4331949212  <NA> #> 3204   2045    3M  CC15 2021 2021-06-03       NO23 -5.5214609179     U #> 3205   2045    3M  CC15 2021 2021-06-03      SALIN  2.9937302709  <NA> #> 3206   2045    3M  CC15 2021 2021-06-03        TKN -0.1743533871  <NA> #> 3207   2045    3M  CC15 2021 2021-06-03         TN -0.1719752647     + #> 3208   2045    3M  CC15 2021 2021-06-03         TP -1.5606477483  <NA> #> 3209   2045    3M  CC15 2021 2021-06-03        TSS  1.7917594692     I #> 3210   2045    3M  CC15 2021 2021-06-03       TURB  1.2237754316  <NA> #> 3211   2045    3M  CC15 2021 2021-07-01      CHLAC  2.1860512767  <NA> #> 3212   2045    3M  CC15 2021 2021-07-01       COND 10.1292277297  <NA> #> 3213   2045    3M  CC15 2021 2021-07-01         DO  1.7351891177  <NA> #> 3214   2045    3M  CC15 2021 2021-07-01      DOSAT  4.3541414312  <NA> #> 3215   2045    3M  CC15 2021 2021-07-01       NO23 -5.5214609179     U #> 3216   2045    3M  CC15 2021 2021-07-01      SALIN  2.7232671669  <NA> #> 3217   2045    3M  CC15 2021 2021-07-01        TKN -0.4155154440  <NA> #> 3218   2045    3M  CC15 2021 2021-07-01         TN -0.4124897230     + #> 3219   2045    3M  CC15 2021 2021-07-01         TP -1.5606477483  <NA> #> 3220   2045    3M  CC15 2021 2021-07-01        TSS  1.0986122887     U #> 3221   2045    3M  CC15 2021 2021-07-01       TURB  1.3083328197  <NA> #> 3222   2045    3M  CC15 2021 2021-07-29      CHLAC  1.5892352051  <NA> #> 3223   2045    3M  CC15 2021 2021-07-29       COND  7.4764723812  <NA> #> 3224   2045    3M  CC15 2021 2021-07-29         DO  1.4303112465  <NA> #> 3225   2045    3M  CC15 2021 2021-07-29      DOSAT  4.0145795938  <NA> #> 3226   2045    3M  CC15 2021 2021-07-29       NO23 -2.4769384801  <NA> #> 3227   2045    3M  CC15 2021 2021-07-29      SALIN -0.1165338163  <NA> #> 3228   2045    3M  CC15 2021 2021-07-29        TKN  0.3364722366  <NA> #> 3229   2045    3M  CC15 2021 2021-07-29         TN  0.3947411447     + #> 3230   2045    3M  CC15 2021 2021-07-29         TP -0.4780358009  <NA> #> 3231   2045    3M  CC15 2021 2021-07-29        TSS  1.7917594692     I #> 3232   2045    3M  CC15 2021 2021-07-29       TURB  1.6292405397  <NA> #> 3233   2045    3M  CC15 2021 2021-08-25      CHLAC  2.7725887222  <NA> #> 3234   2045    3M  CC15 2021 2021-08-25       COND  6.9107507880  <NA> #> 3235   2045    3M  CC15 2021 2021-08-25         DO  1.3376291891  <NA> #> 3236   2045    3M  CC15 2021 2021-08-25      DOSAT  3.9120230054  <NA> #> 3237   2045    3M  CC15 2021 2021-08-25       NO23 -2.9565115604  <NA> #> 3238   2045    3M  CC15 2021 2021-08-25      SALIN -0.7133498879  <NA> #> 3239   2045    3M  CC15 2021 2021-08-25        TKN  0.0953101798  <NA> #> 3240   2045    3M  CC15 2021 2021-08-25         TN  0.1414995623     + #> 3241   2045    3M  CC15 2021 2021-08-25         TP -0.8915981193  <NA> #> 3242   2045    3M  CC15 2021 2021-08-25        TSS  1.0986122887     I #> 3243   2045    3M  CC15 2021 2021-08-25       TURB  1.0647107370  <NA> #> 3244   2045    3M  CC15 2021 2021-09-23      CHLAC  2.2300144002  <NA> #> 3245   2045    3M  CC15 2021 2021-09-23       COND  6.2653012127  <NA> #> 3246   2045    3M  CC15 2021 2021-09-23         DO  1.4060969884  <NA> #> 3247   2045    3M  CC15 2021 2021-09-23      DOSAT  3.9550824949  <NA> #> 3248   2045    3M  CC15 2021 2021-09-23       NO23 -3.0365542681  <NA> #> 3249   2045    3M  CC15 2021 2021-09-23      SALIN -1.3862943611  <NA> #> 3250   2045    3M  CC15 2021 2021-09-23        TKN  0.0953101798  <NA> #> 3251   2045    3M  CC15 2021 2021-09-23         TN  0.1380212979     + #> 3252   2045    3M  CC15 2021 2021-09-23         TP -1.3093333200  <NA> #> 3253   2045    3M  CC15 2021 2021-09-23        TSS  1.3862943611     I #> 3254   2045    3M  CC15 2021 2021-09-23       TURB  1.2527629685  <NA> #> 3255   2045    3M  CC15 2021 2021-10-21      CHLAC  3.5263605246  <NA> #> 3256   2045    3M  CC15 2021 2021-10-21       COND  8.7135820054  <NA> #> 3257   2045    3M  CC15 2021 2021-10-21         DO  1.7732559977  <NA> #> 3258   2045    3M  CC15 2021 2021-10-21      DOSAT  4.2918283668  <NA> #> 3259   2045    3M  CC15 2021 2021-10-21       NO23 -2.9957322736  <NA> #> 3260   2045    3M  CC15 2021 2021-10-21      SALIN  1.1939224685  <NA> #> 3261   2045    3M  CC15 2021 2021-10-21        TKN  0.2623642645  <NA> #> 3262   2045    3M  CC15 2021 2021-10-21         TN  0.3001045925     + #> 3263   2045    3M  CC15 2021 2021-10-21         TP -1.1711829815  <NA> #> 3264   2045    3M  CC15 2021 2021-10-21        TSS  1.6094379124     I #> 3265   2045    3M  CC15 2021 2021-10-21       TURB  1.2809338455  <NA> #> 3266   2045    3M  CC15 2021 2021-11-22       COND  9.2692694395  <NA> #> 3267   2045    3M  CC15 2021 2021-11-22         DO  1.9516081702  <NA> #> 3268   2045    3M  CC15 2021 2021-11-22      DOSAT  4.4647580323  <NA> #> 3269   2045    3M  CC15 2021 2021-11-22       NO23 -4.7105307016     I #> 3270   2045    3M  CC15 2021 2021-11-22      SALIN  1.7917594692  <NA> #> 3271   2045    3M  CC15 2021 2021-11-22        TKN -0.1863295782  <NA> #> 3272   2045    3M  CC15 2021 2021-11-22         TN -0.1815218766     + #> 3273   2045    3M  CC15 2021 2021-11-22         TP -1.7147984281  <NA> #> 3274   2045    3M  CC15 2021 2021-11-22        TSS  1.0986122887     I #> 3275   2045    3M  CC15 2021 2021-11-22       TURB  0.9932517730  <NA> #> 3276   2045    3M  CC15 2022 2022-02-22      CHLAC  1.5040773968  <NA> #> 3277   2045    3M  CC15 2022 2022-02-22       COND 10.3013572215  <NA> #> 3278   2045    3M  CC15 2022 2022-02-22         DO  1.9169226122  <NA> #> 3279   2045    3M  CC15 2022 2022-02-22      DOSAT  4.4986979415  <NA> #> 3280   2045    3M  CC15 2022 2022-02-22       NO23 -5.5214609179     U #> 3281   2045    3M  CC15 2022 2022-02-22      SALIN  2.9139797717  <NA> #> 3282   2045    3M  CC15 2022 2022-02-22        TKN -0.3285040670  <NA> #> 3283   2045    3M  CC15 2022 2022-02-22         TN -0.3257301401     + #> 3284   2045    3M  CC15 2022 2022-02-22         TP -2.0402208285  <NA> #> 3285   2045    3M  CC15 2022 2022-02-22        TSS  2.3978952728  <NA> #> 3286   2045    3M  CC15 2022 2022-02-22       TURB  1.3083328197  <NA> #> 3287   2045    3M  CC15 2022 2022-04-20      CHLAC  0.4700036292     U #> 3288   2045    3M  CC15 2022 2022-04-20       COND 10.5349454823  <NA> #> 3289   2045    3M  CC15 2022 2022-04-20         DO  1.6919391339  <NA> #> 3290   2045    3M  CC15 2022 2022-04-20      DOSAT  4.2972854062  <NA> #> 3291   2045    3M  CC15 2022 2022-04-20       NO23 -5.5214609179     U #> 3292   2045    3M  CC15 2022 2022-04-20      SALIN  3.1722034167  <NA> #> 3293   2045    3M  CC15 2022 2022-04-20        TKN -0.1508228897  <NA> #> 3294   2045    3M  CC15 2022 2022-04-20         TN -0.1485000083     + #> 3295   2045    3M  CC15 2022 2022-04-20         TP -1.9661128564  <NA> #> 3296   2045    3M  CC15 2022 2022-04-20        TSS  2.5649493575  <NA> #> 3297   2045    3M  CC15 2022 2022-04-20       TURB  1.8082887712  <NA> #> 3298   2045    3M  CC15 2022 2022-06-07      CHLAC  1.5260563035  <NA> #> 3299   2045    3M  CC15 2022 2022-06-07       COND 10.2575891884  <NA> #> 3300   2045    3M  CC15 2022 2022-06-07         DO  1.7137979278  <NA> #> 3301   2045    3M  CC15 2022 2022-06-07      DOSAT  4.3870141762  <NA> #> 3302   2045    3M  CC15 2022 2022-06-07       NO23 -4.8283137373     I #> 3303   2045    3M  CC15 2022 2022-06-07      SALIN  2.8604851241  <NA> #> 3304   2045    3M  CC15 2022 2022-06-07        TKN -0.3710636814  <NA> #> 3305   2045    3M  CC15 2022 2022-06-07         TN -0.3652833185     + #> 3306   2045    3M  CC15 2022 2022-06-07         TP -1.5606477483  <NA> #> 3307   2045    3M  CC15 2022 2022-06-07        TSS  2.3025850930  <NA> #> 3308   2045    3M  CC15 2022 2022-06-07       TURB  0.9932517730  <NA> #> 3309   2045    3M  CC15 2022 2022-08-15      CHLAC  3.2188758249  <NA> #> 3310   2045    3M  CC15 2022 2022-08-15       COND  8.2671921859  <NA> #> 3311   2045    3M  CC15 2022 2022-08-15         DO  1.6094379124  <NA> #> 3312   2045    3M  CC15 2022 2022-08-15      DOSAT  4.2136079830  <NA> #> 3313   2045    3M  CC15 2022 2022-08-15       NO23 -4.7105307016     I #> 3314   2045    3M  CC15 2022 2022-08-15      SALIN  0.7129498079  <NA> #> 3315   2045    3M  CC15 2022 2022-08-15        TKN  0.0000000000  <NA> #> 3316   2045    3M  CC15 2022 2022-08-15         TN  0.0039920213     + #> 3317   2045    3M  CC15 2022 2022-08-15         TP -1.2378743560  <NA> #> 3318   2045    3M  CC15 2022 2022-08-15        TSS  1.3862943611     I #> 3319   2045    3M  CC15 2022 2022-08-15       TURB  1.0296194172  <NA> #> 3320   2045    3M  CC15 2022 2022-12-15      CHLAC  4.9416424226  <NA> #> 3321   2045    3M  CC15 2022 2022-12-15       COND  9.5450252980  <NA> #> 3322   2045    3M  CC15 2022 2022-12-15         DO  1.8531680974  <NA> #> 3323   2045    3M  CC15 2022 2022-12-15      DOSAT  4.3681812279  <NA> #> 3324   2045    3M  CC15 2022 2022-12-15       NO23 -5.5214609179     U #> 3325   2045    3M  CC15 2022 2022-12-15      SALIN  2.0881534823  <NA> #> 3326   2045    3M  CC15 2022 2022-12-15        TKN  0.5306282511  <NA> #> 3327   2045    3M  CC15 2022 2022-12-15         TN  0.5318040302     + #> 3328   2045    3M  CC15 2022 2022-12-15         TP -1.0788096614  <NA> #> 3329   2045    3M  CC15 2022 2022-12-15        TSS  2.8332133441  <NA> #> 3330   2045    3M  CC15 2022 2022-12-15       TURB  2.1400661635  <NA> #> 3331   2045    3M  CC15 2023 2023-01-11      CHLAC  2.1400661635  <NA> #> 3332   2045    3M  CC15 2023 2023-01-11       COND  9.5500929367  <NA> #> 3333   2045    3M  CC15 2023 2023-01-11         DO  1.9125010869  <NA> #> 3334   2045    3M  CC15 2023 2023-01-11      DOSAT  4.3630986248  <NA> #> 3335   2045    3M  CC15 2023 2023-01-11       NO23 -4.2686979494  <NA> #> 3336   2045    3M  CC15 2023 2023-01-11      SALIN  2.0992441690  <NA> #> 3337   2045    3M  CC15 2023 2023-01-11        TKN -0.2876820725  <NA> #> 3338   2045    3M  CC15 2023 2023-01-11         TN -0.2691874898     + #> 3339   2045    3M  CC15 2023 2023-01-11         TP -1.6607312068  <NA> #> 3340   2045    3M  CC15 2023 2023-01-11        TSS  1.7917594692     I #> 3341   2045    3M  CC15 2023 2023-01-11       TURB  0.8754687374  <NA> #> 3342   2045    3M  CC15 2023 2023-03-23      CHLAC  1.4109869737     I #> 3343   2045    3M  CC15 2023 2023-03-23       COND 10.2374208545  <NA> #> 3344   2045    3M  CC15 2023 2023-03-23         DO  1.8609745382  <NA> #> 3345   2045    3M  CC15 2023 2023-03-23      DOSAT  4.4030540019  <NA> #> 3346   2045    3M  CC15 2023 2023-03-23       NO23 -5.5214609179     U #> 3347   2045    3M  CC15 2023 2023-03-23      SALIN  2.8449093838  <NA> #> 3348   2045    3M  CC15 2023 2023-03-23        TKN -0.3424903089  <NA> #> 3349   2045    3M  CC15 2023 2023-03-23         TN -0.3396773676     + #> 3350   2045    3M  CC15 2023 2023-03-23         TP -1.5606477483  <NA> #> 3351   2045    3M  CC15 2023 2023-03-23        TSS  1.7917594692     I #> 3352   2045    3M  CC15 2023 2023-03-23       TURB  1.2809338455  <NA> #> 3353   2045    3M  CC15 2023 2023-05-08      CHLAC  1.1314021115  <NA> #> 3354   2045    3M  CC15 2023 2023-05-08       COND 10.4129822911  <NA> #> 3355   2045    3M  CC15 2023 2023-05-08         DO  1.6992786164  <NA> #> 3356   2045    3M  CC15 2023 2023-05-08      DOSAT  4.3148178850  <NA> #> 3357   2045    3M  CC15 2023 2023-05-08       NO23 -5.5214609179     U #> 3358   2045    3M  CC15 2023 2023-05-08      SALIN  3.0359140632  <NA> #> 3359   2045    3M  CC15 2023 2023-05-08        TKN -0.3147107448  <NA> #> 3360   2045    3M  CC15 2023 2023-05-08         TN -0.3119747650     + #> 3361   2045    3M  CC15 2023 2023-05-08         TP -1.6607312068  <NA> #> 3362   2045    3M  CC15 2023 2023-05-08        TSS  2.6390573296  <NA> #> 3363   2045    3M  CC15 2023 2023-05-08       TURB  1.3350010667  <NA> #> 3364   2043    3M  CC16 2014 2014-06-26       COND  9.8119751520  <NA> #> 3365   2043    3M  CC16 2014 2014-06-26         DO  2.4230312461  <NA> #> 3366   2043    3M  CC16 2014 2014-06-26      DOSAT  5.0801613567  <NA> #> 3367   2043    3M  CC16 2014 2014-06-26       COND  9.5792797987  <NA> #> 3368   2043    3M  CC16 2014 2014-06-26         DO  1.2441545940  <NA> #> 3369   2043    3M  CC16 2014 2014-06-26      DOSAT  3.9852734672  <NA> #> 3370   2043    3M  CC16 2018 2018-03-07      CHLAC  1.8870696490  <NA> #> 3371   2043    3M  CC16 2018 2018-03-07       COND 10.1527665775  <NA> #> 3372   2043    3M  CC16 2018 2018-03-07         DO  1.9878743482  <NA> #> 3373   2043    3M  CC16 2018 2018-03-07      DOSAT  4.5347477217  <NA> #> 3374   2043    3M  CC16 2018 2018-03-07       NO23 -5.5214609179     U #> 3375   2043    3M  CC16 2018 2018-03-07      SALIN  2.8081971497     + #> 3376   2043    3M  CC16 2018 2018-03-07        TKN -0.3424903089  <NA> #> 3377   2043    3M  CC16 2018 2018-03-07         TN -0.3396773676     + #> 3378   2043    3M  CC16 2018 2018-03-07         TP -1.7719568419  <NA> #> 3379   2043    3M  CC16 2018 2018-03-07        TSS  1.6094379124     I #> 3380   2043    3M  CC16 2018 2018-03-07       TURB  1.0986122887  <NA> #> 3381   2043    3M  CC16 2018 2018-03-07       COND 10.2049615773  <NA> #> 3382   2043    3M  CC16 2018 2018-03-07         DO  2.0281482473  <NA> #> 3383   2043    3M  CC16 2018 2018-03-07      DOSAT  4.5653893160  <NA> #> 3384   2043    3M  CC16 2018 2018-03-07      SALIN  2.8701690506     + #> 3385   2043    3M  CC16 2018 2018-04-09      CHLAC  1.9315214116  <NA> #> 3386   2043    3M  CC16 2018 2018-04-09       COND 10.4399809231  <NA> #> 3387   2043    3M  CC16 2018 2018-04-09         DO  1.8082887712  <NA> #> 3388   2043    3M  CC16 2018 2018-04-09      DOSAT  4.4426512565  <NA> #> 3389   2043    3M  CC16 2018 2018-04-09       NO23 -5.2983173665     I #> 3390   2043    3M  CC16 2018 2018-04-09      SALIN  3.0445224377     + #> 3391   2043    3M  CC16 2018 2018-04-09        TKN -0.3011050928  <NA> #> 3392   2043    3M  CC16 2018 2018-04-09         TN -0.2957142441     + #> 3393   2043    3M  CC16 2018 2018-04-09         TP -1.6607312068  <NA> #> 3394   2043    3M  CC16 2018 2018-04-09        TSS  2.0794415417     I #> 3395   2043    3M  CC16 2018 2018-04-09       TURB  1.4816045409  <NA> #> 3396   2043    3M  CC16 2018 2018-05-24      CHLAC  2.2925347571  <NA> #> 3397   2043    3M  CC16 2018 2018-05-24       COND  9.8201059436  <NA> #> 3398   2043    3M  CC16 2018 2018-05-24         DO  1.7749523509  <NA> #> 3399   2043    3M  CC16 2018 2018-05-24      DOSAT  4.3719762988  <NA> #> 3400   2043    3M  CC16 2018 2018-05-24       NO23 -4.4228486292  <NA> #> 3401   2043    3M  CC16 2018 2018-05-24      SALIN  2.3360198691     + #> 3402   2043    3M  CC16 2018 2018-05-24        TKN -0.1984509387  <NA> #> 3403   2043    3M  CC16 2018 2018-05-24         TN -0.1839228382     + #> 3404   2043    3M  CC16 2018 2018-05-24         TP -1.6094379124  <NA> #> 3405   2043    3M  CC16 2018 2018-05-24        TSS  2.3025850930     I #> 3406   2043    3M  CC16 2018 2018-05-24       TURB  1.6863989536  <NA> #> 3407   2043    3M  CC16 2018 2018-05-24       COND  9.8362788028  <NA> #> 3408   2043    3M  CC16 2018 2018-05-24         DO  1.7698546338  <NA> #> 3409   2043    3M  CC16 2018 2018-05-24      DOSAT  4.3681812279  <NA> #> 3410   2043    3M  CC16 2018 2018-05-24      SALIN  2.3532782073     + #> 3411   2043    3M  CC16 2018 2018-07-23      CHLAC  2.4849066498  <NA> #> 3412   2043    3M  CC16 2018 2018-07-23       COND  7.2034055211  <NA> #> 3413   2043    3M  CC16 2018 2018-07-23         DO  1.7833912196  <NA> #> 3414   2043    3M  CC16 2018 2018-07-23      DOSAT  4.3694478525  <NA> #> 3415   2043    3M  CC16 2018 2018-07-23       NO23 -2.1202635362  <NA> #> 3416   2043    3M  CC16 2018 2018-07-23      SALIN -0.4004775666  <NA> #> 3417   2043    3M  CC16 2018 2018-07-23        TKN  0.1823215568  <NA> #> 3418   2043    3M  CC16 2018 2018-07-23         TN  0.2776317366     + #> 3419   2043    3M  CC16 2018 2018-07-23         TP -1.1394342832  <NA> #> 3420   2043    3M  CC16 2018 2018-07-23        TSS  1.0986122887     I #> 3421   2043    3M  CC16 2018 2018-07-23       TURB  1.0986122887  <NA> #> 3422   2043    3M  CC16 2018 2018-07-23       COND  7.2034055211  <NA> #> 3423   2043    3M  CC16 2018 2018-07-23         DO  1.7578579176  <NA> #> 3424   2043    3M  CC16 2018 2018-07-23      DOSAT  4.3438054219  <NA> #> 3425   2043    3M  CC16 2018 2018-07-23      SALIN -0.4155154440  <NA> #> 3426   2043    3M  CC16 2018 2018-08-21      CHLAC  2.8332133441     A #> 3427   2043    3M  CC16 2018 2018-08-21       COND  6.5308776277  <NA> #> 3428   2043    3M  CC16 2018 2018-08-21         DO  1.7083778603  <NA> #> 3429   2043    3M  CC16 2018 2018-08-21      DOSAT  4.2931954210  <NA> #> 3430   2043    3M  CC16 2018 2018-08-21       NO23 -2.8824035882  <NA> #> 3431   2043    3M  CC16 2018 2018-08-21      SALIN -1.1086626245  <NA> #> 3432   2043    3M  CC16 2018 2018-08-21        TKN  0.0953101798  <NA> #> 3433   2043    3M  CC16 2018 2018-08-21         TN  0.1449657703     + #> 3434   2043    3M  CC16 2018 2018-08-21         TP -1.2378743560  <NA> #> 3435   2043    3M  CC16 2018 2018-08-21        TSS  1.0986122887     I #> 3436   2043    3M  CC16 2018 2018-08-21       TURB  1.2809338455  <NA> #> 3437   2043    3M  CC16 2018 2018-08-21       COND  6.5337888379  <NA> #> 3438   2043    3M  CC16 2018 2018-08-21         DO  1.6882490929  <NA> #> 3439   2043    3M  CC16 2018 2018-08-21      DOSAT  4.2724907476  <NA> #> 3440   2043    3M  CC16 2018 2018-08-21      SALIN -1.1086626245  <NA> #> 3441   2043    3M  CC16 2019 2019-02-07      CHLAC  3.1354942159  <NA> #> 3442   2043    3M  CC16 2019 2019-02-07       COND  9.1573614472  <NA> #> 3443   2043    3M  CC16 2019 2019-02-07       NO23 -5.5214609179     U #> 3444   2043    3M  CC16 2019 2019-02-07      SALIN  1.6733512382  <NA> #> 3445   2043    3M  CC16 2019 2019-02-07        TKN -0.0725706928  <NA> #> 3446   2043    3M  CC16 2019 2019-02-07         TN -0.0704224643     + #> 3447   2043    3M  CC16 2019 2019-02-07         TP -1.8325814637  <NA> #> 3448   2043    3M  CC16 2019 2019-02-07        TSS  1.9459101491     I #> 3449   2043    3M  CC16 2019 2019-02-07       TURB  1.6863989536  <NA> #> 3450   2043    3M  CC16 2019 2019-03-13      CHLAC  2.1517622033  <NA> #> 3451   2043    3M  CC16 2019 2019-03-13       COND  9.7229244488  <NA> #> 3452   2043    3M  CC16 2019 2019-03-13         DO  1.7369512327  <NA> #> 3453   2043    3M  CC16 2019 2019-03-13      DOSAT  4.2780540443     + #> 3454   2043    3M  CC16 2019 2019-03-13       NO23 -5.5214609179     U #> 3455   2043    3M  CC16 2019 2019-03-13      SALIN  2.2823823857  <NA> #> 3456   2043    3M  CC16 2019 2019-03-13        TKN -0.2613647641  <NA> #> 3457   2043    3M  CC16 2019 2019-03-13         TN -0.2587707290     + #> 3458   2043    3M  CC16 2019 2019-03-13         TP -1.8971199849  <NA> #> 3459   2043    3M  CC16 2019 2019-03-13        TSS  1.6094379124     I #> 3460   2043    3M  CC16 2019 2019-03-13       TURB  1.2527629685  <NA> #> 3461   2043    3M  CC16 2019 2019-03-13       COND  9.7228046524  <NA> #> 3462   2043    3M  CC16 2019 2019-03-13         DO  1.6992786164  <NA> #> 3463   2043    3M  CC16 2019 2019-03-13      DOSAT  4.2398868675  <NA> #> 3464   2043    3M  CC16 2019 2019-03-13      SALIN  2.2823823857  <NA> #> 3465   2043    3M  CC16 2019 2019-04-23      CHLAC  2.3978952728  <NA> #> 3466   2043    3M  CC16 2019 2019-04-23       COND  9.9710060043  <NA> #> 3467   2043    3M  CC16 2019 2019-04-23         DO  1.8341801851  <NA> #> 3468   2043    3M  CC16 2019 2019-04-23      DOSAT  4.3707128748  <NA> #> 3469   2043    3M  CC16 2019 2019-04-23       NO23 -5.5214609179     U #> 3470   2043    3M  CC16 2019 2019-04-23      SALIN  2.5533438113  <NA> #> 3471   2043    3M  CC16 2019 2019-04-23        TKN -0.1863295782  <NA> #> 3472   2043    3M  CC16 2019 2019-04-23         TN -0.1839228382     + #> 3473   2043    3M  CC16 2019 2019-04-23         TP -1.7147984281  <NA> #> 3474   2043    3M  CC16 2019 2019-04-23        TSS  1.6094379124     I #> 3475   2043    3M  CC16 2019 2019-04-23       TURB  1.0296194172  <NA> #> 3476   2043    3M  CC16 2019 2019-07-22      CHLAC  2.4849066498  <NA> #> 3477   2043    3M  CC16 2019 2019-07-22       COND  8.7887458819  <NA> #> 3478   2043    3M  CC16 2019 2019-07-22         DO  1.7850704811  <NA> #> 3479   2043    3M  CC16 2019 2019-07-22      DOSAT  4.3969152472  <NA> #> 3480   2043    3M  CC16 2019 2019-07-22       NO23 -5.5214609179     U #> 3481   2043    3M  CC16 2019 2019-07-22      SALIN  1.2669476035  <NA> #> 3482   2043    3M  CC16 2019 2019-07-22        TKN -0.0833816089  <NA> #> 3483   2043    3M  CC16 2019 2019-07-22         TN -0.0812100554     + #> 3484   2043    3M  CC16 2019 2019-07-22         TP -1.2378743560  <NA> #> 3485   2043    3M  CC16 2019 2019-07-22        TSS  1.0986122887     I #> 3486   2043    3M  CC16 2019 2019-07-22       TURB  1.0986122887  <NA> #> 3487   2043    3M  CC16 2019 2019-09-04      CHLAC  2.3025850930  <NA> #> 3488   2043    3M  CC16 2019 2019-09-04       COND  7.9875244798  <NA> #> 3489   2043    3M  CC16 2019 2019-09-04         DO  1.7101878155  <NA> #> 3490   2043    3M  CC16 2019 2019-09-04      DOSAT  4.2972854062  <NA> #> 3491   2043    3M  CC16 2019 2019-09-04       NO23 -2.3025850930  <NA> #> 3492   2043    3M  CC16 2019 2019-09-04      SALIN  0.4187103349  <NA> #> 3493   2043    3M  CC16 2019 2019-09-04        TKN  0.1823215568  <NA> #> 3494   2043    3M  CC16 2019 2019-09-04         TN  0.2623642645     + #> 3495   2043    3M  CC16 2019 2019-09-04         TP -0.9162907319  <NA> #> 3496   2043    3M  CC16 2019 2019-09-04        TSS  1.7917594692     I #> 3497   2043    3M  CC16 2019 2019-09-04       TURB  1.3350010667  <NA> #> 3498   2043    3M  CC16 2020 2020-02-18      CHLAC  2.3978952728  <NA> #> 3499   2043    3M  CC16 2020 2020-02-18       COND 10.0826374182  <NA> #> 3500   2043    3M  CC16 2020 2020-02-18         DO  2.0202221820  <NA> #> 3501   2043    3M  CC16 2020 2020-02-18      DOSAT  4.6170987569  <NA> #> 3502   2043    3M  CC16 2020 2020-02-18       NO23 -5.5214609179     U #> 3503   2043    3M  CC16 2020 2020-02-18      SALIN  2.6720775406  <NA> #> 3504   2043    3M  CC16 2020 2020-02-18        TKN -0.1984509387  <NA> #> 3505   2043    3M  CC16 2020 2020-02-18         TN -0.1960148839     + #> 3506   2043    3M  CC16 2020 2020-02-18         TP -1.7147984281  <NA> #> 3507   2043    3M  CC16 2020 2020-02-18        TSS  2.4849066498  <NA> #> 3508   2043    3M  CC16 2020 2020-02-18       TURB  1.5260563035  <NA> #> 3509   2043    3M  CC16 2020 2020-02-18       COND 10.0856841015  <NA> #> 3510   2043    3M  CC16 2020 2020-02-18         DO  2.0055258587  <NA> #> 3511   2043    3M  CC16 2020 2020-02-18      DOSAT  4.6001576442  <NA> #> 3512   2043    3M  CC16 2020 2020-02-18      SALIN  2.6755270094  <NA> #> 3513   2043    3M  CC16 2020 2020-06-09      CHLAC  1.9459101491  <NA> #> 3514   2043    3M  CC16 2020 2020-06-09       COND  9.1632487644  <NA> #> 3515   2043    3M  CC16 2020 2020-06-09         DO  1.8779371655  <NA> #> 3516   2043    3M  CC16 2020 2020-06-09      DOSAT  4.4716387934  <NA> #> 3517   2043    3M  CC16 2020 2020-06-09       NO23 -3.5404594490  <NA> #> 3518   2043    3M  CC16 2020 2020-06-09      SALIN  1.6695918353  <NA> #> 3519   2043    3M  CC16 2020 2020-06-09        TKN -0.1743533871  <NA> #> 3520   2043    3M  CC16 2020 2020-06-09         TN -0.1404121537     + #> 3521   2043    3M  CC16 2020 2020-06-09         TP -1.5606477483  <NA> #> 3522   2043    3M  CC16 2020 2020-06-09        TSS  1.0986122887     I #> 3523   2043    3M  CC16 2020 2020-06-09       TURB  0.8329091229  <NA> #> 3524   2043    3M  CC16 2020 2020-06-09       COND  9.4707797080  <NA> #> 3525   2043    3M  CC16 2020 2020-06-09         DO  1.8855533485  <NA> #> 3526   2043    3M  CC16 2020 2020-06-09      DOSAT  4.4986979415  <NA> #> 3527   2043    3M  CC16 2020 2020-06-09      SALIN  2.0041790572  <NA> #> 3528   2043    3M  CC16 2020 2020-08-10       COND  9.6776528834  <NA> #> 3529   2043    3M  CC16 2020 2020-08-10         DO  1.5973653312  <NA> #> 3530   2043    3M  CC16 2020 2020-08-10      DOSAT  4.2541932632  <NA> #> 3531   2043    3M  CC16 2020 2020-08-10      SALIN  2.2093727113  <NA> #> 3532   2043    3M  CC16 2020 2020-09-22      CHLAC  2.1041341543  <NA> #> 3533   2043    3M  CC16 2020 2020-09-22       COND  6.8012830345  <NA> #> 3534   2043    3M  CC16 2020 2020-09-22         DO  1.8500283774  <NA> #> 3535   2043    3M  CC16 2020 2020-09-22      DOSAT  4.3932138241  <NA> #> 3536   2043    3M  CC16 2020 2020-09-22       NO23 -2.6882475738  <NA> #> 3537   2043    3M  CC16 2020 2020-09-22      SALIN -0.8209805521  <NA> #> 3538   2043    3M  CC16 2020 2020-09-22        TKN  0.1823215568  <NA> #> 3539   2043    3M  CC16 2020 2020-09-22         TN  0.2374408560     + #> 3540   2043    3M  CC16 2020 2020-09-22         TP -1.0498221245  <NA> #> 3541   2043    3M  CC16 2020 2020-09-22        TSS  1.3862943611     I #> 3542   2043    3M  CC16 2020 2020-09-22       TURB  1.1314021115     A #> 3543   2043    3M  CC16 2020 2020-10-20      CHLAC  2.3978952728  <NA> #> 3544   2043    3M  CC16 2020 2020-10-20       COND  8.8590793179  <NA> #> 3545   2043    3M  CC16 2020 2020-10-20         DO  1.7281094422  <NA> #> 3546   2043    3M  CC16 2020 2020-10-20      DOSAT  4.2835865619  <NA> #> 3547   2043    3M  CC16 2020 2020-10-20       NO23 -2.2072749132  <NA> #> 3548   2043    3M  CC16 2020 2020-10-20      SALIN  1.3480731483  <NA> #> 3549   2043    3M  CC16 2020 2020-10-20        TKN  0.1823215568  <NA> #> 3550   2043    3M  CC16 2020 2020-10-20         TN  0.2700271372     + #> 3551   2043    3M  CC16 2020 2020-10-20         TP -1.1086626245  <NA> #> 3552   2043    3M  CC16 2020 2020-10-20        TSS  1.7917594692     I #> 3553   2043    3M  CC16 2020 2020-10-20       TURB  1.3350010667  <NA> #> 3554   2043    3M  CC16 2020 2020-12-14      CHLAC  2.6390573296  <NA> #> 3555   2043    3M  CC16 2020 2020-12-14       COND  9.3722891390  <NA> #> 3556   2043    3M  CC16 2020 2020-12-14         DO  2.0554049639  <NA> #> 3557   2043    3M  CC16 2020 2020-12-14      DOSAT  4.5261269786  <NA> #> 3558   2043    3M  CC16 2020 2020-12-14       NO23 -5.5214609179     U #> 3559   2043    3M  CC16 2020 2020-12-14      SALIN  1.9035989510  <NA> #> 3560   2043    3M  CC16 2020 2020-12-14        TKN -0.0408219945  <NA> #> 3561   2043    3M  CC16 2020 2020-12-14         TN -0.0387408283     + #> 3562   2043    3M  CC16 2020 2020-12-14         TP -1.6094379124  <NA> #> 3563   2043    3M  CC16 2020 2020-12-14        TSS  1.6094379124     I #> 3564   2043    3M  CC16 2020 2020-12-14       TURB  1.2237754316  <NA> #> 3565   2043    3M  CC16 2021 2021-02-03      CHLAC  2.3978952728  <NA> #> 3566   2043    3M  CC16 2021 2021-02-03       COND  9.8437906253  <NA> #> 3567   2043    3M  CC16 2021 2021-02-03         DO  2.0360119838  <NA> #> 3568   2043    3M  CC16 2021 2021-02-03      DOSAT  4.4379342666  <NA> #> 3569   2043    3M  CC16 2021 2021-02-03       NO23 -5.5214609179     U #> 3570   2043    3M  CC16 2021 2021-02-03      SALIN  2.4185887688  <NA> #> 3571   2043    3M  CC16 2021 2021-02-03        TKN -0.2484613593  <NA> #> 3572   2043    3M  CC16 2021 2021-02-03         TN -0.2459005384     + #> 3573   2043    3M  CC16 2021 2021-02-03         TP -2.2072749132  <NA> #> 3574   2043    3M  CC16 2021 2021-02-03        TSS  1.3862943611     I #> 3575   2043    3M  CC16 2021 2021-02-03       TURB  1.0986122887  <NA> #> 3576   2043    3M  CC16 2021 2021-03-23      CHLAC  2.5649493575  <NA> #> 3577   2043    3M  CC16 2021 2021-03-23       COND 10.0172179429  <NA> #> 3578   2043    3M  CC16 2021 2021-03-23         DO  1.8484548129  <NA> #> 3579   2043    3M  CC16 2021 2021-03-23      DOSAT  4.3320482649  <NA> #> 3580   2043    3M  CC16 2021 2021-03-23       NO23 -5.5214609179     U #> 3581   2043    3M  CC16 2021 2021-03-23      SALIN  2.6056482675  <NA> #> 3582   2043    3M  CC16 2021 2021-03-23        TKN -0.1165338163  <NA> #> 3583   2043    3M  CC16 2021 2021-03-23         TN -0.1142891464     + #> 3584   2043    3M  CC16 2021 2021-03-23         TP -1.8971199849  <NA> #> 3585   2043    3M  CC16 2021 2021-03-23        TSS  1.7917594692     I #> 3586   2043    3M  CC16 2021 2021-03-23       TURB  1.3862943611  <NA> #> 3587   2043    3M  CC16 2021 2021-05-05      CHLAC  2.2823823857  <NA> #> 3588   2043    3M  CC16 2021 2021-05-05       COND 10.2634321453  <NA> #> 3589   2043    3M  CC16 2021 2021-05-05         DO  1.7263316639  <NA> #> 3590   2043    3M  CC16 2021 2021-05-05      DOSAT  4.4200447019  <NA> #> 3591   2043    3M  CC16 2021 2021-05-05       NO23 -5.5214609179     I #> 3592   2043    3M  CC16 2021 2021-05-05      SALIN  2.8650539499  <NA> #> 3593   2043    3M  CC16 2021 2021-05-05        TKN -0.0833816089  <NA> #> 3594   2043    3M  CC16 2021 2021-05-05         TN -0.0790432073     + #> 3595   2043    3M  CC16 2021 2021-05-05         TP -1.5606477483  <NA> #> 3596   2043    3M  CC16 2021 2021-05-05        TSS  2.0794415417     I #> 3597   2043    3M  CC16 2021 2021-05-05       TURB  1.4816045409  <NA> #> 3598   2043    3M  CC16 2021 2021-06-03      CHLAC  2.4849066498  <NA> #> 3599   2043    3M  CC16 2021 2021-06-03       COND 10.3258753278  <NA> #> 3600   2043    3M  CC16 2021 2021-06-03         DO  1.6524974019  <NA> #> 3601   2043    3M  CC16 2021 2021-06-03      DOSAT  4.3094559418  <NA> #> 3602   2043    3M  CC16 2021 2021-06-03       NO23 -5.5214609179     U #> 3603   2043    3M  CC16 2021 2021-06-03      SALIN  2.9375733594  <NA> #> 3604   2043    3M  CC16 2021 2021-06-03        TKN  0.0000000000  <NA> #> 3605   2043    3M  CC16 2021 2021-06-03         TN  0.0019980027     + #> 3606   2043    3M  CC16 2021 2021-06-03         TP -1.6607312068  <NA> #> 3607   2043    3M  CC16 2021 2021-06-03        TSS  2.0794415417     I #> 3608   2043    3M  CC16 2021 2021-06-03       TURB  1.4109869737  <NA> #> 3609   2043    3M  CC16 2021 2021-07-01      CHLAC  3.0910424534  <NA> #> 3610   2043    3M  CC16 2021 2021-07-01       COND 10.1819522754  <NA> #> 3611   2043    3M  CC16 2021 2021-07-01         DO  1.6956156087  <NA> #> 3612   2043    3M  CC16 2021 2021-07-01      DOSAT  4.3567088267  <NA> #> 3613   2043    3M  CC16 2021 2021-07-01       NO23 -3.0791138825  <NA> #> 3614   2043    3M  CC16 2021 2021-07-01      SALIN  2.7775762638  <NA> #> 3615   2043    3M  CC16 2021 2021-07-01        TKN -0.2357223335  <NA> #> 3616   2043    3M  CC16 2021 2021-07-01         TN -0.1791266659     + #> 3617   2043    3M  CC16 2021 2021-07-01         TP -1.5606477483  <NA> #> 3618   2043    3M  CC16 2021 2021-07-01        TSS  2.3025850930  <NA> #> 3619   2043    3M  CC16 2021 2021-07-01       TURB  1.7404661748  <NA> #> 3620   2043    3M  CC16 2022 2022-02-22      CHLAC  1.0986122887  <NA> #> 3621   2043    3M  CC16 2022 2022-02-22       COND 10.3057809695  <NA> #> 3622   2043    3M  CC16 2022 2022-02-22         DO  1.8794650496  <NA> #> 3623   2043    3M  CC16 2022 2022-02-22      DOSAT  4.4543472963  <NA> #> 3624   2043    3M  CC16 2022 2022-02-22       NO23 -4.9618451299     I #> 3625   2043    3M  CC16 2022 2022-02-22      SALIN  2.9199305601  <NA> #> 3626   2043    3M  CC16 2022 2022-02-22        TKN -0.4307829161  <NA> #> 3627   2043    3M  CC16 2022 2022-02-22         TN -0.4246479275     + #> 3628   2043    3M  CC16 2022 2022-02-22         TP -2.3859667019  <NA> #> 3629   2043    3M  CC16 2022 2022-02-22        TSS  2.3025850930     I #> 3630   2043    3M  CC16 2022 2022-02-22       TURB  0.6931471806  <NA> #> 3631   2043    3M  CC16 2022 2022-06-07      CHLAC  2.7080502011  <NA> #> 3632   2043    3M  CC16 2022 2022-06-07       COND 10.2345882454  <NA> #> 3633   2043    3M  CC16 2022 2022-06-07         DO  1.4182774070  <NA> #> 3634   2043    3M  CC16 2022 2022-06-07      DOSAT  4.1026433650  <NA> #> 3635   2043    3M  CC16 2022 2022-06-07       NO23 -5.5214609179     U #> 3636   2043    3M  CC16 2022 2022-06-07      SALIN  2.8361502037  <NA> #> 3637   2043    3M  CC16 2022 2022-06-07        TKN -0.1165338163  <NA> #> 3638   2043    3M  CC16 2022 2022-06-07         TN -0.1142891464     + #> 3639   2043    3M  CC16 2022 2022-06-07         TP -1.6607312068  <NA> #> 3640   2043    3M  CC16 2022 2022-06-07        TSS  2.5649493575  <NA> #> 3641   2043    3M  CC16 2022 2022-06-07       TURB  1.6863989536  <NA> #> 3642   2043    3M  CC16 2022 2022-08-15      CHLAC  2.9957322736     A #> 3643   2043    3M  CC16 2022 2022-08-15       COND  8.1639409548  <NA> #> 3644   2043    3M  CC16 2022 2022-08-15         DO  1.4350845253  <NA> #> 3645   2043    3M  CC16 2022 2022-08-15      DOSAT  4.0145795938  <NA> #> 3646   2043    3M  CC16 2022 2022-08-15       NO23 -4.7105307016     I #> 3647   2043    3M  CC16 2022 2022-08-15      SALIN  0.6043159669  <NA> #> 3648   2043    3M  CC16 2022 2022-08-15        TKN -0.1278333715  <NA> #> 3649   2043    3M  CC16 2022 2022-08-15         TN -0.1232982163     + #> 3650   2043    3M  CC16 2022 2022-08-15         TP -1.3093333200  <NA> #> 3651   2043    3M  CC16 2022 2022-08-15        TSS  1.3862943611     I #> 3652   2043    3M  CC16 2022 2022-08-15       TURB  1.2527629685  <NA> #> 3653   2043    3M  CC16 2022 2022-12-15      CHLAC  4.8675344505  <NA> #> 3654   2043    3M  CC16 2022 2022-12-15       COND  9.6068992706  <NA> #> 3655   2043    3M  CC16 2022 2022-12-15         DO  2.1781550146  <NA> #> 3656   2043    3M  CC16 2022 2022-12-15      DOSAT  4.6950108900  <NA> #> 3657   2043    3M  CC16 2022 2022-12-15       NO23 -5.5214609179     U #> 3658   2043    3M  CC16 2022 2022-12-15      SALIN  2.1575593209  <NA> #> 3659   2043    3M  CC16 2022 2022-12-15        TKN  0.5306282511  <NA> #> 3660   2043    3M  CC16 2022 2022-12-15         TN  0.5318040302     + #> 3661   2043    3M  CC16 2022 2022-12-15         TP -1.1711829815  <NA> #> 3662   2043    3M  CC16 2022 2022-12-15        TSS  2.8903717579  <NA> #> 3663   2043    3M  CC16 2022 2022-12-15       TURB  1.8562979904  <NA> #> 3664   2043    3M  CC16 2021 2021-02-03      CHLAC  3.1354942159  <NA> #> 3665   2043    3M  CC16 2021 2021-02-03       COND  9.5834200199  <NA> #> 3666   2043    3M  CC16 2021 2021-02-03         DO  2.0041790572  <NA> #> 3667   2043    3M  CC16 2021 2021-02-03      DOSAT  4.4042772436  <NA> #> 3668   2043    3M  CC16 2021 2021-02-03       NO23 -5.5214609179     U #> 3669   2043    3M  CC16 2021 2021-02-03      SALIN  2.1365305087  <NA> #> 3670   2043    3M  CC16 2021 2021-02-03        TKN -0.1278333715  <NA> #> 3671   2043    3M  CC16 2021 2021-02-03         TN -0.1255632230     + #> 3672   2043    3M  CC16 2021 2021-02-03         TP -2.1202635362  <NA> #> 3673   2043    3M  CC16 2021 2021-02-03        TSS  1.9459101491     I #> 3674   2043    3M  CC16 2021 2021-02-03       TURB  1.7578579176  <NA> #> 3675   2043    3M  CC16 2021 2021-03-23      CHLAC  3.2188758249  <NA> #> 3676   2043    3M  CC16 2021 2021-03-23       COND  9.8242819944  <NA> #> 3677   2043    3M  CC16 2021 2021-03-23         DO  1.7867469274  <NA> #> 3678   2043    3M  CC16 2021 2021-03-23      DOSAT  4.2640873368  <NA> #> 3679   2043    3M  CC16 2021 2021-03-23       NO23 -5.5214609179     U #> 3680   2043    3M  CC16 2021 2021-03-23      SALIN  2.3951642743  <NA> #> 3681   2043    3M  CC16 2021 2021-03-23        TKN  0.0953101798  <NA> #> 3682   2043    3M  CC16 2021 2021-03-23         TN  0.0971267107     + #> 3683   2043    3M  CC16 2021 2021-03-23         TP -1.6094379124  <NA> #> 3684   2043    3M  CC16 2021 2021-03-23        TSS  2.3978952728  <NA> #> 3685   2043    3M  CC16 2021 2021-03-23       TURB  2.0412203289  <NA> #> 3686   2043    3M  CC16 2021 2021-05-05      CHLAC  2.7725887222  <NA> #> 3687   2043    3M  CC16 2021 2021-05-05       COND 10.1696522784  <NA> #> 3688   2043    3M  CC16 2021 2021-05-05         DO  1.3711807233  <NA> #> 3689   2043    3M  CC16 2021 2021-05-05      DOSAT  4.0342406382  <NA> #> 3690   2043    3M  CC16 2021 2021-05-05       NO23 -5.5214609179     U #> 3691   2043    3M  CC16 2021 2021-05-05      SALIN  2.7638002162  <NA> #> 3692   2043    3M  CC16 2021 2021-05-05        TKN -0.0304592075  <NA> #> 3693   2043    3M  CC16 2021 2021-05-05         TN -0.0283994745     + #> 3694   2043    3M  CC16 2021 2021-05-05         TP -1.5606477483  <NA> #> 3695   2043    3M  CC16 2021 2021-05-05        TSS  1.7917594692     I #> 3696   2043    3M  CC16 2021 2021-05-05       TURB  1.5260563035  <NA> #> 3697   2043    3M  CC16 2021 2021-06-03      CHLAC  2.8903717579  <NA> #> 3698   2043    3M  CC16 2021 2021-06-03       COND 10.2473963549  <NA> #> 3699   2043    3M  CC16 2021 2021-06-03         DO  1.5475625087  <NA> #> 3700   2043    3M  CC16 2021 2021-06-03      DOSAT  4.2002049529  <NA> #> 3701   2043    3M  CC16 2021 2021-06-03       NO23 -4.9618451299     I #> 3702   2043    3M  CC16 2021 2021-06-03      SALIN  2.8518619031  <NA> #> 3703   2043    3M  CC16 2021 2021-06-03        TKN  0.1823215568  <NA> #> 3704   2043    3M  CC16 2021 2021-06-03         TN  0.1856493469     + #> 3705   2043    3M  CC16 2021 2021-06-03         TP -1.5606477483  <NA> #> 3706   2043    3M  CC16 2021 2021-06-03        TSS  2.3978952728  <NA> #> 3707   2043    3M  CC16 2021 2021-06-03       TURB  1.6486586256  <NA> #> 3708   2043    3M  CC16 2021 2021-07-01      CHLAC  3.4339872045  <NA> #> 3709   2043    3M  CC16 2021 2021-07-01       COND 10.0458547938  <NA> #> 3710   2043    3M  CC16 2021 2021-07-01         DO  1.9837562915  <NA> #> 3711   2043    3M  CC16 2021 2021-07-01      DOSAT  4.6091622073  <NA> #> 3712   2043    3M  CC16 2021 2021-07-01       NO23 -3.4420193762  <NA> #> 3713   2043    3M  CC16 2021 2021-07-01      SALIN  2.6304489551  <NA> #> 3714   2043    3M  CC16 2021 2021-07-01        TKN -0.0304592075  <NA> #> 3715   2043    3M  CC16 2021 2021-07-01         TN  0.0019980027     + #> 3716   2043    3M  CC16 2021 2021-07-01         TP -1.3862943611  <NA> #> 3717   2043    3M  CC16 2021 2021-07-01        TSS  1.7917594692     I #> 3718   2043    3M  CC16 2021 2021-07-01       TURB  1.6677068206  <NA> #> 3719   2043    3M  CC16 2022 2022-02-22      CHLAC  1.6094379124  <NA> #> 3720   2043    3M  CC16 2022 2022-02-22       COND 10.1823685085  <NA> #> 3721   2043    3M  CC16 2022 2022-02-22         DO  1.7422190237  <NA> #> 3722   2043    3M  CC16 2022 2022-02-22      DOSAT  4.3148178850  <NA> #> 3723   2043    3M  CC16 2022 2022-02-22       NO23 -4.6051701860     I #> 3724   2043    3M  CC16 2022 2022-02-22      SALIN  2.7788192720  <NA> #> 3725   2043    3M  CC16 2022 2022-02-22        TKN -0.2484613593  <NA> #> 3726   2043    3M  CC16 2022 2022-02-22         TN -0.2433462586     + #> 3727   2043    3M  CC16 2022 2022-02-22         TP -2.3025850930  <NA> #> 3728   2043    3M  CC16 2022 2022-02-22        TSS  2.4849066498  <NA> #> 3729   2043    3M  CC16 2022 2022-02-22       TURB  1.6486586256  <NA> #> 3730   2043    3M  CC16 2022 2022-06-07      CHLAC  2.1400661635  <NA> #> 3731   2043    3M  CC16 2022 2022-06-07       COND 10.2020724724  <NA> #> 3732   2043    3M  CC16 2022 2022-06-07         DO  1.5151272330  <NA> #> 3733   2043    3M  CC16 2022 2022-06-07      DOSAT  4.1713056034  <NA> #> 3734   2043    3M  CC16 2022 2022-06-07       NO23 -3.9633162998  <NA> #> 3735   2043    3M  CC16 2022 2022-06-07      SALIN  2.7997173896  <NA> #> 3736   2043    3M  CC16 2022 2022-06-07        TKN -0.1625189295  <NA> #> 3737   2043    3M  CC16 2022 2022-06-07         TN -0.1404121537     + #> 3738   2043    3M  CC16 2022 2022-06-07         TP -1.4271163556  <NA> #> 3739   2043    3M  CC16 2022 2022-06-07        TSS  2.3025850930  <NA> #> 3740   2043    3M  CC16 2022 2022-06-07       TURB  1.3350010667  <NA> #> 3741   2043    3M  CC16 2022 2022-08-15      CHLAC  3.0445224377  <NA> #> 3742   2043    3M  CC16 2022 2022-08-15       COND  7.8363697605  <NA> #> 3743   2043    3M  CC16 2022 2022-08-15         DO  1.5539252025  <NA> #> 3744   2043    3M  CC16 2022 2022-08-15      DOSAT  4.1319614258  <NA> #> 3745   2043    3M  CC16 2022 2022-08-15       NO23 -4.0173835211  <NA> #> 3746   2043    3M  CC16 2022 2022-08-15      SALIN  0.2623642645  <NA> #> 3747   2043    3M  CC16 2022 2022-08-15        TKN -0.1863295782  <NA> #> 3748   2043    3M  CC16 2022 2022-08-15         TN -0.1648746432     + #> 3749   2043    3M  CC16 2022 2022-08-15         TP -1.6094379124  <NA> #> 3750   2043    3M  CC16 2022 2022-08-15        TSS  2.0794415417     I #> 3751   2043    3M  CC16 2022 2022-08-15       TURB  1.4109869737  <NA> #> 3752   2043    3M  CC16 2022 2022-12-15      CHLAC  3.6109179126  <NA> #> 3753   2043    3M  CC16 2022 2022-12-15       COND  9.5544264071  <NA> #> 3754   2043    3M  CC16 2022 2022-12-15         DO  1.8405496334  <NA> #> 3755   2043    3M  CC16 2022 2022-12-15      DOSAT  4.3554259529  <NA> #> 3756   2043    3M  CC16 2022 2022-12-15       NO23 -5.5214609179     U #> 3757   2043    3M  CC16 2022 2022-12-15      SALIN  2.0992441690  <NA> #> 3758   2043    3M  CC16 2022 2022-12-15        TKN -0.1743533871  <NA> #> 3759   2043    3M  CC16 2022 2022-12-15         TN -0.1719752647     + #> 3760   2043    3M  CC16 2022 2022-12-15         TP -1.7719568419  <NA> #> 3761   2043    3M  CC16 2022 2022-12-15        TSS  1.7917594692     I #> 3762   2043    3M  CC16 2022 2022-12-15       TURB  1.2809338455  <NA> #> 3763  2048A    3M  CC18 2014 2014-01-06         DO  1.7917594692  <NA> #> 3764  2048A    3M  CC18 2014 2014-01-06      DOSAT  4.3107991254     + #> 3765  2048A    3M  CC18 2014 2014-01-06       NO23 -4.7105307016     I #> 3766  2048A    3M  CC18 2014 2014-01-06      SALIN  3.0819099698  <NA> #> 3767  2048A    3M  CC18 2014 2014-01-06        TKN -0.3011050928  <NA> #> 3768  2048A    3M  CC18 2014 2014-01-06         TN -0.2957142441     + #> 3769  2048A    3M  CC18 2014 2014-01-06         TP -2.7333680091  <NA> #> 3770  2048A    3M  CC18 2014 2014-02-03      CHLAC  1.3350010667  <NA> #> 3771  2048A    3M  CC18 2014 2014-02-03      COLOR  3.2188758249  <NA> #> 3772  2048A    3M  CC18 2014 2014-02-03         DO  1.6677068206  <NA> #> 3773  2048A    3M  CC18 2014 2014-02-03      DOSAT  4.1820501426     + #> 3774  2048A    3M  CC18 2014 2014-02-03       NO23 -4.5098600062  <NA> #> 3775  2048A    3M  CC18 2014 2014-02-03      SALIN  2.9496883351  <NA> #> 3776  2048A    3M  CC18 2014 2014-02-03        TKN -0.6348782724  <NA> #> 3777  2048A    3M  CC18 2014 2014-02-03         TN -0.6143360001     + #> 3778  2048A    3M  CC18 2014 2014-02-03         TP -2.5133061243  <NA> #> 3779  2048A    3M  CC18 2014 2014-02-03       TURB  0.4700036292  <NA> #> 3780  2048A    3M  CC18 2014 2014-03-03      CHLAC  1.0296194172  <NA> #> 3781  2048A    3M  CC18 2014 2014-03-03      COLOR  3.2580965380  <NA> #> 3782  2048A    3M  CC18 2014 2014-03-03      DOSAT  4.3201512310     + #> 3783  2048A    3M  CC18 2014 2014-03-03       NO23 -5.5214609179     I #> 3784  2048A    3M  CC18 2014 2014-03-03      SALIN  3.0349529867  <NA> #> 3785  2048A    3M  CC18 2014 2014-03-03        TKN -0.4155154440  <NA> #> 3786  2048A    3M  CC18 2014 2014-03-03         TN -0.4094731295     + #> 3787  2048A    3M  CC18 2014 2014-03-03         TP -2.3859667019  <NA> #> 3788  2048A    3M  CC18 2014 2014-03-03       TURB  0.6418538862  <NA> #> 3789  2048A    3M  CC18 2014 2014-04-07      CHLAC  1.5892352051  <NA> #> 3790  2048A    3M  CC18 2014 2014-04-07      COLOR  3.3322045102  <NA> #> 3791  2048A    3M  CC18 2014 2014-04-07         DO  2.2082744135  <NA> #> 3792  2048A    3M  CC18 2014 2014-04-07      DOSAT  4.7492705300     + #> 3793  2048A    3M  CC18 2014 2014-04-07       NO23 -4.9618451299     I #> 3794  2048A    3M  CC18 2014 2014-04-07      SALIN  2.0794415417  <NA> #> 3795  2048A    3M  CC18 2014 2014-04-07        TKN -0.4155154440  <NA> #> 3796  2048A    3M  CC18 2014 2014-04-07         TN -0.4094731295     + #> 3797  2048A    3M  CC18 2014 2014-04-07         TP -3.1465551633  <NA> #> 3798  2048A    3M  CC18 2014 2014-04-07       TURB  0.9932517730  <NA> #> 3799  2048A    3M  CC18 2014 2014-05-05      CHLAC  1.5892352051  <NA> #> 3800  2048A    3M  CC18 2014 2014-05-05      COLOR  3.4657359028     A #> 3801  2048A    3M  CC18 2014 2014-05-05         DO  1.5686159179  <NA> #> 3802  2048A    3M  CC18 2014 2014-05-05      DOSAT  4.1866198383     + #> 3803  2048A    3M  CC18 2014 2014-05-05       NO23 -4.3428059215  <NA> #> 3804  2048A    3M  CC18 2014 2014-05-05      SALIN  3.0819099698  <NA> #> 3805  2048A    3M  CC18 2014 2014-05-05        TKN -0.2107210313  <NA> #> 3806  2048A    3M  CC18 2014 2014-05-05         TN -0.1947990783     + #> 3807  2048A    3M  CC18 2014 2014-05-05         TP -1.9661128564  <NA> #> 3808  2048A    3M  CC18 2014 2014-05-05       TURB  1.1314021115     A #> 3809  2048A    3M  CC18 2014 2014-06-02      CHLAC  1.8718021769  <NA> #> 3810  2048A    3M  CC18 2014 2014-06-02      COLOR  3.6635616461     A #> 3811  2048A    3M  CC18 2014 2014-06-02       NO23 -4.6051701860  <NA> #> 3812  2048A    3M  CC18 2014 2014-06-02      SALIN  3.1441522787  <NA> #> 3813  2048A    3M  CC18 2014 2014-06-02        TKN -0.4004775666  <NA> #> 3814  2048A    3M  CC18 2014 2014-06-02         TN -0.3856624808     + #> 3815  2048A    3M  CC18 2014 2014-06-02         TP -1.5606477483  <NA> #> 3816  2048A    3M  CC18 2014 2014-06-02       TURB  0.9555114450  <NA> #> 3817  2048A    3M  CC18 2014 2014-08-04      CHLAC  1.9740810260  <NA> #> 3818  2048A    3M  CC18 2014 2014-08-04      COLOR  4.7874917428  <NA> #> 3819  2048A    3M  CC18 2014 2014-08-04         DO  0.7371640660  <NA> #> 3820  2048A    3M  CC18 2014 2014-08-04      DOSAT  3.3568971228     + #> 3821  2048A    3M  CC18 2014 2014-08-04       NO23 -4.8283137373     I #> 3822  2048A    3M  CC18 2014 2014-08-04        TKN  0.0953101798  <NA> #> 3823  2048A    3M  CC18 2014 2014-08-04         TN  0.0989399479     + #> 3824  2048A    3M  CC18 2014 2014-08-04         TP -1.3862943611  <NA> #> 3825  2048A    3M  CC18 2014 2014-08-04       TURB  1.2527629685  <NA> #> 3826  2048A    3M  CC18 2014 2014-09-08      CHLAC  1.8082887712  <NA> #> 3827  2048A    3M  CC18 2014 2014-09-08      COLOR  4.1108738642  <NA> #> 3828  2048A    3M  CC18 2014 2014-09-08         DO  1.3083328197  <NA> #> 3829  2048A    3M  CC18 2014 2014-09-08      DOSAT  3.8958936235     + #> 3830  2048A    3M  CC18 2014 2014-09-08       NO23 -4.5098600062  <NA> #> 3831  2048A    3M  CC18 2014 2014-09-08      SALIN  2.1162555148  <NA> #> 3832  2048A    3M  CC18 2014 2014-09-08        TKN -0.0833816089  <NA> #> 3833  2048A    3M  CC18 2014 2014-09-08         TN -0.0714960017     + #> 3834  2048A    3M  CC18 2014 2014-09-08         TP -1.4696759701  <NA> #> 3835  2048A    3M  CC18 2014 2014-09-08       TURB  0.5877866649  <NA> #> 3836  2048A    3M  CC18 2014 2014-10-06      CHLAC  2.3978952728  <NA> #> 3837  2048A    3M  CC18 2014 2014-10-06      COLOR  5.1929568509  <NA> #> 3838  2048A    3M  CC18 2014 2014-10-06         DO  2.1400661635  <NA> #> 3839  2048A    3M  CC18 2014 2014-10-06      DOSAT  4.6376373761     + #> 3840  2048A    3M  CC18 2014 2014-10-06       NO23 -3.9633162998  <NA> #> 3841  2048A    3M  CC18 2014 2014-10-06      SALIN  0.5877866649  <NA> #> 3842  2048A    3M  CC18 2014 2014-10-06        TKN -0.0943106795  <NA> #> 3843  2048A    3M  CC18 2014 2014-10-06         TN -0.0736465402     + #> 3844  2048A    3M  CC18 2014 2014-10-06         TP -1.8971199849  <NA> #> 3845  2048A    3M  CC18 2014 2014-10-06       TURB  0.4700036292     A #> 3846  2048A    3M  CC18 2014 2014-11-03      CHLAC  1.8405496334  <NA> #> 3847  2048A    3M  CC18 2014 2014-11-03      COLOR  4.5325994932  <NA> #> 3848  2048A    3M  CC18 2014 2014-11-03       NO23 -4.2686979494  <NA> #> 3849  2048A    3M  CC18 2014 2014-11-03      SALIN  2.5726122302  <NA> #> 3850  2048A    3M  CC18 2014 2014-11-03        TKN -0.1743533871  <NA> #> 3851  2048A    3M  CC18 2014 2014-11-03         TN -0.1578240852     + #> 3852  2048A    3M  CC18 2014 2014-11-03         TP -1.6607312068  <NA> #> 3853  2048A    3M  CC18 2014 2014-11-03       TURB  0.5306282511     A #> 3854  2048A    3M  CC18 2014 2014-12-01      CHLAC  0.6418538862  <NA> #> 3855  2048A    3M  CC18 2014 2014-12-01      COLOR  3.8712010109     A #> 3856  2048A    3M  CC18 2014 2014-12-01         DO  1.7047480922  <NA> #> 3857  2048A    3M  CC18 2014 2014-12-01      SALIN  2.6100697927  <NA> #> 3858  2048A    3M  CC18 2014 2014-12-01         TN -0.0899247075     + #> 3859  2048A    3M  CC18 2014 2014-12-01       TURB  0.0000000000  <NA> #> 3860  2048A    3M  CC18 2015 2015-01-05      CHLAC  2.0149030205  <NA> #> 3861  2048A    3M  CC18 2015 2015-01-05      COLOR  3.5835189385  <NA> #> 3862  2048A    3M  CC18 2015 2015-01-05         DO  1.7578579176  <NA> #> 3863  2048A    3M  CC18 2015 2015-01-05      DOSAT  4.3333614627     + #> 3864  2048A    3M  CC18 2015 2015-01-05       NO23 -3.6496587410  <NA> #> 3865  2048A    3M  CC18 2015 2015-01-05      SALIN  2.9496883351  <NA> #> 3866  2048A    3M  CC18 2015 2015-01-05        TKN -0.5108256238  <NA> #> 3867  2048A    3M  CC18 2015 2015-01-05         TN -0.4684049079     + #> 3868  2048A    3M  CC18 2015 2015-01-05         TP -2.5010360317  <NA> #> 3869  2048A    3M  CC18 2015 2015-01-05       TURB  0.4700036292  <NA> #> 3870  2048A    3M  CC18 2015 2015-02-02      CHLAC  1.5892352051  <NA> #> 3871  2048A    3M  CC18 2015 2015-02-02      COLOR  3.1780538303  <NA> #> 3872  2048A    3M  CC18 2015 2015-02-02      DOSAT  4.1415461637     + #> 3873  2048A    3M  CC18 2015 2015-02-02       NO23 -4.7105307016     I #> 3874  2048A    3M  CC18 2015 2015-02-02      SALIN  2.9957322736  <NA> #> 3875  2048A    3M  CC18 2015 2015-02-02         TN -0.6088060321     + #> 3876  2048A    3M  CC18 2015 2015-02-02       TURB  0.4054651081  <NA> #> 3877  2048A    3M  CC18 2015 2015-03-02      CHLAC  1.3862943611  <NA> #> 3878  2048A    3M  CC18 2015 2015-03-02      COLOR  3.4011973817  <NA> #> 3879  2048A    3M  CC18 2015 2015-03-02         DO  2.0794415417  <NA> #> 3880  2048A    3M  CC18 2015 2015-03-02      DOSAT  4.6395716127     + #> 3881  2048A    3M  CC18 2015 2015-03-02      SALIN  2.9285235239  <NA> #> 3882  2048A    3M  CC18 2015 2015-03-02         TN -0.3147107448     + #> 3883  2048A    3M  CC18 2015 2015-03-02       TURB  0.7884573604  <NA> #> 3884  2048A    3M  CC18 2015 2015-04-06      CHLAC  3.2580965380     A #> 3885  2048A    3M  CC18 2015 2015-04-06      COLOR  3.6109179126  <NA> #> 3886  2048A    3M  CC18 2015 2015-04-06         DO  2.3025850930  <NA> #> 3887  2048A    3M  CC18 2015 2015-04-06      DOSAT  4.8706066495     + #> 3888  2048A    3M  CC18 2015 2015-04-06       NO23 -4.5098600062  <NA> #> 3889  2048A    3M  CC18 2015 2015-04-06      SALIN  2.7278528284  <NA> #> 3890  2048A    3M  CC18 2015 2015-04-06        TKN  0.4700036292  <NA> #> 3891  2048A    3M  CC18 2015 2015-04-06         TN  0.4768551042     + #> 3892  2048A    3M  CC18 2015 2015-04-06         TP -1.2378743560  <NA> #> 3893  2048A    3M  CC18 2015 2015-04-06       TURB  1.5892352051  <NA> #> 3894  2048A    3M  CC18 2015 2015-06-01      CHLAC  1.3083328197  <NA> #> 3895  2048A    3M  CC18 2015 2015-06-01      COLOR  3.6109179126  <NA> #> 3896  2048A    3M  CC18 2015 2015-06-01         DO  1.3609765531  <NA> #> 3897  2048A    3M  CC18 2015 2015-06-01      DOSAT  3.9834130015     + #> 3898  2048A    3M  CC18 2015 2015-06-01       NO23 -4.7105307016     I #> 3899  2048A    3M  CC18 2015 2015-06-01      SALIN  2.9285235239  <NA> #> 3900  2048A    3M  CC18 2015 2015-06-01        TKN -0.3710636814  <NA> #> 3901  2048A    3M  CC18 2015 2015-06-01         TN -0.3652833185     + #> 3902  2048A    3M  CC18 2015 2015-06-01         TP -1.5141277326  <NA> #> 3903  2048A    3M  CC18 2015 2015-06-01       TURB  0.9555114450  <NA> #> 3904  2048A    3M  CC18 2015 2015-08-03      CHLAC  1.6677068206  <NA> #> 3905  2048A    3M  CC18 2015 2015-08-03      COLOR  5.1929568509  <NA> #> 3906  2048A    3M  CC18 2015 2015-08-03       NO23 -4.5098600062  <NA> #> 3907  2048A    3M  CC18 2015 2015-08-03      SALIN  2.1282317058  <NA> #> 3908  2048A    3M  CC18 2015 2015-08-03        TKN -0.0618754037  <NA> #> 3909  2048A    3M  CC18 2015 2015-08-03         TN -0.0502412164     + #> 3910  2048A    3M  CC18 2015 2015-08-03         TP -1.4271163556  <NA> #> 3911  2048A    3M  CC18 2015 2015-08-03       TURB  0.7884573604  <NA> #> 3912  2048A    3M  CC18 2015 2015-09-08      CHLAC  1.7749523509  <NA> #> 3913  2048A    3M  CC18 2015 2015-09-08      COLOR  5.0751738152  <NA> #> 3914  2048A    3M  CC18 2015 2015-09-08         DO  1.2527629685  <NA> #> 3915  2048A    3M  CC18 2015 2015-09-08      DOSAT  3.6163087613     + #> 3916  2048A    3M  CC18 2015 2015-09-08       NO23 -2.9374633654  <NA> #> 3917  2048A    3M  CC18 2015 2015-09-08      SALIN  1.0647107370  <NA> #> 3918  2048A    3M  CC18 2015 2015-09-08        TKN  0.0000000000  <NA> #> 3919  2048A    3M  CC18 2015 2015-09-08         TN  0.0516432332     + #> 3920  2048A    3M  CC18 2015 2015-09-08         TP -1.5606477483  <NA> #> 3921  2048A    3M  CC18 2015 2015-09-08       TURB  0.0953101798  <NA> #> 3922  2048A    3M  CC18 2015 2015-10-05      CHLAC  0.6418538862  <NA> #> 3923  2048A    3M  CC18 2015 2015-10-05      COLOR  5.0751738152  <NA> #> 3924  2048A    3M  CC18 2015 2015-10-05      DOSAT  4.6091622073     + #> 3925  2048A    3M  CC18 2015 2015-10-05       NO23 -3.0576076773  <NA> #> 3926  2048A    3M  CC18 2015 2015-10-05      SALIN  1.9459101491  <NA> #> 3927  2048A    3M  CC18 2015 2015-10-05        TKN -0.0304592075  <NA> #> 3928  2048A    3M  CC18 2015 2015-10-05         TN  0.0168571171     + #> 3929  2048A    3M  CC18 2015 2015-10-05         TP -1.2039728043  <NA> #> 3930  2048A    3M  CC18 2015 2015-10-05       TURB  0.6418538862  <NA> #> 3931  2048A    3M  CC18 2015 2015-12-07      CHLAC  0.8754687374  <NA> #> 3932  2048A    3M  CC18 2015 2015-12-07      COLOR  3.9120230054  <NA> #> 3933  2048A    3M  CC18 2015 2015-12-07         DO  2.5416019935  <NA> #> 3934  2048A    3M  CC18 2015 2015-12-07       NO23 -3.4420193762  <NA> #> 3935  2048A    3M  CC18 2015 2015-12-07        TKN -0.2876820725  <NA> #> 3936  2048A    3M  CC18 2015 2015-12-07         TN -0.2459005384     + #> 3937  2048A    3M  CC18 2015 2015-12-07         TP -2.2072749132  <NA> #> 3938  2048A    3M  CC18 2015 2015-12-07       TURB  0.1823215568  <NA> #> 3939  2048A    3M  CC18 2016 2016-01-04      CHLAC  4.4188406078  <NA> #> 3940  2048A    3M  CC18 2016 2016-01-04      COLOR  3.6888794541     A #> 3941  2048A    3M  CC18 2016 2016-01-04      DOSAT  3.6888794541     + #> 3942  2048A    3M  CC18 2016 2016-01-04       NO23 -3.2968373663  <NA> #> 3943  2048A    3M  CC18 2016 2016-01-04      SALIN  2.8094026954  <NA> #> 3944  2048A    3M  CC18 2016 2016-01-04        TKN -0.1863295782  <NA> #> 3945  2048A    3M  CC18 2016 2016-01-04         TN -0.1427163022     + #> 3946  2048A    3M  CC18 2016 2016-01-04         TP -2.3025850930  <NA> #> 3947  2048A    3M  CC18 2016 2016-01-04       TURB  0.6931471806  <NA> #> 3948  2048A    3M  CC18 2016 2016-02-01      CHLAC  0.8329091229  <NA> #> 3949  2048A    3M  CC18 2016 2016-02-01      COLOR  4.4659081187  <NA> #> 3950  2048A    3M  CC18 2016 2016-02-01         DO  1.5686159179  <NA> #> 3951  2048A    3M  CC18 2016 2016-02-01      DOSAT  4.0018637094     + #> 3952  2048A    3M  CC18 2016 2016-02-01       NO23 -4.8283137373     I #> 3953  2048A    3M  CC18 2016 2016-02-01      SALIN  2.0281482473  <NA> #> 3954  2048A    3M  CC18 2016 2016-02-01        TKN -0.4155154440  <NA> #> 3955  2048A    3M  CC18 2016 2016-02-01         TN -0.4094731295     + #> 3956  2048A    3M  CC18 2016 2016-02-01         TP -2.4304184645  <NA> #> 3957  2048A    3M  CC18 2016 2016-02-01       TURB  0.2623642645     A #> 3958  2048A    3M  CC18 2016 2016-03-07      CHLAC  0.0953101798     I #> 3959  2048A    3M  CC18 2016 2016-03-07      COLOR  4.1108738642  <NA> #> 3960  2048A    3M  CC18 2016 2016-03-07      DOSAT  4.2076732475     + #> 3961  2048A    3M  CC18 2016 2016-03-07       NO23 -4.8283137373     U #> 3962  2048A    3M  CC18 2016 2016-03-07      SALIN  1.9740810260  <NA> #> 3963  2048A    3M  CC18 2016 2016-03-07         TN -0.0790432073     + #> 3964  2048A    3M  CC18 2016 2016-03-07       TURB  0.6931471806  <NA> #> 3965  2048A    3M  CC18 2016 2016-04-04      CHLAC  1.6677068206  <NA> #> 3966  2048A    3M  CC18 2016 2016-04-04      COLOR  3.8918202981  <NA> #> 3967  2048A    3M  CC18 2016 2016-04-04         DO  1.6677068206  <NA> #> 3968  2048A    3M  CC18 2016 2016-04-04      DOSAT  4.1941898972     + #> 3969  2048A    3M  CC18 2016 2016-04-04       NO23 -5.2983173665     I #> 3970  2048A    3M  CC18 2016 2016-04-04      SALIN  2.3978952728  <NA> #> 3971  2048A    3M  CC18 2016 2016-04-04        TKN -0.3011050928  <NA> #> 3972  2048A    3M  CC18 2016 2016-04-04         TN -0.2957142441     + #> 3973  2048A    3M  CC18 2016 2016-04-04         TP -1.9661128564  <NA> #> 3974  2048A    3M  CC18 2016 2016-04-04       TURB  1.0647107370  <NA> #> 3975  2048A    3M  CC18 2016 2016-05-02      CHLAC  1.1314021115  <NA> #> 3976  2048A    3M  CC18 2016 2016-05-02      COLOR  3.8918202981     A #> 3977  2048A    3M  CC18 2016 2016-05-02         DO  1.3862943611  <NA> #> 3978  2048A    3M  CC18 2016 2016-05-02      DOSAT  4.0109629533     + #> 3979  2048A    3M  CC18 2016 2016-05-02       NO23 -5.5214609179     I #> 3980  2048A    3M  CC18 2016 2016-05-02      SALIN  2.7850112422  <NA> #> 3981  2048A    3M  CC18 2016 2016-05-02        TKN -0.1984509387  <NA> #> 3982  2048A    3M  CC18 2016 2016-05-02         TN -0.1935847491     + #> 3983  2048A    3M  CC18 2016 2016-05-02         TP -1.8325814637  <NA> #> 3984  2048A    3M  CC18 2016 2016-05-02       TURB  0.3364722366  <NA> #> 3985  2048A    3M  CC18 2016 2016-07-05      CHLAC  1.4586150227  <NA> #> 3986  2048A    3M  CC18 2016 2016-07-05      COLOR  4.5747109785  <NA> #> 3987  2048A    3M  CC18 2016 2016-07-05      DOSAT  4.0758410907     + #> 3988  2048A    3M  CC18 2016 2016-07-05       NO23 -5.5214609179     I #> 3989  2048A    3M  CC18 2016 2016-07-05      SALIN  2.1400661635  <NA> #> 3990  2048A    3M  CC18 2016 2016-07-05        TKN  0.0000000000  <NA> #> 3991  2048A    3M  CC18 2016 2016-07-05         TN  0.0039920213     + #> 3992  2048A    3M  CC18 2016 2016-07-05         TP -0.9162907319  <NA> #> 3993  2048A    3M  CC18 2016 2016-07-05       TURB  0.6931471806  <NA> #> 3994  2048A    3M  CC18 2016 2016-08-01      CHLAC  1.9878743482  <NA> #> 3995  2048A    3M  CC18 2016 2016-08-01      COLOR  4.4659081187  <NA> #> 3996  2048A    3M  CC18 2016 2016-08-01       NO23 -5.2983173665     I #> 3997  2048A    3M  CC18 2016 2016-08-01      SALIN  1.9878743482  <NA> #> 3998  2048A    3M  CC18 2016 2016-08-01         TN  0.0989399479     + #> 3999  2048A    3M  CC18 2016 2016-08-01       TURB  0.6931471806  <NA> #> 4000  2048A    3M  CC18 2016 2016-10-03      CHLAC  1.9740810260  <NA> #> 4001  2048A    3M  CC18 2016 2016-10-03      COLOR  4.7004803658  <NA> #> 4002  2048A    3M  CC18 2016 2016-10-03         DO  1.8870696490  <NA> #> 4003  2048A    3M  CC18 2016 2016-10-03      DOSAT  4.4438270356     + #> 4004  2048A    3M  CC18 2016 2016-10-03       NO23 -4.8283137373     I #> 4005  2048A    3M  CC18 2016 2016-10-03      SALIN  1.4158531634  <NA> #> 4006  2048A    3M  CC18 2016 2016-10-03        TKN -0.1625189295  <NA> #> 4007  2048A    3M  CC18 2016 2016-10-03         TN -0.1578240852     + #> 4008  2048A    3M  CC18 2016 2016-10-03         TP -1.6607312068  <NA> #> 4009  2048A    3M  CC18 2016 2016-10-03       TURB  0.5306282511  <NA> #> 4010  2048A    3M  CC18 2016 2016-11-07      CHLAC  0.9932517730  <NA> #> 4011  2048A    3M  CC18 2016 2016-11-07      COLOR  3.8918202981  <NA> #> 4012  2048A    3M  CC18 2016 2016-11-07      DOSAT  3.8501476017     + #> 4013  2048A    3M  CC18 2016 2016-11-07       NO23 -4.1997050779  <NA> #> 4014  2048A    3M  CC18 2016 2016-11-07      SALIN  3.0773122605  <NA> #> 4015  2048A    3M  CC18 2016 2016-11-07        TKN -0.3011050928  <NA> #> 4016  2048A    3M  CC18 2016 2016-11-07         TN -0.2810375297     + #> 4017  2048A    3M  CC18 2016 2016-11-07         TP -1.8971199849  <NA> #> 4018  2048A    3M  CC18 2016 2016-11-07       TURB  1.1939224685  <NA> #> 4019  2048A    3M  CC18 2016 2016-12-05      CHLAC  0.9555114450     I #> 4020  2048A    3M  CC18 2016 2016-12-05      COLOR  3.4657359028  <NA> #> 4021  2048A    3M  CC18 2016 2016-12-05         DO  0.9555114450  <NA> #> 4022  2048A    3M  CC18 2016 2016-12-05      DOSAT  3.5263605246     + #> 4023  2048A    3M  CC18 2016 2016-12-05       NO23 -4.2686979494  <NA> #> 4024  2048A    3M  CC18 2016 2016-12-05      SALIN  3.0726933147  <NA> #> 4025  2048A    3M  CC18 2016 2016-12-05        TKN -0.4780358009  <NA> #> 4026  2048A    3M  CC18 2016 2016-12-05         TN -0.4557063245     + #> 4027  2048A    3M  CC18 2016 2016-12-05         TP -2.4191189092  <NA> #> 4028  2048A    3M  CC18 2016 2016-12-05       TURB  0.6418538862  <NA> #> 4029  2048A    3M  CC18 2017 2017-01-03      CHLAC  0.7884573604  <NA> #> 4030  2048A    3M  CC18 2017 2017-01-03      COLOR  3.2580965380     A #> 4031  2048A    3M  CC18 2017 2017-01-03      DOSAT  3.7999735016     + #> 4032  2048A    3M  CC18 2017 2017-01-03       NO23 -4.3428059215  <NA> #> 4033  2048A    3M  CC18 2017 2017-01-03      SALIN  3.1135153092  <NA> #> 4034  2048A    3M  CC18 2017 2017-01-03        TKN -0.4004775666  <NA> #> 4035  2048A    3M  CC18 2017 2017-01-03         TN -0.3812604194     + #> 4036  2048A    3M  CC18 2017 2017-01-03         TP -2.1202635362  <NA> #> 4037  2048A    3M  CC18 2017 2017-01-03       TURB  1.2809338455  <NA> #> 4038  2048A    3M  CC18 2017 2017-02-06      CHLAC  1.4816045409  <NA> #> 4039  2048A    3M  CC18 2017 2017-02-06      COLOR  3.2188758249  <NA> #> 4040  2048A    3M  CC18 2017 2017-02-06      DOSAT  3.7999735016     + #> 4041  2048A    3M  CC18 2017 2017-02-06       NO23 -4.7105307016     I #> 4042  2048A    3M  CC18 2017 2017-02-06      SALIN  3.1135153092  <NA> #> 4043  2048A    3M  CC18 2017 2017-02-06        TKN -0.3011050928  <NA> #> 4044  2048A    3M  CC18 2017 2017-02-06         TN -0.2957142441     + #> 4045  2048A    3M  CC18 2017 2017-02-06         TP -2.3126354288  <NA> #> 4046  2048A    3M  CC18 2017 2017-02-06       TURB  1.0647107370  <NA> #> 4047  2048A    3M  CC18 2017 2017-03-06      CHLAC  1.6677068206  <NA> #> 4048  2048A    3M  CC18 2017 2017-03-06      COLOR  3.0445224377  <NA> #> 4049  2048A    3M  CC18 2017 2017-03-06         DO  2.0541237337  <NA> #> 4050  2048A    3M  CC18 2017 2017-03-06      DOSAT  4.6071681887     + #> 4051  2048A    3M  CC18 2017 2017-03-06       NO23 -5.5214609179     U #> 4052  2048A    3M  CC18 2017 2017-03-06      SALIN  3.2921262866  <NA> #> 4053  2048A    3M  CC18 2017 2017-03-06        TKN -0.3011050928  <NA> #> 4054  2048A    3M  CC18 2017 2017-03-06         TN -0.2984060358     + #> 4055  2048A    3M  CC18 2017 2017-03-06         TP -2.6592600369  <NA> #> 4056  2048A    3M  CC18 2017 2017-03-06       TURB  1.0986122887  <NA> #> 4057  2048A    3M  CC18 2017 2017-04-03      CHLAC  1.5892352051  <NA> #> 4058  2048A    3M  CC18 2017 2017-04-03      COLOR  3.1354942159  <NA> #> 4059  2048A    3M  CC18 2017 2017-04-03         DO  1.7749523509  <NA> #> 4060  2048A    3M  CC18 2017 2017-04-03      DOSAT  4.3040650932     + #> 4061  2048A    3M  CC18 2017 2017-04-03       NO23 -4.7105307016     I #> 4062  2048A    3M  CC18 2017 2017-04-03      SALIN  1.5260563035  <NA> #> 4063  2048A    3M  CC18 2017 2017-04-03         TN -0.2691874898     + #> 4064  2048A    3M  CC18 2017 2017-04-03       TURB  0.9555114450  <NA> #> 4065  2048A    3M  CC18 2017 2017-05-01      CHLAC  2.2407096893     A #> 4066  2048A    3M  CC18 2017 2017-05-01      COLOR  3.4011973817     A #> 4067  2048A    3M  CC18 2017 2017-05-01         DO  1.9169226122  <NA> #> 4068  2048A    3M  CC18 2017 2017-05-01      DOSAT  4.6061696863     + #> 4069  2048A    3M  CC18 2017 2017-05-01       NO23 -5.5214609179     U #> 4070  2048A    3M  CC18 2017 2017-05-01      SALIN  3.4210000090  <NA> #> 4071  2048A    3M  CC18 2017 2017-05-01        TKN  0.0953101798  <NA> #> 4072  2048A    3M  CC18 2017 2017-05-01         TN  0.0971267107     + #> 4073  2048A    3M  CC18 2017 2017-05-01         TP -2.1202635362  <NA> #> 4074  2048A    3M  CC18 2017 2017-05-01       TURB  1.3609765531  <NA> #> 4075  2048A    3M  CC18 2017 2017-06-05      CHLAC  1.4350845253  <NA> #> 4076  2048A    3M  CC18 2017 2017-06-05      COLOR  3.6635616461  <NA> #> 4077  2048A    3M  CC18 2017 2017-06-05         DO  1.8870696490  <NA> #> 4078  2048A    3M  CC18 2017 2017-06-05      DOSAT  4.6141299274     + #> 4079  2048A    3M  CC18 2017 2017-06-05       NO23 -5.2983173665     I #> 4080  2048A    3M  CC18 2017 2017-06-05      SALIN  3.4843122884  <NA> #> 4081  2048A    3M  CC18 2017 2017-06-05         TN -0.1461825102     + #> 4082  2048A    3M  CC18 2017 2017-06-05       TURB  0.8754687374  <NA> #> 4083  2048A    3M  CC18 2017 2017-07-10      CHLAC  2.0281482473  <NA> #> 4084  2048A    3M  CC18 2017 2017-07-10      COLOR  5.1357984371  <NA> #> 4085  2048A    3M  CC18 2017 2017-07-10         DO  0.8754687374  <NA> #> 4086  2048A    3M  CC18 2017 2017-07-10      DOSAT  3.4904285154     + #> 4087  2048A    3M  CC18 2017 2017-07-10      SALIN  2.3513752572  <NA> #> 4088  2048A    3M  CC18 2017 2017-07-10         TN  0.2768738737     + #> 4089  2048A    3M  CC18 2017 2017-07-10       TURB  0.6931471806  <NA> #> 4090  2048A    3M  CC18 2017 2017-08-07      CHLAC  0.7419373447  <NA> #> 4091  2048A    3M  CC18 2017 2017-08-07      COLOR  5.3471075307  <NA> #> 4092  2048A    3M  CC18 2017 2017-08-07      DOSAT  2.9123506646     + #> 4093  2048A    3M  CC18 2017 2017-08-07       NO23 -2.6592600369  <NA> #> 4094  2048A    3M  CC18 2017 2017-08-07      SALIN  0.9162907319  <NA> #> 4095  2048A    3M  CC18 2017 2017-08-07        TKN  0.1823215568  <NA> #> 4096  2048A    3M  CC18 2017 2017-08-07         TN  0.2390169005     + #> 4097  2048A    3M  CC18 2017 2017-08-07         TP -1.3470736480  <NA> #> 4098  2048A    3M  CC18 2017 2017-08-07       TURB  1.0296194172  <NA> #> 4099  2048A    3M  CC18 2017 2017-09-05      CHLAC  2.2512917986  <NA> #> 4100  2048A    3M  CC18 2017 2017-09-05      COLOR  5.2470240722  <NA> #> 4101  2048A    3M  CC18 2017 2017-09-05         DO  2.2721258855  <NA> #> 4102  2048A    3M  CC18 2017 2017-09-05      DOSAT  4.8354879411     + #> 4103  2048A    3M  CC18 2017 2017-09-05       NO23 -3.2968373663  <NA> #> 4104  2048A    3M  CC18 2017 2017-09-05      SALIN  1.1631508098  <NA> #> 4105  2048A    3M  CC18 2017 2017-09-05        TKN  0.0000000000  <NA> #> 4106  2048A    3M  CC18 2017 2017-09-05         TN  0.0363319292     + #> 4107  2048A    3M  CC18 2017 2017-09-05         TP -1.8971199849  <NA> #> 4108  2048A    3M  CC18 2017 2017-09-05       TURB  0.7419373447  <NA> #> 4109  2048A    3M  CC18 2017 2017-11-06      CHLAC  1.2809338455  <NA> #> 4110  2048A    3M  CC18 2017 2017-11-06      COLOR  4.3307333403  <NA> #> 4111  2048A    3M  CC18 2017 2017-11-06         DO  2.0412203289  <NA> #> 4112  2048A    3M  CC18 2017 2017-11-06       NO23 -4.3428059215  <NA> #> 4113  2048A    3M  CC18 2017 2017-11-06      SALIN  2.2721258855  <NA> #> 4114  2048A    3M  CC18 2017 2017-11-06        TKN -0.3285040670  <NA> #> 4115  2048A    3M  CC18 2017 2017-11-06         TN -0.3106095771     + #> 4116  2048A    3M  CC18 2017 2017-11-06         TP -1.8325814637  <NA> #> 4117  2048A    3M  CC18 2017 2017-11-06       TURB  0.3364722366  <NA> #> 4118  2048A    3M  CC18 2017 2017-12-04      CHLAC  0.8329091229  <NA> #> 4119  2048A    3M  CC18 2017 2017-12-04      COLOR  3.8066624898  <NA> #> 4120  2048A    3M  CC18 2017 2017-12-04         DO  2.0794415417  <NA> #> 4121  2048A    3M  CC18 2017 2017-12-04      DOSAT  4.6700211583     + #> 4122  2048A    3M  CC18 2017 2017-12-04       NO23 -5.5214609179     U #> 4123  2048A    3M  CC18 2017 2017-12-04      SALIN  3.3214324132  <NA> #> 4124  2048A    3M  CC18 2017 2017-12-04        TKN -0.2876820725  <NA> #> 4125  2048A    3M  CC18 2017 2017-12-04         TN -0.2850189550     + #> 4126  2048A    3M  CC18 2017 2017-12-04         TP -2.2072749132  <NA> #> 4127  2048A    3M  CC18 2017 2017-12-04       TURB -0.1625189295  <NA> #> 4128  2048A    3M  CC18 2018 2018-01-02      CHLAC  1.5475625087  <NA> #> 4129  2048A    3M  CC18 2018 2018-01-02      COLOR  3.4965075615  <NA> #> 4130  2048A    3M  CC18 2018 2018-01-02      DOSAT  4.3161538905     + #> 4131  2048A    3M  CC18 2018 2018-01-02       NO23 -5.5214609179     U #> 4132  2048A    3M  CC18 2018 2018-01-02      SALIN  2.4248027257  <NA> #> 4133  2048A    3M  CC18 2018 2018-01-02         TN -0.4910229965     + #> 4134  2048A    3M  CC18 2018 2018-01-02       TURB  0.5877866649  <NA> #> 4135  2048A    3M  CC18 2018 2018-03-05      CHLAC  0.8329091229  <NA> #> 4136  2048A    3M  CC18 2018 2018-03-05      COLOR  3.5835189385  <NA> #> 4137  2048A    3M  CC18 2018 2018-03-05       NO23 -5.5214609179     U #> 4138  2048A    3M  CC18 2018 2018-03-05        TKN -0.3011050928  <NA> #> 4139  2048A    3M  CC18 2018 2018-03-05         TN -0.2984060358     + #> 4140  2048A    3M  CC18 2018 2018-03-05         TP -1.8971199849  <NA> #> 4141  2048A    3M  CC18 2018 2018-03-05       TURB  1.0296194172  <NA> #> 4142  2048A    3M  CC18 2018 2018-04-02      CHLAC  1.6677068206  <NA> #> 4143  2048A    3M  CC18 2018 2018-04-02      COLOR  3.3322045102  <NA> #> 4144  2048A    3M  CC18 2018 2018-04-02      DOSAT  4.2513483110     + #> 4145  2048A    3M  CC18 2018 2018-04-02       NO23 -5.2983173665     I #> 4146  2048A    3M  CC18 2018 2018-04-02      SALIN  3.2027464429  <NA> #> 4147  2048A    3M  CC18 2018 2018-04-02        TKN -0.2613647641  <NA> #> 4148  2048A    3M  CC18 2018 2018-04-02         TN -0.2561834054     + #> 4149  2048A    3M  CC18 2018 2018-04-02         TP -1.9661128564  <NA> #> 4150  2048A    3M  CC18 2018 2018-04-02       TURB  1.3083328197  <NA> #> 4151  2048A    3M  CC18 2018 2018-05-07      CHLAC  1.8562979904  <NA> #> 4152  2048A    3M  CC18 2018 2018-05-07      COLOR  3.3322045102     A #> 4153  2048A    3M  CC18 2018 2018-05-07         DO  2.1016921506  <NA> #> 4154  2048A    3M  CC18 2018 2018-05-07      DOSAT  4.6051701860  <NA> #> 4155  2048A    3M  CC18 2018 2018-05-07       NO23 -5.5214609179     I #> 4156  2048A    3M  CC18 2018 2018-05-07      SALIN  3.2812870850  <NA> #> 4157  2048A    3M  CC18 2018 2018-05-07        TKN -0.0943106795  <NA> #> 4158  2048A    3M  CC18 2018 2018-05-07         TN -0.0899247075     + #> 4159  2048A    3M  CC18 2018 2018-05-07         TP -2.2072749132  <NA> #> 4160  2048A    3M  CC18 2018 2018-05-07       TURB  1.2527629685  <NA> #> 4161  2048A    3M  CC18 2018 2018-06-04      CHLAC  1.8405496334  <NA> #> 4162  2048A    3M  CC18 2018 2018-06-04      COLOR  4.6051701860  <NA> #> 4163  2048A    3M  CC18 2018 2018-06-04         DO  2.0906287311  <NA> #> 4164  2048A    3M  CC18 2018 2018-06-04      DOSAT  4.6011621646  <NA> #> 4165  2048A    3M  CC18 2018 2018-06-04       NO23 -4.6051701860     I #> 4166  2048A    3M  CC18 2018 2018-06-04      SALIN  1.8115620965  <NA> #> 4167  2048A    3M  CC18 2018 2018-06-04        TKN -0.0725706928  <NA> #> 4168  2048A    3M  CC18 2018 2018-06-04         TN -0.0682788408     + #> 4169  2048A    3M  CC18 2018 2018-06-04         TP -1.6094379124  <NA> #> 4170  2048A    3M  CC18 2018 2018-06-04       TURB  0.5306282511  <NA> #> 4171  2048A    3M  CC18 2018 2018-07-09      CHLAC  2.4849066498  <NA> #> 4172  2048A    3M  CC18 2018 2018-07-09      COLOR  4.9416424226  <NA> #> 4173  2048A    3M  CC18 2018 2018-07-09         DO  1.4929040962  <NA> #> 4174  2048A    3M  CC18 2018 2018-07-09      DOSAT  4.1415461637  <NA> #> 4175  2048A    3M  CC18 2018 2018-07-09       NO23 -4.9618451299     I #> 4176  2048A    3M  CC18 2018 2018-07-09      SALIN  1.3402504226  <NA> #> 4177  2048A    3M  CC18 2018 2018-07-09        TKN -0.2231435513  <NA> #> 4178  2048A    3M  CC18 2018 2018-07-09         TN -0.2181560098     + #> 4179  2048A    3M  CC18 2018 2018-07-09         TP -1.7719568419  <NA> #> 4180  2048A    3M  CC18 2018 2018-07-09       TURB  0.8754687374  <NA> #> 4181  2048A    3M  CC18 2019 2019-05-06      CHLAC  0.9555114450  <NA> #> 4182  2048A    3M  CC18 2019 2019-05-06      COLOR  3.6109179126  <NA> #> 4183  2048A    3M  CC18 2019 2019-05-06         DO  0.8837675402  <NA> #> 4184  2048A    3M  CC18 2019 2019-05-06      DOSAT  3.5351453542  <NA> #> 4185  2048A    3M  CC18 2019 2019-05-06       NO23 -5.2983173665     I #> 4186  2048A    3M  CC18 2019 2019-05-06      SALIN  2.9719517449  <NA> #> 4187  2048A    3M  CC18 2019 2019-05-06        TKN -0.2744368457  <NA> #> 4188  2048A    3M  CC18 2019 2019-05-06         TN -0.2691874898     + #> 4189  2048A    3M  CC18 2019 2019-05-06         TP -1.7719568419  <NA> #> 4190  2048A    3M  CC18 2019 2019-05-06       TURB  0.7419373447  <NA> #> 4191  2048A    3M  CC18 2019 2019-06-03      CHLAC  1.5686159179  <NA> #> 4192  2048A    3M  CC18 2019 2019-06-03      COLOR  3.7376696183  <NA> #> 4193  2048A    3M  CC18 2019 2019-06-03         DO  0.6418538862  <NA> #> 4194  2048A    3M  CC18 2019 2019-06-03      DOSAT  3.3322045102  <NA> #> 4195  2048A    3M  CC18 2019 2019-06-03       NO23 -5.5214609179     U #> 4196  2048A    3M  CC18 2019 2019-06-03      SALIN  3.0363942553  <NA> #> 4197  2048A    3M  CC18 2019 2019-06-03        TKN -0.0725706928  <NA> #> 4198  2048A    3M  CC18 2019 2019-06-03         TN -0.0704224643     + #> 4199  2048A    3M  CC18 2019 2019-06-03         TP -1.3470736480  <NA> #> 4200  2048A    3M  CC18 2019 2019-06-03       TURB  1.4586150227     A #> 4201  2048A    3M  CC18 2019 2019-07-01      CHLAC  1.6863989536  <NA> #> 4202  2048A    3M  CC18 2019 2019-07-01      COLOR  3.6635616461  <NA> #> 4203  2048A    3M  CC18 2019 2019-07-01         DO  0.9162907319  <NA> #> 4204  2048A    3M  CC18 2019 2019-07-01      DOSAT  3.4483989831  <NA> #> 4205  2048A    3M  CC18 2019 2019-07-01       NO23 -5.5214609179     U #> 4206  2048A    3M  CC18 2019 2019-07-01      SALIN  2.9678470701  <NA> #> 4207  2048A    3M  CC18 2019 2019-07-01        TKN -0.2484613593  <NA> #> 4208  2048A    3M  CC18 2019 2019-07-01         TN -0.2459005384     + #> 4209  2048A    3M  CC18 2019 2019-07-01         TP -1.2729656758  <NA> #> 4210  2048A    3M  CC18 2019 2019-07-01       TURB  0.4054651081  <NA> #> 4211  2048A    3M  CC18 2019 2019-08-05      CHLAC  1.4109869737  <NA> #> 4212  2048A    3M  CC18 2019 2019-08-05      COLOR  5.0751738152  <NA> #> 4213  2048A    3M  CC18 2019 2019-08-05         DO  1.1378330018  <NA> #> 4214  2048A    3M  CC18 2019 2019-08-05      DOSAT  3.7305011288  <NA> #> 4215  2048A    3M  CC18 2019 2019-08-05       NO23 -5.5214609179     I #> 4216  2048A    3M  CC18 2019 2019-08-05      SALIN  1.6134299337  <NA> #> 4217  2048A    3M  CC18 2019 2019-08-05        TKN -0.0618754037  <NA> #> 4218  2048A    3M  CC18 2019 2019-08-05         TN -0.0576291128     + #> 4219  2048A    3M  CC18 2019 2019-08-05         TP -1.5606477483  <NA> #> 4220  2048A    3M  CC18 2019 2019-08-05       TURB  0.8754687374  <NA> #> 4221  2048A    3M  CC18 2019 2019-10-07      CHLAC  1.0986122887     I #> 4222  2048A    3M  CC18 2019 2019-10-07      COLOR  4.3820266347  <NA> #> 4223  2048A    3M  CC18 2019 2019-10-07         DO  1.0152306797  <NA> #> 4224  2048A    3M  CC18 2019 2019-10-07      DOSAT  3.6375861597  <NA> #> 4225  2048A    3M  CC18 2019 2019-10-07       NO23 -4.9618451299     I #> 4226  2048A    3M  CC18 2019 2019-10-07      SALIN  2.7389026646  <NA> #> 4227  2048A    3M  CC18 2019 2019-10-07        TKN -0.1278333715  <NA> #> 4228  2048A    3M  CC18 2019 2019-10-07         TN -0.1232982163     + #> 4229  2048A    3M  CC18 2019 2019-10-07         TP -1.3862943611  <NA> #> 4230  2048A    3M  CC18 2019 2019-10-07       TURB  0.4054651081  <NA> #> 4231  2048A    3M  CC18 2019 2019-11-04      CHLAC  1.0296194172  <NA> #> 4232  2048A    3M  CC18 2019 2019-11-04      COLOR  4.1431347264  <NA> #> 4233  2048A    3M  CC18 2019 2019-11-04         DO  1.2267122913  <NA> #> 4234  2048A    3M  CC18 2019 2019-11-04      DOSAT  3.8177123260  <NA> #> 4235  2048A    3M  CC18 2019 2019-11-04       NO23 -5.5214609179     I #> 4236  2048A    3M  CC18 2019 2019-11-04      SALIN  2.8075938314  <NA> #> 4237  2048A    3M  CC18 2019 2019-11-04        TKN -0.1508228897  <NA> #> 4238  2048A    3M  CC18 2019 2019-11-04         TN -0.1461825102     + #> 4239  2048A    3M  CC18 2019 2019-11-04         TP -1.6094379124  <NA> #> 4240  2048A    3M  CC18 2019 2019-11-04       TURB  0.2623642645     A #> 4241  2048A    3M  CC18 2019 2019-11-04         DO  1.2267122913  <NA> #> 4242  2048A    3M  CC18 2019 2019-11-04      DOSAT  3.8177123260  <NA> #> 4243  2048A    3M  CC18 2019 2019-11-04      SALIN  2.8075938314  <NA> #> 4244  2048A    3M  CC18 2019 2019-12-02      CHLAC  1.2809338455  <NA> #> 4245  2048A    3M  CC18 2019 2019-12-02      COLOR  3.6888794541     A #> 4246  2048A    3M  CC18 2019 2019-12-02         DO  1.5518087996  <NA> #> 4247  2048A    3M  CC18 2019 2019-12-02      DOSAT  4.1059436981  <NA> #> 4248  2048A    3M  CC18 2019 2019-12-02       NO23 -5.5214609179     U #> 4249  2048A    3M  CC18 2019 2019-12-02      SALIN  2.9412760878  <NA> #> 4250  2048A    3M  CC18 2019 2019-12-02        TKN -0.2613647641  <NA> #> 4251  2048A    3M  CC18 2019 2019-12-02         TN -0.2587707290     + #> 4252  2048A    3M  CC18 2019 2019-12-02         TP -2.2072749132  <NA> #> 4253  2048A    3M  CC18 2019 2019-12-02       TURB  0.0953101798  <NA> #> 4254  2048A    3M  CC18 2020 2020-01-06      CHLAC  1.7578579176  <NA> #> 4255  2048A    3M  CC18 2020 2020-01-06      COLOR  3.5263605246  <NA> #> 4256  2048A    3M  CC18 2020 2020-01-06         DO  1.6770965609  <NA> #> 4257  2048A    3M  CC18 2020 2020-01-06      DOSAT  4.1541845626  <NA> #> 4258  2048A    3M  CC18 2020 2020-01-06       NO23 -5.5214609179     U #> 4259  2048A    3M  CC18 2020 2020-01-06      SALIN  2.8713021952  <NA> #> 4260  2048A    3M  CC18 2020 2020-01-06        TKN -0.5276327421  <NA> #> 4261  2048A    3M  CC18 2020 2020-01-06         TN -0.5242486441     + #> 4262  2048A    3M  CC18 2020 2020-01-06         TP -1.8971199849  <NA> #> 4263  2048A    3M  CC18 2020 2020-01-06       TURB  0.3364722366  <NA> #> 4264  2048A    3M  CC18 2020 2020-02-03      CHLAC  2.6390573296  <NA> #> 4265  2048A    3M  CC18 2020 2020-02-03      COLOR  3.3672958300  <NA> #> 4266  2048A    3M  CC18 2020 2020-02-03         DO  1.7137979278  <NA> #> 4267  2048A    3M  CC18 2020 2020-02-03      DOSAT  4.1941898972  <NA> #> 4268  2048A    3M  CC18 2020 2020-02-03       NO23 -4.8283137373     I #> 4269  2048A    3M  CC18 2020 2020-02-03      SALIN  2.9538680695  <NA> #> 4270  2048A    3M  CC18 2020 2020-02-03        TKN -0.0725706928  <NA> #> 4271  2048A    3M  CC18 2020 2020-02-03         TN -0.0682788408     + #> 4272  2048A    3M  CC18 2020 2020-02-03         TP -1.9661128564  <NA> #> 4273  2048A    3M  CC18 2020 2020-02-03       TURB  2.1400661635  <NA> #> 4274  2048A    3M  CC18 2020 2020-03-02      CHLAC  1.8562979904  <NA> #> 4275  2048A    3M  CC18 2020 2020-03-02      COLOR  3.2958368660  <NA> #> 4276  2048A    3M  CC18 2020 2020-03-02         DO  2.1388890003  <NA> #> 4277  2048A    3M  CC18 2020 2020-03-02      DOSAT  4.6530075154  <NA> #> 4278  2048A    3M  CC18 2020 2020-03-02       NO23 -5.5214609179     I #> 4279  2048A    3M  CC18 2020 2020-03-02      SALIN  3.0061775314  <NA> #> 4280  2048A    3M  CC18 2020 2020-03-02        TKN -0.3710636814  <NA> #> 4281  2048A    3M  CC18 2020 2020-03-02         TN -0.3652833185     + #> 4282  2048A    3M  CC18 2020 2020-03-02         TP -2.3025850930  <NA> #> 4283  2048A    3M  CC18 2020 2020-03-02       TURB  1.3609765531  <NA> #> 4284  2048A    3M  CC18 2020 2020-09-08      CHLAC  1.2809338455  <NA> #> 4285  2048A    3M  CC18 2020 2020-09-08      COLOR  4.5432947823  <NA> #> 4286  2048A    3M  CC18 2020 2020-09-08         DO  0.6418538862  <NA> #> 4287  2048A    3M  CC18 2020 2020-09-08      DOSAT  3.2809112158  <NA> #> 4288  2048A    3M  CC18 2020 2020-09-08       NO23 -4.3428059215  <NA> #> 4289  2048A    3M  CC18 2020 2020-09-08      SALIN  2.8237570088  <NA> #> 4290  2048A    3M  CC18 2020 2020-09-08        TKN -0.2231435513  <NA> #> 4291  2048A    3M  CC18 2020 2020-09-08         TN -0.2070241694     + #> 4292  2048A    3M  CC18 2020 2020-09-08         TP -1.3470736480  <NA> #> 4293  2048A    3M  CC18 2020 2020-09-08       TURB  0.9555114450  <NA> #> 4294  2048A    3M  CC18 2020 2020-10-05         DO  1.0885619528  <NA> #> 4295  2048A    3M  CC18 2020 2020-10-05      DOSAT  3.6323091026  <NA> #> 4296  2048A    3M  CC18 2020 2020-10-05       NO23 -3.3524072175  <NA> #> 4297  2048A    3M  CC18 2020 2020-10-05        TKN  0.0000000000  <NA> #> 4298  2048A    3M  CC18 2020 2020-10-05         TN  0.0344014267     + #> 4299  2048A    3M  CC18 2020 2020-10-05         TP -1.4696759701  <NA> #> 4300  2048A    3M  CC18 2020 2020-11-02      CHLAC  1.4816045409     I #> 4301  2048A    3M  CC18 2020 2020-11-02      COLOR  4.7004803658  <NA> #> 4302  2048A    3M  CC18 2020 2020-11-02         DO  1.1631508098  <NA> #> 4303  2048A    3M  CC18 2020 2020-11-02      DOSAT  3.7376696183  <NA> #> 4304  2048A    3M  CC18 2020 2020-11-02       NO23 -3.0365542681  <NA> #> 4305  2048A    3M  CC18 2020 2020-11-02      SALIN  2.2884861686  <NA> #> 4306  2048A    3M  CC18 2020 2020-11-02        TKN -0.1743533871  <NA> #> 4307  2048A    3M  CC18 2020 2020-11-02         TN -0.1187835360     + #> 4308  2048A    3M  CC18 2020 2020-11-02         TP -1.4271163556  <NA> #> 4309  2048A    3M  CC18 2020 2020-11-02       TURB  0.8329091229  <NA> #> 4310  2048A    3M  CC18 2020 2020-12-07      CHLAC  0.6931471806     I #> 4311  2048A    3M  CC18 2020 2020-12-07      COLOR  4.2195077052  <NA> #> 4312  2048A    3M  CC18 2020 2020-12-07         DO  1.7783364489  <NA> #> 4313  2048A    3M  CC18 2020 2020-12-07      DOSAT  4.2297491992  <NA> #> 4314  2048A    3M  CC18 2020 2020-12-07       NO23 -4.6051701860  <NA> #> 4315  2048A    3M  CC18 2020 2020-12-07      SALIN  2.8870328566  <NA> #> 4316  2048A    3M  CC18 2020 2020-12-07        TKN -0.0202027073  <NA> #> 4317  2048A    3M  CC18 2020 2020-12-07         TN -0.0100503359     + #> 4318  2048A    3M  CC18 2020 2020-12-07         TP -1.7719568419  <NA> #> 4319  2048A    3M  CC18 2020 2020-12-07       TURB  1.4350845253  <NA> #> 4320  2048A    3M  CC18 2021 2021-01-04      CHLAC  0.5306282511     I #> 4321  2048A    3M  CC18 2021 2021-01-04      COLOR  3.9120230054     A #> 4322  2048A    3M  CC18 2021 2021-01-04       NO23 -5.1159958098     I #> 4323  2048A    3M  CC18 2021 2021-01-04      SALIN  2.6518325211  <NA> #> 4324  2048A    3M  CC18 2021 2021-01-04        TKN -0.2231435513  <NA> #> 4325  2048A    3M  CC18 2021 2021-01-04         TN -0.2181560098     + #> 4326  2048A    3M  CC18 2021 2021-01-04         TP -2.3025850930  <NA> #> 4327  2048A    3M  CC18 2021 2021-01-04       TURB  0.1823215568  <NA> #> 4328  2048A    3M  CC18 2021 2021-02-01      CHLAC  0.8329091229     I #> 4329  2048A    3M  CC18 2021 2021-02-01      COLOR  3.5553480615  <NA> #> 4330  2048A    3M  CC18 2021 2021-02-01       NO23 -5.5214609179     U #> 4331  2048A    3M  CC18 2021 2021-02-01      SALIN  2.8219739474  <NA> #> 4332  2048A    3M  CC18 2021 2021-02-01        TKN -0.4462871026  <NA> #> 4333  2048A    3M  CC18 2021 2021-02-01         TN -0.4431669753     + #> 4334  2048A    3M  CC18 2021 2021-02-01         TP -2.3025850930  <NA> #> 4335  2048A    3M  CC18 2021 2021-02-01       TURB  0.0000000000  <NA> #> 4336  2048A    3M  CC18 2021 2021-03-01      CHLAC  1.3350010667  <NA> #> 4337  2048A    3M  CC18 2021 2021-03-01      COLOR  3.6109179126  <NA> #> 4338  2048A    3M  CC18 2021 2021-03-01       NO23 -4.9618451299     I #> 4339  2048A    3M  CC18 2021 2021-03-01        TKN -0.5276327421  <NA> #> 4340  2048A    3M  CC18 2021 2021-03-01         TN -0.5208759596     + #> 4341  2048A    3M  CC18 2021 2021-03-01         TP -2.0402208285  <NA> #> 4342  2048A    3M  CC18 2021 2021-03-01       TURB  0.8329091229  <NA> #> 4343  2048A    3M  CC18 2021 2021-04-05      CHLAC  0.4700036292     I #> 4344  2048A    3M  CC18 2021 2021-04-05      COLOR  3.3672958300  <NA> #> 4345  2048A    3M  CC18 2021 2021-04-05         DO  1.8245492921  <NA> #> 4346  2048A    3M  CC18 2021 2021-04-05      DOSAT  4.3870141762  <NA> #> 4347  2048A    3M  CC18 2021 2021-04-05       NO23 -5.2983173665     I #> 4348  2048A    3M  CC18 2021 2021-04-05      SALIN  3.1170645587  <NA> #> 4349  2048A    3M  CC18 2021 2021-04-05        TKN -0.4155154440  <NA> #> 4350  2048A    3M  CC18 2021 2021-04-05         TN -0.4094731295     + #> 4351  2048A    3M  CC18 2021 2021-04-05         TP -2.3434070875  <NA> #> 4352  2048A    3M  CC18 2021 2021-04-05       TURB  0.3364722366  <NA> #> 4353  2048A    3M  CC18 2021 2021-05-03      CHLAC  1.5475625087  <NA> #> 4354  2048A    3M  CC18 2021 2021-05-03      COLOR  3.4339872045     A #> 4355  2048A    3M  CC18 2021 2021-05-03         DO  1.4182774070  <NA> #> 4356  2048A    3M  CC18 2021 2021-05-03      DOSAT  4.1174098352  <NA> #> 4357  2048A    3M  CC18 2021 2021-05-03       NO23 -5.5214609179     I #> 4358  2048A    3M  CC18 2021 2021-05-03      SALIN  3.1726224404  <NA> #> 4359  2048A    3M  CC18 2021 2021-05-03        TKN -0.3566749439  <NA> #> 4360  2048A    3M  CC18 2021 2021-05-03         TN -0.3509769228     + #> 4361  2048A    3M  CC18 2021 2021-05-03         TP -1.8325814637  <NA> #> 4362  2048A    3M  CC18 2021 2021-05-03       TURB  0.5877866649  <NA> #> 4363  2048A    3M  CC18 2021 2021-06-07      CHLAC  1.5686159179     I #> 4364  2048A    3M  CC18 2021 2021-06-07      COLOR  3.5835189385  <NA> #> 4365  2048A    3M  CC18 2021 2021-06-07         DO  1.0508216248  <NA> #> 4366  2048A    3M  CC18 2021 2021-06-07      DOSAT  4.2918283668  <NA> #> 4367  2048A    3M  CC18 2021 2021-06-07       NO23 -5.2983173665     I #> 4368  2048A    3M  CC18 2021 2021-06-07      SALIN  3.2476576263  <NA> #> 4369  2048A    3M  CC18 2021 2021-06-07        TKN -0.2484613593  <NA> #> 4370  2048A    3M  CC18 2021 2021-06-07         TN -0.2433462586     + #> 4371  2048A    3M  CC18 2021 2021-06-07         TP -1.5141277326  <NA> #> 4372  2048A    3M  CC18 2021 2021-06-07       TURB  0.5306282511  <NA> #> 4373  2048A    3M  CC18 2021 2021-08-02      CHLAC  1.8082887712  <NA> #> 4374  2048A    3M  CC18 2021 2021-08-02      COLOR  5.0106352941  <NA> #> 4375  2048A    3M  CC18 2021 2021-08-02         DO  0.0582689081  <NA> #> 4376  2048A    3M  CC18 2021 2021-08-02      DOSAT  2.7080502011  <NA> #> 4377  2048A    3M  CC18 2021 2021-08-02       NO23 -5.5214609179     U #> 4378  2048A    3M  CC18 2021 2021-08-02      SALIN  1.8702625307  <NA> #> 4379  2048A    3M  CC18 2021 2021-08-02        TKN  0.0953101798  <NA> #> 4380  2048A    3M  CC18 2021 2021-08-02         TN  0.0971267107     + #> 4381  2048A    3M  CC18 2021 2021-08-02         TP -0.9416085399  <NA> #> 4382  2048A    3M  CC18 2021 2021-08-02       TURB  1.0986122887     A #> 4383  2048A    3M  CC18 2021 2021-09-07      CHLAC  1.7917594692  <NA> #> 4384  2048A    3M  CC18 2021 2021-09-07      COLOR  4.9416424226  <NA> #> 4385  2048A    3M  CC18 2021 2021-09-07       NO23 -3.6888794541  <NA> #> 4386  2048A    3M  CC18 2021 2021-09-07      SALIN  1.5581446180  <NA> #> 4387  2048A    3M  CC18 2021 2021-09-07        TKN -0.0725706928  <NA> #> 4388  2048A    3M  CC18 2021 2021-09-07         TN -0.0460439385     + #> 4389  2048A    3M  CC18 2021 2021-09-07         TP -1.6094379124  <NA> #> 4390  2048A    3M  CC18 2021 2021-09-07       TURB  0.4054651081  <NA> #> 4391  2048A    3M  CC18 2021 2021-10-04      CHLAC  1.0986122887  <NA> #> 4392  2048A    3M  CC18 2021 2021-10-04      COLOR  5.0106352941  <NA> #> 4393  2048A    3M  CC18 2021 2021-10-04         DO  1.1631508098  <NA> #> 4394  2048A    3M  CC18 2021 2021-10-04      DOSAT  3.7208625000  <NA> #> 4395  2048A    3M  CC18 2021 2021-10-04       NO23 -3.2441936329  <NA> #> 4396  2048A    3M  CC18 2021 2021-10-04      SALIN  1.5390154481  <NA> #> 4397  2048A    3M  CC18 2021 2021-10-04        TKN -0.0304592075  <NA> #> 4398  2048A    3M  CC18 2021 2021-10-04         TN  0.0089597414     + #> 4399  2048A    3M  CC18 2021 2021-10-04         TP -1.4696759701  <NA> #> 4400  2048A    3M  CC18 2021 2021-10-04       TURB -0.1625189295  <NA> #> 4401  2048A    3M  CC18 2021 2021-11-01      CHLAC  0.9162907319     I #> 4402  2048A    3M  CC18 2021 2021-11-01      COLOR  4.3567088267  <NA> #> 4403  2048A    3M  CC18 2021 2021-11-01         DO  1.5973653312  <NA> #> 4404  2048A    3M  CC18 2021 2021-11-01      DOSAT  4.1447207695  <NA> #> 4405  2048A    3M  CC18 2021 2021-11-01       NO23 -3.1700856607  <NA> #> 4406  2048A    3M  CC18 2021 2021-11-01        TKN -0.2744368457  <NA> #> 4407  2048A    3M  CC18 2021 2021-11-01         TN -0.2206466711     + #> 4408  2048A    3M  CC18 2021 2021-11-01         TP -1.5141277326  <NA> #> 4409  2048A    3M  CC18 2021 2021-11-01       TURB  0.0953101798  <NA> #> 4410  2048A    3M  CC18 2021 2021-12-06      CHLAC  0.9932517730     I #> 4411  2048A    3M  CC18 2021 2021-12-06      COLOR  3.4657359028  <NA> #> 4412  2048A    3M  CC18 2021 2021-12-06         DO  1.7351891177  <NA> #> 4413  2048A    3M  CC18 2021 2021-12-06      DOSAT  4.2794400459  <NA> #> 4414  2048A    3M  CC18 2021 2021-12-06       NO23 -5.2983173665     I #> 4415  2048A    3M  CC18 2021 2021-12-06      SALIN  3.4452142671  <NA> #> 4416  2048A    3M  CC18 2021 2021-12-06        TKN -0.7550225843  <NA> #> 4417  2048A    3M  CC18 2021 2021-12-06         TN -0.7465479573     + #> 4418  2048A    3M  CC18 2021 2021-12-06         TP -2.3126354288  <NA> #> 4419  2048A    3M  CC18 2021 2021-12-06       TURB -0.2876820725  <NA> #> 4420  2048A    3M  CC18 2022 2022-01-03      CHLAC  0.8329091229     I #> 4421  2048A    3M  CC18 2022 2022-01-03      COLOR  3.3322045102     A #> 4422  2048A    3M  CC18 2022 2022-01-03         DO  1.6733512382  <NA> #> 4423  2048A    3M  CC18 2022 2022-01-03      DOSAT  4.2541932632  <NA> #> 4424  2048A    3M  CC18 2022 2022-01-03       NO23 -4.9618451299     I #> 4425  2048A    3M  CC18 2022 2022-01-03      SALIN  2.9714395810  <NA> #> 4426  2048A    3M  CC18 2022 2022-01-03        TKN -0.6348782724  <NA> #> 4427  2048A    3M  CC18 2022 2022-01-03         TN -0.6273594400     + #> 4428  2048A    3M  CC18 2022 2022-01-03         TP -2.5902671654  <NA> #> 4429  2048A    3M  CC18 2022 2022-01-03       TURB  0.1823215568  <NA> #> 4430  2048A    3M  CC18 2022 2022-02-07      CHLAC  0.6931471806     I #> 4431  2048A    3M  CC18 2022 2022-02-07      COLOR  3.0910424534     A #> 4432  2048A    3M  CC18 2022 2022-02-07         DO  0.0000000000  <NA> #> 4433  2048A    3M  CC18 2022 2022-02-07      DOSAT  4.0412953411  <NA> #> 4434  2048A    3M  CC18 2022 2022-02-07       NO23 -4.7105307016     I #> 4435  2048A    3M  CC18 2022 2022-02-07      SALIN  3.1144038033  <NA> #> 4436  2048A    3M  CC18 2022 2022-02-07        TKN -0.4620354596  <NA> #> 4437  2048A    3M  CC18 2022 2022-02-07         TN -0.4557063245     + #> 4438  2048A    3M  CC18 2022 2022-02-07         TP -2.4418471603  <NA> #> 4439  2048A    3M  CC18 2022 2022-02-07       TURB  0.6931471806  <NA> #> 4440  2048A    3M  CC18 2022 2022-03-07      CHLAC  1.0647107370     I #> 4441  2048A    3M  CC18 2022 2022-03-07      COLOR  3.2580965380  <NA> #> 4442  2048A    3M  CC18 2022 2022-03-07         DO  1.3217558400  <NA> #> 4443  2048A    3M  CC18 2022 2022-03-07      DOSAT  3.9318256327  <NA> #> 4444  2048A    3M  CC18 2022 2022-03-07       NO23 -4.7105307016     I #> 4445  2048A    3M  CC18 2022 2022-03-07      SALIN  3.2216719122  <NA> #> 4446  2048A    3M  CC18 2022 2022-03-07        TKN -0.0304592075  <NA> #> 4447  2048A    3M  CC18 2022 2022-03-07         TN -0.0263439753     + #> 4448  2048A    3M  CC18 2022 2022-03-07         TP -2.1202635362  <NA> #> 4449  2048A    3M  CC18 2022 2022-03-07       TURB  1.3083328197  <NA> #> 4450  2048A    3M  CC18 2022 2022-04-04      CHLAC  1.7227665977  <NA> #> 4451  2048A    3M  CC18 2022 2022-04-04      COLOR  3.2580965380     A #> 4452  2048A    3M  CC18 2022 2022-04-04         DO  1.3244189574  <NA> #> 4453  2048A    3M  CC18 2022 2022-04-04      DOSAT  3.9415818077  <NA> #> 4454  2048A    3M  CC18 2022 2022-04-04       NO23 -4.6051701860  <NA> #> 4455  2048A    3M  CC18 2022 2022-04-04      SALIN  3.2928695048  <NA> #> 4456  2048A    3M  CC18 2022 2022-04-04        TKN -0.3856624808  <NA> #> 4457  2048A    3M  CC18 2022 2022-04-04         TN -0.3710636814     + #> 4458  2048A    3M  CC18 2022 2022-04-04         TP -1.8325814637  <NA> #> 4459  2048A    3M  CC18 2022 2022-04-04       TURB  1.3350010667  <NA> #> 4460  2048A    3M  CC18 2022 2022-05-02      CHLAC  0.9162907319     I #> 4461  2048A    3M  CC18 2022 2022-05-02      COLOR  3.4965075615     A #> 4462  2048A    3M  CC18 2022 2022-05-02         DO  1.3164082337  <NA> #> 4463  2048A    3M  CC18 2022 2022-05-02      DOSAT  3.9550824949  <NA> #> 4464  2048A    3M  CC18 2022 2022-05-02       NO23 -4.1997050779  <NA> #> 4465  2048A    3M  CC18 2022 2022-05-02      SALIN  3.2343553957  <NA> #> 4466  2048A    3M  CC18 2022 2022-05-02        TKN -0.3566749439  <NA> #> 4467  2048A    3M  CC18 2022 2022-05-02         TN -0.3354727363     + #> 4468  2048A    3M  CC18 2022 2022-05-02         TP -1.8971199849  <NA> #> 4469  2048A    3M  CC18 2022 2022-05-02       TURB  0.8329091229  <NA> #> 4470  2048A    3M  CC18 2022 2022-06-06      CHLAC  1.8562979904  <NA> #> 4471  2048A    3M  CC18 2022 2022-06-06      COLOR  3.5553480615  <NA> #> 4472  2048A    3M  CC18 2022 2022-06-06         DO  1.3480731483  <NA> #> 4473  2048A    3M  CC18 2022 2022-06-06      DOSAT  4.0377742107  <NA> #> 4474  2048A    3M  CC18 2022 2022-06-06       NO23 -5.1159958098     I #> 4475  2048A    3M  CC18 2022 2022-06-06      SALIN  3.1759683239  <NA> #> 4476  2048A    3M  CC18 2022 2022-06-06        TKN -0.4004775666  <NA> #> 4477  2048A    3M  CC18 2022 2022-06-06         TN -0.3945251681     + #> 4478  2048A    3M  CC18 2022 2022-06-06         TP -1.6094379124  <NA> #> 4479  2048A    3M  CC18 2022 2022-06-06       TURB  0.5877866649  <NA> #> 4480  2048A    3M  CC18 2022 2022-09-06      CHLAC  2.3978952728  <NA> #> 4481  2048A    3M  CC18 2022 2022-09-06      COLOR  4.3820266347  <NA> #> 4482  2048A    3M  CC18 2022 2022-09-06         DO  1.1939224685  <NA> #> 4483  2048A    3M  CC18 2022 2022-09-06      DOSAT  3.8372994592  <NA> #> 4484  2048A    3M  CC18 2022 2022-09-06       NO23 -5.5214609179     U #> 4485  2048A    3M  CC18 2022 2022-09-06      SALIN  2.0967901800  <NA> #> 4486  2048A    3M  CC18 2022 2022-09-06        TKN -0.1165338163  <NA> #> 4487  2048A    3M  CC18 2022 2022-09-06         TN -0.1142891464     + #> 4488  2048A    3M  CC18 2022 2022-09-06         TP -1.7147984281  <NA> #> 4489  2048A    3M  CC18 2022 2022-09-06       TURB  1.2527629685  <NA> #> 4490  2048A    3M  CC18 2022 2022-11-07      CHLAC  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3M  CC18 2022 2022-12-05        TKN -0.1984509387  <NA> #> 4505  2048A    3M  CC18 2022 2022-12-05         TN -0.1863295782     + #> 4506  2048A    3M  CC18 2022 2022-12-05         TP -1.7719568419  <NA> #> 4507  2048A    3M  CC18 2022 2022-12-05       TURB -0.0512932944     I #> 4508  2048A    3M  CC18 2023 2023-02-06      CHLAC  1.5260563035  <NA> #> 4509  2048A    3M  CC18 2023 2023-02-06      COLOR  3.4657359028  <NA> #> 4510  2048A    3M  CC18 2023 2023-02-06         DO  1.6863989536  <NA> #> 4511  2048A    3M  CC18 2023 2023-02-06      DOSAT  4.2341065046  <NA> #> 4512  2048A    3M  CC18 2023 2023-02-06       NO23 -5.2983173665     I #> 4513  2048A    3M  CC18 2023 2023-02-06      SALIN  2.9269179576  <NA> #> 4514  2048A    3M  CC18 2023 2023-02-06        TKN -0.4155154440  <NA> #> 4515  2048A    3M  CC18 2023 2023-02-06         TN -0.4094731295     + #> 4516  2048A    3M  CC18 2023 2023-02-06         TP -2.1202635362  <NA> #> 4517  2048A    3M  CC18 2023 2023-02-06       TURB  0.6931471806  <NA> #> 4518  2048A    3M  CC18 2023 2023-03-06      CHLAC  1.8718021769  <NA> #> 4519  2048A    3M  CC18 2023 2023-03-06      COLOR  3.3672958300  <NA> #> 4520  2048A    3M  CC18 2023 2023-03-06         DO  1.1442227999  <NA> #> 4521  2048A    3M  CC18 2023 2023-03-06      DOSAT  3.7977338590  <NA> #> 4522  2048A    3M  CC18 2023 2023-03-06       NO23 -4.4228486292  <NA> #> 4523  2048A    3M  CC18 2023 2023-03-06      SALIN  3.0199369623  <NA> #> 4524  2048A    3M  CC18 2023 2023-03-06        TKN  0.1823215568  <NA> #> 4525  2048A    3M  CC18 2023 2023-03-06         TN  0.1922718876     + #> 4526  2048A    3M  CC18 2023 2023-03-06         TP -1.9661128564  <NA> #> 4527  2048A    3M  CC18 2023 2023-03-06       TURB  0.7884573604  <NA> #> 4528 2060A1     2  CC25 2014 2014-02-12      CHLAC  1.4109869737  <NA> #> 4529 2060A1     2  CC25 2014 2014-02-12      COLOR  3.2188758249  <NA> #> 4530 2060A1     2  CC25 2014 2014-02-12       COND 10.5921245776  <NA> #> 4531 2060A1     2  CC25 2014 2014-02-12         DO  1.9933388426  <NA> #> 4532 2060A1     2  CC25 2014 2014-02-12      DOSAT  4.5570298107     + #> 4533 2060A1     2  CC25 2014 2014-02-12       NO23 -5.5214609179     U #> 4534 2060A1     2  CC25 2014 2014-02-12      SALIN  3.2367157430  <NA> #> 4535 2060A1     2  CC25 2014 2014-02-12        TKN -0.7657178734  <NA> #> 4536 2060A1     2  CC25 2014 2014-02-12         TN -0.7657178734  <NA> #> 4537 2060A1     2  CC25 2014 2014-02-12         TP -2.0099154790  <NA> #> 4538 2060A1     2  CC25 2014 2014-02-12        TSS  1.7917594692  <NA> #> 4539 2060A1     2  CC25 2014 2014-02-12       TURB  0.1823215568  <NA> #> 4540 2060A1     2  CC25 2014 2014-02-12       COND 10.5938809449  <NA> #> 4541 2060A1     2  CC25 2014 2014-02-12         DO  1.9919755159  <NA> #> 4542 2060A1     2  CC25 2014 2014-02-12      DOSAT  4.5559799418     + #> 4543 2060A1     2  CC25 2014 2014-02-12      SALIN  3.2386784522  <NA> #> 4544 2060A1     2  CC25 2014 2014-07-09      CHLAC  2.1838015570  <NA> #> 4545 2060A1     2  CC25 2014 2014-07-09      COLOR  3.8066624898  <NA> #> 4546 2060A1     2  CC25 2014 2014-07-09       COND 10.5001238327  <NA> #> 4547 2060A1     2  CC25 2014 2014-07-09         DO  1.7047480922  <NA> #> 4548 2060A1     2  CC25 2014 2014-07-09      DOSAT  4.4164280614     + #> 4549 2060A1     2  CC25 2014 2014-07-09       NO23 -5.5214609179     U #> 4550 2060A1     2  CC25 2014 2014-07-09      SALIN  3.1271990363  <NA> #> 4551 2060A1     2  CC25 2014 2014-07-09        TKN -0.2319320573  <NA> #> 4552 2060A1     2  CC25 2014 2014-07-09         TN -0.2319320573  <NA> #> 4553 2060A1     2  CC25 2014 2014-07-09         TP -1.3167682985  <NA> #> 4554 2060A1     2  CC25 2014 2014-07-09        TSS  1.9286186519  <NA> #> 4555 2060A1     2  CC25 2014 2014-07-09       TURB  0.8329091229  <NA> #> 4556 2060A1     2  CC25 2014 2014-07-09       COND 10.5012245483  <NA> #> 4557 2060A1     2  CC25 2014 2014-07-09         DO  1.7029282555  <NA> #> 4558 2060A1     2  CC25 2014 2014-07-09      DOSAT  4.4115854369     + #> 4559 2060A1     2  CC25 2014 2014-07-09      SALIN  3.1285133848  <NA> #> 4560 2060A1     2  CC25 2014 2014-08-12      CHLAC  3.6558396000  <NA> #> 4561 2060A1     2  CC25 2014 2014-08-12      COLOR  4.3820266347  <NA> #> 4562 2060A1     2  CC25 2014 2014-08-12       COND  9.9744118909  <NA> #> 4563 2060A1     2  CC25 2014 2014-08-12         DO  1.9643112344  <NA> #> 4564 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6424659707     + #> 4565 2060A1     2  CC25 2014 2014-08-12       NO23 -5.5214609179     U #> 4566 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5478814489  <NA> #> 4567 2060A1     2  CC25 2014 2014-08-12        TKN  0.1484200051  <NA> #> 4568 2060A1     2  CC25 2014 2014-08-12         TN  0.1484200051  <NA> #> 4569 2060A1     2  CC25 2014 2014-08-12         TP -0.9808292530  <NA> #> 4570 2060A1     2  CC25 2014 2014-08-12        TSS  2.3887627892  <NA> #> 4571 2060A1     2  CC25 2014 2014-08-12       TURB  1.6292405397  <NA> #> 4572 2060A1     2  CC25 2014 2014-08-12       COND  9.9753429896  <NA> #> 4573 2060A1     2  CC25 2014 2014-08-12         DO  1.9586853405  <NA> #> 4574 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6366688530     + #> 4575 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5486636156  <NA> #> 4576 2060A1     2  CC25 2014 2014-08-12       COND  9.9753429896  <NA> #> 4577 2060A1     2  CC25 2014 2014-08-12         DO  1.9530276168  <NA> #> 4578 2060A1     2  CC25 2014 2014-08-12      DOSAT  4.6308379327     + #> 4579 2060A1     2  CC25 2014 2014-08-12      SALIN  2.5486636156  <NA> #> 4580 2060A1     2  CC25 2014 2014-10-21      CHLAC  0.9555114450  <NA> #> 4581 2060A1     2  CC25 2014 2014-10-21      COLOR  4.7874917428  <NA> #> 4582 2060A1     2  CC25 2014 2014-10-21       COND 10.1330107108  <NA> #> 4583 2060A1     2  CC25 2014 2014-10-21         DO  1.4701758451  <NA> #> 4584 2060A1     2  CC25 2014 2014-10-21      DOSAT  4.0809215419     + #> 4585 2060A1     2  CC25 2014 2014-10-21       NO23 -3.1941832123  <NA> #> 4586 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7258901192  <NA> #> 4587 2060A1     2  CC25 2014 2014-10-21        TKN -0.1053605157  <NA> #> 4588 2060A1     2  CC25 2014 2014-10-21         TN -0.0608121394  <NA> #> 4589 2060A1     2  CC25 2014 2014-10-21         TP -1.4354846053  <NA> #> 4590 2060A1     2  CC25 2014 2014-10-21        TSS  1.5973653312  <NA> #> 4591 2060A1     2  CC25 2014 2014-10-21       TURB  0.8329091229  <NA> #> 4592 2060A1     2  CC25 2014 2014-10-21       COND 10.1472177375  <NA> #> 4593 2060A1     2  CC25 2014 2014-10-21         DO  1.4182774070  <NA> #> 4594 2060A1     2  CC25 2014 2014-10-21      DOSAT  4.0271358125     + #> 4595 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7414849772  <NA> #> 4596 2060A1     2  CC25 2014 2014-10-21       COND 10.1612257486  <NA> #> 4597 2060A1     2  CC25 2014 2014-10-21         DO  1.3862943611  <NA> #> 4598 2060A1     2  CC25 2014 2014-10-21      DOSAT  3.9963641539     + #> 4599 2060A1     2  CC25 2014 2014-10-21      SALIN  2.7581094010  <NA> #> 4600 2060A1     2  CC25 2015 2015-02-03      CHLAC  1.7209792872  <NA> #> 4601 2060A1     2  CC25 2015 2015-02-03      COLOR  3.8066624898  <NA> #> 4602 2060A1     2  CC25 2015 2015-02-03       COND 10.4795389612  <NA> #> 4603 2060A1     2  CC25 2015 2015-02-03         DO  2.1758874399  <NA> #> 4604 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6596583713     + #> 4605 2060A1     2  CC25 2015 2015-02-03       NO23 -5.5214609179     U #> 4606 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1130707660  <NA> #> 4607 2060A1     2  CC25 2015 2015-02-03        TKN -0.4975803970  <NA> #> 4608 2060A1     2  CC25 2015 2015-02-03         TN -0.4975803970  <NA> #> 4609 2060A1     2  CC25 2015 2015-02-03         TP -2.1037342342  <NA> #> 4610 2060A1     2  CC25 2015 2015-02-03        TSS  2.6100697927  <NA> #> 4611 2060A1     2  CC25 2015 2015-02-03       TURB  0.7884573604  <NA> #> 4612 2060A1     2  CC25 2015 2015-02-03       COND 10.4887710872  <NA> #> 4613 2060A1     2  CC25 2015 2015-02-03         DO  2.1644717909  <NA> #> 4614 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6482296754     + #> 4615 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1232455939  <NA> #> 4616 2060A1     2  CC25 2015 2015-02-03       COND 10.4921072037  <NA> #> 4617 2060A1     2  CC25 2015 2015-02-03         DO  2.1621729393  <NA> #> 4618 2060A1     2  CC25 2015 2015-02-03      DOSAT  4.6463121293     + #> 4619 2060A1     2  CC25 2015 2015-02-03      SALIN  3.1267605360  <NA> #> 4620 2060A1     2  CC25 2016 2016-09-13      CHLAC  1.4206957878  <NA> #> 4621 2060A1     2  CC25 2016 2016-09-13       COND  8.8724871823  <NA> #> 4622 2060A1     2  CC25 2016 2016-09-13         DO  1.7191887764  <NA> #> 4623 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.3346729383     + #> 4624 2060A1     2  CC25 2016 2016-09-13       NO23 -2.7333680091  <NA> #> 4625 2060A1     2  CC25 2016 2016-09-13      SALIN  1.3584091576  <NA> #> 4626 2060A1     2  CC25 2016 2016-09-13        TKN  0.2851789422  <NA> #> 4627 2060A1     2  CC25 2016 2016-09-13         TN  0.3364722366  <NA> #> 4628 2060A1     2  CC25 2016 2016-09-13         TP -1.2207799226  <NA> #> 4629 2060A1     2  CC25 2016 2016-09-13        TSS  0.4700036292     I #> 4630 2060A1     2  CC25 2016 2016-09-13       TURB  0.6418538862  <NA> #> 4631 2060A1     2  CC25 2016 2016-09-13       COND  9.4834162920  <NA> #> 4632 2060A1     2  CC25 2016 2016-09-13         DO  1.6882490929  <NA> #> 4633 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.3134800921     + #> 4634 2060A1     2  CC25 2016 2016-09-13      SALIN  2.0162354658  <NA> #> 4635 2060A1     2  CC25 2016 2016-09-13       COND  9.6395220067  <NA> #> 4636 2060A1     2  CC25 2016 2016-09-13         DO  1.6544112781  <NA> #> 4637 2060A1     2  CC25 2016 2016-09-13      DOSAT  4.2835865619     + #> 4638 2060A1     2  CC25 2016 2016-09-13      SALIN  2.1849270495  <NA> #> 4639   2046    3M  CC31 2018 2018-03-07      CHLAC  1.6094379124  <NA> #> 4640   2046    3M  CC31 2018 2018-03-07       COND 10.3531928066  <NA> #> 4641   2046    3M  CC31 2018 2018-03-07         DO  1.9021075264  <NA> #> 4642   2046    3M  CC31 2018 2018-03-07      DOSAT  4.4670568839  <NA> #> 4643   2046    3M  CC31 2018 2018-03-07       NO23 -4.7105307016     I #> 4644   2046    3M  CC31 2018 2018-03-07      SALIN  3.0170044088     + #> 4645   2046    3M  CC31 2018 2018-03-07        TKN -0.3710636814  <NA> #> 4646   2046    3M  CC31 2018 2018-03-07         TN -0.3652833185     + #> 4647   2046    3M  CC31 2018 2018-03-07         TP -1.8971199849  <NA> #> 4648   2046    3M  CC31 2018 2018-03-07        TSS  1.3862943611     I #> 4649   2046    3M  CC31 2018 2018-03-07       TURB  0.8754687374  <NA> #> 4650   2046    3M  CC31 2018 2018-04-09      CHLAC  1.2809338455     A #> 4651   2046    3M  CC31 2018 2018-04-09       COND 10.6261935353  <NA> #> 4652   2046    3M  CC31 2018 2018-04-09         DO  1.3083328197  <NA> #> 4653   2046    3M  CC31 2018 2018-04-09      DOSAT  3.9702919136  <NA> #> 4654   2046    3M  CC31 2018 2018-04-09       NO23 -3.7297014486  <NA> #> 4655   2046    3M  CC31 2018 2018-04-09      SALIN  3.2484346271     + #> 4656   2046    3M  CC31 2018 2018-04-09        TKN -0.3147107448  <NA> #> 4657   2046    3M  CC31 2018 2018-04-09         TN -0.2823629110     + #> 4658   2046    3M  CC31 2018 2018-04-09         TP -1.7147984281  <NA> #> 4659   2046    3M  CC31 2018 2018-04-09        TSS  1.6094379124     I #> 4660   2046    3M  CC31 2018 2018-04-09       TURB  0.6931471806  <NA> #> 4661   2046    3M  CC31 2018 2018-05-24      CHLAC  2.7080502011  <NA> #> 4662   2046    3M  CC31 2018 2018-05-24       COND  9.7756541810  <NA> #> 4663   2046    3M  CC31 2018 2018-05-24         DO  1.5303947051  <NA> #> 4664   2046    3M  CC31 2018 2018-05-24      DOSAT  4.1009891049  <NA> #> 4665   2046    3M  CC31 2018 2018-05-24       NO23 -3.1010927892  <NA> #> 4666   2046    3M  CC31 2018 2018-05-24      SALIN  2.3065771143     + #> 4667   2046    3M  CC31 2018 2018-05-24        TKN -0.2613647641  <NA> #> 4668   2046    3M  CC31 2018 2018-05-24         TN -0.2045671657     + #> 4669   2046    3M  CC31 2018 2018-05-24         TP -1.4271163556  <NA> #> 4670   2046    3M  CC31 2018 2018-05-24        TSS  1.6094379124     I #> 4671   2046    3M  CC31 2018 2018-05-24       TURB  0.9932517730  <NA> #> 4672   2046    3M  CC31 2018 2018-07-23      CHLAC  1.4350845253  <NA> #> 4673   2046    3M  CC31 2018 2018-07-23       COND  8.9291703831  <NA> #> 4674   2046    3M  CC31 2018 2018-07-23         DO  1.6937790609  <NA> #> 4675   2046    3M  CC31 2018 2018-07-23      DOSAT  4.3040650932  <NA> #> 4676   2046    3M  CC31 2018 2018-07-23       NO23 -2.0402208285  <NA> #> 4677   2046    3M  CC31 2018 2018-07-23      SALIN  1.4182774070  <NA> #> 4678   2046    3M  CC31 2018 2018-07-23        TKN  0.0000000000  <NA> #> 4679   2046    3M  CC31 2018 2018-07-23         TN  0.1222176327     + #> 4680   2046    3M  CC31 2018 2018-07-23         TP -0.9162907319  <NA> #> 4681   2046    3M  CC31 2018 2018-07-23        TSS  1.3862943611     I #> 4682   2046    3M  CC31 2018 2018-07-23       TURB  0.9162907319     A #> 4683   2046    3M  CC31 2018 2018-08-21      CHLAC  2.7080502011  <NA> #> 4684   2046    3M  CC31 2018 2018-08-21       COND  8.6210125201  <NA> #> 4685   2046    3M  CC31 2018 2018-08-21         DO  1.4586150227  <NA> #> 4686   2046    3M  CC31 2018 2018-08-21      DOSAT  4.0724397268  <NA> #> 4687   2046    3M  CC31 2018 2018-08-21       NO23 -3.4737680745  <NA> #> 4688   2046    3M  CC31 2018 2018-08-21      SALIN  1.0885619528  <NA> #> 4689   2046    3M  CC31 2018 2018-08-21        TKN  1.7047480922  <NA> #> 4690   2046    3M  CC31 2018 2018-08-21         TN  1.7103686310     + #> 4691   2046    3M  CC31 2018 2018-08-21        TSS  1.6094379124     I #> 4692   2046    3M  CC31 2018 2018-08-21       TURB  1.3350010667  <NA> #> 4693   2046    3M  CC31 2018 2018-11-12      CHLAC  1.5686159179  <NA> #> 4694   2046    3M  CC31 2018 2018-11-12       COND 10.1213773269  <NA> #> 4695   2046    3M  CC31 2018 2018-11-12         DO  1.6695918353  <NA> #> 4696   2046    3M  CC31 2018 2018-11-12      DOSAT  4.3121405072  <NA> #> 4697   2046    3M  CC31 2018 2018-11-12       NO23 -3.4112477175  <NA> #> 4698   2046    3M  CC31 2018 2018-11-12      SALIN  2.7127060126  <NA> #> 4699   2046    3M  CC31 2018 2018-11-12        TKN -0.3011050928  <NA> #> 4700   2046    3M  CC31 2018 2018-11-12         TN -0.2574762304     + #> 4701   2046    3M  CC31 2018 2018-11-12         TP -1.8325814637  <NA> #> 4702   2046    3M  CC31 2018 2018-11-12        TSS  1.3862943611     I #> 4703   2046    3M  CC31 2018 2018-11-12       TURB  0.4700036292  <NA> #> 4704   2046    3M  CC31 2018 2018-11-12       COND 10.3160937688  <NA> #> 4705   2046    3M  CC31 2018 2018-11-12         DO  1.5581446180  <NA> #> 4706   2046    3M  CC31 2018 2018-11-12      DOSAT  4.2076732475  <NA> #> 4707   2046    3M  CC31 2018 2018-11-12      SALIN  2.9269179576  <NA> #> 4708   2046    3M  CC31 2019 2019-02-07      CHLAC  3.3672958300  <NA> #> 4709   2046    3M  CC31 2019 2019-02-07       COND  9.8807305654  <NA> #> 4710   2046    3M  CC31 2019 2019-02-07       NO23 -5.5214609179     U #> 4711   2046    3M  CC31 2019 2019-02-07      SALIN  2.4544474423  <NA> #> 4712   2046    3M  CC31 2019 2019-02-07        TKN -0.3710636814  <NA> #> 4713   2046    3M  CC31 2019 2019-02-07         TN -0.3681693234     + #> 4714   2046    3M  CC31 2019 2019-02-07         TP -1.6607312068  <NA> #> 4715   2046    3M  CC31 2019 2019-02-07        TSS  3.3322045102     A #> 4716   2046    3M  CC31 2019 2019-02-07       TURB  2.4849066498     A #> 4717   2046    3M  CC31 2019 2019-03-13      CHLAC  2.3978952728  <NA> #> 4718   2046    3M  CC31 2019 2019-03-13       COND 10.1587109973  <NA> #> 4719   2046    3M  CC31 2019 2019-03-13         DO  1.5830939371  <NA> #> 4720   2046    3M  CC31 2019 2019-03-13      DOSAT  4.1588830834  <NA> #> 4721   2046    3M  CC31 2019 2019-03-13       NO23 -5.5214609179     U #> 4722   2046    3M  CC31 2019 2019-03-13      SALIN  2.7568403653  <NA> #> 4723   2046    3M  CC31 2019 2019-03-13        TKN -0.2876820725  <NA> #> 4724   2046    3M  CC31 2019 2019-03-13         TN -0.2850189550     + #> 4725   2046    3M  CC31 2019 2019-03-13         TP -1.7719568419  <NA> #> 4726   2046    3M  CC31 2019 2019-03-13        TSS  1.3862943611     I #> 4727   2046    3M  CC31 2019 2019-03-13       TURB  0.8754687374  <NA> #> 4728   2046    3M  CC31 2019 2019-04-23      CHLAC  1.8562979904  <NA> #> 4729   2046    3M  CC31 2019 2019-04-23       COND 10.2120745857  <NA> #> 4730   2046    3M  CC31 2019 2019-04-23         DO  1.8389610707  <NA> #> 4731   2046    3M  CC31 2019 2019-04-23      DOSAT  4.4188406078  <NA> #> 4732   2046    3M  CC31 2019 2019-04-23       NO23 -5.5214609179     U #> 4733   2046    3M  CC31 2019 2019-04-23      SALIN  2.8154087194  <NA> #> 4734   2046    3M  CC31 2019 2019-04-23        TKN -0.4307829161  <NA> #> 4735   2046    3M  CC31 2019 2019-04-23         TN -0.4277107171     + #> 4736   2046    3M  CC31 2019 2019-04-23         TP -1.6094379124  <NA> #> 4737   2046    3M  CC31 2019 2019-04-23        TSS  2.5649493575  <NA> #> 4738   2046    3M  CC31 2019 2019-04-23       TURB  1.4350845253  <NA> #> 4739   2046    3M  CC31 2019 2019-07-22      CHLAC  2.0281482473  <NA> #> 4740   2046    3M  CC31 2019 2019-07-22       COND  9.5882287123  <NA> #> 4741   2046    3M  CC31 2019 2019-07-22         DO  1.6808279085  <NA> #> 4742   2046    3M  CC31 2019 2019-07-22      DOSAT  4.3174881135  <NA> #> 4743   2046    3M  CC31 2019 2019-07-22       NO23 -5.1159958098     I #> 4744   2046    3M  CC31 2019 2019-07-22      SALIN  2.1282317058  <NA> #> 4745   2046    3M  CC31 2019 2019-07-22        TKN -0.2484613593  <NA> #> 4746   2046    3M  CC31 2019 2019-07-22         TN -0.2433462586     + #> 4747   2046    3M  CC31 2019 2019-07-22         TP -1.3862943611  <NA> #> 4748   2046    3M  CC31 2019 2019-07-22        TSS  0.6931471806     I #> 4749   2046    3M  CC31 2019 2019-07-22       TURB  0.7419373447  <NA> #> 4750   2046    3M  CC31 2019 2019-09-04      CHLAC  2.6390573296  <NA> #> 4751   2046    3M  CC31 2019 2019-09-04       COND  9.5618419571  <NA> #> 4752   2046    3M  CC31 2019 2019-09-04         DO  1.6486586256  <NA> #> 4753   2046    3M  CC31 2019 2019-09-04      DOSAT  4.2752762647  <NA> #> 4754   2046    3M  CC31 2019 2019-09-04       NO23 -3.1465551633  <NA> #> 4755   2046    3M  CC31 2019 2019-09-04      SALIN  2.1004689089  <NA> #> 4756   2046    3M  CC31 2019 2019-09-04        TKN -0.1863295782  <NA> #> 4757   2046    3M  CC31 2019 2019-09-04         TN -0.1358197231     + #> 4758   2046    3M  CC31 2019 2019-09-04         TP -1.5141277326  <NA> #> 4759   2046    3M  CC31 2019 2019-09-04        TSS  1.3862943611     I #> 4760   2046    3M  CC31 2019 2019-09-04       TURB  0.6418538862  <NA> #> 4761   2046    3M  CC31 2020 2020-01-14       COND 10.2603574775  <NA> #> 4762   2046    3M  CC31 2020 2020-01-14         DO  1.8341801851  <NA> #> 4763   2046    3M  CC31 2020 2020-01-14      DOSAT  4.4140096805  <NA> #> 4764   2046    3M  CC31 2020 2020-01-14      SALIN  2.8690346205  <NA> #> 4765   2046    3M  CC31 2020 2020-02-18      CHLAC  0.8329091229     I #> 4766   2046    3M  CC31 2020 2020-02-18       COND 10.3879178649  <NA> #> 4767   2046    3M  CC31 2020 2020-02-18         DO  1.8976198599  <NA> #> 4768   2046    3M  CC31 2020 2020-02-18      DOSAT  4.5075573571  <NA> #> 4769   2046    3M  CC31 2020 2020-02-18       NO23 -4.8283137373     I #> 4770   2046    3M  CC31 2020 2020-02-18      SALIN  3.0106208860  <NA> #> 4771   2046    3M  CC31 2020 2020-02-18        TKN -0.5447271754  <NA> #> 4772   2046    3M  CC31 2020 2020-02-18         TN -0.5378542962     + #> 4773   2046    3M  CC31 2020 2020-02-18         TP -2.0402208285  <NA> #> 4774   2046    3M  CC31 2020 2020-02-18        TSS  1.0986122887     I #> 4775   2046    3M  CC31 2020 2020-02-18       TURB  0.4700036292  <NA> #> 4776   2046    3M  CC31 2020 2020-06-09      CHLAC  2.9444389792  <NA> #> 4777   2046    3M  CC31 2020 2020-06-09       COND 10.1025842827  <NA> #> 4778   2046    3M  CC31 2020 2020-06-09         DO  1.5973653312  <NA> #> 4779   2046    3M  CC31 2020 2020-06-09      DOSAT  4.2297491992  <NA> #> 4780   2046    3M  CC31 2020 2020-06-09       NO23 -4.9618451299     I #> 4781   2046    3M  CC31 2020 2020-06-09      SALIN  2.6919208192  <NA> #> 4782   2046    3M  CC31 2020 2020-06-09        TKN  0.0000000000  <NA> #> 4783   2046    3M  CC31 2020 2020-06-09         TN  0.0039920213     + #> 4784   2046    3M  CC31 2020 2020-06-09         TP -1.2729656758  <NA> #> 4785   2046    3M  CC31 2020 2020-06-09        TSS  1.3862943611     I #> 4786   2046    3M  CC31 2020 2020-06-09       TURB  0.5306282511  <NA> #> 4787   2046    3M  CC31 2020 2020-08-10       COND 10.0585663729  <NA> #> 4788   2046    3M  CC31 2020 2020-08-10         DO  0.7419373447  <NA> #> 4789   2046    3M  CC31 2020 2020-08-10      DOSAT  3.4177266836  <NA> #> 4790   2046    3M  CC31 2020 2020-08-10      SALIN  2.6426223958  <NA> #> 4791   2046    3M  CC31 2020 2020-09-22      CHLAC  2.4849066498  <NA> #> 4792   2046    3M  CC31 2020 2020-09-22       COND  9.3350328159  <NA> #> 4793   2046    3M  CC31 2020 2020-09-22         DO  1.5789787049  <NA> #> 4794   2046    3M  CC31 2020 2020-09-22      DOSAT  4.1573193614  <NA> #> 4795   2046    3M  CC31 2020 2020-09-22       NO23 -3.0791138825  <NA> #> 4796   2046    3M  CC31 2020 2020-09-22      SALIN  1.8578592709  <NA> #> 4797   2046    3M  CC31 2020 2020-09-22        TKN -0.0408219945  <NA> #> 4798   2046    3M  CC31 2020 2020-09-22         TN  0.0059820717     + #> 4799   2046    3M  CC31 2020 2020-09-22         TP -1.4271163556  <NA> #> 4800   2046    3M  CC31 2020 2020-09-22        TSS  1.0986122887     I #> 4801   2046    3M  CC31 2020 2020-09-22       TURB  0.9932517730  <NA> #> 4802   2046    3M  CC31 2020 2020-10-20      CHLAC  1.4586150227  <NA> #> 4803   2046    3M  CC31 2020 2020-10-20       COND  9.7670949276  <NA> #> 4804   2046    3M  CC31 2020 2020-10-20         DO  1.4085449701  <NA> #> 4805   2046    3M  CC31 2020 2020-10-20      DOSAT  4.0000338828  <NA> #> 4806   2046    3M  CC31 2020 2020-10-20       NO23 -2.5510464523  <NA> #> 4807   2046    3M  CC31 2020 2020-10-20      SALIN  2.3282528397  <NA> #> 4808   2046    3M  CC31 2020 2020-10-20        TKN -0.0833816089  <NA> #> 4809   2046    3M  CC31 2020 2020-10-20         TN -0.0020020027     + #> 4810   2046    3M  CC31 2020 2020-10-20         TP -1.5141277326  <NA> #> 4811   2046    3M  CC31 2020 2020-10-20        TSS  1.0986122887     I #> 4812   2046    3M  CC31 2020 2020-10-20       TURB  0.5877866649  <NA> #> 4813   2046    3M  CC31 2020 2020-12-14      CHLAC  1.0647107370  <NA> #> 4814   2046    3M  CC31 2020 2020-12-14       COND  9.9551782679  <NA> #> 4815   2046    3M  CC31 2020 2020-12-14         DO  1.8293763328  <NA> #> 4816   2046    3M  CC31 2020 2020-12-14      DOSAT  4.3528552574  <NA> #> 4817   2046    3M  CC31 2020 2020-12-14       NO23 -2.7181005370  <NA> #> 4818   2046    3M  CC31 2020 2020-12-14      SALIN  2.5360749364  <NA> #> 4819   2046    3M  CC31 2020 2020-12-14        TKN -0.2107210313  <NA> #> 4820   2046    3M  CC31 2020 2020-12-14         TN -0.1323891880     + #> 4821   2046    3M  CC31 2020 2020-12-14         TP -2.1202635362  <NA> #> 4822   2046    3M  CC31 2020 2020-12-14        TSS  1.6094379124     I #> 4823   2046    3M  CC31 2020 2020-12-14       TURB  0.5306282511  <NA> #> 4824   2046    3M  CC31 2021 2021-02-03      CHLAC  0.9932517730  <NA> #> 4825   2046    3M  CC31 2021 2021-02-03       COND 10.2269830978  <NA> #> 4826   2046    3M  CC31 2021 2021-02-03         DO  2.0655961349  <NA> #> 4827   2046    3M  CC31 2021 2021-02-03      DOSAT  4.5130548971  <NA> #> 4828   2046    3M  CC31 2021 2021-02-03       NO23 -4.0745419349  <NA> #> 4829   2046    3M  CC31 2021 2021-02-03      SALIN  2.8355635214  <NA> #> 4830   2046    3M  CC31 2021 2021-02-03        TKN -0.4780358009  <NA> #> 4831   2046    3M  CC31 2021 2021-02-03         TN -0.4509856234     + #> 4832   2046    3M  CC31 2021 2021-02-03         TP -2.3025850930  <NA> #> 4833   2046    3M  CC31 2021 2021-02-03        TSS  1.7917594692     I #> 4834   2046    3M  CC31 2021 2021-02-03       TURB  0.5306282511  <NA> #> 4835   2046    3M  CC31 2021 2021-03-09      CHLAC  2.0918640617  <NA> #> 4836   2046    3M  CC31 2021 2021-03-09       COND 10.3281668796  <NA> #> 4837   2046    3M  CC31 2021 2021-03-09         DO  2.2523438766  <NA> #> 4838   2046    3M  CC31 2021 2021-03-09      DOSAT  4.7757564866  <NA> #> 4839   2046    3M  CC31 2021 2021-03-09       NO23 -5.5214609179     U #> 4840   2046    3M  CC31 2021 2021-03-09      SALIN  2.9460166813  <NA> #> 4841   2046    3M  CC31 2021 2021-03-09        TKN -0.1863295782  <NA> #> 4842   2046    3M  CC31 2021 2021-03-09         TN -0.1839228382     + #> 4843   2046    3M  CC31 2021 2021-03-09         TP -1.5606477483  <NA> #> 4844   2046    3M  CC31 2021 2021-03-09        TSS  2.8332133441  <NA> #> 4845   2046    3M  CC31 2021 2021-03-09       TURB  2.0412203289  <NA> #> 4846   2046    3M  CC31 2021 2021-05-05      CHLAC  0.9555114450  <NA> #> 4847   2046    3M  CC31 2021 2021-05-05       COND 10.5683895677  <NA> #> 4848   2046    3M  CC31 2021 2021-05-05         DO  1.3402504226  <NA> #> 4849   2046    3M  CC31 2021 2021-05-05      DOSAT  4.0465538984  <NA> #> 4850   2046    3M  CC31 2021 2021-05-05       NO23 -5.5214609179     U #> 4851   2046    3M  CC31 2021 2021-05-05      SALIN  3.2043711387  <NA> #> 4852   2046    3M  CC31 2021 2021-05-05        TKN -0.4620354596  <NA> #> 4853   2046    3M  CC31 2021 2021-05-05         TN -0.4588658848     + #> 4854   2046    3M  CC31 2021 2021-05-05         TP -1.5141277326  <NA> #> 4855   2046    3M  CC31 2021 2021-05-05        TSS  1.7917594692     I #> 4856   2046    3M  CC31 2021 2021-05-05       TURB  0.4700036292  <NA> #> 4857   2046    3M  CC31 2021 2021-06-03      CHLAC  0.9932517730     I #> 4858   2046    3M  CC31 2021 2021-06-03       COND 10.6275033568  <NA> #> 4859   2046    3M  CC31 2021 2021-06-03         DO  0.8329091229  <NA> #> 4860   2046    3M  CC31 2021 2021-06-03      DOSAT  3.5322256441  <NA> #> 4861   2046    3M  CC31 2021 2021-06-03       NO23 -5.5214609179     U #> 4862   2046    3M  CC31 2021 2021-06-03      SALIN  3.2718477096  <NA> #> 4863   2046    3M  CC31 2021 2021-06-03        TKN -0.3285040670  <NA> #> 4864   2046    3M  CC31 2021 2021-06-03         TN -0.3257301401     + #> 4865   2046    3M  CC31 2021 2021-06-03         TP -1.4271163556  <NA> #> 4866   2046    3M  CC31 2021 2021-06-03        TSS  1.0986122887     I #> 4867   2046    3M  CC31 2021 2021-06-03       TURB  0.5306282511  <NA> #> 4868   2046    3M  CC31 2021 2021-07-01      CHLAC  2.7080502011  <NA> #> 4869   2046    3M  CC31 2021 2021-07-01       COND 10.4739019677  <NA> #> 4870   2046    3M  CC31 2021 2021-07-01         DO  1.6770965609  <NA> #> 4871   2046    3M  CC31 2021 2021-07-01      DOSAT  4.3107991254  <NA> #> 4872   2046    3M  CC31 2021 2021-07-01       NO23 -5.2983173665     I #> 4873   2046    3M  CC31 2021 2021-07-01      SALIN  3.1014427280  <NA> #> 4874   2046    3M  CC31 2021 2021-07-01        TKN -0.4462871026  <NA> #> 4875   2046    3M  CC31 2021 2021-07-01         TN -0.4400565529     + #> 4876   2046    3M  CC31 2021 2021-07-01         TP -1.2729656758  <NA> #> 4877   2046    3M  CC31 2021 2021-07-01        TSS  1.7917594692     I #> 4878   2046    3M  CC31 2021 2021-07-01       TURB  0.4054651081  <NA> #> 4879   2046    3M  CC31 2021 2021-07-29      CHLAC  2.9444389792  <NA> #> 4880   2046    3M  CC31 2021 2021-07-29       COND  9.3783094225  <NA> #> 4881   2046    3M  CC31 2021 2021-07-29         DO  1.3558351536  <NA> #> 4882   2046    3M  CC31 2021 2021-07-29      DOSAT  3.9646154555  <NA> #> 4883   2046    3M  CC31 2021 2021-07-29       NO23 -3.3242363405  <NA> #> 4884   2046    3M  CC31 2021 2021-07-29      SALIN  1.9021075264  <NA> #> 4885   2046    3M  CC31 2021 2021-07-29        TKN  0.0953101798  <NA> #> 4886   2046    3M  CC31 2021 2021-07-29         TN  0.1275133203     + #> 4887   2046    3M  CC31 2021 2021-07-29         TP -0.9942522733  <NA> #> 4888   2046    3M  CC31 2021 2021-07-29        TSS  1.6094379124     I #> 4889   2046    3M  CC31 2021 2021-07-29       TURB  1.6094379124  <NA> #> 4890   2046    3M  CC31 2021 2021-08-25      CHLAC  2.4849066498  <NA> #> 4891   2046    3M  CC31 2021 2021-08-25       COND  9.4766200382  <NA> #> 4892   2046    3M  CC31 2021 2021-08-25         DO  0.8153648133  <NA> #> 4893   2046    3M  CC31 2021 2021-08-25      DOSAT  3.4404180948  <NA> #> 4894   2046    3M  CC31 2021 2021-08-25       NO23 -4.0745419349  <NA> #> 4895   2046    3M  CC31 2021 2021-08-25      SALIN  2.0095554142  <NA> #> 4896   2046    3M  CC31 2021 2021-08-25        TKN  0.0000000000  <NA> #> 4897   2046    3M  CC31 2021 2021-08-25         TN  0.0168571171     + #> 4898   2046    3M  CC31 2021 2021-08-25         TP -1.1086626245  <NA> #> 4899   2046    3M  CC31 2021 2021-08-25        TSS  1.7917594692     I #> 4900   2046    3M  CC31 2021 2021-08-25       TURB  1.1939224685  <NA> #> 4901   2046    3M  CC31 2021 2021-09-23      CHLAC  3.0445224377  <NA> #> 4902   2046    3M  CC31 2021 2021-09-23       COND  8.7826296549  <NA> #> 4903   2046    3M  CC31 2021 2021-09-23         DO  1.4747630091  <NA> #> 4904   2046    3M  CC31 2021 2021-09-23      DOSAT  4.0483006237  <NA> #> 4905   2046    3M  CC31 2021 2021-09-23       NO23 -3.0576076773  <NA> #> 4906   2046    3M  CC31 2021 2021-09-23      SALIN  1.2641267271  <NA> #> 4907   2046    3M  CC31 2021 2021-09-23        TKN -0.0943106795  <NA> #> 4908   2046    3M  CC31 2021 2021-09-23         TN -0.0439518875     + #> 4909   2046    3M  CC31 2021 2021-09-23         TP -1.4271163556  <NA> #> 4910   2046    3M  CC31 2021 2021-09-23        TSS  1.3862943611     I #> 4911   2046    3M  CC31 2021 2021-09-23       TURB  1.1631508098  <NA> #> 4912   2046    3M  CC31 2021 2021-10-21      CHLAC  2.3025850930  <NA> #> 4913   2046    3M  CC31 2021 2021-10-21       COND  9.9156631285  <NA> #> 4914   2046    3M  CC31 2021 2021-10-21         DO  1.5040773968  <NA> #> 4915   2046    3M  CC31 2021 2021-10-21      DOSAT  4.0690267542  <NA> #> 4916   2046    3M  CC31 2021 2021-10-21       NO23 -3.1465551633  <NA> #> 4917   2046    3M  CC31 2021 2021-10-21      SALIN  2.4907230351  <NA> #> 4918   2046    3M  CC31 2021 2021-10-21        TKN -0.1278333715  <NA> #> 4919   2046    3M  CC31 2021 2021-10-21         TN -0.0801260445     + #> 4920   2046    3M  CC31 2021 2021-10-21         TP -1.5141277326  <NA> #> 4921   2046    3M  CC31 2021 2021-10-21        TSS  1.0986122887     U #> 4922   2046    3M  CC31 2021 2021-10-21       TURB  0.4700036292     A #> 4923   2046    3M  CC31 2021 2021-11-22       COND 10.1079374614  <NA> #> 4924   2046    3M  CC31 2021 2021-11-22         DO  1.7316555452  <NA> #> 4925   2046    3M  CC31 2021 2021-11-22      DOSAT  4.2877159552  <NA> #> 4926   2046    3M  CC31 2021 2021-11-22       NO23 -2.8134107168  <NA> #> 4927   2046    3M  CC31 2021 2021-11-22      SALIN  2.7020321288  <NA> #> 4928   2046    3M  CC31 2021 2021-11-22        TKN -0.6733445533  <NA> #> 4929   2046    3M  CC31 2021 2021-11-22         TN -0.5621189182     + #> 4930   2046    3M  CC31 2021 2021-11-22         TP -2.3025850930  <NA> #> 4931   2046    3M  CC31 2021 2021-11-22        TSS  1.6094379124     I #> 4932   2046    3M  CC31 2021 2021-11-22       TURB  0.1823215568     A #> 4933   2046    3M  CC31 2022 2022-02-22      CHLAC  1.3083328197  <NA> #> 4934   2046    3M  CC31 2022 2022-02-22       COND 10.5165899421  <NA> #> 4935   2046    3M  CC31 2022 2022-02-22         DO  1.8547342684  <NA> #> 4936   2046    3M  CC31 2022 2022-02-22      DOSAT  4.4320065670  <NA> #> 4937   2046    3M  CC31 2022 2022-02-22       NO23 -5.5214609179     U #> 4938   2046    3M  CC31 2022 2022-02-22      SALIN  3.1527360224  <NA> #> 4939   2046    3M  CC31 2022 2022-02-22        TKN -0.6931471806  <NA> #> 4940   2046    3M  CC31 2022 2022-02-22         TN -0.6891551593     + #> 4941   2046    3M  CC31 2022 2022-02-22         TP -2.4304184645  <NA> #> 4942   2046    3M  CC31 2022 2022-02-22        TSS  2.0794415417     I #> 4943   2046    3M  CC31 2022 2022-02-22       TURB  0.4054651081     A #> 4944   2046    3M  CC31 2022 2022-04-20      CHLAC  1.5260563035  <NA> #> 4945   2046    3M  CC31 2022 2022-04-20       COND 10.6492271832  <NA> #> 4946   2046    3M  CC31 2022 2022-04-20         DO  1.5581446180  <NA> #> 4947   2046    3M  CC31 2022 2022-04-20      DOSAT  4.1805222585  <NA> #> 4948   2046    3M  CC31 2022 2022-04-20       NO23 -5.5214609179     U #> 4949   2046    3M  CC31 2022 2022-04-20      SALIN  3.2987954480  <NA> #> 4950   2046    3M  CC31 2022 2022-04-20        TKN -0.5447271754  <NA> #> 4951   2046    3M  CC31 2022 2022-04-20         TN -0.5412848313     + #> 4952   2046    3M  CC31 2022 2022-04-20         TP -1.8325814637  <NA> #> 4953   2046    3M  CC31 2022 2022-04-20        TSS  2.0794415417     I #> 4954   2046    3M  CC31 2022 2022-04-20       TURB  1.0296194172  <NA> #> 4955   2046    3M  CC31 2022 2022-06-07      CHLAC  1.9021075264  <NA> #> 4956   2046    3M  CC31 2022 2022-06-07       COND 10.4903571304  <NA> #> 4957   2046    3M  CC31 2022 2022-06-07         DO  1.2412685891  <NA> #> 4958   2046    3M  CC31 2022 2022-06-07      DOSAT  3.9318256327  <NA> #> 4959   2046    3M  CC31 2022 2022-06-07       NO23 -5.2983173665     I #> 4960   2046    3M  CC31 2022 2022-06-07      SALIN  3.1188344707  <NA> #> 4961   2046    3M  CC31 2022 2022-06-07        TKN -0.4942963218  <NA> #> 4962   2046    3M  CC31 2022 2022-06-07         TN -0.4877603508     + #> 4963   2046    3M  CC31 2022 2022-06-07         TP -1.4696759701  <NA> #> 4964   2046    3M  CC31 2022 2022-06-07        TSS  2.0794415417     I #> 4965   2046    3M  CC31 2022 2022-06-07       TURB  0.1823215568  <NA> #> 4966   2046    3M  CC31 2022 2022-08-15      CHLAC  2.1282317058  <NA> #> 4967   2046    3M  CC31 2022 2022-08-15       COND  9.6188009891  <NA> #> 4968   2046    3M  CC31 2022 2022-08-15         DO  0.9895411936  <NA> #> 4969   2046    3M  CC31 2022 2022-08-15      DOSAT  3.6054978452  <NA> #> 4970   2046    3M  CC31 2022 2022-08-15       NO23 -3.4737680745  <NA> #> 4971   2046    3M  CC31 2022 2022-08-15      SALIN  2.1667653699  <NA> #> 4972   2046    3M  CC31 2022 2022-08-15        TKN -0.0833816089  <NA> #> 4973   2046    3M  CC31 2022 2022-08-15         TN -0.0502412164     + #> 4974   2046    3M  CC31 2022 2022-08-15         TP -1.4696759701  <NA> #> 4975   2046    3M  CC31 2022 2022-08-15        TSS  1.0986122887     I #> 4976   2046    3M  CC31 2022 2022-08-15       TURB  0.6931471806  <NA> #> 4977   2046    3M  CC31 2022 2022-12-15      CHLAC  0.9555114450  <NA> #> 4978   2046    3M  CC31 2022 2022-12-15       COND 10.2729108893  <NA> #> 4979   2046    3M  CC31 2022 2022-12-15         DO  1.7630170004  <NA> #> 4980   2046    3M  CC31 2022 2022-12-15      DOSAT  4.3267781604  <NA> #> 4981   2046    3M  CC31 2022 2022-12-15       NO23 -2.9759296463  <NA> #> 4982   2046    3M  CC31 2022 2022-12-15      SALIN  2.8836827697  <NA> #> 4983   2046    3M  CC31 2022 2022-12-15        TKN -0.4942963218  <NA> #> 4984   2046    3M  CC31 2022 2022-12-15         TN -0.4140014391     + #> 4985   2046    3M  CC31 2022 2022-12-15         TP -1.6094379124  <NA> #> 4986   2046    3M  CC31 2022 2022-12-15        TSS  2.0794415417     I #> 4987   2046    3M  CC31 2022 2022-12-15       TURB  0.0000000000  <NA> #> 4988   2046    3M  CC31 2023 2023-01-11      CHLAC  2.0668627595  <NA> #> 4989   2046    3M  CC31 2023 2023-01-11       COND 10.2352702390  <NA> #> 4990   2046    3M  CC31 2023 2023-01-11         DO  1.7984040119  <NA> #> 4991   2046    3M  CC31 2023 2023-01-11      DOSAT  4.2849649218  <NA> #> 4992   2046    3M  CC31 2023 2023-01-11       NO23 -3.9633162998  <NA> #> 4993   2046    3M  CC31 2023 2023-01-11      SALIN  2.8443278194  <NA> #> 4994   2046    3M  CC31 2023 2023-01-11        TKN -0.5798184953  <NA> #> 4995   2046    3M  CC31 2023 2023-01-11         TN -0.5464528014     + #> 4996   2046    3M  CC31 2023 2023-01-11         TP -1.8325814637  <NA> #> 4997   2046    3M  CC31 2023 2023-01-11        TSS  1.7917594692     I #> 4998   2046    3M  CC31 2023 2023-01-11       TURB  0.7419373447  <NA> #> 4999   2046    3M  CC31 2023 2023-03-23      CHLAC  1.7578579176  <NA> #> 5000   2046    3M  CC31 2023 2023-03-23       COND 10.4503364755  <NA> #> 5001   2046    3M  CC31 2023 2023-03-23         DO  1.8840347453  <NA> #> 5002   2046    3M  CC31 2023 2023-03-23      DOSAT  4.4461744545  <NA> #> 5003   2046    3M  CC31 2023 2023-03-23       NO23 -5.5214609179     U #> 5004   2046    3M  CC31 2023 2023-03-23      SALIN  3.0796137575  <NA> #> 5005   2046    3M  CC31 2023 2023-03-23        TKN -0.1984509387  <NA> #> 5006   2046    3M  CC31 2023 2023-03-23         TN -0.1960148839     + #> 5007   2046    3M  CC31 2023 2023-03-23         TP -1.1711829815  <NA> #> 5008   2046    3M  CC31 2023 2023-03-23        TSS  2.7725887222  <NA> #> 5009   2046    3M  CC31 2023 2023-03-23       TURB  1.7047480922  <NA> #> 5010   2046    3M  CC31 2023 2023-05-08      CHLAC  1.2809338455  <NA> #> 5011   2046    3M  CC31 2023 2023-05-08       COND 10.5443145959  <NA> #> 5012   2046    3M  CC31 2023 2023-05-08         DO  1.6014057407  <NA> #> 5013   2046    3M  CC31 2023 2023-05-08      DOSAT  4.2370008626  <NA> #> 5014   2046    3M  CC31 2023 2023-05-08       NO23 -4.7105307016     I #> 5015   2046    3M  CC31 2023 2023-05-08      SALIN  3.1813816204  <NA> #> 5016   2046    3M  CC31 2023 2023-05-08        TKN -0.3710636814  <NA> #> 5017   2046    3M  CC31 2023 2023-05-08         TN -0.3652833185     + #> 5018   2046    3M  CC31 2023 2023-05-08         TP -1.6094379124  <NA> #> 5019   2046    3M  CC31 2023 2023-05-08        TSS  1.7917594692     I #> 5020   2046    3M  CC31 2023 2023-05-08       TURB  0.0953101798  <NA> #> 5021  2056E    3M  CC34 2015 2015-04-06      CHLAC  1.5040773968  <NA> #> 5022  2056E    3M  CC34 2015 2015-04-06      COLOR  3.8066624898  <NA> #> 5023  2056E    3M  CC34 2015 2015-04-06       COND 10.4003156667  <NA> #> 5024  2056E    3M  CC34 2015 2015-04-06         DO  2.1317967720  <NA> #> 5025  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7899886230     + #> 5026  2056E    3M  CC34 2015 2015-04-06       NO23 -5.5214609179     U #> 5027  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0194488002  <NA> #> 5028  2056E    3M  CC34 2015 2015-04-06        TKN -0.3509769228  <NA> #> 5029  2056E    3M  CC34 2015 2015-04-06         TN -0.3509769228  <NA> #> 5030  2056E    3M  CC34 2015 2015-04-06         TP -1.6928195214  <NA> #> 5031  2056E    3M  CC34 2015 2015-04-06        TSS  1.6253112616  <NA> #> 5032  2056E    3M  CC34 2015 2015-04-06       TURB  1.0647107370  <NA> #> 5033  2056E    3M  CC34 2015 2015-04-06       COND 10.4033533361  <NA> #> 5034  2056E    3M  CC34 2015 2015-04-06         DO  2.1341664414  <NA> #> 5035  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7899886230     + #> 5036  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0233474406  <NA> #> 5037  2056E    3M  CC34 2015 2015-04-06       COND 10.4069864009  <NA> #> 5038  2056E    3M  CC34 2015 2015-04-06         DO  2.1435893615  <NA> #> 5039  2056E    3M  CC34 2015 2015-04-06      DOSAT  4.7949637576     + #> 5040  2056E    3M  CC34 2015 2015-04-06      SALIN  3.0272309406  <NA> #> 5041  2056E    3M  CC36 2015 2015-04-06      CHLAC  1.5040773968  <NA> #> 5042  2056E    3M  CC36 2015 2015-04-06      COLOR  3.8066624898  <NA> #> 5043  2056E    3M  CC36 2015 2015-04-06       COND 10.4003156667  <NA> #> 5044  2056E    3M  CC36 2015 2015-04-06         DO  2.1317967720  <NA> #> 5045  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7899886230     + #> 5046  2056E    3M  CC36 2015 2015-04-06       NO23 -5.5214609179     U #> 5047  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0194488002  <NA> #> 5048  2056E    3M  CC36 2015 2015-04-06        TKN -0.3509769228  <NA> #> 5049  2056E    3M  CC36 2015 2015-04-06         TN -0.3509769228  <NA> #> 5050  2056E    3M  CC36 2015 2015-04-06         TP -1.6928195214  <NA> #> 5051  2056E    3M  CC36 2015 2015-04-06        TSS  1.6253112616  <NA> #> 5052  2056E    3M  CC36 2015 2015-04-06       TURB  1.0647107370  <NA> #> 5053  2056E    3M  CC36 2015 2015-04-06       COND 10.4033533361  <NA> #> 5054  2056E    3M  CC36 2015 2015-04-06         DO  2.1341664414  <NA> #> 5055  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7899886230     + #> 5056  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0233474406  <NA> #> 5057  2056E    3M  CC36 2015 2015-04-06       COND 10.4069864009  <NA> #> 5058  2056E    3M  CC36 2015 2015-04-06         DO  2.1435893615  <NA> #> 5059  2056E    3M  CC36 2015 2015-04-06      DOSAT  4.7949637576     + #> 5060  2056E    3M  CC36 2015 2015-04-06      SALIN  3.0272309406  <NA> #> 5061  2056E    3M  CC37 2014 2014-01-06      CHLAC  1.5686159179  <NA> #> 5062  2056E    3M  CC37 2014 2014-01-06      COLOR  2.9957322736     A #> 5063  2056E    3M  CC37 2014 2014-01-06      DOSAT  4.3832758541     + #> 5064  2056E    3M  CC37 2014 2014-01-06       NO23 -4.3428059215  <NA> #> 5065  2056E    3M  CC37 2014 2014-01-06      SALIN  3.3032169733  <NA> #> 5066  2056E    3M  CC37 2014 2014-01-06        TKN -0.5978370008  <NA> #> 5067  2056E    3M  CC37 2014 2014-01-06         TN -0.5744756508     + #> 5068  2056E    3M  CC37 2014 2014-01-06         TP -2.3025850930  <NA> #> 5069  2056E    3M  CC37 2014 2014-01-06       TURB  0.2623642645  <NA> #> 5070  2056E    3M  CC37 2014 2014-02-03      CHLAC  1.4816045409  <NA> #> 5071  2056E    3M  CC37 2014 2014-02-03      COLOR  2.7725887222  <NA> #> 5072  2056E    3M  CC37 2014 2014-02-03         DO  1.8562979904  <NA> #> 5073  2056E    3M  CC37 2014 2014-02-03      DOSAT  4.3502779364     + #> 5074  2056E    3M  CC37 2014 2014-02-03       NO23 -3.2968373663  <NA> #> 5075  2056E    3M  CC37 2014 2014-02-03      SALIN  2.6461747974  <NA> #> 5076  2056E    3M  CC37 2014 2014-02-03        TKN -0.1743533871  <NA> #> 5077  2056E    3M  CC37 2014 2014-02-03         TN -0.1312482866     + #> 5078  2056E    3M  CC37 2014 2014-02-03         TP -2.3025850930  <NA> #> 5079  2056E    3M  CC37 2014 2014-02-03       TURB  0.7419373447  <NA> #> 5080  2056E    3M  CC37 2014 2014-03-03      CHLAC  1.7578579176  <NA> #> 5081  2056E    3M  CC37 2014 2014-03-03      COLOR  2.8903717579     A #> 5082  2056E    3M  CC37 2014 2014-03-03         DO  1.8082887712  <NA> #> 5083  2056E    3M  CC37 2014 2014-03-03      DOSAT  4.3579900568     + #> 5084  2056E    3M  CC37 2014 2014-03-03       NO23 -4.5098600062  <NA> #> 5085  2056E    3M  CC37 2014 2014-03-03      SALIN  3.1000922889  <NA> #> 5086  2056E    3M  CC37 2014 2014-03-03        TKN -0.2744368457  <NA> #> 5087  2056E    3M  CC37 2014 2014-03-03         TN -0.2600669054     + #> 5088  2056E    3M  CC37 2014 2014-03-03         TP -1.8971199849  <NA> #> 5089  2056E    3M  CC37 2014 2014-03-03       TURB  1.0296194172  <NA> #> 5090  2056E    3M  CC37 2014 2014-04-07      CHLAC  2.2721258855  <NA> #> 5091  2056E    3M  CC37 2014 2014-04-07      COLOR  2.9444389792  <NA> #> 5092  2056E    3M  CC37 2014 2014-04-07         DO  1.8718021769  <NA> #> 5093  2056E    3M  CC37 2014 2014-04-07      DOSAT  4.4953553200     + #> 5094  2056E    3M  CC37 2014 2014-04-07       NO23 -4.9618451299     I #> 5095  2056E    3M  CC37 2014 2014-04-07      SALIN  3.1000922889  <NA> #> 5096  2056E    3M  CC37 2014 2014-04-07        TKN -0.4942963218  <NA> #> 5097  2056E    3M  CC37 2014 2014-04-07         TN -0.4877603508     + #> 5098  2056E    3M  CC37 2014 2014-04-07         TP -1.7147984281  <NA> #> 5099  2056E    3M  CC37 2014 2014-04-07       TURB  1.2237754316  <NA> #> 5100  2056E    3M  CC37 2014 2014-05-05      CHLAC  3.0445224377  <NA> #> 5101  2056E    3M  CC37 2014 2014-05-05      COLOR  3.0910424534  <NA> #> 5102  2056E    3M  CC37 2014 2014-05-05         DO  1.7917594692  <NA> #> 5103  2056E    3M  CC37 2014 2014-05-05      DOSAT  4.4152196020     + #> 5104  2056E    3M  CC37 2014 2014-05-05       NO23 -5.1159958098     I #> 5105  2056E    3M  CC37 2014 2014-05-05      SALIN  3.2068032436  <NA> #> 5106  2056E    3M  CC37 2014 2014-05-05        TKN -0.0100503359  <NA> #> 5107  2056E    3M  CC37 2014 2014-05-05         TN -0.0060180723     + #> 5108  2056E    3M  CC37 2014 2014-05-05         TP -1.2729656758  <NA> #> 5109  2056E    3M  CC37 2014 2014-05-05       TURB  1.9315214116  <NA> #> 5110  2056E    3M  CC37 2014 2014-06-02      CHLAC  2.2617630985  <NA> #> 5111  2056E    3M  CC37 2014 2014-06-02      COLOR  3.2188758249  <NA> #> 5112  2056E    3M  CC37 2014 2014-06-02         DO  1.6292405397  <NA> #> 5113  2056E    3M  CC37 2014 2014-06-02      DOSAT  4.3040650932     + #> 5114  2056E    3M  CC37 2014 2014-06-02       NO23 -5.1159958098     I #> 5115  2056E    3M  CC37 2014 2014-06-02      SALIN  3.2425923515  <NA> #> 5116  2056E    3M  CC37 2014 2014-06-02        TKN -0.1625189295  <NA> #> 5117  2056E    3M  CC37 2014 2014-06-02         TN -0.1578240852     + #> 5118  2056E    3M  CC37 2014 2014-06-02         TP -1.0216512475  <NA> #> 5119  2056E    3M  CC37 2014 2014-06-02       TURB  1.4816045409  <NA> #> 5120  2056E    3M  CC37 2014 2014-07-07      CHLAC  2.5649493575  <NA> #> 5121  2056E    3M  CC37 2014 2014-07-07      COLOR  3.3672958300     A #> 5122  2056E    3M  CC37 2014 2014-07-07       NO23 -5.5214609179     I #> 5123  2056E    3M  CC37 2014 2014-07-07      SALIN  3.1398326175  <NA> #> 5124  2056E    3M  CC37 2014 2014-07-07        TKN -0.0304592075  <NA> #> 5125  2056E    3M  CC37 2014 2014-07-07         TN -0.0263439753     + #> 5126  2056E    3M  CC37 2014 2014-07-07         TP -0.9675840263  <NA> #> 5127  2056E    3M  CC37 2014 2014-07-07       TURB  1.5260563035  <NA> #> 5128  2056E    3M  CC37 2014 2014-08-04      CHLAC  2.7080502011  <NA> #> 5129  2056E    3M  CC37 2014 2014-08-04      COLOR  4.0073331852     A #> 5130  2056E    3M  CC37 2014 2014-08-04         DO  1.7047480922  <NA> #> 5131  2056E    3M  CC37 2014 2014-08-04      DOSAT  4.3214801348     + #> 5132  2056E    3M  CC37 2014 2014-08-04       NO23 -4.5098600062  <NA> #> 5133  2056E    3M  CC37 2014 2014-08-04      SALIN  2.4336133554  <NA> #> 5134  2056E    3M  CC37 2014 2014-08-04        TKN  0.0953101798  <NA> #> 5135  2056E    3M  CC37 2014 2014-08-04         TN  0.1052605107     + #> 5136  2056E    3M  CC37 2014 2014-08-04         TP -0.7550225843  <NA> #> 5137  2056E    3M  CC37 2014 2014-08-04       TURB  1.0296194172  <NA> #> 5138  2056E    3M  CC37 2014 2014-09-08      CHLAC  0.5877866649  <NA> #> 5139  2056E    3M  CC37 2014 2014-09-08      COLOR  3.6375861597     A #> 5140  2056E    3M  CC37 2014 2014-09-08      DOSAT  3.7588718259     + #> 5141  2056E    3M  CC37 2014 2014-09-08       NO23 -4.1997050779  <NA> #> 5142  2056E    3M  CC37 2014 2014-09-08      SALIN  2.6318888401  <NA> #> 5143  2056E    3M  CC37 2014 2014-09-08        TKN -0.1743533871  <NA> #> 5144  2056E    3M  CC37 2014 2014-09-08         TN -0.1566538100     + #> 5145  2056E    3M  CC37 2014 2014-09-08         TP -1.0498221245  <NA> #> 5146  2056E    3M  CC37 2014 2014-09-08       TURB  0.6931471806     A #> 5147  2056E    3M  CC37 2014 2014-10-06      CHLAC  1.7917594692  <NA> #> 5148  2056E    3M  CC37 2014 2014-10-06      COLOR  4.1588830834     A #> 5149  2056E    3M  CC37 2014 2014-10-06         DO  1.3350010667  <NA> #> 5150  2056E    3M  CC37 2014 2014-10-06      DOSAT  3.8458832029     + #> 5151  2056E    3M  CC37 2014 2014-10-06       NO23 -2.9957322736  <NA> #> 5152  2056E    3M  CC37 2014 2014-10-06      SALIN  1.9600947840  <NA> #> 5153  2056E    3M  CC37 2014 2014-10-06        TKN -0.1508228897  <NA> #> 5154  2056E    3M  CC37 2014 2014-10-06         TN -0.0943106795     + #> 5155  2056E    3M  CC37 2014 2014-10-06         TP -1.1086626245  <NA> #> 5156  2056E    3M  CC37 2014 2014-10-06       TURB  0.8754687374  <NA> #> 5157  2056E    3M  CC37 2014 2014-11-03      CHLAC  2.1517622033  <NA> #> 5158  2056E    3M  CC37 2014 2014-11-03      COLOR  3.9318256327     A #> 5159  2056E    3M  CC37 2014 2014-11-03         DO  1.8245492921  <NA> #> 5160  2056E    3M  CC37 2014 2014-11-03      DOSAT  4.2499227940     + #> 5161  2056E    3M  CC37 2014 2014-11-03       NO23 -4.2686979494  <NA> #> 5162  2056E    3M  CC37 2014 2014-11-03      SALIN  2.7600099400  <NA> #> 5163  2056E    3M  CC37 2014 2014-11-03        TKN -0.1508228897  <NA> #> 5164  2056E    3M  CC37 2014 2014-11-03         TN -0.1346749033     + #> 5165  2056E    3M  CC37 2014 2014-11-03         TP -1.5606477483  <NA> #> 5166  2056E    3M  CC37 2014 2014-11-03       TURB  0.7884573604  <NA> #> 5167  2056E    3M  CC37 2014 2014-12-01      CHLAC  2.1633230257  <NA> #> 5168  2056E    3M  CC37 2014 2014-12-01      COLOR  3.4657359028  <NA> #> 5169  2056E    3M  CC37 2014 2014-12-01         DO  1.9600947840  <NA> #> 5170  2056E    3M  CC37 2014 2014-12-01      DOSAT  4.4343818650     + #> 5171  2056E    3M  CC37 2014 2014-12-01       NO23 -3.4737680745  <NA> #> 5172  2056E    3M  CC37 2014 2014-12-01      SALIN  2.8622008809  <NA> #> 5173  2056E    3M  CC37 2014 2014-12-01        TKN -0.3147107448  <NA> #> 5174  2056E    3M  CC37 2014 2014-12-01         TN -0.2731219211     + #> 5175  2056E    3M  CC37 2014 2014-12-01         TP -1.9661128564  <NA> #> 5176  2056E    3M  CC37 2014 2014-12-01       TURB  0.7884573604  <NA> #> 5177  2056E    3M  CC37 2015 2015-01-05      CHLAC  1.8870696490  <NA> #> 5178  2056E    3M  CC37 2015 2015-01-05      COLOR  3.2958368660     A #> 5179  2056E    3M  CC37 2015 2015-01-05         DO  1.7917594692  <NA> #> 5180  2056E    3M  CC37 2015 2015-01-05      DOSAT  4.3732381286     + #> 5181  2056E    3M  CC37 2015 2015-01-05       NO23 -3.9633162998  <NA> #> 5182  2056E    3M  CC37 2015 2015-01-05      SALIN  2.9549102790  <NA> #> 5183  2056E    3M  CC37 2015 2015-01-05        TKN -0.4780358009  <NA> #> 5184  2056E    3M  CC37 2015 2015-01-05         TN -0.4478508246     + #> 5185  2056E    3M  CC37 2015 2015-01-05         TP -2.1202635362  <NA> #> 5186  2056E    3M  CC37 2015 2015-01-05       TURB  0.8754687374  <NA> #> 5187  2056E    3M  CC37 2015 2015-02-02      CHLAC  1.6094379124  <NA> #> 5188  2056E    3M  CC37 2015 2015-02-02      COLOR  2.8332133441     A #> 5189  2056E    3M  CC37 2015 2015-02-02         DO  1.8245492921  <NA> #> 5190  2056E    3M  CC37 2015 2015-02-02      DOSAT  4.3333614627     + #> 5191  2056E    3M  CC37 2015 2015-02-02       NO23 -4.6051701860  <NA> #> 5192  2056E    3M  CC37 2015 2015-02-02      SALIN  3.0773122605  <NA> #> 5193  2056E    3M  CC37 2015 2015-02-02        TKN -0.6733445533  <NA> #> 5194  2056E    3M  CC37 2015 2015-02-02         TN -0.6539264674     + #> 5195  2056E    3M  CC37 2015 2015-02-02         TP -2.1202635362  <NA> #> 5196  2056E    3M  CC37 2015 2015-02-02       TURB  0.9162907319  <NA> #> 5197  2056E    3M  CC37 2015 2015-03-02      CHLAC  2.0014800002  <NA> #> 5198  2056E    3M  CC37 2015 2015-03-02      COLOR  3.2958368660  <NA> #> 5199  2056E    3M  CC37 2015 2015-03-02         DO  1.6486586256  <NA> #> 5200  2056E    3M  CC37 2015 2015-03-02      DOSAT  4.2002049529     + #> 5201  2056E    3M  CC37 2015 2015-03-02       NO23 -2.9759296463  <NA> #> 5202  2056E    3M  CC37 2015 2015-03-02      SALIN  2.9285235239  <NA> #> 5203  2056E    3M  CC37 2015 2015-03-02        TKN -0.3566749439  <NA> #> 5204  2056E    3M  CC37 2015 2015-03-02         TN -0.2863496272     + #> 5205  2056E    3M  CC37 2015 2015-03-02         TP -2.0402208285  <NA> #> 5206  2056E    3M  CC37 2015 2015-03-02       TURB  0.7419373447  <NA> #> 5207  2056E    3M  CC37 2015 2015-04-06      CHLAC  1.8245492921  <NA> #> 5208  2056E    3M  CC37 2015 2015-04-06      COLOR  3.2188758249     A #> 5209  2056E    3M  CC37 2015 2015-04-06         DO  1.6292405397  <NA> #> 5210  2056E    3M  CC37 2015 2015-04-06      DOSAT  4.2297491992     + #> 5211  2056E    3M  CC37 2015 2015-04-06       NO23 -4.5098600062  <NA> #> 5212  2056E    3M  CC37 2015 2015-04-06      SALIN  3.0252910758  <NA> #> 5213  2056E    3M  CC37 2015 2015-04-06        TKN -0.1165338163  <NA> #> 5214  2056E    3M  CC37 2015 2015-04-06         TN -0.1042500214     + #> 5215  2056E    3M  CC37 2015 2015-04-06         TP -1.6094379124  <NA> #> 5216  2056E    3M  CC37 2015 2015-04-06       TURB  1.3083328197  <NA> #> 5217  2056E    3M  CC37 2015 2015-05-04      CHLAC  1.7917594692  <NA> #> 5218  2056E    3M  CC37 2015 2015-05-04      COLOR  3.2958368660     A #> 5219  2056E    3M  CC37 2015 2015-05-04         DO  1.4816045409  <NA> #> 5220  2056E    3M  CC37 2015 2015-05-04      DOSAT  4.0724397268     + #> 5221  2056E    3M  CC37 2015 2015-05-04       NO23 -5.2983173665     I #> 5222  2056E    3M  CC37 2015 2015-05-04      SALIN  3.0773122605  <NA> #> 5223  2056E    3M  CC37 2015 2015-05-04        TKN -0.3856624808  <NA> #> 5224  2056E    3M  CC37 2015 2015-05-04         TN -0.3797973614     + #> 5225  2056E    3M  CC37 2015 2015-05-04         TP -2.0402208285  <NA> #> 5226  2056E    3M  CC37 2015 2015-05-04       TURB  1.3350010667  <NA> #> 5227  2056E    3M  CC37 2015 2015-06-01      CHLAC  2.7080502011  <NA> #> 5228  2056E    3M  CC37 2015 2015-06-01      COLOR  3.2188758249     A #> 5229  2056E    3M  CC37 2015 2015-06-01      DOSAT  4.0587173846     + #> 5230  2056E    3M  CC37 2015 2015-06-01       NO23 -5.1159958098     I #> 5231  2056E    3M  CC37 2015 2015-06-01      SALIN  2.8332133441  <NA> #> 5232  2056E    3M  CC37 2015 2015-06-01        TKN  0.0000000000  <NA> #> 5233  2056E    3M  CC37 2015 2015-06-01         TN  0.0039920213     + #> 5234  2056E    3M  CC37 2015 2015-06-01         TP -1.1711829815  <NA> #> 5235  2056E    3M  CC37 2015 2015-06-01       TURB  1.5475625087     A #> 5236  2056E    3M  CC37 2015 2015-08-03      CHLAC  3.2580965380  <NA> #> 5237  2056E    3M  CC37 2015 2015-08-03      COLOR  3.8286413965  <NA> #> 5238  2056E    3M  CC37 2015 2015-08-03         DO  1.9169226122  <NA> #> 5239  2056E    3M  CC37 2015 2015-08-03      DOSAT  4.4784725329     + #> 5240  2056E    3M  CC37 2015 2015-08-03       NO23 -4.0173835211  <NA> #> 5241  2056E    3M  CC37 2015 2015-08-03      SALIN  1.9021075264  <NA> #> 5242  2056E    3M  CC37 2015 2015-08-03        TKN  0.0000000000  <NA> #> 5243  2056E    3M  CC37 2015 2015-08-03         TN  0.0178399181     + #> 5244  2056E    3M  CC37 2015 2015-08-03         TP -0.8439700703  <NA> #> 5245  2056E    3M  CC37 2015 2015-08-03       TURB  1.0986122887     A #> 5246  2056E    3M  CC37 2015 2015-09-08      CHLAC  2.7080502011  <NA> #> 5247  2056E    3M  CC37 2015 2015-09-08      COLOR  4.7004803658     A #> 5248  2056E    3M  CC37 2015 2015-09-08         DO  1.7227665977  <NA> #> 5249  2056E    3M  CC37 2015 2015-09-08      DOSAT  4.3067641502     + #> 5250  2056E    3M  CC37 2015 2015-09-08       NO23 -3.3242363405  <NA> #> 5251  2056E    3M  CC37 2015 2015-09-08      SALIN  1.7749523509  <NA> #> 5252  2056E    3M  CC37 2015 2015-09-08        TKN  0.1823215568  <NA> #> 5253  2056E    3M  CC37 2015 2015-09-08         TN  0.2118803590     + #> 5254  2056E    3M  CC37 2015 2015-09-08         TP -0.2613647641  <NA> #> 5255  2056E    3M  CC37 2015 2015-09-08       TURB  1.3083328197  <NA> #> 5256  2056E    3M  CC37 2015 2015-10-05      CHLAC  2.3978952728  <NA> #> 5257  2056E    3M  CC37 2015 2015-10-05      COLOR  4.5643481915     A #> 5258  2056E    3M  CC37 2015 2015-10-05         DO  1.8562979904  <NA> #> 5259  2056E    3M  CC37 2015 2015-10-05      DOSAT  4.3732381286     + #> 5260  2056E    3M  CC37 2015 2015-10-05       NO23 -3.7722610631  <NA> #> 5261  2056E    3M  CC37 2015 2015-10-05      SALIN  2.2721258855  <NA> #> 5262  2056E    3M  CC37 2015 2015-10-05        TKN -0.2876820725  <NA> #> 5263  2056E    3M  CC37 2015 2015-10-05         TN -0.2574762304     + #> 5264  2056E    3M  CC37 2015 2015-10-05         TP -0.9416085399  <NA> #> 5265  2056E    3M  CC37 2015 2015-10-05       TURB  0.4054651081  <NA> #> 5266  2056E    3M  CC37 2016 2016-02-01      CHLAC  2.6390573296  <NA> #> 5267  2056E    3M  CC37 2016 2016-02-01      COLOR  4.5217885770     A #> 5268  2056E    3M  CC37 2016 2016-02-01       NO23 -1.9661128564  <NA> #> 5269  2056E    3M  CC37 2016 2016-02-01        TKN -0.3285040670  <NA> #> 5270  2056E    3M  CC37 2016 2016-02-01         TN -0.1508228897     + #> 5271  2056E    3M  CC37 2016 2016-02-01         TP -1.0216512475  <NA> #> 5272  2056E    3M  CC37 2016 2016-02-01       TURB  0.9162907319  <NA> #> 5273  2056E    3M  CC37 2016 2016-03-07      CHLAC  2.4849066498  <NA> #> 5274  2056E    3M  CC37 2016 2016-03-07      COLOR  3.8918202981     A #> 5275  2056E    3M  CC37 2016 2016-03-07         DO  1.6331544391  <NA> #> 5276  2056E    3M  CC37 2016 2016-03-07      DOSAT  4.0859763126     + #> 5277  2056E    3M  CC37 2016 2016-03-07       NO23 -4.1997050779  <NA> #> 5278  2056E    3M  CC37 2016 2016-03-07      SALIN  2.7040421797  <NA> #> 5279  2056E    3M  CC37 2016 2016-03-07        TKN -0.3011050928  <NA> #> 5280  2056E    3M  CC37 2016 2016-03-07         TN -0.2810375297     + #> 5281  2056E    3M  CC37 2016 2016-03-07         TP -1.5141277326  <NA> #> 5282  2056E    3M  CC37 2016 2016-03-07       TURB  1.2527629685  <NA> #> 5283  2056E    3M  CC37 2016 2016-04-04      CHLAC  2.3978952728  <NA> #> 5284  2056E    3M  CC37 2016 2016-04-04      COLOR  3.6635616461  <NA> #> 5285  2056E    3M  CC37 2016 2016-04-04         DO  1.3711807233  <NA> #> 5286  2056E    3M  CC37 2016 2016-04-04      DOSAT  3.9512437186     + #> 5287  2056E    3M  CC37 2016 2016-04-04       NO23 -3.5065578973  <NA> #> 5288  2056E    3M  CC37 2016 2016-04-04      SALIN  2.6905648868  <NA> #> 5289  2056E    3M  CC37 2016 2016-04-04        TKN -0.0202027073  <NA> #> 5290  2056E    3M  CC37 2016 2016-04-04         TN  0.0099503309     + #> 5291  2056E    3M  CC37 2016 2016-04-04         TP -1.3470736480  <NA> #> 5292  2056E    3M  CC37 2016 2016-04-04       TURB  1.5260563035  <NA> #> 5293  2056E    3M  CC37 2017 2017-02-06      CHLAC  2.8903717579  <NA> #> 5294  2056E    3M  CC37 2017 2017-02-06      COLOR  2.9444389792     A #> 5295  2056E    3M  CC37 2017 2017-02-06         DO  1.6311994042  <NA> #> 5296  2056E    3M  CC37 2017 2017-02-06      DOSAT  4.2239097666     + #> 5297  2056E    3M  CC37 2017 2017-02-06       NO23 -5.5214609179     U #> 5298  2056E    3M  CC37 2017 2017-02-06      SALIN  3.3138223022  <NA> #> 5299  2056E    3M  CC37 2017 2017-02-06        TKN -0.0943106795  <NA> #> 5300  2056E    3M  CC37 2017 2017-02-06         TN -0.0921152889     + #> 5301  2056E    3M  CC37 2017 2017-02-06         TP -1.7147984281  <NA> #> 5302  2056E    3M  CC37 2017 2017-02-06       TURB  1.8562979904  <NA> #> 5303  2056E    3M  CC37 2017 2017-03-06      CHLAC  2.1517622033  <NA> #> 5304  2056E    3M  CC37 2017 2017-03-06      COLOR  2.7080502011  <NA> #> 5305  2056E    3M  CC37 2017 2017-03-06         DO  1.7191887764  <NA> #> 5306  2056E    3M  CC37 2017 2017-03-06      DOSAT  4.2931954210     + #> 5307  2056E    3M  CC37 2017 2017-03-06       NO23 -5.5214609179     U #> 5308  2056E    3M  CC37 2017 2017-03-06      SALIN  3.3279095859  <NA> #> 5309  2056E    3M  CC37 2017 2017-03-06        TKN -0.1743533871  <NA> #> 5310  2056E    3M  CC37 2017 2017-03-06         TN -0.1719752647     + #> 5311  2056E    3M  CC37 2017 2017-03-06         TP -1.9661128564  <NA> #> 5312  2056E    3M  CC37 2017 2017-03-06       TURB  1.3862943611  <NA> #> 5313  2056E    3M  CC37 2017 2017-04-03      CHLAC  2.3978952728  <NA> #> 5314  2056E    3M  CC37 2017 2017-04-03      COLOR  2.7080502011     A #> 5315  2056E    3M  CC37 2017 2017-04-03         DO  1.5727739281  <NA> #> 5316  2056E    3M  CC37 2017 2017-04-03      DOSAT  4.2640873368     + #> 5317  2056E    3M  CC37 2017 2017-04-03       NO23 -5.5214609179     U #> 5318  2056E    3M  CC37 2017 2017-04-03      SALIN  3.3914836895  <NA> #> 5319  2056E    3M  CC37 2017 2017-04-03        TKN -0.1508228897  <NA> #> 5320  2056E    3M  CC37 2017 2017-04-03         TN -0.1485000083     + #> 5321  2056E    3M  CC37 2017 2017-04-03         TP -1.6607312068  <NA> #> 5322  2056E    3M  CC37 2017 2017-04-03       TURB  1.3862943611     A #> 5323  2056E    3M  CC37 2017 2017-07-10      CHLAC  2.7080502011  <NA> #> 5324  2056E    3M  CC37 2017 2017-07-10      COLOR  4.7874917428     A #> 5325  2056E    3M  CC37 2017 2017-07-10         DO  0.8415671857  <NA> #> 5326  2056E    3M  CC37 2017 2017-07-10      DOSAT  3.4965075615     + #> 5327  2056E    3M  CC37 2017 2017-07-10       NO23 -5.1159958098     I #> 5328  2056E    3M  CC37 2017 2017-07-10        TKN  0.1823215568  <NA> #> 5329  2056E    3M  CC37 2017 2017-07-10         TN  0.1856493469     + #> 5330  2056E    3M  CC37 2017 2017-07-10         TP -0.4780358009  <NA> #> 5331  2056E    3M  CC37 2017 2017-07-10       TURB  1.1939224685  <NA> #> 5332  2056E    3M  CC37 2017 2017-08-07      CHLAC  1.6863989536  <NA> #> 5333  2056E    3M  CC37 2017 2017-08-07      COLOR  4.7004803658  <NA> #> 5334  2056E    3M  CC37 2017 2017-08-07         DO  0.7793248768  <NA> #> 5335  2056E    3M  CC37 2017 2017-08-07      DOSAT  3.4144426084     + #> 5336  2056E    3M  CC37 2017 2017-08-07       NO23 -2.2072749132  <NA> #> 5337  2056E    3M  CC37 2017 2017-08-07      SALIN  1.7647307968  <NA> #> 5338  2056E    3M  CC37 2017 2017-08-07        TKN  0.1823215568  <NA> #> 5339  2056E    3M  CC37 2017 2017-08-07         TN  0.2700271372     + #> 5340  2056E    3M  CC37 2017 2017-08-07         TP -0.8209805521  <NA> #> 5341  2056E    3M  CC37 2017 2017-08-07       TURB  0.7884573604  <NA> #> 5342  2056E    3M  CC37 2017 2017-09-05      CHLAC  2.8332133441  <NA> #> 5343  2056E    3M  CC37 2017 2017-09-05      COLOR  4.4998096703  <NA> #> 5344  2056E    3M  CC37 2017 2017-09-05         DO  1.4516138272  <NA> #> 5345  2056E    3M  CC37 2017 2017-09-05      DOSAT  4.0377742107     + #> 5346  2056E    3M  CC37 2017 2017-09-05       NO23 -2.4889146712  <NA> #> 5347  2056E    3M  CC37 2017 2017-09-05      SALIN  0.1906203596  <NA> #> 5348  2056E    3M  CC37 2017 2017-09-05        TKN -0.0725706928  <NA> #> 5349  2056E    3M  CC37 2017 2017-09-05         TN  0.0129162253     + #> 5350  2056E    3M  CC37 2017 2017-09-05         TP -0.9675840263  <NA> #> 5351  2056E    3M  CC37 2017 2017-09-05       TURB  1.0986122887  <NA> #> 5352  2056E    3M  CC37 2017 2017-10-02      CHLAC  1.9169226122  <NA> #> 5353  2056E    3M  CC37 2017 2017-10-02      COLOR  4.4886363697     A #> 5354  2056E    3M  CC37 2017 2017-10-02       NO23 -2.9565115604  <NA> #> 5355  2056E    3M  CC37 2017 2017-10-02        TKN -0.8675005677  <NA> #> 5356  2056E    3M  CC37 2017 2017-10-02         TN -0.7507762934     + #> 5357  2056E    3M  CC37 2017 2017-10-02         TP -0.6348782724  <NA> #> 5358  2056E    3M  CC37 2017 2017-10-02       TURB  0.7419373447  <NA> #> 5359  2056E    3M  CC37 2017 2017-11-06      CHLAC  1.6292405397  <NA> #> 5360  2056E    3M  CC37 2017 2017-11-06      COLOR  3.8918202981     A #> 5361  2056E    3M  CC37 2017 2017-11-06         DO  1.7595805709  <NA> #> 5362  2056E    3M  CC37 2017 2017-11-06      DOSAT  4.3605476030  <NA> #> 5363  2056E    3M  CC37 2017 2017-11-06       NO23 -3.7722610631  <NA> #> 5364  2056E    3M  CC37 2017 2017-11-06      SALIN  2.9549102790  <NA> #> 5365  2056E    3M  CC37 2017 2017-11-06        TKN -0.4620354596  <NA> #> 5366  2056E    3M  CC37 2017 2017-11-06         TN -0.4261781497     + #> 5367  2056E    3M  CC37 2017 2017-11-06         TP -1.4696759701  <NA> #> 5368  2056E    3M  CC37 2017 2017-11-06       TURB  0.2623642645  <NA> #> 5369  2056E    3M  CC37 2017 2017-12-04      CHLAC  1.6677068206  <NA> #> 5370  2056E    3M  CC37 2017 2017-12-04      COLOR  3.4657359028  <NA> #> 5371  2056E    3M  CC37 2017 2017-12-04         DO  1.5686159179  <NA> #> 5372  2056E    3M  CC37 2017 2017-12-04      DOSAT  4.1541845626  <NA> #> 5373  2056E    3M  CC37 2017 2017-12-04       NO23 -5.5214609179     U #> 5374  2056E    3M  CC37 2017 2017-12-04      SALIN  3.0914968955  <NA> #> 5375  2056E    3M  CC37 2017 2017-12-04        TKN -0.1743533871  <NA> #> 5376  2056E    3M  CC37 2017 2017-12-04         TN -0.1719752647     + #> 5377  2056E    3M  CC37 2017 2017-12-04         TP -1.2039728043  <NA> #> 5378  2056E    3M  CC37 2017 2017-12-04       TURB  1.0647107370  <NA> #> 5379  2056E    3M  CC37 2018 2018-01-02      CHLAC  2.8332133441  <NA> #> 5380  2056E    3M  CC37 2018 2018-01-02      COLOR  3.2188758249  <NA> #> 5381  2056E    3M  CC37 2018 2018-01-02         DO  1.7101878155  <NA> #> 5382  2056E    3M  CC37 2018 2018-01-02      DOSAT  4.1789920363     + #> 5383  2056E    3M  CC37 2018 2018-01-02       NO23 -5.2983173665     I #> 5384  2056E    3M  CC37 2018 2018-01-02      SALIN  3.1045866785  <NA> #> 5385  2056E    3M  CC37 2018 2018-01-02        TKN -0.1278333715  <NA> #> 5386  2056E    3M  CC37 2018 2018-01-02         TN -0.1232982163     + #> 5387  2056E    3M  CC37 2018 2018-01-02         TP -0.6348782724  <NA> #> 5388  2056E    3M  CC37 2018 2018-01-02       TURB  1.5040773968  <NA> #> 5389  2056E    3M  CC37 2018 2018-02-05      CHLAC  3.0445224377  <NA> #> 5390  2056E    3M  CC37 2018 2018-02-05      COLOR  3.0910424534  <NA> #> 5391  2056E    3M  CC37 2018 2018-02-05         DO  1.7227665977  <NA> #> 5392  2056E    3M  CC37 2018 2018-02-05      DOSAT  4.3067641502  <NA> #> 5393  2056E    3M  CC37 2018 2018-02-05       NO23 -4.1351665567  <NA> #> 5394  2056E    3M  CC37 2018 2018-02-05      SALIN  3.1311369106  <NA> #> 5395  2056E    3M  CC37 2018 2018-02-05        TKN -0.5108256238  <NA> #> 5396  2056E    3M  CC37 2018 2018-02-05         TN -0.4845083154     + #> 5397  2056E    3M  CC37 2018 2018-02-05         TP -2.0402208285  <NA> #> 5398  2056E    3M  CC37 2018 2018-02-05       TURB  1.3609765531  <NA> #> 5399  2056E    3M  CC37 2018 2018-03-05      CHLAC  1.9315214116  <NA> #> 5400  2056E    3M  CC37 2018 2018-03-05      COLOR  3.1780538303     A #> 5401  2056E    3M  CC37 2018 2018-03-05         DO  1.4973884086  <NA> #> 5402  2056E    3M  CC37 2018 2018-03-05      DOSAT  4.0656020934  <NA> #> 5403  2056E    3M  CC37 2018 2018-03-05       NO23 -5.2983173665     I #> 5404  2056E    3M  CC37 2018 2018-03-05      SALIN  3.1540172525  <NA> #> 5405  2056E    3M  CC37 2018 2018-03-05        TKN -0.2613647641  <NA> #> 5406  2056E    3M  CC37 2018 2018-03-05         TN -0.2561834054     + #> 5407  2056E    3M  CC37 2018 2018-03-05         TP -1.6607312068  <NA> #> 5408  2056E    3M  CC37 2018 2018-03-05       TURB  1.3083328197  <NA> #> 5409  2056E    3M  CC37 2018 2018-04-02      CHLAC  2.3978952728  <NA> #> 5410  2056E    3M  CC37 2018 2018-04-02      COLOR  2.9444389792     A #> 5411  2056E    3M  CC37 2018 2018-04-02         DO  1.3660916538  <NA> #> 5412  2056E    3M  CC37 2018 2018-04-02      DOSAT  3.9963641539  <NA> #> 5413  2056E    3M  CC37 2018 2018-04-02       NO23 -4.8283137373     I #> 5414  2056E    3M  CC37 2018 2018-04-02      SALIN  3.2461018111  <NA> #> 5415  2056E    3M  CC37 2018 2018-04-02        TKN -0.2613647641  <NA> #> 5416  2056E    3M  CC37 2018 2018-04-02         TN -0.2561834054     + #> 5417  2056E    3M  CC37 2018 2018-04-02         TP -1.6607312068  <NA> #> 5418  2056E    3M  CC37 2018 2018-04-02       TURB  1.4109869737     A #> 5419  2056E    3M  CC37 2018 2018-05-07      CHLAC  2.6390573296  <NA> #> 5420  2056E    3M  CC37 2018 2018-05-07      COLOR  3.0445224377  <NA> #> 5421  2056E    3M  CC37 2018 2018-05-07         DO  1.4011829736  <NA> #> 5422  2056E    3M  CC37 2018 2018-05-07      DOSAT  4.0656020934  <NA> #> 5423  2056E    3M  CC37 2018 2018-05-07       NO23 -5.2983173665     I #> 5424  2056E    3M  CC37 2018 2018-05-07      SALIN  3.3225148596  <NA> #> 5425  2056E    3M  CC37 2018 2018-05-07        TKN -0.0833816089  <NA> #> 5426  2056E    3M  CC37 2018 2018-05-07         TN -0.0790432073     + #> 5427  2056E    3M  CC37 2018 2018-05-07         TP -1.5606477483  <NA> #> 5428  2056E    3M  CC37 2018 2018-05-07       TURB  1.5260563035  <NA> #> 5429  2056E    3M  CC37 2018 2018-06-04      CHLAC  3.2958368660  <NA> #> 5430  2056E    3M  CC37 2018 2018-06-04      COLOR  4.4773368145  <NA> #> 5431  2056E    3M  CC37 2018 2018-06-04         DO  1.9286186519  <NA> #> 5432  2056E    3M  CC37 2018 2018-06-04      DOSAT  4.5390303835  <NA> #> 5433  2056E    3M  CC37 2018 2018-06-04       NO23 -4.0745419349  <NA> #> 5434  2056E    3M  CC37 2018 2018-06-04      SALIN  1.9095425049  <NA> #> 5435  2056E    3M  CC37 2018 2018-06-04        TKN  0.1823215568  <NA> #> 5436  2056E    3M  CC37 2018 2018-06-04         TN  0.1963888140     + #> 5437  2056E    3M  CC37 2018 2018-06-04         TP -0.9942522733  <NA> #> 5438  2056E    3M  CC37 2018 2018-06-04       TURB  1.3862943611  <NA> #> 5439  2056E    3M  CC37 2018 2018-07-09      CHLAC  2.6390573296  <NA> #> 5440  2056E    3M  CC37 2018 2018-07-09      COLOR  4.8675344505  <NA> #> 5441  2056E    3M  CC37 2018 2018-07-09         DO  1.2919836816  <NA> #> 5442  2056E    3M  CC37 2018 2018-07-09      DOSAT  3.7977338590  <NA> #> 5443  2056E    3M  CC37 2018 2018-07-09       NO23 -2.6310891600  <NA> #> 5444  2056E    3M  CC37 2018 2018-07-09      SALIN  1.8148247422  <NA> #> 5445  2056E    3M  CC37 2018 2018-07-09        TKN  0.1823215568  <NA> #> 5446  2056E    3M  CC37 2018 2018-07-09         TN  0.2405904649     + #> 5447  2056E    3M  CC37 2018 2018-07-09         TP -0.8675005677  <NA> #> 5448  2056E    3M  CC37 2018 2018-07-09       TURB  0.6931471806     A #> 5449  2056E    3M  CC37 2018 2018-08-06      CHLAC  1.8562979904  <NA> #> 5450  2056E    3M  CC37 2018 2018-08-06      COLOR  4.8675344505  <NA> #> 5451  2056E    3M  CC37 2018 2018-08-06         DO  1.3428648032  <NA> #> 5452  2056E    3M  CC37 2018 2018-08-06      DOSAT  3.9435216725  <NA> #> 5453  2056E    3M  CC37 2018 2018-08-06       NO23 -1.8325814637  <NA> #> 5454  2056E    3M  CC37 2018 2018-08-06      SALIN  1.1281710909  <NA> #> 5455  2056E    3M  CC37 2018 2018-08-06        TKN  0.0953101798  <NA> #> 5456  2056E    3M  CC37 2018 2018-08-06         TN  0.2311117210     + #> 5457  2056E    3M  CC37 2018 2018-08-06         TP -0.8209805521  <NA> #> 5458  2056E    3M  CC37 2018 2018-08-06       TURB  0.5877866649  <NA> #> 5459  2056E    3M  CC37 2019 2019-02-04      CHLAC  1.9878743482     A #> 5460  2056E    3M  CC37 2019 2019-02-04      COLOR  3.3322045102  <NA> #> 5461  2056E    3M  CC37 2019 2019-02-04         DO  2.0438143640  <NA> #> 5462  2056E    3M  CC37 2019 2019-02-04      DOSAT  4.5622626850  <NA> #> 5463  2056E    3M  CC37 2019 2019-02-04       NO23 -5.2983173665     I #> 5464  2056E    3M  CC37 2019 2019-02-04      SALIN  2.7447035188  <NA> #> 5465  2056E    3M  CC37 2019 2019-02-04        TKN -0.4780358009  <NA> #> 5466  2056E    3M  CC37 2019 2019-02-04         TN -0.4716049106     + #> 5467  2056E    3M  CC37 2019 2019-02-04         TP -1.7147984281  <NA> #> 5468  2056E    3M  CC37 2019 2019-02-04       TURB  0.7884573604  <NA> #> 5469  2056E    3M  CC37 2019 2019-05-06      CHLAC  2.3978952728  <NA> #> 5470  2056E    3M  CC37 2019 2019-05-06      COLOR  3.1780538303     A #> 5471  2056E    3M  CC37 2019 2019-05-06         DO  1.3110318766  <NA> #> 5472  2056E    3M  CC37 2019 2019-05-06      DOSAT  3.9759363312  <NA> #> 5473  2056E    3M  CC37 2019 2019-05-06       NO23 -5.5214609179     U #> 5474  2056E    3M  CC37 2019 2019-05-06      SALIN  3.0320642028  <NA> #> 5475  2056E    3M  CC37 2019 2019-05-06         TN -0.2331938872     + #> 5476  2056E    3M  CC37 2019 2019-05-06         TP -1.4696759701  <NA> #> 5477  2056E    3M  CC37 2019 2019-05-06       TURB  1.3350010667  <NA> #> 5478  2056E    3M  CC37 2019 2019-06-03      CHLAC  2.0281482473  <NA> #> 5479  2056E    3M  CC37 2019 2019-06-03      COLOR  3.2188758249     A #> 5480  2056E    3M  CC37 2019 2019-06-03         DO  1.2864740258  <NA> #> 5481  2056E    3M  CC37 2019 2019-06-03      DOSAT  3.9815490681  <NA> #> 5482  2056E    3M  CC37 2019 2019-06-03       NO23 -5.5214609179     U #> 5483  2056E    3M  CC37 2019 2019-06-03      SALIN  2.9982291538  <NA> #> 5484  2056E    3M  CC37 2019 2019-06-03        TKN -0.0512932944  <NA> #> 5485  2056E    3M  CC37 2019 2019-06-03         TN -0.0491902442     + #> 5486  2056E    3M  CC37 2019 2019-06-03         TP -0.9416085399  <NA> #> 5487  2056E    3M  CC37 2019 2019-06-03       TURB  0.8754687374  <NA> #> 5488  2056E    3M  CC37 2019 2019-07-01      CHLAC  3.1354942159  <NA> #> 5489  2056E    3M  CC37 2019 2019-07-01      COLOR  3.5553480615     A #> 5490  2056E    3M  CC37 2019 2019-07-01         DO  0.6259384309  <NA> #> 5491  2056E    3M  CC37 2019 2019-07-01      DOSAT  3.1441522787  <NA> #> 5492  2056E    3M  CC37 2019 2019-07-01       NO23 -5.5214609179     I #> 5493  2056E    3M  CC37 2019 2019-07-01      SALIN  2.7825390531  <NA> #> 5494  2056E    3M  CC37 2019 2019-07-01        TKN -0.1278333715  <NA> #> 5495  2056E    3M  CC37 2019 2019-07-01         TN -0.1232982163     + #> 5496  2056E    3M  CC37 2019 2019-07-01         TP -0.5798184953  <NA> #> 5497  2056E    3M  CC37 2019 2019-07-01       TURB  1.0296194172  <NA> #> 5498  2056E    3M  CC37 2019 2019-08-05      CHLAC  3.1354942159  <NA> #> 5499  2056E    3M  CC37 2019 2019-08-05      COLOR  4.2341065046     A #> 5500  2056E    3M  CC37 2019 2019-08-05         DO  1.9685099810  <NA> #> 5501  2056E    3M  CC37 2019 2019-08-05      DOSAT  4.5880240272  <NA> #> 5502  2056E    3M  CC37 2019 2019-08-05       NO23 -4.9618451299     I #> 5503  2056E    3M  CC37 2019 2019-08-05      SALIN  2.0744289999  <NA> #> 5504  2056E    3M  CC37 2019 2019-08-05        TKN -0.1053605157  <NA> #> 5505  2056E    3M  CC37 2019 2019-08-05         TN -0.1009259186     + #> 5506  2056E    3M  CC37 2019 2019-08-05         TP -1.1086626245  <NA> #> 5507  2056E    3M  CC37 2019 2019-08-05       TURB  1.1314021115  <NA> #> 5508  2056E    3M  CC37 2019 2019-10-07      CHLAC  2.0794415417  <NA> #> 5509  2056E    3M  CC37 2019 2019-10-07      COLOR  3.7376696183     A #> 5510  2056E    3M  CC37 2019 2019-10-07         DO  1.4036429995  <NA> #> 5511  2056E    3M  CC37 2019 2019-10-07      DOSAT  4.0910056610  <NA> #> 5512  2056E    3M  CC37 2019 2019-10-07       NO23 -5.5214609179     U #> 5513  2056E    3M  CC37 2019 2019-10-07      SALIN  3.0842009215  <NA> #> 5514  2056E    3M  CC37 2019 2019-10-07        TKN -0.3566749439  <NA> #> 5515  2056E    3M  CC37 2019 2019-10-07         TN -0.3538218750     + #> 5516  2056E    3M  CC37 2019 2019-10-07         TP -1.6607312068  <NA> #> 5517  2056E    3M  CC37 2019 2019-10-07       TURB  0.4054651081  <NA> #> 5518  2056E    3M  CC37 2019 2019-11-04      CHLAC  1.1939224685  <NA> #> 5519  2056E    3M  CC37 2019 2019-11-04      COLOR  3.5835189385  <NA> #> 5520  2056E    3M  CC37 2019 2019-11-04         DO  1.6034198401  <NA> #> 5521  2056E    3M  CC37 2019 2019-11-04      DOSAT  4.2470656492  <NA> #> 5522  2056E    3M  CC37 2019 2019-11-04       NO23 -4.4228486292  <NA> #> 5523  2056E    3M  CC37 2019 2019-11-04      SALIN  2.9922261342  <NA> #> 5524  2056E    3M  CC37 2019 2019-11-04        TKN -0.3285040670  <NA> #> 5525  2056E    3M  CC37 2019 2019-11-04         TN -0.3119747650     + #> 5526  2056E    3M  CC37 2019 2019-11-04         TP -1.4271163556  <NA> #> 5527  2056E    3M  CC37 2019 2019-11-04       TURB  0.0000000000  <NA> #> 5528  2056E    3M  CC37 2019 2019-12-02      CHLAC  1.8245492921     A #> 5529  2056E    3M  CC37 2019 2019-12-02      COLOR  3.3322045102  <NA> #> 5530  2056E    3M  CC37 2019 2019-12-02         DO  1.3532545070  <NA> #> 5531  2056E    3M  CC37 2019 2019-12-02      DOSAT  3.9740583963  <NA> #> 5532  2056E    3M  CC37 2019 2019-12-02       NO23 -5.2983173665     I #> 5533  2056E    3M  CC37 2019 2019-12-02      SALIN  3.1363634033  <NA> #> 5534  2056E    3M  CC37 2019 2019-12-02        TKN -0.4942963218  <NA> #> 5535  2056E    3M  CC37 2019 2019-12-02         TN -0.4877603508     + #> 5536  2056E    3M  CC37 2019 2019-12-02         TP -1.8325814637  <NA> #> 5537  2056E    3M  CC37 2019 2019-12-02       TURB  0.7884573604  <NA> #> 5538  2056E    3M  CC37 2020 2020-01-06      CHLAC  2.7080502011  <NA> #> 5539  2056E    3M  CC37 2020 2020-01-06      COLOR  3.1354942159     A #> 5540  2056E    3M  CC37 2020 2020-01-06         DO  2.0055258587  <NA> #> 5541  2056E    3M  CC37 2020 2020-01-06      DOSAT  4.5347477217  <NA> #> 5542  2056E    3M  CC37 2020 2020-01-06       NO23 -4.7105307016     I #> 5543  2056E    3M  CC37 2020 2020-01-06      SALIN  3.0387917630  <NA> #> 5544  2056E    3M  CC37 2020 2020-01-06        TKN -0.3710636814  <NA> #> 5545  2056E    3M  CC37 2020 2020-01-06         TN -0.3652833185     + #> 5546  2056E    3M  CC37 2020 2020-01-06         TP -1.6607312068  <NA> #> 5547  2056E    3M  CC37 2020 2020-01-06       TURB  1.0647107370  <NA> #> 5548  2056E    3M  CC37 2020 2020-02-03      CHLAC  2.5649493575  <NA> #> 5549  2056E    3M  CC37 2020 2020-02-03      COLOR  2.9957322736  <NA> #> 5550  2056E    3M  CC37 2020 2020-02-03         DO  1.8148247422  <NA> #> 5551  2056E    3M  CC37 2020 2020-02-03      DOSAT  4.2808241292  <NA> #> 5552  2056E    3M  CC37 2020 2020-02-03       NO23 -4.3428059215  <NA> #> 5553  2056E    3M  CC37 2020 2020-02-03      SALIN  3.1175073305  <NA> #> 5554  2056E    3M  CC37 2020 2020-02-03        TKN -0.3856624808  <NA> #> 5555  2056E    3M  CC37 2020 2020-02-03         TN -0.3667252798     + #> 5556  2056E    3M  CC37 2020 2020-02-03         TP -1.9661128564  <NA> #> 5557  2056E    3M  CC37 2020 2020-02-03       TURB  1.4109869737     A #> 5558  2056E    3M  CC37 2020 2020-03-02      CHLAC  1.9740810260  <NA> #> 5559  2056E    3M  CC37 2020 2020-03-02      COLOR  2.8903717579  <NA> #> 5560  2056E    3M  CC37 2020 2020-03-02         DO  1.8484548129  <NA> #> 5561  2056E    3M  CC37 2020 2020-03-02      DOSAT  4.3832758541  <NA> #> 5562  2056E    3M  CC37 2020 2020-03-02       NO23 -5.2983173665     I #> 5563  2056E    3M  CC37 2020 2020-03-02      SALIN  3.1320098918  <NA> #> 5564  2056E    3M  CC37 2020 2020-03-02        TKN -0.4004775666  <NA> #> 5565  2056E    3M  CC37 2020 2020-03-02         TN -0.3945251681     + #> 5566  2056E    3M  CC37 2020 2020-03-02         TP -1.9661128564  <NA> #> 5567  2056E    3M  CC37 2020 2020-03-02       TURB  1.2809338455     A #> 5568  2056E    3M  CC37 2020 2020-09-08      CHLAC  1.6486586256  <NA> #> 5569  2056E    3M  CC37 2020 2020-09-08      COLOR  4.4998096703  <NA> #> 5570  2056E    3M  CC37 2020 2020-09-08         DO  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3M  CC37 2020 2020-10-05        TKN  0.1823215568  <NA> #> 5585  2056E    3M  CC37 2020 2020-10-05         TN  0.2134971743     + #> 5586  2056E    3M  CC37 2020 2020-10-05         TP -0.7765287895  <NA> #> 5587  2056E    3M  CC37 2020 2020-10-05       TURB  0.3364722366  <NA> #> 5588  2056E    3M  CC37 2020 2020-11-02      CHLAC  2.1400661635  <NA> #> 5589  2056E    3M  CC37 2020 2020-11-02      COLOR  4.2046926194  <NA> #> 5590  2056E    3M  CC37 2020 2020-11-02         DO  1.8468787684  <NA> #> 5591  2056E    3M  CC37 2020 2020-11-02      DOSAT  4.4670568839  <NA> #> 5592  2056E    3M  CC37 2020 2020-11-02       NO23 -3.2968373663  <NA> #> 5593  2056E    3M  CC37 2020 2020-11-02      SALIN  2.6525374912  <NA> #> 5594  2056E    3M  CC37 2020 2020-11-02        TKN -0.3147107448  <NA> #> 5595  2056E    3M  CC37 2020 2020-11-02         TN -0.2652684776     + #> 5596  2056E    3M  CC37 2020 2020-11-02         TP -1.3093333200  <NA> #> 5597  2056E    3M  CC37 2020 2020-11-02       TURB  0.6931471806     A #> 5598  2056E    3M  CC37 2020 2020-12-07      CHLAC  1.6677068206  <NA> #> 5599  2056E    3M  CC37 2020 2020-12-07      COLOR  3.8712010109  <NA> #> 5600  2056E    3M  CC37 2020 2020-12-07         DO  1.9050881545  <NA> #> 5601  2056E    3M  CC37 2020 2020-12-07      DOSAT  4.4164280614  <NA> #> 5602  2056E    3M  CC37 2020 2020-12-07       NO23 -3.9633162998  <NA> #> 5603  2056E    3M  CC37 2020 2020-12-07      SALIN  2.8735646396  <NA> #> 5604  2056E    3M  CC37 2020 2020-12-07        TKN -0.4942963218  <NA> #> 5605  2056E    3M  CC37 2020 2020-12-07         TN -0.4636240223     + #> 5606  2056E    3M  CC37 2020 2020-12-07         TP -1.8325814637  <NA> #> 5607  2056E    3M  CC37 2020 2020-12-07       TURB  0.1823215568  <NA> #> 5608  2056E    3M  CC37 2021 2021-01-04      CHLAC  0.8754687374     I #> 5609  2056E    3M  CC37 2021 2021-01-04      COLOR  3.5835189385  <NA> #> 5610  2056E    3M  CC37 2021 2021-01-04         DO  1.4279160358  <NA> #> 5611  2056E    3M  CC37 2021 2021-01-04      DOSAT  3.9569963711  <NA> #> 5612  2056E    3M  CC37 2021 2021-01-04       NO23 -4.1351665567  <NA> #> 5613  2056E    3M  CC37 2021 2021-01-04      SALIN  2.8249439526  <NA> #> 5614  2056E    3M  CC37 2021 2021-01-04        TKN -0.3285040670  <NA> #> 5615  2056E    3M  CC37 2021 2021-01-04         TN -0.3065251603     + #> 5616  2056E    3M  CC37 2021 2021-01-04         TP -1.8971199849  <NA> #> 5617  2056E    3M  CC37 2021 2021-01-04       TURB  0.6418538862  <NA> #> 5618  2056E    3M  CC37 2021 2021-02-01      CHLAC  1.0986122887  <NA> #> 5619  2056E    3M  CC37 2021 2021-02-01      COLOR  3.2958368660     A #> 5620  2056E    3M  CC37 2021 2021-02-01         DO  2.0464016876  <NA> #> 5621  2056E    3M  CC37 2021 2021-02-01      DOSAT  4.5767707115  <NA> #> 5622  2056E    3M  CC37 2021 2021-02-01       NO23 -5.1159958098     I #> 5623  2056E    3M  CC37 2021 2021-02-01      SALIN  2.9957322736  <NA> #> 5624  2056E    3M  CC37 2021 2021-02-01        TKN 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3M  CC37 2021 2021-04-05      CHLAC  1.7917594692  <NA> #> 5639  2056E    3M  CC37 2021 2021-04-05      COLOR  3.1354942159  <NA> #> 5640  2056E    3M  CC37 2021 2021-04-05         DO  1.5040773968  <NA> #> 5641  2056E    3M  CC37 2021 2021-04-05      DOSAT  4.0604430105  <NA> #> 5642  2056E    3M  CC37 2021 2021-04-05       NO23 -4.5098600062  <NA> #> 5643  2056E    3M  CC37 2021 2021-04-05      SALIN  3.1599747169  <NA> #> 5644  2056E    3M  CC37 2021 2021-04-05        TKN -0.1984509387  <NA> #> 5645  2056E    3M  CC37 2021 2021-04-05         TN -0.1851254841     + #> 5646  2056E    3M  CC37 2021 2021-04-05         TP -1.7719568419  <NA> #> 5647  2056E    3M  CC37 2021 2021-04-05       TURB  1.7047480922  <NA> #> 5648  2056E    3M  CC37 2021 2021-05-03      CHLAC  2.0149030205  <NA> #> 5649  2056E    3M  CC37 2021 2021-05-03      COLOR  3.1354942159  <NA> #> 5650  2056E    3M  CC37 2021 2021-05-03         DO  1.1314021115  <NA> #> 5651  2056E    3M  CC37 2021 2021-05-03      DOSAT  3.8286413965  <NA> #> 5652  2056E    3M  CC37 2021 2021-05-03       NO23 -4.8283137373     I #> 5653  2056E    3M  CC37 2021 2021-05-03      SALIN  3.2196755050  <NA> #> 5654  2056E    3M  CC37 2021 2021-05-03        TKN -0.3011050928  <NA> #> 5655  2056E    3M  CC37 2021 2021-05-03         TN -0.2957142441     + #> 5656  2056E    3M  CC37 2021 2021-05-03         TP -1.4696759701  <NA> #> 5657  2056E    3M  CC37 2021 2021-05-03       TURB  1.5260563035  <NA> #> 5658  2056E    3M  CC37 2021 2021-06-07      CHLAC  2.2617630985  <NA> #> 5659  2056E    3M  CC37 2021 2021-06-07      COLOR  2.8903717579  <NA> #> 5660  2056E    3M  CC37 2021 2021-06-07         DO  1.1314021115  <NA> #> 5661  2056E    3M  CC37 2021 2021-06-07      DOSAT  3.8286413965  <NA> #> 5662  2056E    3M  CC37 2021 2021-06-07       NO23 -5.5214609179     U #> 5663  2056E    3M  CC37 2021 2021-06-07      SALIN  3.2196755050  <NA> #> 5664  2056E    3M  CC37 2021 2021-06-07        TKN  0.0953101798  <NA> #> 5665  2056E    3M  CC37 2021 2021-06-07         TN  0.0971267107     + #> 5666  2056E    3M  CC37 2021 2021-06-07         TP -1.3093333200  <NA> #> 5667  2056E    3M  CC37 2021 2021-06-07       TURB  1.2809338455  <NA> #> 5668  2056E    3M  CC37 2021 2021-08-02      CHLAC  2.7080502011  <NA> #> 5669  2056E    3M  CC37 2021 2021-08-02      COLOR  4.5217885770  <NA> #> 5670  2056E    3M  CC37 2021 2021-08-02         DO  1.6034198401  <NA> #> 5671  2056E    3M  CC37 2021 2021-08-02      DOSAT  4.2766661190  <NA> #> 5672  2056E    3M  CC37 2021 2021-08-02       NO23 -5.5214609179     U #> 5673  2056E    3M  CC37 2021 2021-08-02      SALIN  2.1871742415  <NA> #> 5674  2056E    3M  CC37 2021 2021-08-02        TKN -0.1053605157  <NA> #> 5675  2056E    3M  CC37 2021 2021-08-02         TN -0.1031407589     + #> 5676  2056E    3M  CC37 2021 2021-08-02         TP -0.6733445533  <NA> #> 5677  2056E    3M  CC37 2021 2021-08-02       TURB  0.8754687374  <NA> #> 5678  2056E    3M  CC37 2021 2021-09-07      CHLAC  1.8405496334  <NA> #> 5679  2056E    3M  CC37 2021 2021-09-07      COLOR  4.2341065046  <NA> #> 5680  2056E    3M  CC37 2021 2021-09-07         DO  1.5260563035  <NA> #> 5681  2056E    3M  CC37 2021 2021-09-07      DOSAT  4.1447207695  <NA> #> 5682  2056E    3M  CC37 2021 2021-09-07       NO23 -3.6119184130  <NA> #> 5683  2056E    3M  CC37 2021 2021-09-07      SALIN  2.0041790572  <NA> #> 5684  2056E    3M  CC37 2021 2021-09-07        TKN -0.0943106795  <NA> #> 5685  2056E    3M  CC37 2021 2021-09-07         TN -0.0650719967     + #> 5686  2056E    3M  CC37 2021 2021-09-07         TP -1.0788096614  <NA> #> 5687  2056E    3M  CC37 2021 2021-09-07       TURB  0.5306282511     A #> 5688  2056E    3M  CC37 2021 2021-10-04      CHLAC  2.4849066498  <NA> #> 5689  2056E    3M  CC37 2021 2021-10-04      COLOR  4.5643481915     A #> 5690  2056E    3M  CC37 2021 2021-10-04         DO  0.4446858213  <NA> #> 5691  2056E    3M  CC37 2021 2021-10-04      DOSAT  3.0587070727  <NA> #> 5692  2056E    3M  CC37 2021 2021-10-04       NO23 -3.0576076773  <NA> #> 5693  2056E    3M  CC37 2021 2021-10-04      SALIN  2.4932054526  <NA> #> 5694  2056E    3M  CC37 2021 2021-10-04        TKN  0.0953101798  <NA> #> 5695  2056E    3M  CC37 2021 2021-10-04         TN  0.1371498381     + #> 5696  2056E    3M  CC37 2021 2021-10-04         TP -0.7985076962  <NA> #> 5697  2056E    3M  CC37 2021 2021-10-04       TURB  0.4054651081  <NA> #> 5698  2056E    3M  CC37 2021 2021-11-01      CHLAC  1.7749523509  <NA> #> 5699  2056E    3M  CC37 2021 2021-11-01      COLOR  3.7612001157     A #> 5700  2056E    3M  CC37 2021 2021-11-01         DO  1.2325602612  <NA> #> 5701  2056E    3M  CC37 2021 2021-11-01      DOSAT  3.8177123260  <NA> #> 5702  2056E    3M  CC37 2021 2021-11-01       NO23 -3.5065578973  <NA> #> 5703  2056E    3M  CC37 2021 2021-11-01      SALIN  2.9444389792  <NA> #> 5704  2056E    3M  CC37 2021 2021-11-01        TKN -0.2231435513  <NA> #> 5705  2056E    3M  CC37 2021 2021-11-01         TN -0.1863295782     + #> 5706  2056E    3M  CC37 2021 2021-11-01         TP -1.6094379124  <NA> #> 5707  2056E    3M  CC37 2021 2021-11-01       TURB  0.2623642645  <NA> #> 5708  2056E    3M  CC37 2021 2021-12-06      CHLAC  1.7578579176  <NA> #> 5709  2056E    3M  CC37 2021 2021-12-06      COLOR  3.0445224377  <NA> #> 5710  2056E    3M  CC37 2021 2021-12-06         DO  1.5260563035  <NA> #> 5711  2056E    3M  CC37 2021 2021-12-06      DOSAT  4.1157798429  <NA> #> 5712  2056E    3M  CC37 2021 2021-12-06       NO23 -4.7105307016     I #> 5713  2056E    3M  CC37 2021 2021-12-06      SALIN  3.1471649773  <NA> #> 5714  2056E    3M  CC37 2021 2021-12-06        TKN -0.5978370008  <NA> #> 5715  2056E    3M  CC37 2021 2021-12-06         TN -0.5905905922     + #> 5716  2056E    3M  CC37 2021 2021-12-06         TP -2.1202635362  <NA> #> 5717  2056E    3M  CC37 2021 2021-12-06       TURB  0.4700036292  <NA> #> 5718  2056E    3M  CC37 2022 2022-01-03      CHLAC  2.1162555148  <NA> #> 5719  2056E    3M  CC37 2022 2022-01-03      COLOR  2.8903717579  <NA> #> 5720  2056E    3M  CC37 2022 2022-01-03         DO  1.2974631474  <NA> #> 5721  2056E    3M  CC37 2022 2022-01-03      DOSAT  3.9160150267  <NA> #> 5722  2056E    3M  CC37 2022 2022-01-03       NO23 -4.9618451299     I #> 5723  2056E    3M  CC37 2022 2022-01-03      SALIN  3.1289511173  <NA> #> 5724  2056E    3M  CC37 2022 2022-01-03        TKN -0.4780358009  <NA> #> 5725  2056E    3M  CC37 2022 2022-01-03         TN -0.4716049106     + #> 5726  2056E    3M  CC37 2022 2022-01-03         TP -1.9661128564  <NA> #> 5727  2056E    3M  CC37 2022 2022-01-03       TURB  1.2809338455     A #> 5728  2056E    3M  CC37 2022 2022-02-07      CHLAC  2.0918640617  <NA> #> 5729  2056E    3M  CC37 2022 2022-02-07      COLOR  2.6390573296  <NA> #> 5730  2056E    3M  CC37 2022 2022-02-07         DO  1.5518087996  <NA> #> 5731  2056E    3M  CC37 2022 2022-02-07      DOSAT  4.1075897890  <NA> #> 5732  2056E    3M  CC37 2022 2022-02-07       NO23 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3M  CC37 2022 2022-03-07         TP -2.0402208285  <NA> #> 5747  2056E    3M  CC37 2022 2022-03-07       TURB  1.0647107370  <NA> #> 5748  2056E    3M  CC37 2022 2022-04-04      CHLAC  1.6863989536  <NA> #> 5749  2056E    3M  CC37 2022 2022-04-04      COLOR  2.5649493575  <NA> #> 5750  2056E    3M  CC37 2022 2022-04-04         DO  1.4816045409  <NA> #> 5751  2056E    3M  CC37 2022 2022-04-04      DOSAT  4.1319614258  <NA> #> 5752  2056E    3M  CC37 2022 2022-04-04       NO23 -4.5098600062  <NA> #> 5753  2056E    3M  CC37 2022 2022-04-04      SALIN  3.3311325072  <NA> #> 5754  2056E    3M  CC37 2022 2022-04-04         TN -0.6520052372     + #> 5755  2056E    3M  CC37 2022 2022-04-04         TP -1.7719568419  <NA> #> 5756  2056E    3M  CC37 2022 2022-04-04       TURB  1.1631508098  <NA> #> 5757  2056E    3M  CC37 2022 2022-05-02      CHLAC  1.5892352051  <NA> #> 5758  2056E    3M  CC37 2022 2022-05-02      COLOR  2.7080502011  <NA> #> 5759  2056E    3M  CC37 2022 2022-05-02         DO  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3M  CC37 2022 2022-06-06        TKN -0.0725706928  <NA> #> 5774  2056E    3M  CC37 2022 2022-06-06         TN -0.0682788408     + #> 5775  2056E    3M  CC37 2022 2022-06-06         TP -1.1711829815  <NA> #> 5776  2056E    3M  CC37 2022 2022-06-06       TURB  1.3609765531     A #> 5777  2056E    3M  CC37 2022 2022-07-05      CHLAC  1.7047480922  <NA> #> 5778  2056E    3M  CC37 2022 2022-07-05      COLOR  3.6635616461  <NA> #> 5779  2056E    3M  CC37 2022 2022-07-05         DO  1.3056264581  <NA> #> 5780  2056E    3M  CC37 2022 2022-07-05      DOSAT  3.9684033389  <NA> #> 5781  2056E    3M  CC37 2022 2022-07-05       NO23 -5.5214609179     U #> 5782  2056E    3M  CC37 2022 2022-07-05      SALIN  2.7047112998  <NA> #> 5783  2056E    3M  CC37 2022 2022-07-05        TKN -0.2613647641  <NA> #> 5784  2056E    3M  CC37 2022 2022-07-05         TN -0.2587707290     + #> 5785  2056E    3M  CC37 2022 2022-07-05         TP -1.3093333200  <NA> #> 5786  2056E    3M  CC37 2022 2022-07-05       TURB  0.5877866649     A #> 5787  2056E    3M  CC37 2022 2022-08-01      CHLAC  1.9459101491  <NA> #> 5788  2056E    3M  CC37 2022 2022-08-01      COLOR  4.1588830834  <NA> #> 5789  2056E    3M  CC37 2022 2022-08-01         DO  1.2029723040  <NA> #> 5790  2056E    3M  CC37 2022 2022-08-01      DOSAT  3.8501476017  <NA> #> 5791  2056E    3M  CC37 2022 2022-08-01       NO23 -5.5214609179     I #> 5792  2056E    3M  CC37 2022 2022-08-01      SALIN  2.5201129055  <NA> #> 5793  2056E    3M  CC37 2022 2022-08-01        TKN  0.0000000000  <NA> #> 5794  2056E    3M  CC37 2022 2022-08-01         TN  0.0039920213     + #> 5795  2056E    3M  CC37 2022 2022-08-01         TP -1.1394342832  <NA> #> 5796  2056E    3M  CC37 2022 2022-08-01       TURB  0.7419373447  <NA> #> 5797  2056E    3M  CC37 2022 2022-09-06      CHLAC  2.5649493575  <NA> #> 5798  2056E    3M  CC37 2022 2022-09-06      COLOR  4.3694478525     A #> 5799  2056E    3M  CC37 2022 2022-09-06       NO23 -5.1159958098     I #> 5800  2056E    3M  CC37 2022 2022-09-06      SALIN  2.2955604781  <NA> #> 5801  2056E    3M  CC37 2022 2022-09-06        TKN -0.1508228897  <NA> #> 5802  2056E    3M  CC37 2022 2022-09-06         TN -0.1461825102     + #> 5803  2056E    3M  CC37 2022 2022-09-06         TP -1.1086626245  <NA> #> 5804  2056E    3M  CC37 2022 2022-09-06       TURB  0.6418538862  <NA> #> 5805  2056E    3M  CC37 2022 2022-11-07      COLOR  4.2046926194     A #> 5806  2056E    3M  CC37 2022 2022-11-07         DO  1.5238800241  <NA> #> 5807  2056E    3M  CC37 2022 2022-11-07      DOSAT  4.1383614476  <NA> #> 5808  2056E    3M  CC37 2022 2022-11-07       NO23 -3.0159349809  <NA> #> 5809  2056E    3M  CC37 2022 2022-11-07      SALIN  2.7744619666  <NA> #> 5810  2056E    3M  CC37 2022 2022-11-07        TKN -0.0725706928  <NA> #> 5811  2056E    3M  CC37 2022 2022-11-07         TN -0.0212236365     + #> 5812  2056E    3M  CC37 2022 2022-11-07         TP -0.9416085399  <NA> #> 5813  2056E    3M  CC37 2022 2022-11-07       TURB  0.5306282511  <NA> #> 5814  2056E    3M  CC37 2022 2022-11-07      CHLAC  2.1517622033  <NA> #> 5815  2056E    3M  CC37 2022 2022-11-07      COLOR  4.1431347264  <NA> #> 5816  2056E    3M  CC37 2022 2022-11-07         DO  1.5238800241  <NA> #> 5817  2056E    3M  CC37 2022 2022-11-07      DOSAT  4.1383614476  <NA> #> 5818  2056E    3M  CC37 2022 2022-11-07       NO23 -2.9957322736  <NA> #> 5819  2056E    3M  CC37 2022 2022-11-07      SALIN  2.7744619666  <NA> #> 5820  2056E    3M  CC37 2022 2022-11-07        TKN  0.0000000000  <NA> #> 5821  2056E    3M  CC37 2022 2022-11-07         TN  0.0487901642     + #> 5822  2056E    3M  CC37 2022 2022-11-07         TP -0.9162907319  <NA> #> 5823  2056E    3M  CC37 2022 2022-11-07       TURB  0.6418538862  <NA> #> 5824  2056E    3M  CC37 2022 2022-12-05      CHLAC  2.3025850930  <NA> #> 5825  2056E    3M  CC37 2022 2022-12-05      COLOR  3.8918202981     A #> 5826  2056E    3M  CC37 2022 2022-12-05         DO  1.3812818193  <NA> #> 5827  2056E    3M  CC37 2022 2022-12-05      DOSAT  3.9337844972  <NA> #> 5828  2056E    3M  CC37 2022 2022-12-05       NO23 -2.8824035882  <NA> #> 5829  2056E    3M  CC37 2022 2022-12-05      SALIN  2.8219739474  <NA> #> 5830  2056E    3M  CC37 2022 2022-12-05        TKN -0.3147107448  <NA> #> 5831  2056E    3M  CC37 2022 2022-12-05         TN -0.2407984866     + #> 5832  2056E    3M  CC37 2022 2022-12-05         TP -1.4696759701  <NA> #> 5833  2056E    3M  CC37 2022 2022-12-05       TURB  0.5306282511  <NA> #> 5834  2056E    3M  CC37 2023 2023-01-03      CHLAC  2.8903717579  <NA> #> 5835  2056E    3M  CC37 2023 2023-01-03      COLOR  3.4011973817     A #> 5836  2056E    3M  CC37 2023 2023-01-03         DO  1.5953389881  <NA> #> 5837  2056E    3M  CC37 2023 2023-01-03      DOSAT  4.1510399059  <NA> #> 5838  2056E    3M  CC37 2023 2023-01-03       NO23 -3.8167128256  <NA> #> 5839  2056E    3M  CC37 2023 2023-01-03      SALIN  2.9699015135  <NA> #> 5840  2056E    3M  CC37 2023 2023-01-03        TKN -0.1984509387  <NA> #> 5841  2056E    3M  CC37 2023 2023-01-03         TN -0.1719752647     + #> 5842  2056E    3M  CC37 2023 2023-01-03         TP -1.6094379124  <NA> #> 5843  2056E    3M  CC37 2023 2023-01-03       TURB  1.4109869737  <NA> #> 5844  2056E    3M  CC37 2023 2023-02-06      CHLAC  1.8082887712  <NA> #> 5845  2056E    3M  CC37 2023 2023-02-06      COLOR  3.1780538303  <NA> #> 5846  2056E    3M  CC37 2023 2023-02-06         DO  1.5953389881  <NA> #> 5847  2056E    3M  CC37 2023 2023-02-06      DOSAT  4.1510399059  <NA> #> 5848  2056E    3M  CC37 2023 2023-02-06       NO23 -5.5214609179     U #> 5849  2056E    3M  CC37 2023 2023-02-06      SALIN  2.9699015135  <NA> #> 5850  2056E    3M  CC37 2023 2023-02-06        TKN -0.3011050928  <NA> #> 5851  2056E    3M  CC37 2023 2023-02-06         TN -0.2984060358     + #> 5852  2056E    3M  CC37 2023 2023-02-06         TP -1.7147984281  <NA> #> 5853  2056E    3M  CC37 2023 2023-02-06       TURB  0.6418538862  <NA> #> 5854  2056E    3M  CC37 2023 2023-03-06         DO  1.1085626195  <NA> #> 5855  2056E    3M  CC37 2023 2023-03-06      DOSAT  3.7727609381  <NA> #> 5856  2056E    3M  CC37 2023 2023-03-06      SALIN  3.0905878046  <NA> #> 5857  2056E    3M  CC42 2019 2019-10-10      CHLAC  1.5892352051  <NA> #> 5858  2056E    3M  CC42 2019 2019-10-10       COND  9.8078573215  <NA> #> 5859  2056E    3M  CC42 2019 2019-10-10       NO23 -3.7722610631  <NA> #> 5860  2056E    3M  CC42 2019 2019-10-10      SALIN  2.3721111556  <NA> #> 5861  2056E    3M  CC42 2019 2019-10-10        TKN -0.3566749439  <NA> #> 5862  2056E    3M  CC42 2019 2019-10-10         TN -0.3243460568     + #> 5863  2056E    3M  CC42 2019 2019-10-10         TP -1.0498221245  <NA> #> 5864  2056E    3M  CC42 2019 2019-10-10        TSS  1.7917594692     I #> 5865  2056E    3M  CC42 2019 2019-10-10       TURB  1.0647107370  <NA> #> 5866 2056C2    3M  CC45 2014 2014-06-10       COND  9.8892364868  <NA> #> 5867 2056C2    3M  CC45 2014 2014-06-10         DO  1.9344157696  <NA> #> 5868 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.5920849464     + #> 5869 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.4595888418  <NA> #> 5870 2056C2    3M  CC45 2014 2014-06-10       NO23 -5.5214609179     U #> 5871 2056C2    3M  CC45 2014 2014-06-10        TKN  1.2809338455  <NA> #> 5872 2056C2    3M  CC45 2014 2014-06-10         TN  1.2809338455  <NA> #> 5873 2056C2    3M  CC45 2014 2014-06-10        TSS  2.3513752572  <NA> #> 5874 2056C2    3M  CC45 2014 2014-06-10       COND  9.8874597915  <NA> #> 5875 2056C2    3M  CC45 2014 2014-06-10         DO  2.0014800002  <NA> #> 5876 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.6587109529     + #> 5877 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.4587337755  <NA> #> 5878 2056C2    3M  CC45 2014 2014-06-10       COND  9.9269599087  <NA> #> 5879 2056C2    3M  CC45 2014 2014-06-10         DO  1.9933388426  <NA> #> 5880 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.6510991179     + #> 5881 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5014359517  <NA> #> 5882 2056C2    3M  CC45 2014 2014-06-10       COND  9.9782238987  <NA> #> 5883 2056C2    3M  CC45 2014 2014-06-10         DO  1.8916048042  <NA> #> 5884 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.5475410732     + #> 5885 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5572273114  <NA> #> 5886 2056C2    3M  CC45 2014 2014-06-10       COND 10.0037852739  <NA> #> 5887 2056C2    3M  CC45 2014 2014-06-10         DO  1.8017098001  <NA> #> 5888 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.4578295981     + #> 5889 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.5862591440  <NA> #> 5890 2056C2    3M  CC45 2014 2014-06-10       COND 10.0950165901  <NA> #> 5891 2056C2    3M  CC45 2014 2014-06-10         DO  1.5475625087  <NA> #> 5892 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.2061840440     + #> 5893 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.6932749155  <NA> #> 5894 2056C2    3M  CC45 2014 2014-06-10       COND 10.1085078656  <NA> #> 5895 2056C2    3M  CC45 2014 2014-06-10         DO  1.4562867329  <NA> #> 5896 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.1141471895     + #> 5897 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.6932749155  <NA> #> 5898 2056C2    3M  CC45 2014 2014-06-10       COND 10.1103391071  <NA> #> 5899 2056C2    3M  CC45 2014 2014-06-10         DO  1.4182774070  <NA> #> 5900 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0775374439     + #> 5901 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7020321288  <NA> #> 5902 2056C2    3M  CC45 2014 2014-06-10       COND 10.1112331617  <NA> #> 5903 2056C2    3M  CC45 2014 2014-06-10         DO  1.4109869737  <NA> #> 5904 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0690267542     + #> 5905 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7027025948  <NA> #> 5906 2056C2    3M  CC45 2014 2014-06-10       COND 10.1134242764  <NA> #> 5907 2056C2    3M  CC45 2014 2014-06-10         DO  1.3787660947  <NA> #> 5908 2056C2    3M  CC45 2014 2014-06-10      DOSAT  4.0377742107     + #> 5909 2056C2    3M  CC45 2014 2014-06-10      SALIN  2.7053799725  <NA> #> 5910 2056C2    3M  CC45 2014 2014-07-10       COND  9.9863570304  <NA> #> 5911 2056C2    3M  CC45 2014 2014-07-10         DO  2.9204697891  <NA> #> 5912 2056C2    3M  CC45 2014 2014-07-10      DOSAT  5.6028565561     + #> 5913 2056C2    3M  CC45 2014 2014-07-10      SALIN  2.5664866368  <NA> #> 5914 2056C2    3M  CC45 2014 2014-07-10       NO23 -4.1351665567     I #> 5915 2056C2    3M  CC45 2014 2014-07-10        TKN  0.5933268453  <NA> #> 5916 2056C2    3M  CC45 2014 2014-07-10         TN  0.5988365011  <NA> #> 5917 2056C2    3M  CC45 2014 2014-07-10        TSS  2.6602595373  <NA> #> 5918 2056C2    3M  CC45 2014 2014-07-10       COND 10.2631181243  <NA> #> 5919 2056C2    3M  CC45 2014 2014-07-10         DO  2.5136560631  <NA> #> 5920 2056C2    3M  CC45 2014 2014-07-10      DOSAT  5.1935122522     + #> 5921 2056C2    3M  CC45 2014 2014-07-10      SALIN  2.7219531063  <NA> #> 5922 2056C2    3M  CC45 2014 2014-07-10       COND 10.5858012624  <NA> #> 5923 2056C2    3M  CC45 2014 2014-07-10         DO  1.3584091576  <NA> #> 5924 2056C2    3M  CC45 2014 2014-07-10      DOSAT  4.0893320204     + #> 5925 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2284300377  <NA> #> 5926 2056C2    3M  CC45 2014 2014-07-10       COND 10.5893079577  <NA> #> 5927 2056C2    3M  CC45 2014 2014-07-10         DO  1.2383742310  <NA> #> 5928 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.9702919136     + #> 5929 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2327787300  <NA> #> 5930 2056C2    3M  CC45 2014 2014-07-10       COND 10.5894086880  <NA> #> 5931 2056C2    3M  CC45 2014 2014-07-10         DO  1.2178757095  <NA> #> 5932 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.9493187902     + #> 5933 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2335673736  <NA> #> 5934 2056C2    3M  CC45 2014 2014-07-10       COND 10.5868621364  <NA> #> 5935 2056C2    3M  CC45 2014 2014-07-10         DO  0.7654678421  <NA> #> 5936 2056C2    3M  CC45 2014 2014-07-10      DOSAT  3.4965075615     + #> 5937 2056C2    3M  CC45 2014 2014-07-10      SALIN  3.2331731296  <NA> #> 5938   2053     2  CC50 2018 2018-03-15      CHLAC  0.9932517730  <NA> #> 5939   2053     2  CC50 2018 2018-03-15       COND 10.6964800681  <NA> #> 5940   2053     2  CC50 2018 2018-03-15         DO  2.0918640617  <NA> #> 5941   2053     2  CC50 2018 2018-03-15      DOSAT  4.6249728133  <NA> #> 5942   2053     2  CC50 2018 2018-03-15       NO23 -5.5214609179     U #> 5943   2053     2  CC50 2018 2018-03-15      SALIN  3.5010427166     + #> 5944   2053     2  CC50 2018 2018-03-15        TKN -0.5108256238  <NA> #> 5945   2053     2  CC50 2018 2018-03-15         TN -0.5074978337     + #> 5946   2053     2  CC50 2018 2018-03-15         TP -1.8325814637  <NA> #> 5947   2053     2  CC50 2018 2018-03-15        TSS  1.7917594692     I #> 5948   2053     2  CC50 2018 2018-03-15       TURB  1.1631508098     A #> 5949   2053     2  CC50 2018 2018-03-29      CHLAC  1.9459101491  <NA> #> 5950   2053     2  CC50 2018 2018-03-29       COND 10.6310361598  <NA> #> 5951   2053     2  CC50 2018 2018-03-29         DO  1.8405496334  <NA> #> 5952   2053     2  CC50 2018 2018-03-29      DOSAT  4.4426512565  <NA> #> 5953   2053     2  CC50 2018 2018-03-29       NO23 -5.5214609179     U #> 5954   2053     2  CC50 2018 2018-03-29      SALIN  3.3382575819     + #> 5955   2053     2  CC50 2018 2018-03-29        TKN  0.4054651081  <NA> #> 5956   2053     2  CC50 2018 2018-03-29         TN  0.4067975533     + #> 5957   2053     2  CC50 2018 2018-03-29         TP -1.8325814637  <NA> #> 5958   2053     2  CC50 2018 2018-03-29        TSS  2.6390573296  <NA> #> 5959   2053     2  CC50 2018 2018-03-29       TURB  1.7047480922  <NA> #> 5960   2053     2  CC50 2018 2018-04-23      CHLAC  2.0794415417  <NA> #> 5961   2053     2  CC50 2018 2018-04-23       COND 10.6468524493  <NA> #> 5962   2053     2  CC50 2018 2018-04-23         DO  1.9459101491  <NA> #> 5963   2053     2  CC50 2018 2018-04-23      DOSAT  4.6249728133  <NA> #> 5964   2053     2  CC50 2018 2018-04-23       NO23 -5.5214609179     U #> 5965   2053     2  CC50 2018 2018-04-23      SALIN  3.2649957605     + #> 5966   2053     2  CC50 2018 2018-04-23        TKN -0.3710636814  <NA> #> 5967   2053     2  CC50 2018 2018-04-23         TN -0.3681693234     + #> 5968   2053     2  CC50 2018 2018-04-23         TP -1.5141277326  <NA> #> 5969   2053     2  CC50 2018 2018-04-23        TSS  3.3322045102     A #> 5970   2053     2  CC50 2018 2018-04-23       TURB  1.8718021769  <NA> #> 5971   2053     2  CC50 2018 2018-05-10      CHLAC  1.7917594692  <NA> #> 5972   2053     2  CC50 2018 2018-05-10       COND 10.6712318713  <NA> #> 5973   2053     2  CC50 2018 2018-05-10         DO  1.5040773968  <NA> #> 5974   2053     2  CC50 2018 2018-05-10      DOSAT  4.1588830834  <NA> #> 5975   2053     2  CC50 2018 2018-05-10       NO23 -5.2983173665     I #> 5976   2053     2  CC50 2018 2018-05-10      SALIN  3.3214324132  <NA> #> 5977   2053     2  CC50 2018 2018-05-10        TKN -0.1165338163  <NA> #> 5978   2053     2  CC50 2018 2018-05-10         TN -0.1120495038     + #> 5979   2053     2  CC50 2018 2018-05-10         TP -1.3862943611  <NA> #> 5980   2053     2  CC50 2018 2018-05-10        TSS  2.7080502011  <NA> #> 5981   2053     2  CC50 2018 2018-05-10       TURB  1.9021075264  <NA> #> 5982   2053     2  CC50 2018 2018-06-11      CHLAC  2.6390573296  <NA> #> 5983   2053     2  CC50 2018 2018-06-11       COND  9.5468126086  <NA> #> 5984   2053     2  CC50 2018 2018-06-11         DO  1.6094379124  <NA> #> 5985   2053     2  CC50 2018 2018-06-11      DOSAT  4.2341065046  <NA> #> 5986   2053     2  CC50 2018 2018-06-11       NO23 -2.7806208939  <NA> #> 5987   2053     2  CC50 2018 2018-06-11      SALIN  2.0918640617  <NA> #> 5988   2053     2  CC50 2018 2018-06-11        TKN  0.1823215568  <NA> #> 5989   2053     2  CC50 2018 2018-06-11         TN  0.2326977641     + #> 5990   2053     2  CC50 2018 2018-06-11         TP -0.7133498879  <NA> #> 5991   2053     2  CC50 2018 2018-06-11        TSS  1.3862943611     I #> 5992   2053     2  CC50 2018 2018-06-11       TURB  0.7419373447  <NA> #> 5993   2053     2  CC50 2018 2018-06-25      CHLAC  3.4011973817  <NA> #> 5994   2053     2  CC50 2018 2018-06-25       COND 10.0243768698  <NA> #> 5995   2053     2  CC50 2018 2018-06-25         DO  1.7209792872  <NA> #> 5996   2053     2  CC50 2018 2018-06-25      DOSAT  4.3719762988  <NA> #> 5997   2053     2  CC50 2018 2018-06-25       NO23 -2.9374633654  <NA> #> 5998   2053     2  CC50 2018 2018-06-25      SALIN  2.5055259370     + #> 5999   2053     2  CC50 2018 2018-06-25        TKN  0.0953101798  <NA> #> 6000   2053     2  CC50 2018 2018-06-25         TN  0.1423672413     + #> 6001   2053     2  CC50 2018 2018-06-25         TP -0.9162907319  <NA> #> 6002   2053     2  CC50 2018 2018-06-25        TSS  1.3862943611     I #> 6003   2053     2  CC50 2018 2018-06-25       TURB  0.9932517730  <NA> #> 6004   2053     2  CC50 2018 2018-08-07      CHLAC  2.8332133441  <NA> #> 6005   2053     2  CC50 2018 2018-08-07       COND  7.3382381501  <NA> #> 6006   2053     2  CC50 2018 2018-08-07         DO  1.7698546338  <NA> #> 6007   2053     2  CC50 2018 2018-08-07      DOSAT  4.3438054219  <NA> #> 6008   2053     2  CC50 2018 2018-08-07       NO23 -3.1235656451  <NA> #> 6009   2053     2  CC50 2018 2018-08-07      SALIN -0.2613647641  <NA> #> 6010   2053     2  CC50 2018 2018-08-07        TKN  0.0953101798  <NA> #> 6011   2053     2  CC50 2018 2018-08-07         TN  0.1345308930     + #> 6012   2053     2  CC50 2018 2018-08-07         TP -1.2378743560  <NA> #> 6013   2053     2  CC50 2018 2018-08-07        TSS  1.3862943611     I #> 6014   2053     2  CC50 2018 2018-08-07       TURB  0.9162907319     A #> 6015   2053     2  CC50 2018 2018-09-06      CHLAC  2.0014800002  <NA> #> 6016   2053     2  CC50 2018 2018-09-06       COND  8.6513743729  <NA> #> 6017   2053     2  CC50 2018 2018-09-06         DO  1.8341801851  <NA> #> 6018   2053     2  CC50 2018 2018-09-06      DOSAT  4.4236483094  <NA> #> 6019   2053     2  CC50 2018 2018-09-06       NO23 -2.5383074265  <NA> #> 6020   2053     2  CC50 2018 2018-09-06      SALIN  1.1281710909  <NA> #> 6021   2053     2  CC50 2018 2018-09-06        TKN  0.1823215568  <NA> #> 6022   2053     2  CC50 2018 2018-09-06         TN  0.2460785226     + #> 6023   2053     2  CC50 2018 2018-09-06         TP -1.2378743560  <NA> #> 6024   2053     2  CC50 2018 2018-09-06        TSS  1.3862943611     I #> 6025   2053     2  CC50 2018 2018-09-06       TURB  0.6931471806  <NA> #> 6026   2053     2  CC50 2018 2018-09-20      CHLAC  2.5649493575  <NA> #> 6027   2053     2  CC50 2018 2018-09-20       COND  9.3369730229  <NA> #> 6028   2053     2  CC50 2018 2018-09-20         DO  1.6582280766  <NA> #> 6029   2053     2  CC50 2018 2018-09-20      DOSAT  4.1682144108  <NA> #> 6030   2053     2  CC50 2018 2018-09-20       NO23 -4.1351665567  <NA> #> 6031   2053     2  CC50 2018 2018-09-20      SALIN  1.8562979904  <NA> #> 6032   2053     2  CC50 2018 2018-09-20        TKN -0.0725706928  <NA> #> 6033   2053     2  CC50 2018 2018-09-20         TN -0.0555127099     + #> 6034   2053     2  CC50 2018 2018-09-20         TP -1.1394342832  <NA> #> 6035   2053     2  CC50 2018 2018-09-20        TSS  1.3862943611     I #> 6036   2053     2  CC50 2018 2018-09-20       TURB  0.4700036292  <NA> #> 6037   2053     2  CC50 2018 2018-10-24      CHLAC  1.9600947840  <NA> #> 6038   2053     2  CC50 2018 2018-10-24       COND 10.0400269167  <NA> #> 6039   2053     2  CC50 2018 2018-10-24         DO  1.9430489168  <NA> #> 6040   2053     2  CC50 2018 2018-10-24      DOSAT  4.5496574761  <NA> #> 6041   2053     2  CC50 2018 2018-10-24       NO23 -2.7488721956  <NA> #> 6042   2053     2  CC50 2018 2018-10-24      SALIN  2.6246685922  <NA> #> 6043   2053     2  CC50 2018 2018-10-24        TKN -0.3011050928  <NA> #> 6044   2053     2  CC50 2018 2018-10-24         TN -0.2181560098     + #> 6045   2053     2  CC50 2018 2018-10-24         TP -1.4271163556  <NA> #> 6046   2053     2  CC50 2018 2018-10-24        TSS  1.6094379124     I #> 6047   2053     2  CC50 2018 2018-10-24       TURB  0.9162907319  <NA> #> 6048   2053     2  CC50 2019 2019-04-17      CHLAC  1.5892352051     I #> 6049   2053     2  CC50 2019 2019-04-17       COND 10.3074515345  <NA> #> 6050   2053     2  CC50 2019 2019-04-17         DO  1.9878743482  <NA> #> 6051   2053     2  CC50 2019 2019-04-17      DOSAT  4.5981455711  <NA> #> 6052   2053     2  CC50 2019 2019-04-17       NO23 -5.5214609179     U #> 6053   2053     2  CC50 2019 2019-04-17      SALIN  2.9193910403  <NA> #> 6054   2053     2  CC50 2019 2019-04-17        TKN -0.4462871026  <NA> #> 6055   2053     2  CC50 2019 2019-04-17         TN -0.4431669753     + #> 6056   2053     2  CC50 2019 2019-04-17         TP -1.6607312068  <NA> #> 6057   2053     2  CC50 2019 2019-04-17        TSS  2.9444389792     A #> 6058   2053     2  CC50 2019 2019-04-17       TURB  1.0296194172  <NA> #> 6059   2053     2  CC50 2019 2019-07-15      CHLAC  3.0910424534  <NA> #> 6060   2053     2  CC50 2019 2019-07-15       COND 10.0506999322  <NA> #> 6061   2053     2  CC50 2019 2019-07-15         DO  1.9430489168  <NA> #> 6062   2053     2  CC50 2019 2019-07-15      DOSAT  4.5971380143  <NA> #> 6063   2053     2  CC50 2019 2019-07-15       NO23 -5.5214609179     U #> 6064   2053     2  CC50 2019 2019-07-15      SALIN  2.6333266549  <NA> #> 6065   2053     2  CC50 2019 2019-07-15        TKN -0.2107210313  <NA> #> 6066   2053     2  CC50 2019 2019-07-15         TN -0.2082549388     + #> 6067   2053     2  CC50 2019 2019-07-15         TP -1.4696759701  <NA> #> 6068   2053     2  CC50 2019 2019-07-15        TSS  2.0794415417     I #> 6069   2053     2  CC50 2019 2019-07-15       TURB  0.9932517730  <NA> #> 6070   2053     2  CC50 2019 2019-08-19      CHLAC  1.4816045409  <NA> #> 6071   2053     2  CC50 2019 2019-08-19       COND  7.3530819205  <NA> #> 6072   2053     2  CC50 2019 2019-08-19         DO  1.5665304114  <NA> #> 6073   2053     2  CC50 2019 2019-08-19      DOSAT  4.1367652781  <NA> #> 6074   2053     2  CC50 2019 2019-08-19       NO23 -2.6036901858  <NA> #> 6075   2053     2  CC50 2019 2019-08-19      SALIN -0.2484613593  <NA> #> 6076   2053     2  CC50 2019 2019-08-19        TKN  0.3364722366  <NA> #> 6077   2053     2  CC50 2019 2019-08-19         TN  0.3879797938     + #> 6078   2053     2  CC50 2019 2019-08-19         TP -0.8209805521  <NA> #> 6079   2053     2  CC50 2019 2019-08-19        TSS  1.0986122887     I #> 6080   2053     2  CC50 2019 2019-08-19       TURB  0.7884573604  <NA> #> 6081   2053     2  CC50 2019 2019-09-11      CHLAC  3.0910424534  <NA> #> 6082   2053     2  CC50 2019 2019-09-11       COND  9.8378817954  <NA> #> 6083   2053     2  CC50 2019 2019-09-11         DO  1.9139771020  <NA> #> 6084   2053     2  CC50 2019 2019-09-11      DOSAT  4.5475410732  <NA> #> 6085   2053     2  CC50 2019 2019-09-11       NO23 -4.0173835211  <NA> #> 6086   2053     2  CC50 2019 2019-09-11      SALIN  2.4015250408  <NA> #> 6087   2053     2  CC50 2019 2019-09-11        TKN -0.0725706928  <NA> #> 6088   2053     2  CC50 2019 2019-09-11         TN -0.0534007767     + #> 6089   2053     2  CC50 2019 2019-09-11         TP -1.2039728043  <NA> #> 6090   2053     2  CC50 2019 2019-09-11        TSS  1.6094379124     I #> 6091   2053     2  CC50 2019 2019-09-11       TURB  0.7884573604  <NA> #> 6092   2053     2  CC50 2019 2019-10-09      CHLAC  1.1939224685  <NA> #> 6093   2053     2  CC50 2019 2019-10-09       COND 10.2652793829  <NA> #> 6094   2053     2  CC50 2019 2019-10-09         DO  1.7065646232  <NA> #> 6095   2053     2  CC50 2019 2019-10-09      DOSAT  4.3554259529  <NA> #> 6096   2053     2  CC50 2019 2019-10-09       NO23 -5.5214609179     I #> 6097   2053     2  CC50 2019 2019-10-09      SALIN  2.8713021952  <NA> #> 6098   2053     2  CC50 2019 2019-10-09        TKN -0.4155154440  <NA> #> 6099   2053     2  CC50 2019 2019-10-09         TN -0.4094731295     + #> 6100   2053     2  CC50 2019 2019-10-09         TP -1.5141277326  <NA> #> 6101   2053     2  CC50 2019 2019-10-09        TSS  1.0986122887     U #> 6102   2053     2  CC50 2019 2019-10-09       TURB -0.1625189295  <NA> #> 6103   2053     2  CC50 2020 2020-02-13      CHLAC  1.5475625087  <NA> #> 6104   2053     2  CC50 2020 2020-02-13       COND 10.4652439050  <NA> #> 6105   2053     2  CC50 2020 2020-02-13         DO  1.8017098001  <NA> #> 6106   2053     2  CC50 2020 2020-02-13      DOSAT  4.4067192473  <NA> #> 6107   2053     2  CC50 2020 2020-02-13       NO23 -5.5214609179     U #> 6108   2053     2  CC50 2020 2020-02-13      SALIN  3.0946722214  <NA> #> 6109   2053     2  CC50 2020 2020-02-13        TKN -0.4620354596  <NA> #> 6110   2053     2  CC50 2020 2020-02-13         TN -0.4588658848     + #> 6111   2053     2  CC50 2020 2020-02-13         TP -1.8325814637  <NA> #> 6112   2053     2  CC50 2020 2020-02-13        TSS  2.7080502011  <NA> #> 6113   2053     2  CC50 2020 2020-02-13       TURB  2.0014800002     A #> 6114   2053     2  CC50 2020 2020-03-24      CHLAC  1.3350010667  <NA> #> 6115   2053     2  CC50 2020 2020-03-24       COND 10.5688523521  <NA> #> 6116   2053     2  CC50 2020 2020-03-24         DO  1.9401794743  <NA> #> 6117   2053     2  CC50 2020 2020-03-24      DOSAT  4.6434288981  <NA> #> 6118   2053     2  CC50 2020 2020-03-24       NO23 -5.5214609179     U #> 6119   2053     2  CC50 2020 2020-03-24      SALIN  3.2047769005  <NA> #> 6120   2053     2  CC50 2020 2020-03-24        TKN -0.4462871026  <NA> #> 6121   2053     2  CC50 2020 2020-03-24         TN -0.4431669753     + #> 6122   2053     2  CC50 2020 2020-03-24         TP -1.8325814637  <NA> #> 6123   2053     2  CC50 2020 2020-03-24        TSS  2.7725887222  <NA> #> 6124   2053     2  CC50 2020 2020-03-24       TURB  1.5260563035  <NA> #> 6125   2053     2  CC50 2020 2020-06-22      CHLAC  3.1780538303  <NA> #> 6126   2053     2  CC50 2020 2020-06-22       COND  9.9972510823  <NA> #> 6127   2053     2  CC50 2020 2020-06-22         DO  1.7173950539  <NA> #> 6128   2053     2  CC50 2020 2020-06-22      DOSAT  4.3795235045  <NA> #> 6129   2053     2  CC50 2020 2020-06-22       NO23 -4.5098600062  <NA> #> 6130   2053     2  CC50 2020 2020-06-22      SALIN  2.5718485799  <NA> #> 6131   2053     2  CC50 2020 2020-06-22        TKN -0.0100503359  <NA> #> 6132   2053     2  CC50 2020 2020-06-22         TN  0.0009995003     + #> 6133   2053     2  CC50 2020 2020-06-22         TP -1.2039728043  <NA> #> 6134   2053     2  CC50 2020 2020-06-22        TSS  1.7917594692     I #> 6135   2053     2  CC50 2020 2020-06-22       TURB  0.7884573604     A #> 6136   2053     2  CC50 2020 2020-07-27      CHLAC  1.7578579176  <NA> #> 6137   2053     2  CC50 2020 2020-07-27       COND 10.1123293191  <NA> #> 6138   2053     2  CC50 2020 2020-07-27         DO  1.5644405465  <NA> #> 6139   2053     2  CC50 2020 2020-07-27      DOSAT  4.2239097666  <NA> #> 6140   2053     2  CC50 2020 2020-07-27       NO23 -4.1351665567  <NA> #> 6141   2053     2  CC50 2020 2020-07-27      SALIN  2.7006898467  <NA> #> 6142   2053     2  CC50 2020 2020-07-27         TN -0.3481400415     + #> 6143   2053     2  CC50 2020 2020-07-27         TP -1.3093333200  <NA> #> 6144   2053     2  CC50 2020 2020-07-27        TSS  1.0986122887     U #> 6145   2053     2  CC50 2020 2020-07-27       TURB  0.5306282511  <NA> #> 6146   2053     2  CC50 2020 2020-08-26      CHLAC  2.2300144002  <NA> #> 6147   2053     2  CC50 2020 2020-08-26       COND  9.8854254097  <NA> #> 6148   2053     2  CC50 2020 2020-08-26         DO  1.7850704811  <NA> #> 6149   2053     2  CC50 2020 2020-08-26      DOSAT  4.4188406078  <NA> #> 6150   2053     2  CC50 2020 2020-08-26       NO23 -5.5214609179     U #> 6151   2053     2  CC50 2020 2020-08-26      SALIN  2.4535879665  <NA> #> 6152   2053     2  CC50 2020 2020-08-26        TKN -0.1984509387  <NA> #> 6153   2053     2  CC50 2020 2020-08-26         TN -0.1960148839     + #> 6154   2053     2  CC50 2020 2020-08-26         TP -1.3862943611  <NA> #> 6155   2053     2  CC50 2020 2020-08-26        TSS  1.0986122887     U #> 6156   2053     2  CC50 2020 2020-08-26       TURB  0.0953101798  <NA> #> 6157   2053     2  CC50 2021 2021-01-14      CHLAC  1.6094379124     A #> 6158   2053     2  CC50 2021 2021-01-14       COND 10.2228136303  <NA> #> 6159   2053     2  CC50 2021 2021-01-14         DO  2.0967901800  <NA> #> 6160   2053     2  CC50 2021 2021-01-14      DOSAT  4.5580785785  <NA> #> 6161   2053     2  CC50 2021 2021-01-14       NO23 -5.5214609179     I #> 6162   2053     2  CC50 2021 2021-01-14      SALIN  2.8314470792  <NA> #> 6163   2053     2  CC50 2021 2021-01-14        TKN -0.2876820725  <NA> #> 6164   2053     2  CC50 2021 2021-01-14         TN -0.2823629110     + #> 6165   2053     2  CC50 2021 2021-01-14         TP -1.7147984281  <NA> #> 6166   2053     2  CC50 2021 2021-01-14        TSS  2.5649493575     A #> 6167   2053     2  CC50 2021 2021-01-14       TURB  1.4586150227  <NA> #> 6168   2053     2  CC50 2021 2021-02-24       COND 10.2486009183  <NA> #> 6169   2053     2  CC50 2021 2021-02-24         DO  2.0955609236  <NA> #> 6170   2053     2  CC50 2021 2021-02-24      DOSAT  4.6453519756  <NA> #> 6171   2053     2  CC50 2021 2021-02-24       NO23 -5.5214609179     U #> 6172   2053     2  CC50 2021 2021-02-24      SALIN  2.8581928595  <NA> #> 6173   2053     2  CC50 2021 2021-02-24        TKN -0.6733445533  <NA> #> 6174   2053     2  CC50 2021 2021-02-24         TN -0.6694306539     + #> 6175   2053     2  CC50 2021 2021-02-24         TP -1.8971199849  <NA> #> 6176   2053     2  CC50 2021 2021-02-24        TSS  1.0986122887     I #> 6177   2053     2  CC50 2021 2021-03-23      CHLAC  0.9555114450  <NA> #> 6178   2053     2  CC50 2021 2021-03-23       COND 10.5061901968  <NA> #> 6179   2053     2  CC50 2021 2021-03-23         DO  1.9685099810  <NA> #> 6180   2053     2  CC50 2021 2021-03-23      DOSAT  4.5119578043  <NA> #> 6181   2053     2  CC50 2021 2021-03-23       NO23 -5.2983173665     I #> 6182   2053     2  CC50 2021 2021-03-23      SALIN  3.1419947805  <NA> #> 6183   2053     2  CC50 2021 2021-03-23        TKN -0.4620354596  <NA> #> 6184   2053     2  CC50 2021 2021-03-23         TN -0.4557063245     + #> 6185   2053     2  CC50 2021 2021-03-23         TP -1.8971199849  <NA> #> 6186   2053     2  CC50 2021 2021-03-23        TSS  1.0986122887     U #> 6187   2053     2  CC50 2021 2021-03-23       TURB  0.6418538862  <NA> #> 6188   2053     2  CC50 2021 2021-07-28      CHLAC  2.2721258855  <NA> #> 6189   2053     2  CC50 2021 2021-07-28       COND  9.4095190458  <NA> #> 6190   2053     2  CC50 2021 2021-07-28         DO  0.9516578757  <NA> #> 6191   2053     2  CC50 2021 2021-07-28      DOSAT  3.5638829639  <NA> #> 6192   2053     2  CC50 2021 2021-07-28       NO23 -3.1700856607  <NA> #> 6193   2053     2  CC50 2021 2021-07-28      SALIN  1.9373017745  <NA> #> 6194   2053     2  CC50 2021 2021-07-28        TKN  0.1823215568  <NA> #> 6195   2053     2  CC50 2021 2021-07-28         TN  0.2167229835     + #> 6196   2053     2  CC50 2021 2021-07-28         TP -0.7550225843  <NA> #> 6197   2053     2  CC50 2021 2021-07-28        TSS  1.3862943611     I #> 6198   2053     2  CC50 2021 2021-07-28       TURB  1.7404661748  <NA> #> 6199   2053     2  CC50 2021 2021-08-26      CHLAC  1.5260563035  <NA> #> 6200   2053     2  CC50 2021 2021-08-26       COND  9.2069345788  <NA> #> 6201   2053     2  CC50 2021 2021-08-26         DO  1.0296194172  <NA> #> 6202   2053     2  CC50 2021 2021-08-26      DOSAT  3.6270040504  <NA> #> 6203   2053     2  CC50 2021 2021-08-26       NO23 -2.7488721956  <NA> #> 6204   2053     2  CC50 2021 2021-08-26      SALIN  1.7191887764  <NA> #> 6205   2053     2  CC50 2021 2021-08-26        TKN -0.3285040670  <NA> #> 6206   2053     2  CC50 2021 2021-08-26         TN -0.2433462586     + #> 6207   2053     2  CC50 2021 2021-08-26         TP -1.0216512475  <NA> #> 6208   2053     2  CC50 2021 2021-08-26        TSS  1.0986122887     I #> 6209   2053     2  CC50 2021 2021-08-26       TURB  0.9555114450  <NA> #> 6210   2053     2  CC50 2021 2021-09-13      CHLAC  1.7578579176  <NA> #> 6211   2053     2  CC50 2021 2021-09-13       COND  9.5941731800  <NA> #> 6212   2053     2  CC50 2021 2021-09-13         DO  1.4422019931  <NA> #> 6213   2053     2  CC50 2021 2021-09-13      DOSAT  4.0707346966  <NA> #> 6214   2053     2  CC50 2021 2021-09-13       NO23 -2.7806208939  <NA> #> 6215   2053     2  CC50 2021 2021-09-13      SALIN  2.1365305087  <NA> #> 6216   2053     2  CC50 2021 2021-09-13        TKN -0.0618754037  <NA> #> 6217   2053     2  CC50 2021 2021-09-13         TN  0.0019980027     + #> 6218   2053     2  CC50 2021 2021-09-13         TP -1.2039728043  <NA> #> 6219   2053     2  CC50 2021 2021-09-13        TSS  1.0986122887     I #> 6220   2053     2  CC50 2021 2021-09-13       TURB  0.5877866649  <NA> #> 6221   2053     2  CC50 2022 2022-03-16       COND 10.6209126256  <NA> #> 6222   2053     2  CC50 2022 2022-03-16         DO  1.9080599249  <NA> #> 6223   2053     2  CC50 2022 2022-03-16      DOSAT  4.5152454785  <NA> #> 6224   2053     2  CC50 2022 2022-03-16      SALIN  3.2676659890  <NA> #> 6225   2053     2  CC50 2022 2022-05-04       COND 10.6380165709  <NA> #> 6226   2053     2  CC50 2022 2022-05-04         DO  1.8748743759  <NA> #> 6227   2053     2  CC50 2022 2022-05-04      DOSAT  4.5622626850  <NA> #> 6228   2053     2  CC50 2022 2022-05-04      SALIN  3.2839142210  <NA> #> 6229   2053     2  CC50 2022 2022-09-14       COND  8.8230589343  <NA> #> 6230   2053     2  CC50 2022 2022-09-14         DO  1.0367368850  <NA> #> 6231   2053     2  CC50 2022 2022-09-14      DOSAT  3.6296600945  <NA> #> 6232   2053     2  CC50 2022 2022-09-14      SALIN  1.3056264581  <NA> #> 6233   2053     2  CC50 2022 2022-10-31       COND  9.8828255561  <NA> #> 6234   2053     2  CC50 2022 2022-10-31         DO  1.6505798558  <NA> #> 6235   2053     2  CC50 2022 2022-10-31      DOSAT  4.2398868675  <NA> #> 6236   2053     2  CC50 2022 2022-10-31      SALIN  2.4535879665  <NA> #> 6237   2054    3F  CC53 2014 2014-01-06      CHLAC  3.3672958300  <NA> #> 6238   2054    3F  CC53 2014 2014-01-06      COLOR  4.1271343850     A #> 6239   2054    3F  CC53 2014 2014-01-06         DO  1.8245492921  <NA> #> 6240   2054    3F  CC53 2014 2014-01-06      DOSAT  4.2209772132     + #> 6241   2054    3F  CC53 2014 2014-01-06       NO23 -2.5133061243  <NA> #> 6242   2054    3F  CC53 2014 2014-01-06      SALIN  0.3364722366  <NA> #> 6243   2054    3F  CC53 2014 2014-01-06        TKN -0.1625189295  <NA> #> 6244   2054    3F  CC53 2014 2014-01-06         TN -0.0714960017     + #> 6245   2054    3F  CC53 2014 2014-01-06         TP 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3F  CC53 2014 2014-06-02      CHLAC  2.3978952728  <NA> #> 6287   2054    3F  CC53 2014 2014-06-02      COLOR  4.1108738642  <NA> #> 6288   2054    3F  CC53 2014 2014-06-02         DO  1.7578579176  <NA> #> 6289   2054    3F  CC53 2014 2014-06-02      DOSAT  4.2780540443     + #> 6290   2054    3F  CC53 2014 2014-06-02       NO23 -4.9618451299     I #> 6291   2054    3F  CC53 2014 2014-06-02        TKN -0.0408219945  <NA> #> 6292   2054    3F  CC53 2014 2014-06-02         TN -0.0366639844     + #> 6293   2054    3F  CC53 2014 2014-06-02         TP -1.5141277326  <NA> #> 6294   2054    3F  CC53 2014 2014-06-02       TURB  1.2527629685  <NA> #> 6295   2054    3F  CC53 2014 2014-07-07      CHLAC  2.3025850930  <NA> #> 6296   2054    3F  CC53 2014 2014-07-07      COLOR  4.8675344505  <NA> #> 6297   2054    3F  CC53 2014 2014-07-07       NO23 -3.0365542681  <NA> #> 6298   2054    3F  CC53 2014 2014-07-07        TKN  0.4054651081  <NA> #> 6299   2054    3F  CC53 2014 2014-07-07         TN  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3F  CC53 2014 2014-12-01      COLOR  4.2626798770  <NA> #> 6341   2054    3F  CC53 2014 2014-12-01         DO  1.7578579176  <NA> #> 6342   2054    3F  CC53 2014 2014-12-01      DOSAT  4.0926765051     + #> 6343   2054    3F  CC53 2014 2014-12-01       NO23 -3.0791138825  <NA> #> 6344   2054    3F  CC53 2014 2014-12-01        TKN -0.1743533871  <NA> #> 6345   2054    3F  CC53 2014 2014-12-01         TN -0.1210383284     + #> 6346   2054    3F  CC53 2014 2014-12-01         TP -2.5257286443  <NA> #> 6347   2054    3F  CC53 2014 2014-12-01       TURB  1.1631508098  <NA> #> 6348   2054    3F  CC53 2015 2015-01-05      CHLAC  2.1400661635  <NA> #> 6349   2054    3F  CC53 2015 2015-01-05      COLOR  4.1896547420  <NA> #> 6350   2054    3F  CC53 2015 2015-01-05         DO  1.6292405397  <NA> #> 6351   2054    3F  CC53 2015 2015-01-05       NO23 -2.7030626596  <NA> #> 6352   2054    3F  CC53 2015 2015-01-05        TKN -0.2613647641  <NA> #> 6353   2054    3F  CC53 2015 2015-01-05         TN 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3F  CC53 2015 2015-03-02         DO  1.9169226122  <NA> #> 6368   2054    3F  CC53 2015 2015-03-02      DOSAT  4.3399017084     + #> 6369   2054    3F  CC53 2015 2015-03-02       NO23 -3.9120230054  <NA> #> 6370   2054    3F  CC53 2015 2015-03-02        TKN -0.1984509387  <NA> #> 6371   2054    3F  CC53 2015 2015-03-02         TN -0.1743533871     + #> 6372   2054    3F  CC53 2015 2015-03-02         TP -2.5770219387  <NA> #> 6373   2054    3F  CC53 2015 2015-03-02       TURB  1.4109869737  <NA> #> 6374   2054    3F  CC53 2015 2015-04-06      CHLAC  2.0412203289  <NA> #> 6375   2054    3F  CC53 2015 2015-04-06      COLOR  4.1431347264  <NA> #> 6376   2054    3F  CC53 2015 2015-04-06         DO  1.5260563035  <NA> #> 6377   2054    3F  CC53 2015 2015-04-06      DOSAT  4.0018637094     + #> 6378   2054    3F  CC53 2015 2015-04-06       NO23 -4.2686979494  <NA> #> 6379   2054    3F  CC53 2015 2015-04-06        TKN  0.0953101798  <NA> #> 6380   2054    3F  CC53 2015 2015-04-06         TN  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3F  CC53 2015 2015-06-01         DO  1.3711807233  <NA> #> 6395   2054    3F  CC53 2015 2015-06-01      DOSAT  3.9259259106     + #> 6396   2054    3F  CC53 2015 2015-06-01       NO23 -4.6051701860  <NA> #> 6397   2054    3F  CC53 2015 2015-06-01      SALIN  1.2059708070  <NA> #> 6398   2054    3F  CC53 2015 2015-06-01        TKN -0.0100503359  <NA> #> 6399   2054    3F  CC53 2015 2015-06-01         TN  0.0000000000     + #> 6400   2054    3F  CC53 2015 2015-06-01         TP -1.5141277326  <NA> #> 6401   2054    3F  CC53 2015 2015-06-01       TURB  0.7419373447  <NA> #> 6402   2054    3F  CC53 2015 2015-08-03      CHLAC  0.5877866649  <NA> #> 6403   2054    3F  CC53 2015 2015-08-03      COLOR  4.9416424226  <NA> #> 6404   2054    3F  CC53 2015 2015-08-03         DO  1.3428648032  <NA> #> 6405   2054    3F  CC53 2015 2015-08-03      DOSAT  3.8897773965     + #> 6406   2054    3F  CC53 2015 2015-08-03       NO23 -4.0745419349  <NA> #> 6407   2054    3F  CC53 2015 2015-08-03      SALIN 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3F  CC53 2015 2015-09-08       TURB  0.9932517730  <NA> #> 6422   2054    3F  CC53 2015 2015-10-05      CHLAC  0.0000000000     I #> 6423   2054    3F  CC53 2015 2015-10-05      COLOR  4.7004803658  <NA> #> 6424   2054    3F  CC53 2015 2015-10-05         DO  1.1505720276  <NA> #> 6425   2054    3F  CC53 2015 2015-10-05      DOSAT  3.6737658163     + #> 6426   2054    3F  CC53 2015 2015-10-05       NO23 -4.4228486292  <NA> #> 6427   2054    3F  CC53 2015 2015-10-05      SALIN -2.6592600369  <NA> #> 6428   2054    3F  CC53 2015 2015-10-05        TKN -0.1625189295  <NA> #> 6429   2054    3F  CC53 2015 2015-10-05         TN -0.1485000083     + #> 6430   2054    3F  CC53 2015 2015-10-05         TP -1.9661128564  <NA> #> 6431   2054    3F  CC53 2015 2015-10-05       TURB  0.5306282511  <NA> #> 6432   2054    3F  CC53 2015 2015-12-07      CHLAC  1.3350010667  <NA> #> 6433   2054    3F  CC53 2015 2015-12-07      COLOR  4.3567088267     A #> 6434   2054    3F  CC53 2015 2015-12-07         DO  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3F  CC53 2016 2016-01-04         TN -0.0661398025     + #> 6449   2054    3F  CC53 2016 2016-01-04         TP -2.5510464523  <NA> #> 6450   2054    3F  CC53 2016 2016-01-04       TURB  0.7419373447  <NA> #> 6451   2054    3F  CC53 2016 2016-02-01      CHLAC -0.1984509387     U #> 6452   2054    3F  CC53 2016 2016-02-01      COLOR  4.5432947823  <NA> #> 6453   2054    3F  CC53 2016 2016-02-01         DO  1.9974177062  <NA> #> 6454   2054    3F  CC53 2016 2016-02-01      DOSAT  4.3630986248     + #> 6455   2054    3F  CC53 2016 2016-02-01       NO23 -5.5214609179     I #> 6456   2054    3F  CC53 2016 2016-02-01      SALIN -3.5065578973  <NA> #> 6457   2054    3F  CC53 2016 2016-02-01        TKN -0.6161861394  <NA> #> 6458   2054    3F  CC53 2016 2016-02-01         TN -0.6088060321     + #> 6459   2054    3F  CC53 2016 2016-02-01         TP -2.6592600369  <NA> #> 6460   2054    3F  CC53 2016 2016-02-01       TURB  0.5877866649     A #> 6461   2054    3F  CC53 2016 2016-03-07      CHLAC  0.4054651081     I #> 6462   2054    3F  CC53 2016 2016-03-07      COLOR  4.3174881135  <NA> #> 6463   2054    3F  CC53 2016 2016-03-07         DO  1.6074359098  <NA> #> 6464   2054    3F  CC53 2016 2016-03-07      DOSAT  4.0127729085     + #> 6465   2054    3F  CC53 2016 2016-03-07       NO23 -3.6119184130  <NA> #> 6466   2054    3F  CC53 2016 2016-03-07      SALIN -2.3025850930  <NA> #> 6467   2054    3F  CC53 2016 2016-03-07        TKN -0.3147107448  <NA> #> 6468   2054    3F  CC53 2016 2016-03-07         TN -0.2783920255     + #> 6469   2054    3F  CC53 2016 2016-03-07         TP -2.9004220937  <NA> #> 6470   2054    3F  CC53 2016 2016-03-07       TURB  0.5306282511     A #> 6471   2054    3F  CC53 2016 2016-04-04      CHLAC  2.0149030205  <NA> #> 6472   2054    3F  CC53 2016 2016-04-04      COLOR  4.0604430105  <NA> #> 6473   2054    3F  CC53 2016 2016-04-04         DO  1.5454325825  <NA> #> 6474   2054    3F  CC53 2016 2016-04-04      DOSAT  4.0253516907     + #> 6475   2054    3F  CC53 2016 2016-04-04       NO23 -3.7722610631  <NA> #> 6476   2054    3F  CC53 2016 2016-04-04      SALIN -1.3093333200  <NA> #> 6477   2054    3F  CC53 2016 2016-04-04        TKN -0.1984509387  <NA> #> 6478   2054    3F  CC53 2016 2016-04-04         TN -0.1707883210     + #> 6479   2054    3F  CC53 2016 2016-04-04         TP -2.3330443005  <NA> #> 6480   2054    3F  CC53 2016 2016-04-04       TURB  1.2527629685  <NA> #> 6481   2054    3F  CC53 2016 2016-05-02      CHLAC  1.0647107370  <NA> #> 6482   2054    3F  CC53 2016 2016-05-02      COLOR  4.1588830834  <NA> #> 6483   2054    3F  CC53 2016 2016-05-02         DO  1.3164082337  <NA> #> 6484   2054    3F  CC53 2016 2016-05-02      DOSAT  3.8372994592     + #> 6485   2054    3F  CC53 2016 2016-05-02       NO23 -5.5214609179     U #> 6486   2054    3F  CC53 2016 2016-05-02      SALIN  0.3220834992  <NA> #> 6487   2054    3F  CC53 2016 2016-05-02        TKN -0.2107210313  <NA> #> 6488   2054    3F  CC53 2016 2016-05-02         TN 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3F  CC53 2016 2016-07-05      DOSAT  3.9100210028     + #> 6503   2054    3F  CC53 2016 2016-07-05       NO23 -2.5770219387  <NA> #> 6504   2054    3F  CC53 2016 2016-07-05      SALIN -1.5606477483  <NA> #> 6505   2054    3F  CC53 2016 2016-07-05        TKN  0.0953101798  <NA> #> 6506   2054    3F  CC53 2016 2016-07-05         TN  0.1621188495     + #> 6507   2054    3F  CC53 2016 2016-07-05         TP -1.7719568419  <NA> #> 6508   2054    3F  CC53 2016 2016-07-05       TURB  0.9932517730  <NA> #> 6509   2054    3F  CC53 2016 2016-08-01      CHLAC  0.6418538862  <NA> #> 6510   2054    3F  CC53 2016 2016-08-01      COLOR  4.7004803658  <NA> #> 6511   2054    3F  CC53 2016 2016-08-01         DO  1.0331844833  <NA> #> 6512   2054    3F  CC53 2016 2016-08-01      DOSAT  3.6189933266     + #> 6513   2054    3F  CC53 2016 2016-08-01       NO23 -3.8632328413  <NA> #> 6514   2054    3F  CC53 2016 2016-08-01      SALIN -2.6592600369  <NA> #> 6515   2054    3F  CC53 2016 2016-08-01        TKN 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3F  CC53 2016 2016-11-07      CHLAC  2.1041341543  <NA> #> 6530   2054    3F  CC53 2016 2016-11-07      COLOR  4.2341065046  <NA> #> 6531   2054    3F  CC53 2016 2016-11-07         DO  2.2544447177  <NA> #> 6532   2054    3F  CC53 2016 2016-11-07      DOSAT  4.7202829931     + #> 6533   2054    3F  CC53 2016 2016-11-07       NO23 -3.2968373663  <NA> #> 6534   2054    3F  CC53 2016 2016-11-07      SALIN -1.1086626245  <NA> #> 6535   2054    3F  CC53 2016 2016-11-07        TKN  0.0000000000  <NA> #> 6536   2054    3F  CC53 2016 2016-11-07         TN  0.0363319292     + #> 6537   2054    3F  CC53 2016 2016-11-07         TP -2.4191189092  <NA> #> 6538   2054    3F  CC53 2016 2016-11-07       TURB  0.9555114450  <NA> #> 6539   2054    3F  CC53 2016 2016-12-05      CHLAC  2.4849066498  <NA> #> 6540   2054    3F  CC53 2016 2016-12-05      COLOR  3.9702919136  <NA> #> 6541   2054    3F  CC53 2016 2016-12-05         DO  1.5518087996  <NA> #> 6542   2054    3F  CC53 2016 2016-12-05      DOSAT  4.0306945351     + #> 6543   2054    3F  CC53 2016 2016-12-05       NO23 -4.6051701860  <NA> #> 6544   2054    3F  CC53 2016 2016-12-05      SALIN  1.5706970841  <NA> #> 6545   2054    3F  CC53 2016 2016-12-05        TKN  0.0000000000  <NA> #> 6546   2054    3F  CC53 2016 2016-12-05         TN  0.0099503309     + #> 6547   2054    3F  CC53 2016 2016-12-05         TP -1.8325814637  <NA> #> 6548   2054    3F  CC53 2016 2016-12-05       TURB  1.3350010667     A #> 6549   2054    3F  CC53 2017 2017-01-03      CHLAC  2.1633230257  <NA> #> 6550   2054    3F  CC53 2017 2017-01-03      COLOR  3.7841896339     A #> 6551   2054    3F  CC53 2017 2017-01-03         DO  1.5892352051  <NA> #> 6552   2054    3F  CC53 2017 2017-01-03      DOSAT  4.0638853547     + #> 6553   2054    3F  CC53 2017 2017-01-03       NO23 -5.1159958098     I #> 6554   2054    3F  CC53 2017 2017-01-03      SALIN  1.8405496334  <NA> #> 6555   2054    3F  CC53 2017 2017-01-03        TKN -0.3710636814  <NA> #> 6556   2054    3F  CC53 2017 2017-01-03         TN -0.3652833185     + #> 6557   2054    3F  CC53 2017 2017-01-03         TP -1.9661128564  <NA> #> 6558   2054    3F  CC53 2017 2017-01-03       TURB  0.9555114450  <NA> #> 6559   2054    3F  CC53 2017 2017-02-06      CHLAC  1.7047480922  <NA> #> 6560   2054    3F  CC53 2017 2017-02-06      COLOR  3.6635616461  <NA> #> 6561   2054    3F  CC53 2017 2017-02-06         DO  1.3609765531  <NA> #> 6562   2054    3F  CC53 2017 2017-02-06      DOSAT  3.7819143201     + #> 6563   2054    3F  CC53 2017 2017-02-06       NO23 -2.6310891600  <NA> #> 6564   2054    3F  CC53 2017 2017-02-06      SALIN  1.2527629685  <NA> #> 6565   2054    3F  CC53 2017 2017-02-06        TKN -0.2876820725  <NA> #> 6566   2054    3F  CC53 2017 2017-02-06         TN -0.1960148839     + #> 6567   2054    3F  CC53 2017 2017-02-06         TP -2.1202635362  <NA> #> 6568   2054    3F  CC53 2017 2017-02-06       TURB  1.1939224685     A #> 6569   2054    3F  CC53 2017 2017-03-06      CHLAC  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3F  CC53 2017 2017-04-03       NO23 -3.4112477175  <NA> #> 6584   2054    3F  CC53 2017 2017-04-03      SALIN  2.1610215287  <NA> #> 6585   2054    3F  CC53 2017 2017-04-03        TKN -0.0725706928  <NA> #> 6586   2054    3F  CC53 2017 2017-04-03         TN -0.0377018672     + #> 6587   2054    3F  CC53 2017 2017-04-03         TP -1.4271163556  <NA> #> 6588   2054    3F  CC53 2017 2017-04-03       TURB  1.0296194172     A #> 6589   2054    3F  CC53 2017 2017-05-01      CHLAC  2.2512917986  <NA> #> 6590   2054    3F  CC53 2017 2017-05-01      COLOR  4.0253516907     A #> 6591   2054    3F  CC53 2017 2017-05-01         DO  1.1817271954  <NA> #> 6592   2054    3F  CC53 2017 2017-05-01      DOSAT  3.7796338174     + #> 6593   2054    3F  CC53 2017 2017-05-01       NO23 -4.7105307016     I #> 6594   2054    3F  CC53 2017 2017-05-01      SALIN  2.6049094422  <NA> #> 6595   2054    3F  CC53 2017 2017-05-01        TKN  0.5306282511  <NA> #> 6596   2054    3F  CC53 2017 2017-05-01         TN  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3F  CC53 2017 2017-07-10        TKN  0.3364722366  <NA> #> 6611   2054    3F  CC53 2017 2017-07-10         TN  0.4317824164     + #> 6612   2054    3F  CC53 2017 2017-07-10         TP -1.4696759701  <NA> #> 6613   2054    3F  CC53 2017 2017-07-10       TURB  1.1939224685  <NA> #> 6614   2054    3F  CC53 2017 2017-11-06      CHLAC  1.8870696490  <NA> #> 6615   2054    3F  CC53 2017 2017-11-06      COLOR  4.9416424226  <NA> #> 6616   2054    3F  CC53 2017 2017-11-06         DO  1.5973653312  <NA> #> 6617   2054    3F  CC53 2017 2017-11-06      DOSAT  4.0621656639  <NA> #> 6618   2054    3F  CC53 2017 2017-11-06       NO23 -1.3470736480  <NA> #> 6619   2054    3F  CC53 2017 2017-11-06      SALIN -1.4696759701  <NA> #> 6620   2054    3F  CC53 2017 2017-11-06        TKN  0.0953101798  <NA> #> 6621   2054    3F  CC53 2017 2017-11-06         TN  0.3074846997     + #> 6622   2054    3F  CC53 2017 2017-11-06         TP -2.0402208285  <NA> #> 6623   2054    3F  CC53 2017 2017-11-06       TURB  1.3609765531  <NA> #> 6624   2054    3F  CC53 2017 2017-12-04      CHLAC  2.7080502011  <NA> #> 6625   2054    3F  CC53 2017 2017-12-04      COLOR  4.2341065046  <NA> #> 6626   2054    3F  CC53 2017 2017-12-04         DO  1.7422190237  <NA> #> 6627   2054    3F  CC53 2017 2017-12-04      DOSAT  4.1759245492  <NA> #> 6628   2054    3F  CC53 2017 2017-12-04       NO23 -1.6094379124  <NA> #> 6629   2054    3F  CC53 2017 2017-12-04      SALIN -0.7133498879  <NA> #> 6630   2054    3F  CC53 2017 2017-12-04        TKN -0.0202027073  <NA> #> 6631   2054    3F  CC53 2017 2017-12-04         TN  0.1655144385     + #> 6632   2054    3F  CC53 2017 2017-12-04         TP -2.0402208285  <NA> #> 6633   2054    3F  CC53 2017 2017-12-04       TURB  1.2809338455     A #> 6634   2054    3F  CC53 2018 2018-01-02      CHLAC  3.2188758249  <NA> #> 6635   2054    3F  CC53 2018 2018-01-02      COLOR  4.0253516907  <NA> #> 6636   2054    3F  CC53 2018 2018-01-02         DO  1.7298840655  <NA> #> 6637   2054    3F  CC53 2018 2018-01-02      DOSAT  4.0758410907     + #> 6638   2054    3F  CC53 2018 2018-01-02       NO23 -2.0402208285  <NA> #> 6639   2054    3F  CC53 2018 2018-01-02      SALIN -0.8915981193  <NA> #> 6640   2054    3F  CC53 2018 2018-01-02        TKN  0.0000000000  <NA> #> 6641   2054    3F  CC53 2018 2018-01-02         TN  0.1222176327     + #> 6642   2054    3F  CC53 2018 2018-01-02         TP -1.9661128564  <NA> #> 6643   2054    3F  CC53 2018 2018-01-02       TURB  1.8245492921  <NA> #> 6644   2054    3F  CC53 2018 2018-02-05      CHLAC  3.5263605246  <NA> #> 6645   2054    3F  CC53 2018 2018-02-05      COLOR  4.2484952420  <NA> #> 6646   2054    3F  CC53 2018 2018-02-05         DO  1.9712993831  <NA> #> 6647   2054    3F  CC53 2018 2018-02-05      DOSAT  4.3681812279  <NA> #> 6648   2054    3F  CC53 2018 2018-02-05       NO23 -0.9416085399  <NA> #> 6649   2054    3F  CC53 2018 2018-02-05      SALIN -0.9416085399  <NA> #> 6650   2054    3F  CC53 2018 2018-02-05        TKN  0.1823215568  <NA> #> 6651   2054    3F  CC53 2018 2018-02-05         TN  0.4637340162     + #> 6652   2054    3F  CC53 2018 2018-02-05         TP -1.7719568419  <NA> #> 6653   2054    3F  CC53 2018 2018-02-05       TURB  1.8870696490  <NA> #> 6654   2054    3F  CC53 2018 2018-05-07      CHLAC  2.6390573296  <NA> #> 6655   2054    3F  CC53 2018 2018-05-07      COLOR  3.9318256327  <NA> #> 6656   2054    3F  CC53 2018 2018-05-07         DO  1.3217558400  <NA> #> 6657   2054    3F  CC53 2018 2018-05-07      DOSAT  3.8877303129  <NA> #> 6658   2054    3F  CC53 2018 2018-05-07       NO23 -5.1159958098     I #> 6659   2054    3F  CC53 2018 2018-05-07      SALIN  1.9974177062  <NA> #> 6660   2054    3F  CC53 2018 2018-05-07        TKN -0.0100503359  <NA> #> 6661   2054    3F  CC53 2018 2018-05-07         TN -0.0060180723     + #> 6662   2054    3F  CC53 2018 2018-05-07         TP -1.3862943611  <NA> #> 6663   2054    3F  CC53 2018 2018-05-07       TURB  1.1939224685  <NA> #> 6664   2054    3F  CC53 2018 2018-07-09      CHLAC  0.9162907319  <NA> #> 6665   2054    3F  CC53 2018 2018-07-09      COLOR  5.0106352941  <NA> #> 6666   2054    3F  CC53 2018 2018-07-09         DO  1.3532545070  <NA> #> 6667   2054    3F  CC53 2018 2018-07-09      DOSAT  3.9435216725  <NA> #> 6668   2054    3F  CC53 2018 2018-07-09       NO23 -4.3428059215  <NA> #> 6669   2054    3F  CC53 2018 2018-07-09      SALIN -3.2188758249  <NA> #> 6670   2054    3F  CC53 2018 2018-07-09        TKN  0.0953101798  <NA> #> 6671   2054    3F  CC53 2018 2018-07-09         TN  0.1070590723     + #> 6672   2054    3F  CC53 2018 2018-07-09         TP -2.5510464523  <NA> #> 6673   2054    3F  CC53 2018 2018-07-09       TURB  0.9555114450  <NA> #> 6674   2054    3F  CC53 2019 2019-02-04      CHLAC  1.2527629685  <NA> #> 6675   2054    3F  CC53 2019 2019-02-04      COLOR  4.2766661190  <NA> #> 6676   2054    3F  CC53 2019 2019-02-04         DO  1.7011051010  <NA> #> 6677   2054    3F  CC53 2019 2019-02-04      DOSAT  4.0976723523  <NA> #> 6678   2054    3F  CC53 2019 2019-02-04       NO23 -0.8439700703  <NA> #> 6679   2054    3F  CC53 2019 2019-02-04      SALIN -1.1394342832  <NA> #> 6680   2054    3F  CC53 2019 2019-02-04        TKN  0.2623642645  <NA> #> 6681   2054    3F  CC53 2019 2019-02-04         TN  0.5481214085     + #> 6682   2054    3F  CC53 2019 2019-02-04         TP -2.0402208285  <NA> #> 6683   2054    3F  CC53 2019 2019-02-04       TURB  1.4350845253  <NA> #> 6684   2054    3F  CC53 2019 2019-03-04      CHLAC  3.4657359028  <NA> #> 6685   2054    3F  CC53 2019 2019-03-04      COLOR  4.3040650932  <NA> #> 6686   2054    3F  CC53 2019 2019-03-04         DO  1.8115620965  <NA> #> 6687   2054    3F  CC53 2019 2019-03-04      DOSAT  4.2986450257  <NA> #> 6688   2054    3F  CC53 2019 2019-03-04       NO23 -2.9759296463  <NA> #> 6689   2054    3F  CC53 2019 2019-03-04      SALIN -1.1711829815  <NA> #> 6690   2054    3F  CC53 2019 2019-03-04        TKN  0.1823215568  <NA> #> 6691   2054    3F  CC53 2019 2019-03-04         TN  0.2239432315     + #> 6692   2054    3F  CC53 2019 2019-03-04         TP -2.2072749132  <NA> #> 6693   2054    3F  CC53 2019 2019-03-04       TURB  2.0918640617  <NA> #> 6694   2054    3F  CC53 2019 2019-04-01      CHLAC  2.0794415417  <NA> #> 6695   2054    3F  CC53 2019 2019-04-01      COLOR  4.1896547420  <NA> #> 6696   2054    3F  CC53 2019 2019-04-01         DO  1.6074359098  <NA> #> 6697   2054    3F  CC53 2019 2019-04-01      DOSAT  4.0775374439  <NA> #> 6698   2054    3F  CC53 2019 2019-04-01       NO23 -4.8283137373     I #> 6699   2054    3F  CC53 2019 2019-04-01      SALIN -0.9675840263  <NA> #> 6700   2054    3F  CC53 2019 2019-04-01        TKN  0.0000000000  <NA> #> 6701   2054    3F  CC53 2019 2019-04-01         TN  0.0039920213     + #> 6702   2054    3F  CC53 2019 2019-04-01         TP -2.3434070875  <NA> #> 6703   2054    3F  CC53 2019 2019-04-01       TURB  1.0986122887  <NA> #> 6704   2054    3F  CC53 2019 2019-05-06      CHLAC  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3F  CC53 2019 2019-08-05       NO23 -2.3859667019  <NA> #> 6719   2054    3F  CC53 2019 2019-08-05      SALIN -1.7719568419  <NA> #> 6720   2054    3F  CC53 2019 2019-08-05        TKN  0.4700036292  <NA> #> 6721   2054    3F  CC53 2019 2019-08-05         TN  0.5259112612     + #> 6722   2054    3F  CC53 2019 2019-08-05         TP -1.3862943611  <NA> #> 6723   2054    3F  CC53 2019 2019-08-05       TURB  0.9162907319  <NA> #> 6724   2054    3F  CC53 2020 2020-01-06      CHLAC  1.8405496334  <NA> #> 6725   2054    3F  CC53 2020 2020-01-06      COLOR  3.8712010109     A #> 6726   2054    3F  CC53 2020 2020-01-06         DO  1.7439688054  <NA> #> 6727   2054    3F  CC53 2020 2020-01-06      DOSAT  4.1255201797  <NA> #> 6728   2054    3F  CC53 2020 2020-01-06       NO23 -2.8824035882  <NA> #> 6729   2054    3F  CC53 2020 2020-01-06      SALIN -0.5276327421  <NA> #> 6730   2054    3F  CC53 2020 2020-01-06        TKN -0.4155154440  <NA> #> 6731   2054    3F  CC53 2020 2020-01-06         TN 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3F  CC53 2020 2020-03-02      COLOR  3.8501476017  <NA> #> 6746   2054    3F  CC53 2020 2020-03-02         DO  1.9657127764  <NA> #> 6747   2054    3F  CC53 2020 2020-03-02      DOSAT  4.3451032806  <NA> #> 6748   2054    3F  CC53 2020 2020-03-02       NO23 -5.5214609179     U #> 6749   2054    3F  CC53 2020 2020-03-02      SALIN -0.5621189182  <NA> #> 6750   2054    3F  CC53 2020 2020-03-02        TKN  0.0000000000  <NA> #> 6751   2054    3F  CC53 2020 2020-03-02         TN  0.0019980027     + #> 6752   2054    3F  CC53 2020 2020-03-02         TP -1.9661128564  <NA> #> 6753   2054    3F  CC53 2020 2020-03-02       TURB  1.4816045409     A #> 6754   2054    3F  CC53 2020 2020-09-08      CHLAC  0.8754687374     I #> 6755   2054    3F  CC53 2020 2020-09-08      COLOR  5.5214609179  <NA> #> 6756   2054    3F  CC53 2020 2020-09-08         DO  1.5325568681  <NA> #> 6757   2054    3F  CC53 2020 2020-09-08      DOSAT  4.0621656639  <NA> #> 6758   2054    3F  CC53 2020 2020-09-08       NO23 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3F  CC53 2020 2020-12-07         TP -2.0402208285  <NA> #> 6773   2054    3F  CC53 2020 2020-12-07       TURB  0.8754687374  <NA> #> 6774   2054    3F  CC53 2021 2021-01-04      CHLAC  1.6863989536  <NA> #> 6775   2054    3F  CC53 2021 2021-01-04      COLOR  4.4773368145     A #> 6776   2054    3F  CC53 2021 2021-01-04         DO  1.7766458314  <NA> #> 6777   2054    3F  CC53 2021 2021-01-04      DOSAT  4.1866198383  <NA> #> 6778   2054    3F  CC53 2021 2021-01-04       NO23 -2.2072749132  <NA> #> 6779   2054    3F  CC53 2021 2021-01-04      SALIN -1.3470736480  <NA> #> 6780   2054    3F  CC53 2021 2021-01-04         TN  0.1906203596     + #> 6781   2054    3F  CC53 2021 2021-01-04         TP -2.3025850930  <NA> #> 6782   2054    3F  CC53 2021 2021-01-04       TURB  0.9932517730  <NA> #> 6783   2054    3F  CC53 2021 2021-02-01      CHLAC  2.6390573296  <NA> #> 6784   2054    3F  CC53 2021 2021-02-01      COLOR  4.2046926194     A #> 6785   2054    3F  CC53 2021 2021-02-01         DO  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3F  CC53 2021 2021-03-01        TKN  0.0953101798  <NA> #> 6800   2054    3F  CC53 2021 2021-03-01         TN  0.0971267107     + #> 6801   2054    3F  CC53 2021 2021-03-01         TP -2.0402208285  <NA> #> 6802   2054    3F  CC53 2021 2021-03-01       TURB  1.2237754316  <NA> #> 6803   2054    3F  CC53 2021 2021-04-05      CHLAC  1.7047480922  <NA> #> 6804   2054    3F  CC53 2021 2021-04-05      COLOR  3.9889840466     A #> 6805   2054    3F  CC53 2021 2021-04-05       NO23 -5.5214609179     I #> 6806   2054    3F  CC53 2021 2021-04-05      SALIN  0.9122827105  <NA> #> 6807   2054    3F  CC53 2021 2021-04-05        TKN -0.2484613593  <NA> #> 6808   2054    3F  CC53 2021 2021-04-05         TN -0.2433462586     + #> 6809   2054    3F  CC53 2021 2021-04-05         TP -1.8971199849  <NA> #> 6810   2054    3F  CC53 2021 2021-04-05       TURB  0.8754687374  <NA> #> 6811   2054    3F  CC53 2021 2021-05-03      CHLAC  1.4350845253  <NA> #> 6812   2054    3F  CC53 2021 2021-05-03      COLOR  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3F  CC53 2021 2021-06-07      SALIN  1.9300710850  <NA> #> 6827   2054    3F  CC53 2021 2021-06-07        TKN -0.0833816089  <NA> #> 6828   2054    3F  CC53 2021 2021-06-07         TN -0.0418642041     + #> 6829   2054    3F  CC53 2021 2021-06-07         TP -1.1711829815  <NA> #> 6830   2054    3F  CC53 2021 2021-06-07       TURB  0.6931471806  <NA> #> 6831   2054    3F  CC53 2021 2021-08-02      CHLAC  1.8870696490  <NA> #> 6832   2054    3F  CC53 2021 2021-08-02      COLOR  5.0106352941  <NA> #> 6833   2054    3F  CC53 2021 2021-08-02         DO  0.9669838462  <NA> #> 6834   2054    3F  CC53 2021 2021-08-02      DOSAT  3.5467396870  <NA> #> 6835   2054    3F  CC53 2021 2021-08-02       NO23 -3.5065578973  <NA> #> 6836   2054    3F  CC53 2021 2021-08-02      SALIN -1.4271163556  <NA> #> 6837   2054    3F  CC53 2021 2021-08-02        TKN  0.4054651081  <NA> #> 6838   2054    3F  CC53 2021 2021-08-02         TN  0.4252677354     + #> 6839   2054    3F  CC53 2021 2021-08-02         TP 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3F  CC53 2021 2021-10-04         DO  1.0296194172  <NA> #> 6854   2054    3F  CC53 2021 2021-10-04      DOSAT  3.5524868292  <NA> #> 6855   2054    3F  CC53 2021 2021-10-04       NO23 -2.9004220937  <NA> #> 6856   2054    3F  CC53 2021 2021-10-04      SALIN -2.0402208285  <NA> #> 6857   2054    3F  CC53 2021 2021-10-04        TKN -0.0725706928  <NA> #> 6858   2054    3F  CC53 2021 2021-10-04         TN -0.0151136378     + #> 6859   2054    3F  CC53 2021 2021-10-04         TP -1.7719568419  <NA> #> 6860   2054    3F  CC53 2021 2021-10-04       TURB  0.7419373447     A #> 6861   2054    3F  CC53 2021 2021-11-01      CHLAC  2.1282317058  <NA> #> 6862   2054    3F  CC53 2021 2021-11-01      COLOR  4.2766661190  <NA> #> 6863   2054    3F  CC53 2021 2021-11-01         DO  1.0681530812  <NA> #> 6864   2054    3F  CC53 2021 2021-11-01      DOSAT  3.5322256441  <NA> #> 6865   2054    3F  CC53 2021 2021-11-01       NO23 -2.6450754019  <NA> #> 6866   2054    3F  CC53 2021 2021-11-01      SALIN 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3F  CC53 2022 2022-01-03         DO  1.3402504226  <NA> #> 6881   2054    3F  CC53 2022 2022-01-03      DOSAT  3.8286413965  <NA> #> 6882   2054    3F  CC53 2022 2022-01-03       NO23 -4.1997050779  <NA> #> 6883   2054    3F  CC53 2022 2022-01-03      SALIN  1.3376291891  <NA> #> 6884   2054    3F  CC53 2022 2022-01-03        TKN -0.1053605157  <NA> #> 6885   2054    3F  CC53 2022 2022-01-03         TN -0.0888312137     + #> 6886   2054    3F  CC53 2022 2022-01-03         TP -1.7719568419  <NA> #> 6887   2054    3F  CC53 2022 2022-01-03       TURB  0.6418538862  <NA> #> 6888   2054    3F  CC53 2022 2022-02-07      CHLAC  2.2082744135  <NA> #> 6889   2054    3F  CC53 2022 2022-02-07      COLOR  3.8286413965  <NA> #> 6890   2054    3F  CC53 2022 2022-02-07         DO  1.7047480922  <NA> #> 6891   2054    3F  CC53 2022 2022-02-07      DOSAT  4.1541845626  <NA> #> 6892   2054    3F  CC53 2022 2022-02-07       NO23 -4.9618451299     I #> 6893   2054    3F  CC53 2022 2022-02-07      SALIN  1.3270750015  <NA> #> 6894   2054    3F  CC53 2022 2022-02-07        TKN -0.1863295782  <NA> #> 6895   2054    3F  CC53 2022 2022-02-07         TN -0.1815218766     + #> 6896   2054    3F  CC53 2022 2022-02-07         TP -1.8325814637  <NA> #> 6897   2054    3F  CC53 2022 2022-02-07       TURB  1.2237754316  <NA> #> 6898   2054    3F  CC53 2022 2022-03-07      CHLAC  2.3025850930  <NA> #> 6899   2054    3F  CC53 2022 2022-03-07      COLOR  3.8066624898     A #> 6900   2054    3F  CC53 2022 2022-03-07       NO23 -5.2983173665     I #> 6901   2054    3F  CC53 2022 2022-03-07        TKN -0.1278333715  <NA> #> 6902   2054    3F  CC53 2022 2022-03-07         TN -0.1232982163     + #> 6903   2054    3F  CC53 2022 2022-03-07         TP -1.6094379124  <NA> #> 6904   2054    3F  CC53 2022 2022-03-07       TURB  1.0296194172  <NA> #> 6905   2054    3F  CC53 2022 2022-04-04      CHLAC  2.7725887222  <NA> #> 6906   2054    3F  CC53 2022 2022-04-04      COLOR  3.9702919136     A #> 6907   2054    3F  CC53 2022 2022-04-04         DO  1.1908875648  <NA> #> 6908   2054    3F  CC53 2022 2022-04-04      DOSAT  3.7208625000  <NA> #> 6909   2054    3F  CC53 2022 2022-04-04       NO23 -4.1997050779  <NA> #> 6910   2054    3F  CC53 2022 2022-04-04      SALIN  2.1860512767  <NA> #> 6911   2054    3F  CC53 2022 2022-04-04        TKN -0.3147107448  <NA> #> 6912   2054    3F  CC53 2022 2022-04-04         TN -0.2943710606     + #> 6913   2054    3F  CC53 2022 2022-04-04         TP -1.2378743560  <NA> #> 6914   2054    3F  CC53 2022 2022-04-04       TURB  1.0296194172  <NA> #> 6915   2054    3F  CC53 2022 2022-05-02      CHLAC  2.4849066498  <NA> #> 6916   2054    3F  CC53 2022 2022-05-02      COLOR  4.0073331852  <NA> #> 6917   2054    3F  CC53 2022 2022-05-02       NO23 -3.9120230054  <NA> #> 6918   2054    3F  CC53 2022 2022-05-02      SALIN  2.5152741864  <NA> #> 6919   2054    3F  CC53 2022 2022-05-02        TKN  0.0953101798  <NA> #> 6920   2054    3F  CC53 2022 2022-05-02         TN  0.1133286853     + #> 6921   2054    3F  CC53 2022 2022-05-02         TP -1.1394342832  <NA> #> 6922   2054    3F  CC53 2022 2022-05-02       TURB  1.0986122887  <NA> #> 6923   2054    3F  CC53 2022 2022-12-05      CHLAC  1.6094379124  <NA> #> 6924   2054    3F  CC53 2022 2022-12-05      COLOR  4.7004803658  <NA> #> 6925   2054    3F  CC53 2022 2022-12-05       NO23 -1.4696759701  <NA> #> 6926   2054    3F  CC53 2022 2022-12-05      SALIN -1.3862943611  <NA> #> 6927   2054    3F  CC53 2022 2022-12-05        TKN -0.0833816089  <NA> #> 6928   2054    3F  CC53 2022 2022-12-05         TN  0.1397619424     + #> 6929   2054    3F  CC53 2022 2022-12-05         TP -1.8971199849  <NA> #> 6930   2054    3F  CC53 2022 2022-12-05       TURB  1.3350010667  <NA> #> 6931   2054    3F  CC53 2023 2023-01-03      CHLAC  2.3978952728  <NA> #> 6932   2054    3F  CC53 2023 2023-01-03      COLOR  4.2484952420     A #> 6933   2054    3F  CC53 2023 2023-01-03         DO  2.1090003439  <NA> #> 6934   2054    3F  CC53 2023 2023-01-03      DOSAT  4.5261269786  <NA> #> 6935   2054    3F  CC53 2023 2023-01-03       NO23 -1.4271163556  <NA> #> 6936   2054    3F  CC53 2023 2023-01-03      SALIN -1.1086626245  <NA> #> 6937   2054    3F  CC53 2023 2023-01-03        TKN -0.1625189295  <NA> #> 6938   2054    3F  CC53 2023 2023-01-03         TN  0.0861776962     + #> 6939   2054    3F  CC53 2023 2023-01-03         TP -2.3025850930  <NA> #> 6940   2054    3F  CC53 2023 2023-01-03       TURB  0.7884573604  <NA> #> 6941   2054    3F  CC53 2023 2023-02-06      CHLAC  3.4965075615  <NA> #> 6942   2054    3F  CC53 2023 2023-02-06      COLOR  4.0253516907  <NA> #> 6943   2054    3F  CC53 2023 2023-02-06         DO  1.9740810260  <NA> #> 6944   2054    3F  CC53 2023 2023-02-06      DOSAT  4.3919769655  <NA> #> 6945   2054    3F  CC53 2023 2023-02-06       NO23 -5.2983173665     I #> 6946   2054    3F  CC53 2023 2023-02-06      SALIN -0.4780358009  <NA> #> 6947   2054    3F  CC53 2023 2023-02-06        TKN  0.0953101798  <NA> #> 6948   2054    3F  CC53 2023 2023-02-06         TN  0.0989399479     + #> 6949   2054    3F  CC53 2023 2023-02-06         TP -1.8325814637  <NA> #> 6950   2054    3F  CC53 2023 2023-02-06       TURB  1.6863989536  <NA> #> 6951   2054    3F  CC53 2023 2023-03-06         DO  1.5623463049  <NA> #> 6952   2054    3F  CC53 2023 2023-03-06      DOSAT  4.0253516907  <NA> #> 6953   2054    3F  CC53 2023 2023-03-06      SALIN  0.8501509294  <NA> #> 6954   2054    3F  CC53 2014 2014-04-07      CHLAC  1.0986122887  <NA> #> 6955   2054    3F  CC53 2014 2014-04-07      COLOR  5.0751738152  <NA> #> 6956   2054    3F  CC53 2014 2014-04-07       COND  7.1701195434  <NA> #> 6957   2054    3F  CC53 2014 2014-04-07         DO  1.7029282555  <NA> #> 6958   2054    3F  CC53 2014 2014-04-07      DOSAT  4.0976723523  <NA> #> 6959   2054    3F  CC53 2014 2014-04-07       NO23 -3.1700856607  <NA> #> 6960   2054    3F  CC53 2014 2014-04-07      SALIN -0.3566749439     + #> 6961   2054    3F  CC53 2014 2014-04-07        TKN  0.6418538862  <NA> #> 6962   2054    3F  CC53 2014 2014-04-07         TN  0.6637183699     + #> 6963   2054    3F  CC53 2014 2014-04-07         TP  0.0953101798  <NA> #> 6964   2054    3F  CC53 2014 2014-04-07        TSS  2.9444389792  <NA> #> 6965   2054    3F  CC53 2014 2014-04-07       TURB  2.7725887222  <NA> #> 6966   2054    3F  CC53 2015 2015-05-21       COND  7.9291264873  <NA> #> 6967   2054    3F  CC53 2015 2015-05-21         DO  1.4109869737  <NA> #> 6968   2054    3F  CC53 2015 2015-05-21      DOSAT  3.9702919136  <NA> #> 6969   2054    3F  CC53 2015 2015-05-21      SALIN  0.2851789422     + #> 6970   2054    3F  CC53 2015 2015-07-15       COND  6.5439118456  <NA> #> 6971   2054    3F  CC53 2015 2015-07-15       COND  6.5453496603  <NA> #> 6972   2054    3F  CC53 2015 2015-07-15      SALIN -1.1711829815     + #> 6973   2054    3F  CC53 2015 2015-08-06       COND  4.9052747784  <NA> #> 6974   2054    3F  CC53 2015 2015-08-06         DO  1.4109869737  <NA> #> 6975   2054    3F  CC53 2015 2015-08-06      DOSAT  3.9702919136  <NA> #> 6976   2054    3F  CC53 2015 2015-08-19       COND  4.8751973232  <NA> #> 6977   2054    3F  CC53 2015 2015-08-19         DO  1.2527629685  <NA> #> 6978   2054    3F  CC53 2015 2015-08-19      DOSAT  3.8501476017  <NA> #> 6979   2054    3F  CC53 2015 2015-09-15       COND  5.4764635519  <NA> #> 6980   2054    3F  CC53 2015 2015-09-15         DO  1.1314021115  <NA> #> 6981   2054    3F  CC53 2015 2015-09-15      DOSAT  3.6888794541  <NA> #> 6982   2054    3F  CC53 2015 2015-09-15      SALIN -2.2072749132     + #> 6983   2054    3F  CC53 2015 2015-09-15       COND  5.4764635519  <NA> #> 6984   2054    3F  CC53 2015 2015-09-15         DO  1.0986122887  <NA> #> 6985   2054    3F  CC53 2015 2015-09-15      DOSAT  3.6635616461  <NA> #> 6986   2054    3F  CC53 2015 2015-09-15      SALIN -2.2072749132     + #> 6987   2054    3F  CC53 2015 2015-11-25       COND  6.2225762681  <NA> #> 6988   2054    3F  CC53 2015 2015-11-25         DO  1.7047480922  <NA> #> 6989   2054    3F  CC53 2015 2015-11-25      DOSAT  4.1431347264  <NA> #> 6990   2054    3F  CC53 2015 2015-11-25      SALIN -1.3470736480     + #> 6991   2054    3F  CC53 2015 2015-11-25       COND  6.2285110036  <NA> #> 6992   2054    3F  CC53 2015 2015-11-25         DO  1.6863989536  <NA> #> 6993   2054    3F  CC53 2015 2015-11-25      DOSAT  4.1431347264  <NA> #> 6994   2054    3F  CC53 2015 2015-11-25      SALIN -1.3470736480     + #> 6995   2054    3F  CC53 2021 2021-02-02       COND  7.0184017991  <NA> #> 6996   2054    3F  CC53 2021 2021-02-02         DO  1.9183921202  <NA> #> 6997   2054    3F  CC53 2021 2021-02-02      DOSAT  4.2822062994  <NA> #> 6998   2054    3F  CC53 2021 2021-02-02      SALIN -0.5798184953  <NA> #> 6999   2054    3F  CC53 2021 2021-03-16       COND  7.8504931809  <NA> #> 7000   2054    3F  CC53 2021 2021-03-16         DO  1.7783364489  <NA> #> 7001   2054    3F  CC53 2021 2021-03-16      DOSAT  4.2527717988  <NA> #> 7002   2054    3F  CC53 2021 2021-03-16      SALIN  0.2776317366  <NA> #> 7003   2054    3F  CC53 2021 2021-09-30       COND  4.8880909413  <NA> #> 7004   2054    3F  CC53 2021 2021-09-30         DO  1.3532545070  <NA> #> 7005   2054    3F  CC53 2021 2021-09-30      DOSAT  3.8774315607  <NA> #> 7006   2054    3F  CC53 2021 2021-09-30      SALIN -2.8134107168  <NA> #> 7007   2054    3F  CC53 2021 2021-09-30       COND  4.8797670189  <NA> #> 7008   2054    3F  CC53 2021 2021-09-30         DO  1.2412685891  <NA> #> 7009   2054    3F  CC53 2021 2021-09-30      DOSAT  3.7750571504  <NA> #> 7010   2054    3F  CC53 2021 2021-09-30      SALIN -2.8134107168  <NA> #> 7011   2054    3F  CC53 2021 2021-10-27       COND  6.5250296578  <NA> #> 7012   2054    3F  CC53 2021 2021-10-27         DO  1.5195132049  <NA> #> 7013   2054    3F  CC53 2021 2021-10-27      DOSAT  4.0412953411  <NA> #> 7014   2054    3F  CC53 2021 2021-10-27      SALIN -1.1086626245  <NA> #> 7015   2054    3F  CC53 2021 2021-10-27       COND  6.5264948596  <NA> #> 7016   2054    3F  CC53 2021 2021-10-27         DO  1.5129270121  <NA> #> 7017   2054    3F  CC53 2021 2021-10-27      DOSAT  4.0342406382  <NA> #> 7018   2054    3F  CC53 2021 2021-10-27      SALIN -1.1086626245  <NA> #> 7019   2054    3F  CC53 2021 2021-11-18       COND  4.7104306966  <NA> #> 7020   2054    3F  CC53 2021 2021-11-18         DO  1.8578592709  <NA> #> 7021   2054    3F  CC53 2021 2021-11-18      DOSAT  4.2682978693  <NA> #> 7022   2054    3F  CC53 2021 2021-11-18      SALIN -2.9957322736  <NA> #> 7023   2059    3M  CC55 2015 2015-05-21       COND  9.9007337643  <NA> #> 7024   2059    3M  CC55 2015 2015-05-21         DO  1.2237754316  <NA> #> 7025   2059    3M  CC55 2015 2015-05-21      DOSAT  3.8286413965  <NA> #> 7026   2059    3M  CC55 2015 2015-05-21      SALIN  2.4105422345     + #> 7027   2059    3M  CC55 2015 2015-07-15       COND  6.7190131544  <NA> #> 7028   2059    3M  CC55 2015 2015-07-15      SALIN -0.9416085399     + #> 7029   2059    3M  CC55 2015 2015-08-06       COND  6.4019171967  <NA> #> 7030   2059    3M  CC55 2015 2015-08-06         DO  1.6292405397  <NA> #> 7031   2059    3M  CC55 2015 2015-08-06      DOSAT  4.1896547420  <NA> #> 7032   2059    3M  CC55 2015 2015-08-06      SALIN -1.3093333200     + #> 7033   2059    3M  CC55 2015 2015-08-19       COND  6.2785214242  <NA> #> 7034   2059    3M  CC55 2015 2015-08-19         DO  1.6094379124  <NA> #> 7035   2059    3M  CC55 2015 2015-08-19      DOSAT  4.1431347264  <NA> #> 7036   2059    3M  CC55 2015 2015-08-19      SALIN -1.3862943611     + #> 7037   2059    3M  CC55 2015 2015-09-15       COND  6.2205901701  <NA> #> 7038   2059    3M  CC55 2015 2015-09-15         DO  1.4816045409  <NA> #> 7039   2059    3M  CC55 2015 2015-09-15      DOSAT  4.0073331852  <NA> #> 7040   2059    3M  CC55 2015 2015-09-15      SALIN -1.4271163556     + #> 7041   2059    3M  CC55 2015 2015-10-08      CHLAC  0.2623642645     I #> 7042   2059    3M  CC55 2015 2015-10-08       COND  6.3969296552  <NA> #> 7043   2059    3M  CC55 2015 2015-10-08         DO  1.6486586256  <NA> #> 7044   2059    3M  CC55 2015 2015-10-08      DOSAT  4.2046926194  <NA> #> 7045   2059    3M  CC55 2015 2015-10-08       NO23 -2.7646205526  <NA> #> 7046   2059    3M  CC55 2015 2015-10-08      SALIN -1.2378743560     + #> 7047   2059    3M  CC55 2015 2015-10-08        TKN -0.1625189295  <NA> #> 7048   2059    3M  CC55 2015 2015-10-08         TN -0.0910193984     + #> 7049   2059    3M  CC55 2015 2015-10-08         TP -2.6310891600  <NA> #> 7050   2059    3M  CC55 2015 2015-10-08        TSS  1.9459101491     I #> 7051   2059    3M  CC55 2015 2015-10-08       TURB  2.0794415417  <NA> #> 7052   2059    3M  CC55 2015 2015-11-05      CHLAC  0.5877866649  <NA> #> 7053   2059    3M  CC55 2015 2015-11-05       COND  6.6982680541  <NA> #> 7054   2059    3M  CC55 2015 2015-11-05         DO  1.9600947840  <NA> #> 7055   2059    3M  CC55 2015 2015-11-05      DOSAT  4.4773368145  <NA> #> 7056   2059    3M  CC55 2015 2015-11-05      SALIN -0.9416085399     + #> 7057   2059    3M  CC55 2015 2015-11-05         TN -0.0693500781     + #> 7058   2059    3M  CC55 2015 2015-11-05        TSS  1.7917594692     I #> 7059   2059    3M  CC55 2015 2015-11-05       TURB  2.2721258855  <NA> #> 7060   2059    3M  CC55 2015 2015-11-25       COND  6.7007311095  <NA> #> 7061   2059    3M  CC55 2015 2015-11-25         DO  2.0014800002  <NA> #> 7062   2059    3M  CC55 2015 2015-11-25      DOSAT  4.4188406078  <NA> #> 7063   2059    3M  CC55 2015 2015-11-25      SALIN -0.8209805521     + #> 7064   2059    3M  CC55 2015 2015-12-03      CHLAC  0.5306282511  <NA> #> 7065   2059    3M  CC55 2015 2015-12-03      COLOR  4.7004803658  <NA> #> 7066   2059    3M  CC55 2015 2015-12-03       COND  6.8448154792  <NA> #> 7067   2059    3M  CC55 2015 2015-12-03         DO  1.8900953699  <NA> #> 7068   2059    3M  CC55 2015 2015-12-03      DOSAT  4.3694478525  <NA> #> 7069   2059    3M  CC55 2015 2015-12-03       NO23 -2.7488721956  <NA> #> 7070   2059    3M  CC55 2015 2015-12-03      SALIN -0.7550225843     + #> 7071   2059    3M  CC55 2015 2015-12-03        TKN -0.2357223335  <NA> #> 7072   2059    3M  CC55 2015 2015-12-03         TN -0.1578240852     + #> 7073   2059    3M  CC55 2015 2015-12-03         TP -2.8647040111  <NA> #> 7074   2059    3M  CC55 2015 2015-12-03        TSS  1.3862943611     I #> 7075   2059    3M  CC55 2015 2015-12-03       TURB  2.1282317058  <NA> #> 7076   2059    3M  CC55 2015 2015-05-21       COND  7.3472997007  <NA> #> 7077   2059    3M  CC55 2015 2015-05-21         DO  0.9932517730  <NA> #> 7078   2059    3M  CC55 2015 2015-05-21      DOSAT  3.4657359028  <NA> #> 7079   2059    3M  CC55 2015 2015-05-21      SALIN -0.3285040670     + #> 7080   2059    3M  CC55 2015 2015-07-15       COND  9.6044074351  <NA> #> 7081   2059    3M  CC55 2015 2015-08-06       COND  6.4068799861  <NA> #> 7082   2059    3M  CC55 2015 2015-08-06         DO  1.6486586256  <NA> #> 7083   2059    3M  CC55 2015 2015-08-06      DOSAT  4.2195077052  <NA> #> 7084   2059    3M  CC55 2015 2015-08-06      SALIN -1.3093333200     + #> 7085   2059    3M  CC55 2015 2015-08-19       COND  6.2653012127  <NA> #> 7086   2059    3M  CC55 2015 2015-08-19         DO  1.3862943611  <NA> #> 7087   2059    3M  CC55 2015 2015-08-19      DOSAT  4.0604430105  <NA> #> 7088   2059    3M  CC55 2015 2015-08-19      SALIN -1.4271163556     + #> 7089   2059    3M  CC55 2015 2015-09-15       COND  6.2519038832  <NA> #> 7090   2059    3M  CC55 2015 2015-09-15         DO  1.6863989536  <NA> #> 7091   2059    3M  CC55 2015 2015-09-15      DOSAT  4.1271343850  <NA> #> 7092   2059    3M  CC55 2015 2015-09-15      SALIN -1.4271163556     + #> 7093   2059    3M  CC55 2015 2015-11-25       COND  8.4348979487  <NA> #> 7094   2059    3M  CC55 2015 2015-11-25         DO -0.1053605157  <NA> #> 7095   2059    3M  CC55 2015 2015-11-25      DOSAT  2.3025850930  <NA> #> 7096   2059    3M  CC55 2015 2015-11-25      SALIN  1.0152306797     + #> 7097   2059    3M  CC56 2015 2015-05-21       COND  9.6019769721  <NA> #> 7098   2059    3M  CC56 2015 2015-05-21         DO  0.6931471806  <NA> #> 7099   2059    3M  CC56 2015 2015-05-21      DOSAT  3.1780538303  <NA> #> 7100   2059    3M  CC56 2015 2015-05-21      SALIN  2.1459312829     + #> 7101   2059    3M  CC56 2015 2015-07-15       COND  8.4859089014  <NA> #> 7102   2059    3M  CC56 2015 2015-07-15      SALIN  0.9001613499     + #> 7103   2059    3M  CC56 2015 2015-08-06       COND  6.3952615981  <NA> #> 7104   2059    3M  CC56 2015 2015-08-06         DO  0.9932517730  <NA> #> 7105   2059    3M  CC56 2015 2015-08-06      DOSAT  3.4657359028  <NA> #> 7106   2059    3M  CC56 2015 2015-08-06      SALIN -1.3093333200     + #> 7107   2059    3M  CC56 2015 2015-08-19       COND  6.1820849067  <NA> #> 7108   2059    3M  CC56 2015 2015-08-19         DO  0.9932517730  <NA> #> 7109   2059    3M  CC56 2015 2015-08-19      DOSAT  3.4965075615  <NA> #> 7110   2059    3M  CC56 2015 2015-08-19      SALIN -1.5141277326     + #> 7111   2059    3M  CC56 2015 2015-09-15       COND  6.2576675879  <NA> #> 7112   2059    3M  CC56 2015 2015-09-15         DO  0.0953101798  <NA> #> 7113   2059    3M  CC56 2015 2015-09-15      DOSAT  2.5649493575  <NA> #> 7114   2059    3M  CC56 2015 2015-09-15      SALIN -1.4271163556     + #> 7115   2059    3M  CC56 2015 2015-11-25       COND  7.6343372356  <NA> #> 7116   2059    3M  CC56 2015 2015-11-25         DO  0.9555114450  <NA> #> 7117   2059    3M  CC56 2015 2015-11-25      DOSAT  3.4011973817  <NA> #> 7118   2059    3M  CC56 2015 2015-11-25      SALIN  0.1570037488     + #> 7119   2059    3M  CC56 2015 2015-05-21       COND  9.9350831141  <NA> #> 7120   2059    3M  CC56 2015 2015-05-21         DO  0.7884573604  <NA> #> 7121   2059    3M  CC56 2015 2015-05-21      DOSAT  3.3672958300  <NA> #> 7122   2059    3M  CC56 2015 2015-05-21      SALIN  2.4865719291     + #> 7123   2059    3M  CC56 2015 2015-07-15      CHLAC  1.0986122887  <NA> #> 7124   2059    3M  CC56 2015 2015-07-15       COND  9.6128678361  <NA> #> 7125   2059    3M  CC56 2015 2015-07-15       NO23 -5.5214609179     U #> 7126   2059    3M  CC56 2015 2015-07-15      SALIN  2.0881534823     + #> 7127   2059    3M  CC56 2015 2015-07-15        TKN  0.2623642645  <NA> #> 7128   2059    3M  CC56 2015 2015-07-15         TN  0.2639015438     + #> 7129   2059    3M  CC56 2015 2015-07-15         TP -0.9416085399  <NA> #> 7130   2059    3M  CC56 2015 2015-07-15        TSS  1.0986122887     U #> 7131   2059    3M  CC56 2015 2015-07-15       TURB  1.3862943611  <NA> #> 7132   2059    3M  CC56 2015 2015-08-06       COND  6.5366915976  <NA> #> 7133   2059    3M  CC56 2015 2015-08-06         DO  0.2623642645  <NA> #> 7134   2059    3M  CC56 2015 2015-08-06      DOSAT  2.7725887222  <NA> #> 7135   2059    3M  CC56 2015 2015-08-06      SALIN -1.1394342832     + #> 7136   2059    3M  CC56 2015 2015-08-19      CHLAC  1.0296194172  <NA> #> 7137   2059    3M  CC56 2015 2015-08-19      COLOR  5.4380793089  <NA> #> 7138   2059    3M  CC56 2015 2015-08-19       COND  6.4488893941  <NA> #> 7139   2059    3M  CC56 2015 2015-08-19         DO  0.1823215568  <NA> #> 7140   2059    3M  CC56 2015 2015-08-19      DOSAT  2.7725887222  <NA> #> 7141   2059    3M  CC56 2015 2015-08-19       NO23 -5.5214609179     U #> 7142   2059    3M  CC56 2015 2015-08-19      SALIN -1.2378743560     + #> 7143   2059    3M  CC56 2015 2015-08-19        TKN  0.4054651081  <NA> #> 7144   2059    3M  CC56 2015 2015-08-19         TN  0.4067975533     + #> 7145   2059    3M  CC56 2015 2015-08-19         TP -0.0304592075  <NA> #> 7146   2059    3M  CC56 2015 2015-08-19        TSS  1.7917594692     I #> 7147   2059    3M  CC56 2015 2015-08-19       TURB  1.5686159179  <NA> #> 7148   2059    3M  CC56 2015 2015-09-15       COND  6.8134445995  <NA> #> 7149   2059    3M  CC56 2015 2015-09-15         DO  0.0000000000  <NA> #> 7150   2059    3M  CC56 2015 2015-09-15      DOSAT  2.3025850930  <NA> #> 7151   2059    3M  CC56 2015 2015-09-15      SALIN -0.8439700703     + #> 7152   2059    3M  CC56 2015 2015-11-25       COND  7.8038433035  <NA> #> 7153   2059    3M  CC56 2015 2015-11-25         DO  1.8718021769  <NA> #> 7154   2059    3M  CC56 2015 2015-11-25      DOSAT  4.2626798770  <NA> #> 7155   2059    3M  CC56 2015 2015-11-25      SALIN  0.3576744443     + #> 7156   2059    3M  CC56 2018 2018-03-06      CHLAC  1.7917594692  <NA> #> 7157   2059    3M  CC56 2018 2018-03-06       COND  9.8471817163  <NA> #> 7158   2059    3M  CC56 2018 2018-03-06         DO  0.6205764877  <NA> #> 7159   2059    3M  CC56 2018 2018-03-06      DOSAT  3.0445224377  <NA> #> 7160   2059    3M  CC56 2018 2018-03-06       NO23 -2.6592600369  <NA> #> 7161   2059    3M  CC56 2018 2018-03-06      SALIN  2.5748996883     + #> 7162   2059    3M  CC56 2018 2018-03-06        TKN -0.0833816089  <NA> #> 7163   2059    3M  CC56 2018 2018-03-06         TN -0.0100503359     + #> 7164   2059    3M  CC56 2018 2018-03-06         TP -1.2378743560  <NA> #> 7165   2059    3M  CC56 2018 2018-03-06        TSS  1.0986122887     U #> 7166   2059    3M  CC56 2018 2018-03-06       TURB  0.1823215568  <NA> #> 7167   2059    3M  CC56 2018 2018-03-29      CHLAC  2.1747517215  <NA> #> 7168   2059    3M  CC56 2018 2018-03-29       COND 10.2506170836  <NA> #> 7169   2059    3M  CC56 2018 2018-03-29         DO  1.3083328197  <NA> #> 7170   2059    3M  CC56 2018 2018-03-29      DOSAT  3.8501476017  <NA> #> 7171   2059    3M  CC56 2018 2018-03-29       NO23 -4.7105307016     I #> 7172   2059    3M  CC56 2018 2018-03-29      SALIN  2.9156062291     + #> 7173   2059    3M  CC56 2018 2018-03-29        TKN -0.2484613593  <NA> #> 7174   2059    3M  CC56 2018 2018-03-29         TN -0.2433462586     + #> 7175   2059    3M  CC56 2018 2018-03-29         TP -1.2039728043  <NA> #> 7176   2059    3M  CC56 2018 2018-03-29        TSS  1.3862943611     I #> 7177   2059    3M  CC56 2018 2018-03-29       TURB  0.8754687374  <NA> #> 7178   2059    3M  CC56 2018 2018-04-12       COND 10.0096027833  <NA> #> 7179   2059    3M  CC56 2018 2018-04-12         DO -0.3566749439  <NA> #> 7180   2059    3M  CC56 2018 2018-04-12      DOSAT  2.0794415417  <NA> #> 7181   2059    3M  CC56 2018 2018-04-12      SALIN  2.6932749155     + #> 7182   2059    3M  CC56 2018 2018-04-19      CHLAC  0.0953101798     I #> 7183   2059    3M  CC56 2018 2018-04-19       COND 10.2545668701  <NA> #> 7184   2059    3M  CC56 2018 2018-04-19         DO  1.0260415958  <NA> #> 7185   2059    3M  CC56 2018 2018-04-19      DOSAT  3.5025498759  <NA> #> 7186   2059    3M  CC56 2018 2018-04-19       NO23 -4.6051701860     I #> 7187   2059    3M  CC56 2018 2018-04-19      SALIN  2.9150643705     + #> 7188   2059    3M  CC56 2018 2018-04-19        TKN -0.1863295782  <NA> #> 7189   2059    3M  CC56 2018 2018-04-19         TN -0.1815218766     + #> 7190   2059    3M  CC56 2018 2018-04-19         TP -1.0788096614  <NA> #> 7191   2059    3M  CC56 2018 2018-04-19        TSS  1.3862943611     I #> 7192   2059    3M  CC56 2018 2018-04-19       TURB  0.1823215568  <NA> #> 7193   2059    3M  CC56 2018 2018-05-10      CHLAC  1.0296194172  <NA> #> 7194   2059    3M  CC56 2018 2018-05-10       COND 10.2722540975  <NA> #> 7195   2059    3M  CC56 2018 2018-05-10         DO -0.1053605157  <NA> #> 7196   2059    3M  CC56 2018 2018-05-10      DOSAT  2.4849066498  <NA> #> 7197   2059    3M  CC56 2018 2018-05-10       NO23 -5.5214609179     U #> 7198   2059    3M  CC56 2018 2018-05-10      SALIN  2.8848007128  <NA> #> 7199   2059    3M  CC56 2018 2018-05-10        TKN -0.0725706928  <NA> #> 7200   2059    3M  CC56 2018 2018-05-10         TN -0.0704224643     + #> 7201   2059    3M  CC56 2018 2018-05-10         TP -0.8209805521  <NA> #> 7202   2059    3M  CC56 2018 2018-05-10        TSS  1.0986122887     I #> 7203   2059    3M  CC56 2018 2018-05-10       TURB  0.5306282511  <NA> #> 7204   2059    3M  CC56 2018 2018-06-25      CHLAC  0.6931471806  <NA> #> 7205   2059    3M  CC56 2018 2018-06-25       COND  7.7536235466  <NA> #> 7206   2059    3M  CC56 2018 2018-06-25         DO  1.0296194172  <NA> #> 7207   2059    3M  CC56 2018 2018-06-25      DOSAT  3.2695689392  <NA> #> 7208   2059    3M  CC56 2018 2018-06-25       NO23 -5.5214609179     U #> 7209   2059    3M  CC56 2018 2018-06-25      SALIN  0.1397619424     + #> 7210   2059    3M  CC56 2018 2018-06-25        TKN  0.2623642645  <NA> #> 7211   2059    3M  CC56 2018 2018-06-25         TN  0.2639015438     + #> 7212   2059    3M  CC56 2018 2018-06-25         TP -1.4696759701  <NA> #> 7213   2059    3M  CC56 2018 2018-06-25        TSS  1.0986122887     I #> 7214   2059    3M  CC56 2018 2018-06-25       TURB  1.3862943611  <NA> #> 7215   2059    3M  CC56 2018 2018-07-17      CHLAC  0.9932517730  <NA> #> 7216   2059    3M  CC56 2018 2018-07-17       COND  6.8437499490  <NA> #> 7217   2059    3M  CC56 2018 2018-07-17         DO -0.1863295782  <NA> #> 7218   2059    3M  CC56 2018 2018-07-17      DOSAT  2.3418058061  <NA> #> 7219   2059    3M  CC56 2018 2018-07-17       NO23 -3.3524072175  <NA> #> 7220   2059    3M  CC56 2018 2018-07-17      SALIN -0.8439700703     + #> 7221   2059    3M  CC56 2018 2018-07-17        TKN  0.2623642645  <NA> #> 7222   2059    3M  CC56 2018 2018-07-17         TN  0.2889312919     + #> 7223   2059    3M  CC56 2018 2018-07-17         TP -1.3093333200  <NA> #> 7224   2059    3M  CC56 2018 2018-07-17        TSS  1.0986122887     I #> 7225   2059    3M  CC56 2018 2018-07-17       TURB  0.0953101798  <NA> #> 7226   2059    3M  CC56 2018 2018-08-01      CHLAC  0.8754687374  <NA> #> 7227   2059    3M  CC56 2018 2018-08-01       COND  6.0038870671  <NA> #> 7228   2059    3M  CC56 2018 2018-08-01         DO  0.7129498079  <NA> #> 7229   2059    3M  CC56 2018 2018-08-01      DOSAT  3.2580965380  <NA> #> 7230   2059    3M  CC56 2018 2018-08-01       NO23 -3.6119184130  <NA> #> 7231   2059    3M  CC56 2018 2018-08-01      SALIN -1.6607312068  <NA> #> 7232   2059    3M  CC56 2018 2018-08-01        TKN  0.0953101798  <NA> #> 7233   2059    3M  CC56 2018 2018-08-01         TN  0.1195592351     + #> 7234   2059    3M  CC56 2018 2018-08-01         TP -1.7719568419  <NA> #> 7235   2059    3M  CC56 2018 2018-08-01        TSS  0.6931471806     U #> 7236   2059    3M  CC56 2018 2018-08-01       TURB  0.0953101798  <NA> #> 7237   2059    3M  CC56 2018 2018-08-20      CHLAC  0.4054651081     I #> 7238   2059    3M  CC56 2018 2018-08-20       NO23 -1.4696759701  <NA> #> 7239   2059    3M  CC56 2018 2018-08-20        TKN -0.3147107448  <NA> #> 7240   2059    3M  CC56 2018 2018-08-20         TN -0.0408219945     + #> 7241   2059    3M  CC56 2018 2018-08-20         TP -0.9416085399  <NA> #> 7242   2059    3M  CC56 2018 2018-08-20        TSS  1.0986122887     U #> 7243   2059    3M  CC56 2018 2018-08-20       TURB  0.7419373447  <NA> #> 7244   2059    3M  CC56 2018 2018-08-21      CHLAC  0.7419373447  <NA> #> 7245   2059    3M  CC56 2018 2018-08-21       COND  5.9401712527  <NA> #> 7246   2059    3M  CC56 2018 2018-08-21         DO  0.9516578757  <NA> #> 7247   2059    3M  CC56 2018 2018-08-21      DOSAT  3.4436180975  <NA> #> 7248   2059    3M  CC56 2018 2018-08-21       NO23 -3.7297014486  <NA> #> 7249   2059    3M  CC56 2018 2018-08-21      SALIN -1.7147984281  <NA> #> 7250   2059    3M  CC56 2018 2018-08-21        TKN  0.0000000000  <NA> #> 7251   2059    3M  CC56 2018 2018-08-21         TN  0.0237165266     + #> 7252   2059    3M  CC56 2018 2018-08-21         TP -1.8325814637  <NA> #> 7253   2059    3M  CC56 2018 2018-08-21        TSS  1.0986122887     I #> 7254   2059    3M  CC56 2018 2018-08-21       TURB  0.3364722366     A #> 7255   2059    3M  CC56 2018 2018-09-20      CHLAC  1.5040773968  <NA> #> 7256   2059    3M  CC56 2018 2018-09-20       COND  7.2661287796  <NA> #> 7257   2059    3M  CC56 2018 2018-09-20         DO  0.9555114450  <NA> #> 7258   2059    3M  CC56 2018 2018-09-20      DOSAT  3.5862928653  <NA> #> 7259   2059    3M  CC56 2018 2018-09-20       NO23 -3.1010927892  <NA> #> 7260   2059    3M  CC56 2018 2018-09-20      SALIN -0.3424903089  <NA> #> 7261   2059    3M  CC56 2018 2018-09-20        TKN  0.1823215568  <NA> #> 7262   2059    3M  CC56 2018 2018-09-20         TN  0.2191355299     + #> 7263   2059    3M  CC56 2018 2018-09-20         TP -1.0788096614  <NA> #> 7264   2059    3M  CC56 2018 2018-09-20        TSS  1.0986122887     I #> 7265   2059    3M  CC56 2018 2018-09-20       TURB  0.9162907319  <NA> #> 7266   2059    3M  CC56 2018 2018-10-24      CHLAC  1.1314021115  <NA> #> 7267   2059    3M  CC56 2018 2018-10-24       COND  9.4323632956  <NA> #> 7268   2059    3M  CC56 2018 2018-10-24         DO  0.5068176024  <NA> #> 7269   2059    3M  CC56 2018 2018-10-24      DOSAT  3.0726933147  <NA> #> 7270   2059    3M  CC56 2018 2018-10-24       NO23 -3.4737680745  <NA> #> 7271   2059    3M  CC56 2018 2018-10-24      SALIN  1.9671123567  <NA> #> 7272   2059    3M  CC56 2018 2018-10-24        TKN -0.0408219945  <NA> #> 7273   2059    3M  CC56 2018 2018-10-24         TN -0.0090407447     + #> 7274   2059    3M  CC56 2018 2018-10-24         TP -1.2039728043  <NA> #> 7275   2059    3M  CC56 2018 2018-10-24        TSS  0.6931471806     I #> 7276   2059    3M  CC56 2018 2018-10-24       TURB  1.7227665977  <NA> #> 7277   2059    3M  CC56 2019 2019-01-16      CHLAC -0.1053605157     I #> 7278   2059    3M  CC56 2019 2019-01-16       COND  9.0122552200  <NA> #> 7279   2059    3M  CC56 2019 2019-01-16         DO  0.3852624008  <NA> #> 7280   2059    3M  CC56 2019 2019-01-16      DOSAT  2.7080502011  <NA> #> 7281   2059    3M  CC56 2019 2019-01-16       NO23 -2.5010360317  <NA> #> 7282   2059    3M  CC56 2019 2019-01-16      SALIN  1.5216989981  <NA> #> 7283   2059    3M  CC56 2019 2019-01-16        TKN -0.0618754037  <NA> #> 7284   2059    3M  CC56 2019 2019-01-16         TN  0.0217614918     + #> 7285   2059    3M  CC56 2019 2019-01-16         TP -1.3862943611  <NA> #> 7286   2059    3M  CC56 2019 2019-01-16        TSS  0.6931471806     U #> 7287   2059    3M  CC56 2019 2019-01-16       TURB  0.0000000000  <NA> #> 7288   2059    3M  CC56 2019 2019-01-24       COND  9.8578100390  <NA> #> 7289   2059    3M  CC56 2019 2019-01-24         DO  1.6770965609  <NA> #> 7290   2059    3M  CC56 2019 2019-01-24      DOSAT  4.1588830834  <NA> #> 7291   2059    3M  CC56 2019 2019-01-24       NO23 -3.2968373663  <NA> #> 7292   2059    3M  CC56 2019 2019-01-24      SALIN  2.4327357775  <NA> #> 7293   2059    3M  CC56 2019 2019-01-24        TKN -0.3147107448  <NA> #> 7294   2059    3M  CC56 2019 2019-01-24         TN -0.2652684776     + #> 7295   2059    3M  CC56 2019 2019-01-24         TP -1.3470736480  <NA> #> 7296   2059    3M  CC56 2019 2019-01-24        TSS  1.0986122887     U #> 7297   2059    3M  CC56 2019 2019-01-24       TURB  0.6418538862  <NA> #> 7298   2059    3M  CC56 2019 2019-03-12      CHLAC  0.1823215568     I #> 7299   2059    3M  CC56 2019 2019-03-12       COND  9.1291303166  <NA> #> 7300   2059    3M  CC56 2019 2019-03-12         DO  0.4824261492  <NA> #> 7301   2059    3M  CC56 2019 2019-03-12      DOSAT  2.9496883351  <NA> #> 7302   2059    3M  CC56 2019 2019-03-12       NO23 -3.2968373663  <NA> #> 7303   2059    3M  CC56 2019 2019-03-12      SALIN  1.6114359151  <NA> #> 7304   2059    3M  CC56 2019 2019-03-12        TKN -0.0408219945  <NA> #> 7305   2059    3M  CC56 2019 2019-03-12         TN -0.0030045090     + #> 7306   2059    3M  CC56 2019 2019-03-12         TP -1.0498221245  <NA> #> 7307   2059    3M  CC56 2019 2019-03-12        TSS  0.6931471806     I #> 7308   2059    3M  CC56 2019 2019-03-12       TURB  0.0000000000  <NA> #> 7309   2059    3M  CC56 2019 2019-04-23      CHLAC  1.1939224685  <NA> #> 7310   2059    3M  CC56 2019 2019-04-23       COND  9.4766200382  <NA> #> 7311   2059    3M  CC56 2019 2019-04-23         DO  0.7929925155  <NA> #> 7312   2059    3M  CC56 2019 2019-04-23      DOSAT  3.3286266888  <NA> #> 7313   2059    3M  CC56 2019 2019-04-23       NO23 -3.5755507688  <NA> #> 7314   2059    3M  CC56 2019 2019-04-23      SALIN  2.0175661380  <NA> #> 7315   2059    3M  CC56 2019 2019-04-23        TKN -0.1984509387  <NA> #> 7316   2059    3M  CC56 2019 2019-04-23         TN -0.1648746432     + #> 7317   2059    3M  CC56 2019 2019-04-23         TP -1.1086626245  <NA> #> 7318   2059    3M  CC56 2019 2019-04-23        TSS  0.6931471806     I #> 7319   2059    3M  CC56 2019 2019-04-23       TURB  0.2623642645  <NA> #> 7320   2059    3M  CC56 2019 2019-06-11      CHLAC  1.8245492921     I #> 7321   2059    3M  CC56 2019 2019-06-11       COND  9.8113722636  <NA> #> 7322   2059    3M  CC56 2019 2019-06-11         DO -1.0216512475  <NA> #> 7323   2059    3M  CC56 2019 2019-06-11      DOSAT  1.6094379124  <NA> #> 7324   2059    3M  CC56 2019 2019-06-11       NO23 -5.5214609179     U #> 7325   2059    3M  CC56 2019 2019-06-11      SALIN  2.4221443281  <NA> #> 7326   2059    3M  CC56 2019 2019-06-11        TKN  0.0000000000  <NA> #> 7327   2059    3M  CC56 2019 2019-06-11         TN  0.0019980027     + #> 7328   2059    3M  CC56 2019 2019-06-11         TP -1.0498221245  <NA> #> 7329   2059    3M  CC56 2019 2019-06-11        TSS  1.3862943611     I #> 7330   2059    3M  CC56 2019 2019-06-11       TURB  1.4350845253     A #> 7331   2059    3M  CC56 2019 2019-08-13      CHLAC  0.4054651081     I #> 7332   2059    3M  CC56 2019 2019-08-13       COND  6.6644090204  <NA> #> 7333   2059    3M  CC56 2019 2019-08-13         DO -0.3285040670  <NA> #> 7334   2059    3M  CC56 2019 2019-08-13      DOSAT  2.2192034841  <NA> #> 7335   2059    3M  CC56 2019 2019-08-13       NO23 -2.7488721956  <NA> #> 7336   2059    3M  CC56 2019 2019-08-13      SALIN -0.9675840263  <NA> #> 7337   2059    3M  CC56 2019 2019-08-13        TKN  0.1823215568  <NA> #> 7338   2059    3M  CC56 2019 2019-08-13         TN  0.2342812957     + #> 7339   2059    3M  CC56 2019 2019-08-13         TP -1.3470736480  <NA> #> 7340   2059    3M  CC56 2019 2019-08-13        TSS  0.6931471806     I #> 7341   2059    3M  CC56 2019 2019-08-13       TURB  0.0000000000  <NA> #> 7342   2059    3M  CC56 2019 2019-10-01       COND  8.7345600900  <NA> #> 7343   2059    3M  CC56 2019 2019-10-01         DO  0.1310282624  <NA> #> 7344   2059    3M  CC56 2019 2019-10-01      DOSAT  2.6532419646  <NA> #> 7345   2059    3M  CC56 2019 2019-10-01      SALIN  1.2149127444  <NA> #> 7346   2059    3M  CC56 2019 2019-11-04       COND  8.7934603611  <NA> #> 7347   2059    3M  CC56 2019 2019-11-04         DO  0.0000000000  <NA> #> 7348   2059    3M  CC56 2019 2019-11-04      DOSAT  2.5649493575  <NA> #> 7349   2059    3M  CC56 2019 2019-11-04      SALIN  1.2809338455  <NA> #> 7350   2059    3M  CC56 2019 2019-11-19      CHLAC  1.2809338455  <NA> #> 7351   2059    3M  CC56 2019 2019-11-19       COND  9.6775902130  <NA> #> 7352   2059    3M  CC56 2019 2019-11-19         DO  0.9631743178  <NA> #> 7353   2059    3M  CC56 2019 2019-11-19      DOSAT  3.4078419244  <NA> #> 7354   2059    3M  CC56 2019 2019-11-19       NO23 -2.9565115604  <NA> #> 7355   2059    3M  CC56 2019 2019-11-19      SALIN  2.2364452905  <NA> #> 7356   2059    3M  CC56 2019 2019-11-19        TKN -0.3011050928  <NA> #> 7357   2059    3M  CC56 2019 2019-11-19         TN -0.2331938872     + #> 7358   2059    3M  CC56 2019 2019-11-19         TP -1.2378743560  <NA> #> 7359   2059    3M  CC56 2019 2019-11-19        TSS  1.0986122887     U #> 7360   2059    3M  CC56 2019 2019-11-19       TURB  0.1823215568  <NA> #> 7361   2059    3M  CC56 2020 2020-01-28      CHLAC  0.7419373447     U #> 7362   2059    3M  CC56 2020 2020-01-28       COND  8.9703049530  <NA> #> 7363   2059    3M  CC56 2020 2020-01-28         DO  1.0784095814  <NA> #> 7364   2059    3M  CC56 2020 2020-01-28      DOSAT  3.4468078929  <NA> #> 7365   2059    3M  CC56 2020 2020-01-28       NO23 -1.4271163556  <NA> #> 7366   2059    3M  CC56 2020 2020-01-28      SALIN  1.4747630091  <NA> #> 7367   2059    3M  CC56 2020 2020-01-28        TKN -0.2744368457  <NA> #> 7368   2059    3M  CC56 2020 2020-01-28         TN  0.0000000000     + #> 7369   2059    3M  CC56 2020 2020-01-28         TP -1.9661128564  <NA> #> 7370   2059    3M  CC56 2020 2020-01-28        TSS  0.6931471806     U #> 7371   2059    3M  CC56 2020 2020-01-28       TURB  0.0000000000  <NA> #> 7372   2059    3M  CC56 2020 2020-03-05      CHLAC  0.6418538862     I #> 7373   2059    3M  CC56 2020 2020-03-05       COND 10.0861423871  <NA> #> 7374   2059    3M  CC56 2020 2020-03-05         DO  0.4700036292  <NA> #> 7375   2059    3M  CC56 2020 2020-03-05      DOSAT  2.9957322736  <NA> #> 7376   2059    3M  CC56 2020 2020-03-05       NO23 -2.9004220937  <NA> #> 7377   2059    3M  CC56 2020 2020-03-05      SALIN  2.6817062258  <NA> #> 7378   2059    3M  CC56 2020 2020-03-05        TKN -0.3424903089  <NA> #> 7379   2059    3M  CC56 2020 2020-03-05         TN -0.2678794452     + #> 7380   2059    3M  CC56 2020 2020-03-05         TP -1.2378743560  <NA> #> 7381   2059    3M  CC56 2020 2020-03-05        TSS  1.3862943611     I #> 7382   2059    3M  CC56 2020 2020-03-05       TURB  0.9932517730  <NA> #> 7383   2059    3M  CC56 2020 2020-07-28      CHLAC  1.3083328197  <NA> #> 7384   2059    3M  CC56 2020 2020-07-28       COND  9.3060141220  <NA> #> 7385   2059    3M  CC56 2020 2020-07-28         DO -0.1053605157  <NA> #> 7386   2059    3M  CC56 2020 2020-07-28      DOSAT  2.4849066498  <NA> #> 7387   2059    3M  CC56 2020 2020-07-28       NO23 -3.6119184130  <NA> #> 7388   2059    3M  CC56 2020 2020-07-28      SALIN  1.8261608959  <NA> #> 7389   2059    3M  CC56 2020 2020-07-28        TKN  0.0000000000  <NA> #> 7390   2059    3M  CC56 2020 2020-07-28         TN  0.0266419309     + #> 7391   2059    3M  CC56 2020 2020-07-28         TP -0.6733445533  <NA> #> 7392   2059    3M  CC56 2020 2020-07-28        TSS  0.6931471806     I #> 7393   2059    3M  CC56 2020 2020-07-28       TURB  1.1939224685  <NA> #> 7394   2059    3M  CC56 2020 2020-08-31      CHLAC  0.4700036292     U #> 7395   2059    3M  CC56 2020 2020-08-31       COND  7.2751723195  <NA> #> 7396   2059    3M  CC56 2020 2020-08-31         DO -1.2378743560  <NA> #> 7397   2059    3M  CC56 2020 2020-08-31      DOSAT  1.3083328197  <NA> #> 7398   2059    3M  CC56 2020 2020-08-31       NO23 -3.5404594490  <NA> #> 7399   2059    3M  CC56 2020 2020-08-31      SALIN -0.3285040670  <NA> #> 7400   2059    3M  CC56 2020 2020-08-31        TKN  0.3364722366  <NA> #> 7401   2059    3M  CC56 2020 2020-08-31         TN  0.3569748989     + #> 7402   2059    3M  CC56 2020 2020-08-31         TP -1.3862943611  <NA> #> 7403   2059    3M  CC56 2020 2020-08-31        TSS  0.6931471806     U #> 7404   2059    3M  CC56 2020 2020-08-31       TURB  0.4054651081  <NA> #> 7405   2059    3M  CC56 2020 2020-09-16      CHLAC  0.4700036292     U #> 7406   2059    3M  CC56 2020 2020-09-16       COND  6.8068293604  <NA> #> 7407   2059    3M  CC56 2020 2020-09-16         DO  0.4054651081  <NA> #> 7408   2059    3M  CC56 2020 2020-09-16      DOSAT  2.9444389792  <NA> #> 7409   2059    3M  CC56 2020 2020-09-16       NO23 -2.6882475738  <NA> #> 7410   2059    3M  CC56 2020 2020-09-16      SALIN -0.8209805521  <NA> #> 7411   2059    3M  CC56 2020 2020-09-16        TKN -0.2107210313  <NA> #> 7412   2059    3M  CC56 2020 2020-09-16         TN -0.1301086853     + #> 7413   2059    3M  CC56 2020 2020-09-16         TP -1.3862943611  <NA> #> 7414   2059    3M  CC56 2020 2020-09-16        TSS  0.6931471806     I #> 7415   2059    3M  CC56 2020 2020-09-16       TURB  0.6418538862  <NA> #> 7416   2059    3M  CC56 2023 2023-01-04       COND 10.3353673668  <NA> #> 7417   2059    3M  CC56 2023 2023-01-04         DO  1.8148247422  <NA> #> 7418   2059    3M  CC56 2023 2023-01-04      DOSAT  4.3320482649  <NA> #> 7419   2059    3M  CC56 2023 2023-01-04      SALIN  2.9538680695  <NA> #> 7420   2059    3M  CC56 2023 2023-01-18      CHLAC  0.9932517730     I #> 7421   2059    3M  CC56 2023 2023-01-18       COND 10.0905063931  <NA> #> 7422   2059    3M  CC56 2023 2023-01-18         DO  1.8131947499  <NA> #> 7423   2059    3M  CC56 2023 2023-01-18      DOSAT  4.2541932632  <NA> #> 7424   2059    3M  CC56 2023 2023-01-18       NO23 -1.8971199849  <NA> #> 7425   2059    3M  CC56 2023 2023-01-18      SALIN  2.6864860232  <NA> #> 7426   2059    3M  CC56 2023 2023-01-18        TKN  0.4054651081  <NA> #> 7427   2059    3M  CC56 2023 2023-01-18         TN  0.5007752879     + #> 7428   2059    3M  CC56 2023 2023-01-18         TP -1.7147984281  <NA> #> 7429   2059    3M  CC56 2023 2023-01-18        TSS  1.0986122887     U #> 7430   2059    3M  CC56 2023 2023-01-18       TURB  0.3364722366  <NA> #> 7431   2059    3M  CC56 2023 2023-03-01      CHLAC  2.9957322736  <NA> #> 7432   2059    3M  CC56 2023 2023-03-01       COND 10.0265897497  <NA> #> 7433   2059    3M  CC56 2023 2023-03-01         DO -0.8439700703  <NA> #> 7434   2059    3M  CC56 2023 2023-03-01      DOSAT  1.7227665977  <NA> #> 7435   2059    3M  CC56 2023 2023-03-01       NO23 -0.4780358009  <NA> #> 7436   2059    3M  CC56 2023 2023-03-01      SALIN  2.6130066524  <NA> #> 7437   2059    3M  CC56 2023 2023-03-01        TKN  0.9555114450  <NA> #> 7438   2059    3M  CC56 2023 2023-03-01         TN  1.1693813596     + #> 7439   2059    3M  CC56 2023 2023-03-01         TP -0.8209805521  <NA> #> 7440   2059    3M  CC56 2023 2023-03-01        TSS  3.4965075615  <NA> #> 7441   2059    3M  CC56 2023 2023-03-01       TURB  4.0073331852  <NA> #> 7442   2059    3M  CC56 2023 2023-03-15      CHLAC  1.5260563035     I #> 7443   2059    3M  CC56 2023 2023-03-15       COND 10.0164590312  <NA> #> 7444   2059    3M  CC56 2023 2023-03-15         DO -0.7550225843  <NA> #> 7445   2059    3M  CC56 2023 2023-03-15      DOSAT  1.8082887712  <NA> #> 7446   2059    3M  CC56 2023 2023-03-15       NO23 -0.2107210313  <NA> #> 7447   2059    3M  CC56 2023 2023-03-15      SALIN  2.6026896854  <NA> #> 7448   2059    3M  CC56 2023 2023-03-15        TKN  0.7419373447  <NA> #> 7449   2059    3M  CC56 2023 2023-03-15         TN  1.0681530812     + #> 7450   2059    3M  CC56 2023 2023-03-15         TP -1.1711829815  <NA> #> 7451   2059    3M  CC56 2023 2023-03-15        TSS  3.3322045102  <NA> #> 7452   2059    3M  CC56 2023 2023-03-15       TURB  3.6109179126  <NA> #> 7453   2059    3M  CC56 2023 2023-05-02       COND  7.8264431355  <NA> #> 7454   2059    3M  CC56 2023 2023-05-02         DO  0.7514160887  <NA> #> 7455   2059    3M  CC56 2023 2023-05-02      DOSAT  3.2503744919  <NA> #> 7456   2059    3M  CC56 2023 2023-05-02      SALIN  0.2390169005  <NA> #> 7457   2059    3M  CC56 2018 2018-07-16      CHLAC  1.1314021115  <NA> #> 7458   2059    3M  CC56 2018 2018-07-16      COLOR  5.9661467391  <NA> #> 7459   2059    3M  CC56 2018 2018-07-16       COND  6.0969500550  <NA> #> 7460   2059    3M  CC56 2018 2018-07-16         DO  0.1988508587  <NA> #> 7461   2059    3M  CC56 2018 2018-07-16      DOSAT  2.7536607124  <NA> #> 7462   2059    3M  CC56 2018 2018-07-16       NO23 -3.1700856607  <NA> #> 7463   2059    3M  CC56 2018 2018-07-16      SALIN -1.6094379124     + #> 7464   2059    3M  CC56 2018 2018-07-16        TKN  0.2623642645  <NA> #> 7465   2059    3M  CC56 2018 2018-07-16         TN  0.2941610385     + #> 7466   2059    3M  CC56 2018 2018-07-16         TP -1.4271163556  <NA> #> 7467   2059    3M  CC56 2018 2018-07-16        TSS  0.6931471806     I #> 7468   2059    3M  CC56 2018 2018-07-16       TURB -0.0512932944  <NA> #> 7469   2063    3M  CC64 2014 2014-01-06      CHLAC  1.3862943611  <NA> #> 7470   2063    3M  CC64 2014 2014-01-06      COLOR  2.6390573296  <NA> #> 7471   2063    3M  CC64 2014 2014-01-06         DO  1.7785053535  <NA> #> 7472   2063    3M  CC64 2014 2014-01-06      DOSAT  4.3412046402     + #> 7473   2063    3M  CC64 2014 2014-01-06       NO23 -5.1159958098     I #> 7474   2063    3M  CC64 2014 2014-01-06      SALIN  3.3534067178  <NA> #> 7475   2063    3M  CC64 2014 2014-01-06        TKN -0.8915981193  <NA> #> 7476   2063    3M  CC64 2014 2014-01-06         TN -0.8818893052     + #> 7477   2063    3M  CC64 2014 2014-01-06         TP -2.4889146712  <NA> #> 7478   2063    3M  CC64 2014 2014-01-06       TURB  0.4700036292  <NA> #> 7479   2063    3M  CC64 2014 2014-02-03      CHLAC  0.1823215568     I #> 7480   2063    3M  CC64 2014 2014-02-03      COLOR  1.7227665977     I #> 7481   2063    3M  CC64 2014 2014-02-03         DO  1.6992786164  <NA> #> 7482   2063    3M  CC64 2014 2014-02-03      DOSAT  4.2527717988     + #> 7483   2063    3M  CC64 2014 2014-02-03       NO23 -4.7105307016     I #> 7484   2063    3M  CC64 2014 2014-02-03      SALIN  3.3432150991  <NA> #> 7485   2063    3M  CC64 2014 2014-02-03        TKN -0.7339691751  <NA> #> 7486   2063    3M  CC64 2014 2014-02-03         TN -0.7256703723     + #> 7487   2063    3M  CC64 2014 2014-02-03         TP -2.4534079827  <NA> #> 7488   2063    3M  CC64 2014 2014-02-03       TURB  0.1823215568  <NA> #> 7489   2063    3M  CC64 2014 2014-03-03      CHLAC  1.3609765531  <NA> #> 7490   2063    3M  CC64 2014 2014-03-03      COLOR  2.3025850930  <NA> #> 7491   2063    3M  CC64 2014 2014-03-03         DO  1.7173950539  <NA> #> 7492   2063    3M  CC64 2014 2014-03-03      DOSAT  4.3201512310     + #> 7493   2063    3M  CC64 2014 2014-03-03       NO23 -5.2983173665     I #> 7494   2063    3M  CC64 2014 2014-03-03      SALIN  3.3307749174  <NA> #> 7495   2063    3M  CC64 2014 2014-03-03        TKN -0.6161861394  <NA> #> 7496   2063    3M  CC64 2014 2014-03-03         TN -0.6088060321     + #> 7497   2063    3M  CC64 2014 2014-03-03         TP -2.3644604967  <NA> #> 7498   2063    3M  CC64 2014 2014-03-03       TURB  0.4054651081  <NA> #> 7499   2063    3M  CC64 2014 2014-04-07      CHLAC  1.2237754316  <NA> #> 7500   2063    3M  CC64 2014 2014-04-07      COLOR  2.6390573296  <NA> #> 7501   2063    3M  CC64 2014 2014-04-07         DO  1.3244189574  <NA> #> 7502   2063    3M  CC64 2014 2014-04-07      DOSAT  3.9759363312     + #> 7503   2063    3M  CC64 2014 2014-04-07       NO23 -4.8283137373     I #> 7504   2063    3M  CC64 2014 2014-04-07      SALIN  3.3246762438  <NA> #> 7505   2063    3M  CC64 2014 2014-04-07        TKN -0.4942963218  <NA> #> 7506   2063    3M  CC64 2014 2014-04-07         TN -0.4877603508     + #> 7507   2063    3M  CC64 2014 2014-04-07         TP -2.3330443005  <NA> #> 7508   2063    3M  CC64 2014 2014-04-07       TURB  0.8329091229  <NA> #> 7509   2063    3M  CC64 2014 2014-05-05      CHLAC  1.3350010667  <NA> #> 7510   2063    3M  CC64 2014 2014-05-05      COLOR  2.6390573296  <NA> #> 7511   2063    3M  CC64 2014 2014-05-05         DO  1.4398351280  <NA> #> 7512   2063    3M  CC64 2014 2014-05-05      DOSAT  4.0910056610     + #> 7513   2063    3M  CC64 2014 2014-05-05       NO23 -4.9618451299     I #> 7514   2063    3M  CC64 2014 2014-05-05      SALIN  3.3039519972  <NA> #> 7515   2063    3M  CC64 2014 2014-05-05        TKN -0.4780358009  <NA> #> 7516   2063    3M  CC64 2014 2014-05-05         TN -0.4716049106     + #> 7517   2063    3M  CC64 2014 2014-05-05         TP -2.2072749132  <NA> #> 7518   2063    3M  CC64 2014 2014-05-05       TURB  0.9555114450  <NA> #> 7519   2063    3M  CC64 2014 2014-06-02      CHLAC  1.3083328197  <NA> #> 7520   2063    3M  CC64 2014 2014-06-02      COLOR  2.3978952728  <NA> #> 7521   2063    3M  CC64 2014 2014-06-02         DO  1.0116009117  <NA> #> 7522   2063    3M  CC64 2014 2014-06-02      DOSAT  3.7111300630     + #> 7523   2063    3M  CC64 2014 2014-06-02       NO23 -5.1159958098     I #> 7524   2063    3M  CC64 2014 2014-06-02      SALIN  3.3347013904  <NA> #> 7525   2063    3M  CC64 2014 2014-06-02        TKN -0.4462871026  <NA> #> 7526   2063    3M  CC64 2014 2014-06-02         TN -0.4400565529     + #> 7527   2063    3M  CC64 2014 2014-06-02         TP -2.0402208285  <NA> #> 7528   2063    3M  CC64 2014 2014-06-02       TURB  0.6931471806  <NA> #> 7529   2063    3M  CC64 2014 2014-07-07      CHLAC  1.7047480922  <NA> #> 7530   2063    3M  CC64 2014 2014-07-07      COLOR  3.1354942159  <NA> #> 7531   2063    3M  CC64 2014 2014-07-07      DOSAT  3.7495040759     + #> 7532   2063    3M  CC64 2014 2014-07-07       NO23 -4.5098600062  <NA> #> 7533   2063    3M  CC64 2014 2014-07-07      SALIN  3.2611687371  <NA> #> 7534   2063    3M  CC64 2014 2014-07-07        TKN -0.1863295782  <NA> #> 7535   2063    3M  CC64 2014 2014-07-07         TN -0.1731636190     + #> 7536   2063    3M  CC64 2014 2014-07-07         TP -2.0402208285  <NA> #> 7537   2063    3M  CC64 2014 2014-07-07       TURB  0.6931471806  <NA> #> 7538   2063    3M  CC64 2014 2014-08-04      CHLAC  2.4849066498  <NA> #> 7539   2063    3M  CC64 2014 2014-08-04      COLOR  3.7612001157  <NA> #> 7540   2063    3M  CC64 2014 2014-08-04         DO  0.9932517730  <NA> #> 7541   2063    3M  CC64 2014 2014-08-04      DOSAT  3.6863763239     + #> 7542   2063    3M  CC64 2014 2014-08-04       NO23 -4.8283137373     I #> 7543   2063    3M  CC64 2014 2014-08-04      SALIN  2.9439125248  <NA> #> 7544   2063    3M  CC64 2014 2014-08-04        TKN -0.1743533871  <NA> #> 7545   2063    3M  CC64 2014 2014-08-04         TN -0.1696027844     + #> 7546   2063    3M  CC64 2014 2014-08-04         TP -1.6607312068  <NA> #> 7547   2063    3M  CC64 2014 2014-08-04       TURB  1.0296194172  <NA> #> 7548   2063    3M  CC64 2014 2014-09-08      CHLAC  0.9162907319  <NA> #> 7549   2063    3M  CC64 2014 2014-09-08      COLOR  3.4011973817  <NA> #> 7550   2063    3M  CC64 2014 2014-09-08         DO  0.7178397932  <NA> #> 7551   2063    3M  CC64 2014 2014-09-08      DOSAT  3.3911470458     + #> 7552   2063    3M  CC64 2014 2014-09-08       NO23 -4.1351665567  <NA> #> 7553   2063    3M  CC64 2014 2014-09-08      SALIN  2.9242362718  <NA> #> 7554   2063    3M  CC64 2014 2014-09-08        TKN -0.2231435513  <NA> #> 7555   2063    3M  CC64 2014 2014-09-08         TN -0.2033409240     + #> 7556   2063    3M  CC64 2014 2014-09-08         TP -1.9661128564  <NA> #> 7557   2063    3M  CC64 2014 2014-09-08       TURB -0.0512932944  <NA> #> 7558   2063    3M  CC64 2014 2014-10-06      CHLAC  1.5040773968  <NA> #> 7559   2063    3M  CC64 2014 2014-10-06      COLOR  4.5951198501  <NA> #> 7560   2063    3M  CC64 2014 2014-10-06         DO  0.9162907319  <NA> #> 7561   2063    3M  CC64 2014 2014-10-06      DOSAT  3.4781584228     + #> 7562   2063    3M  CC64 2014 2014-10-06       NO23 -3.3813947544  <NA> #> 7563   2063    3M  CC64 2014 2014-10-06      SALIN  2.0819384219  <NA> #> 7564   2063    3M  CC64 2014 2014-10-06        TKN -0.0408219945  <NA> #> 7565   2063    3M  CC64 2014 2014-10-06         TN -0.0060180723     + #> 7566   2063    3M  CC64 2014 2014-10-06         TP -1.8325814637  <NA> #> 7567   2063    3M  CC64 2014 2014-10-06       TURB  0.4054651081  <NA> #> 7568   2063    3M  CC64 2014 2014-11-03      CHLAC  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3M  CC64 2014 2014-12-01       NO23 -2.7181005370  <NA> #> 7583   2063    3M  CC64 2014 2014-12-01      SALIN  3.0449985149  <NA> #> 7584   2063    3M  CC64 2014 2014-12-01        TKN -0.3566749439  <NA> #> 7585   2063    3M  CC64 2014 2014-12-01         TN -0.2665731092     + #> 7586   2063    3M  CC64 2014 2014-12-01         TP -2.3025850930  <NA> #> 7587   2063    3M  CC64 2014 2014-12-01       TURB  0.4700036292  <NA> #> 7588   2063    3M  CC64 2015 2015-01-05      CHLAC  0.7884573604     A #> 7589   2063    3M  CC64 2015 2015-01-05      COLOR  2.9444389792  <NA> #> 7590   2063    3M  CC64 2015 2015-01-05       NO23 -2.8824035882  <NA> #> 7591   2063    3M  CC64 2015 2015-01-05      SALIN  3.2592497190  <NA> #> 7592   2063    3M  CC64 2015 2015-01-05        TKN -0.5621189182  <NA> #> 7593   2063    3M  CC64 2015 2015-01-05         TN -0.4684049079     + #> 7594   2063    3M  CC64 2015 2015-01-05         TP -2.3025850930  <NA> #> 7595   2063    3M  CC64 2015 2015-01-05       TURB  0.6931471806  <NA> #> 7596   2063    3M  CC64 2015 2015-02-02      CHLAC  0.2623642645     I #> 7597   2063    3M  CC64 2015 2015-02-02      COLOR  2.3025850930  <NA> #> 7598   2063    3M  CC64 2015 2015-02-02      DOSAT  4.3932138241     + #> 7599   2063    3M  CC64 2015 2015-02-02       NO23 -4.3428059215  <NA> #> 7600   2063    3M  CC64 2015 2015-02-02      SALIN  3.3214324132  <NA> #> 7601   2063    3M  CC64 2015 2015-02-02        TKN -0.9942522733     I #> 7602   2063    3M  CC64 2015 2015-02-02         TN -1.7544636845     + #> 7603   2063    3M  CC64 2015 2015-02-02         TP -2.4534079827  <NA> #> 7604   2063    3M  CC64 2015 2015-02-02       TURB  0.7884573604     A #> 7605   2063    3M  CC64 2015 2015-03-02      CHLAC  1.1631508098     A #> 7606   2063    3M  CC64 2015 2015-03-02      COLOR  2.8903717579  <NA> #> 7607   2063    3M  CC64 2015 2015-03-02         DO  1.9430489168  <NA> #> 7608   2063    3M  CC64 2015 2015-03-02      DOSAT  4.5152454785     + #> 7609   2063    3M  CC64 2015 2015-03-02       NO23 -3.1941832123  <NA> #> 7610   2063    3M  CC64 2015 2015-03-02      SALIN  3.2136622578  <NA> #> 7611   2063    3M  CC64 2015 2015-03-02        TKN -0.4942963218  <NA> #> 7612   2063    3M  CC64 2015 2015-03-02         TN -0.4292456368     + #> 7613   2063    3M  CC64 2015 2015-03-02         TP -2.2072749132  <NA> #> 7614   2063    3M  CC64 2015 2015-03-02       TURB  0.8754687374  <NA> #> 7615   2063    3M  CC64 2015 2015-04-06      CHLAC  0.9162907319  <NA> #> 7616   2063    3M  CC64 2015 2015-04-06      COLOR  2.9957322736  <NA> #> 7617   2063    3M  CC64 2015 2015-04-06         DO  1.3558351536  <NA> #> 7618   2063    3M  CC64 2015 2015-04-06      DOSAT  4.0036901940     + #> 7619   2063    3M  CC64 2015 2015-04-06       NO23 -4.6051701860  <NA> #> 7620   2063    3M  CC64 2015 2015-04-06      SALIN  3.2268439945  <NA> #> 7621   2063    3M  CC64 2015 2015-04-06        TKN -0.4462871026  <NA> #> 7622   2063    3M  CC64 2015 2015-04-06         TN 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3M  CC64 2015 2015-06-01         DO  1.0647107370  <NA> #> 7637   2063    3M  CC64 2015 2015-06-01      DOSAT  3.7773481021     + #> 7638   2063    3M  CC64 2015 2015-06-01       NO23 -4.6051701860     I #> 7639   2063    3M  CC64 2015 2015-06-01      SALIN  3.3214324132  <NA> #> 7640   2063    3M  CC64 2015 2015-06-01        TKN -0.5621189182  <NA> #> 7641   2063    3M  CC64 2015 2015-06-01         TN -0.5551258827     + #> 7642   2063    3M  CC64 2015 2015-06-01         TP -2.3025850930  <NA> #> 7643   2063    3M  CC64 2015 2015-06-01       TURB  0.4700036292  <NA> #> 7644   2063    3M  CC64 2015 2015-08-03      CHLAC  2.2407096893  <NA> #> 7645   2063    3M  CC64 2015 2015-08-03      COLOR  4.1588830834  <NA> #> 7646   2063    3M  CC64 2015 2015-08-03         DO  0.7654678421  <NA> #> 7647   2063    3M  CC64 2015 2015-08-03      DOSAT  3.4045251718     + #> 7648   2063    3M  CC64 2015 2015-08-03       NO23 -4.6051701860     I #> 7649   2063    3M  CC64 2015 2015-08-03      SALIN  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3M  CC64 2015 2015-10-05      COLOR  4.5643481915  <NA> #> 7664   2063    3M  CC64 2015 2015-10-05         DO  1.1085626195  <NA> #> 7665   2063    3M  CC64 2015 2015-10-05      DOSAT  3.6888794541     + #> 7666   2063    3M  CC64 2015 2015-10-05       NO23 -3.3524072175  <NA> #> 7667   2063    3M  CC64 2015 2015-10-05      SALIN  2.4069451083  <NA> #> 7668   2063    3M  CC64 2015 2015-10-05        TKN -0.1984509387  <NA> #> 7669   2063    3M  CC64 2015 2015-10-05         TN -0.1566538100     + #> 7670   2063    3M  CC64 2015 2015-10-05         TP -1.5606477483  <NA> #> 7671   2063    3M  CC64 2015 2015-10-05       TURB  0.3364722366     A #> 7672   2063    3M  CC64 2015 2015-12-07      CHLAC  0.9555114450  <NA> #> 7673   2063    3M  CC64 2015 2015-12-07      COLOR  3.4965075615  <NA> #> 7674   2063    3M  CC64 2015 2015-12-07         DO  1.1314021115  <NA> #> 7675   2063    3M  CC64 2015 2015-12-07      DOSAT  3.6988297850     + #> 7676   2063    3M  CC64 2015 2015-12-07       NO23 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3M  CC64 2016 2016-01-04         TP -2.0402208285  <NA> #> 7691   2063    3M  CC64 2016 2016-01-04       TURB  0.9162907319  <NA> #> 7692   2063    3M  CC64 2016 2016-02-01      COLOR  4.1896547420     A #> 7693   2063    3M  CC64 2016 2016-02-01      DOSAT  4.5053498507     + #> 7694   2063    3M  CC64 2016 2016-02-01       NO23 -4.1997050779  <NA> #> 7695   2063    3M  CC64 2016 2016-02-01      SALIN  1.9810014689  <NA> #> 7696   2063    3M  CC64 2016 2016-02-01        TKN -0.5447271754  <NA> #> 7697   2063    3M  CC64 2016 2016-02-01         TN -0.5191938734     + #> 7698   2063    3M  CC64 2016 2016-02-01         TP -2.8473122684  <NA> #> 7699   2063    3M  CC64 2016 2016-02-01       TURB  0.5877866649  <NA> #> 7700   2063    3M  CC64 2016 2016-03-07      CHLAC  0.6418538862     I #> 7701   2063    3M  CC64 2016 2016-03-07      COLOR  3.7841896339  <NA> #> 7702   2063    3M  CC64 2016 2016-03-07       NO23 -4.1997050779  <NA> #> 7703   2063    3M  CC64 2016 2016-03-07      SALIN  2.6159349122  <NA> #> 7704   2063    3M  CC64 2016 2016-03-07        TKN -0.2231435513  <NA> #> 7705   2063    3M  CC64 2016 2016-03-07         TN -0.2045671657     + #> 7706   2063    3M  CC64 2016 2016-03-07         TP -2.3538783874  <NA> #> 7707   2063    3M  CC64 2016 2016-03-07       TURB  0.4700036292  <NA> #> 7708   2063    3M  CC64 2016 2016-04-04      CHLAC  1.2237754316  <NA> #> 7709   2063    3M  CC64 2016 2016-04-04      COLOR  3.3322045102     A #> 7710   2063    3M  CC64 2016 2016-04-04         DO  1.6094379124  <NA> #> 7711   2063    3M  CC64 2016 2016-04-04      DOSAT  4.2061840440     + #> 7712   2063    3M  CC64 2016 2016-04-04       NO23 -3.7297014486  <NA> #> 7713   2063    3M  CC64 2016 2016-04-04      SALIN  2.9236990707  <NA> #> 7714   2063    3M  CC64 2016 2016-04-04         TN -0.3092462504     + #> 7715   2063    3M  CC64 2016 2016-04-04         TP -2.2072749132  <NA> #> 7716   2063    3M  CC64 2016 2016-04-04       TURB  0.7419373447  <NA> #> 7717   2063    3M  CC64 2016 2016-05-02      CHLAC  0.8754687374  <NA> #> 7718   2063    3M  CC64 2016 2016-05-02      COLOR  3.1780538303  <NA> #> 7719   2063    3M  CC64 2016 2016-05-02         DO  1.1631508098  <NA> #> 7720   2063    3M  CC64 2016 2016-05-02      DOSAT  3.8394523126     + #> 7721   2063    3M  CC64 2016 2016-05-02       NO23 -4.5098600062  <NA> #> 7722   2063    3M  CC64 2016 2016-05-02      SALIN  3.1428583384  <NA> #> 7723   2063    3M  CC64 2016 2016-05-02        TKN -0.5276327421  <NA> #> 7724   2063    3M  CC64 2016 2016-05-02         TN -0.5091603444     + #> 7725   2063    3M  CC64 2016 2016-05-02         TP -2.3025850930  <NA> #> 7726   2063    3M  CC64 2016 2016-05-02       TURB  0.6931471806  <NA> #> 7727   2063    3M  CC64 2016 2016-06-06       NO23 -4.6051701860     I #> 7728   2063    3M  CC64 2016 2016-06-06      SALIN  3.2120525995  <NA> #> 7729   2063    3M  CC64 2016 2016-06-06        TKN -0.4462871026  <NA> #> 7730   2063    3M  CC64 2016 2016-06-06         TN 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3M  CC64 2016 2016-08-01         DO  0.9669838462  <NA> #> 7745   2063    3M  CC64 2016 2016-08-01      DOSAT  3.6428355156     + #> 7746   2063    3M  CC64 2016 2016-08-01       NO23 -4.3428059215  <NA> #> 7747   2063    3M  CC64 2016 2016-08-01      SALIN  2.6232182656  <NA> #> 7748   2063    3M  CC64 2016 2016-08-01        TKN -0.1625189295  <NA> #> 7749   2063    3M  CC64 2016 2016-08-01         TN -0.1473405879     + #> 7750   2063    3M  CC64 2016 2016-08-01         TP -1.9661128564  <NA> #> 7751   2063    3M  CC64 2016 2016-08-01       TURB  0.3364722366  <NA> #> 7752   2063    3M  CC64 2016 2016-10-03      CHLAC  1.3350010667  <NA> #> 7753   2063    3M  CC64 2016 2016-10-03      COLOR  3.9702919136  <NA> #> 7754   2063    3M  CC64 2016 2016-10-03         DO  0.7178397932  <NA> #> 7755   2063    3M  CC64 2016 2016-10-03      DOSAT  3.3568971228     + #> 7756   2063    3M  CC64 2016 2016-10-03       NO23 -4.1351665567  <NA> #> 7757   2063    3M  CC64 2016 2016-10-03      SALIN  2.5892666651  <NA> #> 7758   2063    3M  CC64 2016 2016-10-03        TKN -0.4620354596  <NA> #> 7759   2063    3M  CC64 2016 2016-10-03         TN -0.4369557752     + #> 7760   2063    3M  CC64 2016 2016-10-03         TP -1.8325814637  <NA> #> 7761   2063    3M  CC64 2016 2016-10-03       TURB  0.1823215568  <NA> #> 7762   2063    3M  CC64 2016 2016-11-07      CHLAC  0.8754687374  <NA> #> 7763   2063    3M  CC64 2016 2016-11-07      COLOR  2.8332133441     A #> 7764   2063    3M  CC64 2016 2016-11-07         DO  1.3402504226  <NA> #> 7765   2063    3M  CC64 2016 2016-11-07      DOSAT  3.9473901493     + #> 7766   2063    3M  CC64 2016 2016-11-07       NO23 -4.7105307016     I #> 7767   2063    3M  CC64 2016 2016-11-07      SALIN  3.3178157727  <NA> #> 7768   2063    3M  CC64 2016 2016-11-07        TKN -0.4155154440  <NA> #> 7769   2063    3M  CC64 2016 2016-11-07         TN -0.4094731295     + #> 7770   2063    3M  CC64 2016 2016-11-07         TP -2.3330443005  <NA> #> 7771   2063    3M  CC64 2016 2016-11-07       TURB  0.6418538862  <NA> #> 7772   2063    3M  CC64 2016 2016-12-05      CHLAC  2.6390573296  <NA> #> 7773   2063    3M  CC64 2016 2016-12-05      COLOR  2.7080502011  <NA> #> 7774   2063    3M  CC64 2016 2016-12-05         DO  1.6094379124  <NA> #> 7775   2063    3M  CC64 2016 2016-12-05      DOSAT  4.2165621949     + #> 7776   2063    3M  CC64 2016 2016-12-05       NO23 -5.5214609179     U #> 7777   2063    3M  CC64 2016 2016-12-05      SALIN  3.3792925463  <NA> #> 7778   2063    3M  CC64 2016 2016-12-05        TKN -0.3285040670  <NA> #> 7779   2063    3M  CC64 2016 2016-12-05         TN -0.3257301401     + #> 7780   2063    3M  CC64 2016 2016-12-05         TP -1.7147984281  <NA> #> 7781   2063    3M  CC64 2016 2016-12-05       TURB  0.8329091229  <NA> #> 7782   2063    3M  CC64 2017 2017-01-03      CHLAC  0.7419373447  <NA> #> 7783   2063    3M  CC64 2017 2017-01-03      COLOR  2.1860512767  <NA> #> 7784   2063    3M  CC64 2017 2017-01-03         DO  1.6292405397  <NA> #> 7785   2063    3M  CC64 2017 2017-01-03      DOSAT  4.2370008626     + #> 7786   2063    3M  CC64 2017 2017-01-03       NO23 -5.5214609179     U #> 7787   2063    3M  CC64 2017 2017-01-03      SALIN  3.3911470458  <NA> #> 7788   2063    3M  CC64 2017 2017-01-03        TKN -0.6733445533  <NA> #> 7789   2063    3M  CC64 2017 2017-01-03         TN -0.6694306539     + #> 7790   2063    3M  CC64 2017 2017-01-03         TP -2.3751557858  <NA> #> 7791   2063    3M  CC64 2017 2017-01-03       TURB  0.4700036292  <NA> #> 7792   2063    3M  CC64 2017 2017-02-06      CHLAC  1.3083328197  <NA> #> 7793   2063    3M  CC64 2017 2017-02-06      COLOR  2.2300144002  <NA> #> 7794   2063    3M  CC64 2017 2017-02-06         DO  1.6770965609  <NA> #> 7795   2063    3M  CC64 2017 2017-02-06      DOSAT  4.2654928184     + #> 7796   2063    3M  CC64 2017 2017-02-06       NO23 -3.3242363405  <NA> #> 7797   2063    3M  CC64 2017 2017-02-06      SALIN  3.3965197921  <NA> #> 7798   2063    3M  CC64 2017 2017-02-06        TKN -0.3566749439  <NA> #> 7799   2063    3M  CC64 2017 2017-02-06         TN -0.3065251603     + #> 7800   2063    3M  CC64 2017 2017-02-06         TP -2.4418471603  <NA> #> 7801   2063    3M  CC64 2017 2017-02-06       TURB  0.9555114450  <NA> #> 7802   2063    3M  CC64 2017 2017-03-06      CHLAC  1.2237754316  <NA> #> 7803   2063    3M  CC64 2017 2017-03-06      COLOR  1.7917594692  <NA> #> 7804   2063    3M  CC64 2017 2017-03-06         DO  1.6770965609  <NA> #> 7805   2063    3M  CC64 2017 2017-03-06      DOSAT  4.2598590007     + #> 7806   2063    3M  CC64 2017 2017-03-06       NO23 -5.1159958098     I #> 7807   2063    3M  CC64 2017 2017-03-06      SALIN  3.4124669739  <NA> #> 7808   2063    3M  CC64 2017 2017-03-06        TKN -0.5798184953  <NA> #> 7809   2063    3M  CC64 2017 2017-03-06         TN -0.5727010275     + #> 7810   2063    3M  CC64 2017 2017-03-06         TP -2.5257286443  <NA> #> 7811   2063    3M  CC64 2017 2017-03-06       TURB  0.9932517730  <NA> #> 7812   2063    3M  CC64 2017 2017-04-03      CHLAC  1.4586150227  <NA> #> 7813   2063    3M  CC64 2017 2017-04-03      COLOR  2.3978952728  <NA> #> 7814   2063    3M  CC64 2017 2017-04-03         DO  1.3635373740  <NA> #> 7815   2063    3M  CC64 2017 2017-04-03      DOSAT  4.0638853547     + #> 7816   2063    3M  CC64 2017 2017-04-03       NO23 -4.9618451299     I #> 7817   2063    3M  CC64 2017 2017-04-03      SALIN  3.5115454388  <NA> #> 7818   2063    3M  CC64 2017 2017-04-03        TKN -0.3424903089  <NA> #> 7819   2063    3M  CC64 2017 2017-04-03         TN -0.3368723166     + #> 7820   2063    3M  CC64 2017 2017-04-03         TP -2.4769384801  <NA> #> 7821   2063    3M  CC64 2017 2017-04-03       TURB  0.8754687374  <NA> #> 7822   2063    3M  CC64 2017 2017-05-01      CHLAC  1.0296194172  <NA> #> 7823   2063    3M  CC64 2017 2017-05-01      COLOR  2.6390573296  <NA> #> 7824   2063    3M  CC64 2017 2017-05-01         DO  1.3480731483  <NA> #> 7825   2063    3M  CC64 2017 2017-05-01      DOSAT  4.0604430105     + #> 7826   2063    3M  CC64 2017 2017-05-01       NO23 -5.5214609179     U #> 7827   2063    3M  CC64 2017 2017-05-01      SALIN  3.5377658244  <NA> #> 7828   2063    3M  CC64 2017 2017-05-01        TKN -0.2876820725  <NA> #> 7829   2063    3M  CC64 2017 2017-05-01         TN -0.2850189550     + #> 7830   2063    3M  CC64 2017 2017-05-01         TP -2.6736487744  <NA> #> 7831   2063    3M  CC64 2017 2017-05-01       TURB  0.7419373447  <NA> #> 7832   2063    3M  CC64 2017 2017-06-05      CHLAC  1.3862943611     A #> 7833   2063    3M  CC64 2017 2017-06-05      COLOR  2.7080502011  <NA> #> 7834   2063    3M  CC64 2017 2017-06-05         DO  2.1294214740  <NA> #> 7835   2063    3M  CC64 2017 2017-06-05      DOSAT  4.8835592115     + #> 7836   2063    3M  CC64 2017 2017-06-05       NO23 -4.5098600062  <NA> #> 7837   2063    3M  CC64 2017 2017-06-05      SALIN  3.5322256441  <NA> #> 7838   2063    3M  CC64 2017 2017-06-05        TKN 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3M  CC64 2017 2017-08-07      CHLAC  1.5892352051  <NA> #> 7853   2063    3M  CC64 2017 2017-08-07      COLOR  4.5747109785     A #> 7854   2063    3M  CC64 2017 2017-08-07         DO  0.4121096508  <NA> #> 7855   2063    3M  CC64 2017 2017-08-07      DOSAT  3.0349529867     + #> 7856   2063    3M  CC64 2017 2017-08-07       NO23 -3.7297014486  <NA> #> 7857   2063    3M  CC64 2017 2017-08-07      SALIN  2.0693912058  <NA> #> 7858   2063    3M  CC64 2017 2017-08-07        TKN -0.0202027073  <NA> #> 7859   2063    3M  CC64 2017 2017-08-07         TN  0.0039920213     + #> 7860   2063    3M  CC64 2017 2017-08-07         TP -1.6607312068  <NA> #> 7861   2063    3M  CC64 2017 2017-08-07       TURB  0.6931471806  <NA> #> 7862   2063    3M  CC64 2017 2017-09-05      CHLAC  1.6094379124  <NA> #> 7863   2063    3M  CC64 2017 2017-09-05      COLOR  4.7874917428  <NA> #> 7864   2063    3M  CC64 2017 2017-09-05         DO  0.8586616190  <NA> #> 7865   2063    3M  CC64 2017 2017-09-05      DOSAT  3.4404180948     + #> 7866   2063    3M  CC64 2017 2017-09-05       NO23 -3.0159349809  <NA> #> 7867   2063    3M  CC64 2017 2017-09-05      SALIN  0.9001613499  <NA> #> 7868   2063    3M  CC64 2017 2017-09-05        TKN -0.1508228897  <NA> #> 7869   2063    3M  CC64 2017 2017-09-05         TN -0.0954101848     + #> 7870   2063    3M  CC64 2017 2017-09-05         TP -2.0402208285  <NA> #> 7871   2063    3M  CC64 2017 2017-09-05       TURB  0.5877866649  <NA> #> 7872   2063    3M  CC64 2017 2017-10-02      CHLAC  1.3083328197  <NA> #> 7873   2063    3M  CC64 2017 2017-10-02      COLOR  4.4998096703  <NA> #> 7874   2063    3M  CC64 2017 2017-10-02       NO23 -3.1465551633  <NA> #> 7875   2063    3M  CC64 2017 2017-10-02        TKN -0.9675840263  <NA> #> 7876   2063    3M  CC64 2017 2017-10-02         TN -0.8603830999     + #> 7877   2063    3M  CC64 2017 2017-10-02         TP -1.6094379124  <NA> #> 7878   2063    3M  CC64 2017 2017-10-02       TURB  0.3364722366  <NA> #> 7879   2063    3M  CC64 2017 2017-11-06      CHLAC  0.7419373447  <NA> #> 7880   2063    3M  CC64 2017 2017-11-06      COLOR  3.5835189385  <NA> #> 7881   2063    3M  CC64 2017 2017-11-06         DO  2.0014800002  <NA> #> 7882   2063    3M  CC64 2017 2017-11-06      DOSAT  4.5890408041     + #> 7883   2063    3M  CC64 2017 2017-11-06       NO23 -3.4420193762  <NA> #> 7884   2063    3M  CC64 2017 2017-11-06      SALIN  3.0864866368  <NA> #> 7885   2063    3M  CC64 2017 2017-11-06        TKN -0.5798184953  <NA> #> 7886   2063    3M  CC64 2017 2017-11-06         TN -0.5242486441     + #> 7887   2063    3M  CC64 2017 2017-11-06         TP -1.8971199849  <NA> #> 7888   2063    3M  CC64 2017 2017-11-06       TURB  0.3364722366  <NA> #> 7889   2063    3M  CC64 2017 2017-12-04      CHLAC  0.9162907319  <NA> #> 7890   2063    3M  CC64 2017 2017-12-04      COLOR  3.1780538303  <NA> #> 7891   2063    3M  CC64 2017 2017-12-04         DO  1.5644405465  <NA> #> 7892   2063    3M  CC64 2017 2017-12-04      DOSAT  4.1287459889  <NA> #> 7893   2063    3M  CC64 2017 2017-12-04       NO23 -4.5098600062  <NA> #> 7894   2063    3M  CC64 2017 2017-12-04      SALIN  3.3403852423  <NA> #> 7895   2063    3M  CC64 2017 2017-12-04        TKN -0.5276327421  <NA> #> 7896   2063    3M  CC64 2017 2017-12-04         TN -0.5091603444     + #> 7897   2063    3M  CC64 2017 2017-12-04         TP -2.2072749132  <NA> #> 7898   2063    3M  CC64 2017 2017-12-04       TURB  0.3364722366  <NA> #> 7899   2063    3M  CC64 2018 2018-01-02      CHLAC  2.7725887222  <NA> #> 7900   2063    3M  CC64 2018 2018-01-02      COLOR  3.0910424534  <NA> #> 7901   2063    3M  CC64 2018 2018-01-02      DOSAT  4.0360089852     + #> 7902   2063    3M  CC64 2018 2018-01-02       NO23 -5.5214609179     U #> 7903   2063    3M  CC64 2018 2018-01-02      SALIN  3.2657594108  <NA> #> 7904   2063    3M  CC64 2018 2018-01-02        TKN -0.3147107448  <NA> #> 7905   2063    3M  CC64 2018 2018-01-02         TN -0.3119747650     + #> 7906   2063    3M  CC64 2018 2018-01-02         TP -1.6607312068  <NA> #> 7907   2063    3M  CC64 2018 2018-01-02       TURB  2.3978952728  <NA> #> 7908   2063    3M  CC64 2018 2018-03-05      CHLAC  0.5306282511     I #> 7909   2063    3M  CC64 2018 2018-03-05      COLOR  2.6390573296  <NA> #> 7910   2063    3M  CC64 2018 2018-03-05      DOSAT  4.2416144810  <NA> #> 7911   2063    3M  CC64 2018 2018-03-05       NO23 -5.5214609179     I #> 7912   2063    3M  CC64 2018 2018-03-05      SALIN  3.3467411959  <NA> #> 7913   2063    3M  CC64 2018 2018-03-05        TKN -0.5621189182  <NA> #> 7914   2063    3M  CC64 2018 2018-03-05         TN -0.5551258827     + #> 7915   2063    3M  CC64 2018 2018-03-05         TP -2.1202635362  <NA> #> 7916   2063    3M  CC64 2018 2018-03-05       TURB  0.4700036292  <NA> #> 7917   2063    3M  CC64 2018 2018-04-02      CHLAC  0.7419373447  <NA> #> 7918   2063    3M  CC64 2018 2018-04-02      COLOR  2.3978952728  <NA> #> 7919   2063    3M  CC64 2018 2018-04-02         DO  1.5040773968  <NA> #> 7920   2063    3M  CC64 2018 2018-04-02      DOSAT  3.4307561839  <NA> #> 7921   2063    3M  CC64 2018 2018-04-02       NO23 -4.9618451299     I #> 7922   2063    3M  CC64 2018 2018-04-02      SALIN  3.4330189940  <NA> #> 7923   2063    3M  CC64 2018 2018-04-02        TKN -0.6539264674  <NA> #> 7924   2063    3M  CC64 2018 2018-04-02         TN -0.6462635947     + #> 7925   2063    3M  CC64 2018 2018-04-02         TP -2.2072749132  <NA> #> 7926   2063    3M  CC64 2018 2018-04-02       TURB  0.7884573604  <NA> #> 7927   2063    3M  CC64 2018 2018-05-07      CHLAC  1.4350845253  <NA> #> 7928   2063    3M  CC64 2018 2018-05-07      COLOR  2.5649493575  <NA> #> 7929   2063    3M  CC64 2018 2018-05-07         DO  1.3962446920  <NA> #> 7930   2063    3M  CC64 2018 2018-05-07      DOSAT  4.0842942264  <NA> #> 7931   2063    3M  CC64 2018 2018-05-07       NO23 -5.1159958098     I #> 7932   2063    3M  CC64 2018 2018-05-07      SALIN  3.4388142452  <NA> #> 7933   2063    3M  CC64 2018 2018-05-07        TKN -0.3424903089  <NA> #> 7934   2063    3M  CC64 2018 2018-05-07         TN -0.3368723166     + #> 7935   2063    3M  CC64 2018 2018-05-07         TP -2.0402208285  <NA> #> 7936   2063    3M  CC64 2018 2018-05-07       TURB  1.0986122887  <NA> #> 7937   2063    3M  CC64 2018 2018-07-09      CHLAC  0.9555114450  <NA> #> 7938   2063    3M  CC64 2018 2018-07-09      COLOR  4.5747109785  <NA> #> 7939   2063    3M  CC64 2018 2018-07-09         DO  0.6312717768  <NA> #> 7940   2063    3M  CC64 2018 2018-07-09      DOSAT  3.2308043957  <NA> #> 7941   2063    3M  CC64 2018 2018-07-09       NO23 -3.6119184130  <NA> #> 7942   2063    3M  CC64 2018 2018-07-09      SALIN  1.8640801308  <NA> #> 7943   2063    3M  CC64 2018 2018-07-09        TKN  0.0000000000  <NA> #> 7944   2063    3M  CC64 2018 2018-07-09         TN  0.0266419309     + #> 7945   2063    3M  CC64 2018 2018-07-09         TP -2.3025850930  <NA> #> 7946   2063    3M  CC64 2018 2018-07-09       TURB  0.1823215568  <NA> #> 7947   2063    3M  CC64 2018 2018-08-06      CHLAC  1.0986122887  <NA> #> 7948   2063    3M  CC64 2018 2018-08-06      COLOR  4.5951198501  <NA> #> 7949   2063    3M  CC64 2018 2018-08-06         DO  0.8796267475  <NA> #> 7950   2063    3M  CC64 2018 2018-08-06      DOSAT  3.4339872045  <NA> #> 7951   2063    3M  CC64 2018 2018-08-06       NO23 -3.4737680745  <NA> #> 7952   2063    3M  CC64 2018 2018-08-06      SALIN  1.6448050563  <NA> #> 7953   2063    3M  CC64 2018 2018-08-06        TKN -0.1508228897  <NA> #> 7954   2063    3M  CC64 2018 2018-08-06         TN -0.1154108515     + #> 7955   2063    3M  CC64 2018 2018-08-06         TP -2.3227878003  <NA> #> 7956   2063    3M  CC64 2018 2018-08-06       TURB  0.5877866649  <NA> #> 7957   2063    3M  CC64 2019 2019-02-04      CHLAC  1.1314021115  <NA> #> 7958   2063    3M  CC64 2019 2019-02-04      COLOR  3.0910424534  <NA> #> 7959   2063    3M  CC64 2019 2019-02-04         DO  1.8764069433  <NA> #> 7960   2063    3M  CC64 2019 2019-02-04      DOSAT  4.4200447019  <NA> #> 7961   2063    3M  CC64 2019 2019-02-04       NO23 -4.8283137373     I #> 7962   2063    3M  CC64 2019 2019-02-04      SALIN  3.0928589843  <NA> #> 7963   2063    3M  CC64 2019 2019-02-04        TKN -0.7765287895  <NA> #> 7964   2063    3M  CC64 2019 2019-02-04         TN -0.7678707268     + #> 7965   2063    3M  CC64 2019 2019-02-04         TP -2.3025850930  <NA> #> 7966   2063    3M  CC64 2019 2019-02-04       TURB  0.6418538862  <NA> #> 7967   2063    3M  CC64 2019 2019-03-04      CHLAC  0.8329091229  <NA> #> 7968   2063    3M  CC64 2019 2019-03-04      COLOR  3.1354942159  <NA> #> 7969   2063    3M  CC64 2019 2019-03-04         DO  1.6014057407  <NA> #> 7970   2063    3M  CC64 2019 2019-03-04      DOSAT  4.2297491992  <NA> #> 7971   2063    3M  CC64 2019 2019-03-04       NO23 -4.8283137373     I #> 7972   2063    3M  CC64 2019 2019-03-04      SALIN  2.9992261628  <NA> #> 7973   2063    3M  CC64 2019 2019-03-04        TKN -0.5798184953  <NA> #> 7974   2063    3M  CC64 2019 2019-03-04         TN -0.5727010275     + #> 7975   2063    3M  CC64 2019 2019-03-04         TP -2.3025850930  <NA> #> 7976   2063    3M  CC64 2019 2019-03-04       TURB  0.5306282511  <NA> #> 7977   2063    3M  CC64 2019 2019-04-01      CHLAC  0.4700036292     I #> 7978   2063    3M  CC64 2019 2019-04-01      COLOR  2.7725887222  <NA> #> 7979   2063    3M  CC64 2019 2019-04-01         DO  1.3962446920  <NA> #> 7980   2063    3M  CC64 2019 2019-04-01      DOSAT  3.9889840466  <NA> #> 7981   2063    3M  CC64 2019 2019-04-01       NO23 -4.5098600062  <NA> #> 7982   2063    3M  CC64 2019 2019-04-01      SALIN  3.1210424645  <NA> #> 7983   2063    3M  CC64 2019 2019-04-01        TKN -0.5276327421  <NA> #> 7984   2063    3M  CC64 2019 2019-04-01         TN -0.5091603444     + #> 7985   2063    3M  CC64 2019 2019-04-01         TP -2.3126354288  <NA> #> 7986   2063    3M  CC64 2019 2019-04-01       TURB  0.4700036292  <NA> #> 7987   2063    3M  CC64 2019 2019-05-06      CHLAC  0.6931471806     I #> 7988   2063    3M  CC64 2019 2019-05-06      COLOR  2.9444389792  <NA> #> 7989   2063    3M  CC64 2019 2019-05-06         DO  0.8372475245  <NA> #> 7990   2063    3M  CC64 2019 2019-05-06      DOSAT  3.5292973843  <NA> #> 7991   2063    3M  CC64 2019 2019-05-06       NO23 -4.6051701860     I #> 7992   2063    3M  CC64 2019 2019-05-06      SALIN  3.2331731296  <NA> #> 7993   2063    3M  CC64 2019 2019-05-06        TKN -0.5621189182  <NA> #> 7994   2063    3M  CC64 2019 2019-05-06         TN -0.5551258827     + #> 7995   2063    3M  CC64 2019 2019-05-06         TP -2.2072749132  <NA> #> 7996   2063    3M  CC64 2019 2019-05-06       TURB  0.2623642645  <NA> #> 7997   2063    3M  CC64 2019 2019-06-03      CHLAC  0.7419373447     I #> 7998   2063    3M  CC64 2019 2019-06-03      COLOR  2.8903717579  <NA> #> 7999   2063    3M  CC64 2019 2019-06-03         DO  1.2974631474  <NA> #> 8000   2063    3M  CC64 2019 2019-06-03      DOSAT  3.7220724215  <NA> #> 8001   2063    3M  CC64 2019 2019-06-03       NO23 -5.2983173665     I #> 8002   2063    3M  CC64 2019 2019-06-03      SALIN  3.2703291065  <NA> #> 8003   2063    3M  CC64 2019 2019-06-03        TKN -0.3856624808  <NA> #> 8004   2063    3M  CC64 2019 2019-06-03         TN -0.3797973614     + #> 8005   2063    3M  CC64 2019 2019-06-03         TP -2.3025850930  <NA> #> 8006   2063    3M  CC64 2019 2019-06-03       TURB  0.2623642645  <NA> #> 8007   2063    3M  CC64 2019 2019-07-01      CHLAC  1.0986122887  <NA> #> 8008   2063    3M  CC64 2019 2019-07-01      COLOR  2.8903717579  <NA> #> 8009   2063    3M  CC64 2019 2019-07-01         DO  1.4036429995  <NA> #> 8010   2063    3M  CC64 2019 2019-07-01      DOSAT  4.1108738642  <NA> #> 8011   2063    3M  CC64 2019 2019-07-01       NO23 -5.1159958098     I #> 8012   2063    3M  CC64 2019 2019-07-01      SALIN  3.1675825305  <NA> #> 8013   2063    3M  CC64 2019 2019-07-01        TKN -0.4780358009  <NA> #> 8014   2063    3M  CC64 2019 2019-07-01         TN -0.4716049106     + #> 8015   2063    3M  CC64 2019 2019-07-01         TP -2.2072749132  <NA> #> 8016   2063    3M  CC64 2019 2019-07-01       TURB  0.5877866649  <NA> #> 8017   2063    3M  CC64 2019 2019-08-05      CHLAC  1.7578579176  <NA> #> 8018   2063    3M  CC64 2019 2019-08-05      COLOR  3.9120230054  <NA> #> 8019   2063    3M  CC64 2019 2019-08-05         DO  1.3001916621  <NA> #> 8020   2063    3M  CC64 2019 2019-08-05      DOSAT  3.9702919136  <NA> #> 8021   2063    3M  CC64 2019 2019-08-05       NO23 -5.5214609179     U #> 8022   2063    3M  CC64 2019 2019-08-05      SALIN  2.8273136219  <NA> #> 8023   2063    3M  CC64 2019 2019-08-05        TKN -0.1863295782  <NA> #> 8024   2063    3M  CC64 2019 2019-08-05         TN -0.1839228382     + #> 8025   2063    3M  CC64 2019 2019-08-05         TP -1.8325814637  <NA> #> 8026   2063    3M  CC64 2019 2019-08-05       TURB  0.4700036292  <NA> #> 8027   2063    3M  CC64 2019 2019-10-07      CHLAC  1.1939224685  <NA> #> 8028   2063    3M  CC64 2019 2019-10-07      COLOR  3.2958368660  <NA> #> 8029   2063    3M  CC64 2019 2019-10-07         DO  1.6863989536  <NA> #> 8030   2063    3M  CC64 2019 2019-10-07      DOSAT  4.3412046402  <NA> #> 8031   2063    3M  CC64 2019 2019-10-07       NO23 -5.1159958098     I #> 8032   2063    3M  CC64 2019 2019-10-07      SALIN  3.2672849641  <NA> #> 8033   2063    3M  CC64 2019 2019-10-07        TKN -0.4780358009  <NA> #> 8034   2063    3M  CC64 2019 2019-10-07         TN -0.4716049106     + #> 8035   2063    3M  CC64 2019 2019-10-07         TP -2.1202635362  <NA> #> 8036   2063    3M  CC64 2019 2019-10-07       TURB  0.2623642645  <NA> #> 8037   2063    3M  CC64 2019 2019-11-04      CHLAC  1.1939224685  <NA> #> 8038   2063    3M  CC64 2019 2019-11-04      COLOR  3.1354942159  <NA> #> 8039   2063    3M  CC64 2019 2019-11-04         DO  1.3110318766  <NA> #> 8040   2063    3M  CC64 2019 2019-11-04      DOSAT  3.9646154555  <NA> #> 8041   2063    3M  CC64 2019 2019-11-04       NO23 -4.6051701860  <NA> #> 8042   2063    3M  CC64 2019 2019-11-04      SALIN  3.2503744919  <NA> #> 8043   2063    3M  CC64 2019 2019-11-04        TKN -0.4307829161  <NA> #> 8044   2063    3M  CC64 2019 2019-11-04         TN -0.4155154440     + #> 8045   2063    3M  CC64 2019 2019-11-04         TP -2.1202635362  <NA> #> 8046   2063    3M  CC64 2019 2019-11-04       TURB  0.0953101798  <NA> #> 8047   2063    3M  CC64 2020 2020-01-06      CHLAC  1.0296194172  <NA> #> 8048   2063    3M  CC64 2020 2020-01-06      COLOR  2.8332133441  <NA> #> 8049   2063    3M  CC64 2020 2020-01-06         DO  1.6937790609  <NA> #> 8050   2063    3M  CC64 2020 2020-01-06      DOSAT  4.2312037449  <NA> #> 8051   2063    3M  CC64 2020 2020-01-06       NO23 -4.0745419349  <NA> #> 8052   2063    3M  CC64 2020 2020-01-06      SALIN  3.2188758249  <NA> #> 8053   2063    3M  CC64 2020 2020-01-06        TKN -0.4155154440  <NA> #> 8054   2063    3M  CC64 2020 2020-01-06         TN 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3M  CC64 2020 2020-03-02      COLOR  2.5649493575     A #> 8069   2063    3M  CC64 2020 2020-03-02         DO  1.7749523509  <NA> #> 8070   2063    3M  CC64 2020 2020-03-02      DOSAT  4.3067641502  <NA> #> 8071   2063    3M  CC64 2020 2020-03-02       NO23 -5.5214609179     I #> 8072   2063    3M  CC64 2020 2020-03-02      SALIN  3.2924979647  <NA> #> 8073   2063    3M  CC64 2020 2020-03-02        TKN -0.8915981193  <NA> #> 8074   2063    3M  CC64 2020 2020-03-02         TN -0.8818893052     + #> 8075   2063    3M  CC64 2020 2020-03-02         TP -2.3968957725  <NA> #> 8076   2063    3M  CC64 2020 2020-03-02       TURB  0.2623642645  <NA> #> 8077   2063    3M  CC64 2020 2020-09-08      CHLAC  2.3025850930     A #> 8078   2063    3M  CC64 2020 2020-09-08      COLOR  4.0253516907  <NA> #> 8079   2063    3M  CC64 2020 2020-09-08         DO  0.1484200051  <NA> #> 8080   2063    3M  CC64 2020 2020-09-08      DOSAT  2.8332133441  <NA> #> 8081   2063    3M  CC64 2020 2020-09-08       NO23 -5.1159958098     I #> 8082   2063    3M  CC64 2020 2020-09-08      SALIN  2.9693882982  <NA> #> 8083   2063    3M  CC64 2020 2020-09-08        TKN -0.2231435513  <NA> #> 8084   2063    3M  CC64 2020 2020-09-08         TN -0.2181560098     + #> 8085   2063    3M  CC64 2020 2020-09-08         TP -1.5141277326  <NA> #> 8086   2063    3M  CC64 2020 2020-09-08       TURB  0.5306282511  <NA> #> 8087   2063    3M  CC64 2020 2020-10-05      CHLAC  1.5040773968  <NA> #> 8088   2063    3M  CC64 2020 2020-10-05      COLOR  4.2626798770  <NA> #> 8089   2063    3M  CC64 2020 2020-10-05         DO  1.1600209168  <NA> #> 8090   2063    3M  CC64 2020 2020-10-05      DOSAT  3.7495040759  <NA> #> 8091   2063    3M  CC64 2020 2020-10-05       NO23 -3.0365542681  <NA> #> 8092   2063    3M  CC64 2020 2020-10-05      SALIN  2.5649493575  <NA> #> 8093   2063    3M  CC64 2020 2020-10-05        TKN -0.0408219945  <NA> #> 8094   2063    3M  CC64 2020 2020-10-05         TN  0.0079681696     + #> 8095   2063    3M  CC64 2020 2020-10-05         TP -1.8971199849  <NA> #> 8096   2063    3M  CC64 2020 2020-10-05       TURB  0.0953101798  <NA> #> 8097   2063    3M  CC64 2020 2020-11-02      CHLAC  1.1631508098     I #> 8098   2063    3M  CC64 2020 2020-11-02      COLOR  4.0073331852     A #> 8099   2063    3M  CC64 2020 2020-11-02       NO23 -3.9633162998  <NA> #> 8100   2063    3M  CC64 2020 2020-11-02      SALIN  2.7562052430  <NA> #> 8101   2063    3M  CC64 2020 2020-11-02        TKN -0.3710636814  <NA> #> 8102   2063    3M  CC64 2020 2020-11-02         TN -0.3438997525     + #> 8103   2063    3M  CC64 2020 2020-11-02         TP -2.0402208285  <NA> #> 8104   2063    3M  CC64 2020 2020-11-02       TURB  0.2623642645  <NA> #> 8105   2063    3M  CC64 2020 2020-12-07      CHLAC  0.3364722366     I #> 8106   2063    3M  CC64 2020 2020-12-07      COLOR  3.6635616461  <NA> #> 8107   2063    3M  CC64 2020 2020-12-07         DO  1.6677068206  <NA> #> 8108   2063    3M  CC64 2020 2020-12-07      DOSAT  4.1743872699  <NA> #> 8109   2063    3M  CC64 2020 2020-12-07       NO23 -3.8167128256  <NA> #> 8110   2063    3M  CC64 2020 2020-12-07      SALIN  2.9982291538  <NA> #> 8111   2063    3M  CC64 2020 2020-12-07        TKN -0.3856624808  <NA> #> 8112   2063    3M  CC64 2020 2020-12-07         TN -0.3538218750     + #> 8113   2063    3M  CC64 2020 2020-12-07         TP -2.4769384801  <NA> #> 8114   2063    3M  CC64 2020 2020-12-07       TURB  0.1823215568  <NA> #> 8115   2063    3M  CC64 2021 2021-01-04      CHLAC  0.3364722366     I #> 8116   2063    3M  CC64 2021 2021-01-04      COLOR  3.1780538303  <NA> #> 8117   2063    3M  CC64 2021 2021-01-04         DO  1.4816045409  <NA> #> 8118   2063    3M  CC64 2021 2021-01-04      DOSAT  4.0271358125  <NA> #> 8119   2063    3M  CC64 2021 2021-01-04       NO23 -4.1351665567  <NA> #> 8120   2063    3M  CC64 2021 2021-01-04      SALIN  3.1376657694  <NA> #> 8121   2063    3M  CC64 2021 2021-01-04        TKN -0.5276327421  <NA> #> 8122   2063    3M  CC64 2021 2021-01-04         TN -0.5008752929     + #> 8123   2063    3M  CC64 2021 2021-01-04         TP -2.3025850930  <NA> #> 8124   2063    3M  CC64 2021 2021-01-04       TURB  0.2623642645  <NA> #> 8125   2063    3M  CC64 2021 2021-02-01      CHLAC  0.9932517730  <NA> #> 8126   2063    3M  CC64 2021 2021-02-01      COLOR  2.8332133441  <NA> #> 8127   2063    3M  CC64 2021 2021-02-01         DO  1.8082887712  <NA> #> 8128   2063    3M  CC64 2021 2021-02-01      DOSAT  4.3489867806  <NA> #> 8129   2063    3M  CC64 2021 2021-02-01       NO23 -4.9618451299     I #> 8130   2063    3M  CC64 2021 2021-02-01      SALIN  3.2120525995  <NA> #> 8131   2063    3M  CC64 2021 2021-02-01        TKN -0.5276327421  <NA> #> 8132   2063    3M  CC64 2021 2021-02-01         TN -0.5208759596     + #> 8133   2063    3M  CC64 2021 2021-02-01         TP -2.3751557858  <NA> #> 8134   2063    3M  CC64 2021 2021-02-01       TURB  1.1631508098  <NA> #> 8135   2063    3M  CC64 2021 2021-03-01      CHLAC  0.6418538862     I #> 8136   2063    3M  CC64 2021 2021-03-01      COLOR  2.6390573296  <NA> #> 8137   2063    3M  CC64 2021 2021-03-01         DO  1.5454325825  <NA> #> 8138   2063    3M  CC64 2021 2021-03-01      DOSAT  4.1956970565  <NA> #> 8139   2063    3M  CC64 2021 2021-03-01       NO23 -4.8283137373     I #> 8140   2063    3M  CC64 2021 2021-03-01      SALIN  3.2861605717  <NA> #> 8141   2063    3M  CC64 2021 2021-03-01        TKN -0.9675840263     I #> 8142   2063    3M  CC64 2021 2021-03-01         TN -1.8078888512     + #> 8143   2063    3M  CC64 2021 2021-03-01         TP -2.3859667019  <NA> #> 8144   2063    3M  CC64 2021 2021-03-01       TURB  0.6931471806     A #> 8145   2063    3M  CC64 2021 2021-04-05      CHLAC  1.5475625087  <NA> #> 8146   2063    3M  CC64 2021 2021-04-05      COLOR  2.7080502011  <NA> #> 8147   2063    3M  CC64 2021 2021-04-05         DO  1.6505798558  <NA> #> 8148   2063    3M  CC64 2021 2021-04-05      DOSAT  4.2370008626  <NA> #> 8149   2063    3M  CC64 2021 2021-04-05       NO23 -5.5214609179     U #> 8150   2063    3M  CC64 2021 2021-04-05      SALIN  3.3010086544  <NA> #> 8151   2063    3M  CC64 2021 2021-04-05         TN -0.4277107171     + #> 8152   2063    3M  CC64 2021 2021-04-05         TP -2.2072749132  <NA> #> 8153   2063    3M  CC64 2021 2021-04-05       TURB  1.2527629685  <NA> #> 8154   2063    3M  CC64 2021 2021-05-03      CHLAC  0.9932517730  <NA> #> 8155   2063    3M  CC64 2021 2021-05-03      COLOR  2.9957322736  <NA> #> 8156   2063    3M  CC64 2021 2021-05-03         DO  1.2584609896  <NA> #> 8157   2063    3M  CC64 2021 2021-05-03      DOSAT  3.9740583963  <NA> #> 8158   2063    3M  CC64 2021 2021-05-03       NO23 -5.5214609179     U #> 8159   2063    3M  CC64 2021 2021-05-03      SALIN  3.3641875560  <NA> #> 8160   2063    3M  CC64 2021 2021-05-03        TKN -0.7133498879  <NA> #> 8161   2063    3M  CC64 2021 2021-05-03         TN -0.7092765625     + #> 8162   2063    3M  CC64 2021 2021-05-03         TP 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3M  CC64 2021 2021-08-02         DO  1.4255150743  <NA> #> 8177   2063    3M  CC64 2021 2021-08-02      DOSAT  4.1092331747  <NA> #> 8178   2063    3M  CC64 2021 2021-08-02       NO23 -4.8283137373     I #> 8179   2063    3M  CC64 2021 2021-08-02      SALIN  2.4292177439  <NA> #> 8180   2063    3M  CC64 2021 2021-08-02        TKN -0.1278333715  <NA> #> 8181   2063    3M  CC64 2021 2021-08-02         TN -0.1232982163     + #> 8182   2063    3M  CC64 2021 2021-08-02         TP -1.7719568419  <NA> #> 8183   2063    3M  CC64 2021 2021-08-02       TURB  0.6418538862  <NA> #> 8184   2063    3M  CC64 2021 2021-09-07      CHLAC  0.9555114450  <NA> #> 8185   2063    3M  CC64 2021 2021-09-07      COLOR  4.1271343850  <NA> #> 8186   2063    3M  CC64 2021 2021-09-07         DO  0.9820784724  <NA> #> 8187   2063    3M  CC64 2021 2021-09-07      DOSAT  3.6375861597  <NA> #> 8188   2063    3M  CC64 2021 2021-09-07       NO23 -3.8167128256  <NA> #> 8189   2063    3M  CC64 2021 2021-09-07      SALIN  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3M  CC64 2022 2022-09-06       TURB  0.7419373447  <NA> #> 8312   2063    3M  CC64 2022 2022-11-07      CHLAC  0.8754687374     I #> 8313   2063    3M  CC64 2022 2022-11-07      COLOR  4.2341065046  <NA> #> 8314   2063    3M  CC64 2022 2022-11-07         DO  0.9360933592  <NA> #> 8315   2063    3M  CC64 2022 2022-11-07      DOSAT  3.5263605246  <NA> #> 8316   2063    3M  CC64 2022 2022-11-07       NO23 -3.2968373663  <NA> #> 8317   2063    3M  CC64 2022 2022-11-07      SALIN  2.6049094422  <NA> #> 8318   2063    3M  CC64 2022 2022-11-07        TKN -0.2744368457  <NA> #> 8319   2063    3M  CC64 2022 2022-11-07         TN -0.2269006002     + #> 8320   2063    3M  CC64 2022 2022-11-07         TP -1.7147984281  <NA> #> 8321   2063    3M  CC64 2022 2022-11-07       TURB  0.1823215568  <NA> #> 8322   2063    3M  CC64 2022 2022-12-05      CHLAC  1.0296194172  <NA> #> 8323   2063    3M  CC64 2022 2022-12-05      COLOR  3.6109179126  <NA> #> 8324   2063    3M  CC64 2022 2022-12-05         DO  1.3190856114  <NA> #> 8325   2063    3M  CC64 2022 2022-12-05      DOSAT  3.8918202981  <NA> #> 8326   2063    3M  CC64 2022 2022-12-05       NO23 -2.8647040111  <NA> #> 8327   2063    3M  CC64 2022 2022-12-05      SALIN  2.9992261628  <NA> #> 8328   2063    3M  CC64 2022 2022-12-05        TKN -0.4004775666  <NA> #> 8329   2063    3M  CC64 2022 2022-12-05         TN -0.3188288014     + #> 8330   2063    3M  CC64 2022 2022-12-05         TP -1.7719568419  <NA> #> 8331   2063    3M  CC64 2022 2022-12-05       TURB  1.0296194172  <NA> #> 8332   2063    3M  CC64 2023 2023-01-03      CHLAC  1.3083328197  <NA> #> 8333   2063    3M  CC64 2023 2023-01-03      COLOR  2.7080502011  <NA> #> 8334   2063    3M  CC64 2023 2023-01-03         DO  1.6524974019  <NA> #> 8335   2063    3M  CC64 2023 2023-01-03      DOSAT  3.6133473915  <NA> #> 8336   2063    3M  CC64 2023 2023-01-03       NO23 -3.2188758249  <NA> #> 8337   2063    3M  CC64 2023 2023-01-03      SALIN  3.1582762027  <NA> #> 8338   2063    3M  CC64 2023 2023-01-03        TKN -0.7133498879  <NA> #> 8339   2063    3M  CC64 2023 2023-01-03         TN -0.6348782724     + #> 8340   2063    3M  CC64 2023 2023-01-03         TP -1.9661128564  <NA> #> 8341   2063    3M  CC64 2023 2023-01-03       TURB  0.2623642645  <NA> #> 8342   2063    3M  CC64 2023 2023-02-06      CHLAC  1.0986122887  <NA> #> 8343   2063    3M  CC64 2023 2023-02-06      COLOR  2.7725887222  <NA> #> 8344   2063    3M  CC64 2023 2023-02-06         DO  1.4586150227  <NA> #> 8345   2063    3M  CC64 2023 2023-02-06      DOSAT  4.0430512678  <NA> #> 8346   2063    3M  CC64 2023 2023-02-06       NO23 -4.2686979494  <NA> #> 8347   2063    3M  CC64 2023 2023-02-06      SALIN  3.2284300377  <NA> #> 8348   2063    3M  CC64 2023 2023-02-06        TKN -0.4942963218  <NA> #> 8349   2063    3M  CC64 2023 2023-02-06         TN -0.4716049106     + #> 8350   2063    3M  CC64 2023 2023-02-06         TP -2.0402208285  <NA> #> 8351   2063    3M  CC64 2023 2023-02-06       TURB  0.6418538862  <NA> #> 8352   2063    3M  CC64 2023 2023-03-06      CHLAC  0.9932517730  <NA> #> 8353   2063    3M  CC64 2023 2023-03-06      COLOR  2.7725887222  <NA> #> 8354   2063    3M  CC64 2023 2023-03-06         DO  1.3962446920  <NA> #> 8355   2063    3M  CC64 2023 2023-03-06      DOSAT  4.0758410907  <NA> #> 8356   2063    3M  CC64 2023 2023-03-06       NO23 -4.9618451299     I #> 8357   2063    3M  CC64 2023 2023-03-06      SALIN  3.3170908724  <NA> #> 8358   2063    3M  CC64 2023 2023-03-06        TKN -0.6161861394  <NA> #> 8359   2063    3M  CC64 2023 2023-03-06         TN -0.6088060321     + #> 8360   2063    3M  CC64 2023 2023-03-06         TP -2.0402208285  <NA> #> 8361   2063    3M  CC64 2023 2023-03-06       TURB  0.8754687374  <NA> #> 8362   2063    3M  CC64 2014 2014-01-07      CHLAC  1.0986122887  <NA> #> 8363   2063    3M  CC64 2014 2014-01-07         TN -0.9942522733  <NA> #> 8364   2063    3M  CC64 2014 2014-01-07         TP -2.5510464523  <NA> #> 8365   2063    3M  CC64 2014 2014-02-04      CHLAC  0.0000000000  <NA> #> 8366   2063    3M  CC64 2014 2014-02-04         TN -1.0498221245  <NA> #> 8367   2063    3M  CC64 2014 2014-02-04         TP -2.6310891600  <NA> #> 8368   2063    3M  CC64 2014 2014-03-04      CHLAC  1.3862943611  <NA> #> 8369   2063    3M  CC64 2014 2014-03-04         TN -0.5978370008  <NA> #> 8370   2063    3M  CC64 2014 2014-03-04         TP -2.7333680091  <NA> #> 8371   2063    3M  CC64 2014 2014-04-01      CHLAC  1.0986122887  <NA> #> 8372   2063    3M  CC64 2014 2014-04-01         TN -1.0788096614  <NA> #> 8373   2063    3M  CC64 2014 2014-04-01         TP -2.7181005370  <NA> #> 8374   2063    3M  CC64 2014 2014-06-03      CHLAC  1.3862943611  <NA> #> 8375   2063    3M  CC64 2014 2014-06-03         TN -0.5798184953  <NA> #> 8376   2063    3M  CC64 2014 2014-06-03         TP -2.2072749132  <NA> #> 8377   2063    3M  CC64 2014 2014-09-02      CHLAC  3.1354942159  <NA> #> 8378   2063    3M  CC64 2014 2014-09-02         TP -2.3126354288  <NA> #> 8379   2063    3M  CC64 2014 2014-11-04      CHLAC  0.6931471806  <NA> #> 8380   2063    3M  CC64 2014 2014-11-04         TN -0.5798184953  <NA> #> 8381   2063    3M  CC64 2014 2014-11-04         TP -2.6310891600  <NA> #> 8382   2063    3M  CC64 2014 2014-12-02      CHLAC  0.0000000000  <NA> #> 8383   2063    3M  CC64 2014 2014-12-02         TN -0.4942963218  <NA> #> 8384   2063    3M  CC64 2014 2014-12-02         TP -2.3751557858  <NA> #> 8385   2063    3M  CC64 2015 2015-01-03      CHLAC  0.0000000000  <NA> #> 8386   2063    3M  CC64 2015 2015-01-03         TN -0.3011050928  <NA> #> 8387   2063    3M  CC64 2015 2015-01-03         TP -1.8018098051  <NA> #> 8388   2063    3M  CC64 2015 2015-02-02      CHLAC  0.6931471806  <NA> #> 8389   2063    3M  CC64 2015 2015-03-03      CHLAC  0.0000000000  <NA> #> 8390   2063    3M  CC64 2015 2015-03-03         TN -0.5798184953  <NA> #> 8391   2063    3M  CC64 2015 2015-03-03         TP -2.2730262908  <NA> #> 8392   2063    3M  CC64 2015 2015-04-02      CHLAC  0.6931471806  <NA> #> 8393   2063    3M  CC64 2015 2015-04-02         TN -0.4462871026  <NA> #> 8394   2063    3M  CC64 2015 2015-04-02         TP -2.2926347621  <NA> #> 8395   2063    3M  CC64 2015 2015-05-05      CHLAC  1.0986122887  <NA> #> 8396   2063    3M  CC64 2015 2015-05-05         TN -0.8209805521  <NA> #> 8397   2063    3M  CC64 2015 2015-05-05         TP -2.5257286443  <NA> #> 8398   2063    3M  CC64 2015 2015-09-09      CHLAC  1.0986122887  <NA> #> 8399   2063    3M  CC64 2015 2015-09-09         TN -0.5978370008  <NA> #> 8400   2063    3M  CC64 2015 2015-09-09         TP -2.9759296463  <NA> #> 8401   2063    3M  CC64 2015 2015-10-07      CHLAC  1.6094379124  <NA> #> 8402   2063    3M  CC64 2015 2015-11-04      CHLAC  1.0986122887  <NA> #> 8403   2063    3M  CC64 2015 2015-11-04         TN -0.6539264674  <NA> #> 8404   2063    3M  CC64 2015 2015-11-04         TP -2.6172958378  <NA> #> 8405   2063    3M  CC64 2015 2015-11-15      CHLAC  1.6094379124  <NA> #> 8406   2063    3M  CC64 2015 2015-11-15         TN -0.8439700703  <NA> #> 8407   2063    3M  CC64 2015 2015-11-15         TP -2.7968814148  <NA> #> 8408   2063    3M  CC64 2016 2016-01-06         TN -0.1053605157  <NA> #> 8409   2063    3M  CC64 2016 2016-01-06         TP -2.3126354288  <NA> #> 8410   2063    3M  CC64 2016 2016-02-02      CHLAC  1.6094379124  <NA> #> 8411   2063    3M  CC64 2016 2016-02-02         TN -0.2231435513  <NA> #> 8412   2063    3M  CC64 2016 2016-02-02         TP -2.9957322736  <NA> #> 8413   2063    3M  CC64 2016 2016-06-11      CHLAC  2.5649493575  <NA> #> 8414   2063    3M  CC64 2016 2016-06-11         TN -0.8439700703  <NA> #> 8415   2063    3M  CC64 2016 2016-06-11         TP -2.7488721956  <NA> #> 8416   2063    3M  CC64 2016 2016-07-08      CHLAC  1.0986122887  <NA> #> 8417   2063    3M  CC64 2016 2016-07-08         TN -0.7765287895  <NA> #> 8418   2063    3M  CC64 2016 2016-07-08         TP -3.7722610631  <NA> #> 8419   2063    3M  CC64 2016 2016-10-03      CHLAC  1.0986122887  <NA> #> 8420   2063    3M  CC64 2016 2016-10-03         TN -0.2231435513  <NA> #> 8421   2063    3M  CC64 2016 2016-10-03         TP -2.0874737134  <NA> #> 8422   2063    3M  CC64 2018 2018-12-04      CHLAC  1.0986122887  <NA> #> 8423   2063    3M  CC64 2018 2018-12-04         TN -0.7985076962  <NA> #> 8424   2063    3M  CC64 2018 2018-12-04         TP -2.3644604967  <NA> #> 8425   2063    3M  CC64 2019 2019-01-09      CHLAC  0.6931471806     I #> 8426   2063    3M  CC64 2019 2019-01-09         TN -1.2039728043  <NA> #> 8427   2063    3M  CC64 2019 2019-01-09         TP -2.7333680091  <NA> #> 8428  2065B     2  CC67 2015 2015-04-07      CHLAC  0.6931471806  <NA> #> 8429  2065B     2  CC67 2015 2015-04-07      COLOR  3.4011973817  <NA> #> 8430  2065B     2  CC67 2015 2015-04-07       COND 10.6960274770  <NA> #> 8431  2065B     2  CC67 2015 2015-04-07         DO  1.8164520818  <NA> #> 8432  2065B     2  CC67 2015 2015-04-07      DOSAT  4.4931206822     + #> 8433  2065B     2  CC67 2015 2015-04-07       NO23 -5.1159958098     I #> 8434  2065B     2  CC67 2015 2015-04-07      SALIN  3.3492020865  <NA> #> 8435  2065B     2  CC67 2015 2015-04-07        TKN -0.2587707290  <NA> #> 8436  2065B     2  CC67 2015 2015-04-07         TN -0.2510287548  <NA> #> 8437  2065B     2  CC67 2015 2015-04-07         TP -2.4079456087  <NA> #> 8438  2065B     2  CC67 2015 2015-04-07        TSS  2.2257040487  <NA> #> 8439  2065B     2  CC67 2015 2015-04-07       TURB  0.2623642645  <NA> #> 8440  2065B     2  CC67 2015 2015-04-07       COND 10.6958011046  <NA> #> 8441  2065B     2  CC67 2015 2015-04-07         DO  1.8033586051  <NA> #> 8442  2065B     2  CC67 2015 2015-04-07      DOSAT  4.4796069630     + #> 8443  2065B     2  CC67 2015 2015-04-07      SALIN  3.3488509013  <NA> #> 8444  2065B     2  CC67 2015 2015-11-03      CHLAC  2.0476928434  <NA> #> 8445  2065B     2  CC67 2015 2015-11-03      COLOR  4.0073331852  <NA> #> 8446  2065B     2  CC67 2015 2015-11-03       COND 10.5339611386  <NA> #> 8447  2065B     2  CC67 2015 2015-11-03         DO  2.0731719287  <NA> #> 8448  2065B     2  CC67 2015 2015-11-03      DOSAT  4.7723781050     + #> 8449  2065B     2  CC67 2015 2015-11-03       NO23 -5.5214609179     U #> 8450  2065B     2  CC67 2015 2015-11-03      SALIN  3.1658969001  <NA> #> 8451  2065B     2  CC67 2015 2015-11-03        TKN -0.4557063245  <NA> #> 8452  2065B     2  CC67 2015 2015-11-03         TN -0.4557063245  <NA> #> 8453  2065B     2  CC67 2015 2015-11-03         TP -2.0557250151  <NA> #> 8454  2065B     2  CC67 2015 2015-11-03        TSS  1.7369512327  <NA> #> 8455  2065B     2  CC67 2015 2015-11-03       TURB -0.3566749439  <NA> #> 8456  2065B     2  CC67 2015 2015-11-03       COND 10.5312958918  <NA> #> 8457  2065B     2  CC67 2015 2015-11-03         DO  2.0955609236  <NA> #> 8458  2065B     2  CC67 2015 2015-11-03      DOSAT  4.7966166506     + #> 8459  2065B     2  CC67 2015 2015-11-03      SALIN  3.1629401925  <NA> #> 8460  2065B     2  CC67 2017 2017-04-05      CHLAC -0.0502412164     I #> 8461  2065B     2  CC67 2017 2017-04-05       COND 10.7904503955  <NA> #> 8462  2065B     2  CC67 2017 2017-04-05         DO  1.9586853405  <NA> #> 8463  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6653241088     + #> 8464  2065B     2  CC67 2017 2017-04-05       NO23 -4.8283137373     I #> 8465  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8466  2065B     2  CC67 2017 2017-04-05        TKN -0.4261781497  <NA> #> 8467  2065B     2  CC67 2017 2017-04-05         TN -0.4140014391  <NA> #> 8468  2065B     2  CC67 2017 2017-04-05         TP -2.7030626596  <NA> #> 8469  2065B     2  CC67 2017 2017-04-05        TSS  2.1972245773  <NA> #> 8470  2065B     2  CC67 2017 2017-04-05       TURB  0.0000000000  <NA> #> 8471  2065B     2  CC67 2017 2017-04-05       COND 10.7904771690  <NA> #> 8472  2065B     2  CC67 2017 2017-04-05         DO  1.9699056546  <NA> #> 8473  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6784206477     + #> 8474  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8475  2065B     2  CC67 2017 2017-04-05       COND 10.7905760186  <NA> #> 8476  2065B     2  CC67 2017 2017-04-05         DO  1.9712993831  <NA> #> 8477  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6802776585     + #> 8478  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8479  2065B     2  CC67 2017 2017-04-05       COND 10.7905821964  <NA> #> 8480  2065B     2  CC67 2017 2017-04-05         DO  1.9726911717  <NA> #> 8481  2065B     2  CC67 2017 2017-04-05      DOSAT  4.6812048723     + #> 8482  2065B     2  CC67 2017 2017-04-05      SALIN  3.4541060373  <NA> #> 8483  2065B     2  CC67 2017 2017-06-05      CHLAC  1.3686394259  <NA> #> 8484  2065B     2  CC67 2017 2017-06-05       NO23 -4.1351665567  <NA> #> 8485  2065B     2  CC67 2017 2017-06-05        TKN -0.2600669054  <NA> #> 8486  2065B     2  CC67 2017 2017-06-05         TN -0.2395270306  <NA> #> 8487  2065B     2  CC67 2017 2017-06-05         TP -2.5770219387  <NA> #> 8488  2065B     2  CC67 2017 2017-06-05        TSS  2.4595888418  <NA> #> 8489  2065B     2  CC67 2017 2017-06-05       TURB  0.0000000000  <NA> #> 8490  2065B     2  CC67 2017 2017-06-05       COND 10.8045448425  <NA> #> 8491  2065B     2  CC67 2017 2017-06-05         DO  1.6134299337  <NA> #> 8492  2065B     2  CC67 2017 2017-06-05      DOSAT  4.3592696476     + #> 8493  2065B     2  CC67 2017 2017-06-05      SALIN  3.4679210137  <NA> #> 8494  2065B     2  CC67 2017 2017-06-05       COND 10.8049143616  <NA> #> 8495  2065B     2  CC67 2017 2017-06-05         DO  1.6524974019  <NA> #> 8496  2065B     2  CC67 2017 2017-06-05      DOSAT  4.3981460166     + #> 8497  2065B     2  CC67 2017 2017-06-05      SALIN  3.4682327830  <NA> #> 8498  2065B     2  CC67 2017 2017-06-05       COND 10.8052533058  <NA> #> 8499  2065B     2  CC67 2017 2017-06-05         DO  1.6677068206  <NA> #> 8500  2065B     2  CC67 2017 2017-06-05      DOSAT  4.4140096805     + #> 8501  2065B     2  CC67 2017 2017-06-05      SALIN  3.4685444551  <NA> #> 8502  2065B     2  CC67 2017 2017-08-15      CHLAC  2.7850112422  <NA> #> 8503  2065B     2  CC67 2017 2017-08-15       COND 10.0070409363  <NA> #> 8504  2065B     2  CC67 2017 2017-08-15         DO  1.7474592103  <NA> #> 8505  2065B     2  CC67 2017 2017-08-15      DOSAT  4.4693504628     + #> 8506  2065B     2  CC67 2017 2017-08-15       NO23 -3.2968373663  <NA> #> 8507  2065B     2  CC67 2017 2017-08-15      SALIN  2.5794589667  <NA> #> 8508  2065B     2  CC67 2017 2017-08-15        TKN  0.0953101798  <NA> #> 8509  2065B     2  CC67 2017 2017-08-15         TN  0.1310282624  <NA> #> 8510  2065B     2  CC67 2017 2017-08-15         TP -1.0555527992  <NA> #> 8511  2065B     2  CC67 2017 2017-08-15        TSS  0.8458682676  <NA> #> 8512  2065B     2  CC67 2017 2017-08-15       TURB  0.6931471806  <NA> #> 8513  2065B     2  CC67 2017 2017-08-15       COND 10.1682757999  <NA> #> 8514  2065B     2  CC67 2017 2017-08-15         DO  0.5822156199  <NA> #> 8515  2065B     2  CC67 2017 2017-08-15      DOSAT  3.2771447330     + #> 8516  2065B     2  CC67 2017 2017-08-15      SALIN  2.7593768283  <NA> #> 8517  2065B     2  CC67 2017 2017-08-15       COND 10.1784604545  <NA> #> 8518  2065B     2  CC67 2017 2017-08-15         DO  0.5306282511  <NA> #> 8519  2065B     2  CC67 2017 2017-08-15      DOSAT  3.2268439945     + #> 8520  2065B     2  CC67 2017 2017-08-15      SALIN  2.7707119622  <NA> #> 8521  2065B     2  CC67 2018 2018-04-09      CHLAC  0.8109302162  <NA> #> 8522  2065B     2  CC67 2018 2018-04-09       COND 10.7756173069  <NA> #> 8523  2065B     2  CC67 2018 2018-04-09         DO  1.9387416596  <NA> #> 8524  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6395716127     + #> 8525  2065B     2  CC67 2018 2018-04-09       NO23 -4.8283137373     I #> 8526  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8527  2065B     2  CC67 2018 2018-04-09        TKN -0.3945251681  <NA> #> 8528  2065B     2  CC67 2018 2018-04-09         TN -0.3827256211  <NA> #> 8529  2065B     2  CC67 2018 2018-04-09         TP -2.5902671654  <NA> #> 8530  2065B     2  CC67 2018 2018-04-09        TSS  1.4816045409  <NA> #> 8531  2065B     2  CC67 2018 2018-04-09       TURB  0.0953101798  <NA> #> 8532  2065B     2  CC67 2018 2018-04-09       COND 10.7754082549  <NA> #> 8533  2065B     2  CC67 2018 2018-04-09         DO  1.9473377010  <NA> #> 8534  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6482296754     + #> 8535  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8536  2065B     2  CC67 2018 2018-04-09       COND 10.7754082549  <NA> #> 8537  2065B     2  CC67 2018 2018-04-09         DO  1.9487632180  <NA> #> 8538  2065B     2  CC67 2018 2018-04-09      DOSAT  4.6501435516     + #> 8539  2065B     2  CC67 2018 2018-04-09      SALIN  3.4375293109  <NA> #> 8540  2065B     2  CC67 2018 2018-05-23      CHLAC  1.1216775616  <NA> #> 8541  2065B     2  CC67 2018 2018-05-23       COND 10.7435212354  <NA> #> 8542  2065B     2  CC67 2018 2018-05-23         DO  1.8885836539  <NA> #> 8543  2065B     2  CC67 2018 2018-05-23      DOSAT  4.5910712616     + #> 8544  2065B     2  CC67 2018 2018-05-23       NO23 -4.6051701860     I #> 8545  2065B     2  CC67 2018 2018-05-23      SALIN  3.4011973817  <NA> #> 8546  2065B     2  CC67 2018 2018-05-23        TKN -0.1696027844  <NA> #> 8547  2065B     2  CC67 2018 2018-05-23         TN -0.1578240852  <NA> #> 8548  2065B     2  CC67 2018 2018-05-23         TP -2.0794415417  <NA> #> 8549  2065B     2  CC67 2018 2018-05-23        TSS  1.5686159179  <NA> #> 8550  2065B     2  CC67 2018 2018-05-23       TURB  1.0647107370  <NA> #> 8551  2065B     2  CC67 2018 2018-05-23      DOSAT  4.6793495842     + #> 8552  2065B     2  CC67 2018 2018-05-23       COND 10.7527727226  <NA> #> 8553  2065B     2  CC67 2018 2018-05-23         DO  1.9782390362  <NA> #> 8554  2065B     2  CC67 2018 2018-05-23      SALIN  3.4118075608  <NA> #> 8555  2065B     2  CC67 2018 2018-10-11      CHLAC  1.4109869737  <NA> #> 8556  2065B     2  CC67 2018 2018-10-11       COND 10.5316641186  <NA> #> 8557  2065B     2  CC67 2018 2018-10-11         DO  1.6467336972  <NA> #> 8558  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3148178850     + #> 8559  2065B     2  CC67 2018 2018-10-11       NO23 -4.9618451299     I #> 8560  2065B     2  CC67 2018 2018-10-11      SALIN  3.1654750481  <NA> #> 8561  2065B     2  CC67 2018 2018-10-11        TKN -0.1960148839  <NA> #> 8562  2065B     2  CC67 2018 2018-10-11         TN -0.1875351238  <NA> #> 8563  2065B     2  CC67 2018 2018-10-11         TP -2.1202635362  <NA> #> 8564  2065B     2  CC67 2018 2018-10-11        TSS  1.8453002362  <NA> #> 8565  2065B     2  CC67 2018 2018-10-11       TURB  0.6931471806  <NA> #> 8566  2065B     2  CC67 2018 2018-10-11       COND 10.5317548204  <NA> #> 8567  2065B     2  CC67 2018 2018-10-11         DO  1.6448050563  <NA> #> 8568  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3121405072     + #> 8569  2065B     2  CC67 2018 2018-10-11      SALIN  3.1654750481  <NA> #> 8570  2065B     2  CC67 2018 2018-10-11       COND 10.5326214074  <NA> #> 8571  2065B     2  CC67 2018 2018-10-11         DO  1.6370530795  <NA> #> 8572  2065B     2  CC67 2018 2018-10-11      DOSAT  4.3054155323     + #> 8573  2065B     2  CC67 2018 2018-10-11      SALIN  3.1663185741  <NA> #> 8574  2065B     2  CC67 2019 2019-03-05      CHLAC  1.6094379124  <NA> #> 8575  2065B     2  CC67 2019 2019-03-05       COND 10.4627604245  <NA> #> 8576  2065B     2  CC67 2019 2019-03-05         DO  1.8325814637  <NA> #> 8577  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5163389723     + #> 8578  2065B     2  CC67 2019 2019-03-05       NO23 -5.1159958098     U #> 8579  2065B     2  CC67 2019 2019-03-05      SALIN  3.5550051456  <NA> #> 8580  2065B     2  CC67 2019 2019-03-05        TKN -0.2691874898  <NA> #> 8581  2065B     2  CC67 2019 2019-03-05         TN -0.2691874898  <NA> #> 8582  2065B     2  CC67 2019 2019-03-05         TP -2.3644604967  <NA> #> 8583  2065B     2  CC67 2019 2019-03-05        TSS  1.9919755159  <NA> #> 8584  2065B     2  CC67 2019 2019-03-05       TURB  0.8754687374  <NA> #> 8585  2065B     2  CC67 2019 2019-03-05       COND 10.4628461645  <NA> #> 8586  2065B     2  CC67 2019 2019-03-05         DO  1.8309801824  <NA> #> 8587  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5152454785     + #> 8588  2065B     2  CC67 2019 2019-03-05      SALIN  3.5550908856  <NA> #> 8589  2065B     2  CC67 2019 2019-03-05       COND 10.4631604817  <NA> #> 8590  2065B     2  CC67 2019 2019-03-05         DO  1.8277699068  <NA> #> 8591  2065B     2  CC67 2019 2019-03-05      DOSAT  4.5119578043     + #> 8592  2065B     2  CC67 2019 2019-03-05      SALIN  3.5554052027  <NA> #> 8593  2065B     2  CC67 2020 2020-01-15       COND 10.6506753751  <NA> #> 8594  2065B     2  CC67 2020 2020-01-15         DO  2.0592388344  <NA> #> 8595  2065B     2  CC67 2020 2020-01-15      DOSAT  4.6737629775     + #> 8596  2065B     2  CC67 2020 2020-01-15       NO23 -5.1159958098     U #> 8597  2065B     2  CC67 2020 2020-01-15      SALIN  3.3010086544  <NA> #> 8598  2065B     2  CC67 2020 2020-01-15        TKN -0.4109802888  <NA> #> 8599  2065B     2  CC67 2020 2020-01-15         TN -0.4109802888  <NA> #> 8600  2065B     2  CC67 2020 2020-01-15         TP -2.4304184645  <NA> #> 8601  2065B     2  CC67 2020 2020-01-15        TSS  1.4816045409  <NA> #> 8602  2065B     2  CC67 2020 2020-01-15       TURB  0.0000000000  <NA> #> 8603  2065B     2  CC67 2020 2020-01-15       COND 10.6625933392  <NA> #> 8604  2065B     2  CC67 2020 2020-01-15         DO  2.0630580624  <NA> #> 8605  2065B     2  CC67 2020 2020-01-15      DOSAT  4.6756286496     + #> 8606  2065B     2  CC67 2020 2020-01-15      SALIN  3.3141860047  <NA> #> 8607  2065B     2  CC67 2020 2020-02-11       COND 10.6620033783  <NA> #> 8608  2065B     2  CC67 2020 2020-02-11       NO23 -5.1159958098     U #> 8609  2065B     2  CC67 2020 2020-02-11      SALIN  3.3141860047  <NA> #> 8610  2065B     2  CC67 2020 2020-02-11        TKN -0.3538218750  <NA> #> 8611  2065B     2  CC67 2020 2020-02-11         TN -0.3495574762     + #> 8612  2065B     2  CC67 2020 2020-02-11         TP -2.6036901858  <NA> #> 8613  2065B     2  CC67 2020 2020-02-11        TSS  1.2029723040  <NA> #> 8614  2065B     2  CC67 2020 2020-02-11       TURB -0.2613647641  <NA> #> 8615  2065B     2  CC67 2020 2020-02-11       COND 10.6633887669  <NA> #> 8616  2065B     2  CC67 2020 2020-02-11      SALIN  3.3156394933  <NA> #> 8617  2065B     2  CC67 2020 2020-11-04       COND 10.4405071004  <NA> #> 8618  2065B     2  CC67 2020 2020-11-04         DO  1.8033586051  <NA> #> 8619  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3782695858     + #> 8620  2065B     2  CC67 2020 2020-11-04       NO23 -5.1159958098     U #> 8621  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8622  2065B     2  CC67 2020 2020-11-04        TKN -0.9808292530  <NA> #> 8623  2065B     2  CC67 2020 2020-11-04         TN -0.9808292530  <NA> #> 8624  2065B     2  CC67 2020 2020-11-04         TP -1.9173226922  <NA> #> 8625  2065B     2  CC67 2020 2020-11-04        TSS  3.3322045102  <NA> #> 8626  2065B     2  CC67 2020 2020-11-04       TURB  0.5306282511  <NA> #> 8627  2065B     2  CC67 2020 2020-11-04       COND 10.4404486499  <NA> #> 8628  2065B     2  CC67 2020 2020-11-04         DO  1.8000582720  <NA> #> 8629  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3744983683     + #> 8630  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8631  2065B     2  CC67 2020 2020-11-04       COND 10.4404778756  <NA> #> 8632  2065B     2  CC67 2020 2020-11-04         DO  1.7984040119  <NA> #> 8633  2065B     2  CC67 2020 2020-11-04      DOSAT  4.3732381286     + #> 8634  2065B     2  CC67 2020 2020-11-04      SALIN  3.0685179433  <NA> #> 8635  2065B     2  CC67 2021 2021-05-17       COND 10.7266756661  <NA> #> 8636  2065B     2  CC67 2021 2021-05-17         DO  1.8976198599  <NA> #> 8637  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5859873666     + #> 8638  2065B     2  CC67 2021 2021-05-17       NO23 -5.1159958098     U #> 8639  2065B     2  CC67 2021 2021-05-17      SALIN  3.3830334110  <NA> #> 8640  2065B     2  CC67 2021 2021-05-17        TKN -0.6520052372  <NA> #> 8641  2065B     2  CC67 2021 2021-05-17         TN -0.6520052372  <NA> #> 8642  2065B     2  CC67 2021 2021-05-17         TP -2.2926347621  <NA> #> 8643  2065B     2  CC67 2021 2021-05-17        TSS  2.7343675094  <NA> #> 8644  2065B     2  CC67 2021 2021-05-17       TURB -0.4416105547  <NA> #> 8645  2065B     2  CC67 2021 2021-05-17       COND 10.7266317622  <NA> #> 8646  2065B     2  CC67 2021 2021-05-17         DO  1.9110228901  <NA> #> 8647  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5991521137     + #> 8648  2065B     2  CC67 2021 2021-05-17      SALIN  3.3830334110  <NA> #> 8649  2065B     2  CC67 2021 2021-05-17       COND 10.7261267283  <NA> #> 8650  2065B     2  CC67 2021 2021-05-17         DO  1.9110228901  <NA> #> 8651  2065B     2  CC67 2021 2021-05-17      DOSAT  4.5991521137     + #> 8652  2065B     2  CC67 2021 2021-05-17      SALIN  3.3823542939  <NA> #> 8653   2081    3F  CC67 2016 2016-04-27      CHLAC  1.7404661748  <NA> #> 8654   2081    3F  CC67 2016 2016-04-27      COLOR  4.2046926194  <NA> #> 8655   2081    3F  CC67 2016 2016-04-27       COND  6.3135480463  <NA> #> 8656   2081    3F  CC67 2016 2016-04-27         DO  2.0918640617  <NA> #> 8657   2081    3F  CC67 2016 2016-04-27      DOSAT  4.5849674787  <NA> #> 8658   2081    3F  CC67 2016 2016-04-27       NO23 -4.3428059215  <NA> #> 8659   2081    3F  CC67 2016 2016-04-27      SALIN -1.3093333200     + #> 8660   2081    3F  CC67 2016 2016-04-27        TKN -0.1625189295  <NA> #> 8661   2081    3F  CC67 2016 2016-04-27         TN -0.1473405879     + #> 8662   2081    3F  CC67 2016 2016-04-27         TP -2.9187712324  <NA> #> 8663   2081    3F  CC67 2016 2016-04-27        TSS  1.0986122887     I #> 8664   2081    3F  CC67 2016 2016-04-27       TURB  1.8870696490  <NA> #> 8665   2081    3F  CC67 2016 2016-09-21      CHLAC  2.2082744135     A #> 8666   2081    3F  CC67 2016 2016-09-21      COLOR  4.9416424226  <NA> #> 8667   2081    3F  CC67 2016 2016-09-21       COND  5.8636311756  <NA> #> 8668   2081    3F  CC67 2016 2016-09-21         DO  1.7227665977  <NA> #> 8669   2081    3F  CC67 2016 2016-09-21      DOSAT  4.3040650932  <NA> #> 8670   2081    3F  CC67 2016 2016-09-21       NO23 -2.9565115604  <NA> #> 8671   2081    3F  CC67 2016 2016-09-21      SALIN -1.6094379124  <NA> #> 8672   2081    3F  CC67 2016 2016-09-21        TKN -0.1863295782  <NA> #> 8673   2081    3F  CC67 2016 2016-09-21         TN -0.1255632230     + #> 8674   2081    3F  CC67 2016 2016-09-21         TP -2.3025850930  <NA> #> 8675   2081    3F  CC67 2016 2016-09-21        TSS  2.8332133441  <NA> #> 8676   2081    3F  CC67 2016 2016-09-21       TURB  2.3025850930  <NA> #> 8677   2081    3F  CC67 2016 2016-12-13      CHLAC  0.5306282511     I #> 8678   2081    3F  CC67 2016 2016-12-13      COLOR  4.0253516907  <NA> #> 8679   2081    3F  CC67 2016 2016-12-13       COND  6.2709884319  <NA> #> 8680   2081    3F  CC67 2016 2016-12-13         DO  2.1860512767  <NA> #> 8681   2081    3F  CC67 2016 2016-12-13      DOSAT  4.5951198501  <NA> #> 8682   2081    3F  CC67 2016 2016-12-13       NO23 -1.8971199849  <NA> #> 8683   2081    3F  CC67 2016 2016-12-13      SALIN -1.6094379124  <NA> #> 8684   2081    3F  CC67 2016 2016-12-13        TKN -0.4942963218  <NA> #> 8685   2081    3F  CC67 2016 2016-12-13         TN -0.2744368457     + #> 8686   2081    3F  CC67 2016 2016-12-13         TP -2.9759296463  <NA> #> 8687   2081    3F  CC67 2016 2016-12-13        TSS  1.3862943611     I #> 8688   2081    3F  CC67 2016 2016-12-13       TURB  1.6486586256  <NA> #> 8689   2081    3F  CC67 2016 2016-12-28      CHLAC  1.0296194172  <NA> #> 8690   2081    3F  CC67 2016 2016-12-28      COLOR  4.1896547420     A #> 8691   2081    3F  CC67 2016 2016-12-28       COND  6.2747620212  <NA> #> 8692   2081    3F  CC67 2016 2016-12-28       NO23 -2.2072749132  <NA> #> 8693   2081    3F  CC67 2016 2016-12-28      SALIN -1.3093333200     + #> 8694   2081    3F  CC67 2016 2016-12-28        TKN -0.4004775666  <NA> #> 8695   2081    3F  CC67 2016 2016-12-28         TN -0.2484613593     + #> 8696   2081    3F  CC67 2016 2016-12-28         TP -2.6882475738  <NA> #> 8697   2081    3F  CC67 2016 2016-12-28        TSS  1.7917594692     I #> 8698   2081    3F  CC67 2016 2016-12-28       TURB  1.9878743482     A #> 8699   2081    3F  CC67 2017 2017-07-26      CHLAC  2.3025850930  <NA> #> 8700   2081    3F  CC67 2017 2017-07-26      COLOR  5.3471075307  <NA> #> 8701   2081    3F  CC67 2017 2017-07-26       COND  5.8435444170  <NA> #> 8702   2081    3F  CC67 2017 2017-07-26         DO  1.6486586256  <NA> #> 8703   2081    3F  CC67 2017 2017-07-26      DOSAT  4.2626798770  <NA> #> 8704   2081    3F  CC67 2017 2017-07-26       NO23 -3.3813947544  <NA> #> 8705   2081    3F  CC67 2017 2017-07-26        TKN  0.0953101798  <NA> #> 8706   2081    3F  CC67 2017 2017-07-26         TN  0.1257512053     + #> 8707   2081    3F  CC67 2017 2017-07-26         TP -2.4191189092  <NA> #> 8708   2081    3F  CC67 2017 2017-07-26        TSS  2.4849066498  <NA> #> 8709   2081    3F  CC67 2017 2017-07-26       TURB  1.9315214116  <NA> #> 8710   2081    3F  CC67 2017 2017-08-21      CHLAC  1.4350845253  <NA> #> 8711   2081    3F  CC67 2017 2017-08-21      COLOR  4.7874917428  <NA> #> 8712   2081    3F  CC67 2017 2017-08-21       COND  6.0497334552  <NA> #> 8713   2081    3F  CC67 2017 2017-08-21         DO  1.9169226122  <NA> #> 8714   2081    3F  CC67 2017 2017-08-21      DOSAT  4.5108595065  <NA> #> 8715   2081    3F  CC67 2017 2017-08-21       NO23 -2.9957322736  <NA> #> 8716   2081    3F  CC67 2017 2017-08-21        TKN -0.1984509387  <NA> #> 8717   2081    3F  CC67 2017 2017-08-21         TN -0.1392620673     + #> 8718   2081    3F  CC67 2017 2017-08-21         TP -2.7488721956  <NA> #> 8719   2081    3F  CC67 2017 2017-08-21        TSS  2.3025850930     I #> 8720   2081    3F  CC67 2017 2017-08-21       TURB  1.9740810260     A #> 8721   2081    3F  CC67 2017 2017-10-04      CHLAC  2.0014800002  <NA> #> 8722   2081    3F  CC67 2017 2017-10-04      COLOR  4.7874917428  <NA> #> 8723   2081    3F  CC67 2017 2017-10-04       COND  5.9188938543  <NA> #> 8724   2081    3F  CC67 2017 2017-10-04         DO  1.8718021769  <NA> #> 8725   2081    3F  CC67 2017 2017-10-04      DOSAT  4.3944491547  <NA> #> 8726   2081    3F  CC67 2017 2017-10-04       NO23 -3.1235656451  <NA> #> 8727   2081    3F  CC67 2017 2017-10-04      SALIN -1.7719568419     + #> 8728   2081    3F  CC67 2017 2017-10-04        TKN -0.2231435513  <NA> #> 8729   2081    3F  CC67 2017 2017-10-04         TN -0.1696027844     + #> 8730   2081    3F  CC67 2017 2017-10-04         TP -2.7488721956  <NA> #> 8731   2081    3F  CC67 2017 2017-10-04        TSS  2.0794415417     I #> 8732   2081    3F  CC67 2017 2017-10-04       TURB  1.6486586256     A #> 8733   2081    3F  CC67 2017 2017-11-08      CHLAC  1.7404661748  <NA> #> 8734   2081    3F  CC67 2017 2017-11-08      COLOR  4.2341065046  <NA> #> 8735   2081    3F  CC67 2017 2017-11-08       COND  6.1377270541  <NA> #> 8736   2081    3F  CC67 2017 2017-11-08         DO  2.1747517215  <NA> #> 8737   2081    3F  CC67 2017 2017-11-08      DOSAT  4.6634390941  <NA> #> 8738   2081    3F  CC67 2017 2017-11-08       NO23 -2.7030626596  <NA> #> 8739   2081    3F  CC67 2017 2017-11-08      SALIN -1.4696759701     + #> 8740   2081    3F  CC67 2017 2017-11-08        TKN -0.4942963218  <NA> #> 8741   2081    3F  CC67 2017 2017-11-08         TN -0.3900840061     + #> 8742   2081    3F  CC67 2017 2017-11-08         TP -3.1235656451  <NA> #> 8743   2081    3F  CC67 2017 2017-11-08        TSS  1.0986122887     I #> 8744   2081    3F  CC67 2017 2017-11-08       TURB  1.5686159179  <NA> #> 8745   2081    3F  CC67 2017 2017-11-30      CHLAC  1.6677068206  <NA> #> 8746   2081    3F  CC67 2017 2017-11-30      COLOR  4.1271343850     A #> 8747   2081    3F  CC67 2017 2017-11-30       COND  6.2519038832  <NA> #> 8748   2081    3F  CC67 2017 2017-11-30         DO  2.3025850930  <NA> #> 8749   2081    3F  CC67 2017 2017-11-30      DOSAT  4.7535901911  <NA> #> 8750   2081    3F  CC67 2017 2017-11-30       NO23 -3.2188758249  <NA> #> 8751   2081    3F  CC67 2017 2017-11-30      SALIN -1.3470736480     + #> 8752   2081    3F  CC67 2017 2017-11-30        TKN -0.5798184953  <NA> #> 8753   2081    3F  CC67 2017 2017-11-30         TN -0.5108256238     + #> 8754   2081    3F  CC67 2017 2017-11-30         TP -3.1700856607  <NA> #> 8755   2081    3F  CC67 2017 2017-11-30        TSS  1.3862943611     I #> 8756   2081    3F  CC67 2017 2017-11-30       TURB  1.5475625087  <NA> #> 8757   2081    3F  CC67 2018 2018-04-12       COND  6.1717005974  <NA> #> 8758   2081    3F  CC67 2018 2018-04-12         DO  2.6461747974  <NA> #> 8759   2081    3F  CC67 2018 2018-04-12      DOSAT  5.1239639794  <NA> #> 8760   2081    3F  CC67 2018 2018-04-12      SALIN -1.4696759701     + #> 8761   2081    3F  CC67 2018 2018-04-19      CHLAC  2.2512917986  <NA> #> 8762   2081    3F  CC67 2018 2018-04-19      COLOR  4.0943445622  <NA> #> 8763   2081    3F  CC67 2018 2018-04-19       COND  6.0980742822  <NA> #> 8764   2081    3F  CC67 2018 2018-04-19         DO  2.7317667277  <NA> #> 8765   2081    3F  CC67 2018 2018-04-19      DOSAT  5.3107398865  <NA> #> 8766   2081    3F  CC67 2018 2018-04-19       NO23 -5.5214609179     U #> 8767   2081    3F  CC67 2018 2018-04-19      SALIN -1.6094379124     + #> 8768   2081    3F  CC67 2018 2018-04-19        TKN -0.3424903089  <NA> #> 8769   2081    3F  CC67 2018 2018-04-19         TN -0.3396773676     + #> 8770   2081    3F  CC67 2018 2018-04-19         TP -4.2686979494  <NA> #> 8771   2081    3F  CC67 2018 2018-04-19        TSS  1.0986122887     I #> 8772   2081    3F  CC67 2018 2018-04-19       TURB  0.4054651081  <NA> #> 8773   2081    3F  CC67 2018 2018-07-17      CHLAC  2.3978952728  <NA> #> 8774   2081    3F  CC67 2018 2018-07-17      COLOR  5.2470240722  <NA> #> 8775   2081    3F  CC67 2018 2018-07-17       COND  5.6559918108  <NA> #> 8776   2081    3F  CC67 2018 2018-07-17         DO  1.6677068206  <NA> #> 8777   2081    3F  CC67 2018 2018-07-17      DOSAT  4.2541932632  <NA> #> 8778   2081    3F  CC67 2018 2018-07-17       NO23 -3.8167128256  <NA> #> 8779   2081    3F  CC67 2018 2018-07-17        TKN -0.0304592075  <NA> #> 8780   2081    3F  CC67 2018 2018-07-17         TN -0.0080321717     + #> 8781   2081    3F  CC67 2018 2018-07-17         TP -2.7968814148  <NA> #> 8782   2081    3F  CC67 2018 2018-07-17        TSS  1.7917594692     I #> 8783   2081    3F  CC67 2018 2018-07-17       TURB  1.7047480922  <NA> #> 8784   2081    3F  CC67 2018 2018-08-01      CHLAC  2.0014800002  <NA> #> 8785   2081    3F  CC67 2018 2018-08-01      COLOR  4.9416424226  <NA> #> 8786   2081    3F  CC67 2018 2018-08-01       COND  5.9269260260  <NA> #> 8787   2081    3F  CC67 2018 2018-08-01         DO  1.8900953699  <NA> #> 8788   2081    3F  CC67 2018 2018-08-01      DOSAT  4.4624538838  <NA> #> 8789   2081    3F  CC67 2018 2018-08-01       NO23 -3.2188758249  <NA> #> 8790   2081    3F  CC67 2018 2018-08-01      SALIN -1.7147984281  <NA> #> 8791   2081    3F  CC67 2018 2018-08-01        TKN -0.2613647641  <NA> #> 8792   2081    3F  CC67 2018 2018-08-01         TN -0.2107210313     + #> 8793   2081    3F  CC67 2018 2018-08-01         TP -2.8824035882  <NA> #> 8794   2081    3F  CC67 2018 2018-08-01        TSS  1.7917594692     I #> 8795   2081    3F  CC67 2018 2018-08-01       TURB  1.7404661748  <NA> #> 8796   2081    3F  CC67 2018 2018-08-01       COND  5.9269260260  <NA> #> 8797   2081    3F  CC67 2018 2018-08-01         DO  1.8900953699  <NA> #> 8798   2081    3F  CC67 2018 2018-08-01      DOSAT  4.4624538838  <NA> #> 8799   2081    3F  CC67 2018 2018-08-01      SALIN -1.7147984281  <NA> #> 8800   2081    3F  CC67 2018 2018-08-20      CHLAC  2.2407096893  <NA> #> 8801   2081    3F  CC67 2018 2018-08-20      COLOR  5.0751738152  <NA> #> 8802   2081    3F  CC67 2018 2018-08-20       COND  5.3706380281  <NA> #> 8803   2081    3F  CC67 2018 2018-08-20         DO  1.5216989981  <NA> #> 8804   2081    3F  CC67 2018 2018-08-20      DOSAT  4.0758410907  <NA> #> 8805   2081    3F  CC67 2018 2018-08-20       NO23 -3.4420193762  <NA> #> 8806   2081    3F  CC67 2018 2018-08-20      SALIN -2.3025850930  <NA> #> 8807   2081    3F  CC67 2018 2018-08-20        TKN -0.0618754037  <NA> #> 8808   2081    3F  CC67 2018 2018-08-20         TN -0.0283994745     + #> 8809   2081    3F  CC67 2018 2018-08-20         TP -2.4534079827  <NA> #> 8810   2081    3F  CC67 2018 2018-08-20        TSS  2.1972245773     I #> 8811   2081    3F  CC67 2018 2018-08-20       TURB  1.9315214116  <NA> #> 8812   2081    3F  CC67 2018 2018-09-10      CHLAC  1.5260563035  <NA> #> 8813   2081    3F  CC67 2018 2018-09-10      COLOR  4.4998096703     A #> 8814   2081    3F  CC67 2018 2018-09-10       COND  6.0520891689  <NA> #> 8815   2081    3F  CC67 2018 2018-09-10         DO  1.9865035460  <NA> #> 8816   2081    3F  CC67 2018 2018-09-10      DOSAT  4.5941092386  <NA> #> 8817   2081    3F  CC67 2018 2018-09-10      SALIN -1.6094379124  <NA> #> 8818   2081    3F  CC67 2018 2018-09-10         TN -0.2057949130     + #> 8819   2081    3F  CC67 2018 2018-09-10        TSS  2.3025850930     A #> 8820   2081    3F  CC67 2018 2018-09-10       TURB  2.0281482473  <NA> #> 8821   2081    3F  CC67 2018 2018-11-12      CHLAC  2.2300144002  <NA> #> 8822   2081    3F  CC67 2018 2018-11-12      COLOR  3.9120230054  <NA> #> 8823   2081    3F  CC67 2018 2018-11-12       COND  6.2595814641  <NA> #> 8824   2081    3F  CC67 2018 2018-11-12         DO  2.1174596089  <NA> #> 8825   2081    3F  CC67 2018 2018-11-12      DOSAT  4.6180864113  <NA> #> 8826   2081    3F  CC67 2018 2018-11-12       NO23 -2.3751557858  <NA> #> 8827   2081    3F  CC67 2018 2018-11-12      SALIN -1.3862943611  <NA> #> 8828   2081    3F  CC67 2018 2018-11-12        TKN -0.2484613593  <NA> #> 8829   2081    3F  CC67 2018 2018-11-12         TN -0.1358197231     + #> 8830   2081    3F  CC67 2018 2018-11-12         TP -2.8473122684  <NA> #> 8831   2081    3F  CC67 2018 2018-11-12        TSS  2.1972245773     I #> 8832   2081    3F  CC67 2018 2018-11-12       TURB  2.0014800002     A #> 8833  2082A    3F  CC70 2018 2018-10-18      CHLAC  0.9932517730  <NA> #> 8834  2082A    3F  CC70 2018 2018-10-18      COLOR  4.2484952420  <NA> #> 8835  2082A    3F  CC70 2018 2018-10-18       COND  5.5721540322  <NA> #> 8836  2082A    3F  CC70 2018 2018-10-18         DO  1.7681496036  <NA> #> 8837  2082A    3F  CC70 2018 2018-10-18      DOSAT  4.3148178850  <NA> #> 8838  2082A    3F  CC70 2018 2018-10-18       NO23 -2.1202635362  <NA> #> 8839  2082A    3F  CC70 2018 2018-10-18      SALIN -2.1202635362  <NA> #> 8840  2082A    3F  CC70 2018 2018-10-18        TKN  0.1823215568  <NA> #> 8841  2082A    3F  CC70 2018 2018-10-18         TN  0.2776317366     + #> 8842  2082A    3F  CC70 2018 2018-10-18         TP -3.0365542681  <NA> #> 8843  2082A    3F  CC70 2018 2018-10-18        TSS  2.3978952728     A #> 8844  2082A    3F  CC70 2018 2018-10-18       TURB  1.9600947840  <NA> #> 8845  2082A    3F  CC70 2019 2019-05-08      CHLAC  0.4054651081     I #> 8846  2082A    3F  CC70 2019 2019-05-08      COLOR  3.5263605246     A #> 8847  2082A    3F  CC70 2019 2019-05-08       COND  6.4167322825  <NA> #> 8848  2082A    3F  CC70 2019 2019-05-08         DO  1.6900958155  <NA> #> 8849  2082A    3F  CC70 2019 2019-05-08      DOSAT  4.2384449062  <NA> #> 8850  2082A    3F  CC70 2019 2019-05-08       NO23 -5.5214609179     U #> 8851  2082A    3F  CC70 2019 2019-05-08      SALIN -1.2039728043  <NA> #> 8852  2082A    3F  CC70 2019 2019-05-08        TKN -0.3011050928  <NA> #> 8853  2082A    3F  CC70 2019 2019-05-08         TN -0.2984060358     + #> 8854  2082A    3F  CC70 2019 2019-05-08         TP -3.1941832123  <NA> #> 8855  2082A    3F  CC70 2019 2019-05-08        TSS  0.6931471806     I #> 8856  2082A    3F  CC70 2019 2019-05-08       TURB  1.2527629685  <NA> #> 8857   2079     2  CC74 2017 2017-03-13       COND 11.1102514581  <NA> #> 8858   2079     2  CC74 2017 2017-03-13         DO  2.0668627595  <NA> #> 8859   2079     2  CC74 2017 2017-03-13      DOSAT  4.8362819070  <NA> #> 8860   2079     2  CC74 2017 2017-03-13      SALIN  3.8066624898  <NA> #> 8861   2079     2  CC74 2017 2017-05-15      CHLAC  0.9162907319  <NA> #> 8862   2079     2  CC74 2017 2017-05-15       COND 10.9460055668  <NA> #> 8863   2079     2  CC74 2017 2017-05-15         DO  1.7917594692  <NA> #> 8864   2079     2  CC74 2017 2017-05-15      DOSAT  4.2341065046  <NA> #> 8865   2079     2  CC74 2017 2017-05-15       NO23 -4.8283137373     U #> 8866   2079     2  CC74 2017 2017-05-15      SALIN  3.5759906720     + #> 8867   2079     2  CC74 2017 2017-05-15        TKN -0.3011050928  <NA> #> 8868   2079     2  CC74 2017 2017-05-15         TN -0.2957142441     + #> 8869   2079     2  CC74 2017 2017-05-15         TP -3.6888794541  <NA> #> 8870   2079     2  CC74 2017 2017-05-15        TSS  1.3862943611     I #> 8871   2079     2  CC74 2017 2017-05-15       TURB  0.0000000000  <NA> #> 8872   2079     2  CC74 2017 2017-07-20      CHLAC  1.5475625087  <NA> #> 8873   2079     2  CC74 2017 2017-07-20       COND 10.6434228946  <NA> #> 8874   2079     2  CC74 2017 2017-07-20         DO  1.5040773968  <NA> #> 8875   2079     2  CC74 2017 2017-07-20      DOSAT  4.2484952420  <NA> #> 8876   2079     2  CC74 2017 2017-07-20       NO23 -5.5214609179     U #> 8877   2079     2  CC74 2017 2017-07-20        TKN -0.0943106795  <NA> #> 8878   2079     2  CC74 2017 2017-07-20         TN -0.0921152889     + #> 8879   2079     2  CC74 2017 2017-07-20         TP -3.4112477175  <NA> #> 8880   2079     2  CC74 2017 2017-07-20        TSS  1.0986122887     U #> 8881   2079     2  CC74 2017 2017-07-20       TURB  0.4054651081  <NA> #> 8882   2079     2  CC74 2017 2017-10-24       COND 10.5655567775  <NA> #> 8883   2079     2  CC74 2017 2017-10-24         DO  1.4586150227  <NA> #> 8884   2079     2  CC74 2017 2017-10-24      DOSAT  4.1431347264  <NA> #> 8885   2079     2  CC74 2017 2017-10-24      SALIN  3.1531632815     + #> 8886   2079     2  CC74 2018 2018-03-15      CHLAC  2.0918640617  <NA> #> 8887   2079     2  CC74 2018 2018-03-15       COND 11.0381102787  <NA> #> 8888   2079     2  CC74 2018 2018-03-15         DO  2.2407096893  <NA> #> 8889   2079     2  CC74 2018 2018-03-15      DOSAT  4.9972122738  <NA> #> 8890   2079     2  CC74 2018 2018-03-15       NO23 -4.1997050779  <NA> #> 8891   2079     2  CC74 2018 2018-03-15        TKN -0.1508228897  <NA> #> 8892   2079     2  CC74 2018 2018-03-15         TN -0.1335313926     + #> 8893   2079     2  CC74 2018 2018-03-15         TP -3.1941832123  <NA> #> 8894   2079     2  CC74 2018 2018-03-15        TSS  1.9459101491     I #> 8895   2079     2  CC74 2018 2018-03-15       TURB  1.0986122887  <NA> #> 8896   2079     2  CC74 2018 2018-04-23      CHLAC  2.7725887222  <NA> #> 8897   2079     2  CC74 2018 2018-04-23       COND 10.9748485413  <NA> #> 8898   2079     2  CC74 2018 2018-04-23         DO  2.2823823857  <NA> #> 8899   2079     2  CC74 2018 2018-04-23      DOSAT  5.0498560072  <NA> #> 8900   2079     2  CC74 2018 2018-04-23       NO23 -5.5214609179     U #> 8901   2079     2  CC74 2018 2018-04-23      SALIN  3.5937442590     + #> 8902   2079     2  CC74 2018 2018-04-23        TKN -0.1984509387  <NA> #> 8903   2079     2  CC74 2018 2018-04-23         TN -0.1960148839     + #> 8904   2079     2  CC74 2018 2018-04-23         TP -3.2441936329  <NA> #> 8905   2079     2  CC74 2018 2018-04-23        TSS  2.4849066498  <NA> #> 8906   2079     2  CC74 2018 2018-04-23       TURB  0.6931471806  <NA> #> 8907   2079     2  CC74 2018 2018-06-11      CHLAC  3.1780538303  <NA> #> 8908   2079     2  CC74 2018 2018-06-11       COND 10.6286177789  <NA> #> 8909   2079     2  CC74 2018 2018-06-11         DO  1.8245492921  <NA> #> 8910   2079     2  CC74 2018 2018-06-11      DOSAT  4.5643481915  <NA> #> 8911   2079     2  CC74 2018 2018-06-11       NO23 -5.5214609179     U #> 8912   2079     2  CC74 2018 2018-06-11      SALIN  3.2695689392  <NA> #> 8913   2079     2  CC74 2018 2018-06-11        TKN -0.0943106795  <NA> #> 8914   2079     2  CC74 2018 2018-06-11         TN -0.0921152889     + #> 8915   2079     2  CC74 2018 2018-06-11         TP -2.9957322736  <NA> #> 8916   2079     2  CC74 2018 2018-06-11        TSS  1.7917594692     I #> 8917   2079     2  CC74 2018 2018-06-11       TURB  1.1314021115  <NA> #> 8918   2079     2  CC74 2018 2018-08-07      CHLAC  1.9600947840  <NA> #> 8919   2079     2  CC74 2018 2018-08-07       COND 10.5844609322  <NA> #> 8920   2079     2  CC74 2018 2018-08-07         DO  1.9387416596  <NA> #> 8921   2079     2  CC74 2018 2018-08-07      DOSAT  4.6709579265  <NA> #> 8922   2079     2  CC74 2018 2018-08-07       NO23 -5.5214609179     U #> 8923   2079     2  CC74 2018 2018-08-07      SALIN  3.2200751054  <NA> #> 8924   2079     2  CC74 2018 2018-08-07        TKN -0.0202027073  <NA> #> 8925   2079     2  CC74 2018 2018-08-07         TN -0.0181639706     + #> 8926   2079     2  CC74 2018 2018-08-07         TP -2.6882475738  <NA> #> 8927   2079     2  CC74 2018 2018-08-07        TSS  1.0986122887     U #> 8928   2079     2  CC74 2018 2018-08-07       TURB  0.4054651081  <NA> #> 8929   2079     2  CC74 2018 2018-09-06      CHLAC  1.6486586256  <NA> #> 8930   2079     2  CC74 2018 2018-09-06       COND 10.3441267357  <NA> #> 8931   2079     2  CC74 2018 2018-09-06         DO  1.4231083342  <NA> #> 8932   2079     2  CC74 2018 2018-09-06      DOSAT  4.1026433650  <NA> #> 8933   2079     2  CC74 2018 2018-09-06       NO23 -5.5214609179     U #> 8934   2079     2  CC74 2018 2018-09-06      SALIN  2.9559514035  <NA> #> 8935   2079     2  CC74 2018 2018-09-06        TKN  0.7419373447  <NA> #> 8936   2079     2  CC74 2018 2018-09-06         TN  0.7428892725     + #> 8937   2079     2  CC74 2018 2018-09-06         TP -2.5770219387  <NA> #> 8938   2079     2  CC74 2018 2018-09-06        TSS  1.0986122887     I #> 8939   2079     2  CC74 2018 2018-09-06       TURB  0.0953101798  <NA> #> 8940   2079     2  CC74 2019 2019-04-17      CHLAC  2.1162555148  <NA> #> 8941   2079     2  CC74 2019 2019-04-17       COND 10.8549137412  <NA> #> 8942   2079     2  CC74 2019 2019-04-17         DO  2.2159372863  <NA> #> 8943   2079     2  CC74 2019 2019-04-17      DOSAT  4.9236239171  <NA> #> 8944   2079     2  CC74 2019 2019-04-17       NO23 -5.5214609179     U #> 8945   2079     2  CC74 2019 2019-04-17      SALIN  3.5269485870  <NA> #> 8946   2079     2  CC74 2019 2019-04-17        TKN -0.1278333715  <NA> #> 8947   2079     2  CC74 2019 2019-04-17         TN -0.1255632230     + #> 8948   2079     2  CC74 2019 2019-04-17         TP -3.4737680745  <NA> #> 8949   2079     2  CC74 2019 2019-04-17        TSS  3.4011973817  <NA> #> 8950   2079     2  CC74 2019 2019-04-17       TURB -0.2231435513  <NA> #> 8951   2079     2  CC74 2019 2019-07-15      CHLAC  3.7612001157  <NA> #> 8952   2079     2  CC74 2019 2019-07-15       COND 10.6353745614  <NA> #> 8953   2079     2  CC74 2019 2019-07-15         DO  1.9796212064  <NA> #> 8954   2079     2  CC74 2019 2019-07-15      DOSAT  4.7104306966  <NA> #> 8955   2079     2  CC74 2019 2019-07-15       NO23 -5.5214609179     U #> 8956   2079     2  CC74 2019 2019-07-15      SALIN  3.2782761681  <NA> #> 8957   2079     2  CC74 2019 2019-07-15        TKN  0.0953101798  <NA> #> 8958   2079     2  CC74 2019 2019-07-15         TN  0.0971267107     + #> 8959   2079     2  CC74 2019 2019-07-15         TP -2.7806208939  <NA> #> 8960   2079     2  CC74 2019 2019-07-15        TSS  2.8332133441  <NA> #> 8961   2079     2  CC74 2019 2019-07-15       TURB  1.6094379124  <NA> #> 8962   2079     2  CC74 2019 2019-08-19      CHLAC  2.4849066498  <NA> #> 8963   2079     2  CC74 2019 2019-08-19       COND 10.4673514473  <NA> #> 8964   2079     2  CC74 2019 2019-08-19         DO  1.3635373740  <NA> #> 8965   2079     2  CC74 2019 2019-08-19      DOSAT  4.0826093060  <NA> #> 8966   2079     2  CC74 2019 2019-08-19       NO23 -5.5214609179     U #> 8967   2079     2  CC74 2019 2019-08-19      SALIN  3.0901329490  <NA> #> 8968   2079     2  CC74 2019 2019-08-19        TKN  0.4054651081  <NA> #> 8969   2079     2  CC74 2019 2019-08-19         TN  0.4067975533     + #> 8970   2079     2  CC74 2019 2019-08-19         TP -3.2968373663  <NA> #> 8971   2079     2  CC74 2019 2019-08-19        TSS  2.4849066498  <NA> #> 8972   2079     2  CC74 2019 2019-08-19       TURB  0.7419373447  <NA> #> 8973   2079     2  CC74 2019 2019-09-11      CHLAC  2.9444389792  <NA> #> 8974   2079     2  CC74 2019 2019-09-11       COND 10.7330214205  <NA> #> 8975   2079     2  CC74 2019 2019-09-11         DO  1.7783364489  <NA> #> 8976   2079     2  CC74 2019 2019-09-11      DOSAT  4.5152454785  <NA> #> 8977   2079     2  CC74 2019 2019-09-11       NO23 -5.5214609179     U #> 8978   2079     2  CC74 2019 2019-09-11      SALIN  3.3874364664  <NA> #> 8979   2079     2  CC74 2019 2019-09-11        TKN -0.0100503359  <NA> #> 8980   2079     2  CC74 2019 2019-09-11         TN -0.0080321717     + #> 8981   2079     2  CC74 2019 2019-09-11         TP -2.8647040111  <NA> #> 8982   2079     2  CC74 2019 2019-09-11        TSS  1.3862943611     I #> 8983   2079     2  CC74 2019 2019-09-11       TURB  0.7884573604  <NA> #> 8984   2079     2  CC74 2019 2019-10-09      CHLAC  3.4339872045  <NA> #> 8985   2079     2  CC74 2019 2019-10-09       COND 10.7419897010  <NA> #> 8986   2079     2  CC74 2019 2019-10-09         DO  1.5432981099  <NA> #> 8987   2079     2  CC74 2019 2019-10-09      DOSAT  4.2640873368  <NA> #> 8988   2079     2  CC74 2019 2019-10-09       NO23 -5.5214609179     U #> 8989   2079     2  CC74 2019 2019-10-09      SALIN  3.3981928726  <NA> #> 8990   2079     2  CC74 2019 2019-10-09        TKN -0.1278333715  <NA> #> 8991   2079     2  CC74 2019 2019-10-09         TN -0.1255632230     + #> 8992   2079     2  CC74 2019 2019-10-09         TP -2.8302178351  <NA> #> 8993   2079     2  CC74 2019 2019-10-09        TSS  1.9459101491     I #> 8994   2079     2  CC74 2019 2019-10-09       TURB  0.6931471806  <NA> #> 8995   2079     2  CC74 2020 2020-02-13      CHLAC  2.3978952728  <NA> #> 8996   2079     2  CC74 2020 2020-02-13       COND 10.7930235471  <NA> #> 8997   2079     2  CC74 2020 2020-02-13         DO  2.0464016876  <NA> #> 8998   2079     2  CC74 2020 2020-02-13      DOSAT  4.7388265708  <NA> #> 8999   2079     2  CC74 2020 2020-02-13       NO23 -5.5214609179     U #> 9000   2079     2  CC74 2020 2020-02-13      SALIN  3.4575777151  <NA> #> 9001   2079     2  CC74 2020 2020-02-13        TKN -0.0512932944  <NA> #> 9002   2079     2  CC74 2020 2020-02-13         TN -0.0491902442     + #> 9003   2079     2  CC74 2020 2020-02-13         TP -3.0365542681  <NA> #> 9004   2079     2  CC74 2020 2020-02-13        TSS  2.3025850930     I #> 9005   2079     2  CC74 2020 2020-02-13       TURB  0.6931471806  <NA> #> 9006   2079     2  CC74 2020 2020-03-24      CHLAC  2.0014800002  <NA> #> 9007   2079     2  CC74 2020 2020-03-24       COND 10.9585136130  <NA> #> 9008   2079     2  CC74 2020 2020-03-24         DO  1.8115620965  <NA> #> 9009   2079     2  CC74 2020 2020-03-24      DOSAT  4.5664293577  <NA> #> 9010   2079     2  CC74 2020 2020-03-24       NO23 -5.5214609179     U #> 9011   2079     2  CC74 2020 2020-03-24      SALIN  3.6425737012  <NA> #> 9012   2079     2  CC74 2020 2020-03-24        TKN -0.0512932944  <NA> #> 9013   2079     2  CC74 2020 2020-03-24         TN -0.0491902442     + #> 9014   2079     2  CC74 2020 2020-03-24         TP -3.3242363405  <NA> #> 9015   2079     2  CC74 2020 2020-03-24        TSS  1.6094379124     I #> 9016   2079     2  CC74 2020 2020-03-24       TURB  0.7419373447  <NA> #> 9017   2079     2  CC74 2020 2020-06-15      CHLAC  3.1354942159  <NA> #> 9018   2079     2  CC74 2020 2020-06-15       COND 10.7369834598  <NA> #> 9019   2079     2  CC74 2020 2020-06-15         DO  0.5822156199  <NA> #> 9020   2079     2  CC74 2020 2020-06-15      DOSAT  3.3141860047  <NA> #> 9021   2079     2  CC74 2020 2020-06-15       NO23 -5.5214609179     U #> 9022   2079     2  CC74 2020 2020-06-15      SALIN  3.3924929410  <NA> #> 9023   2079     2  CC74 2020 2020-06-15        TKN  0.3364722366  <NA> #> 9024   2079     2  CC74 2020 2020-06-15         TN  0.3378997886     + #> 9025   2079     2  CC74 2020 2020-06-15         TP -2.7488721956  <NA> #> 9026   2079     2  CC74 2020 2020-06-15        TSS  1.3862943611     I #> 9027   2079     2  CC74 2020 2020-06-15       TURB  2.0668627595  <NA> #> 9028   2079     2  CC74 2020 2020-07-27      CHLAC  3.4339872045  <NA> #> 9029   2079     2  CC74 2020 2020-07-27       COND 10.7988201898  <NA> #> 9030   2079     2  CC74 2020 2020-07-27         DO  1.9572739077  <NA> #> 9031   2079     2  CC74 2020 2020-07-27      DOSAT  4.7326835063  <NA> #> 9032   2079     2  CC74 2020 2020-07-27       NO23 -5.5214609179     U #> 9033   2079     2  CC74 2020 2020-07-27      SALIN  3.4594662898  <NA> #> 9034   2079     2  CC74 2020 2020-07-27        TKN  0.0000000000  <NA> #> 9035   2079     2  CC74 2020 2020-07-27         TN  0.0019980027     + #> 9036   2079     2  CC74 2020 2020-07-27         TP -3.1700856607  <NA> #> 9037   2079     2  CC74 2020 2020-07-27        TSS  1.7917594692     I #> 9038   2079     2  CC74 2020 2020-07-27       TURB  1.2809338455  <NA> #> 9039   2079     2  CC74 2023 2023-02-13      CHLAC  3.3672958300  <NA> #> 9040   2079     2  CC74 2023 2023-02-13       COND 10.8175959048  <NA> #> 9041   2079     2  CC74 2023 2023-02-13         DO  1.8277699068  <NA> #> 9042   2079     2  CC74 2023 2023-02-13      DOSAT  4.4091553021  <NA> #> 9043   2079     2  CC74 2023 2023-02-13       NO23 -5.5214609179     U #> 9044   2079     2  CC74 2023 2023-02-13      SALIN  3.4879865117  <NA> #> 9045   2079     2  CC74 2023 2023-02-13        TKN  0.2623642645  <NA> #> 9046   2079     2  CC74 2023 2023-02-13         TN  0.2639015438     + #> 9047   2079     2  CC74 2023 2023-02-13         TP -2.2072749132  <NA> #> 9048   2079     2  CC74 2023 2023-02-13        TSS  2.8903717579     A #> 9049   2079     2  CC74 2023 2023-02-13       TURB  1.4350845253  <NA> #> 9050   2079     2  CC74 2023 2023-04-10       COND 10.9901959367  <NA> #> 9051   2079     2  CC74 2023 2023-04-10         DO  1.6714733034  <NA> #> 9052   2079     2  CC74 2023 2023-04-10      DOSAT  4.3770140929  <NA> #> 9053   2079     2  CC74 2023 2023-04-10       NO23 -5.5214609179     U #> 9054   2079     2  CC74 2023 2023-04-10      SALIN  3.6810992668  <NA> #> 9055   2079     2  CC74 2023 2023-04-10        TKN -0.0618754037  <NA> #> 9056   2079     2  CC74 2023 2023-04-10         TN -0.0597500044     + #> 9057   2079     2  CC74 2023 2023-04-10         TP -3.4737680745  <NA> #> 9058   2079     2  CC74 2023 2023-04-10        TSS  1.3862943611     I #> 9059   2079     2  CC74 2014 2014-03-26      SALIN  3.5351453542  <NA> #> 9060   2079     2  CC74 2014 2014-03-26      SALIN  3.5351453542  <NA> #> 9061   2079     2  CC74 2014 2014-07-22      SALIN  3.4719664526  <NA> #> 9062   2079     2  CC74 2014 2014-07-22      SALIN  3.4719664526  <NA> #> 9063   2079     2  CC74 2014 2014-09-11         DO  1.5475625087  <NA> #> 9064   2079     2  CC74 2014 2014-09-11      DOSAT  4.3280982926     + #> 9065   2079     2  CC74 2014 2014-09-11      SALIN  3.4011973817  <NA> #> 9066   2079     2  CC74 2015 2015-09-14      SALIN  3.1986731176  <NA> #> 9067   2079     2  CC74 2015 2015-09-14      SALIN  3.1986731176  <NA> #> 9068   2079     2  CC74 2016 2016-05-18         DO  2.1282317058  <NA> #> 9069   2079     2  CC74 2016 2016-05-18      DOSAT  4.8933521335     + #> 9070   2079     2  CC74 2016 2016-05-18      SALIN  3.5145260670  <NA> #> 9071   2079     2  CC74 2016 2016-05-18         DO  2.2721258855  <NA> #> 9072   2079     2  CC74 2016 2016-05-18      DOSAT  5.0395466376     + #> 9073   2079     2  CC74 2016 2016-05-18      SALIN  3.5174978374  <NA> #> 9074   2079     2  CC74 2016 2016-08-01         DO  2.1282317058  <NA> #> 9075   2079     2  CC74 2016 2016-08-01      DOSAT  4.9243509255     + #> 9076   2079     2  CC74 2016 2016-08-01      SALIN  3.4531571206  <NA> #> 9077   2079     2  CC74 2016 2016-08-01         DO  2.1162555148  <NA> #> 9078   2079     2  CC74 2016 2016-08-01      DOSAT  4.9170569471     + #> 9079   2079     2  CC74 2016 2016-08-01      SALIN  3.4995332824  <NA> #> 9080   2079     2  CC74 2016 2016-08-17         DO  2.0014800002  <NA> #> 9081   2079     2  CC74 2016 2016-08-17      DOSAT  4.7578912730     + #> 9082   2079     2  CC74 2016 2016-08-17      SALIN  3.3357695763  <NA> #> 9083   2079     2  CC74 2016 2016-08-17         DO  1.9021075264  <NA> #> 9084   2079     2  CC74 2016 2016-08-17      DOSAT  4.6672055769     + #> 9085   2079     2  CC74 2016 2016-08-17      SALIN  3.4111477125  <NA> #> 9086   2079     2  CC74 2016 2016-09-08         DO  1.9459101491  <NA> #> 9087   2079     2  CC74 2016 2016-09-08      DOSAT  4.6463121293     + #> 9088   2079     2  CC74 2016 2016-09-08      SALIN  3.0492730405  <NA> #> 9089   2079     2  CC74 2016 2016-09-08         DO  1.7749523509  <NA> #> 9090   2079     2  CC74 2016 2016-09-08      DOSAT  4.5009201646     + #>      newComment disqual disqual2 #> 1          <NA>      NA       NA #> 2             U      NA       NA #> 3             +      NA       NA #> 4             U      NA       NA #> 5          <NA>      NA       NA #> 6          <NA>      NA       NA #> 7             +      NA       NA #> 8          <NA>      NA       NA #> 9          <NA>      NA       NA #> 10            I      NA       NA #> 11            U      NA       NA #> 12         <NA>      NA       NA #> 13            +      NA       NA #> 14            I      NA       NA #> 15         <NA>      NA       NA #> 16         <NA>      NA       NA #> 17            +      NA       NA #> 18         <NA>      NA       NA #> 19         <NA>      NA       NA #> 20         <NA>      NA       NA #> 21         <NA>      NA       NA #> 22         <NA>      NA       NA #> 23            +      NA       NA #> 24            I      NA       NA #> 25         <NA>      NA       NA #> 26         <NA>      NA       NA #> 27            +      NA       NA #> 28         <NA>      NA       NA #> 29            A      NA       NA #> 30         <NA>      NA       NA #> 31         <NA>      NA       NA #> 32         <NA>      NA       NA #> 33            +      NA       NA #> 34            I      NA       NA #> 35         <NA>      NA       NA #> 36         <NA>      NA       NA #> 37            +      NA       NA #> 38         <NA>      NA       NA #> 39         <NA>      NA       NA #> 40         <NA>      NA       NA #> 41         <NA>      NA       NA #> 42         <NA>      NA       NA #> 43            U      NA       NA #> 44         <NA>      NA       NA #> 45            +      NA       NA #> 46         <NA>      NA       NA #> 47         <NA>      NA       NA #> 48         <NA>      NA       NA #> 49         <NA>      NA       NA #> 50         <NA>      NA       NA #> 51            +      NA       NA #> 52            U      NA       NA #> 53         <NA>      NA       NA #> 54            +      NA       NA #> 55         <NA>      NA       NA #> 56         <NA>      NA       NA #> 57         <NA>      NA       NA #> 58         <NA>      NA       NA #> 59            +      NA       NA #> 60            I      NA       NA #> 61         <NA>      NA       NA #> 62         <NA>      NA       NA #> 63            +      NA       NA #> 64         <NA>      NA       NA #> 65         <NA>      NA       NA #> 66         <NA>      NA       NA #> 67         <NA>      NA       NA #> 68            +      NA       NA #> 69         <NA>      NA       NA #> 70         <NA>      NA       NA #> 71         <NA>      NA       NA #> 72            +      NA       NA #> 73         <NA>      NA       NA #> 74         <NA>      NA       NA #> 75            A      NA       NA #> 76            A      NA       NA #> 77            +      NA       NA #> 78         <NA>      NA       NA #> 79         <NA>      NA       NA #> 80         <NA>      NA       NA #> 81            +      NA       NA #> 82         <NA>      NA       NA #> 83         <NA>      NA       NA #> 84         <NA>      NA       NA #> 85            A      NA       NA #> 86            +      NA       NA #> 87         <NA>      NA       NA #> 88         <NA>      NA       NA #> 89         <NA>      NA       NA #> 90            +      NA       NA #> 91         <NA>      NA       NA #> 92         <NA>      NA       NA #> 93         <NA>      NA       NA #> 94         <NA>      NA       NA #> 95         <NA>      NA       NA #> 96            +      NA       NA #> 97            I      NA       NA #> 98         <NA>      NA       NA #> 99         <NA>      NA       NA #> 100           +      NA       NA #> 101        <NA>      NA       NA #> 102        <NA>      NA       NA #> 103           I      NA       NA #> 104           U      NA       NA #> 105        <NA>      NA       NA #> 106           +      NA       NA #> 107           I      NA       NA #> 108        <NA>      NA       NA #> 109           I      NA       NA #> 110           +      NA       NA #> 111        <NA>      NA       NA #> 112        <NA>      NA       NA #> 113        <NA>      NA       NA #> 114        <NA>      NA       NA #> 115        <NA>      NA       NA #> 116           +      NA       NA #> 117           U      NA       NA #> 118        <NA>      NA       NA #> 119        <NA>      NA       NA #> 120           +      NA       NA #> 121        <NA>      NA       NA #> 122        <NA>      NA       NA #> 123        <NA>      NA       NA #> 124        <NA>      NA       NA #> 125        <NA>      NA       NA #> 126           +      NA       NA #> 127           U      NA       NA #> 128        <NA>      NA       NA #> 129           I      NA       NA #> 130           +      NA       NA #> 131        <NA>      NA       NA #> 132        <NA>      NA       NA #> 133        <NA>      NA       NA #> 134        <NA>      NA       NA #> 135        <NA>      NA       NA #> 136           +      NA       NA #> 137        <NA>      NA       NA #> 138        <NA>      NA       NA #> 139        <NA>      NA       NA #> 140           +      NA       NA #> 141        <NA>      NA       NA #> 142        <NA>      NA       NA #> 143        <NA>      NA       NA #> 144        <NA>      NA       NA #> 145        <NA>      NA       NA #> 146           +      NA       NA #> 147        <NA>      NA       NA #> 148        <NA>      NA       NA #> 149        <NA>      NA       NA #> 150           +      NA       NA #> 151        <NA>      NA       NA #> 152        <NA>      NA       NA #> 153        <NA>      NA       NA #> 154        <NA>      NA       NA #> 155        <NA>      NA       NA #> 156           +      NA       NA #> 157        <NA>      NA       NA #> 158        <NA>      NA       NA #> 159        <NA>      NA       NA #> 160           +      NA       NA #> 161        <NA>      NA       NA #> 162        <NA>      NA       NA #> 163        <NA>      NA       NA #> 164        <NA>      NA       NA #> 165        <NA>      NA       NA #> 166           +      NA       NA #> 167        <NA>      NA       NA #> 168        <NA>      NA       NA #> 169        <NA>      NA       NA #> 170           +      NA       NA #> 171        <NA>      NA       NA #> 172        <NA>      NA       NA #> 173        <NA>      NA       NA #> 174        <NA>      NA       NA #> 175        <NA>      NA       NA #> 176           +      NA       NA #> 177        <NA>      NA       NA #> 178        <NA>      NA       NA #> 179        <NA>      NA       NA #> 180           +      NA       NA #> 181        <NA>      NA       NA #> 182        <NA>      NA       NA #> 183        <NA>      NA       NA #> 184        <NA>      NA       NA #> 185        <NA>      NA       NA #> 186           +      NA       NA #> 187           I      NA       NA #> 188        <NA>      NA       NA #> 189        <NA>      NA       NA #> 190           +      NA       NA #> 191        <NA>      NA       NA #> 192        <NA>      NA       NA #> 193        <NA>      NA       NA #> 194        <NA>      NA       NA #> 195        <NA>      NA       NA #> 196           +      NA       NA #> 197        <NA>      NA       NA #> 198        <NA>      NA       NA #> 199        <NA>      NA       NA #> 200           +      NA       NA #> 201        <NA>      NA       NA #> 202        <NA>      NA       NA #> 203           I      NA       NA #> 204        <NA>      NA       NA #> 205        <NA>      NA       NA #> 206           +      NA       NA #> 207           U      NA       NA #> 208        <NA>      NA       NA #> 209           I      NA       NA #> 210           +      NA       NA #> 211        <NA>      NA       NA #> 212        <NA>      NA       NA #> 213        <NA>      NA       NA #> 214        <NA>      NA       NA #> 215        <NA>      NA       NA #> 216           +      NA       NA #> 217           I      NA       NA #> 218        <NA>      NA       NA #> 219        <NA>      NA       NA #> 220           +      NA       NA #> 221        <NA>      NA       NA #> 222        <NA>      NA       NA #> 223        <NA>      NA       NA #> 224        <NA>      NA       NA #> 225        <NA>      NA       NA #> 226           +      NA       NA #> 227        <NA>      NA       NA #> 228        <NA>      NA       NA #> 229        <NA>      NA       NA #> 230           +      NA       NA #> 231        <NA>      NA       NA #> 232        <NA>      NA       NA #> 233        <NA>      NA       NA #> 234        <NA>      NA       NA #> 235        <NA>      NA       NA #> 236           +      NA       NA #> 237           I      NA       NA #> 238        <NA>      NA       NA #> 239        <NA>      NA       NA #> 240           +      NA       NA #> 241        <NA>      NA       NA #> 242        <NA>      NA       NA #> 243        <NA>      NA       NA #> 244        <NA>      NA       NA #> 245        <NA>      NA       NA #> 246           +      NA       NA #> 247        <NA>      NA       NA #> 248        <NA>      NA       NA #> 249        <NA>      NA       NA #> 250           +      NA       NA #> 251        <NA>      NA       NA #> 252        <NA>      NA       NA #> 253           I      NA       NA #> 254           U      NA       NA #> 255        <NA>      NA       NA #> 256           +      NA       NA #> 257           I      NA       NA #> 258        <NA>      NA       NA #> 259        <NA>      NA       NA #> 260           +      NA       NA #> 261        <NA>      NA       NA #> 262        <NA>      NA       NA #> 263        <NA>      NA       NA #> 264           I      NA       NA #> 265        <NA>      NA       NA #> 266           +      NA       NA #> 267        <NA>      NA       NA #> 268        <NA>      NA       NA #> 269        <NA>      NA       NA #> 270           +      NA       NA #> 271        <NA>      NA       NA #> 272        <NA>      NA       NA #> 273           I      NA       NA #> 274           U      NA       NA #> 275        <NA>      NA       NA #> 276           +      NA       NA #> 277           U      NA       NA #> 278        <NA>      NA       NA #> 279        <NA>      NA       NA #> 280           +      NA       NA #> 281        <NA>      NA       NA #> 282        <NA>      NA       NA #> 283        <NA>      NA       NA #> 284        <NA>      NA       NA #> 285           +      NA       NA #> 286        <NA>      NA       NA #> 287           I      NA       NA #> 288        <NA>      NA       NA #> 289        <NA>      NA       NA #> 290           +      NA       NA #> 291           I      NA       NA #> 292        <NA>      NA       NA #> 293        <NA>      NA       NA #> 294           +      NA       NA #> 295        <NA>      NA       NA #> 296        <NA>      NA       NA #> 297        <NA>      NA       NA #> 298           +      NA       NA #> 299        <NA>      NA       NA #> 300        <NA>      NA       NA #> 301           A      NA       NA #> 302        <NA>      NA       NA #> 303           +      NA       NA #> 304           I      NA       NA #> 305        <NA>      NA       NA #> 306        <NA>      NA       NA #> 307           +      NA       NA #> 308        <NA>      NA       NA #> 309        <NA>      NA       NA #> 310        <NA>      NA       NA #> 311        <NA>      NA       NA #> 312        <NA>      NA       NA #> 313           +      NA       NA #> 314        <NA>      NA       NA #> 315        <NA>      NA       NA #> 316        <NA>      NA       NA #> 317           +      NA       NA #> 318        <NA>      NA       NA #> 319           A      NA       NA #> 320        <NA>      NA       NA #> 321        <NA>      NA       NA #> 322           I      NA       NA #> 323        <NA>      NA       NA #> 324           +      NA       NA #> 325        <NA>      NA       NA #> 326        <NA>      NA       NA #> 327        <NA>      NA       NA #> 328        <NA>      NA       NA #> 329        <NA>      NA       NA #> 330           +      NA       NA #> 331        <NA>      NA       NA #> 332        <NA>      NA       NA #> 333        <NA>      NA       NA #> 334           +      NA       NA #> 335        <NA>      NA       NA #> 336        <NA>      NA       NA #> 337           I      NA       NA #> 338        <NA>      NA       NA #> 339        <NA>      NA       NA #> 340           +      NA       NA #> 341           I      NA       NA #> 342        <NA>      NA       NA #> 343        <NA>      NA       NA #> 344           +      NA       NA #> 345        <NA>      NA       NA #> 346        <NA>      NA       NA #> 347           I      NA       NA #> 348        <NA>      NA       NA #> 349        <NA>      NA       NA #> 350           +      NA       NA #> 351        <NA>      NA       NA #> 352        <NA>      NA       NA #> 353        <NA>      NA       NA #> 354           +      NA       NA #> 355        <NA>      NA       NA #> 356        <NA>      NA       NA #> 357        <NA>      NA       NA #> 358        <NA>      NA       NA #> 359        <NA>      NA       NA #> 360           +      NA       NA #> 361        <NA>      NA       NA #> 362        <NA>      NA       NA #> 363        <NA>      NA       NA #> 364           +      NA       NA #> 365        <NA>      NA       NA #> 366           A      NA       NA #> 367           I      NA       NA #> 368        <NA>      NA       NA #> 369        <NA>      NA       NA #> 370           +      NA       NA #> 371           U      NA       NA #> 372        <NA>      NA       NA #> 373        <NA>      NA       NA #> 374           +      NA       NA #> 375        <NA>      NA       NA #> 376        <NA>      NA       NA #> 377           I      NA       NA #> 378           I      NA       NA #> 379           +      NA       NA #> 380           U      NA       NA #> 381        <NA>      NA       NA #> 382        <NA>      NA       NA #> 383           +      NA       NA #> 384        <NA>      NA       NA #> 385        <NA>      NA       NA #> 386        <NA>      NA       NA #> 387        <NA>      NA       NA #> 388        <NA>      NA       NA #> 389        <NA>      NA       NA #> 390           U      NA       NA #> 391        <NA>      NA       NA #> 392        <NA>      NA       NA #> 393           +      NA       NA #> 394        <NA>      NA       NA #> 395        <NA>      NA       NA #> 396        <NA>      NA       NA #> 397        <NA>      NA       NA #> 398        <NA>      NA       NA #> 399        <NA>      NA       NA #> 400        <NA>      NA       NA #> 401        <NA>      NA       NA #> 402        <NA>      NA       NA #> 403           +      NA       NA #> 404        <NA>      NA       NA #> 405        <NA>      NA       NA #> 406        <NA>      NA       NA #> 407        <NA>      NA       NA #> 408        <NA>      NA       NA #> 409        <NA>      NA       NA #> 410           I      NA       NA #> 411        <NA>      NA       NA #> 412        <NA>      NA       NA #> 413           +      NA       NA #> 414        <NA>      NA       NA #> 415        <NA>      NA       NA #> 416           I      NA       NA #> 417        <NA>      NA       NA #> 418        <NA>      NA       NA #> 419        <NA>      NA       NA #> 420        <NA>      NA       NA #> 421        <NA>      NA       NA #> 422        <NA>      NA       NA #> 423           +      NA       NA #> 424        <NA>      NA       NA #> 425        <NA>      NA       NA #> 426           I      NA       NA #> 427        <NA>      NA       NA #> 428        <NA>      NA       NA #> 429        <NA>      NA       NA #> 430           I      NA       NA #> 431        <NA>      NA       NA #> 432           +      NA       NA #> 433        <NA>      NA       NA #> 434        <NA>      NA       NA #> 435        <NA>      NA       NA #> 436        <NA>      NA       NA #> 437        <NA>      NA       NA #> 438        <NA>      NA       NA #> 439           I      NA       NA #> 440        <NA>      NA       NA #> 441           I      NA       NA #> 442           +      NA       NA #> 443        <NA>      NA       NA #> 444        <NA>      NA       NA #> 445           I      NA       NA #> 446           I      NA       NA #> 447        <NA>      NA       NA #> 448        <NA>      NA       NA #> 449           I      NA       NA #> 450        <NA>      NA       NA #> 451        <NA>      NA       NA #> 452           +      NA       NA #> 453        <NA>      NA       NA #> 454        <NA>      NA       NA #> 455           I      NA       NA #> 456        <NA>      NA       NA #> 457        <NA>      NA       NA #> 458        <NA>      NA       NA #> 459           I      NA       NA #> 460        <NA>      NA       NA #> 461        <NA>      NA       NA #> 462           +      NA       NA #> 463        <NA>      NA       NA #> 464        <NA>      NA       NA #> 465        <NA>      NA       NA #> 466           I      NA       NA #> 467        <NA>      NA       NA #> 468        <NA>      NA       NA #> 469           I      NA       NA #> 470        <NA>      NA       NA #> 471        <NA>      NA       NA #> 472           +      NA       NA #> 473        <NA>      NA       NA #> 474        <NA>      NA       NA #> 475        <NA>      NA       NA #> 476           I      NA       NA #> 477        <NA>      NA       NA #> 478        <NA>      NA       NA #> 479        <NA>      NA       NA #> 480        <NA>      NA       NA #> 481        <NA>      NA       NA #> 482           +      NA       NA #> 483        <NA>      NA       NA #> 484        <NA>      NA       NA #> 485           I      NA       NA #> 486           U      NA       NA #> 487           I      NA       NA #> 488        <NA>      NA       NA #> 489           +      NA       NA #> 490        <NA>      NA       NA #> 491        <NA>      NA       NA #> 492           I      NA       NA #> 493        <NA>      NA       NA #> 494        <NA>      NA       NA #> 495        <NA>      NA       NA #> 496        <NA>      NA       NA #> 497        <NA>      NA       NA #> 498        <NA>      NA       NA #> 499           +      NA       NA #> 500        <NA>      NA       NA #> 501        <NA>      NA       NA #> 502           U      NA       NA #> 503           I      NA       NA #> 504        <NA>      NA       NA #> 505        <NA>      NA       NA #> 506        <NA>      NA       NA #> 507        <NA>      NA       NA #> 508        <NA>      NA       NA #> 509           +      NA       NA #> 510        <NA>      NA       NA #> 511        <NA>      NA       NA #> 512           I      NA       NA #> 513           I      NA       NA #> 514        <NA>      NA       NA #> 515        <NA>      NA       NA #> 516           U      NA       NA #> 517        <NA>      NA       NA #> 518           I      NA       NA #> 519           +      NA       NA #> 520        <NA>      NA       NA #> 521        <NA>      NA       NA #> 522           I      NA       NA #> 523           I      NA       NA #> 524        <NA>      NA       NA #> 525        <NA>      NA       NA #> 526        <NA>      NA       NA #> 527           +      NA       NA #> 528        <NA>      NA       NA #> 529           A      NA       NA #> 530           I      NA       NA #> 531           I      NA       NA #> 532        <NA>      NA       NA #> 533        <NA>      NA       NA #> 534           U      NA       NA #> 535        <NA>      NA       NA #> 536           I      NA       NA #> 537           +      NA       NA #> 538        <NA>      NA       NA #> 539        <NA>      NA       NA #> 540        <NA>      NA       NA #> 541           I      NA       NA #> 542        <NA>      NA       NA #> 543        <NA>      NA       NA #> 544           U      NA       NA #> 545        <NA>      NA       NA #> 546        <NA>      NA       NA #> 547           +      NA       NA #> 548        <NA>      NA       NA #> 549        <NA>      NA       NA #> 550        <NA>      NA       NA #> 551        <NA>      NA       NA #> 552        <NA>      NA       NA #> 553        <NA>      NA       NA #> 554           I      NA       NA #> 555        <NA>      NA       NA #> 556        <NA>      NA       NA #> 557           +      NA       NA #> 558        <NA>      NA       NA #> 559        <NA>      NA       NA #> 560        <NA>      NA       NA #> 561        <NA>      NA       NA #> 562        <NA>      NA       NA #> 563        <NA>      NA       NA #> 564        <NA>      NA       NA #> 565        <NA>      NA       NA #> 566        <NA>      NA       NA #> 567           +      NA       NA #> 568        <NA>      NA       NA #> 569        <NA>      NA       NA #> 570        <NA>      NA       NA #> 571        <NA>      NA       NA #> 572        <NA>      NA       NA #> 573        <NA>      NA       NA #> 574           U      NA       NA #> 575        <NA>      NA       NA #> 576        <NA>      NA       NA #> 577           +      NA       NA #> 578        <NA>      NA       NA #> 579        <NA>      NA       NA #> 580        <NA>      NA       NA #> 581        <NA>      NA       NA #> 582        <NA>      NA       NA #> 583        <NA>      NA       NA #> 584        <NA>      NA       NA #> 585        <NA>      NA       NA #> 586        <NA>      NA       NA #> 587           +      NA       NA #> 588        <NA>      NA       NA #> 589        <NA>      NA       NA #> 590           I      NA       NA #> 591           U      NA       NA #> 592        <NA>      NA       NA #> 593        <NA>      NA       NA #> 594           I      NA       NA #> 595        <NA>      NA       NA #> 596        <NA>      NA       NA #> 597           +      NA       NA #> 598        <NA>      NA       NA #> 599        <NA>      NA       NA #> 600           I      NA       NA #> 601           U      NA       NA #> 602        <NA>      NA       NA #> 603        <NA>      NA       NA #> 604           I      NA       NA #> 605        <NA>      NA       NA #> 606           I      NA       NA #> 607           +      NA       NA #> 608        <NA>      NA       NA #> 609           A      NA       NA #> 610           I      NA       NA #> 611           U      NA       NA #> 612        <NA>      NA       NA #> 613        <NA>      NA       NA #> 614           I      NA       NA #> 615        <NA>      NA       NA #> 616        <NA>      NA       NA #> 617           +      NA       NA #> 618        <NA>      NA       NA #> 619        <NA>      NA       NA #> 620           I      NA       NA #> 621           U      NA       NA #> 622        <NA>      NA       NA #> 623        <NA>      NA       NA #> 624           U      NA       NA #> 625        <NA>      NA       NA #> 626           +      NA       NA #> 627        <NA>      NA       NA #> 628        <NA>      NA       NA #> 629           I      NA       NA #> 630           U      NA       NA #> 631        <NA>      NA       NA #> 632        <NA>      NA       NA #> 633           U      NA       NA #> 634        <NA>      NA       NA #> 635        <NA>      NA       NA #> 636           +      NA       NA #> 637        <NA>      NA       NA #> 638        <NA>      NA       NA #> 639           I      NA       NA #> 640           U      NA       NA #> 641        <NA>      NA       NA #> 642        <NA>      NA       NA #> 643           U      NA       NA #> 644        <NA>      NA       NA #> 645        <NA>      NA       NA #> 646           +      NA       NA #> 647        <NA>      NA       NA #> 648        <NA>      NA       NA #> 649        <NA>      NA       NA #> 650        <NA>      NA       NA #> 651        <NA>      NA       NA #> 652        <NA>      NA       NA #> 653           U      NA       NA #> 654        <NA>      NA       NA #> 655        <NA>      NA       NA #> 656           +      NA       NA #> 657        <NA>      NA       NA #> 658        <NA>      NA       NA #> 659        <NA>      NA       NA #> 660        <NA>      NA       NA #> 661        <NA>      NA       NA #> 662        <NA>      NA       NA #> 663           I      NA       NA #> 664        <NA>      NA       NA #> 665        <NA>      NA       NA #> 666           +      NA       NA #> 667        <NA>      NA       NA #> 668        <NA>      NA       NA #> 669        <NA>      NA       NA #> 670        <NA>      NA       NA #> 671        <NA>      NA       NA #> 672        <NA>      NA       NA #> 673           I      NA       NA #> 674        <NA>      NA       NA #> 675        <NA>      NA       NA #> 676           +      NA       NA #> 677        <NA>      NA       NA #> 678        <NA>      NA       NA #> 679        <NA>      NA       NA #> 680           I      NA       NA #> 681        <NA>      NA       NA #> 682        <NA>      NA       NA #> 683           I      NA       NA #> 684        <NA>      NA       NA #> 685        <NA>      NA       NA #> 686           +      NA       NA #> 687        <NA>      NA       NA #> 688        <NA>      NA       NA #> 689        <NA>      NA       NA #> 690        <NA>      NA       NA #> 691        <NA>      NA       NA #> 692        <NA>      NA       NA #> 693        <NA>      NA       NA #> 694        <NA>      NA       NA #> 695        <NA>      NA       NA #> 696           +      NA       NA #> 697        <NA>      NA       NA #> 698        <NA>      NA       NA #> 699        <NA>      NA       NA #> 700        <NA>      NA       NA #> 701        <NA>      NA       NA #> 702        <NA>      NA       NA #> 703           I      NA       NA #> 704        <NA>      NA       NA #> 705        <NA>      NA       NA #> 706           +      NA       NA #> 707        <NA>      NA       NA #> 708        <NA>      NA       NA #> 709           I      NA       NA #> 710           U      NA       NA #> 711        <NA>      NA       NA #> 712        <NA>      NA       NA #> 713           I      NA       NA #> 714        <NA>      NA       NA #> 715           I      NA       NA #> 716           +      NA       NA #> 717        <NA>      NA       NA #> 718        <NA>      NA       NA #> 719        <NA>      NA       NA #> 720           I      NA       NA #> 721           U      NA       NA #> 722        <NA>      NA       NA #> 723        <NA>      NA       NA #> 724           +      NA       NA #> 725        <NA>      NA       NA #> 726        <NA>      NA       NA #> 727        <NA>      NA       NA #> 728           A      NA       NA #> 729        <NA>      NA       NA #> 730           +      NA       NA #> 731        <NA>      NA       NA #> 732        <NA>      NA       NA #> 733        <NA>      NA       NA #> 734           +      NA       NA #> 735        <NA>      NA       NA #> 736        <NA>      NA       NA #> 737        <NA>      NA       NA #> 738           I      NA       NA #> 739        <NA>      NA       NA #> 740           I      NA       NA #> 741        <NA>      NA       NA #> 742        <NA>      NA       NA #> 743           +      NA       NA #> 744        <NA>      NA       NA #> 745        <NA>      NA       NA #> 746        <NA>      NA       NA #> 747           I      NA       NA #> 748        <NA>      NA       NA #> 749           +      NA       NA #> 750           I      NA       NA #> 751        <NA>      NA       NA #> 752        <NA>      NA       NA #> 753           +      NA       NA #> 754        <NA>      NA       NA #> 755        <NA>      NA       NA #> 756        <NA>      NA       NA #> 757        <NA>      NA       NA #> 758           +      NA       NA #> 759           I      NA       NA #> 760        <NA>      NA       NA #> 761        <NA>      NA       NA #> 762           +      NA       NA #> 763        <NA>      NA       NA #> 764        <NA>      NA       NA #> 765        <NA>      NA       NA #> 766        <NA>      NA       NA #> 767        <NA>      NA       NA #> 768           +      NA       NA #> 769           I      NA       NA #> 770        <NA>      NA       NA #> 771        <NA>      NA       NA #> 772           +      NA       NA #> 773        <NA>      NA       NA #> 774        <NA>      NA       NA #> 775        <NA>      NA       NA #> 776        <NA>      NA       NA #> 777           +      NA       NA #> 778        <NA>      NA       NA #> 779        <NA>      NA       NA #> 780        <NA>      NA       NA #> 781           +      NA       NA #> 782        <NA>      NA       NA #> 783        <NA>      NA       NA #> 784           I      NA       NA #> 785        <NA>      NA       NA #> 786           +      NA       NA #> 787        <NA>      NA       NA #> 788        <NA>      NA       NA #> 789        <NA>      NA       NA #> 790           +      NA       NA #> 791        <NA>      NA       NA #> 792        <NA>      NA       NA #> 793           I      NA       NA #> 794           I      NA       NA #> 795        <NA>      NA       NA #> 796           I      NA       NA #> 797        <NA>      NA       NA #> 798           I      NA       NA #> 799           +      NA       NA #> 800        <NA>      NA       NA #> 801        <NA>      NA       NA #> 802        <NA>      NA       NA #> 803        <NA>      NA       NA #> 804        <NA>      NA       NA #> 805           +      NA       NA #> 806        <NA>      NA       NA #> 807        <NA>      NA       NA #> 808        <NA>      NA       NA #> 809           +      NA       NA #> 810        <NA>      NA       NA #> 811        <NA>      NA       NA #> 812        <NA>      NA       NA #> 813        <NA>      NA       NA #> 814        <NA>      NA       NA #> 815        <NA>      NA       NA #> 816        <NA>      NA       NA #> 817        <NA>      NA       NA #> 818           +      NA       NA #> 819        <NA>      NA       NA #> 820        <NA>      NA       NA #> 821        <NA>      NA       NA #> 822        <NA>      NA       NA #> 823           +      NA       NA #> 824        <NA>      NA       NA #> 825        <NA>      NA       NA #> 826        <NA>      NA       NA #> 827           +      NA       NA #> 828        <NA>      NA       NA #> 829        <NA>      NA       NA #> 830        <NA>      NA       NA #> 831        <NA>      NA       NA #> 832           I      NA       NA #> 833        <NA>      NA       NA #> 834        <NA>      NA       NA #> 835           +      NA       NA #> 836        <NA>      NA       NA #> 837           A      NA       NA #> 838           I      NA       NA #> 839        <NA>      NA       NA #> 840        <NA>      NA       NA #> 841        <NA>      NA       NA #> 842        <NA>      NA       NA #> 843        <NA>      NA       NA #> 844           +      NA       NA #> 845        <NA>      NA       NA #> 846        <NA>      NA       NA #> 847        <NA>      NA       NA #> 848           A      NA       NA #> 849        <NA>      NA       NA #> 850           +      NA       NA #> 851           I      NA       NA #> 852        <NA>      NA       NA #> 853        <NA>      NA       NA #> 854           +      NA       NA #> 855        <NA>      NA       NA #> 856        <NA>      NA       NA #> 857        <NA>      NA       NA #> 858        <NA>      NA       NA #> 859        <NA>      NA       NA #> 860           +      NA       NA #> 861        <NA>      NA       NA #> 862        <NA>      NA       NA #> 863        <NA>      NA       NA #> 864           +      NA       NA #> 865        <NA>      NA       NA #> 866        <NA>      NA       NA #> 867        <NA>      NA       NA #> 868        <NA>      NA       NA #> 869        <NA>      NA       NA #> 870        <NA>      NA       NA #> 871        <NA>      NA       NA #> 872           +      NA       NA #> 873        <NA>      NA       NA #> 874        <NA>      NA       NA #> 875           I      NA       NA #> 876        <NA>      NA       NA #> 877        <NA>      NA       NA #> 878           +      NA       NA #> 879        <NA>      NA       NA #> 880        <NA>      NA       NA #> 881        <NA>      NA       NA #> 882           +      NA       NA #> 883        <NA>      NA       NA #> 884           A      NA       NA #> 885           I      NA       NA #> 886        <NA>      NA       NA #> 887        <NA>      NA       NA #> 888           +      NA       NA #> 889           I      NA       NA #> 890        <NA>      NA       NA #> 891        <NA>      NA       NA #> 892           +      NA       NA #> 893        <NA>      NA       NA #> 894        <NA>      NA       NA #> 895           I      NA       NA #> 896        <NA>      NA       NA #> 897        <NA>      NA       NA #> 898           +      NA       NA #> 899           I      NA       NA #> 900        <NA>      NA       NA #> 901        <NA>      NA       NA #> 902           +      NA       NA #> 903        <NA>      NA       NA #> 904        <NA>      NA       NA #> 905        <NA>      NA       NA #> 906        <NA>      NA       NA #> 907        <NA>      NA       NA #> 908           +      NA       NA #> 909           I      NA       NA #> 910        <NA>      NA       NA #> 911        <NA>      NA       NA #> 912           +      NA       NA #> 913        <NA>      NA       NA #> 914        <NA>      NA       NA #> 915        <NA>      NA       NA #> 916        <NA>      NA       NA #> 917        <NA>      NA       NA #> 918           +      NA       NA #> 919        <NA>      NA       NA #> 920        <NA>      NA       NA #> 921        <NA>      NA       NA #> 922           +      NA       NA #> 923        <NA>      NA       NA #> 924        <NA>      NA       NA #> 925        <NA>      NA       NA #> 926        <NA>      NA       NA #> 927        <NA>      NA       NA #> 928           +      NA       NA #> 929        <NA>      NA       NA #> 930        <NA>      NA       NA #> 931        <NA>      NA       NA #> 932           +      NA       NA #> 933        <NA>      NA       NA #> 934        <NA>      NA       NA #> 935           I      NA       NA #> 936           U      NA       NA #> 937        <NA>      NA       NA #> 938           +      NA       NA #> 939        <NA>      NA       NA #> 940        <NA>      NA       NA #> 941        <NA>      NA       NA #> 942           +      NA       NA #> 943        <NA>      NA       NA #> 944           A      NA       NA #> 945        <NA>      NA       NA #> 946           I      NA       NA #> 947        <NA>      NA       NA #> 948           +      NA       NA #> 949        <NA>      NA       NA #> 950        <NA>      NA       NA #> 951        <NA>      NA       NA #> 952           +      NA       NA #> 953        <NA>      NA       NA #> 954        <NA>      NA       NA #> 955        <NA>      NA       NA #> 956           A      NA       NA #> 957        <NA>      NA       NA #> 958           +      NA       NA #> 959        <NA>      NA       NA #> 960        <NA>      NA       NA #> 961        <NA>      NA       NA #> 962           +      NA       NA #> 963        <NA>      NA       NA #> 964        <NA>      NA       NA #> 965           I      NA       NA #> 966        <NA>      NA       NA #> 967        <NA>      NA       NA #> 968           +      NA       NA #> 969           I      NA       NA #> 970        <NA>      NA       NA #> 971        <NA>      NA       NA #> 972           +      NA       NA #> 973        <NA>      NA       NA #> 974        <NA>      NA       NA #> 975        <NA>      NA       NA #> 976        <NA>      NA       NA #> 977        <NA>      NA       NA #> 978           +      NA       NA #> 979           I      NA       NA #> 980        <NA>      NA       NA #> 981        <NA>      NA       NA #> 982           +      NA       NA #> 983        <NA>      NA       NA #> 984        <NA>      NA       NA #> 985        <NA>      NA       NA #> 986           I      NA       NA #> 987        <NA>      NA       NA #> 988           +      NA       NA #> 989           U      NA       NA #> 990        <NA>      NA       NA #> 991        <NA>      NA       NA #> 992           +      NA       NA #> 993        <NA>      NA       NA #> 994        <NA>      NA       NA #> 995        <NA>      NA       NA #> 996        <NA>      NA       NA #> 997        <NA>      NA       NA #> 998           +      NA       NA #> 999        <NA>      NA       NA #> 1000       <NA>      NA       NA #> 1001       <NA>      NA       NA #> 1002          +      NA       NA #> 1003       <NA>      NA       NA #> 1004       <NA>      NA       NA #> 1005       <NA>      NA       NA #> 1006       <NA>      NA       NA #> 1007       <NA>      NA       NA #> 1008          +      NA       NA #> 1009       <NA>      NA       NA #> 1010       <NA>      NA       NA #> 1011       <NA>      NA       NA #> 1012          +      NA       NA #> 1013       <NA>      NA       NA #> 1014       <NA>      NA       NA #> 1015       <NA>      NA       NA #> 1016       <NA>      NA       NA #> 1017          I      NA       NA #> 1018       <NA>      NA       NA #> 1019          +      NA       NA #> 1020       <NA>      NA       NA #> 1021       <NA>      NA       NA #> 1022       <NA>      NA       NA #> 1023       <NA>      NA       NA #> 1024       <NA>      NA       NA #> 1025          +      NA       NA #> 1026       <NA>      NA       NA #> 1027       <NA>      NA       NA #> 1028       <NA>      NA       NA #> 1029          +      NA       NA #> 1030       <NA>      NA       NA #> 1031          A      NA       NA #> 1032       <NA>      NA       NA #> 1033       <NA>      NA       NA #> 1034       <NA>      NA       NA #> 1035          +      NA       NA #> 1036          I      NA       NA #> 1037       <NA>      NA       NA #> 1038       <NA>      NA       NA #> 1039          +      NA       NA #> 1040       <NA>      NA       NA #> 1041          A      NA       NA #> 1042       <NA>      NA       NA #> 1043       <NA>      NA       NA #> 1044       <NA>      NA       NA #> 1045          +      NA       NA #> 1046       <NA>      NA       NA #> 1047       <NA>      NA       NA #> 1048       <NA>      NA       NA #> 1049          +      NA       NA #> 1050       <NA>      NA       NA #> 1051       <NA>      NA       NA #> 1052          I      NA       NA #> 1053       <NA>      NA       NA #> 1054       <NA>      NA       NA #> 1055          +      NA       NA #> 1056       <NA>      NA       NA #> 1057       <NA>      NA       NA #> 1058       <NA>      NA       NA #> 1059          +      NA       NA #> 1060       <NA>      NA       NA #> 1061       <NA>      NA       NA #> 1062       <NA>      NA       NA #> 1063       <NA>      NA       NA #> 1064       <NA>      NA       NA #> 1065          +      NA       NA #> 1066          I      NA       NA #> 1067       <NA>      NA       NA #> 1068       <NA>      NA       NA #> 1069          +      NA       NA #> 1070       <NA>      NA       NA #> 1071          A      NA       NA #> 1072       <NA>      NA       NA #> 1073          I      NA       NA #> 1074       <NA>      NA       NA #> 1075          +      NA       NA #> 1076          I      NA       NA #> 1077       <NA>      NA       NA #> 1078       <NA>      NA       NA #> 1079          +      NA       NA #> 1080       <NA>      NA       NA #> 1081       <NA>      NA       NA #> 1082       <NA>      NA       NA #> 1083       <NA>      NA       NA #> 1084       <NA>      NA       NA #> 1085       <NA>      NA       NA #> 1086          I      NA       NA #> 1087       <NA>      NA       NA #> 1088       <NA>      NA       NA #> 1089          +      NA       NA #> 1090       <NA>      NA       NA #> 1091       <NA>      NA       NA #> 1092       <NA>      NA       NA #> 1093       <NA>      NA       NA #> 1094       <NA>      NA       NA #> 1095       <NA>      NA       NA #> 1096          I      NA       NA #> 1097       <NA>      NA       NA #> 1098       <NA>      NA       NA #> 1099          +      NA       NA #> 1100       <NA>      NA       NA #> 1101       <NA>      NA       NA #> 1102          A      NA       NA #> 1103       <NA>      NA       NA #> 1104       <NA>      NA       NA #> 1105          I      NA       NA #> 1106       <NA>      NA       NA #> 1107       <NA>      NA       NA #> 1108          +      NA       NA #> 1109       <NA>      NA       NA #> 1110          A      NA       NA #> 1111          I      NA       NA #> 1112       <NA>      NA       NA #> 1113       <NA>      NA       NA #> 1114       <NA>      NA       NA #> 1115       <NA>      NA       NA #> 1116       <NA>      NA       NA #> 1117       <NA>      NA       NA #> 1118          +      NA       NA #> 1119       <NA>      NA       NA #> 1120       <NA>      NA       NA #> 1121          I      NA       NA #> 1122       <NA>      NA       NA #> 1123          I      NA       NA #> 1124       <NA>      NA       NA #> 1125       <NA>      NA       NA #> 1126          +      NA       NA #> 1127       <NA>      NA       NA #> 1128       <NA>      NA       NA #> 1129          I      NA       NA #> 1130       <NA>      NA       NA #> 1131          U      NA       NA #> 1132       <NA>      NA       NA #> 1133          +      NA       NA #> 1134       <NA>      NA       NA #> 1135       <NA>      NA       NA #> 1136          I      NA       NA #> 1137       <NA>      NA       NA #> 1138       <NA>      NA       NA #> 1139       <NA>      NA       NA #> 1140          I      NA       NA #> 1141       <NA>      NA       NA #> 1142       <NA>      NA       NA #> 1143          +      NA       NA #> 1144       <NA>      NA       NA #> 1145       <NA>      NA       NA #> 1146   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1174       <NA>      NA       NA #> 1175          I      NA       NA #> 1176       <NA>      NA       NA #> 1177       <NA>      NA       NA #> 1178          I      NA       NA #> 1179       <NA>      NA       NA #> 1180       <NA>      NA       NA #> 1181          +      NA       NA #> 1182       <NA>      NA       NA #> 1183       <NA>      NA       NA #> 1184       <NA>      NA       NA #> 1185          I      NA       NA #> 1186       <NA>      NA       NA #> 1187       <NA>      NA       NA #> 1188       <NA>      NA       NA #> 1189       <NA>      NA       NA #> 1190       <NA>      NA       NA #> 1191          +      NA       NA #> 1192       <NA>      NA       NA #> 1193       <NA>      NA       NA #> 1194          I      NA       NA #> 1195          U      NA       NA #> 1196       <NA>      NA       NA #> 1197       <NA>      NA       NA #> 1198       <NA>      NA       NA #> 1199       <NA>      NA       NA #> 1200       <NA>      NA       NA #> 1201          +      NA      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NA       NA #> 1785          I      NA       NA #> 1786       <NA>      NA       NA #> 1787       <NA>      NA       NA #> 1788          +      NA       NA #> 1789       <NA>      NA       NA #> 1790          A      NA       NA #> 1791       <NA>      NA       NA #> 1792       <NA>      NA       NA #> 1793       <NA>      NA       NA #> 1794          +      NA       NA #> 1795       <NA>      NA       NA #> 1796       <NA>      NA       NA #> 1797       <NA>      NA       NA #> 1798          +      NA       NA #> 1799       <NA>      NA       NA #> 1800       <NA>      NA       NA #> 1801          I      NA       NA #> 1802       <NA>      NA       NA #> 1803       <NA>      NA       NA #> 1804          +      NA       NA #> 1805          U      NA       NA #> 1806       <NA>      NA       NA #> 1807       <NA>      NA       NA #> 1808          +      NA       NA #> 1809       <NA>      NA       NA #> 1810       <NA>      NA       NA #> 1811       <NA>      NA       NA #> 1812       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1840          +      NA       NA #> 1841          I      NA       NA #> 1842       <NA>      NA       NA #> 1843       <NA>      NA       NA #> 1844          +      NA       NA #> 1845       <NA>      NA       NA #> 1846       <NA>      NA       NA #> 1847       <NA>      NA       NA #> 1848       <NA>      NA       NA #> 1849          I      NA       NA #> 1850       <NA>      NA       NA #> 1851       <NA>      NA       NA #> 1852          +      NA       NA #> 1853       <NA>      NA       NA #> 1854       <NA>      NA       NA #> 1855          A      NA       NA #> 1856       <NA>      NA       NA #> 1857       <NA>      NA       NA #> 1858          +      NA       NA #> 1859       <NA>      NA       NA #> 1860       <NA>      NA       NA #> 1861       <NA>      NA       NA #> 1862          +      NA       NA #> 1863       <NA>      NA       NA #> 1864       <NA>      NA       NA #> 1865       <NA>      NA       NA #> 1866       <NA>      NA       NA #> 1867       <NA>      NA      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NA       NA #> 1896       <NA>      NA       NA #> 1897       <NA>      NA       NA #> 1898       <NA>      NA       NA #> 1899          I      NA       NA #> 1900       <NA>      NA       NA #> 1901       <NA>      NA       NA #> 1902          +      NA       NA #> 1903       <NA>      NA       NA #> 1904       <NA>      NA       NA #> 1905          I      NA       NA #> 1906       <NA>      NA       NA #> 1907       <NA>      NA       NA #> 1908       <NA>      NA       NA #> 1909          U      NA       NA #> 1910       <NA>      NA       NA #> 1911       <NA>      NA       NA #> 1912          +      NA       NA #> 1913       <NA>      NA       NA #> 1914       <NA>      NA       NA #> 1915       <NA>      NA       NA #> 1916       <NA>      NA       NA #> 1917       <NA>      NA       NA #> 1918       <NA>      NA       NA #> 1919          U      NA       NA #> 1920       <NA>      NA       NA #> 1921       <NA>      NA       NA #> 1922          +      NA       NA #> 1923       <NA>      NA       NA #> 1924       <NA>      NA       NA #> 1925       <NA>      NA       NA #> 1926       <NA>      NA       NA #> 1927       <NA>      NA       NA #> 1928       <NA>      NA       NA #> 1929          U      NA       NA #> 1930       <NA>      NA       NA #> 1931       <NA>      NA       NA #> 1932          +      NA       NA #> 1933       <NA>      NA       NA #> 1934       <NA>      NA       NA #> 1935       <NA>      NA       NA #> 1936          A      NA       NA #> 1937       <NA>      NA       NA #> 1938       <NA>      NA       NA #> 1939          U      NA       NA #> 1940       <NA>      NA       NA #> 1941       <NA>      NA       NA #> 1942          +      NA       NA #> 1943       <NA>      NA       NA #> 1944          A      NA       NA #> 1945          +      NA       NA #> 1946          I      NA       NA #> 1947       <NA>      NA       NA #> 1948       <NA>      NA       NA #> 1949       <NA>      NA       NA #> 1950          I      NA       NA #> 1951       <NA>      NA       NA #> 1952       <NA>      NA       NA #> 1953       <NA>      NA       NA #> 1954       <NA>      NA       NA #> 1955       <NA>      NA       NA #> 1956       <NA>      NA       NA #> 1957       <NA>      NA       NA #> 1958       <NA>      NA       NA #> 1959       <NA>      NA       NA #> 1960       <NA>      NA       NA #> 1961       <NA>      NA       NA #> 1962          +      NA       NA #> 1963       <NA>      NA       NA #> 1964       <NA>      NA       NA #> 1965          I      NA       NA #> 1966       <NA>      NA       NA #> 1967       <NA>      NA       NA #> 1968       <NA>      NA       NA #> 1969       <NA>      NA       NA #> 1970       <NA>      NA       NA #> 1971       <NA>      NA       NA #> 1972          +      NA       NA #> 1973       <NA>      NA       NA #> 1974       <NA>      NA       NA #> 1975       <NA>      NA       NA #> 1976          A      NA       NA #> 1977       <NA>      NA       NA #> 1978       <NA>      NA      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NA       NA #> 2007       <NA>      NA       NA #> 2008       <NA>      NA       NA #> 2009          U      NA       NA #> 2010       <NA>      NA       NA #> 2011       <NA>      NA       NA #> 2012          +      NA       NA #> 2013       <NA>      NA       NA #> 2014       <NA>      NA       NA #> 2015       <NA>      NA       NA #> 2016       <NA>      NA       NA #> 2017       <NA>      NA       NA #> 2018       <NA>      NA       NA #> 2019          I      NA       NA #> 2020       <NA>      NA       NA #> 2021       <NA>      NA       NA #> 2022          +      NA       NA #> 2023       <NA>      NA       NA #> 2024       <NA>      NA       NA #> 2025       <NA>      NA       NA #> 2026       <NA>      NA       NA #> 2027       <NA>      NA       NA #> 2028       <NA>      NA       NA #> 2029          I      NA       NA #> 2030       <NA>      NA       NA #> 2031       <NA>      NA       NA #> 2032          +      NA       NA #> 2033       <NA>      NA       NA #> 2034       <NA>      NA       NA #> 2035          I      NA       NA #> 2036          A      NA       NA #> 2037       <NA>      NA       NA #> 2038       <NA>      NA       NA #> 2039       <NA>      NA       NA #> 2040       <NA>      NA       NA #> 2041       <NA>      NA       NA #> 2042          +      NA       NA #> 2043       <NA>      NA       NA #> 2044       <NA>      NA       NA #> 2045       <NA>      NA       NA #> 2046          A      NA       NA #> 2047       <NA>      NA       NA #> 2048       <NA>      NA       NA #> 2049       <NA>      NA       NA #> 2050       <NA>      NA       NA #> 2051       <NA>      NA       NA #> 2052          +      NA       NA #> 2053       <NA>      NA       NA #> 2054       <NA>      NA       NA #> 2055          I      NA       NA #> 2056       <NA>      NA       NA #> 2057       <NA>      NA       NA #> 2058       <NA>      NA       NA #> 2059       <NA>      NA       NA #> 2060       <NA>      NA       NA #> 2061       <NA>      NA       NA #> 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2173       <NA>      NA       NA #> 2174       <NA>      NA       NA #> 2175          I      NA       NA #> 2176       <NA>      NA       NA #> 2177       <NA>      NA       NA #> 2178       <NA>      NA       NA #> 2179          I      NA       NA #> 2180       <NA>      NA       NA #> 2181          +      NA       NA #> 2182       <NA>      NA       NA #> 2183       <NA>      NA       NA #> 2184          U      NA       NA #> 2185       <NA>      NA       NA #> 2186       <NA>      NA       NA #> 2187          U      NA       NA #> 2188       <NA>      NA       NA #> 2189          +      NA       NA #> 2190       <NA>      NA       NA #> 2191       <NA>      NA       NA #> 2192       <NA>      NA       NA #> 2193       <NA>      NA       NA #> 2194          I      NA       NA #> 2195       <NA>      NA       NA #> 2196       <NA>      NA       NA #> 2197          +      NA       NA #> 2198       <NA>      NA       NA #> 2199       <NA>      NA       NA #> 2200       <NA>      NA      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NA       NA #> 2229       <NA>      NA       NA #> 2230       <NA>      NA       NA #> 2231       <NA>      NA       NA #> 2232       <NA>      NA       NA #> 2233       <NA>      NA       NA #> 2234          U      NA       NA #> 2235       <NA>      NA       NA #> 2236       <NA>      NA       NA #> 2237          +      NA       NA #> 2238       <NA>      NA       NA #> 2239       <NA>      NA       NA #> 2240       <NA>      NA       NA #> 2241       <NA>      NA       NA #> 2242       <NA>      NA       NA #> 2243       <NA>      NA       NA #> 2244       <NA>      NA       NA #> 2245       <NA>      NA       NA #> 2246          +      NA       NA #> 2247       <NA>      NA       NA #> 2248       <NA>      NA       NA #> 2249       <NA>      NA       NA #> 2250          A      NA       NA #> 2251       <NA>      NA       NA #> 2252       <NA>      NA       NA #> 2253          I      NA       NA #> 2254       <NA>      NA       NA #> 2255       <NA>      NA       NA #> 2256          +      NA       NA #> 2257       <NA>      NA       NA #> 2258       <NA>      NA       NA #> 2259       <NA>      NA       NA #> 2260       <NA>      NA       NA #> 2261       <NA>      NA       NA #> 2262       <NA>      NA       NA #> 2263       <NA>      NA       NA #> 2264       <NA>      NA       NA #> 2265       <NA>      NA       NA #> 2266          I      NA       NA #> 2267          +      NA       NA #> 2268       <NA>      NA       NA #> 2269          +      NA       NA #> 2270       <NA>      NA       NA #> 2271          I      NA       NA #> 2272       <NA>      NA       NA #> 2273       <NA>      NA       NA #> 2274       <NA>      NA       NA #> 2275       <NA>      NA       NA #> 2276       <NA>      NA       NA #> 2277          U      NA       NA #> 2278          +      NA       NA #> 2279       <NA>      NA       NA #> 2280          +      NA       NA #> 2281       <NA>      NA       NA #> 2282          I      NA       NA #> 2283       <NA>      NA       NA #> 2284       <NA>      NA       NA #> 2285       <NA>      NA       NA #> 2286       <NA>      NA       NA #> 2287       <NA>      NA       NA #> 2288          U      NA       NA #> 2289          +      NA       NA #> 2290       <NA>      NA       NA #> 2291          +      NA       NA #> 2292          I      NA       NA #> 2293       <NA>      NA       NA #> 2294       <NA>      NA       NA #> 2295       <NA>      NA       NA #> 2296       <NA>      NA       NA #> 2297       <NA>      NA       NA #> 2298          I      NA       NA #> 2299       <NA>      NA       NA #> 2300          +      NA       NA #> 2301       <NA>      NA       NA #> 2302          U      NA       NA #> 2303          A      NA       NA #> 2304       <NA>      NA       NA #> 2305       <NA>      NA       NA #> 2306       <NA>      NA       NA #> 2307       <NA>      NA       NA #> 2308          G      NA       NA #> 2309       <NA>      NA       NA #> 2310       <NA>      NA       NA #> 2311          +      NA       NA #> 2312       <NA>      NA       NA #> 2313          I      NA       NA #> 2314       <NA>      NA       NA #> 2315       <NA>      NA       NA #> 2316       <NA>      NA       NA #> 2317       <NA>      NA       NA #> 2318       <NA>      NA       NA #> 2319          I      NA       NA #> 2320       <NA>      NA       NA #> 2321       <NA>      NA       NA #> 2322          +      NA       NA #> 2323       <NA>      NA       NA #> 2324          I      NA       NA #> 2325       <NA>      NA       NA #> 2326       <NA>      NA       NA #> 2327       <NA>      NA       NA #> 2328       <NA>      NA       NA #> 2329       <NA>      NA       NA #> 2330          +      NA       NA #> 2331          I      NA       NA #> 2332       <NA>      NA       NA #> 2333       <NA>      NA       NA #> 2334       <NA>      NA       NA #> 2335          I      NA       NA #> 2336       <NA>      NA       NA #> 2337       <NA>      NA       NA #> 2338          +      NA       NA #> 2339       <NA>      NA      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NA       NA #> 2368          I      NA       NA #> 2369       <NA>      NA       NA #> 2370       <NA>      NA       NA #> 2371          +      NA       NA #> 2372       <NA>      NA       NA #> 2373          U      NA       NA #> 2374       <NA>      NA       NA #> 2375       <NA>      NA       NA #> 2376       <NA>      NA       NA #> 2377       <NA>      NA       NA #> 2378       <NA>      NA       NA #> 2379          I      NA       NA #> 2380       <NA>      NA       NA #> 2381       <NA>      NA       NA #> 2382          +      NA       NA #> 2383       <NA>      NA       NA #> 2384          I      NA       NA #> 2385       <NA>      NA       NA #> 2386       <NA>      NA       NA #> 2387       <NA>      NA       NA #> 2388       <NA>      NA       NA #> 2389       <NA>      NA       NA #> 2390       <NA>      NA       NA #> 2391       <NA>      NA       NA #> 2392       <NA>      NA       NA #> 2393       <NA>      NA       NA #> 2394       <NA>      NA       NA #> 2395       <NA>      NA       NA #> 2396       <NA>      NA       NA #> 2397       <NA>      NA       NA #> 2398       <NA>      NA       NA #> 2399       <NA>      NA       NA #> 2400       <NA>      NA       NA #> 2401       <NA>      NA       NA #> 2402          U      NA       NA #> 2403       <NA>      NA       NA #> 2404       <NA>      NA       NA #> 2405          +      NA       NA #> 2406       <NA>      NA       NA #> 2407          I      NA       NA #> 2408          A      NA       NA #> 2409          A      NA       NA #> 2410       <NA>      NA       NA #> 2411       <NA>      NA       NA #> 2412       <NA>      NA       NA #> 2413          U      NA       NA #> 2414       <NA>      NA       NA #> 2415       <NA>      NA       NA #> 2416          +      NA       NA #> 2417       <NA>      NA       NA #> 2418          I      NA       NA #> 2419       <NA>      NA       NA #> 2420       <NA>      NA       NA #> 2421       <NA>      NA       NA #> 2422       <NA>      NA       NA #> 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NA       NA #> 2479       <NA>      NA       NA #> 2480       <NA>      NA       NA #> 2481          +      NA       NA #> 2482       <NA>      NA       NA #> 2483          I      NA       NA #> 2484       <NA>      NA       NA #> 2485       <NA>      NA       NA #> 2486       <NA>      NA       NA #> 2487       <NA>      NA       NA #> 2488          I      NA       NA #> 2489       <NA>      NA       NA #> 2490       <NA>      NA       NA #> 2491          +      NA       NA #> 2492       <NA>      NA       NA #> 2493       <NA>      NA       NA #> 2494       <NA>      NA       NA #> 2495       <NA>      NA       NA #> 2496       <NA>      NA       NA #> 2497       <NA>      NA       NA #> 2498       <NA>      NA       NA #> 2499          U      NA       NA #> 2500       <NA>      NA       NA #> 2501       <NA>      NA       NA #> 2502          +      NA       NA #> 2503       <NA>      NA       NA #> 2504          I      NA       NA #> 2505       <NA>      NA       NA #> 2506       <NA>      NA       NA #> 2507       <NA>      NA       NA #> 2508       <NA>      NA       NA #> 2509       <NA>      NA       NA #> 2510          U      NA       NA #> 2511       <NA>      NA       NA #> 2512       <NA>      NA       NA #> 2513          +      NA       NA #> 2514       <NA>      NA       NA #> 2515          I      NA       NA #> 2516       <NA>      NA       NA #> 2517       <NA>      NA       NA #> 2518       <NA>      NA       NA #> 2519       <NA>      NA       NA #> 2520       <NA>      NA       NA #> 2521          U      NA       NA #> 2522       <NA>      NA       NA #> 2523       <NA>      NA       NA #> 2524          +      NA       NA #> 2525       <NA>      NA       NA #> 2526          I      NA       NA #> 2527          A      NA       NA #> 2528       <NA>      NA       NA #> 2529       <NA>      NA       NA #> 2530       <NA>      NA       NA #> 2531       <NA>      NA       NA #> 2532          U      NA       NA #> 2533       <NA>      NA       NA #> 2534       <NA>      NA       NA #> 2535          +      NA       NA #> 2536       <NA>      NA       NA #> 2537       <NA>      NA       NA #> 2538          A      NA       NA #> 2539       <NA>      NA       NA #> 2540       <NA>      NA       NA #> 2541       <NA>      NA       NA #> 2542       <NA>      NA       NA #> 2543          U      NA       NA #> 2544       <NA>      NA       NA #> 2545       <NA>      NA       NA #> 2546          +      NA       NA #> 2547       <NA>      NA       NA #> 2548          I      NA       NA #> 2549       <NA>      NA       NA #> 2550       <NA>      NA       NA #> 2551       <NA>      NA       NA #> 2552       <NA>      NA       NA #> 2553       <NA>      NA       NA #> 2554          U      NA       NA #> 2555       <NA>      NA       NA #> 2556       <NA>      NA       NA #> 2557          +      NA       NA #> 2558       <NA>      NA       NA #> 2559          I      NA       NA #> 2560          A      NA       NA #> 2561       <NA>      NA      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NA       NA #> 2590          +      NA       NA #> 2591       <NA>      NA       NA #> 2592          U      NA       NA #> 2593       <NA>      NA       NA #> 2594       <NA>      NA       NA #> 2595       <NA>      NA       NA #> 2596       <NA>      NA       NA #> 2597       <NA>      NA       NA #> 2598          U      NA       NA #> 2599       <NA>      NA       NA #> 2600       <NA>      NA       NA #> 2601          +      NA       NA #> 2602       <NA>      NA       NA #> 2603          I      NA       NA #> 2604       <NA>      NA       NA #> 2605          A      NA       NA #> 2606       <NA>      NA       NA #> 2607       <NA>      NA       NA #> 2608       <NA>      NA       NA #> 2609          U      NA       NA #> 2610       <NA>      NA       NA #> 2611       <NA>      NA       NA #> 2612          +      NA       NA #> 2613       <NA>      NA       NA #> 2614          I      NA       NA #> 2615       <NA>      NA       NA #> 2616       <NA>      NA       NA #> 2617       <NA>      NA       NA #> 2618       <NA>      NA       NA #> 2619       <NA>      NA       NA #> 2620          U      NA       NA #> 2621       <NA>      NA       NA #> 2622       <NA>      NA       NA #> 2623          +      NA       NA #> 2624       <NA>      NA       NA #> 2625          I      NA       NA #> 2626       <NA>      NA       NA #> 2627       <NA>      NA       NA #> 2628       <NA>      NA       NA #> 2629       <NA>      NA       NA #> 2630       <NA>      NA       NA #> 2631          U      NA       NA #> 2632       <NA>      NA       NA #> 2633       <NA>      NA       NA #> 2634          +      NA       NA #> 2635       <NA>      NA       NA #> 2636          I      NA       NA #> 2637       <NA>      NA       NA #> 2638       <NA>      NA       NA #> 2639       <NA>      NA       NA #> 2640       <NA>      NA       NA #> 2641       <NA>      NA       NA #> 2642          U      NA       NA #> 2643       <NA>      NA       NA #> 2644       <NA>      NA       NA #> 2645          +      NA       NA #> 2646       <NA>      NA       NA #> 2647          I      NA       NA #> 2648       <NA>      NA       NA #> 2649          I      NA       NA #> 2650       <NA>      NA       NA #> 2651       <NA>      NA       NA #> 2652       <NA>      NA       NA #> 2653          U      NA       NA #> 2654       <NA>      NA       NA #> 2655       <NA>      NA       NA #> 2656          +      NA       NA #> 2657       <NA>      NA       NA #> 2658          I      NA       NA #> 2659          I      NA       NA #> 2660          A      NA       NA #> 2661       <NA>      NA       NA #> 2662       <NA>      NA       NA #> 2663       <NA>      NA       NA #> 2664          U      NA       NA #> 2665       <NA>      NA       NA #> 2666       <NA>      NA       NA #> 2667          +      NA       NA #> 2668       <NA>      NA       NA #> 2669          I      NA       NA #> 2670       <NA>      NA       NA #> 2671       <NA>      NA       NA #> 2672       <NA>      NA      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NA       NA #> 2701       <NA>      NA       NA #> 2702       <NA>      NA       NA #> 2703          +      NA       NA #> 2704       <NA>      NA       NA #> 2705       <NA>      NA       NA #> 2706       <NA>      NA       NA #> 2707          +      NA       NA #> 2708       <NA>      NA       NA #> 2709       <NA>      NA       NA #> 2710       <NA>      NA       NA #> 2711          +      NA       NA #> 2712       <NA>      NA       NA #> 2713       <NA>      NA       NA #> 2714       <NA>      NA       NA #> 2715          +      NA       NA #> 2716       <NA>      NA       NA #> 2717       <NA>      NA       NA #> 2718       <NA>      NA       NA #> 2719          +      NA       NA #> 2720       <NA>      NA       NA #> 2721       <NA>      NA       NA #> 2722       <NA>      NA       NA #> 2723          +      NA       NA #> 2724       <NA>      NA       NA #> 2725       <NA>      NA       NA #> 2726       <NA>      NA       NA #> 2727          +      NA       NA #> 2728       <NA>      NA       NA #> 2729          +      NA       NA #> 2730       <NA>      NA       NA #> 2731       <NA>      NA       NA #> 2732       <NA>      NA       NA #> 2733          +      NA       NA #> 2734       <NA>      NA       NA #> 2735       <NA>      NA       NA #> 2736       <NA>      NA       NA #> 2737          +      NA       NA #> 2738       <NA>      NA       NA #> 2739       <NA>      NA       NA #> 2740       <NA>      NA       NA #> 2741          +      NA       NA #> 2742       <NA>      NA       NA #> 2743       <NA>      NA       NA #> 2744       <NA>      NA       NA #> 2745          +      NA       NA #> 2746       <NA>      NA       NA #> 2747       <NA>      NA       NA #> 2748       <NA>      NA       NA #> 2749          +      NA       NA #> 2750       <NA>      NA       NA #> 2751       <NA>      NA       NA #> 2752       <NA>      NA       NA #> 2753          +      NA       NA #> 2754       <NA>      NA       NA #> 2755       <NA>      NA       NA #> 2756       <NA>      NA       NA #> 2757          +      NA       NA #> 2758       <NA>      NA       NA #> 2759          +      NA       NA #> 2760       <NA>      NA       NA #> 2761       <NA>      NA       NA #> 2762       <NA>      NA       NA #> 2763          +      NA       NA #> 2764       <NA>      NA       NA #> 2765       <NA>      NA       NA #> 2766       <NA>      NA       NA #> 2767          +      NA       NA #> 2768       <NA>      NA       NA #> 2769       <NA>      NA       NA #> 2770       <NA>      NA       NA #> 2771          +      NA       NA #> 2772       <NA>      NA       NA #> 2773       <NA>      NA       NA #> 2774       <NA>      NA       NA #> 2775          +      NA       NA #> 2776       <NA>      NA       NA #> 2777       <NA>      NA       NA #> 2778       <NA>      NA       NA #> 2779          +      NA       NA #> 2780       <NA>      NA       NA #> 2781       <NA>      NA       NA #> 2782       <NA>      NA       NA #> 2783       <NA>      NA      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NA       NA #> 2812       <NA>      NA       NA #> 2813       <NA>      NA       NA #> 2814       <NA>      NA       NA #> 2815       <NA>      NA       NA #> 2816          +      NA       NA #> 2817       <NA>      NA       NA #> 2818          I      NA       NA #> 2819       <NA>      NA       NA #> 2820          I      NA       NA #> 2821          A      NA       NA #> 2822       <NA>      NA       NA #> 2823       <NA>      NA       NA #> 2824       <NA>      NA       NA #> 2825       <NA>      NA       NA #> 2826       <NA>      NA       NA #> 2827       <NA>      NA       NA #> 2828          +      NA       NA #> 2829       <NA>      NA       NA #> 2830          I      NA       NA #> 2831          A      NA       NA #> 2832       <NA>      NA       NA #> 2833          A      NA       NA #> 2834       <NA>      NA       NA #> 2835       <NA>      NA       NA #> 2836       <NA>      NA       NA #> 2837       <NA>      NA       NA #> 2838       <NA>      NA       NA #> 2839       <NA>      NA       NA #> 2840          +      NA       NA #> 2841       <NA>      NA       NA #> 2842          I      NA       NA #> 2843          A      NA       NA #> 2844          I      NA       NA #> 2845          A      NA       NA #> 2846       <NA>      NA       NA #> 2847       <NA>      NA       NA #> 2848       <NA>      NA       NA #> 2849       <NA>      NA       NA #> 2850       <NA>      NA       NA #> 2851       <NA>      NA       NA #> 2852          +      NA       NA #> 2853       <NA>      NA       NA #> 2854       <NA>      NA       NA #> 2855       <NA>      NA       NA #> 2856       <NA>      NA       NA #> 2857       <NA>      NA       NA #> 2858       <NA>      NA       NA #> 2859       <NA>      NA       NA #> 2860       <NA>      NA       NA #> 2861       <NA>      NA       NA #> 2862       <NA>      NA       NA #> 2863          +      NA       NA #> 2864       <NA>      NA       NA #> 2865          I      NA       NA #> 2866       <NA>      NA       NA #> 2867       <NA>      NA       NA #> 2868       <NA>      NA       NA #> 2869       <NA>      NA       NA #> 2870       <NA>      NA       NA #> 2871       <NA>      NA       NA #> 2872       <NA>      NA       NA #> 2873       <NA>      NA       NA #> 2874          +      NA       NA #> 2875       <NA>      NA       NA #> 2876          I      NA       NA #> 2877       <NA>      NA       NA #> 2878       <NA>      NA       NA #> 2879       <NA>      NA       NA #> 2880       <NA>      NA       NA #> 2881       <NA>      NA       NA #> 2882       <NA>      NA       NA #> 2883       <NA>      NA       NA #> 2884       <NA>      NA       NA #> 2885          +      NA       NA #> 2886       <NA>      NA       NA #> 2887          I      NA       NA #> 2888       <NA>      NA       NA #> 2889       <NA>      NA       NA #> 2890       <NA>      NA       NA #> 2891       <NA>      NA       NA #> 2892       <NA>      NA       NA #> 2893       <NA>      NA       NA #> 2894       <NA>      NA      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NA       NA #> 2923       <NA>      NA       NA #> 2924       <NA>      NA       NA #> 2925       <NA>      NA       NA #> 2926       <NA>      NA       NA #> 2927       <NA>      NA       NA #> 2928       <NA>      NA       NA #> 2929       <NA>      NA       NA #> 2930       <NA>      NA       NA #> 2931       <NA>      NA       NA #> 2932       <NA>      NA       NA #> 2933       <NA>      NA       NA #> 2934       <NA>      NA       NA #> 2935       <NA>      NA       NA #> 2936       <NA>      NA       NA #> 2937       <NA>      NA       NA #> 2938       <NA>      NA       NA #> 2939       <NA>      NA       NA #> 2940       <NA>      NA       NA #> 2941       <NA>      NA       NA #> 2942       <NA>      NA       NA #> 2943       <NA>      NA       NA #> 2944       <NA>      NA       NA #> 2945       <NA>      NA       NA #> 2946       <NA>      NA       NA #> 2947          +      NA       NA #> 2948       <NA>      NA       NA #> 2949       <NA>      NA       NA #> 2950       <NA>      NA       NA #> 2951          +      NA       NA #> 2952       <NA>      NA       NA #> 2953       <NA>      NA       NA #> 2954       <NA>      NA       NA #> 2955          +      NA       NA #> 2956       <NA>      NA       NA #> 2957       <NA>      NA       NA #> 2958       <NA>      NA       NA #> 2959          +      NA       NA #> 2960       <NA>      NA       NA #> 2961       <NA>      NA       NA #> 2962       <NA>      NA       NA #> 2963          +      NA       NA #> 2964       <NA>      NA       NA #> 2965       <NA>      NA       NA #> 2966       <NA>      NA       NA #> 2967          +      NA       NA #> 2968       <NA>      NA       NA #> 2969       <NA>      NA       NA #> 2970       <NA>      NA       NA #> 2971          +      NA       NA #> 2972       <NA>      NA       NA #> 2973       <NA>      NA       NA #> 2974       <NA>      NA       NA #> 2975          +      NA       NA #> 2976       <NA>      NA       NA #> 2977       <NA>      NA       NA #> 2978       <NA>      NA       NA #> 2979       <NA>      NA       NA #> 2980       <NA>      NA       NA #> 2981          U      NA       NA #> 2982          +      NA       NA #> 2983       <NA>      NA       NA #> 2984          +      NA       NA #> 2985       <NA>      NA       NA #> 2986          U      NA       NA #> 2987       <NA>      NA       NA #> 2988       <NA>      NA       NA #> 2989       <NA>      NA       NA #> 2990       <NA>      NA       NA #> 2991       <NA>      NA       NA #> 2992          I      NA       NA #> 2993          +      NA       NA #> 2994       <NA>      NA       NA #> 2995          +      NA       NA #> 2996       <NA>      NA       NA #> 2997       <NA>      NA       NA #> 2998          A      NA       NA #> 2999       <NA>      NA       NA #> 3000       <NA>      NA       NA #> 3001       <NA>      NA       NA #> 3002       <NA>      NA       NA #> 3003       <NA>      NA       NA #> 3004          +      NA       NA #> 3005       <NA>      NA      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NA       NA #> 3034       <NA>      NA       NA #> 3035       <NA>      NA       NA #> 3036          +      NA       NA #> 3037       <NA>      NA       NA #> 3038          I      NA       NA #> 3039       <NA>      NA       NA #> 3040       <NA>      NA       NA #> 3041       <NA>      NA       NA #> 3042       <NA>      NA       NA #> 3043       <NA>      NA       NA #> 3044          A      NA       NA #> 3045       <NA>      NA       NA #> 3046          I      NA       NA #> 3047       <NA>      NA       NA #> 3048       <NA>      NA       NA #> 3049          +      NA       NA #> 3050       <NA>      NA       NA #> 3051          I      NA       NA #> 3052       <NA>      NA       NA #> 3053       <NA>      NA       NA #> 3054       <NA>      NA       NA #> 3055       <NA>      NA       NA #> 3056       <NA>      NA       NA #> 3057          I      NA       NA #> 3058       <NA>      NA       NA #> 3059       <NA>      NA       NA #> 3060          +      NA       NA #> 3061       <NA>      NA       NA #> 3062          I      NA       NA #> 3063       <NA>      NA       NA #> 3064       <NA>      NA       NA #> 3065       <NA>      NA       NA #> 3066       <NA>      NA       NA #> 3067       <NA>      NA       NA #> 3068          U      NA       NA #> 3069       <NA>      NA       NA #> 3070       <NA>      NA       NA #> 3071          +      NA       NA #> 3072       <NA>      NA       NA #> 3073          I      NA       NA #> 3074       <NA>      NA       NA #> 3075       <NA>      NA       NA #> 3076       <NA>      NA       NA #> 3077       <NA>      NA       NA #> 3078       <NA>      NA       NA #> 3079       <NA>      NA       NA #> 3080       <NA>      NA       NA #> 3081       <NA>      NA       NA #> 3082          +      NA       NA #> 3083       <NA>      NA       NA #> 3084          I      NA       NA #> 3085       <NA>      NA       NA #> 3086       <NA>      NA       NA #> 3087       <NA>      NA       NA #> 3088       <NA>      NA       NA #> 3089       <NA>      NA       NA #> 3090       <NA>      NA       NA #> 3091       <NA>      NA       NA #> 3092          +      NA       NA #> 3093       <NA>      NA       NA #> 3094          I      NA       NA #> 3095       <NA>      NA       NA #> 3096       <NA>      NA       NA #> 3097       <NA>      NA       NA #> 3098       <NA>      NA       NA #> 3099       <NA>      NA       NA #> 3100          I      NA       NA #> 3101       <NA>      NA       NA #> 3102       <NA>      NA       NA #> 3103          +      NA       NA #> 3104       <NA>      NA       NA #> 3105       <NA>      NA       NA #> 3106       <NA>      NA       NA #> 3107       <NA>      NA       NA #> 3108       <NA>      NA       NA #> 3109       <NA>      NA       NA #> 3110       <NA>      NA       NA #> 3111       <NA>      NA       NA #> 3112       <NA>      NA       NA #> 3113       <NA>      NA       NA #> 3114       <NA>      NA       NA #> 3115       <NA>      NA       NA #> 3116       <NA>      NA      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3200       <NA>      NA       NA #> 3201       <NA>      NA       NA #> 3202       <NA>      NA       NA #> 3203       <NA>      NA       NA #> 3204          U      NA       NA #> 3205       <NA>      NA       NA #> 3206       <NA>      NA       NA #> 3207          +      NA       NA #> 3208       <NA>      NA       NA #> 3209          I      NA       NA #> 3210       <NA>      NA       NA #> 3211       <NA>      NA       NA #> 3212       <NA>      NA       NA #> 3213       <NA>      NA       NA #> 3214       <NA>      NA       NA #> 3215          U      NA       NA #> 3216       <NA>      NA       NA #> 3217       <NA>      NA       NA #> 3218          +      NA       NA #> 3219       <NA>      NA       NA #> 3220          U      NA       NA #> 3221       <NA>      NA       NA #> 3222       <NA>      NA       NA #> 3223       <NA>      NA       NA #> 3224       <NA>      NA       NA #> 3225       <NA>      NA       NA #> 3226       <NA>      NA       NA #> 3227       <NA>      NA      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+      NA       NA #> 3284       <NA>      NA       NA #> 3285       <NA>      NA       NA #> 3286       <NA>      NA       NA #> 3287          U      NA       NA #> 3288       <NA>      NA       NA #> 3289       <NA>      NA       NA #> 3290       <NA>      NA       NA #> 3291          U      NA       NA #> 3292       <NA>      NA       NA #> 3293       <NA>      NA       NA #> 3294          +      NA       NA #> 3295       <NA>      NA       NA #> 3296       <NA>      NA       NA #> 3297       <NA>      NA       NA #> 3298       <NA>      NA       NA #> 3299       <NA>      NA       NA #> 3300       <NA>      NA       NA #> 3301       <NA>      NA       NA #> 3302          I      NA       NA #> 3303       <NA>      NA       NA #> 3304       <NA>      NA       NA #> 3305          +      NA       NA #> 3306       <NA>      NA       NA #> 3307       <NA>      NA       NA #> 3308       <NA>      NA       NA #> 3309       <NA>      NA       NA #> 3310       <NA>      NA       NA #> 3311       <NA>      NA       NA #> 3312       <NA>      NA       NA #> 3313          I      NA       NA #> 3314       <NA>      NA       NA #> 3315       <NA>      NA       NA #> 3316          +      NA       NA #> 3317       <NA>      NA       NA #> 3318          I      NA       NA #> 3319       <NA>      NA       NA #> 3320       <NA>      NA       NA #> 3321       <NA>      NA       NA #> 3322       <NA>      NA       NA #> 3323       <NA>      NA       NA #> 3324          U      NA       NA #> 3325       <NA>      NA       NA #> 3326       <NA>      NA       NA #> 3327          +      NA       NA #> 3328       <NA>      NA       NA #> 3329       <NA>      NA       NA #> 3330       <NA>      NA       NA #> 3331       <NA>      NA       NA #> 3332       <NA>      NA       NA #> 3333       <NA>      NA       NA #> 3334       <NA>      NA       NA #> 3335       <NA>      NA       NA #> 3336       <NA>      NA       NA #> 3337       <NA>      NA       NA #> 3338          +      NA       NA #> 3339       <NA>      NA       NA #> 3340          I      NA       NA #> 3341       <NA>      NA       NA #> 3342          I      NA       NA #> 3343       <NA>      NA       NA #> 3344       <NA>      NA       NA #> 3345       <NA>      NA       NA #> 3346          U      NA       NA #> 3347       <NA>      NA       NA #> 3348       <NA>      NA       NA #> 3349          +      NA       NA #> 3350       <NA>      NA       NA #> 3351          I      NA       NA #> 3352       <NA>      NA       NA #> 3353       <NA>      NA       NA #> 3354       <NA>      NA       NA #> 3355       <NA>      NA       NA #> 3356       <NA>      NA       NA #> 3357          U      NA       NA #> 3358       <NA>      NA       NA #> 3359       <NA>      NA       NA #> 3360          +      NA       NA #> 3361       <NA>      NA       NA #> 3362       <NA>      NA       NA #> 3363       <NA>      NA       NA #> 3364       <NA>      NA       NA #> 3365       <NA>      NA       NA #> 3366       <NA>      NA      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<NA>      NA       NA #> 3423       <NA>      NA       NA #> 3424       <NA>      NA       NA #> 3425       <NA>      NA       NA #> 3426          A      NA       NA #> 3427       <NA>      NA       NA #> 3428       <NA>      NA       NA #> 3429       <NA>      NA       NA #> 3430       <NA>      NA       NA #> 3431       <NA>      NA       NA #> 3432       <NA>      NA       NA #> 3433          +      NA       NA #> 3434       <NA>      NA       NA #> 3435          I      NA       NA #> 3436       <NA>      NA       NA #> 3437       <NA>      NA       NA #> 3438       <NA>      NA       NA #> 3439       <NA>      NA       NA #> 3440       <NA>      NA       NA #> 3441       <NA>      NA       NA #> 3442       <NA>      NA       NA #> 3443          U      NA       NA #> 3444       <NA>      NA       NA #> 3445       <NA>      NA       NA #> 3446          +      NA       NA #> 3447       <NA>      NA       NA #> 3448          I      NA       NA #> 3449       <NA>      NA       NA #> 3450       <NA>      NA       NA #> 3451       <NA>      NA       NA #> 3452       <NA>      NA       NA #> 3453          +      NA       NA #> 3454          U      NA       NA #> 3455       <NA>      NA       NA #> 3456       <NA>      NA       NA #> 3457          +      NA       NA #> 3458       <NA>      NA       NA #> 3459          I      NA       NA #> 3460       <NA>      NA       NA #> 3461       <NA>      NA       NA #> 3462       <NA>      NA       NA #> 3463       <NA>      NA       NA #> 3464       <NA>      NA       NA #> 3465       <NA>      NA       NA #> 3466       <NA>      NA       NA #> 3467       <NA>      NA       NA #> 3468       <NA>      NA       NA #> 3469          U      NA       NA #> 3470       <NA>      NA       NA #> 3471       <NA>      NA       NA #> 3472          +      NA       NA #> 3473       <NA>      NA       NA #> 3474          I      NA       NA #> 3475       <NA>      NA       NA #> 3476       <NA>      NA       NA #> 3477       <NA>      NA      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NA       NA #> 3506       <NA>      NA       NA #> 3507       <NA>      NA       NA #> 3508       <NA>      NA       NA #> 3509       <NA>      NA       NA #> 3510       <NA>      NA       NA #> 3511       <NA>      NA       NA #> 3512       <NA>      NA       NA #> 3513       <NA>      NA       NA #> 3514       <NA>      NA       NA #> 3515       <NA>      NA       NA #> 3516       <NA>      NA       NA #> 3517       <NA>      NA       NA #> 3518       <NA>      NA       NA #> 3519       <NA>      NA       NA #> 3520          +      NA       NA #> 3521       <NA>      NA       NA #> 3522          I      NA       NA #> 3523       <NA>      NA       NA #> 3524       <NA>      NA       NA #> 3525       <NA>      NA       NA #> 3526       <NA>      NA       NA #> 3527       <NA>      NA       NA #> 3528       <NA>      NA       NA #> 3529       <NA>      NA       NA #> 3530       <NA>      NA       NA #> 3531       <NA>      NA       NA #> 3532       <NA>      NA       NA #> 3533       <NA>      NA       NA #> 3534       <NA>      NA       NA #> 3535       <NA>      NA       NA #> 3536       <NA>      NA       NA #> 3537       <NA>      NA       NA #> 3538       <NA>      NA       NA #> 3539          +      NA       NA #> 3540       <NA>      NA       NA #> 3541          I      NA       NA #> 3542          A      NA       NA #> 3543       <NA>      NA       NA #> 3544       <NA>      NA       NA #> 3545       <NA>      NA       NA #> 3546       <NA>      NA       NA #> 3547       <NA>      NA       NA #> 3548       <NA>      NA       NA #> 3549       <NA>      NA       NA #> 3550          +      NA       NA #> 3551       <NA>      NA       NA #> 3552          I      NA       NA #> 3553       <NA>      NA       NA #> 3554       <NA>      NA       NA #> 3555       <NA>      NA       NA #> 3556       <NA>      NA       NA #> 3557       <NA>      NA       NA #> 3558          U      NA       NA #> 3559       <NA>      NA       NA #> 3560       <NA>      NA       NA #> 3561          +      NA       NA #> 3562       <NA>      NA       NA #> 3563          I      NA       NA #> 3564       <NA>      NA       NA #> 3565       <NA>      NA       NA #> 3566       <NA>      NA       NA #> 3567       <NA>      NA       NA #> 3568       <NA>      NA       NA #> 3569          U      NA       NA #> 3570       <NA>      NA       NA #> 3571       <NA>      NA       NA #> 3572          +      NA       NA #> 3573       <NA>      NA       NA #> 3574          I      NA       NA #> 3575       <NA>      NA       NA #> 3576       <NA>      NA       NA #> 3577       <NA>      NA       NA #> 3578       <NA>      NA       NA #> 3579       <NA>      NA       NA #> 3580          U      NA       NA #> 3581       <NA>      NA       NA #> 3582       <NA>      NA       NA #> 3583          +      NA       NA #> 3584       <NA>      NA       NA #> 3585          I      NA       NA #> 3586       <NA>      NA       NA #> 3587       <NA>      NA       NA #> 3588       <NA>      NA      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NA       NA #> 3617       <NA>      NA       NA #> 3618       <NA>      NA       NA #> 3619       <NA>      NA       NA #> 3620       <NA>      NA       NA #> 3621       <NA>      NA       NA #> 3622       <NA>      NA       NA #> 3623       <NA>      NA       NA #> 3624          I      NA       NA #> 3625       <NA>      NA       NA #> 3626       <NA>      NA       NA #> 3627          +      NA       NA #> 3628       <NA>      NA       NA #> 3629          I      NA       NA #> 3630       <NA>      NA       NA #> 3631       <NA>      NA       NA #> 3632       <NA>      NA       NA #> 3633       <NA>      NA       NA #> 3634       <NA>      NA       NA #> 3635          U      NA       NA #> 3636       <NA>      NA       NA #> 3637       <NA>      NA       NA #> 3638          +      NA       NA #> 3639       <NA>      NA       NA #> 3640       <NA>      NA       NA #> 3641       <NA>      NA       NA #> 3642          A      NA       NA #> 3643       <NA>      NA       NA #> 3644       <NA>      NA       NA #> 3645       <NA>      NA       NA #> 3646          I      NA       NA #> 3647       <NA>      NA       NA #> 3648       <NA>      NA       NA #> 3649          +      NA       NA #> 3650       <NA>      NA       NA #> 3651          I      NA       NA #> 3652       <NA>      NA       NA #> 3653       <NA>      NA       NA #> 3654       <NA>      NA       NA #> 3655       <NA>      NA       NA #> 3656       <NA>      NA       NA #> 3657          U      NA       NA #> 3658       <NA>      NA       NA #> 3659       <NA>      NA       NA #> 3660          +      NA       NA #> 3661       <NA>      NA       NA #> 3662       <NA>      NA       NA #> 3663       <NA>      NA       NA #> 3664       <NA>      NA       NA #> 3665       <NA>      NA       NA #> 3666       <NA>      NA       NA #> 3667       <NA>      NA       NA #> 3668          U      NA       NA #> 3669       <NA>      NA       NA #> 3670       <NA>      NA       NA #> 3671          +      NA       NA #> 3672       <NA>      NA       NA #> 3673          I      NA       NA #> 3674       <NA>      NA       NA #> 3675       <NA>      NA       NA #> 3676       <NA>      NA       NA #> 3677       <NA>      NA       NA #> 3678       <NA>      NA       NA #> 3679          U      NA       NA #> 3680       <NA>      NA       NA #> 3681       <NA>      NA       NA #> 3682          +      NA       NA #> 3683       <NA>      NA       NA #> 3684       <NA>      NA       NA #> 3685       <NA>      NA       NA #> 3686       <NA>      NA       NA #> 3687       <NA>      NA       NA #> 3688       <NA>      NA       NA #> 3689       <NA>      NA       NA #> 3690          U      NA       NA #> 3691       <NA>      NA       NA #> 3692       <NA>      NA       NA #> 3693          +      NA       NA #> 3694       <NA>      NA       NA #> 3695          I      NA       NA #> 3696       <NA>      NA       NA #> 3697       <NA>      NA       NA #> 3698       <NA>      NA       NA #> 3699       <NA>      NA      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NA       NA #> 3728       <NA>      NA       NA #> 3729       <NA>      NA       NA #> 3730       <NA>      NA       NA #> 3731       <NA>      NA       NA #> 3732       <NA>      NA       NA #> 3733       <NA>      NA       NA #> 3734       <NA>      NA       NA #> 3735       <NA>      NA       NA #> 3736       <NA>      NA       NA #> 3737          +      NA       NA #> 3738       <NA>      NA       NA #> 3739       <NA>      NA       NA #> 3740       <NA>      NA       NA #> 3741       <NA>      NA       NA #> 3742       <NA>      NA       NA #> 3743       <NA>      NA       NA #> 3744       <NA>      NA       NA #> 3745       <NA>      NA       NA #> 3746       <NA>      NA       NA #> 3747       <NA>      NA       NA #> 3748          +      NA       NA #> 3749       <NA>      NA       NA #> 3750          I      NA       NA #> 3751       <NA>      NA       NA #> 3752       <NA>      NA       NA #> 3753       <NA>      NA       NA #> 3754       <NA>      NA       NA #> 3755       <NA>      NA       NA #> 3756          U      NA       NA #> 3757       <NA>      NA       NA #> 3758       <NA>      NA       NA #> 3759          +      NA       NA #> 3760       <NA>      NA       NA #> 3761          I      NA       NA #> 3762       <NA>      NA       NA #> 3763       <NA>      NA       NA #> 3764          +      NA       NA #> 3765          I      NA       NA #> 3766       <NA>      NA       NA #> 3767       <NA>      NA       NA #> 3768          +      NA       NA #> 3769       <NA>      NA       NA #> 3770       <NA>      NA       NA #> 3771       <NA>      NA       NA #> 3772       <NA>      NA       NA #> 3773          +      NA       NA #> 3774       <NA>      NA       NA #> 3775       <NA>      NA       NA #> 3776       <NA>      NA       NA #> 3777          +      NA       NA #> 3778       <NA>      NA       NA #> 3779       <NA>      NA       NA #> 3780       <NA>      NA       NA #> 3781       <NA>      NA       NA #> 3782          +      NA       NA #> 3783          I      NA       NA #> 3784       <NA>      NA       NA #> 3785       <NA>      NA       NA #> 3786          +      NA       NA #> 3787       <NA>      NA       NA #> 3788       <NA>      NA       NA #> 3789       <NA>      NA       NA #> 3790       <NA>      NA       NA #> 3791       <NA>      NA       NA #> 3792          +      NA       NA #> 3793          I      NA       NA #> 3794       <NA>      NA       NA #> 3795       <NA>      NA       NA #> 3796          +      NA       NA #> 3797       <NA>      NA       NA #> 3798       <NA>      NA       NA #> 3799       <NA>      NA       NA #> 3800          A      NA       NA #> 3801       <NA>      NA       NA #> 3802          +      NA       NA #> 3803       <NA>      NA       NA #> 3804       <NA>      NA       NA #> 3805       <NA>      NA       NA #> 3806          +      NA       NA #> 3807       <NA>      NA       NA #> 3808          A      NA       NA #> 3809       <NA>      NA       NA #> 3810          A      NA      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NA       NA #> 3839          +      NA       NA #> 3840       <NA>      NA       NA #> 3841       <NA>      NA       NA #> 3842       <NA>      NA       NA #> 3843          +      NA       NA #> 3844       <NA>      NA       NA #> 3845          A      NA       NA #> 3846       <NA>      NA       NA #> 3847       <NA>      NA       NA #> 3848       <NA>      NA       NA #> 3849       <NA>      NA       NA #> 3850       <NA>      NA       NA #> 3851          +      NA       NA #> 3852       <NA>      NA       NA #> 3853          A      NA       NA #> 3854       <NA>      NA       NA #> 3855          A      NA       NA #> 3856       <NA>      NA       NA #> 3857       <NA>      NA       NA #> 3858          +      NA       NA #> 3859       <NA>      NA       NA #> 3860       <NA>      NA       NA #> 3861       <NA>      NA       NA #> 3862       <NA>      NA       NA #> 3863          +      NA       NA #> 3864       <NA>      NA       NA #> 3865       <NA>      NA       NA #> 3866       <NA>      NA       NA #> 3867          +      NA       NA #> 3868       <NA>      NA       NA #> 3869       <NA>      NA       NA #> 3870       <NA>      NA       NA #> 3871       <NA>      NA       NA #> 3872          +      NA       NA #> 3873          I      NA       NA #> 3874       <NA>      NA       NA #> 3875          +      NA       NA #> 3876       <NA>      NA       NA #> 3877       <NA>      NA       NA #> 3878       <NA>      NA       NA #> 3879       <NA>      NA       NA #> 3880          +      NA       NA #> 3881       <NA>      NA       NA #> 3882          +      NA       NA #> 3883       <NA>      NA       NA #> 3884          A      NA       NA #> 3885       <NA>      NA       NA #> 3886       <NA>      NA       NA #> 3887          +      NA       NA #> 3888       <NA>      NA       NA #> 3889       <NA>      NA       NA #> 3890       <NA>      NA       NA #> 3891          +      NA       NA #> 3892       <NA>      NA       NA #> 3893       <NA>      NA       NA #> 3894       <NA>      NA       NA #> 3895       <NA>      NA       NA #> 3896       <NA>      NA       NA #> 3897          +      NA       NA #> 3898          I      NA       NA #> 3899       <NA>      NA       NA #> 3900       <NA>      NA       NA #> 3901          +      NA       NA #> 3902       <NA>      NA       NA #> 3903       <NA>      NA       NA #> 3904       <NA>      NA       NA #> 3905       <NA>      NA       NA #> 3906       <NA>      NA       NA #> 3907       <NA>      NA       NA #> 3908       <NA>      NA       NA #> 3909          +      NA       NA #> 3910       <NA>      NA       NA #> 3911       <NA>      NA       NA #> 3912       <NA>      NA       NA #> 3913       <NA>      NA       NA #> 3914       <NA>      NA       NA #> 3915          +      NA       NA #> 3916       <NA>      NA       NA #> 3917       <NA>      NA       NA #> 3918       <NA>      NA       NA #> 3919          +      NA       NA #> 3920       <NA>      NA       NA #> 3921       <NA>      NA      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NA       NA #> 3950       <NA>      NA       NA #> 3951          +      NA       NA #> 3952          I      NA       NA #> 3953       <NA>      NA       NA #> 3954       <NA>      NA       NA #> 3955          +      NA       NA #> 3956       <NA>      NA       NA #> 3957          A      NA       NA #> 3958          I      NA       NA #> 3959       <NA>      NA       NA #> 3960          +      NA       NA #> 3961          U      NA       NA #> 3962       <NA>      NA       NA #> 3963          +      NA       NA #> 3964       <NA>      NA       NA #> 3965       <NA>      NA       NA #> 3966       <NA>      NA       NA #> 3967       <NA>      NA       NA #> 3968          +      NA       NA #> 3969          I      NA       NA #> 3970       <NA>      NA       NA #> 3971       <NA>      NA       NA #> 3972          +      NA       NA #> 3973       <NA>      NA       NA #> 3974       <NA>      NA       NA #> 3975       <NA>      NA       NA #> 3976          A      NA       NA #> 3977       <NA>      NA       NA #> 3978          +      NA       NA #> 3979          I      NA       NA #> 3980       <NA>      NA       NA #> 3981       <NA>      NA       NA #> 3982          +      NA       NA #> 3983       <NA>      NA       NA #> 3984       <NA>      NA       NA #> 3985       <NA>      NA       NA #> 3986       <NA>      NA       NA #> 3987          +      NA       NA #> 3988          I      NA       NA #> 3989       <NA>      NA       NA #> 3990       <NA>      NA       NA #> 3991          +      NA       NA #> 3992       <NA>      NA       NA #> 3993       <NA>      NA       NA #> 3994       <NA>      NA       NA #> 3995       <NA>      NA       NA #> 3996          I      NA       NA #> 3997       <NA>      NA       NA #> 3998          +      NA       NA #> 3999       <NA>      NA       NA #> 4000       <NA>      NA       NA #> 4001       <NA>      NA       NA #> 4002       <NA>      NA       NA #> 4003          +      NA       NA #> 4004          I      NA       NA #> 4005       <NA>      NA       NA #> 4006       <NA>      NA       NA #> 4007          +      NA       NA #> 4008       <NA>      NA       NA #> 4009       <NA>      NA       NA #> 4010       <NA>      NA       NA #> 4011       <NA>      NA       NA #> 4012          +      NA       NA #> 4013       <NA>      NA       NA #> 4014       <NA>      NA       NA #> 4015       <NA>      NA       NA #> 4016          +      NA       NA #> 4017       <NA>      NA       NA #> 4018       <NA>      NA       NA #> 4019          I      NA       NA #> 4020       <NA>      NA       NA #> 4021       <NA>      NA       NA #> 4022          +      NA       NA #> 4023       <NA>      NA       NA #> 4024       <NA>      NA       NA #> 4025       <NA>      NA       NA #> 4026          +      NA       NA #> 4027       <NA>      NA       NA #> 4028       <NA>      NA       NA #> 4029       <NA>      NA       NA #> 4030          A      NA       NA #> 4031          +      NA       NA #> 4032       <NA>      NA      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NA       NA #> 4061          I      NA       NA #> 4062       <NA>      NA       NA #> 4063          +      NA       NA #> 4064       <NA>      NA       NA #> 4065          A      NA       NA #> 4066          A      NA       NA #> 4067       <NA>      NA       NA #> 4068          +      NA       NA #> 4069          U      NA       NA #> 4070       <NA>      NA       NA #> 4071       <NA>      NA       NA #> 4072          +      NA       NA #> 4073       <NA>      NA       NA #> 4074       <NA>      NA       NA #> 4075       <NA>      NA       NA #> 4076       <NA>      NA       NA #> 4077       <NA>      NA       NA #> 4078          +      NA       NA #> 4079          I      NA       NA #> 4080       <NA>      NA       NA #> 4081          +      NA       NA #> 4082       <NA>      NA       NA #> 4083       <NA>      NA       NA #> 4084       <NA>      NA       NA #> 4085       <NA>      NA       NA #> 4086          +      NA       NA #> 4087       <NA>      NA       NA #> 4088          +      NA       NA #> 4089       <NA>      NA       NA #> 4090       <NA>      NA       NA #> 4091       <NA>      NA       NA #> 4092          +      NA       NA #> 4093       <NA>      NA       NA #> 4094       <NA>      NA       NA #> 4095       <NA>      NA       NA #> 4096          +      NA       NA #> 4097       <NA>      NA       NA #> 4098       <NA>      NA       NA #> 4099       <NA>      NA       NA #> 4100       <NA>      NA       NA #> 4101       <NA>      NA       NA #> 4102          +      NA       NA #> 4103       <NA>      NA       NA #> 4104       <NA>      NA       NA #> 4105       <NA>      NA       NA #> 4106          +      NA       NA #> 4107       <NA>      NA       NA #> 4108       <NA>      NA       NA #> 4109       <NA>      NA       NA #> 4110       <NA>      NA       NA #> 4111       <NA>      NA       NA #> 4112       <NA>      NA       NA #> 4113       <NA>      NA       NA #> 4114       <NA>      NA       NA #> 4115          +      NA       NA #> 4116       <NA>      NA       NA #> 4117       <NA>      NA       NA #> 4118       <NA>      NA       NA #> 4119       <NA>      NA       NA #> 4120       <NA>      NA       NA #> 4121          +      NA       NA #> 4122          U      NA       NA #> 4123       <NA>      NA       NA #> 4124       <NA>      NA       NA #> 4125          +      NA       NA #> 4126       <NA>      NA       NA #> 4127       <NA>      NA       NA #> 4128       <NA>      NA       NA #> 4129       <NA>      NA       NA #> 4130          +      NA       NA #> 4131          U      NA       NA #> 4132       <NA>      NA       NA #> 4133          +      NA       NA #> 4134       <NA>      NA       NA #> 4135       <NA>      NA       NA #> 4136       <NA>      NA       NA #> 4137          U      NA       NA #> 4138       <NA>      NA       NA #> 4139          +      NA       NA #> 4140       <NA>      NA       NA #> 4141       <NA>      NA       NA #> 4142       <NA>      NA       NA #> 4143       <NA>      NA       NA #> 4144          +      NA       NA #> 4145          I      NA       NA #> 4146       <NA>      NA       NA #> 4147       <NA>      NA       NA #> 4148          +      NA       NA #> 4149       <NA>      NA       NA #> 4150       <NA>      NA       NA #> 4151       <NA>      NA       NA #> 4152          A      NA       NA #> 4153       <NA>      NA       NA #> 4154       <NA>      NA       NA #> 4155          I      NA       NA #> 4156       <NA>      NA       NA #> 4157       <NA>      NA       NA #> 4158          +      NA       NA #> 4159       <NA>      NA       NA #> 4160       <NA>      NA       NA #> 4161       <NA>      NA       NA #> 4162       <NA>      NA       NA #> 4163       <NA>      NA       NA #> 4164       <NA>      NA       NA #> 4165          I      NA       NA #> 4166       <NA>      NA       NA #> 4167       <NA>      NA       NA #> 4168          +      NA       NA #> 4169       <NA>      NA       NA #> 4170       <NA>      NA       NA #> 4171       <NA>      NA      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<NA>      NA       NA #> 4228          +      NA       NA #> 4229       <NA>      NA       NA #> 4230       <NA>      NA       NA #> 4231       <NA>      NA       NA #> 4232       <NA>      NA       NA #> 4233       <NA>      NA       NA #> 4234       <NA>      NA       NA #> 4235          I      NA       NA #> 4236       <NA>      NA       NA #> 4237       <NA>      NA       NA #> 4238          +      NA       NA #> 4239       <NA>      NA       NA #> 4240          A      NA       NA #> 4241       <NA>      NA       NA #> 4242       <NA>      NA       NA #> 4243       <NA>      NA       NA #> 4244       <NA>      NA       NA #> 4245          A      NA       NA #> 4246       <NA>      NA       NA #> 4247       <NA>      NA       NA #> 4248          U      NA       NA #> 4249       <NA>      NA       NA #> 4250       <NA>      NA       NA #> 4251          +      NA       NA #> 4252       <NA>      NA       NA #> 4253       <NA>      NA       NA #> 4254       <NA>      NA       NA #> 4255       <NA>      NA       NA #> 4256       <NA>      NA       NA #> 4257       <NA>      NA       NA #> 4258          U      NA       NA #> 4259       <NA>      NA       NA #> 4260       <NA>      NA       NA #> 4261          +      NA       NA #> 4262       <NA>      NA       NA #> 4263       <NA>      NA       NA #> 4264       <NA>      NA       NA #> 4265       <NA>      NA       NA #> 4266       <NA>      NA       NA #> 4267       <NA>      NA       NA #> 4268          I      NA       NA #> 4269       <NA>      NA       NA #> 4270       <NA>      NA       NA #> 4271          +      NA       NA #> 4272       <NA>      NA       NA #> 4273       <NA>      NA       NA #> 4274       <NA>      NA       NA #> 4275       <NA>      NA       NA #> 4276       <NA>      NA       NA #> 4277       <NA>      NA       NA #> 4278          I      NA       NA #> 4279       <NA>      NA       NA #> 4280       <NA>      NA       NA #> 4281          +      NA       NA #> 4282       <NA>      NA      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NA       NA #> 4311       <NA>      NA       NA #> 4312       <NA>      NA       NA #> 4313       <NA>      NA       NA #> 4314       <NA>      NA       NA #> 4315       <NA>      NA       NA #> 4316       <NA>      NA       NA #> 4317          +      NA       NA #> 4318       <NA>      NA       NA #> 4319       <NA>      NA       NA #> 4320          I      NA       NA #> 4321          A      NA       NA #> 4322          I      NA       NA #> 4323       <NA>      NA       NA #> 4324       <NA>      NA       NA #> 4325          +      NA       NA #> 4326       <NA>      NA       NA #> 4327       <NA>      NA       NA #> 4328          I      NA       NA #> 4329       <NA>      NA       NA #> 4330          U      NA       NA #> 4331       <NA>      NA       NA #> 4332       <NA>      NA       NA #> 4333          +      NA       NA #> 4334       <NA>      NA       NA #> 4335       <NA>      NA       NA #> 4336       <NA>      NA       NA #> 4337       <NA>      NA       NA #> 4338          I      NA       NA #> 4339       <NA>      NA       NA #> 4340          +      NA       NA #> 4341       <NA>      NA       NA #> 4342       <NA>      NA       NA #> 4343          I      NA       NA #> 4344       <NA>      NA       NA #> 4345       <NA>      NA       NA #> 4346       <NA>      NA       NA #> 4347          I      NA       NA #> 4348       <NA>      NA       NA #> 4349       <NA>      NA       NA #> 4350          +      NA       NA #> 4351       <NA>      NA       NA #> 4352       <NA>      NA       NA #> 4353       <NA>      NA       NA #> 4354          A      NA       NA #> 4355       <NA>      NA       NA #> 4356       <NA>      NA       NA #> 4357          I      NA       NA #> 4358       <NA>      NA       NA #> 4359       <NA>      NA       NA #> 4360          +      NA       NA #> 4361       <NA>      NA       NA #> 4362       <NA>      NA       NA #> 4363          I      NA       NA #> 4364       <NA>      NA       NA #> 4365       <NA>      NA       NA #> 4366       <NA>      NA       NA #> 4367          I      NA       NA #> 4368       <NA>      NA       NA #> 4369       <NA>      NA       NA #> 4370          +      NA       NA #> 4371       <NA>      NA       NA #> 4372       <NA>      NA       NA #> 4373       <NA>      NA       NA #> 4374       <NA>      NA       NA #> 4375       <NA>      NA       NA #> 4376       <NA>      NA       NA #> 4377          U      NA       NA #> 4378       <NA>      NA       NA #> 4379       <NA>      NA       NA #> 4380          +      NA       NA #> 4381       <NA>      NA       NA #> 4382          A      NA       NA #> 4383       <NA>      NA       NA #> 4384       <NA>      NA       NA #> 4385       <NA>      NA       NA #> 4386       <NA>      NA       NA #> 4387       <NA>      NA       NA #> 4388          +      NA       NA #> 4389       <NA>      NA       NA #> 4390       <NA>      NA       NA #> 4391       <NA>      NA       NA #> 4392       <NA>      NA       NA #> 4393       <NA>      NA       NA #> 4394       <NA>      NA       NA #> 4395       <NA>      NA       NA #> 4396       <NA>      NA       NA #> 4397       <NA>      NA       NA #> 4398          +      NA       NA #> 4399       <NA>      NA       NA #> 4400       <NA>      NA       NA #> 4401          I      NA       NA #> 4402       <NA>      NA       NA #> 4403       <NA>      NA       NA #> 4404       <NA>      NA       NA #> 4405       <NA>      NA       NA #> 4406       <NA>      NA       NA #> 4407          +      NA       NA #> 4408       <NA>      NA       NA #> 4409       <NA>      NA       NA #> 4410          I      NA       NA #> 4411       <NA>      NA       NA #> 4412       <NA>      NA       NA #> 4413       <NA>      NA       NA #> 4414          I      NA       NA #> 4415       <NA>      NA       NA #> 4416       <NA>      NA       NA #> 4417          +      NA       NA #> 4418       <NA>      NA       NA #> 4419       <NA>      NA       NA #> 4420          I      NA       NA #> 4421          A      NA      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NA       NA #> 4450       <NA>      NA       NA #> 4451          A      NA       NA #> 4452       <NA>      NA       NA #> 4453       <NA>      NA       NA #> 4454       <NA>      NA       NA #> 4455       <NA>      NA       NA #> 4456       <NA>      NA       NA #> 4457          +      NA       NA #> 4458       <NA>      NA       NA #> 4459       <NA>      NA       NA #> 4460          I      NA       NA #> 4461          A      NA       NA #> 4462       <NA>      NA       NA #> 4463       <NA>      NA       NA #> 4464       <NA>      NA       NA #> 4465       <NA>      NA       NA #> 4466       <NA>      NA       NA #> 4467          +      NA       NA #> 4468       <NA>      NA       NA #> 4469       <NA>      NA       NA #> 4470       <NA>      NA       NA #> 4471       <NA>      NA       NA #> 4472       <NA>      NA       NA #> 4473       <NA>      NA       NA #> 4474          I      NA       NA #> 4475       <NA>      NA       NA #> 4476       <NA>      NA       NA #> 4477          +      NA       NA #> 4478       <NA>      NA       NA #> 4479       <NA>      NA       NA #> 4480       <NA>      NA       NA #> 4481       <NA>      NA       NA #> 4482       <NA>      NA       NA #> 4483       <NA>      NA       NA #> 4484          U      NA       NA #> 4485       <NA>      NA       NA #> 4486       <NA>      NA       NA #> 4487          +      NA       NA #> 4488       <NA>      NA       NA #> 4489       <NA>      NA       NA #> 4490       <NA>      NA       NA #> 4491       <NA>      NA       NA #> 4492          U      NA       NA #> 4493       <NA>      NA       NA #> 4494       <NA>      NA       NA #> 4495          +      NA       NA #> 4496       <NA>      NA       NA #> 4497       <NA>      NA       NA #> 4498       <NA>      NA       NA #> 4499       <NA>      NA       NA #> 4500       <NA>      NA       NA #> 4501       <NA>      NA       NA #> 4502       <NA>      NA       NA #> 4503       <NA>      NA       NA #> 4504       <NA>      NA       NA #> 4505          +      NA       NA #> 4506       <NA>      NA       NA #> 4507          I      NA       NA #> 4508       <NA>      NA       NA #> 4509       <NA>      NA       NA #> 4510       <NA>      NA       NA #> 4511       <NA>      NA       NA #> 4512          I      NA       NA #> 4513       <NA>      NA       NA #> 4514       <NA>      NA       NA #> 4515          +      NA       NA #> 4516       <NA>      NA       NA #> 4517       <NA>      NA       NA #> 4518       <NA>      NA       NA #> 4519       <NA>      NA       NA #> 4520       <NA>      NA       NA #> 4521       <NA>      NA       NA #> 4522       <NA>      NA       NA #> 4523       <NA>      NA       NA #> 4524       <NA>      NA       NA #> 4525          +      NA       NA #> 4526       <NA>      NA       NA #> 4527       <NA>      NA       NA #> 4528       <NA>      NA       NA #> 4529       <NA>      NA       NA #> 4530       <NA>      NA       NA #> 4531       <NA>      NA       NA #> 4532          +      NA       NA #> 4533          U      NA       NA #> 4534       <NA>      NA       NA #> 4535       <NA>      NA       NA #> 4536       <NA>      NA       NA #> 4537       <NA>      NA       NA #> 4538       <NA>      NA       NA #> 4539       <NA>      NA       NA #> 4540       <NA>      NA       NA #> 4541       <NA>      NA       NA #> 4542          +      NA       NA #> 4543       <NA>      NA       NA #> 4544       <NA>      NA       NA #> 4545       <NA>      NA       NA #> 4546       <NA>      NA       NA #> 4547       <NA>      NA       NA #> 4548          +      NA       NA #> 4549          U      NA       NA #> 4550       <NA>      NA       NA #> 4551       <NA>      NA       NA #> 4552       <NA>      NA       NA #> 4553       <NA>      NA       NA #> 4554       <NA>      NA       NA #> 4555       <NA>      NA       NA #> 4556       <NA>      NA       NA #> 4557       <NA>      NA       NA #> 4558          +      NA       NA #> 4559       <NA>      NA       NA #> 4560       <NA>      NA      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NA       NA #> 4589       <NA>      NA       NA #> 4590       <NA>      NA       NA #> 4591       <NA>      NA       NA #> 4592       <NA>      NA       NA #> 4593       <NA>      NA       NA #> 4594          +      NA       NA #> 4595       <NA>      NA       NA #> 4596       <NA>      NA       NA #> 4597       <NA>      NA       NA #> 4598          +      NA       NA #> 4599       <NA>      NA       NA #> 4600       <NA>      NA       NA #> 4601       <NA>      NA       NA #> 4602       <NA>      NA       NA #> 4603       <NA>      NA       NA #> 4604          +      NA       NA #> 4605          U      NA       NA #> 4606       <NA>      NA       NA #> 4607       <NA>      NA       NA #> 4608       <NA>      NA       NA #> 4609       <NA>      NA       NA #> 4610       <NA>      NA       NA #> 4611       <NA>      NA       NA #> 4612       <NA>      NA       NA #> 4613       <NA>      NA       NA #> 4614          +      NA       NA #> 4615       <NA>      NA       NA #> 4616       <NA>      NA       NA #> 4617       <NA>      NA       NA #> 4618          +      NA       NA #> 4619       <NA>      NA       NA #> 4620       <NA>      NA       NA #> 4621       <NA>      NA       NA #> 4622       <NA>      NA       NA #> 4623          +      NA       NA #> 4624       <NA>      NA       NA #> 4625       <NA>      NA       NA #> 4626       <NA>      NA       NA #> 4627       <NA>      NA       NA #> 4628       <NA>      NA       NA #> 4629          I      NA       NA #> 4630       <NA>      NA       NA #> 4631       <NA>      NA       NA #> 4632       <NA>      NA       NA #> 4633          +      NA       NA #> 4634       <NA>      NA       NA #> 4635       <NA>      NA       NA #> 4636       <NA>      NA       NA #> 4637          +      NA       NA #> 4638       <NA>      NA       NA #> 4639       <NA>      NA       NA #> 4640       <NA>      NA       NA #> 4641       <NA>      NA       NA #> 4642       <NA>      NA       NA #> 4643          I      NA       NA #> 4644          +      NA       NA #> 4645       <NA>      NA       NA #> 4646          +      NA       NA #> 4647       <NA>      NA       NA #> 4648          I      NA       NA #> 4649       <NA>      NA       NA #> 4650          A      NA       NA #> 4651       <NA>      NA       NA #> 4652       <NA>      NA       NA #> 4653       <NA>      NA       NA #> 4654       <NA>      NA       NA #> 4655          +      NA       NA #> 4656       <NA>      NA       NA #> 4657          +      NA       NA #> 4658       <NA>      NA       NA #> 4659          I      NA       NA #> 4660       <NA>      NA       NA #> 4661       <NA>      NA       NA #> 4662       <NA>      NA       NA #> 4663       <NA>      NA       NA #> 4664       <NA>      NA       NA #> 4665       <NA>      NA       NA #> 4666          +      NA       NA #> 4667       <NA>      NA       NA #> 4668          +      NA       NA #> 4669       <NA>      NA       NA #> 4670          I      NA       NA #> 4671       <NA>      NA      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NA       NA #> 4700          +      NA       NA #> 4701       <NA>      NA       NA #> 4702          I      NA       NA #> 4703       <NA>      NA       NA #> 4704       <NA>      NA       NA #> 4705       <NA>      NA       NA #> 4706       <NA>      NA       NA #> 4707       <NA>      NA       NA #> 4708       <NA>      NA       NA #> 4709       <NA>      NA       NA #> 4710          U      NA       NA #> 4711       <NA>      NA       NA #> 4712       <NA>      NA       NA #> 4713          +      NA       NA #> 4714       <NA>      NA       NA #> 4715          A      NA       NA #> 4716          A      NA       NA #> 4717       <NA>      NA       NA #> 4718       <NA>      NA       NA #> 4719       <NA>      NA       NA #> 4720       <NA>      NA       NA #> 4721          U      NA       NA #> 4722       <NA>      NA       NA #> 4723       <NA>      NA       NA #> 4724          +      NA       NA #> 4725       <NA>      NA       NA #> 4726          I      NA       NA #> 4727       <NA>      NA       NA #> 4728       <NA>      NA       NA #> 4729       <NA>      NA       NA #> 4730       <NA>      NA       NA #> 4731       <NA>      NA       NA #> 4732          U      NA       NA #> 4733       <NA>      NA       NA #> 4734       <NA>      NA       NA #> 4735          +      NA       NA #> 4736       <NA>      NA       NA #> 4737       <NA>      NA       NA #> 4738       <NA>      NA       NA #> 4739       <NA>      NA       NA #> 4740       <NA>      NA       NA #> 4741       <NA>      NA       NA #> 4742       <NA>      NA       NA #> 4743          I      NA       NA #> 4744       <NA>      NA       NA #> 4745       <NA>      NA       NA #> 4746          +      NA       NA #> 4747       <NA>      NA       NA #> 4748          I      NA       NA #> 4749       <NA>      NA       NA #> 4750       <NA>      NA       NA #> 4751       <NA>      NA       NA #> 4752       <NA>      NA       NA #> 4753       <NA>      NA       NA #> 4754       <NA>      NA       NA #> 4755       <NA>      NA       NA #> 4756       <NA>      NA       NA #> 4757          +      NA       NA #> 4758       <NA>      NA       NA #> 4759          I      NA       NA #> 4760       <NA>      NA       NA #> 4761       <NA>      NA       NA #> 4762       <NA>      NA       NA #> 4763       <NA>      NA       NA #> 4764       <NA>      NA       NA #> 4765          I      NA       NA #> 4766       <NA>      NA       NA #> 4767       <NA>      NA       NA #> 4768       <NA>      NA       NA #> 4769          I      NA       NA #> 4770       <NA>      NA       NA #> 4771       <NA>      NA       NA #> 4772          +      NA       NA #> 4773       <NA>      NA       NA #> 4774          I      NA       NA #> 4775       <NA>      NA       NA #> 4776       <NA>      NA       NA #> 4777       <NA>      NA       NA #> 4778       <NA>      NA       NA #> 4779       <NA>      NA       NA #> 4780          I      NA       NA #> 4781       <NA>      NA       NA #> 4782       <NA>      NA      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NA       NA #> 4811          I      NA       NA #> 4812       <NA>      NA       NA #> 4813       <NA>      NA       NA #> 4814       <NA>      NA       NA #> 4815       <NA>      NA       NA #> 4816       <NA>      NA       NA #> 4817       <NA>      NA       NA #> 4818       <NA>      NA       NA #> 4819       <NA>      NA       NA #> 4820          +      NA       NA #> 4821       <NA>      NA       NA #> 4822          I      NA       NA #> 4823       <NA>      NA       NA #> 4824       <NA>      NA       NA #> 4825       <NA>      NA       NA #> 4826       <NA>      NA       NA #> 4827       <NA>      NA       NA #> 4828       <NA>      NA       NA #> 4829       <NA>      NA       NA #> 4830       <NA>      NA       NA #> 4831          +      NA       NA #> 4832       <NA>      NA       NA #> 4833          I      NA       NA #> 4834       <NA>      NA       NA #> 4835       <NA>      NA       NA #> 4836       <NA>      NA       NA #> 4837       <NA>      NA       NA #> 4838       <NA>      NA       NA #> 4839          U      NA       NA #> 4840       <NA>      NA       NA #> 4841       <NA>      NA       NA #> 4842          +      NA       NA #> 4843       <NA>      NA       NA #> 4844       <NA>      NA       NA #> 4845       <NA>      NA       NA #> 4846       <NA>      NA       NA #> 4847       <NA>      NA       NA #> 4848       <NA>      NA       NA #> 4849       <NA>      NA       NA #> 4850          U      NA       NA #> 4851       <NA>      NA       NA #> 4852       <NA>      NA       NA #> 4853          +      NA       NA #> 4854       <NA>      NA       NA #> 4855          I      NA       NA #> 4856       <NA>      NA       NA #> 4857          I      NA       NA #> 4858       <NA>      NA       NA #> 4859       <NA>      NA       NA #> 4860       <NA>      NA       NA #> 4861          U      NA       NA #> 4862       <NA>      NA       NA #> 4863       <NA>      NA       NA #> 4864          +      NA       NA #> 4865       <NA>      NA       NA #> 4866          I      NA       NA #> 4867       <NA>      NA       NA #> 4868       <NA>      NA       NA #> 4869       <NA>      NA       NA #> 4870       <NA>      NA       NA #> 4871       <NA>      NA       NA #> 4872          I      NA       NA #> 4873       <NA>      NA       NA #> 4874       <NA>      NA       NA #> 4875          +      NA       NA #> 4876       <NA>      NA       NA #> 4877          I      NA       NA #> 4878       <NA>      NA       NA #> 4879       <NA>      NA       NA #> 4880       <NA>      NA       NA #> 4881       <NA>      NA       NA #> 4882       <NA>      NA       NA #> 4883       <NA>      NA       NA #> 4884       <NA>      NA       NA #> 4885       <NA>      NA       NA #> 4886          +      NA       NA #> 4887       <NA>      NA       NA #> 4888          I      NA       NA #> 4889       <NA>      NA       NA #> 4890       <NA>      NA       NA #> 4891       <NA>      NA       NA #> 4892       <NA>      NA       NA #> 4893       <NA>      NA      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NA       NA #> 4922          A      NA       NA #> 4923       <NA>      NA       NA #> 4924       <NA>      NA       NA #> 4925       <NA>      NA       NA #> 4926       <NA>      NA       NA #> 4927       <NA>      NA       NA #> 4928       <NA>      NA       NA #> 4929          +      NA       NA #> 4930       <NA>      NA       NA #> 4931          I      NA       NA #> 4932          A      NA       NA #> 4933       <NA>      NA       NA #> 4934       <NA>      NA       NA #> 4935       <NA>      NA       NA #> 4936       <NA>      NA       NA #> 4937          U      NA       NA #> 4938       <NA>      NA       NA #> 4939       <NA>      NA       NA #> 4940          +      NA       NA #> 4941       <NA>      NA       NA #> 4942          I      NA       NA #> 4943          A      NA       NA #> 4944       <NA>      NA       NA #> 4945       <NA>      NA       NA #> 4946       <NA>      NA       NA #> 4947       <NA>      NA       NA #> 4948          U      NA       NA #> 4949       <NA>      NA       NA #> 4950       <NA>      NA       NA #> 4951          +      NA       NA #> 4952       <NA>      NA       NA #> 4953          I      NA       NA #> 4954       <NA>      NA       NA #> 4955       <NA>      NA       NA #> 4956       <NA>      NA       NA #> 4957       <NA>      NA       NA #> 4958       <NA>      NA       NA #> 4959          I      NA       NA #> 4960       <NA>      NA       NA #> 4961       <NA>      NA       NA #> 4962          +      NA       NA #> 4963       <NA>      NA       NA #> 4964          I      NA       NA #> 4965       <NA>      NA       NA #> 4966       <NA>      NA       NA #> 4967       <NA>      NA       NA #> 4968       <NA>      NA       NA #> 4969       <NA>      NA       NA #> 4970       <NA>      NA       NA #> 4971       <NA>      NA       NA #> 4972       <NA>      NA       NA #> 4973          +      NA       NA #> 4974       <NA>      NA       NA #> 4975          I      NA       NA #> 4976       <NA>      NA       NA #> 4977       <NA>      NA       NA #> 4978       <NA>      NA       NA #> 4979       <NA>      NA       NA #> 4980       <NA>      NA       NA #> 4981       <NA>      NA       NA #> 4982       <NA>      NA       NA #> 4983       <NA>      NA       NA #> 4984          +      NA       NA #> 4985       <NA>      NA       NA #> 4986          I      NA       NA #> 4987       <NA>      NA       NA #> 4988       <NA>      NA       NA #> 4989       <NA>      NA       NA #> 4990       <NA>      NA       NA #> 4991       <NA>      NA       NA #> 4992       <NA>      NA       NA #> 4993       <NA>      NA       NA #> 4994       <NA>      NA       NA #> 4995          +      NA       NA #> 4996       <NA>      NA       NA #> 4997          I      NA       NA #> 4998       <NA>      NA       NA #> 4999       <NA>      NA       NA #> 5000       <NA>      NA       NA #> 5001       <NA>      NA       NA #> 5002       <NA>      NA       NA #> 5003          U      NA       NA #> 5004       <NA>      NA      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NA       NA #> 5033       <NA>      NA       NA #> 5034       <NA>      NA       NA #> 5035          +      NA       NA #> 5036       <NA>      NA       NA #> 5037       <NA>      NA       NA #> 5038       <NA>      NA       NA #> 5039          +      NA       NA #> 5040       <NA>      NA       NA #> 5041       <NA>      NA       NA #> 5042       <NA>      NA       NA #> 5043       <NA>      NA       NA #> 5044       <NA>      NA       NA #> 5045          +      NA       NA #> 5046          U      NA       NA #> 5047       <NA>      NA       NA #> 5048       <NA>      NA       NA #> 5049       <NA>      NA       NA #> 5050       <NA>      NA       NA #> 5051       <NA>      NA       NA #> 5052       <NA>      NA       NA #> 5053       <NA>      NA       NA #> 5054       <NA>      NA       NA #> 5055          +      NA       NA #> 5056       <NA>      NA       NA #> 5057       <NA>      NA       NA #> 5058       <NA>      NA       NA #> 5059          +      NA       NA #> 5060       <NA>      NA       NA #> 5061       <NA>      NA       NA #> 5062          A      NA       NA #> 5063          +      NA       NA #> 5064       <NA>      NA       NA #> 5065       <NA>      NA       NA #> 5066       <NA>      NA       NA #> 5067          +      NA       NA #> 5068       <NA>      NA       NA #> 5069       <NA>      NA       NA #> 5070       <NA>      NA       NA #> 5071       <NA>      NA       NA #> 5072       <NA>      NA       NA #> 5073          +      NA       NA #> 5074       <NA>      NA       NA #> 5075       <NA>      NA       NA #> 5076       <NA>      NA       NA #> 5077          +      NA       NA #> 5078       <NA>      NA       NA #> 5079       <NA>      NA       NA #> 5080       <NA>      NA       NA #> 5081          A      NA       NA #> 5082       <NA>      NA       NA #> 5083          +      NA       NA #> 5084       <NA>      NA       NA #> 5085       <NA>      NA       NA #> 5086       <NA>      NA       NA #> 5087          +      NA       NA #> 5088       <NA>      NA       NA #> 5089       <NA>      NA       NA #> 5090       <NA>      NA       NA #> 5091       <NA>      NA       NA #> 5092       <NA>      NA       NA #> 5093          +      NA       NA #> 5094          I      NA       NA #> 5095       <NA>      NA       NA #> 5096       <NA>      NA       NA #> 5097          +      NA       NA #> 5098       <NA>      NA       NA #> 5099       <NA>      NA       NA #> 5100       <NA>      NA       NA #> 5101       <NA>      NA       NA #> 5102       <NA>      NA       NA #> 5103          +      NA       NA #> 5104          I      NA       NA #> 5105       <NA>      NA       NA #> 5106       <NA>      NA       NA #> 5107          +      NA       NA #> 5108       <NA>      NA       NA #> 5109       <NA>      NA       NA #> 5110       <NA>      NA       NA #> 5111       <NA>      NA       NA #> 5112       <NA>      NA       NA #> 5113          +      NA       NA #> 5114          I      NA       NA #> 5115       <NA>      NA      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NA       NA #> 5144          +      NA       NA #> 5145       <NA>      NA       NA #> 5146          A      NA       NA #> 5147       <NA>      NA       NA #> 5148          A      NA       NA #> 5149       <NA>      NA       NA #> 5150          +      NA       NA #> 5151       <NA>      NA       NA #> 5152       <NA>      NA       NA #> 5153       <NA>      NA       NA #> 5154          +      NA       NA #> 5155       <NA>      NA       NA #> 5156       <NA>      NA       NA #> 5157       <NA>      NA       NA #> 5158          A      NA       NA #> 5159       <NA>      NA       NA #> 5160          +      NA       NA #> 5161       <NA>      NA       NA #> 5162       <NA>      NA       NA #> 5163       <NA>      NA       NA #> 5164          +      NA       NA #> 5165       <NA>      NA       NA #> 5166       <NA>      NA       NA #> 5167       <NA>      NA       NA #> 5168       <NA>      NA       NA #> 5169       <NA>      NA       NA #> 5170          +      NA       NA #> 5171       <NA>      NA       NA #> 5172       <NA>      NA       NA #> 5173       <NA>      NA       NA #> 5174          +      NA       NA #> 5175       <NA>      NA       NA #> 5176       <NA>      NA       NA #> 5177       <NA>      NA       NA #> 5178          A      NA       NA #> 5179       <NA>      NA       NA #> 5180          +      NA       NA #> 5181       <NA>      NA       NA #> 5182       <NA>      NA       NA #> 5183       <NA>      NA       NA #> 5184          +      NA       NA #> 5185       <NA>      NA       NA #> 5186       <NA>      NA       NA #> 5187       <NA>      NA       NA #> 5188          A      NA       NA #> 5189       <NA>      NA       NA #> 5190          +      NA       NA #> 5191       <NA>      NA       NA #> 5192       <NA>      NA       NA #> 5193       <NA>      NA       NA #> 5194          +      NA       NA #> 5195       <NA>      NA       NA #> 5196       <NA>      NA       NA #> 5197       <NA>      NA       NA #> 5198       <NA>      NA       NA #> 5199       <NA>      NA       NA #> 5200          +      NA       NA #> 5201       <NA>      NA       NA #> 5202       <NA>      NA       NA #> 5203       <NA>      NA       NA #> 5204          +      NA       NA #> 5205       <NA>      NA       NA #> 5206       <NA>      NA       NA #> 5207       <NA>      NA       NA #> 5208          A      NA       NA #> 5209       <NA>      NA       NA #> 5210          +      NA       NA #> 5211       <NA>      NA       NA #> 5212       <NA>      NA       NA #> 5213       <NA>      NA       NA #> 5214          +      NA       NA #> 5215       <NA>      NA       NA #> 5216       <NA>      NA       NA #> 5217       <NA>      NA       NA #> 5218          A      NA       NA #> 5219       <NA>      NA       NA #> 5220          +      NA       NA #> 5221          I      NA       NA #> 5222       <NA>      NA       NA #> 5223       <NA>      NA       NA #> 5224          +      NA       NA #> 5225       <NA>      NA       NA #> 5226       <NA>      NA      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NA       NA #> 5255       <NA>      NA       NA #> 5256       <NA>      NA       NA #> 5257          A      NA       NA #> 5258       <NA>      NA       NA #> 5259          +      NA       NA #> 5260       <NA>      NA       NA #> 5261       <NA>      NA       NA #> 5262       <NA>      NA       NA #> 5263          +      NA       NA #> 5264       <NA>      NA       NA #> 5265       <NA>      NA       NA #> 5266       <NA>      NA       NA #> 5267          A      NA       NA #> 5268       <NA>      NA       NA #> 5269       <NA>      NA       NA #> 5270          +      NA       NA #> 5271       <NA>      NA       NA #> 5272       <NA>      NA       NA #> 5273       <NA>      NA       NA #> 5274          A      NA       NA #> 5275       <NA>      NA       NA #> 5276          +      NA       NA #> 5277       <NA>      NA       NA #> 5278       <NA>      NA       NA #> 5279       <NA>      NA       NA #> 5280          +      NA       NA #> 5281       <NA>      NA       NA #> 5282       <NA>      NA       NA #> 5283       <NA>      NA       NA #> 5284       <NA>      NA       NA #> 5285       <NA>      NA       NA #> 5286          +      NA       NA #> 5287       <NA>      NA       NA #> 5288       <NA>      NA       NA #> 5289       <NA>      NA       NA #> 5290          +      NA       NA #> 5291       <NA>      NA       NA #> 5292       <NA>      NA       NA #> 5293       <NA>      NA       NA #> 5294          A      NA       NA #> 5295       <NA>      NA       NA #> 5296          +      NA       NA #> 5297          U      NA       NA #> 5298       <NA>      NA       NA #> 5299       <NA>      NA       NA #> 5300          +      NA       NA #> 5301       <NA>      NA       NA #> 5302       <NA>      NA       NA #> 5303       <NA>      NA       NA #> 5304       <NA>      NA       NA #> 5305       <NA>      NA       NA #> 5306          +      NA       NA #> 5307          U      NA       NA #> 5308       <NA>      NA       NA #> 5309       <NA>      NA       NA #> 5310          +      NA       NA #> 5311       <NA>      NA       NA #> 5312       <NA>      NA       NA #> 5313       <NA>      NA       NA #> 5314          A      NA       NA #> 5315       <NA>      NA       NA #> 5316          +      NA       NA #> 5317          U      NA       NA #> 5318       <NA>      NA       NA #> 5319       <NA>      NA       NA #> 5320          +      NA       NA #> 5321       <NA>      NA       NA #> 5322          A      NA       NA #> 5323       <NA>      NA       NA #> 5324          A      NA       NA #> 5325       <NA>      NA       NA #> 5326          +      NA       NA #> 5327          I      NA       NA #> 5328       <NA>      NA       NA #> 5329          +      NA       NA #> 5330       <NA>      NA       NA #> 5331       <NA>      NA       NA #> 5332       <NA>      NA       NA #> 5333       <NA>      NA       NA #> 5334       <NA>      NA       NA #> 5335          +      NA       NA #> 5336       <NA>      NA       NA #> 5337       <NA>      NA      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NA       NA #> 5366          +      NA       NA #> 5367       <NA>      NA       NA #> 5368       <NA>      NA       NA #> 5369       <NA>      NA       NA #> 5370       <NA>      NA       NA #> 5371       <NA>      NA       NA #> 5372       <NA>      NA       NA #> 5373          U      NA       NA #> 5374       <NA>      NA       NA #> 5375       <NA>      NA       NA #> 5376          +      NA       NA #> 5377       <NA>      NA       NA #> 5378       <NA>      NA       NA #> 5379       <NA>      NA       NA #> 5380       <NA>      NA       NA #> 5381       <NA>      NA       NA #> 5382          +      NA       NA #> 5383          I      NA       NA #> 5384       <NA>      NA       NA #> 5385       <NA>      NA       NA #> 5386          +      NA       NA #> 5387       <NA>      NA       NA #> 5388       <NA>      NA       NA #> 5389       <NA>      NA       NA #> 5390       <NA>      NA       NA #> 5391       <NA>      NA       NA #> 5392       <NA>      NA       NA #> 5393       <NA>      NA       NA #> 5394       <NA>      NA       NA #> 5395       <NA>      NA       NA #> 5396          +      NA       NA #> 5397       <NA>      NA       NA #> 5398       <NA>      NA       NA #> 5399       <NA>      NA       NA #> 5400          A      NA       NA #> 5401       <NA>      NA       NA #> 5402       <NA>      NA       NA #> 5403          I      NA       NA #> 5404       <NA>      NA       NA #> 5405       <NA>      NA       NA #> 5406          +      NA       NA #> 5407       <NA>      NA       NA #> 5408       <NA>      NA       NA #> 5409       <NA>      NA       NA #> 5410          A      NA       NA #> 5411       <NA>      NA       NA #> 5412       <NA>      NA       NA #> 5413          I      NA       NA #> 5414       <NA>      NA       NA #> 5415       <NA>      NA       NA #> 5416          +      NA       NA #> 5417       <NA>      NA       NA #> 5418          A      NA       NA #> 5419       <NA>      NA       NA #> 5420       <NA>      NA       NA #> 5421       <NA>      NA       NA #> 5422       <NA>      NA       NA #> 5423          I      NA       NA #> 5424       <NA>      NA       NA #> 5425       <NA>      NA       NA #> 5426          +      NA       NA #> 5427       <NA>      NA       NA #> 5428       <NA>      NA       NA #> 5429       <NA>      NA       NA #> 5430       <NA>      NA       NA #> 5431       <NA>      NA       NA #> 5432       <NA>      NA       NA #> 5433       <NA>      NA       NA #> 5434       <NA>      NA       NA #> 5435       <NA>      NA       NA #> 5436          +      NA       NA #> 5437       <NA>      NA       NA #> 5438       <NA>      NA       NA #> 5439       <NA>      NA       NA #> 5440       <NA>      NA       NA #> 5441       <NA>      NA       NA #> 5442       <NA>      NA       NA #> 5443       <NA>      NA       NA #> 5444       <NA>      NA       NA #> 5445       <NA>      NA       NA #> 5446          +      NA       NA #> 5447       <NA>      NA       NA #> 5448          A      NA      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NA       NA #> 5477       <NA>      NA       NA #> 5478       <NA>      NA       NA #> 5479          A      NA       NA #> 5480       <NA>      NA       NA #> 5481       <NA>      NA       NA #> 5482          U      NA       NA #> 5483       <NA>      NA       NA #> 5484       <NA>      NA       NA #> 5485          +      NA       NA #> 5486       <NA>      NA       NA #> 5487       <NA>      NA       NA #> 5488       <NA>      NA       NA #> 5489          A      NA       NA #> 5490       <NA>      NA       NA #> 5491       <NA>      NA       NA #> 5492          I      NA       NA #> 5493       <NA>      NA       NA #> 5494       <NA>      NA       NA #> 5495          +      NA       NA #> 5496       <NA>      NA       NA #> 5497       <NA>      NA       NA #> 5498       <NA>      NA       NA #> 5499          A      NA       NA #> 5500       <NA>      NA       NA #> 5501       <NA>      NA       NA #> 5502          I      NA       NA #> 5503       <NA>      NA       NA #> 5504       <NA>      NA       NA #> 5505          +      NA       NA #> 5506       <NA>      NA       NA #> 5507       <NA>      NA       NA #> 5508       <NA>      NA       NA #> 5509          A      NA       NA #> 5510       <NA>      NA       NA #> 5511       <NA>      NA       NA #> 5512          U      NA       NA #> 5513       <NA>      NA       NA #> 5514       <NA>      NA       NA #> 5515          +      NA       NA #> 5516       <NA>      NA       NA #> 5517       <NA>      NA       NA #> 5518       <NA>      NA       NA #> 5519       <NA>      NA       NA #> 5520       <NA>      NA       NA #> 5521       <NA>      NA       NA #> 5522       <NA>      NA       NA #> 5523       <NA>      NA       NA #> 5524       <NA>      NA       NA #> 5525          +      NA       NA #> 5526       <NA>      NA       NA #> 5527       <NA>      NA       NA #> 5528          A      NA       NA #> 5529       <NA>      NA       NA #> 5530       <NA>      NA       NA #> 5531       <NA>      NA       NA #> 5532          I      NA       NA #> 5533       <NA>      NA       NA #> 5534       <NA>      NA       NA #> 5535          +      NA       NA #> 5536       <NA>      NA       NA #> 5537       <NA>      NA       NA #> 5538       <NA>      NA       NA #> 5539          A      NA       NA #> 5540       <NA>      NA       NA #> 5541       <NA>      NA       NA #> 5542          I      NA       NA #> 5543       <NA>      NA       NA #> 5544       <NA>      NA       NA #> 5545          +      NA       NA #> 5546       <NA>      NA       NA #> 5547       <NA>      NA       NA #> 5548       <NA>      NA       NA #> 5549       <NA>      NA       NA #> 5550       <NA>      NA       NA #> 5551       <NA>      NA       NA #> 5552       <NA>      NA       NA #> 5553       <NA>      NA       NA #> 5554       <NA>      NA       NA #> 5555          +      NA       NA #> 5556       <NA>      NA       NA #> 5557          A      NA       NA #> 5558       <NA>      NA       NA #> 5559       <NA>      NA      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NA       NA #> 5588       <NA>      NA       NA #> 5589       <NA>      NA       NA #> 5590       <NA>      NA       NA #> 5591       <NA>      NA       NA #> 5592       <NA>      NA       NA #> 5593       <NA>      NA       NA #> 5594       <NA>      NA       NA #> 5595          +      NA       NA #> 5596       <NA>      NA       NA #> 5597          A      NA       NA #> 5598       <NA>      NA       NA #> 5599       <NA>      NA       NA #> 5600       <NA>      NA       NA #> 5601       <NA>      NA       NA #> 5602       <NA>      NA       NA #> 5603       <NA>      NA       NA #> 5604       <NA>      NA       NA #> 5605          +      NA       NA #> 5606       <NA>      NA       NA #> 5607       <NA>      NA       NA #> 5608          I      NA       NA #> 5609       <NA>      NA       NA #> 5610       <NA>      NA       NA #> 5611       <NA>      NA       NA #> 5612       <NA>      NA       NA #> 5613       <NA>      NA       NA #> 5614       <NA>      NA       NA #> 5615          +      NA       NA #> 5616       <NA>      NA       NA #> 5617       <NA>      NA       NA #> 5618       <NA>      NA       NA #> 5619          A      NA       NA #> 5620       <NA>      NA       NA #> 5621       <NA>      NA       NA #> 5622          I      NA       NA #> 5623       <NA>      NA       NA #> 5624       <NA>      NA       NA #> 5625          +      NA       NA #> 5626       <NA>      NA       NA #> 5627       <NA>      NA       NA #> 5628       <NA>      NA       NA #> 5629          A      NA       NA #> 5630       <NA>      NA       NA #> 5631       <NA>      NA       NA #> 5632          I      NA       NA #> 5633       <NA>      NA       NA #> 5634       <NA>      NA       NA #> 5635          +      NA       NA #> 5636       <NA>      NA       NA #> 5637          A      NA       NA #> 5638       <NA>      NA       NA #> 5639       <NA>      NA       NA #> 5640       <NA>      NA       NA #> 5641       <NA>      NA       NA #> 5642       <NA>      NA       NA #> 5643       <NA>      NA       NA #> 5644       <NA>      NA       NA #> 5645          +      NA       NA #> 5646       <NA>      NA       NA #> 5647       <NA>      NA       NA #> 5648       <NA>      NA       NA #> 5649       <NA>      NA       NA #> 5650       <NA>      NA       NA #> 5651       <NA>      NA       NA #> 5652          I      NA       NA #> 5653       <NA>      NA       NA #> 5654       <NA>      NA       NA #> 5655          +      NA       NA #> 5656       <NA>      NA       NA #> 5657       <NA>      NA       NA #> 5658       <NA>      NA       NA #> 5659       <NA>      NA       NA #> 5660       <NA>      NA       NA #> 5661       <NA>      NA       NA #> 5662          U      NA       NA #> 5663       <NA>      NA       NA #> 5664       <NA>      NA       NA #> 5665          +      NA       NA #> 5666       <NA>      NA       NA #> 5667       <NA>      NA       NA #> 5668       <NA>      NA       NA #> 5669       <NA>      NA       NA #> 5670       <NA>      NA       NA #> 5671       <NA>      NA       NA #> 5672          U      NA       NA #> 5673       <NA>      NA       NA #> 5674       <NA>      NA       NA #> 5675          +      NA       NA #> 5676       <NA>      NA       NA #> 5677       <NA>      NA       NA #> 5678       <NA>      NA       NA #> 5679       <NA>      NA       NA #> 5680       <NA>      NA       NA #> 5681       <NA>      NA       NA #> 5682       <NA>      NA       NA #> 5683       <NA>      NA       NA #> 5684       <NA>      NA       NA #> 5685          +      NA       NA #> 5686       <NA>      NA       NA #> 5687          A      NA       NA #> 5688       <NA>      NA       NA #> 5689          A      NA       NA #> 5690       <NA>      NA       NA #> 5691       <NA>      NA       NA #> 5692       <NA>      NA       NA #> 5693       <NA>      NA       NA #> 5694       <NA>      NA       NA #> 5695          +      NA       NA #> 5696       <NA>      NA       NA #> 5697       <NA>      NA       NA #> 5698       <NA>      NA      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+      NA       NA #> 5755       <NA>      NA       NA #> 5756       <NA>      NA       NA #> 5757       <NA>      NA       NA #> 5758       <NA>      NA       NA #> 5759       <NA>      NA       NA #> 5760       <NA>      NA       NA #> 5761          I      NA       NA #> 5762       <NA>      NA       NA #> 5763       <NA>      NA       NA #> 5764          +      NA       NA #> 5765       <NA>      NA       NA #> 5766          A      NA       NA #> 5767       <NA>      NA       NA #> 5768       <NA>      NA       NA #> 5769       <NA>      NA       NA #> 5770       <NA>      NA       NA #> 5771          I      NA       NA #> 5772       <NA>      NA       NA #> 5773       <NA>      NA       NA #> 5774          +      NA       NA #> 5775       <NA>      NA       NA #> 5776          A      NA       NA #> 5777       <NA>      NA       NA #> 5778       <NA>      NA       NA #> 5779       <NA>      NA       NA #> 5780       <NA>      NA       NA #> 5781          U      NA       NA #> 5782       <NA>      NA       NA #> 5783       <NA>      NA       NA #> 5784          +      NA       NA #> 5785       <NA>      NA       NA #> 5786          A      NA       NA #> 5787       <NA>      NA       NA #> 5788       <NA>      NA       NA #> 5789       <NA>      NA       NA #> 5790       <NA>      NA       NA #> 5791          I      NA       NA #> 5792       <NA>      NA       NA #> 5793       <NA>      NA       NA #> 5794          +      NA       NA #> 5795       <NA>      NA       NA #> 5796       <NA>      NA       NA #> 5797       <NA>      NA       NA #> 5798          A      NA       NA #> 5799          I      NA       NA #> 5800       <NA>      NA       NA #> 5801       <NA>      NA       NA #> 5802          +      NA       NA #> 5803       <NA>      NA       NA #> 5804       <NA>      NA       NA #> 5805          A      NA       NA #> 5806       <NA>      NA       NA #> 5807       <NA>      NA       NA #> 5808       <NA>      NA       NA #> 5809       <NA>      NA       NA #> 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<NA>      NA       NA #> 5894       <NA>      NA       NA #> 5895       <NA>      NA       NA #> 5896          +      NA       NA #> 5897       <NA>      NA       NA #> 5898       <NA>      NA       NA #> 5899       <NA>      NA       NA #> 5900          +      NA       NA #> 5901       <NA>      NA       NA #> 5902       <NA>      NA       NA #> 5903       <NA>      NA       NA #> 5904          +      NA       NA #> 5905       <NA>      NA       NA #> 5906       <NA>      NA       NA #> 5907       <NA>      NA       NA #> 5908          +      NA       NA #> 5909       <NA>      NA       NA #> 5910       <NA>      NA       NA #> 5911       <NA>      NA       NA #> 5912          +      NA       NA #> 5913       <NA>      NA       NA #> 5914          I      NA       NA #> 5915       <NA>      NA       NA #> 5916       <NA>      NA       NA #> 5917       <NA>      NA       NA #> 5918       <NA>      NA       NA #> 5919       <NA>      NA       NA #> 5920          +      NA       NA #> 5921       <NA>      NA       NA #> 5922       <NA>      NA       NA #> 5923       <NA>      NA       NA #> 5924          +      NA       NA #> 5925       <NA>      NA       NA #> 5926       <NA>      NA       NA #> 5927       <NA>      NA       NA #> 5928          +      NA       NA #> 5929       <NA>      NA       NA #> 5930       <NA>      NA       NA #> 5931       <NA>      NA       NA #> 5932          +      NA       NA #> 5933       <NA>      NA       NA #> 5934       <NA>      NA       NA #> 5935       <NA>      NA       NA #> 5936          +      NA       NA #> 5937       <NA>      NA       NA #> 5938       <NA>      NA       NA #> 5939       <NA>      NA       NA #> 5940       <NA>      NA       NA #> 5941       <NA>      NA       NA #> 5942          U      NA       NA #> 5943          +      NA       NA #> 5944       <NA>      NA       NA #> 5945          +      NA       NA #> 5946       <NA>      NA       NA #> 5947          I      NA       NA #> 5948          A      NA      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6032       <NA>      NA       NA #> 6033          +      NA       NA #> 6034       <NA>      NA       NA #> 6035          I      NA       NA #> 6036       <NA>      NA       NA #> 6037       <NA>      NA       NA #> 6038       <NA>      NA       NA #> 6039       <NA>      NA       NA #> 6040       <NA>      NA       NA #> 6041       <NA>      NA       NA #> 6042       <NA>      NA       NA #> 6043       <NA>      NA       NA #> 6044          +      NA       NA #> 6045       <NA>      NA       NA #> 6046          I      NA       NA #> 6047       <NA>      NA       NA #> 6048          I      NA       NA #> 6049       <NA>      NA       NA #> 6050       <NA>      NA       NA #> 6051       <NA>      NA       NA #> 6052          U      NA       NA #> 6053       <NA>      NA       NA #> 6054       <NA>      NA       NA #> 6055          +      NA       NA #> 6056       <NA>      NA       NA #> 6057          A      NA       NA #> 6058       <NA>      NA       NA #> 6059       <NA>      NA      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<NA>      NA       NA #> 6116       <NA>      NA       NA #> 6117       <NA>      NA       NA #> 6118          U      NA       NA #> 6119       <NA>      NA       NA #> 6120       <NA>      NA       NA #> 6121          +      NA       NA #> 6122       <NA>      NA       NA #> 6123       <NA>      NA       NA #> 6124       <NA>      NA       NA #> 6125       <NA>      NA       NA #> 6126       <NA>      NA       NA #> 6127       <NA>      NA       NA #> 6128       <NA>      NA       NA #> 6129       <NA>      NA       NA #> 6130       <NA>      NA       NA #> 6131       <NA>      NA       NA #> 6132          +      NA       NA #> 6133       <NA>      NA       NA #> 6134          I      NA       NA #> 6135          A      NA       NA #> 6136       <NA>      NA       NA #> 6137       <NA>      NA       NA #> 6138       <NA>      NA       NA #> 6139       <NA>      NA       NA #> 6140       <NA>      NA       NA #> 6141       <NA>      NA       NA #> 6142          +      NA       NA #> 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<NA>      NA       NA #> 6227       <NA>      NA       NA #> 6228       <NA>      NA       NA #> 6229       <NA>      NA       NA #> 6230       <NA>      NA       NA #> 6231       <NA>      NA       NA #> 6232       <NA>      NA       NA #> 6233       <NA>      NA       NA #> 6234       <NA>      NA       NA #> 6235       <NA>      NA       NA #> 6236       <NA>      NA       NA #> 6237       <NA>      NA       NA #> 6238          A      NA       NA #> 6239       <NA>      NA       NA #> 6240          +      NA       NA #> 6241       <NA>      NA       NA #> 6242       <NA>      NA       NA #> 6243       <NA>      NA       NA #> 6244          +      NA       NA #> 6245       <NA>      NA       NA #> 6246          A      NA       NA #> 6247       <NA>      NA       NA #> 6248       <NA>      NA       NA #> 6249       <NA>      NA       NA #> 6250          +      NA       NA #> 6251       <NA>      NA       NA #> 6252       <NA>      NA       NA #> 6253       <NA>      NA       NA #> 6254          +      NA       NA #> 6255       <NA>      NA       NA #> 6256       <NA>      NA       NA #> 6257       <NA>      NA       NA #> 6258       <NA>      NA       NA #> 6259       <NA>      NA       NA #> 6260          +      NA       NA #> 6261          U      NA       NA #> 6262       <NA>      NA       NA #> 6263       <NA>      NA       NA #> 6264          +      NA       NA #> 6265       <NA>      NA       NA #> 6266       <NA>      NA       NA #> 6267       <NA>      NA       NA #> 6268       <NA>      NA       NA #> 6269       <NA>      NA       NA #> 6270          +      NA       NA #> 6271       <NA>      NA       NA #> 6272       <NA>      NA       NA #> 6273          +      NA       NA #> 6274       <NA>      NA       NA #> 6275       <NA>      NA       NA #> 6276       <NA>      NA       NA #> 6277       <NA>      NA       NA #> 6278       <NA>      NA       NA #> 6279          +      NA       NA #> 6280       <NA>      NA       NA #> 6281       <NA>      NA      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NA       NA #> 6310       <NA>      NA       NA #> 6311       <NA>      NA       NA #> 6312       <NA>      NA       NA #> 6313       <NA>      NA       NA #> 6314       <NA>      NA       NA #> 6315          +      NA       NA #> 6316       <NA>      NA       NA #> 6317       <NA>      NA       NA #> 6318          +      NA       NA #> 6319       <NA>      NA       NA #> 6320       <NA>      NA       NA #> 6321          I      NA       NA #> 6322          A      NA       NA #> 6323       <NA>      NA       NA #> 6324          +      NA       NA #> 6325       <NA>      NA       NA #> 6326       <NA>      NA       NA #> 6327          +      NA       NA #> 6328       <NA>      NA       NA #> 6329          A      NA       NA #> 6330       <NA>      NA       NA #> 6331          A      NA       NA #> 6332          +      NA       NA #> 6333       <NA>      NA       NA #> 6334       <NA>      NA       NA #> 6335       <NA>      NA       NA #> 6336          +      NA       NA #> 6337       <NA>      NA       NA #> 6338       <NA>      NA       NA #> 6339       <NA>      NA       NA #> 6340       <NA>      NA       NA #> 6341       <NA>      NA       NA #> 6342          +      NA       NA #> 6343       <NA>      NA       NA #> 6344       <NA>      NA       NA #> 6345          +      NA       NA #> 6346       <NA>      NA       NA #> 6347       <NA>      NA       NA #> 6348       <NA>      NA       NA #> 6349       <NA>      NA       NA #> 6350       <NA>      NA       NA #> 6351       <NA>      NA       NA #> 6352       <NA>      NA       NA #> 6353          +      NA       NA #> 6354       <NA>      NA       NA #> 6355       <NA>      NA       NA #> 6356       <NA>      NA       NA #> 6357       <NA>      NA       NA #> 6358          +      NA       NA #> 6359          U      NA       NA #> 6360       <NA>      NA       NA #> 6361       <NA>      NA       NA #> 6362          +      NA       NA #> 6363       <NA>      NA       NA #> 6364       <NA>      NA       NA #> 6365       <NA>      NA       NA #> 6366       <NA>      NA       NA #> 6367       <NA>      NA       NA #> 6368          +      NA       NA #> 6369       <NA>      NA       NA #> 6370       <NA>      NA       NA #> 6371          +      NA       NA #> 6372       <NA>      NA       NA #> 6373       <NA>      NA       NA #> 6374       <NA>      NA       NA #> 6375       <NA>      NA       NA #> 6376       <NA>      NA       NA #> 6377          +      NA       NA #> 6378       <NA>      NA       NA #> 6379       <NA>      NA       NA #> 6380          +      NA       NA #> 6381       <NA>      NA       NA #> 6382       <NA>      NA       NA #> 6383       <NA>      NA       NA #> 6384       <NA>      NA       NA #> 6385       <NA>      NA       NA #> 6386          +      NA       NA #> 6387       <NA>      NA       NA #> 6388       <NA>      NA       NA #> 6389          +      NA       NA #> 6390       <NA>      NA       NA #> 6391       <NA>      NA       NA #> 6392       <NA>      NA      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+      NA       NA #> 6449       <NA>      NA       NA #> 6450       <NA>      NA       NA #> 6451          U      NA       NA #> 6452       <NA>      NA       NA #> 6453       <NA>      NA       NA #> 6454          +      NA       NA #> 6455          I      NA       NA #> 6456       <NA>      NA       NA #> 6457       <NA>      NA       NA #> 6458          +      NA       NA #> 6459       <NA>      NA       NA #> 6460          A      NA       NA #> 6461          I      NA       NA #> 6462       <NA>      NA       NA #> 6463       <NA>      NA       NA #> 6464          +      NA       NA #> 6465       <NA>      NA       NA #> 6466       <NA>      NA       NA #> 6467       <NA>      NA       NA #> 6468          +      NA       NA #> 6469       <NA>      NA       NA #> 6470          A      NA       NA #> 6471       <NA>      NA       NA #> 6472       <NA>      NA       NA #> 6473       <NA>      NA       NA #> 6474          +      NA       NA #> 6475       <NA>      NA       NA #> 6476       <NA>      NA       NA #> 6477       <NA>      NA       NA #> 6478          +      NA       NA #> 6479       <NA>      NA       NA #> 6480       <NA>      NA       NA #> 6481       <NA>      NA       NA #> 6482       <NA>      NA       NA #> 6483       <NA>      NA       NA #> 6484          +      NA       NA #> 6485          U      NA       NA #> 6486       <NA>      NA       NA #> 6487       <NA>      NA       NA #> 6488          +      NA       NA #> 6489       <NA>      NA       NA #> 6490       <NA>      NA       NA #> 6491       <NA>      NA       NA #> 6492       <NA>      NA       NA #> 6493       <NA>      NA       NA #> 6494          +      NA       NA #> 6495       <NA>      NA       NA #> 6496       <NA>      NA       NA #> 6497          +      NA       NA #> 6498       <NA>      NA       NA #> 6499       <NA>      NA       NA #> 6500       <NA>      NA       NA #> 6501       <NA>      NA       NA #> 6502          +      NA       NA #> 6503       <NA>      NA       NA #> 6504       <NA>      NA       NA #> 6505       <NA>      NA       NA #> 6506          +      NA       NA #> 6507       <NA>      NA       NA #> 6508       <NA>      NA       NA #> 6509       <NA>      NA       NA #> 6510       <NA>      NA       NA #> 6511       <NA>      NA       NA #> 6512          +      NA       NA #> 6513       <NA>      NA       NA #> 6514       <NA>      NA       NA #> 6515       <NA>      NA       NA #> 6516          +      NA       NA #> 6517       <NA>      NA       NA #> 6518       <NA>      NA       NA #> 6519       <NA>      NA       NA #> 6520       <NA>      NA       NA #> 6521       <NA>      NA       NA #> 6522          +      NA       NA #> 6523       <NA>      NA       NA #> 6524       <NA>      NA       NA #> 6525       <NA>      NA       NA #> 6526          +      NA       NA #> 6527       <NA>      NA       NA #> 6528       <NA>      NA       NA #> 6529       <NA>      NA       NA #> 6530       <NA>      NA       NA #> 6531       <NA>      NA      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<NA>      NA       NA #> 6588          A      NA       NA #> 6589       <NA>      NA       NA #> 6590          A      NA       NA #> 6591       <NA>      NA       NA #> 6592          +      NA       NA #> 6593          I      NA       NA #> 6594       <NA>      NA       NA #> 6595       <NA>      NA       NA #> 6596          +      NA       NA #> 6597       <NA>      NA       NA #> 6598       <NA>      NA       NA #> 6599          A      NA       NA #> 6600       <NA>      NA       NA #> 6601       <NA>      NA       NA #> 6602          +      NA       NA #> 6603       <NA>      NA       NA #> 6604       <NA>      NA       NA #> 6605       <NA>      NA       NA #> 6606       <NA>      NA       NA #> 6607          +      NA       NA #> 6608       <NA>      NA       NA #> 6609       <NA>      NA       NA #> 6610       <NA>      NA       NA #> 6611          +      NA       NA #> 6612       <NA>      NA       NA #> 6613       <NA>      NA       NA #> 6614       <NA>      NA       NA #> 6615       <NA>      NA       NA #> 6616       <NA>      NA       NA #> 6617       <NA>      NA       NA #> 6618       <NA>      NA       NA #> 6619       <NA>      NA       NA #> 6620       <NA>      NA       NA #> 6621          +      NA       NA #> 6622       <NA>      NA       NA #> 6623       <NA>      NA       NA #> 6624       <NA>      NA       NA #> 6625       <NA>      NA       NA #> 6626       <NA>      NA       NA #> 6627       <NA>      NA       NA #> 6628       <NA>      NA       NA #> 6629       <NA>      NA       NA #> 6630       <NA>      NA       NA #> 6631          +      NA       NA #> 6632       <NA>      NA       NA #> 6633          A      NA       NA #> 6634       <NA>      NA       NA #> 6635       <NA>      NA       NA #> 6636       <NA>      NA       NA #> 6637          +      NA       NA #> 6638       <NA>      NA       NA #> 6639       <NA>      NA       NA #> 6640       <NA>      NA       NA #> 6641          +      NA       NA #> 6642       <NA>      NA      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I      NA       NA #> 6699       <NA>      NA       NA #> 6700       <NA>      NA       NA #> 6701          +      NA       NA #> 6702       <NA>      NA       NA #> 6703       <NA>      NA       NA #> 6704       <NA>      NA       NA #> 6705          A      NA       NA #> 6706       <NA>      NA       NA #> 6707       <NA>      NA       NA #> 6708          I      NA       NA #> 6709       <NA>      NA       NA #> 6710       <NA>      NA       NA #> 6711          +      NA       NA #> 6712       <NA>      NA       NA #> 6713       <NA>      NA       NA #> 6714          I      NA       NA #> 6715       <NA>      NA       NA #> 6716       <NA>      NA       NA #> 6717       <NA>      NA       NA #> 6718       <NA>      NA       NA #> 6719       <NA>      NA       NA #> 6720       <NA>      NA       NA #> 6721          +      NA       NA #> 6722       <NA>      NA       NA #> 6723       <NA>      NA       NA #> 6724       <NA>      NA       NA #> 6725          A      NA       NA #> 6726       <NA>      NA       NA #> 6727       <NA>      NA       NA #> 6728       <NA>      NA       NA #> 6729       <NA>      NA       NA #> 6730       <NA>      NA       NA #> 6731          +      NA       NA #> 6732       <NA>      NA       NA #> 6733       <NA>      NA       NA #> 6734       <NA>      NA       NA #> 6735       <NA>      NA       NA #> 6736       <NA>      NA       NA #> 6737       <NA>      NA       NA #> 6738       <NA>      NA       NA #> 6739       <NA>      NA       NA #> 6740       <NA>      NA       NA #> 6741          +      NA       NA #> 6742       <NA>      NA       NA #> 6743       <NA>      NA       NA #> 6744       <NA>      NA       NA #> 6745       <NA>      NA       NA #> 6746       <NA>      NA       NA #> 6747       <NA>      NA       NA #> 6748          U      NA       NA #> 6749       <NA>      NA       NA #> 6750       <NA>      NA       NA #> 6751          +      NA       NA #> 6752       <NA>      NA       NA #> 6753          A      NA       NA #> 6754          I      NA       NA #> 6755       <NA>      NA       NA #> 6756       <NA>      NA       NA #> 6757       <NA>      NA       NA #> 6758       <NA>      NA       NA #> 6759       <NA>      NA       NA #> 6760       <NA>      NA       NA #> 6761          +      NA       NA #> 6762       <NA>      NA       NA #> 6763       <NA>      NA       NA #> 6764       <NA>      NA       NA #> 6765       <NA>      NA       NA #> 6766       <NA>      NA       NA #> 6767       <NA>      NA       NA #> 6768       <NA>      NA       NA #> 6769       <NA>      NA       NA #> 6770       <NA>      NA       NA #> 6771          +      NA       NA #> 6772       <NA>      NA       NA #> 6773       <NA>      NA       NA #> 6774       <NA>      NA       NA #> 6775          A      NA       NA #> 6776       <NA>      NA       NA #> 6777       <NA>      NA       NA #> 6778       <NA>      NA       NA #> 6779       <NA>      NA       NA #> 6780          +      NA       NA #> 6781       <NA>      NA      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NA       NA #> 6810       <NA>      NA       NA #> 6811       <NA>      NA       NA #> 6812          A      NA       NA #> 6813       <NA>      NA       NA #> 6814       <NA>      NA       NA #> 6815       <NA>      NA       NA #> 6816       <NA>      NA       NA #> 6817       <NA>      NA       NA #> 6818          +      NA       NA #> 6819       <NA>      NA       NA #> 6820       <NA>      NA       NA #> 6821       <NA>      NA       NA #> 6822       <NA>      NA       NA #> 6823       <NA>      NA       NA #> 6824       <NA>      NA       NA #> 6825       <NA>      NA       NA #> 6826       <NA>      NA       NA #> 6827       <NA>      NA       NA #> 6828          +      NA       NA #> 6829       <NA>      NA       NA #> 6830       <NA>      NA       NA #> 6831       <NA>      NA       NA #> 6832       <NA>      NA       NA #> 6833       <NA>      NA       NA #> 6834       <NA>      NA       NA #> 6835       <NA>      NA       NA #> 6836       <NA>      NA       NA #> 6837       <NA>      NA       NA #> 6838          +      NA       NA #> 6839       <NA>      NA       NA #> 6840       <NA>      NA       NA #> 6841          I      NA       NA #> 6842       <NA>      NA       NA #> 6843       <NA>      NA       NA #> 6844       <NA>      NA       NA #> 6845       <NA>      NA       NA #> 6846       <NA>      NA       NA #> 6847       <NA>      NA       NA #> 6848          +      NA       NA #> 6849       <NA>      NA       NA #> 6850       <NA>      NA       NA #> 6851       <NA>      NA       NA #> 6852       <NA>      NA       NA #> 6853       <NA>      NA       NA #> 6854       <NA>      NA       NA #> 6855       <NA>      NA       NA #> 6856       <NA>      NA       NA #> 6857       <NA>      NA       NA #> 6858          +      NA       NA #> 6859       <NA>      NA       NA #> 6860          A      NA       NA #> 6861       <NA>      NA       NA #> 6862       <NA>      NA       NA #> 6863       <NA>      NA       NA #> 6864       <NA>      NA       NA #> 6865       <NA>      NA       NA #> 6866       <NA>      NA       NA #> 6867       <NA>      NA       NA #> 6868          +      NA       NA #> 6869       <NA>      NA       NA #> 6870       <NA>      NA       NA #> 6871       <NA>      NA       NA #> 6872       <NA>      NA       NA #> 6873       <NA>      NA       NA #> 6874       <NA>      NA       NA #> 6875          +      NA       NA #> 6876       <NA>      NA       NA #> 6877       <NA>      NA       NA #> 6878       <NA>      NA       NA #> 6879          A      NA       NA #> 6880       <NA>      NA       NA #> 6881       <NA>      NA       NA #> 6882       <NA>      NA       NA #> 6883       <NA>      NA       NA #> 6884       <NA>      NA       NA #> 6885          +      NA       NA #> 6886       <NA>      NA       NA #> 6887       <NA>      NA       NA #> 6888       <NA>      NA       NA #> 6889       <NA>      NA       NA #> 6890       <NA>      NA       NA #> 6891       <NA>      NA       NA #> 6892          I      NA      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NA       NA #> 6921       <NA>      NA       NA #> 6922       <NA>      NA       NA #> 6923       <NA>      NA       NA #> 6924       <NA>      NA       NA #> 6925       <NA>      NA       NA #> 6926       <NA>      NA       NA #> 6927       <NA>      NA       NA #> 6928          +      NA       NA #> 6929       <NA>      NA       NA #> 6930       <NA>      NA       NA #> 6931       <NA>      NA       NA #> 6932          A      NA       NA #> 6933       <NA>      NA       NA #> 6934       <NA>      NA       NA #> 6935       <NA>      NA       NA #> 6936       <NA>      NA       NA #> 6937       <NA>      NA       NA #> 6938          +      NA       NA #> 6939       <NA>      NA       NA #> 6940       <NA>      NA       NA #> 6941       <NA>      NA       NA #> 6942       <NA>      NA       NA #> 6943       <NA>      NA       NA #> 6944       <NA>      NA       NA #> 6945          I      NA       NA #> 6946       <NA>      NA       NA #> 6947       <NA>      NA       NA #> 6948          +      NA       NA #> 6949       <NA>      NA       NA #> 6950       <NA>      NA       NA #> 6951       <NA>      NA       NA #> 6952       <NA>      NA       NA #> 6953       <NA>      NA       NA #> 6954       <NA>      NA       NA #> 6955       <NA>      NA       NA #> 6956       <NA>      NA       NA #> 6957       <NA>      NA       NA #> 6958       <NA>      NA       NA #> 6959       <NA>      NA       NA #> 6960          +      NA       NA #> 6961       <NA>      NA       NA #> 6962          +      NA       NA #> 6963       <NA>      NA       NA #> 6964       <NA>      NA       NA #> 6965       <NA>      NA       NA #> 6966       <NA>      NA       NA #> 6967       <NA>      NA       NA #> 6968       <NA>      NA       NA #> 6969          +      NA       NA #> 6970       <NA>      NA       NA #> 6971       <NA>      NA       NA #> 6972          +      NA       NA #> 6973       <NA>      NA       NA #> 6974       <NA>      NA       NA #> 6975       <NA>      NA       NA #> 6976   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<NA>      NA       NA #> 7310       <NA>      NA       NA #> 7311       <NA>      NA       NA #> 7312       <NA>      NA       NA #> 7313       <NA>      NA       NA #> 7314       <NA>      NA       NA #> 7315       <NA>      NA       NA #> 7316          +      NA       NA #> 7317       <NA>      NA       NA #> 7318          I      NA       NA #> 7319       <NA>      NA       NA #> 7320          I      NA       NA #> 7321       <NA>      NA       NA #> 7322       <NA>      NA       NA #> 7323       <NA>      NA       NA #> 7324          U      NA       NA #> 7325       <NA>      NA       NA #> 7326       <NA>      NA       NA #> 7327          +      NA       NA #> 7328       <NA>      NA       NA #> 7329          I      NA       NA #> 7330          A      NA       NA #> 7331          I      NA       NA #> 7332       <NA>      NA       NA #> 7333       <NA>      NA       NA #> 7334       <NA>      NA       NA #> 7335       <NA>      NA       NA #> 7336       <NA>      NA       NA #> 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NA       NA #> 7393       <NA>      NA       NA #> 7394          U      NA       NA #> 7395       <NA>      NA       NA #> 7396       <NA>      NA       NA #> 7397       <NA>      NA       NA #> 7398       <NA>      NA       NA #> 7399       <NA>      NA       NA #> 7400       <NA>      NA       NA #> 7401          +      NA       NA #> 7402       <NA>      NA       NA #> 7403          U      NA       NA #> 7404       <NA>      NA       NA #> 7405          U      NA       NA #> 7406       <NA>      NA       NA #> 7407       <NA>      NA       NA #> 7408       <NA>      NA       NA #> 7409       <NA>      NA       NA #> 7410       <NA>      NA       NA #> 7411       <NA>      NA       NA #> 7412          +      NA       NA #> 7413       <NA>      NA       NA #> 7414          I      NA       NA #> 7415       <NA>      NA       NA #> 7416       <NA>      NA       NA #> 7417       <NA>      NA       NA #> 7418       <NA>      NA       NA #> 7419       <NA>      NA       NA #> 7420          I      NA       NA #> 7421       <NA>      NA       NA #> 7422       <NA>      NA       NA #> 7423       <NA>      NA       NA #> 7424       <NA>      NA       NA #> 7425       <NA>      NA       NA #> 7426       <NA>      NA       NA #> 7427          +      NA       NA #> 7428       <NA>      NA       NA #> 7429          U      NA       NA #> 7430       <NA>      NA       NA #> 7431       <NA>      NA       NA #> 7432       <NA>      NA       NA #> 7433       <NA>      NA       NA #> 7434       <NA>      NA       NA #> 7435       <NA>      NA       NA #> 7436       <NA>      NA       NA #> 7437       <NA>      NA       NA #> 7438          +      NA       NA #> 7439       <NA>      NA       NA #> 7440       <NA>      NA       NA #> 7441       <NA>      NA       NA #> 7442          I      NA       NA #> 7443       <NA>      NA       NA #> 7444       <NA>      NA       NA #> 7445       <NA>      NA       NA #> 7446       <NA>      NA       NA #> 7447       <NA>      NA       NA #> 7448   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<NA>      NA       NA #> 7560       <NA>      NA       NA #> 7561          +      NA       NA #> 7562       <NA>      NA       NA #> 7563       <NA>      NA       NA #> 7564       <NA>      NA       NA #> 7565          +      NA       NA #> 7566       <NA>      NA       NA #> 7567       <NA>      NA       NA #> 7568       <NA>      NA       NA #> 7569       <NA>      NA       NA #> 7570       <NA>      NA       NA #> 7571          +      NA       NA #> 7572       <NA>      NA       NA #> 7573       <NA>      NA       NA #> 7574       <NA>      NA       NA #> 7575          +      NA       NA #> 7576       <NA>      NA       NA #> 7577       <NA>      NA       NA #> 7578          I      NA       NA #> 7579       <NA>      NA       NA #> 7580       <NA>      NA       NA #> 7581          +      NA       NA #> 7582       <NA>      NA       NA #> 7583       <NA>      NA       NA #> 7584       <NA>      NA       NA #> 7585          +      NA       NA #> 7586       <NA>      NA       NA #> 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<NA>      NA       NA #> 7671          A      NA       NA #> 7672       <NA>      NA       NA #> 7673       <NA>      NA       NA #> 7674       <NA>      NA       NA #> 7675          +      NA       NA #> 7676       <NA>      NA       NA #> 7677       <NA>      NA       NA #> 7678       <NA>      NA       NA #> 7679          +      NA       NA #> 7680       <NA>      NA       NA #> 7681       <NA>      NA       NA #> 7682          I      NA       NA #> 7683       <NA>      NA       NA #> 7684       <NA>      NA       NA #> 7685          +      NA       NA #> 7686       <NA>      NA       NA #> 7687       <NA>      NA       NA #> 7688       <NA>      NA       NA #> 7689          +      NA       NA #> 7690       <NA>      NA       NA #> 7691       <NA>      NA       NA #> 7692          A      NA       NA #> 7693          +      NA       NA #> 7694       <NA>      NA       NA #> 7695       <NA>      NA       NA #> 7696       <NA>      NA       NA #> 7697          +      NA       NA #> 7698       <NA>      NA       NA #> 7699       <NA>      NA       NA #> 7700          I      NA       NA #> 7701       <NA>      NA       NA #> 7702       <NA>      NA       NA #> 7703       <NA>      NA       NA #> 7704       <NA>      NA       NA #> 7705          +      NA       NA #> 7706       <NA>      NA       NA #> 7707       <NA>      NA       NA #> 7708       <NA>      NA       NA #> 7709          A      NA       NA #> 7710       <NA>      NA       NA #> 7711          +      NA       NA #> 7712       <NA>      NA       NA #> 7713       <NA>      NA       NA #> 7714          +      NA       NA #> 7715       <NA>      NA       NA #> 7716       <NA>      NA       NA #> 7717       <NA>      NA       NA #> 7718       <NA>      NA       NA #> 7719       <NA>      NA       NA #> 7720          +      NA       NA #> 7721       <NA>      NA       NA #> 7722       <NA>      NA       NA #> 7723       <NA>      NA       NA #> 7724          +      NA       NA #> 7725       <NA>      NA      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<NA>      NA       NA #> 7782       <NA>      NA       NA #> 7783       <NA>      NA       NA #> 7784       <NA>      NA       NA #> 7785          +      NA       NA #> 7786          U      NA       NA #> 7787       <NA>      NA       NA #> 7788       <NA>      NA       NA #> 7789          +      NA       NA #> 7790       <NA>      NA       NA #> 7791       <NA>      NA       NA #> 7792       <NA>      NA       NA #> 7793       <NA>      NA       NA #> 7794       <NA>      NA       NA #> 7795          +      NA       NA #> 7796       <NA>      NA       NA #> 7797       <NA>      NA       NA #> 7798       <NA>      NA       NA #> 7799          +      NA       NA #> 7800       <NA>      NA       NA #> 7801       <NA>      NA       NA #> 7802       <NA>      NA       NA #> 7803       <NA>      NA       NA #> 7804       <NA>      NA       NA #> 7805          +      NA       NA #> 7806          I      NA       NA #> 7807       <NA>      NA       NA #> 7808       <NA>      NA       NA #> 7809          +      NA       NA #> 7810       <NA>      NA       NA #> 7811       <NA>      NA       NA #> 7812       <NA>      NA       NA #> 7813       <NA>      NA       NA #> 7814       <NA>      NA       NA #> 7815          +      NA       NA #> 7816          I      NA       NA #> 7817       <NA>      NA       NA #> 7818       <NA>      NA       NA #> 7819          +      NA       NA #> 7820       <NA>      NA       NA #> 7821       <NA>      NA       NA #> 7822       <NA>      NA       NA #> 7823       <NA>      NA       NA #> 7824       <NA>      NA       NA #> 7825          +      NA       NA #> 7826          U      NA       NA #> 7827       <NA>      NA       NA #> 7828       <NA>      NA       NA #> 7829          +      NA       NA #> 7830       <NA>      NA       NA #> 7831       <NA>      NA       NA #> 7832          A      NA       NA #> 7833       <NA>      NA       NA #> 7834       <NA>      NA       NA #> 7835          +      NA       NA #> 7836       <NA>      NA      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NA       NA #> 7865          +      NA       NA #> 7866       <NA>      NA       NA #> 7867       <NA>      NA       NA #> 7868       <NA>      NA       NA #> 7869          +      NA       NA #> 7870       <NA>      NA       NA #> 7871       <NA>      NA       NA #> 7872       <NA>      NA       NA #> 7873       <NA>      NA       NA #> 7874       <NA>      NA       NA #> 7875       <NA>      NA       NA #> 7876          +      NA       NA #> 7877       <NA>      NA       NA #> 7878       <NA>      NA       NA #> 7879       <NA>      NA       NA #> 7880       <NA>      NA       NA #> 7881       <NA>      NA       NA #> 7882          +      NA       NA #> 7883       <NA>      NA       NA #> 7884       <NA>      NA       NA #> 7885       <NA>      NA       NA #> 7886          +      NA       NA #> 7887       <NA>      NA       NA #> 7888       <NA>      NA       NA #> 7889       <NA>      NA       NA #> 7890       <NA>      NA       NA #> 7891       <NA>      NA       NA #> 7892       <NA>      NA       NA #> 7893       <NA>      NA       NA #> 7894       <NA>      NA       NA #> 7895       <NA>      NA       NA #> 7896          +      NA       NA #> 7897       <NA>      NA       NA #> 7898       <NA>      NA       NA #> 7899       <NA>      NA       NA #> 7900       <NA>      NA       NA #> 7901          +      NA       NA #> 7902          U      NA       NA #> 7903       <NA>      NA       NA #> 7904       <NA>      NA       NA #> 7905          +      NA       NA #> 7906       <NA>      NA       NA #> 7907       <NA>      NA       NA #> 7908          I      NA       NA #> 7909       <NA>      NA       NA #> 7910       <NA>      NA       NA #> 7911          I      NA       NA #> 7912       <NA>      NA       NA #> 7913       <NA>      NA       NA #> 7914          +      NA       NA #> 7915       <NA>      NA       NA #> 7916       <NA>      NA       NA #> 7917       <NA>      NA       NA #> 7918       <NA>      NA       NA #> 7919       <NA>      NA       NA #> 7920       <NA>      NA       NA #> 7921          I      NA       NA #> 7922       <NA>      NA       NA #> 7923       <NA>      NA       NA #> 7924          +      NA       NA #> 7925       <NA>      NA       NA #> 7926       <NA>      NA       NA #> 7927       <NA>      NA       NA #> 7928       <NA>      NA       NA #> 7929       <NA>      NA       NA #> 7930       <NA>      NA       NA #> 7931          I      NA       NA #> 7932       <NA>      NA       NA #> 7933       <NA>      NA       NA #> 7934          +      NA       NA #> 7935       <NA>      NA       NA #> 7936       <NA>      NA       NA #> 7937       <NA>      NA       NA #> 7938       <NA>      NA       NA #> 7939       <NA>      NA       NA #> 7940       <NA>      NA       NA #> 7941       <NA>      NA       NA #> 7942       <NA>      NA       NA #> 7943       <NA>      NA       NA #> 7944          +      NA       NA #> 7945       <NA>      NA       NA #> 7946       <NA>      NA       NA #> 7947       <NA>      NA      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NA       NA #> 7976       <NA>      NA       NA #> 7977          I      NA       NA #> 7978       <NA>      NA       NA #> 7979       <NA>      NA       NA #> 7980       <NA>      NA       NA #> 7981       <NA>      NA       NA #> 7982       <NA>      NA       NA #> 7983       <NA>      NA       NA #> 7984          +      NA       NA #> 7985       <NA>      NA       NA #> 7986       <NA>      NA       NA #> 7987          I      NA       NA #> 7988       <NA>      NA       NA #> 7989       <NA>      NA       NA #> 7990       <NA>      NA       NA #> 7991          I      NA       NA #> 7992       <NA>      NA       NA #> 7993       <NA>      NA       NA #> 7994          +      NA       NA #> 7995       <NA>      NA       NA #> 7996       <NA>      NA       NA #> 7997          I      NA       NA #> 7998       <NA>      NA       NA #> 7999       <NA>      NA       NA #> 8000       <NA>      NA       NA #> 8001          I      NA       NA #> 8002       <NA>      NA       NA #> 8003       <NA>      NA       NA #> 8004          +      NA       NA #> 8005       <NA>      NA       NA #> 8006       <NA>      NA       NA #> 8007       <NA>      NA       NA #> 8008       <NA>      NA       NA #> 8009       <NA>      NA       NA #> 8010       <NA>      NA       NA #> 8011          I      NA       NA #> 8012       <NA>      NA       NA #> 8013       <NA>      NA       NA #> 8014          +      NA       NA #> 8015       <NA>      NA       NA #> 8016       <NA>      NA       NA #> 8017       <NA>      NA       NA #> 8018       <NA>      NA       NA #> 8019       <NA>      NA       NA #> 8020       <NA>      NA       NA #> 8021          U      NA       NA #> 8022       <NA>      NA       NA #> 8023       <NA>      NA       NA #> 8024          +      NA       NA #> 8025       <NA>      NA       NA #> 8026       <NA>      NA       NA #> 8027       <NA>      NA       NA #> 8028       <NA>      NA       NA #> 8029       <NA>      NA       NA #> 8030       <NA>      NA       NA #> 8031          I      NA       NA #> 8032       <NA>      NA       NA #> 8033       <NA>      NA       NA #> 8034          +      NA       NA #> 8035       <NA>      NA       NA #> 8036       <NA>      NA       NA #> 8037       <NA>      NA       NA #> 8038       <NA>      NA       NA #> 8039       <NA>      NA       NA #> 8040       <NA>      NA       NA #> 8041       <NA>      NA       NA #> 8042       <NA>      NA       NA #> 8043       <NA>      NA       NA #> 8044          +      NA       NA #> 8045       <NA>      NA       NA #> 8046       <NA>      NA       NA #> 8047       <NA>      NA       NA #> 8048       <NA>      NA       NA #> 8049       <NA>      NA       NA #> 8050       <NA>      NA       NA #> 8051       <NA>      NA       NA #> 8052       <NA>      NA       NA #> 8053       <NA>      NA       NA #> 8054          +      NA       NA #> 8055       <NA>      NA       NA #> 8056       <NA>      NA       NA #> 8057          I      NA       NA #> 8058       <NA>      NA      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NA       NA #> 8087       <NA>      NA       NA #> 8088       <NA>      NA       NA #> 8089       <NA>      NA       NA #> 8090       <NA>      NA       NA #> 8091       <NA>      NA       NA #> 8092       <NA>      NA       NA #> 8093       <NA>      NA       NA #> 8094          +      NA       NA #> 8095       <NA>      NA       NA #> 8096       <NA>      NA       NA #> 8097          I      NA       NA #> 8098          A      NA       NA #> 8099       <NA>      NA       NA #> 8100       <NA>      NA       NA #> 8101       <NA>      NA       NA #> 8102          +      NA       NA #> 8103       <NA>      NA       NA #> 8104       <NA>      NA       NA #> 8105          I      NA       NA #> 8106       <NA>      NA       NA #> 8107       <NA>      NA       NA #> 8108       <NA>      NA       NA #> 8109       <NA>      NA       NA #> 8110       <NA>      NA       NA #> 8111       <NA>      NA       NA #> 8112          +      NA       NA #> 8113       <NA>      NA       NA #> 8114       <NA>      NA       NA #> 8115          I      NA       NA #> 8116       <NA>      NA       NA #> 8117       <NA>      NA       NA #> 8118       <NA>      NA       NA #> 8119       <NA>      NA       NA #> 8120       <NA>      NA       NA #> 8121       <NA>      NA       NA #> 8122          +      NA       NA #> 8123       <NA>      NA       NA #> 8124       <NA>      NA       NA #> 8125       <NA>      NA       NA #> 8126       <NA>      NA       NA #> 8127       <NA>      NA       NA #> 8128       <NA>      NA       NA #> 8129          I      NA       NA #> 8130       <NA>      NA       NA #> 8131       <NA>      NA       NA #> 8132          +      NA       NA #> 8133       <NA>      NA       NA #> 8134       <NA>      NA       NA #> 8135          I      NA       NA #> 8136       <NA>      NA       NA #> 8137       <NA>      NA       NA #> 8138       <NA>      NA       NA #> 8139          I      NA       NA #> 8140       <NA>      NA       NA #> 8141          I      NA       NA #> 8142          +      NA       NA #> 8143       <NA>      NA       NA #> 8144          A      NA       NA #> 8145       <NA>      NA       NA #> 8146       <NA>      NA       NA #> 8147       <NA>      NA       NA #> 8148       <NA>      NA       NA #> 8149          U      NA       NA #> 8150       <NA>      NA       NA #> 8151          +      NA       NA #> 8152       <NA>      NA       NA #> 8153       <NA>      NA       NA #> 8154       <NA>      NA       NA #> 8155       <NA>      NA       NA #> 8156       <NA>      NA       NA #> 8157       <NA>      NA       NA #> 8158          U      NA       NA #> 8159       <NA>      NA       NA #> 8160       <NA>      NA       NA #> 8161          +      NA       NA #> 8162       <NA>      NA       NA #> 8163       <NA>      NA       NA #> 8164       <NA>      NA       NA #> 8165       <NA>      NA       NA #> 8166       <NA>      NA       NA #> 8167       <NA>      NA       NA #> 8168       <NA>      NA       NA #> 8169       <NA>      NA      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NA       NA #> 8198          I      NA       NA #> 8199       <NA>      NA       NA #> 8200       <NA>      NA       NA #> 8201          +      NA       NA #> 8202       <NA>      NA       NA #> 8203       <NA>      NA       NA #> 8204          I      NA       NA #> 8205          A      NA       NA #> 8206       <NA>      NA       NA #> 8207       <NA>      NA       NA #> 8208       <NA>      NA       NA #> 8209       <NA>      NA       NA #> 8210       <NA>      NA       NA #> 8211          +      NA       NA #> 8212       <NA>      NA       NA #> 8213       <NA>      NA       NA #> 8214          I      NA       NA #> 8215          A      NA       NA #> 8216       <NA>      NA       NA #> 8217          +      NA       NA #> 8218       <NA>      NA       NA #> 8219       <NA>      NA       NA #> 8220       <NA>      NA       NA #> 8221          +      NA       NA #> 8222       <NA>      NA       NA #> 8223       <NA>      NA       NA #> 8224       <NA>      NA       NA #> 8225       <NA>      NA       NA #> 8226       <NA>      NA       NA #> 8227       <NA>      NA       NA #> 8228       <NA>      NA       NA #> 8229       <NA>      NA       NA #> 8230       <NA>      NA       NA #> 8231          +      NA       NA #> 8232       <NA>      NA       NA #> 8233       <NA>      NA       NA #> 8234          I      NA       NA #> 8235          I      NA       NA #> 8236       <NA>      NA       NA #> 8237       <NA>      NA       NA #> 8238          I      NA       NA #> 8239       <NA>      NA       NA #> 8240       <NA>      NA       NA #> 8241          +      NA       NA #> 8242       <NA>      NA       NA #> 8243          I      NA       NA #> 8244          I      NA       NA #> 8245          I      NA       NA #> 8246       <NA>      NA       NA #> 8247       <NA>      NA       NA #> 8248          U      NA       NA #> 8249       <NA>      NA       NA #> 8250       <NA>      NA       NA #> 8251          +      NA       NA #> 8252       <NA>      NA       NA #> 8253       <NA>      NA       NA #> 8254       <NA>      NA       NA #> 8255       <NA>      NA       NA #> 8256       <NA>      NA       NA #> 8257       <NA>      NA       NA #> 8258          I      NA       NA #> 8259       <NA>      NA       NA #> 8260          I      NA       NA #> 8261          +      NA       NA #> 8262       <NA>      NA       NA #> 8263       <NA>      NA       NA #> 8264       <NA>      NA       NA #> 8265          I      NA       NA #> 8266       <NA>      NA       NA #> 8267       <NA>      NA       NA #> 8268          I      NA       NA #> 8269       <NA>      NA       NA #> 8270       <NA>      NA       NA #> 8271          +      NA       NA #> 8272       <NA>      NA       NA #> 8273          I      NA       NA #> 8274       <NA>      NA       NA #> 8275          A      NA       NA #> 8276       <NA>      NA       NA #> 8277       <NA>      NA       NA #> 8278          I      NA       NA #> 8279       <NA>      NA       NA #> 8280       <NA>      NA      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NA       NA #> 8309          +      NA       NA #> 8310       <NA>      NA       NA #> 8311       <NA>      NA       NA #> 8312          I      NA       NA #> 8313       <NA>      NA       NA #> 8314       <NA>      NA       NA #> 8315       <NA>      NA       NA #> 8316       <NA>      NA       NA #> 8317       <NA>      NA       NA #> 8318       <NA>      NA       NA #> 8319          +      NA       NA #> 8320       <NA>      NA       NA #> 8321       <NA>      NA       NA #> 8322       <NA>      NA       NA #> 8323       <NA>      NA       NA #> 8324       <NA>      NA       NA #> 8325       <NA>      NA       NA #> 8326       <NA>      NA       NA #> 8327       <NA>      NA       NA #> 8328       <NA>      NA       NA #> 8329          +      NA       NA #> 8330       <NA>      NA       NA #> 8331       <NA>      NA       NA #> 8332       <NA>      NA       NA #> 8333       <NA>      NA       NA #> 8334       <NA>      NA       NA #> 8335       <NA>      NA       NA #> 8336       <NA>      NA       NA #> 8337       <NA>      NA       NA #> 8338       <NA>      NA       NA #> 8339          +      NA       NA #> 8340       <NA>      NA       NA #> 8341       <NA>      NA       NA #> 8342       <NA>      NA       NA #> 8343       <NA>      NA       NA #> 8344       <NA>      NA       NA #> 8345       <NA>      NA       NA #> 8346       <NA>      NA       NA #> 8347       <NA>      NA       NA #> 8348       <NA>      NA       NA #> 8349          +      NA       NA #> 8350       <NA>      NA       NA #> 8351       <NA>      NA       NA #> 8352       <NA>      NA       NA #> 8353       <NA>      NA       NA #> 8354       <NA>      NA       NA #> 8355       <NA>      NA       NA #> 8356          I      NA       NA #> 8357       <NA>      NA       NA #> 8358       <NA>      NA       NA #> 8359          +      NA       NA #> 8360       <NA>      NA       NA #> 8361       <NA>      NA       NA #> 8362       <NA>      NA       NA #> 8363       <NA>      NA       NA #> 8364       <NA>      NA       NA #> 8365       <NA>      NA       NA #> 8366       <NA>      NA       NA #> 8367       <NA>      NA       NA #> 8368       <NA>      NA       NA #> 8369       <NA>      NA       NA #> 8370       <NA>      NA       NA #> 8371       <NA>      NA       NA #> 8372       <NA>      NA       NA #> 8373       <NA>      NA       NA #> 8374       <NA>      NA       NA #> 8375       <NA>      NA       NA #> 8376       <NA>      NA       NA #> 8377       <NA>      NA       NA #> 8378       <NA>      NA       NA #> 8379       <NA>      NA       NA #> 8380       <NA>      NA       NA #> 8381       <NA>      NA       NA #> 8382       <NA>      NA       NA #> 8383       <NA>      NA       NA #> 8384       <NA>      NA       NA #> 8385       <NA>      NA       NA #> 8386       <NA>      NA       NA #> 8387       <NA>      NA       NA #> 8388       <NA>      NA       NA #> 8389       <NA>      NA       NA #> 8390       <NA>      NA       NA #> 8391       <NA>      NA      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NA       NA #> 8420       <NA>      NA       NA #> 8421       <NA>      NA       NA #> 8422       <NA>      NA       NA #> 8423       <NA>      NA       NA #> 8424       <NA>      NA       NA #> 8425          I      NA       NA #> 8426       <NA>      NA       NA #> 8427       <NA>      NA       NA #> 8428       <NA>      NA       NA #> 8429       <NA>      NA       NA #> 8430       <NA>      NA       NA #> 8431       <NA>      NA       NA #> 8432          +      NA       NA #> 8433          I      NA       NA #> 8434       <NA>      NA       NA #> 8435       <NA>      NA       NA #> 8436       <NA>      NA       NA #> 8437       <NA>      NA       NA #> 8438       <NA>      NA       NA #> 8439       <NA>      NA       NA #> 8440       <NA>      NA       NA #> 8441       <NA>      NA       NA #> 8442          +      NA       NA #> 8443       <NA>      NA       NA #> 8444       <NA>      NA       NA #> 8445       <NA>      NA       NA #> 8446       <NA>      NA       NA #> 8447       <NA>      NA       NA #> 8448          +      NA       NA #> 8449          U      NA       NA #> 8450       <NA>      NA       NA #> 8451       <NA>      NA       NA #> 8452       <NA>      NA       NA #> 8453       <NA>      NA       NA #> 8454       <NA>      NA       NA #> 8455       <NA>      NA       NA #> 8456       <NA>      NA       NA #> 8457       <NA>      NA       NA #> 8458          +      NA       NA #> 8459       <NA>      NA       NA #> 8460          I      NA       NA #> 8461       <NA>      NA       NA #> 8462       <NA>      NA       NA #> 8463          +      NA       NA #> 8464          I      NA       NA #> 8465       <NA>      NA       NA #> 8466       <NA>      NA       NA #> 8467       <NA>      NA       NA #> 8468       <NA>      NA       NA #> 8469       <NA>      NA       NA #> 8470       <NA>      NA       NA #> 8471       <NA>      NA       NA #> 8472       <NA>      NA       NA #> 8473          +      NA       NA #> 8474       <NA>      NA       NA #> 8475       <NA>      NA       NA #> 8476       <NA>      NA       NA #> 8477          +      NA       NA #> 8478       <NA>      NA       NA #> 8479       <NA>      NA       NA #> 8480       <NA>      NA       NA #> 8481          +      NA       NA #> 8482       <NA>      NA       NA #> 8483       <NA>      NA       NA #> 8484       <NA>      NA       NA #> 8485       <NA>      NA       NA #> 8486       <NA>      NA       NA #> 8487       <NA>      NA       NA #> 8488       <NA>      NA       NA #> 8489       <NA>      NA       NA #> 8490       <NA>      NA       NA #> 8491       <NA>      NA       NA #> 8492          +      NA       NA #> 8493       <NA>      NA       NA #> 8494       <NA>      NA       NA #> 8495       <NA>      NA       NA #> 8496          +      NA       NA #> 8497       <NA>      NA       NA #> 8498       <NA>      NA       NA #> 8499       <NA>      NA       NA #> 8500          +      NA       NA #> 8501       <NA>      NA       NA #> 8502       <NA>      NA      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NA       NA #> 8531       <NA>      NA       NA #> 8532       <NA>      NA       NA #> 8533       <NA>      NA       NA #> 8534          +      NA       NA #> 8535       <NA>      NA       NA #> 8536       <NA>      NA       NA #> 8537       <NA>      NA       NA #> 8538          +      NA       NA #> 8539       <NA>      NA       NA #> 8540       <NA>      NA       NA #> 8541       <NA>      NA       NA #> 8542       <NA>      NA       NA #> 8543          +      NA       NA #> 8544          I      NA       NA #> 8545       <NA>      NA       NA #> 8546       <NA>      NA       NA #> 8547       <NA>      NA       NA #> 8548       <NA>      NA       NA #> 8549       <NA>      NA       NA #> 8550       <NA>      NA       NA #> 8551          +      NA       NA #> 8552       <NA>      NA       NA #> 8553       <NA>      NA       NA #> 8554       <NA>      NA       NA #> 8555       <NA>      NA       NA #> 8556       <NA>      NA       NA #> 8557       <NA>      NA       NA #> 8558          +      NA       NA #> 8559          I      NA       NA #> 8560       <NA>      NA       NA #> 8561       <NA>      NA       NA #> 8562       <NA>      NA       NA #> 8563       <NA>      NA       NA #> 8564       <NA>      NA       NA #> 8565       <NA>      NA       NA #> 8566       <NA>      NA       NA #> 8567       <NA>      NA       NA #> 8568          +      NA       NA #> 8569       <NA>      NA       NA #> 8570       <NA>      NA       NA #> 8571       <NA>      NA       NA #> 8572          +      NA       NA #> 8573       <NA>      NA       NA #> 8574       <NA>      NA       NA #> 8575       <NA>      NA       NA #> 8576       <NA>      NA       NA #> 8577          +      NA       NA #> 8578          U      NA       NA #> 8579       <NA>      NA       NA #> 8580       <NA>      NA       NA #> 8581       <NA>      NA       NA #> 8582       <NA>      NA       NA #> 8583       <NA>      NA       NA #> 8584       <NA>      NA       NA #> 8585       <NA>      NA       NA #> 8586       <NA>      NA       NA #> 8587          +      NA       NA #> 8588       <NA>      NA       NA #> 8589       <NA>      NA       NA #> 8590       <NA>      NA       NA #> 8591          +      NA       NA #> 8592       <NA>      NA       NA #> 8593       <NA>      NA       NA #> 8594       <NA>      NA       NA #> 8595          +      NA       NA #> 8596          U      NA       NA #> 8597       <NA>      NA       NA #> 8598       <NA>      NA       NA #> 8599       <NA>      NA       NA #> 8600       <NA>      NA       NA #> 8601       <NA>      NA       NA #> 8602       <NA>      NA       NA #> 8603       <NA>      NA       NA #> 8604       <NA>      NA       NA #> 8605          +      NA       NA #> 8606       <NA>      NA       NA #> 8607       <NA>      NA       NA #> 8608          U      NA       NA #> 8609       <NA>      NA       NA #> 8610       <NA>      NA       NA #> 8611          +      NA       NA #> 8612       <NA>      NA       NA #> 8613       <NA>      NA       NA #> 8614       <NA>      NA       NA #> 8615       <NA>      NA       NA #> 8616       <NA>      NA       NA #> 8617       <NA>      NA       NA #> 8618       <NA>      NA       NA #> 8619          +      NA       NA #> 8620          U      NA       NA #> 8621       <NA>      NA       NA #> 8622       <NA>      NA       NA #> 8623       <NA>      NA       NA #> 8624       <NA>      NA       NA #> 8625       <NA>      NA       NA #> 8626       <NA>      NA       NA #> 8627       <NA>      NA       NA #> 8628       <NA>      NA       NA #> 8629          +      NA       NA #> 8630       <NA>      NA       NA #> 8631       <NA>      NA       NA #> 8632       <NA>      NA       NA #> 8633          +      NA       NA #> 8634       <NA>      NA       NA #> 8635       <NA>      NA       NA #> 8636       <NA>      NA       NA #> 8637          +      NA       NA #> 8638          U      NA       NA #> 8639       <NA>      NA       NA #> 8640       <NA>      NA       NA #> 8641       <NA>      NA      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I      NA       NA #> 8698          A      NA       NA #> 8699       <NA>      NA       NA #> 8700       <NA>      NA       NA #> 8701       <NA>      NA       NA #> 8702       <NA>      NA       NA #> 8703       <NA>      NA       NA #> 8704       <NA>      NA       NA #> 8705       <NA>      NA       NA #> 8706          +      NA       NA #> 8707       <NA>      NA       NA #> 8708       <NA>      NA       NA #> 8709       <NA>      NA       NA #> 8710       <NA>      NA       NA #> 8711       <NA>      NA       NA #> 8712       <NA>      NA       NA #> 8713       <NA>      NA       NA #> 8714       <NA>      NA       NA #> 8715       <NA>      NA       NA #> 8716       <NA>      NA       NA #> 8717          +      NA       NA #> 8718       <NA>      NA       NA #> 8719          I      NA       NA #> 8720          A      NA       NA #> 8721       <NA>      NA       NA #> 8722       <NA>      NA       NA #> 8723       <NA>      NA       NA #> 8724       <NA>      NA       NA #> 8725       <NA>      NA       NA #> 8726       <NA>      NA       NA #> 8727          +      NA       NA #> 8728       <NA>      NA       NA #> 8729          +      NA       NA #> 8730       <NA>      NA       NA #> 8731          I      NA       NA #> 8732          A      NA       NA #> 8733       <NA>      NA       NA #> 8734       <NA>      NA       NA #> 8735       <NA>      NA       NA #> 8736       <NA>      NA       NA #> 8737       <NA>      NA       NA #> 8738       <NA>      NA       NA #> 8739          +      NA       NA #> 8740       <NA>      NA       NA #> 8741          +      NA       NA #> 8742       <NA>      NA       NA #> 8743          I      NA       NA #> 8744       <NA>      NA       NA #> 8745       <NA>      NA       NA #> 8746          A      NA       NA #> 8747       <NA>      NA       NA #> 8748       <NA>      NA       NA #> 8749       <NA>      NA       NA #> 8750       <NA>      NA       NA #> 8751          +      NA       NA #> 8752       <NA>      NA       NA #> 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data frame object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert references csv to bib — anlz_refs","text":"data frame references formatted bib entries","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert references csv to bib — anlz_refs","text":"","code":"# input and format path <- 'https://raw.githubusercontent.com/tbep-tech/tbep-refs/master/tbep-refs.csv' bibs <- anlz_refs(path)  if (FALSE) { # \\dontrun{ # save output  writeLines(bibs, 'formatted.bib') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":null,"dir":"Reference","previous_headings":"","what":"Add contaminant totals to sediment data — anlz_sedimentaddtot","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"Add contaminant totals sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   param = NULL,   pelave = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" param optional character string parameter filter results pelave logical indicating output used anlz_sedimentpel","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"data.frame object similar input, filtered arguments contaminant totals added. Replicate samples also removed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"function adds totals sedimentdata input total PCBs, total DDT, total LMW PAH, total HMW PAH, total PAH.  Appropriate TEL/PEL values totals also added.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(sedimentdata) #> # A tibble: 62,667 × 24 #>    ProgramId ProgramName   FundingProject    yr AreaAbbr StationID StationNumber #>        <int> <chr>         <chr>          <int> <chr>        <int> <chr>         #>  1         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  2         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  3         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  4         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  5         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  6         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  7         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  8         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #>  9         4 Benthic Moni… TBEP            1993 HB            2463 93HB15        #> 10         4 Benthic Moni… TBEP            1993 HB            2464 93HB16        #> # ℹ 62,657 more rows #> # ℹ 17 more variables: Latitude <dbl>, Longitude <dbl>, Replicate <chr>, #> #   SedResultsType <chr>, Parameter <chr>, ValueAdjusted <dbl>, Units <chr>, #> #   Qualifier <chr>, MDLnum <dbl>, PQLnum <dbl>, TEL <dbl>, PEL <dbl>, #> #   BetweenTELPEL <chr>, ExceedsPEL <chr>, PELRatio <dbl>, #> #   PreparationDate <chr>, AnalysisTimeMerge <chr>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"data.frame object average sediment concentrations selected parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(sedimentdata, param = 'Arsenic') #> # A tibble: 7 × 8 #>   AreaAbbr   TEL   PEL Units   ave   lov   hiv grandave #>   <fct>    <dbl> <dbl> <chr> <dbl> <dbl> <dbl>    <dbl> #> 1 BCB       7.24  41.6 mg/kg  2.64 2.34   2.94     2.57 #> 2 HB        7.24  41.6 mg/kg  2.93 0.665  5.20     2.57 #> 3 LTB       7.24  41.6 mg/kg  2.93 2.47   3.40     2.57 #> 4 MR        7.24  41.6 mg/kg  1.66 1.37   1.95     2.57 #> 5 MTB       7.24  41.6 mg/kg  2.17 1.86   2.48     2.57 #> 6 OTB       7.24  41.6 mg/kg  3.24 0.707  5.78     2.57 #> 7 TCB       7.24  41.6 mg/kg  2.40 1.92   2.88     2.57"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Get sediment PEL ratios stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"data.frame object average PEL ratios grades station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Average PEL ratios contaminants graded F benthic stations monitored Tampa Bay estimated. PEL measure likely contaminant toxic effect invertebrates inhabit sediment. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station grade applies average. grade breaks PEL ratio 0.00756, 0.02052, 0.08567, 0.28026, lower grades assigned higher breaks.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(sedimentdata) #> # A tibble: 2,233 × 7 #>       yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #>    <int> <chr>    <chr>            <dbl>     <dbl>    <dbl> <fct> #>  1  1993 HB       93HB15            27.8     -82.4  0.0157  B     #>  2  1993 HB       93HB16            27.8     -82.5  0.0261  C     #>  3  1993 HB       93HB23            27.9     -82.4  0.0174  B     #>  4  1993 LTB      93LTB24           27.7     -82.6  0.0124  B     #>  5  1993 LTB      93LTB25           27.6     -82.6  0.0189  B     #>  6  1993 LTB      93LTB26           27.6     -82.7  0.00997 B     #>  7  1993 LTB      93LTB27           27.6     -82.7  0.0125  B     #>  8  1993 LTB      93LTB28           27.6     -82.7  0.0887  D     #>  9  1993 LTB      93LTB29           27.6     -82.6  0.0350  C     #> 10  1993 LTB      93LTB30           27.6     -82.6  0.0496  C     #> # ℹ 2,223 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"data.frame average average PEL ratios bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(sedimentdata) #> # A tibble: 7 × 5 #>   AreaAbbr    ave    lov    hiv grandave #>   <fct>     <dbl>  <dbl>  <dbl>    <dbl> #> 1 BCB      0.0535 0.0445 0.0625   0.0522 #> 2 HB       0.118  0.0663 0.169    0.0522 #> 3 LTB      0.0281 0.0247 0.0315   0.0522 #> 4 MR       0.0446 0.0375 0.0516   0.0522 #> 5 MTB      0.0374 0.0327 0.0421   0.0522 #> 6 OTB      0.0506 0.0371 0.0642   0.0522 #> 7 TCB      0.0337 0.0265 0.0409   0.0522"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Get annual medians Tampa Bay Benthic Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"anlz_tbbimed(   tbbiscr,   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"),   rev = FALSE,   yrrng = c(1993, 2022) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" rev logical factor levels bay segments reversed yrrng numeric indicating year ranges evaluate","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"data frame annual medians bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\"). sampling funded TBEP part routine EPC benthic monitoring program included final categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) anlz_tbbimed(tbbiscr) #> # A tibble: 268 × 6 #> # Rowwise:  #>    bay_segment    yr Degraded Healthy Intermediate TBBICat #>    <fct>       <dbl>    <dbl>   <dbl>        <dbl> <fct>   #>  1 All          1993    0.3     0.244        0.456 Poor    #>  2 All          1994    0.449   0.180        0.371 Poor    #>  3 All          1995    0.133   0.508        0.359 Fair    #>  4 All          1996    0.138   0.569        0.292 Fair    #>  5 All          1997    0.157   0.421        0.421 Fair    #>  6 All          1998    0.231   0.316        0.453 Poor    #>  7 All          1999    0.107   0.377        0.516 Fair    #>  8 All          2000    0.163   0.407        0.430 Fair    #>  9 All          2001    0.231   0.321        0.449 Poor    #> 10 All          2002    0.2     0.425        0.375 Poor    #> # ℹ 258 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"Get Tampa Bay Benthic Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"benthicdata nested tibble formatted read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"single data frame TBBI scores site.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"function calculates scores TBBI based station, taxa, field sample data.  total TBBI scores returned TBBI TBBICat, latter categorical description scores.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata) #> # A tibble: 4,787 × 15 #>    StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName        #>        <int> <chr>         <chr>    <chr>              <int> <chr>              #>  1       448 02BBs301      MTB      Apollo Beach           4 Benthic Monitoring #>  2       449 02BBs305      MTB      Apollo Beach           4 Benthic Monitoring #>  3       450 02BBs307      MTB      Apollo Beach           4 Benthic Monitoring #>  4       451 02BBs364      MTB      Apollo Beach           4 Benthic Monitoring #>  5       452 02BBs369      MTB      Apollo Beach           4 Benthic Monitoring #>  6       453 02BBs395      MTB      Apollo Beach           4 Benthic Monitoring #>  7       454 02BBs397      MTB      Apollo Beach           4 Benthic Monitoring #>  8       455 02BBs398      MTB      Apollo Beach           4 Benthic Monitoring #>  9       456 02BBs401      MTB      Apollo Beach           4 Benthic Monitoring #> 10       457 02BBs402      MTB      Apollo Beach           4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude <dbl>, Longitude <dbl>, date <date>, yr <dbl>, #> #   TotalAbundance <dbl>, SpeciesRichness <dbl>, TBBI <dbl>, TBBICat <chr>, #> #   Salinity <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"Get annual averages Tampa Bay Nekton Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"anlz_tbniave(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   rev = FALSE,   perc = c(32, 46) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" rev logical factor levels bay segments reversed perc numeric values indicating break points score categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) anlz_tbniave(tbniscr) #> # A tibble: 104 × 5 #>    bay_segment  Year Segment_TBNI Action          outcome #>    <fct>       <dbl>        <dbl> <fct>           <chr>   #>  1 HB           1998           47 Stay the Course green   #>  2 HB           1999           47 Stay the Course green   #>  3 HB           2000           44 Caution         yellow  #>  4 HB           2001           44 Caution         yellow  #>  5 HB           2002           39 Caution         yellow  #>  6 HB           2003           41 Caution         yellow  #>  7 HB           2004           41 Caution         yellow  #>  8 HB           2005           32 Caution         yellow  #>  9 HB           2006           41 Caution         yellow  #> 10 HB           2007           42 Caution         yellow  #> # ℹ 94 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":null,"dir":"Reference","previous_headings":"","what":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"Get raw metrics Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"fimdata data.frame formatted read_importfim logical indicating TBNI metrics returned (default), otherwise calcualted","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"data frame raw metrics wide fomat.  = TRUE, metrics returned, otherwise NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"raw metrics returned addition required TBNI.  row shows metric values station, year, month fish catch data available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata) #> # A tibble: 7,766 × 10 #>    Reference  Year Month Season bay_segment NumTaxa Shannon TaxaSelect NumGuilds #>    <chr>     <dbl> <dbl> <chr>  <chr>         <dbl>   <dbl>      <dbl>     <dbl> #>  1 TBM19980…  1998     1 Winter OTB               2   0.362          0         2 #>  2 TBM19980…  1998     1 Winter OTB               1   0              1         1 #>  3 TBM19980…  1998     1 Winter OTB               0   0              0         0 #>  4 TBM19980…  1998     1 Winter OTB               2   0.693          0         1 #>  5 TBM19980…  1998     1 Winter MTB               4   1.16           1         2 #>  6 TBM19980…  1998     1 Winter MTB               2   0.500          1         1 #>  7 TBM19980…  1998     1 Winter MTB               5   0.426          2         3 #>  8 TBM19980…  1998     1 Winter OTB               0   0              0         0 #>  9 TBM19980…  1998     1 Winter HB                4   0.794          1         4 #> 10 TBM19980…  1998     1 Winter HB                1   0              0         1 #> # ℹ 7,756 more rows #> # ℹ 1 more variable: BenthicTaxa <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"Get Tampa Bay Nekton Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata, raw = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"fimdata data.frame formatted read_importfim raw logical indicating raw metric values also returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"data frame metrics TBNI scores wide format.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"function calculates raw scored metrics TBNI, including NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon.  total TBNI score returned TBNI_Score.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata) #> # A tibble: 7,766 × 16 #>    Reference      Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #>    <chr>         <dbl> <dbl> <chr>  <chr>            <dbl>   <dbl>        <dbl> #>  1 TBM1998010906  1998     1 Winter OTB                 18       2            2 #>  2 TBM1998010910  1998     1 Winter OTB                 14       1            1 #>  3 TBM1998010912  1998     1 Winter OTB                  0       0            0 #>  4 TBM1998010914  1998     1 Winter OTB                 20       2            2 #>  5 TBM1998010915  1998     1 Winter MTB                 46       4            4 #>  6 TBM1998010917  1998     1 Winter MTB                 24       2            2 #>  7 TBM1998010920  1998     1 Winter MTB                 50       5            5 #>  8 TBM1998010922  1998     1 Winter OTB                  0       0            0 #>  9 TBM1998010926  1998     1 Winter HB                  48       4            4 #> 10 TBM1998010928  1998     1 Winter HB                   8       1            1 #> # ℹ 7,756 more rows #> # ℹ 8 more variables: BenthicTaxa <dbl>, ScoreBenthicTaxa <dbl>, #> #   TaxaSelect <dbl>, ScoreTaxaSelect <dbl>, NumGuilds <dbl>, #> #   ScoreNumGuilds <dbl>, Shannon <dbl>, ScoreShannon <dbl>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate tidal creek report card scores — anlz_tdlcrk","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"Estimate tidal creek report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, tidtrgs = NULL, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters data base data.frame tidtrgs optional data.frame tidal creek nitrogen targets, defaults tidaltargets yr numeric reference year evaluate, scores based planning period beginning ten years prior date","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"data.frame report card scores creek, prioritize, investigate, caution, monitor, data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) #> # A tibble: 615 × 10 #>       id wbid  JEI   name     class monitor caution investigate prioritize score #>    <int> <chr> <chr> <chr>    <chr>   <dbl>   <dbl>       <dbl>      <dbl> <chr> #>  1     1 1983B CC01  Rock Cr… 2          NA      NA          NA         NA No D… #>  2     2 2052  CC01  Rock Cr… 3M         10      NA          NA         NA Moni… #>  3     3 1983B CC02  Oyster … 2          NA      NA          NA         NA No D… #>  4     4 2067  CC02  Oyster … 3M         10      NA          NA         NA Moni… #>  5     5 1983B CC03  Buck Cr… 2          NA      NA          NA         NA No D… #>  6     6 2068  CC03  Buck Cr… 3M          9       1          NA         NA Moni… #>  7     7 2078A CC04  Buck Cr… 2          NA      NA           1         NA Inve… #>  8     8 2078A CC05  Coral C… 2          NA      NA          NA         NA No D… #>  9     9 2078B CC05  Coral C… 2           4       1          NA         NA Moni… #> 10    10 2065C CC06  Catfish… 2          NA      NA          NA         NA No D… #> # ℹ 605 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Estimate tidal creek water quality indicators support report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters rule data base data.frame yr numeric reference year evaluate, scores based planning period beginning ten years prior date radar logical indicating output show_tdlcrkradar, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"data.frame indicator values tidal creek","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Annual geometric means additional water quality data available wbid, JEI combination.  Florida trophic state index values also estimated data available. Nitrogen ratios estimated JEIs cover source (upstream, freshwater) tidal (downstream) WBIDs, defined ratio concentrations two (.e., ratios > 1 mean source higher concentrations).  Nitrogen ratios given year reflect ratio median nitrogen concentrations measured source tidal segment day.  Note ratio one can obtained source tidal segments minimum detection. Indicators years 10% observations exceed saturation criteria also estimated.  do_bnml do_prop columns show 1 0 given year indicate ten percent observations percent saturation 42.  first column based binomial probability exceedance takes account number observations year second column based simple proportional estimate raw data. radar = TRUE, output returned format use show_tdlcrkradar  Specifically, results calculated percentage years indicator exceeds relevant threshold.  applies marine WBIDs tidal creeks (Florida DEP class 2, 3M).  Six indicators returned percentage exceedances based total nitrogen (tn_ind) greater 1.1 mg/L, chlorophyll (chla_ind) greater 11 ug/L, trophic state index (tsi_ind) greater 55 (100), nitrate/nitrite ratio marine upstream segments (nox_ind) greater one, chlorophyll total nitrogen ratios > 15, percentage years ten percent observations percent saturation 42.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"dat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) head(dat) #>   id       name  JEI wbid class year    CHLAC    COLOR COND       DO    DOSAT #> 1  2 Rock Creek CC01 2052    3M 2014 2.380249 14.69473   NA 3.308289 60.31523 #> 2  2 Rock Creek CC01 2052    3M 2015 2.647817 21.91113   NA 4.034172 55.41609 #> 3  2 Rock Creek CC01 2052    3M 2016 2.265462 19.13080   NA 3.980251 55.96637 #> 4  2 Rock Creek CC01 2052    3M 2017 2.851726 15.39576   NA 4.157777 60.18017 #> 5  2 Rock Creek CC01 2052    3M 2018 1.934899 11.65500   NA 4.219790 63.32630 #> 6  2 Rock Creek CC01 2052    3M 2019 2.071003  7.21425   NA 3.015847 44.90322 #>          NO23 ORGN    SALIN       TKN        TN         TP TSS     TURB #> 1 0.007575792   NA 26.63714 0.6161702 0.6228782 0.06938150  NA 2.044623 #> 2 0.009361504   NA 19.10494 0.6465161 0.5678241 0.07602770  NA 1.814818 #> 3 0.008532522   NA 25.84531 0.5813818 0.5408161 0.08330509  NA 2.082253 #> 4 0.007447260   NA 24.86909 0.6255197 0.6326848 0.07566682  NA 1.802161 #> 5 0.006994714   NA 31.32419 0.5668727 0.5734574 0.07432007  NA 2.454007 #> 6 0.007047106   NA 31.63214 0.5053022 0.4577485 0.06300538  NA 1.831953 #>   chla_tn_ratio tn_tp_ratio chla_tsi   tn_tsi  tn2_tsi   tp_tsi  tp2_tsi #> 1      3.821371    8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2      4.663093    7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3      4.188970    6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4      4.507341    8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5      3.374095    7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6      4.524324    7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #>    nut_tsi      tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651          NA         NA         NA       0       1 #> 2 47.43600 39.12890          NA         NA         NA       0       1 #> 3 46.38844 37.48223          NA         NA         NA       0       1 #> 4 49.76107 40.82559          NA         NA         NA       0       0 #> 5 47.64821 36.97650          NA         NA         NA       0       1 #> 6 42.80384 35.04375          NA         NA         NA       1       1"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"Get annual averages seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"anlz_transectave(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   total = TRUE,   yrrng = c(1998, 2023),   rev = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments yrrng numeric indicating year ranges evaluate rev logical factor levels bay segments reversed","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"focat column returned results shows color category based arbitrary breaks frequency occurrence estimates (foest) 25, 50, 75 percent.  necessarily translate ecological breakpoints.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) anlz_transectave(transectocc) #> # A tibble: 156 × 4 #> # Groups:   bay_segment [6] #>    bay_segment    yr foest focat   #>    <fct>       <dbl> <dbl> <fct>   #>  1 Tampa Bay    1998  58.0 #E9C318 #>  2 OTB          1998  65.5 #E9C318 #>  3 HB           1998  15.0 #CC3231 #>  4 MTB          1998  53.7 #E9C318 #>  5 LTB          1998  80.8 #2DC938 #>  6 BCB          1998  81.0 #2DC938 #>  7 Tampa Bay    1999  51.5 #E9C318 #>  8 OTB          1999  64.7 #E9C318 #>  9 HB           1999  10.1 #CC3231 #> 10 MTB          1999  51.8 #E9C318 #> # ℹ 146 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Get annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"anlz_transectavespp(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   yrrng = c(1998, 2023),   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\",     \"Dapis\"),   total = TRUE,   by_seg = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned by_seg logical indicating separate results bay segments retained","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Frequency occurrence estimates averaged across segments bay_segment by_seg = F, .e., separate results location returned.  Results retained bay segment by_seg = T.  Also note totals across species (total = T) returned by_seg = T.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) anlz_transectavespp(transectocc) #> # A tibble: 208 × 3 #>       yr Savspecies   foest #>    <dbl> <fct>        <dbl> #>  1  1998 Caulerpa    0.0166 #>  2  1998 Dapis       0      #>  3  1998 Halodule    0.361  #>  4  1998 Halophila   0      #>  5  1998 Ruppia      0.0112 #>  6  1998 Syringodium 0.0451 #>  7  1998 Thalassia   0.254  #>  8  1998 total       0.580  #>  9  1999 Caulerpa    0.0277 #> 10  1999 Dapis       0      #> # ℹ 198 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":null,"dir":"Reference","previous_headings":"","what":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Get seagrass average abundance occurrence across transects","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"anlz_transectocc(transect)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"transect data frame returned read_transect","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"data frame abundance frequency occurrence estimates aggregated species, transect, date.  nsites column total number placements sampled along transect particular date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2.  short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect.  estimates obtained seagrass species including Caulerpa (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Sherwood, E.T., Greening, H.S., Johansson, J.O.R., Kaufman, K., Raulerson, G.E. 2017. Tampa Bay (Florida, USA): Documenting seagrass recovery since 1980's reviewing benefits. Southeastern Geographer. 57(3):294-319.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } anlz_transectocc(transect) #> # A tibble: 37,625 × 6 #> # Groups:   Date, Transect [1,505] #>    Date       Transect Savspecies              nsites foest bbest #>    <date>     <chr>    <chr>                    <int> <dbl> <dbl> #>  1 1997-10-11 S2T3     \"AA\"                        41     0     0 #>  2 1997-10-11 S2T3     \"Caulerpa\"                  41     0     0 #>  3 1997-10-11 S2T3     \"DA\"                        41     0     0 #>  4 1997-10-11 S2T3     \"DB: Dictyota\\r\\n\"          41     0     0 #>  5 1997-10-11 S2T3     \"DB: Drift Brown\\r\\n\"       41     0     0 #>  6 1997-10-11 S2T3     \"DG: Chaetomorpha\\r\\n\"      41     0     0 #>  7 1997-10-11 S2T3     \"DG: Drift Green\"           41     0     0 #>  8 1997-10-11 S2T3     \"DG: Ulva\"                  41     0     0 #>  9 1997-10-11 S2T3     \"DG: Ulva fasciata\\r\\n\"     41     0     0 #> 10 1997-10-11 S2T3     \"DR: Acanthophora\"          41     0     0 #> # ℹ 37,615 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories for a chosen year — anlz_yrattain","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"Get attainment categories chosen year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"anlz_yrattain(epcdata, yrsel, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"data.frame chosen year bay segments showing bay segment averages chloropyll concentration, light attenuations, segment targets, attainment categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"# defaults to current year anlz_yrattain(epcdata, yrsel = 2023) #> # A tibble: 4 × 6 #>   bay_segment chla_val chla_target la_val la_target outcome #>   <fct>          <dbl>       <dbl>  <dbl>     <dbl> <chr>   #> 1 OTB             6.21         8.5  0.734      0.83 green   #> 2 HB              6.93        13.2  0.791      1.58 green   #> 3 MTB             3.68         7.4  0.472      0.83 green   #> 4 LTB             2.60         4.6  0.536      0.63 green"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 03132024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"benthicdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"nested tibble 3 rows 2 variables: name chr identifying dataset stations, fieldsamples, taxacounts value list dataframes dataset","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/benthic.zip'  # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE, remove = TRUE)  save(benthicdata, file = 'data/benthicdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Terrain basemap — bsmap","title":"Terrain basemap — bsmap","text":"Terrain basemap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Terrain basemap — bsmap","text":"","code":"bsmap"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Terrain basemap — bsmap","text":"ggmap object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":null,"dir":"Reference","previous_headings":"","what":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"Catchments radar pixels (precip) selected Enterococcus stations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"","code":"catchpixels"},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"data frame two columns: station character string Water Quality Portal station name pixel number; row single pixel Southwest Florida Water Management District's radar-estimated rainfall shapefile","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchpixels.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Catchments and radar pixels (for precip) of selected Enterococcus stations — catchpixels","text":"Generated data-raw/catchpixels-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/catchpixels-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":null,"dir":"Reference","previous_headings":"","what":"Daily precip by catchment for selected Enterococcus stations — catchprecip","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Daily precip catchment selected Enterococcus stations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"","code":"catchprecip"},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"data frame three columns: station character string Water Quality Portal station name date date rain number; inches rain date, averaged across pixels station's catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Southwest Florida Management District radar-estimated daily rainfall data, ftp://ftp.swfwmd.state.fl.us/pub/radar_rainfall/Daily_Data/","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/catchprecip.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Daily precip by catchment for selected Enterococcus stations — catchprecip","text":"Daily precipitation data 1995-2023, provided Southwest Florida Water Management District, downloaded pixel level averaged catchment level key Enterococcus sampling stations. Generated data-raw/catchprecip-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/catchprecip-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"Enterococcus data 53 key Enterococcus stations since 1995","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"","code":"enterodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"data frame 6266 rows 16 columns: date date, sample date yr numeric, year sample date mo numeric, month sample date time character, sample time time_zone character, sample time zone long_name character, long name bay segment subwatershed bay_segment character, short name bay segment subwatershed station character, sample station entero numeric, Enterococcus concentration entero_censored logical, whether entero value laboratory MDL, minimum detection limit MDL numeric, minimum detection limit time processing entero_units character, units measurement entero qualifier qualifier codes associated sample LabComments lab comments sample Latitude numeric, latitude decimal degrees Longitude numeric, longitude decimal degrees","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"Water Quality Portal, https://waterqualitydata.us","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/enterodata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Enterococcus data from 53 key Enterococcus stations since 1995 — enterodata","text":"sample dataset containing Enterococcus 53 stations TBEP watershed 1995-2023. Generated data-raw/enterodata-raw.R (view github: https://github.com/tbep-tech/tbeptools/blob/master/data-raw/enterodata-raw.R)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All bay data as of 20240201 — epcdata","title":"All bay data as of 20240201 — epcdata","text":"bay data 20240201","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All bay data as of 20240201 — epcdata","text":"","code":"epcdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All bay data as of 20240201 — epcdata","text":"data frame 27961 rows 26 variables: bay_segment chr epchc_station num SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num tn num tn_q chr sd_m num sd_raw_m num sd_q chr chla num chla_q chr Sal_Top_ppth num Sal_Mid_ppth num Sal_Bottom_ppth num Temp_Water_Top_degC num Temp_Water_Mid_degC num Temp_Water_Bottom_degC num Turbidity_JTU-NTU num Turbidity_Q num Color_345_F45_PCU num Color_345_F45_Q num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All bay data as of 20240201 — epcdata","text":"","code":"if (FALSE) { # \\dontrun{ xlsx <- '~/Desktop/epcdata.xlsx' epcdata <- read_importwq(xlsx, download_latest = TRUE)  nrow(epcdata) ncol(epcdata)  save(epcdata, file = 'data/epcdata.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20240814","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"","code":"fibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"data frame 77526 rows 18 variables: area chr epchc_station num class chr SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num ecoli num ecoli_q chr entero num entero_q chr fcolif num fcolif_q chr totcol num totcol_q chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All Fecal Indicator Bacteria (FIB) data as of 20240814 — fibdata","text":"","code":"if (FALSE) { # \\dontrun{ xlsx <- tempfile(fileext = '.xlsx') fibdata <- read_importfib(xlsx, download_latest = TRUE)  nrow(fibdata) ncol(fibdata)  save(fibdata, file = 'data/fibdata.RData', compress = 'xz')  file.remove(xlsx) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":null,"dir":"Reference","previous_headings":"","what":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"FIM data Tampa Bay Nekton Index current 07092024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"","code":"fimdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"data frame 52042 rows 19 variables: Reference chr Sampling_Date Date Latitude num Longitude num Zone chr Grid int NODCCODE chr Year num Month num Total_N num ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FIM data for Tampa Bay Nekton Index current as of 07092024 — fimdata","text":"","code":"if (FALSE) { # \\dontrun{ csv <- '~/Desktop/TampaBay_NektonIndexData.csv'  fimdata <- read_importfim(csv, download_latest = TRUE)  save(fimdata, file = 'data/fimdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"Spatial data object FIM stations including Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"fimstations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"simple features sf object (POINT) 7771 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Reference num bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"if (FALSE) { # \\dontrun{ # file path csv <- '~/Desktop/fimdata.csv'  # load and assign to object fimstations <- read_importfim(csv, download_latest = FALSE, locs = TRUE) save(fimstations, file = 'data/fimstations.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":null,"dir":"Reference","previous_headings":"","what":"Habitat Master Plan targets and goals — hmptrgs","title":"Habitat Master Plan targets and goals — hmptrgs","text":"Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"hmptrgs"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Habitat Master Plan targets and goals — hmptrgs","text":"data frame showing 2030 targets 2050 goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/trgs.RData\"))  hmptrgs <- trgs %>%    rename(Goal2050 = Target2050)  save(hmptrgs, file = 'data/hmptrgs.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"FDEP IWR run 65 — iwrraw","title":"FDEP IWR run 65 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 65 — iwrraw","text":"","code":"iwrraw"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FDEP IWR run 65 — iwrraw","text":"data frame 537946 rows 11 variables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"FDEP IWR run 65 — iwrraw","text":"File created using workflow <https://tbep-tech.github.io/tidalcreek-stats/Creek_select_tbeptools>, example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FDEP IWR run 65 — iwrraw","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  load(file = '../../02_DOCUMENTS/tidal_creeks/iwrraw_run61.RData') iwrraw <- sf::st_set_geometry(iwrraw, NULL) %>%   rename(JEI = jei) save(iwrraw, file = 'data/iwrraw.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Manatee County FIB data as of 20241011 — mancofibdata","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"Manatee County FIB data 20241011","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"","code":"mancofibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"data frame 12765 rows 13 variables: manco_station chr, Station name SampleTime POSIXct, Date/time sampling class chr, Waterbody class (Fresh, Estuary) yr num, Year sampling mo num, Month sampling Latitude num, Latitude, WGS84 Longitude num, Latitude, WGS84 Sample_Depth_m num, Depth sample, meters var chr, Variable name (ecoli, entero, fcolif, totcol) val num, Value variable uni num, Units variable qual num, Qualifier code area chr, Location name based USF Water Alas waterbody name","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/mancofibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Manatee County FIB data as of 20241011 — mancofibdata","text":"","code":"if (FALSE) { # \\dontrun{ mancofibdata <- read_importwqp('21FLMANA_WQX', type = 'fib')  nrow(mancofibdata) ncol(mancofibdata)  save(mancofibdata, file = 'data/mancofibdata.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Phytoplankton data current as of 03202024 — phytodata","title":"Phytoplankton data current as of 03202024 — phytodata","text":"Phytoplankton data current 03202024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"phytodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Phytoplankton data current as of 03202024 — phytodata","text":"nested tibble 21143 rows 8 variables: epchc_station chr Date Date name chr units chr count num yrqrt Date yr num mo Ord.factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- tempfile(fileext = '.xlsx')  # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE)  nrow(phytodata) ncol(phytodata)  save(phytodata, file = 'data/phytodata.RData', compress = 'xz')  file.remove(path) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":null,"dir":"Reference","previous_headings":"","what":"Download latest file from epchc.org — read_dlcurrent","title":"Download latest file from epchc.org — read_dlcurrent","text":"Download latest file epchc.org","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"read_dlcurrent(locin, download_latest = TRUE, urlin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download latest file from epchc.org — read_dlcurrent","text":"locin chr string path local file, overwrite current download_latest logical download latest file regardless local copy urlin url file location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy specified path locin overwritten new file current download_latest = TRUE.  function nothing download_latest = FALSE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy checked temporary file downloaded location specified urlin.  local file replaced downloaded file MD5 hashes different.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"if (FALSE) { # \\dontrun{ locin <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(locin = locin, urlin = urlin) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Format benthic data Tampa Bay Benthic Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"read_formbenthic(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"pathin path unzipped csv files base tables used calculate benthic index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"nested tibble station, field sample, taxa data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Function used internally within read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"if (FALSE) { # \\dontrun{  # location to download data path <- '~/Desktop/benthic.zip'  # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin)  # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE)  # format benthic data read_formbenthic(pathin = tmppth)  # remove temporary path unlink(tmppth, recursive = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Format Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"read_formfib(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"datin input data.frame loaded read_importepc logical indicating stations FIB data returned, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"lightly formatted data.frame FIB data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Formats input data read_importepc appropriate FIB results, see details read_importfib information.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T)  # final formatting fibdata <- read_formfib(epcall) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Format FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"read_formfim(datin, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"datin input data.frame loaded read_importfim locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Function used internally within read_importfim","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"# file path csv <- url('https://raw.githubusercontent.com/tbep-tech/tbni-proc/master/data/TampaBay_NektonIndexData.csv')  datin <- read.csv(csv)  # load and assign to object fimdata <- read_formfim(datin) #> Warning: attribute variables are assumed to be spatially constant throughout all geometries"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Format phytoplankton data — read_formphyto","title":"Format phytoplankton data — read_formphyto","text":"Format phytoplankton data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format phytoplankton data — read_formphyto","text":"","code":"read_formphyto(datin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format phytoplankton data — read_formphyto","text":"datin input data.frame loaded read_importphyto","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format phytoplankton data — read_formphyto","text":"formatted data.frame phytoplankton count data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format phytoplankton data — read_formphyto","text":"seven taxonomic groups summarized. Pyrodinium bahamense, Karenia brevis, Tripos hircus, Pseudo-nitzschia sp., Pseudo-nitzschia pungens retained species level.  Bacillariophyta Cyanobacteria retained phylum level.  taxa grouped \"\" category.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format phytoplankton data — read_formphyto","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/phyto_data.xlsx'  # load and assign to object phytodata <- read_importphyto(xlsx) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Format sediment data — read_formsediment","title":"Format sediment data — read_formsediment","text":"Format sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format sediment data — read_formsediment","text":"","code":"read_formsediment(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format sediment data — read_formsediment","text":"pathin path unzipped csv files sediment result tables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format sediment data — read_formsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format sediment data — read_formsediment","text":"Function used internally within read_importsediment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format sediment data — read_formsediment","text":"","code":"if (FALSE) { # \\dontrun{  # location to download data path <- '~/Desktop/sediment.zip'  # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin)  # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE)  # format sediment data read_formsediment(pathin = tmppth)  # remove temporary path unlink(tmppth, recursive = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":null,"dir":"Reference","previous_headings":"","what":"Format seagrass transect data from Water Atlas — read_formtransect","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Format seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"read_formtransect(jsn, training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"jsn data frame returned fromJSON training logical input transect training data complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"data frame long format","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Shoot density reported number shoots per square meter corrected quadrat size entered raw data.  Shoot density blade height (cm) based averages across random observations transect point entered separately data form. Abundance reported numeric value 0 - 5 Braun-Blanquet coverage estimates. raw = TRUE, unformatted data returned.  default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"library(jsonlite)  if (FALSE) { # \\dontrun{ # all transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use-with-care' jsn <- fromJSON(url) trndat <- read_formtransect(jsn) } # }  # training transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/training' jsn <- fromJSON(url) trndat <- read_formtransect(jsn, training = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Format water quality data — read_formwq","title":"Format water quality data — read_formwq","text":"Format water quality data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format water quality data — read_formwq","text":"","code":"read_formwq(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format water quality data — read_formwq","text":"datin input data.frame loaded read_importepc logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format water quality data — read_formwq","text":"lightly formatted data.frame chloropyll secchi observations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format water quality data — read_formwq","text":"Secchi data VOB depths secchis < 0.5 ft bottom assigned NA, function used internally within read_importwq","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format water quality data — read_formwq","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T)  # final formatting epcdata <- read_formwq(epcall) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Format data and station metadata from the Water Quality Portal — read_formwqp","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"Format data station metadata Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"read_formwqp(res, sta, org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"res data frame containing results obtained API sta data frame containing station metadata obtained API org chr string indicating organization identifier type chr string indicating data type download, one \"wq\" \"fib\" trace Logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"data frame containing formatted water quality station metadata","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"function used read_importwqp combine, format, process data (res) station metadata (sta) obtained Water Quality Portal selected county data type. resulting data frame includes date, time, station identifier, latitude, longitude, variable name, value, unit, quality flag.  Manatee County FIB data (21FLMANA_WQX) also include area column indicating waterbody name used USF Water Atlas.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"if (FALSE) { # \\dontrun{ url <- list(   Result = \"https://www.waterqualitydata.us/data/Result/search?mimeType=csv&zip=no\",   Station = \"https://www.waterqualitydata.us/data/Station/search?mimeType=csv&zip=no\" )  headers <- c(   \"Content-Type\" = \"application/json\",   \"Accept\" = \"application/zip\" )  body <- list(   organization = c(\"21FLMANA_WQX\"),   sampleMedia = c(\"Water\"),   characteristicType = c(\"Information\", \"Nutrient\", \"Biological, Algae, Phytoplankton,     Photosynthetic Pigments\"),   providers = c(\"STORET\"),   siteType = c(\"Estuary\") )  res <- url[['Result']] %>%   httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>%   httr::content('text') %>%   read.csv(text = .)  sta <- url[['Station']] %>%   httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>%   httr::content('text') %>%   read.csv(text = .)  # combine and format read_formwqp(res, sta, '21FLMANA_WQX', type = 'wq') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import benthic data for Tampa Bay — read_importbenthic","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"Download import benthic data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"read_importbenthic(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"nested tibble station, taxa, field sample data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"function downloads unzips folder base tables used calculate benthic index https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/benthic.zip'  # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Enterococcus data from the Water Quality Portal — read_importentero","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"Download Enterococcus data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"","code":"read_importentero(stas = NULL, startDate, endDate)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"stas character, vector stations.  NULL, defaults stations catchprecip. startDate character, starting date observations YYYY-MM-DD endDate character, ending date observations YYYY-MM-DD","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"data frame containing one row sample. Columns returned : date date, sample date yr numeric, year sample date mo numeric, month sample date time character, sample time time_zone character, sample time zone long_name character, long name bay segment subwatershed bay_segment character, short name bay segment subwatershed station character, sample station entero numeric, Enterococcus concentration entero_censored logical, whether entero value laboratory MDL, minimum detection limit MDL numeric, minimum detection limit time processing entero_units character, units measurement entero qualifier qualifier codes associated sample LabComments lab comments sample Latitude numeric, latitude decimal degrees Longitude numeric, longitude decimal degrees","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"Retrieves Enterococcus sample data selected stations date range Water Quality Portal, https://www.waterqualitydata.us","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importentero.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download Enterococcus data from the Water Quality Portal — read_importentero","text":"","code":"if (FALSE) { # \\dontrun{ # stations to download stas <- c('21FLHILL_WQX-101', '21FLHILL_WQX-102', '21FLHILL_WQX-103')  # download and read the data entero_in <- read_importentero(stas = stas, startDate = '2023-01-01', endDate = '2023-02-01')  head(entero_in)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and/or import local water quality file for internal use — read_importepc","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Download /import local water quality file internal use","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"read_importepc(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and/or import local water quality file for internal use — read_importepc","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and/or import local water quality file for internal use — read_importepc","text":"unformatted data.frame EPC","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. function used internally read_importwq read_importfib use source data Environmental Protection Commission Hillsborough County.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object epcall <- read_importepc(xlsx, download_latest = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Load local water quality file Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"read_importfib(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating stations FIB data returned, default TRUE, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"data.frame formatted FIB data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Returns FIB data including E. coli, Enterococcus, Fecal Coliform, Total Coliform concentrations waterbody class (freshwater 1 3F, marine 2 3M) stations sample dates, function used internally within read_importfib Values returned E. coli (ecoli), Enterococcus (entero), Fecal Coliform (fcolif), Total Coliform (totcol).  Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown.  Samples notation can determined qualifier columns. = FALSE, stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object fibdata <- read_importfib(xlsx, download_latest = T)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Load local FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"read_importfim(csv, download_latest = FALSE, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"csv chr string path local csv file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing csv available locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Data downloaded ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"if (FALSE) { # \\dontrun{ # file path csv <- '~/Desktop/fimraw.csv'  # load and assign to object fimdata <- read_importfim(csv, download_latest = TRUE) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local phytoplankton cell count file — read_importphyto","title":"Load local phytoplankton cell count file — read_importphyto","text":"Load local phytoplankton cell count file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"read_importphyto(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local phytoplankton cell count file — read_importphyto","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local phytoplankton cell count file — read_importphyto","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local phytoplankton cell count file — read_importphyto","text":"Phytoplankton cell count data downloaded https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/phyto_data.xlsx'  # load and assign to object phytodata <- read_importphyto(xlsx, download_latest = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily precip data and summarise by station catchment — read_importrain","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"Download daily precip data summarise station catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"","code":"read_importrain(curyr, catchpixels, mos = 1:12, quiet = T)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"curyr numeric year catchpixels data.frame columns named 'station' 'pixel'. data frame created key Enterococcus stations, associating station pixels station's catchment layer. tbeptools object 'catchpixels'. mos numeric vector months download quiet logical messages","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"data.frame station, date, rain columns daily average (inches) pixels catchment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"Data Southwest Florida Water Management District's (SWFWMD) ftp site: ftp://ftp.swfwmd.state.fl.us/pub/radar_rainfall/Daily_Data/","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importrain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download daily precip data and summarise by station catchment — read_importrain","text":"","code":"if (FALSE) { # \\dontrun{ read_importrain(2021, catchpixels, quiet = F) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import sediment data for Tampa Bay — read_importsediment","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"Download import sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"read_importsediment(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"function downloads unzips folder results tables https://epcbocc.sharepoint.com/:u:/s/Share/Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). row entries columns \"BetweenTELPEL\" \"ExceedsPEL\" rows \"Qualifier\" column \"U\" \"T\" (detection, detected) assigned NA, regardless entry source data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/sediment.zip'  # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE)  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file — read_importwq","title":"Load local water quality file — read_importwq","text":"Load local water quality file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file — read_importwq","text":"","code":"read_importwq(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file — read_importwq","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file — read_importwq","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file — read_importwq","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx.  file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1.  files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Water quality parameters returned default total nitrogen (tn), Secchi depth (sd), chlorophyll-(chla), salinity (top, mid, bottom depths, Sal_ prefix), water temperature (top, mid, bottom depths, Temp_Water_ prefix), turbidity (Turbidity_JTU-NTU), water color (Color_345_F45).  Additional qualifier columns include _Q suffix also returned, excluding salinity water temperature.  water quality parameters qualifiers can returned setting = T.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file — read_importwq","text":"","code":"if (FALSE) { # \\dontrun{ # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx'  # load and assign to object epcdata <- read_importwq(xlsx, download_latest = T)  # get all water quality parameters epcdataall <- read_importwq(xlsx, download_latest = T, all = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Import data from the Water Quality Portal — read_importwqp","title":"Import data from the Water Quality Portal — read_importwqp","text":"Import data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"read_importwqp(org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import data from the Water Quality Portal — read_importwqp","text":"org chr string indicating organization identifier, see details type chr string indicating data type download, one \"wq\" \"fib\" trace logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import data from the Water Quality Portal — read_importwqp","text":"data frame containing imported data selected county","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import data from the Water Quality Portal — read_importwqp","text":"function retrieves data Water Quality Portal API (https://www.waterqualitydata.us/) selected counties around Tampa Bay watershed. type data returned defined type argument either \"wq\" \"fib\" water quality Fecal Indicator Bacteria data, respectively. org argument retrieves data specific organization. Valid entries org include \"21FLCOSP_WQX\" (City St. Petersburg), \"21FLDOH_WQX\" (Florida Department Health), \"21FLHILL_WQX\" (Hillsborough County), \"21FLMANA_WQX\" (Manatee County), \"21FLPASC_WQX\" (Pasco County), \"21FLPDEM_WQX\" (Pinellas County), \"21FLPOLK_WQX\" (Polk County), \"21FLTPA_WQX\" (Florida Department Environmental Protection, Southwest District).  naming convention follows Organization ID Water Quality Portal. function fetches results station metadata, combines formats using read_formwqp function, returns processed data data frame.  Parameters specific type argument.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"if (FALSE) { # \\dontrun{ # get Manatee County water quality data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T)  # get Pinellas County FIB data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T) } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Import JSON seagrass transect data from Water Atlas — read_transect","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"Import JSON seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"read_transect(training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"training logical training data imported complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"function imports JSON file USF Water Atlas.  training = TRUE, dataset TBEP training survey imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/training.  training = FALSE, entire transect survey database imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use--care. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates, blade length cm, short shoot density number shoots per square meter.  short density corrected quadrat size included raw data. raw = TRUE, unformatted data returned.  default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"if (FALSE) { # \\dontrun{ # get training data transect <- read_transect(training = TRUE)  # import all transect data transect <- read_transect() } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass coverage by year — seagrass","title":"Seagrass coverage by year — seagrass","text":"Seagrass coverage year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass coverage by year — seagrass","text":"","code":"seagrass"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass coverage by year — seagrass","text":"data frame used create flagship seagrass coverage graphic: Year int Acres num Hectares num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass coverage by year — seagrass","text":"Original data Southwest Florida Water Management District available online <https://data-swfwmd.opendata.arcgis.com/>.  Totals Tampa Bay.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass coverage by year — seagrass","text":"","code":"if (FALSE) { # \\dontrun{  seagrass <- structure(list(    Year = c(1950L, 1982L, 1988L, 1990L, 1992L, 1994L, 1996L,         1999L, 2001L, 2004L, 2006L, 2008L, 2010L, 2012L, 2014L,         2016L, 2018L, 2020L, 2022L),    Acres = c(40420, 21650, 23285, 25226, 25753, 26518, 26916,         24841, 26078, 27021, 28299, 29647, 32897, 34642, 40294.71,         41655.16, 40651.55, 34298, 30137),    Hectares = c(16357.39, 8761.44, 9423.11, 10208.6, 10421.87,         10731.45, 10892.52, 10052.8, 10553.39, 10935.01, 11452.2,         11997.72, 13312.94, 14019.27, 16306.69, 16857.25, 16451.1,         13880, 12196)  ), class = \"data.frame\", row.names = c(NA, -19L))  save(seagrass, file = 'data/seagrass.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"Sediment data Tampa Bay current 12142023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"sedimentdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"data.frame 216627 rows 24 variables: ProgramId int ProgramName chr FundingProject chr yr int AreaAbbr chr StationID int StationNumber chr Latitude num Longitude num Replicate chr SedResultsType chr Parameter chr ValueAdjusted num Units chr Qualifier chr MDLnum num PQLnum num TEL num PEL num BetweenTELPEL chr ExceedsPEL chr PreparationDate chr AnalysisTimeMerge chr PELGrade Factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"if (FALSE) { # \\dontrun{ # location to download data path <- '~/Desktop/sediment.zip'  # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE, remove = TRUE)  save(sedimentdata, file = 'data/sedimentdata.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass management areas for Tampa Bay — sgmanagement","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"Seagrass management areas Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"sgmanagement"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"simple features sf object (MULTIPOLYGON) 30 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs areas int","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"polygons seagrass management areas Tampa Bay provide finer division areas within major segments (tbseg) relevance locations seagrass beds.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tools)  # NAD83(HARN) / Florida West (ftUS) # same as sgseg prj <- 2882  # create sf object of boundaries sgmanagement <- st_read(   dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Management_Areas/TBEP_SG_MA_FINAL_Projectfix.shp',   drivers = 'ESRI Shapefile'   ) %>%   select(areas = TBEP_SG_MA) %>%   st_zm() %>%   st_transform(prj)  # save save(sgmanagement, file = 'data/sgmanagement.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass segment reporting boundaries for southwest Florida — sgseg","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"Seagrass segment reporting boundaries southwest Florida","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"sgseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"simple features sf object (POLYGON) 22 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"polygons used Southwest Florida Water Management District summarizing seagrass coverage estimates major coastal estuarine boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tools)  # create sf object of boundaries # make sure projection does not change sgseg <- st_read(   dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Segment_Boundaries/Seagrass_Segment_Boundaries.shp',   drivers = 'ESRI Shapefile'   ) %>%   select(segment = SEAGRASSSE) %>%   mutate(      segment = tolower(segment),      segment = case_when(         segment == 'terra ciea bay' ~ 'Terra Ceia Bay',         T ~ segment      ),      segment = toTitleCase(segment)   )  # save save(sgseg, file = 'data/sgseg.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a table for the annual management outcome assessments — show_annualassess","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Create table annual management outcome assessments chlorophyll-light attenuation bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"","code":"show_annualassess(   epcdata,   yrsel,   partialyr = F,   caption = F,   family = \"Arial\",   txtsz = 12,   width = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter caption logical indicating caption added using set_caption family chr string indicating font family text labels txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"flextable object showing segment-averaged chlorophyll-light attenuation selected year, bay segment names colored management outcome used show_matrix.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1)  2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63","code":"show_annualassess(epcdata, yrsel = 2023) .cl-8c530592{}.cl-8c4bf702{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-8c4bf70c{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-8c4fafc8{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c4fafdc{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c4fca58{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca62{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6c{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca6e{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c4fca76{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63show_annualassess(epcdata, yrsel = 2023, caption = TRUE) .cl-8ca1351e{}.cl-8c9be05a{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-8c9be064{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-8c9e1898{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c9e18a2{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-8c9e308a{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e3094{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e3095{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e309e{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e309f{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9e30a8{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-8c9865d8{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}Water quality outcomes for 2023.SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Plot monthly chlorophyll light attenuation values bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(   epcdata,   param = c(\"chla\", \"la\"),   yrsel = NULL,   yrrng = c(1975, 2023),   ptsz = 0.5,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   trgs = NULL,   family = NA,   labelexp = TRUE,   txtlab = TRUE,   partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation yrsel numeric year emphasize, shown separate red points plot yrrng numeric vector indicating min, max years include ptsz numeric indicating point size observations yrsel bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" trgs optional data.frame annual bay segment water quality targets, defaults targets family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Points included yrsel plotted box plots using position_jitter. Use ptsz = -1 suppress.  dotted line plot shows large exceedance value.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a bar plot for transect training group comparisons — show_compplot","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"Make bar plot transect training group comparisons","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"show_compplot(   transect,   yr,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\"),   varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"),   base_size = 18,   xtxt = 10,   size = 1 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"transect data frame returned read_transect yr numeric year training data plot site chr string indicating site results plot species chr string indicating species plot varplo chr string indicating variable plot base_size numeric indicating text scaling size plot xtxt numeric indicating text size x-axis labels size numeric indicating line size","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"transect <- read_transect(training = TRUE) show_compplot(transect, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Enterococcus results by month, year, and location — show_enteromap","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"Map Enterococcus results month, year, location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"","code":"show_enteromap(   fibdata,   yrsel,   mosel,   areasel = NULL,   wetdry = FALSE,   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"fibdata data frame Enterococcus sample data returned enterodata anlz_fibwetdry yrsel optional numeric filter data year mosel optional numeric filter data month areasel optional character string filter output stations long_name column enterodata, see details wetdry logical; TRUE, incorporate wet/dry differences (result call anlz_fibwetdry, case temporal_window wet_threshold required). FALSE (default), differentiate wet dry samples. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required wetdry TRUE. number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required wetdry TRUE. inches accumulated defined temporal window, sample defined 'wet' time period","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_enteromap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Enterococcus results by month, year, and location — show_enteromap","text":"","code":"show_enteromap(enterodata, yrsel = 2020, mosel = 9)  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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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Number: 21FLHILL_WQX-101<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: all<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: all<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: all<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: all<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: all<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: all<br> Category: 130 - 999 (908/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-109<br>Sample Condition: all<br> Category: < 35 (1/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-133<br>Sample Condition: all<br> Category: > 999 (3100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-144<br>Sample Condition: all<br> Category: 130 - 999 (620/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-2<br>Sample Condition: all<br> Category: 130 - 999 (280/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-560<br>Sample Condition: all<br> Category: 130 - 999 (600/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-561<br>Sample Condition: all<br> Category: > 999 (3500/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-594<br>Sample Condition: all<br> Category: 130 - 999 (300/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-595<br>Sample Condition: all<br> Category: > 999 (6100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-596<br>Sample Condition: all<br> Category: 130 - 999 (580/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-597<br>Sample Condition: all<br> Category: > 999 (1350/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-598<br>Sample Condition: all<br> Category: 130 - 999 (525/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-74<br>Sample Condition: all<br> Category: 35 - 129 (85/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-32-03<br>Sample Condition: all<br> Category: < 35 (20/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-44-02<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SC-01<br>Sample Condition: all<br> Category: 130 - 999 (480/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-112<br>Sample Condition: all<br> Category: 130 - 999 (220/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-180<br>Sample Condition: all<br> Category: 35 - 129 (56/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-264<br>Sample Condition: all<br> Category: 35 - 129 (40/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-592<br>Sample Condition: all<br> Category: 130 - 999 (320/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-22<br>Sample Condition: all<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-48-03<br>Sample Condition: all<br> Category: < 35 (31/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-CENTRAL CANAL<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-COSP580<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-NORTH CANAL<br>Sample Condition: all<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SOUTH CANAL<br>Sample Condition: all<br> Category: 130 - 999 (360/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-01<br>Sample Condition: all<br> Category: 130 - 999 (717/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-05<br>Sample Condition: all<br> Category: 130 - 999 (727/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>All samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.535934301,28.0257081],\"lng\":[-82.74574933,-82.381683]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # wet/dry samples show_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,                temporal_window = 2, wet_threshold = 0.5)  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.535934301,-82.74574933,28.0257081,-82.381683,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide 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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAq4AAAK5CAYAAAB+LKwlAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAFrRSURBVHhe7d0LlF1Xfd/xSVKgaZzysOfuM8YkbTF9UAhp0tDyStxFaFaz8mjNCiQkpaxCSFgQmjQJTeLFildKkq4AThNaDMQGG2EbsGVjyza2/Bjdfa5kCQv8ErZs48gWlu4+R5ZlG4PtAlb//zPbkX3vX9JoZu7d+5z7/a31WRaa0WjmnL33/zfD1b1zhBAya9n+8blnVdvmi+Fm97Jh6U6pBsUbQ1n8Rj1Y+KPKuw8FX3xE/vvx4N05oV9cIP9dL793ufzeRvl1v/LFDfLfr8h/d8jv3y2/f5/8OsjvHZBff1N+7ztq6df6e0XQ91l6X/0zzZ/VjyEfSz9mcbn8en38u86R35O/u/kcPqSfk35u+jnWvvip4aJ7WbU4X+jXEL8cQgghhBDSlhxcnPt79aYTXlJvLn6yKotTQ7nwzqp0fyg+XA+kCJZSOstiqxTAu0MpRbIsDnaBfi1LX1PztWn5PUeK+If1a5fC++vyPqfqNdFro9coXi5CCCGEEDLJ3N8/8UVSxl4nZeytwRd/XJfFp6S4bZKydt/TyxwOT6+VXrPm2sk1lN97q15TvbbxMhNCCCGEkKPlke0LJ+zdXPzEsHRvqgbufZV3Z0rRukr+u1P++8RoCcPaaq6xXutSrnnpztR7oPdC74nem3ibCCGEEEJmJ7u3nPT9D2xxrwz93jukMP1V5YtFKU37R4sU8tLcI7lX8uu/0nun91DvZbythBBCCCHtznDR/aN9pfv54IvTxOeq0t0+WojQdu52vbd6j/Ve6z2Pt58QQgghJL/oT96G3v2betB7RyiLvw59t6nip6izS+69rgFdC7omdG3w01lCCCGEJEkoe/+k8sV/1sehSlG5Zay4ALZbmjUja0fXUFxOhBBCCCFrl7q/8GNV6d4jxeN8+e+9I2UEWKFmLZ0/7Lv37JE1FpcbIYQQQsjycteVJz9n38D9u9oXp0mxuCL44qHxwgFMxIGwtOZOG8oa1LUYlyUhhBBCyNzccLPrBb/wH0NZ/EVduoFRJoBkpMgOdG3qGtW1GpctIYQQQmYllV94TeXdn0gh2GaVBSBXzZqVtatrOC5nQgghhHQpe30xH3zxa1XfrQulq61CALRNs5Z1Tcva1jUelzshhBBC2pZhX5/kv3h/6PN//2M26FrXNa9rP24DQgghhOSYA4vPfZ4M7DfL4P5kVbr7rcEOzA53v+4F3RO6N+I2IYQQQkiqDDe7l8lg/oPKF9fbwxtAQ/aI7hXdM3H7EEIIIWTSqbbMn6wDOHh3ozmgARyR7p3mGz7ZS3FbEUIIIWStcn//xBeF/sJvy8AtrUEMYGV0T+ne0j0WtxshhBBCjjXNMwEMit+sfHGNNXABrDHZa7rneIYCQgghZBnZNzj+B6uBe5sM0Q1jQxXANG3Qvah7Mm5PQgghhBzcPves4Hu/Ery7yBieABLTval7VPdq3LaEEELIbKXeXPxk8MXZoXSPWcMSQF50r+qe1b0btzEhhBDS3Tyw9QX/cOjdb8kA3G4NRgDtoHtY97Lu6bi9CSGEkG6kHiy8LvjirFAW37aGIIB20j2te1v3eNzuhBBCSPui/6hj2Hfv0eeMtAYegG7Rva57nn/QRQghpDWpyoXXDn3xN1XpnrCGG4Cuc08snQELr43HAiGEEJJPqsX544Z9924ZWtvGhxiAGbatORvkjIjHBSGEEJIm1WD+RyvvPl6V7nFjYAFAJGeEnhVyZsTjgxBCCJlOgu+9Pni33h5QAHB4enboGRKPE0IIIWQyqcvil0LpNlnDCACOhZ4leqbE44UQQghZm+jrl8uguXV08ADAGrhVz5h43BBCCCHHngOLz31e8MVpYo8xaABgTelZo2eOnj3xGCKEEEKOnGow/+KqdB8Onn9wBWD6ls4e92E9i+KxRAghhDwzw757pQyMc6xBAgAp6JmkZ1M8pgghhMx6hqU7JZTFBmtoAEAO9IzSsyoeW4QQQmYtD2xxrwylu8gaEgCQIz2z9OyKxxghhJCuJ2zqvbwq3TprKABAK/TdOj3L4rFGCCGka6kW509eepUrYwhgNg3cY8G7h+QbmSDulV/vFDfL27bKf33li8Xge9fJutkYSvdF+fUVwReXyfteEgZufSiLz1dl7wJ5+3ny9k/r4xEr3zu72uw+0ZBf6+/p2/R99H31z+ifbT6GfKzmY8rHbv6O5u/Sv1P+7qXP4WaxUz83/Rzl1w/p5/yMrwGzTc603XK2xWOOEEJI27NvcPyJUgb+t3noo4selSI4FHdJ2btFyuA2KXx9KYlXyzq4VP77Ofnf50oB/LgO/VaSz12/Bv1a4td09dLX2NtW9eVrlq9dr4Fei5Frg44ayhmnZ1089gghhLQt95U/9HwZ6H8eyuI71kGPdpJC9lhdurr2xT1S1vQnkqW4cqmQFmeZRW+G6TVZujZ6jZprdbNeOyn1tV5L6xqjnfSsqwfFn+nZF49BQgghuefJu05+jhzg7xffsA53tEDzf+EXe+qyuG3oixvkv1fXZe+iUPY+ZZUzrJxeU722eo3jtb5Nrz0PSWgvPfv0DNSzMB6LhBBCckzVL36v8kVlHebIlHcPSlH6WuV7X6r1sZ4Dd95ouUIici+aeyL3ZukeuQfNe4g86VkoZ2I8HgkhhOQSOaTfKnY949BGVpr/W3rpJS1vk1/364G7WP43/9d+6xRn6b3Te6j3srmnPOQgd7v29ov/Eo9LQgghqRIGvVfJMN1oHNRIKHj33VhoviK+WOu/qDdLELpC77Hea73nS9+gyBow1gYS0meukDMzHp+EEEKmlT2LCyfIgPy/5uGMBJqfuOlPvLdKablU/9X7aLHBjGnWgKwFXRPN2uCnsrnQs1PP0HicEkIImWTqsvffQlk8ZB3ImA65/g9LEblTCoqXIXjhWGkBDLpWQvMcte7OpTVkry9Mnp6hod/77XisEkIIWevUg+JnZejdaB3CmCy57vsqfTxj6a6VAsL/7Y+1ct7SmtJnMpA1Zqw9TJaeqXq2xmOWEELIalNvOuElw7I43zp0MRnBF/9Phtk9VdnrN+XCLh3AWtNXF+tXsvZ0DVprE5OhZ6yetfHYJYQQspJUpTvdOmSx9qQo7NdXXZLicLlRKIDpk7UYBvoiE7I2jTWLSXCnx+OXEELIchMGC78qw+pr9sGKtRC8+46Ug3tr70p9Df2x0gDkRNaorFlZq8WuZu0aaxprQ89ePYPjcUwIIeRwuX/Tif8q6BOeG4cpVk8G/gEZSrdVA3dl1XefMAsCkDtZu0HWsK5lXdPWWsfq6VmsZ3I8ngkhhDw9MoROsw5PrI4MHymr7itivVkCgJbTtd2scVnr1h7A6ujZHI9pQgghVX/+1aEsNlsHJlbskarUx6u6L1iDHugsXfPN2tc9YO4NrEBzRstZHY9tQgiZzciA+YB1SGIl3DcrX+yoyt4Gc6ADs6bZC7onZG+YewbHzn0gHt+EEDI72be59/rg3U32wYjlkmv4hAzoO5rHrFqDG8CSpT1yR7NnjL2E5dOzW8/weJwTQkh3c/Dg3PdWfXeGdRhieWRofFfcXZfF1WPDGcBR6d7RPaR7ydpjWJ6hnOUHPz/3ffF4J4SQbmVYup+XobHTOgCxHK4OpRuEfu+To4MYwLHTvaR7SveWvedwNFL+d+rZHo95Qghpf6rF+eNkMJxpHXo4slAW+tPVOypfXGoNXgBrpbhU95ruOWsv4mjkjJezPh77hBDSztSle5MMg932QYfDkWu2T67doC756SowTbrnht5t1j1o7U0cgXf3DfvuzfH4J4SQ9uTATc99nhz855qHG0yhXzwp12xn8MVlo8MUwPTpXmz2pOxNa8/Cpme/zoA4DgghJO/s3VT8bOWLXdaBhnH6k51Q6k94ep+yhieAtHRvNnu05KewyyYzQGdBHAuEEJJnht79T/MQwxgprHfz01WgXeJPYe+29jTG6UyI44EQQvJJ7U/8p1W/uNY6uHCIDL0nK1/cJr/+rDUUAbREs4eL25o9bex1PMO19w9O/GdxXBBCSNoM++5tcpDzyjRH4t23Qum262O/njH8ALSa7um6dDfKr79l7n0s0RkhsyKODUIImX4OHpz7vubwtg4pNGSoHdBnB6gG4wMPQIfIHg99N9A9b50FiORa6eyIY4QQQqaTPZsWXieH0K1jhxIaoXTDyveuGxtuADovyN5vzgDjbEDjVp0hcZwQQshkIwfz+4yDCCJ4d6+4YnSQAZhBpZwFpbvXOisgZJbEsUIIIWufun/CghzCl5gH0IwLfXfn0LuLxwYXgJmnZ4OeEdbZAXfJfYPjT4xjhhBC1iZVv3ijHDJh/NCZbcEXXwsDt94aVgDwdHpWDOXMsM6SGRd0xsRxQwghq4uUs78wDpqZpg8JkEF06ehgAoBluFTOEV6kZYTOmjh2CCHk2PPQlpNeIAfJZdYBM7vc16uyd7kxiADg2OhZ0pwp1lkzm3Tm6OyJY4gQQpaXavP8q4N3d1kHyyzSfyFcl+4qc/gAwCro2cKzEBzSzB6ZQXEcEULIkSOH6H+1DpNZJMNk37DvrrWGDQCsJT1rpLTts86iWaSzKI4lQgixU5c8nnWJO1ANikVruADAZMnZo2eQeTbNFp1JcTwRQsihPLztxOPlsOTxrPrSrN6V44MEAKYrnkW8lKzMJp1RcVwRQmY9lV94jRwOPJ61dLdUg97Zo8MDAJLRM0nPJvPMmil36ayKY4sQMqupS/d244CYMe7eoee5WAHkK+gZxatw6eNe3x7HFyFk1hIG7oPWwTArZBAcqAbuGmtIAECOajmzmrPLONNmhc6uOMYIIbOQPYsLJ8jm3zB6GMyK0C+eDKX7kjUUAKAV5AwLvnjSOuNmxAadZXGsEUK6mj3lwmtDWdxtHAIzQb5Tv3PYd+ebgwAAWqQ5y+RMs866WaCzTGdaHG+EkK5FNvqpstG/Pbr5Z0QIvneFdfgDQJstnW1FMM69zosz7dQ45gghXYkcau8a3fCzIHj3WM3TWwGYAXrW6ZlnnYWdJzMujjtCSNtTle50c6N3nBzgO8PAnWMd8ADQRXrm6dlnnYnd506PY48Q0tbIQXamvcG7K/jiEfm6Nz79MAeAWTKUM3DYl7PQOCM7TWZeHH+EkDbl4Pa5Z8kGvtjc2F3mix37fHHW0w9wAJhFzVk4KHaYZ2WXyezTGRjHISEk93x98YUnhdINzA3dVd49WA3clU8/tAEAYulsfNA8OztKZ6DOwjgWCSG5Zm+58OPBz9bTXYWBu3nsoAYAPEPwclYaZ2hX6dNl6UyM45EQklvqsvgPzeM7jQ3cRXXp6lD2NlgHNABgnJ6ZenZaZ2oX6UzU2RjHJCEkl1QD9zZr03ZVKN2XrUMZAHB0wcsZapytnSUzMo5LQkjqyCH0P8yN2kFD74ZV6S4ZPYQBAMdIztKlM9U+bztHZmUcm4SQVBn23RnmBu0kt33s4AUArI6ereaZ20XujDg+CSHTTijdR+2N2S3BFw/LYcPLtQLApMgZu3TW2udwp/Bcr4RMP3LAnGVuyK7x7q667H3yGQcsAGDNxbP2LvMs7hqZoXGcEkImneDdueZG7JgwcOXowQoAmKzm7DXO5K4Jpft0HKuEkElFNtsFo5uvc3wR5Dv/i6wDFQAweUtncBHMM7pbLojjlRCy1gnerTc2Xce4W6xDFACQgJ7J5lndHTpb45glhKxFDh6c+x75zvcya8N1hnffqgZu49ihCQBIa+ls/pZ5dneFzFidtXHsEkJWmoM7Xvps+W7wKnOjdUZvV126dWOHJQAgC80ZLWe1fYZ3g85anblx/BJCjjXV4vxxspmuG91cHbPVOiQBABnSM9s+y7vBy8yV2RvHMCFkuXmo/KHny3d/Hf6Xne6b8vVdaR6MAIBsNWe3nOH22d4FzusMjuOYEHK0hBt6TjZPd7+r9cWeYd+dbx2IAID8LZ3hxR7zjO+GrTqL41gmhBwu9/dPfJF8N/sVYxN1w8B91ToEAQAtpGe6ddZ3gM5inclxPBNCRlMtzhfyHeyt1gbqgrp0m82DDwDQWs3Zbpz5naAzWWZzHNOEkKfS/EMsX2wxN07befdNccXTDzoAQKfoGd/Nx73qbOYfbBHyzDTPk2dtmPbbUw/ceSMHHACgY5qzXs78kRnQDTKj47gmhFSlu8TcKK3H41kBYObo2W/OhLZzl8SxTcjsRjbCOnuDtFvwPJ4VAGZVMwOM2dB+bl0c34TMXmRzf8zeGC3mm+dn5fGsADDj4izo3uNeZXbHMU7I7EQW/ofMDdFqrg793gVPHVoAgNnWzASZDfbMaDGZ4XGcE9L9yCY+3dwILRb67r7K984ePbQAALOud3YzI4zZ0W7u9DjWCeluqr77fXsDtFfwbqd9WAEAsKSZFcYMaTWZ6XG8E9K9VL54l7nwW2zoi5usAwoAgFHNzDBmSavJbI9jnpDuRBb3W8cWe8sFXgkLAHCMmtlhzJSWe2sc94S0P7KgTx1Z4K1Xl+5a60ACAOBomhlizJaWOzWOfULam32lO8VY3C3mHqvK3gbrIAIAYNl0ljQzxZo17aQzP45/QtqXanH+5FAWe63F3Ure7a/L4vNjhw8AACsQZ8p+c+a0UDPzZfbHGkBIe3LXlSc/RxbxttFF3WL3B+/OHT10AABYjWa2yIwZmTlttk07QKwDhLQjoXQXGYu5leQ7yLutwwYAgLXSzBpjBrWRdoBYBwjJP9XA/aW1kFvJuztGDxcAACbkDnMWtZF0gVgLCMk38h3j75oLuJXcV41DBQCAydHZY86k9tFOEOsBIfmlLt2brIXbSr64zTxQAACYOJlB1mxqIe0GsSYQkk/CoPcqWaDfHl2w7eRusQ8SAACmRGeROaNa59vaEWJdICR9Htj6wpNkYf7tyEJtJV7CFQCQiw69ROzfaleItYGQtAneeWORtpDbbh0cAAAko7PJnFntol0h1gZC0qXyxXnWAm2bULovmQcGAACJNTPKmF2tI50h1gdCpp9QFv/LXJjts9U6KAAAyIbOKnuGtYp2h1gjCJleqtK921qQrePdlrHDAQCAPG0xZ1nruHfHOkHI5BPK3k/bC7Fdau9K41AAACBbzewyZlrbaJeItYKQyWW42fVkwe0aXYBtQ2kFALRVF8pr8O5e7RSxXhAymQRfXGYtwJbhMa0AgHbrwGNetVPEekHI2mdYug9YC69NQum+bB4AAAC0TDPTjFnXLu4DsWYQsnaR0tr6l3OteUUsAEDXdOAVtnhZWLKm2bd54Z8HXzxiLbb2cLebGx4AgPa73Z597aAdQ7tGrB2ErC6hdANrobVF8O5uY5MDANAZzawzZmBbaNeItYOQlUcW0ketBdYWwfd2WRscAIDOKWXmGbOwLbRzxPpByLEnDIrftBZWWwRf3F8NjI0NAEAXycxrZp8xE9tCu0esIYQsP9Xm+VdbC6o1fFHVZe+T5sYGAKCjdPZJea3M2dgW0kFiHSHk6KkW548L3t1hLqZWcPvFOmtDAwDQeToDm1lozcj8NR1kx/xxsZYQcuTId2qfsxZSG+i/TKz6vQvMjQwAwKyQWdjMRGNWtoF2kVhLCDl8ZKGcZi2gNgil+049cBebGxgAgBmjM1FnozUz20A7SawnhIwnlL03WAunNbzbOLppAQCYcRvNmdkS2k1iTSHkUA7ueOmzq7K9j2uV7yg3G5sVAICZ18xIY3a2g7tDO0qsK4QsZaiL21wwbcBLuQIAcERtfmnYgftYrCuENA8ReIu5UFpg2C/uMTcoAAB4hmZmGrO0DcKm3ltibSGznN3XvuCFwbsHrEXSAqHa7D5hbU4AADBCZ6bOTnumZk27inaWWF/IrEYWwnprgeSuLotvDEt3vrkxAQCASWenzlBrtuZOO0usL2QWU3v3XmthtIFsukutDQkAAI6smaHGbG2DoXSXWGPILKUq519hLYh26F1nbUQAALBMOkvNGdsG86+IdYbMSqrS9e3FkDnf22ZuQAAAcIxkplqzNnNBOkysM2QWUg3cn1gLIXu+2GFvPAAAsDIyW62ZmzvpMrHWkC4nlL2fNhdA5oJ3u+0NBwAAVqOZscbszZ12mlhvSBezffvcs2Rx3m7d/Kz53qN16dZZmw0AAKxOM2PL3qPmDM6YdhrtNrHmkK5FFueZ1o3P3dC7K0c3GQAAWDtSAq+0ZnD2pNvEmkO6FCl/v2ze8PxtHd1cAABgAnTm2rM4a9pxYt0hXcjB7Qv/oCrb9/gVWYh3mxsLAABMRNDZa8zkvLnd2nVi7SFtT/DFR+wbnS/ZOPurQXGWtakAAMCELM3e/dZszlldFn8daw9pc4Lvvd66wbmrB+7isc0EAAAmrpnBxmzOnXaeWH9IWxO8u9G6uXlzfWsjAQCAKWnhCxVp54n1h7QxtS9Os25s1nxxm7mBAADAlMlMtmZ1xoJ0n1iDSJsyXHQvs25o1nyxx944AAAgDZnN1szO2P7S/ctYh0hbIjduw+iNzFnw7vGq7F1gbxoAAJDE0myWGW3P70xtiHWItCGh33uHcROzVpfF1WObBQAAJNfMaGN250y7UKxFJOfsWVw4IXj3gHUTcxXK4iZrowAAgDw0s9qY4bnSLqSdKNYjkmsqX5xl3cCMBWuDAACAzOjMtmd5loJ0oliPSI6pvfs568blrB649ebmAAAAWWlmtjHLc6bdKNYkklsqX+ywblquhr64wdoYAAAgT83sNmZ6tqQbxZpEcsqw7/7UvGG58u7e0c0AAADyF3SGW7M9W+4DsS6RHLJ3c/ET9o3KU/DFE7LwzxvdCAAAoBXOa2a5MeNzpV0p1iaSOvKdz5XWTcrVXl8sGpsAAAC0RnG9NeNzpV0p1iaSMnVZ/JJ1g/Ll7rA3AAAAaJk77FmfJ+1MsT6RVAkteh3hUBYPV753trHwAQBA6/TObma7MfNzpJ0p1ieSInID/rt1Y7I1cFfaCx8AALRR0NluzfxMaXeKNYpMM7u3nPQCufgPWTclR7w6FgAA3dSmV9XS7qQdKtYpMq1UA/eX1g3Jki8qa6EDAIBukEJYmR0gR9KhYp0i00hVzr/CvBGZGvbdJdYiBwAA3dDMeqMD5Gv+FbFWkUknlO4i+ybkZ+h5iAAAALOgmflGF8iRdqlYq8gkM/Tu56wbkKPg3QFrYQMAgG5qZr/RCXKknSrWKzKpyIXeNnrhc1WX7iprUQMAgG6S4nqV1QkytS3WKzKJVL54l3HR8+TdztHFDAAAZsJOsxvkSLpVrFlkLXNw8Yf/fiiLveZFz413j8t3XOeOLGIAADADYgd43OwImdFupR0r1i2yVgm++DPrguep1x9dxAAAYIZoFzA7Qn60Y8W6RdYi9Q0nvMS60Fny7r6xxQsAAGbRfWZXyJB2rVi7yGpTlW6ddZFzFPruQmPhAgCAGdN0AqMr5Mmti7WLrCZ7y4Ufty9whry7cXTRAgCA2RW0G1idIUPauWL9IitN5YvzrIubHe/2jS5WAAAAsc/sDrmRzhXrF1lJ9g2Kf21e2Cz1LjcWKgAAmHXaEczukB/tXrGGkWONXMALRi9olnyxw1yoAAAADekKVofIzwWxhpFjybDvXmlczOwEXzwRBu4ce5ECAAC4j2tX0M5gdYncaAeLdYwsN3JzP2ddzNwMfXGDtUABAACerukMRpfIjXawWMfIchLK3r+1LmRugnf7rYUJAABgabqD0Slyo10s1jJytNRl8XnrImbHu2tGFyQAAMARXGN2isxoF4u1jBwpYdB7lXUBcyPfMe02FiMAAMARNR3C6Ba50U4W6xk5XORmXmRdvPy4S6zFCAAAcETaIcxukRftZLGeESuVX3iNdeFyE0p3u7kQAQAAlqHpEkbHyI50s1jTyGjkRl5sXrSMyHcf35X/fmZ0AQIAACybdInYKcy+kQ3pZrGmkadnz6aF15kXLDOyyG4cW3wAAADHqOkURtfIjXa0WNfIU2nD4z2CLx62Fh4AAMBKNN3C6Bx5cZfEukY09aAlP23tF4vWogMAAFiJplsYnSM32tVibSPS5D9jXaSs+GKPteAAAABWRzqG1T2y4j4Ta9tspxrMv9i+QLnpbbAXGwAAwCpoxzC7R2aks8X6NrsJ3n3QvDg5GRT3mAsNAABgLWjXsDpIRrSzxfo2m9m95aTvD754xLo4eeHFBgAAwAS14x+pP6LdLda42YtcgN+xLkxW+vy0FQAATEMbfupa/E6scbMXuUk7rYuSk2Gfn7YCAIApaMNLwUp3izVutiKF8M3mBcmIfFfxtbFFBQAAMCFN9zA6SU60w8U6NzuRL/z60QuRHX0JWmNRAQAATEj2L38vro91bjbShhccCGVxt7GYAAAAJqrWDmJ0k5zM1AsStOEFB+qBW28tJgAAgElqOojRTfIyIy9I0IYXHAje8dNWAACQTCilixgdJSuz8IIEbXjBAfkc+WkrAABIptYuYnSUnHT+BQna8IID8h3OXdYCAgAAmLK7rK6SC+10nX5BAn3SWusLz0ld9i4yFg4AAMBU1aW7yOoqOdFuF2te9yI3IfMXHHB3ji4aAACAZLSbmJ0lE119QYLQ7/2i+QVnpB7MbxxbMAAAAKn056+xOktOtOPFutedhNJdaH2x2fC9XeaCAQAASEo6itVdMqEdL9a9buS+jcefaH2hOQneXWkvFgAAgHSajmJ0l5zcNzj+xFj72p+hd++zvshchL6rrYUCAACQg6arGB0mG9L1Yu1rfypf3Gp+kdlwm0YXCAAAQDa0q5gdJhPS9WLta3f2le4U8wvMx6PmAgEAAMiJdha7y2RBO1+sf+2NNPCzrC8uF8G7G83FAQAAkJGmsxhdJhfBF2fH+tfODK92PyAX+Qnri8tBKIsn64E711ocAAAAOdHOot3F6jQ50M43vNn9QKyB7Ytc3N+wvrBs9N1XrYUBAACQJe0uVqfJhHa/WAPbF2nepfVF5aIuexeaiwIAACBDTXcxOk0uaul+sQa2K3v6Cz9mfUG5CLzgAAAAaKGmwxjdJhe1dMBYB9uTqu/OsL6YXARecAAAALRQ02GMbpMPd0asg+2JfNLZPlEuLzgAAADaLO8XJHB1rIPtSL3Z/bL9heSCFxwAAAAtlvkLEgTf+5VYC/NP8O4K64vIg3vMXAAAAABtop3G7DrpaReMtTDvVIP5F1tfQD7crebNBwAAaBPtNGbXycTi/MmxHuYbuZDvMz/5TNTerR+78QAAAC3TdBqj62RDOmGsh/lGPtEtY594JkLphqM3HQAAoK2abmN0nkxsifUwz9SbTniJ8UlnQ26ut246AABAGzXdxug8udBuGGtifqkG7vetTzoHQ+++W/ne2dZNBwAAaKfe2U3HMbpPDuRzy/fhApXP+GEC3u20bzgAAECLle4Oq/tkQbphrIl55euZP0ygKnsbzJsNAADQZtpxzO6TB+2IsS7mk6qf78ME5KbuH7vJAAAA3bHf7EA5GLjfj3Uxn4Sy2Gx+snnYatxgAACATpAettXoP3nI7eEC1Zb5k81PNBtunXWTAQAAOkG7jtmBMiFdMdbG9Bnm/DCBQXGPeYMBAAC6RDuP1YVyIF0x1sb0yflhAsG7q82bCwAA0CFN5zG6UA60K8bamDa7F/N9mEDwxTesGwsAANBFTfcxOlEWpDPG+pgu8on83tgnlgm5eTdZNxUAAKCLmu5jdKJM/F6sj+kSvMv42QTcJdZNBQAA6CTtPmYnSk87Y6yPaVIN5l9sfWI5CKU7YN5QAACADms6kNGNsiDdMdbI6afq5/swgZqHCQAAgBnUdCCjG2VBumOskdNP5YvrzU8qCzxMAAAAzKCMHy6g3THWyOmm2jF/nPkJZYCHCQAAgFmW9cMFpEPGOjm9hHLhP5mfTAZCycMEAADA7Gq6kNGRcqAdMtbJ6UWa/EetTyYPPEwAAADMsJyfXUA6ZKyT00vwxd3WJ5Na8O4h8wYCAADMkKYTGV0pNe2QsU5OJw/cUPwL6xPJAQ8TAAAAyPvhAtolY62cfGrv3mt9EnngYQIAAAA5P1xgKF0y1srJRxr8BuuTSI2HCQAAAByS7cMFpEvGWjnZHDw49z3S4B+zPonUQt/dbN00AACAWdR0I6MzpeceO/jHc98b6+XkUg0W/r39CeSAhwkAAAD8nYwfLqCdMtbLySV490HzL0+NhwkAAABYMn12AffBWC8nl7p0Wf4LteCLHcaNAgAAmGlNRzK6U2raKWO9nEz2lAs/ZP3FOZAv/irrZgEAAMyypiMZ3SkHe68rfjjWzLXPsHRvt/7SLPR7Z1s3CwAAYKZpR7K6UwakVL891sy1j/wFF4z+hTkIvrjfvFEAAAD4eDVwX7c6VGrS4T4ba+bapyrdA9ZfmoGt5k0CAADAx5uuZHeoxNwDsWaubfb4+dfYf2F6wbv15k0CAADAx8NAupLRoXKgHTPWzbVLKIvftf6y1IIvHrVuEAAAAA6py+IbVpdKTTtmrJtrl1C6C62/LDX5vHZaNwcAAACHNJ3J6FKpaceMdXPtUpV5Pqi38r3rrJsDAACAQ4J2JqtLJRa8uz/WzbVJNZh/sfUX5UC+2HOtmwMAAIBDms5kdKkc7F6cPznWztUn+OLXrL8kOV8E68YAAADAIt3J6lSJadeMtXP1kQ/2f6y/JLVQui/bNwUAAACjmu5kdKrUaumasXauPsHn+UXKdw2XWjcFAAAAFulOVqdKTAt1rJ2rS7U4f5z1F6QmX+Dj9g0BAADA4TQdyuhWyUnnjPVz5Qmbem8wP3hq/eIe62YAAADgCLRDWd0qsVD23hDr58oTyuL91gdPrS6LLebNAAAAwGE1HcroVqnJ5/X+WD9XnuDdldYHT89dYt0MAAAAHIF2KLNbpaWdM9bPlUe+wAetD56W+87YTQAAAMDyaJcyO1ZC0jlj/VxZ9m/pvdz8wImF0u0duwEAAABYlqZLGR0rteB7PxJr6LEnlAvvtD5oasEXN1k3AQAAAEdXl9KljI6VmnbPWEOPPVIQP2V90NSCd1dbNwEAAABH13Qpo2Olpt0z1tBjT1W6O6wPmloo3aetmwAAAICja7qU0bHSc3fEGnps2bO4cIL9AdOS7xAOWDcAAAAAy9d0KqNrpaYdNNbR5Wdf6U6xPlhq8h3CTuviAwAA4BhopzK6VmraQWMdXX7ki3mP9cFSk+8OvHnxAQAAsGxNpzK6VnruPbGOLj/yBX3M/mBphdJdOHrhAQAAcGxq7VRG10pOOmiso8uPfDED84Ml5R4fvegAAABYIe1WZudKRztorKPLT/DFw9YHS8q7+8YuOAAAAFbqPrNzJaQdNNbR5eXAVvePrQ+UWvDuRuOCAwAAYAWabmV0rtS0i8ZaevSETb1fsD5Ier3LrYsOAACAFdBuZXautLSLxlp69ATf+yPrg6RWe3euedEBAABwzJpuZXSu1LSLxlp69MgfOH/0A6QmX8A3rQsOAACAlavL3qNW90rs/FhLjx5551tH/nAG3Netiw0AAICVC9qxzO6V1K2xlh45Bz8/933BF08aHyAxd4t1sQEAALAK2rHM7pWOdlHtpLGeHj5VOf8K6wMkNygWzYsNAACAldOOZXWv5OZfEevp4RMGC79q/+HEvLt47EIDAABgtS42u1di2kljPT18al/8ufWHk/PFWcaFBgAAwKpIx7K6V2LaSWM9PXzkHTeM/sHkvDswfpEBAACwRg6YHSytDbGeHj7yTrtG/lB6g+Ie4wIDAABgLWjXsjpYWrtiPbWza/G5zzP+UHKhdNvNiwwAAIBVa7qW0cFS024aa+p4sn1GAe82jl5gAAAArJmNZgdL7gjPLBD6vV+0/1BawRefMy4wAAAA1kDTtYwOlpp201hTx1N7917rD6Xlvm1dYAAAAKwh7VxmF0tHu2msqeOp+u4M6w+lFPquNi8uAAAA1kzTuYwulpR001hTxxMGbr35hxIK3u20Li4AAADWTtO5jC6WknbTWFPHE0r3ZesPpdXbZl1cAAAArCHtXGYXS0e7aayp45Gmvd/6QynVA3eteXEBAACwZprOZXSxlLSbxpr6zDy4/fnPtf5Act59YfTCAgAAYM19wexiiWlHjXX1ULJ9DtfSrTMuLAAAANaSdi6zi6VmPJfrvkHvF+x3TomnwgIAAJiaDJ8SSztqrKuHMszwOVyDdwfMiwoAAIA113Qvo5OlpB011tVDGWb4HK7S+ndbFxUAAAAToN3L7GQpuQ/Hunoo0rCzew5XuYC3j11QAAAATMrtZidLSDtqrKuHwnO4AgAAzLgcn8vVG8/lWpXuAeudU+I5XAEAAKYnx+dy1Y4a6+pS7rmG53AFAABAns/lql011lZ9fGvvR6x3So/ncAUAAJiaTJ/LVbtqrK1zc1V/4Wesd0ppWLrvmBcUAAAAE9N0MKObJSVdNdZW/YdZvbeY75QQz+EKAAAwfTk+l6t21Vhbmxcf+C3rndLiOVwBAACmLsPnctWuGmtr84wCp1vvlBTP4QoAAJBCds/lql011ta5ubos/tp+p5Tcl40LCQAAgEka5Pfc/sEXH4m1dW6uGhTnWe+UkpTpLebFBAAAwMQ0HczoZikNy+L8WFv1J67uKuudkvLF9dbFBAAAwCRJB7O6WULBu6tjbW0e43qj9U4phdJ90b6YAAAAmJSmgxndLCX5nLbH2qovQFDsst4pLXeJdTEBAAAwObV2MLObpaNdNdbWprg+Yr1TWr0LrIsJAACACdIOZnazdLSrNqX14I6XPtt6h9Rq784xLyYAAAAmpulgRjdL7a4rT37OXN0/YcF6Y0rSqp+0LiQAAAAmr+liRkdLad/g+BPnhpvdy6w3phRK95h1EQEAADB5TRczOlpKYVPv5XO1L37KemNa7oB1EQEAADB5wUsXMztaOsPSnTInvzh19A2p1aUbWhcRAAAAkxe0ixkdLal+8ca54Bd+3XxjWrusiwgAAIDJC97da/SzpEK58E598YE/sN6YklysndZFBAAAwOSFUrqY0dFSGvbdH86Fgfug9cak+u4W6yICAABgCrSLWR0tJe8+pC8+8BHzjQmFsrdt7AICAABgKpouZnS0lLSzzjWfoPHGtHr90QsIAACAKdEuZna0hOTzmgs5vjpCv1gcu4AAAACYDu1iVkdLSDurPh3W+aNvSK0euGvNiwgAAICJa7qY0dESO3+uLt1FxhvS8m7j6AUEAADA1Gw0O1pC2lnnQllssN6YUijdF40LCAAAgCloupjR0VLSzirF1V1tvTEp764YvYAAAACYmivMjpaQdta5yuf34Fv5nC4zLiAAAACmQrqY1dFSks6qxXWL+cak3BfsiwgAAICJ0y5mdrSEpLPqS75uN9+YUBi49eZFBAAAwMQ1XczoaGm57frKWbfZb0wnlO5C6yICAABg8pouZnS0lLSz6j/OutN6Y2KftS4iAAAApkC7mN3RktHOqi9AsGv0DakN++588yICAABg4pouZnS0xHbp87juNd6QmFtnXUQAAABMgXYxs6Olo511Tj65B6w3phS8O3fsAgIAAGAqmi5mdLSkpLPqP856xHxjQnXZ++ToBQQAAMB0NF3M6GgpaWeV4uqesN6Y0r6y+BvrIgIAAGDymi5mdLSUtLPqP84y35iUcQEBAAAwRVZHS4yfuAIAAOAZsv2Ja46PcQ08xhUAACCZbB/jKp9cfs8q0OdZBQAAAFLJ91kFeB5XAAAAPF22z+PKK2cBAADgaTJ+5Sx3p/GG1D5rXUQAAABMgXYxu6Mlo51V/3HWbdYbU5JP7ELzIgIAAGDimi5mdLSUtLPOVaXbbr0xpXrg1lsXEQAAAJMXtIsZHS0tt32u8sUW+40JefeF0QsIAACAKSmli1kdLSXprFpcF803puSLy8yLCAAAgCmQLmZ1tJSks+o/zrrafGNCwbsr7IsIAACAKbjC6mgpaWfV53HdYL0xJfnEvmhcQAAAAExB08WMjpaSdta5unQXWW9MyruNoxcQAAAAU7PR7GgJaWfVFyDI7glm64G71riAAAAAmIKmixkdLbHz54J35xhvSKtfLFoXEQAAAFOgXczqaAlpZ51rPjnjjWn1+mMXEAAAANOhXczsaAnJ56WvnPUR840JhbK3bewCAgAAYCqaLmZ0tJS0s86Fgfug9cak+u4W6yICAABgCrSLWR0tJe8+pC/5+gfmGxMKpds5dgEBAAAwFcFLFzM6WkrDvvvDuXqw8OvWG1OSi3WvdREBAAAwBWWxa7SfpRbKhXfq02GdOvqG1ELphuZFBAAAwMTV2sWMjpZUv3jjXO2LnzLfmFDw7oB1EQEAADAFpXQxo6OlNCzdKXP7N7uXWW9MKZTuMfMiAgAAYOKaLmZ0tJTCpt7L5+r+CQvWG1MKvnjSuogAAACYvKaLGR0tpX2D40+cO7jjpc+23phara/oZVxIAAAATE7TwYxultpdV578nDmNtOpHrHdIq3eBdTEBAAAwQdrBzG6WjnbVprRq5H9k95QHdekuMS8mAAAAJkc7mNHNUtKuGmurFNfSbbfeKSX5nL5oXkwAAABMTNPBjG6WknbVWFv1J67uauudkvLF9dbFBAAAwCRJB7O6WULaVWNtnZsblsX51julVJfFFvtiAgAAYFKaDmZ0s5S0q8ba2jzG9SPWOyU1cF+2LiYAAAAmqJQOZnWzhLSrxto6Nyef4OnWOyXl3e1jFxIAAACTdrvZzZJyp8faOjc39O637HdKye02LiQAAAAmSTuY2c3S0a4aa6s+q0DvLdY7pRS8O2BeTAAAAExM08GMbpaSdtVYW+fmqv7Cz1jvlNKwdN+xLiYAAAAmp+lgRjdLSrpqrK36j7N6P2K+U3JunXVBAQAAMAHavcxOlpZ21Vhb5+buueb5z7XeKTnvvjB2QQEAADApXzA7WWLaVWNtXYo07Aesd0ypHrhrjQsKAACACWi6l9HJ0nIPxLp6KMHn95xdVdnbZl1UAAAATIB2L7OTpaMdNdbVQ5HfXG+9c1I8lysAAMA0ZfccrtpRY109lKp0H7beOS2eyxUAAGBqMnwOV+2osa4eytC799rvnE7zPGLWRQUAAMCaa7qX0clS0o4a6+qh7Bv0fsF657Tct62LCgAAgAnQ7mV2snS0o8a6eihVOf8K653T47lcAQAAJi7T53DVjhrr6qE8uJ3ncgUAAJhhWT6Hq3bUWFefmeDdfusPpMRzuQIAAExejs/hqt001tTxhJLncgUAAJhJOT6Hq3TTWFPHEwb5PZerNO2d5sUFAADAmmk6l9HFUtJuGmvqeKq+O8P6QymFvqutiwsAAIC103Quo4slJd001tTx1Bk+lytPiQUAADAFGT4VlnbTWFPHE/q9X7T+UGrBF58zLzAAAABWrelaRgdLTbtprKnjyfa5XL3bOHqBAQAAsGY2mh0sOeM5XJ/KrsXnPs/+Q2mF0m03LjAAAADWQNO1jA6WmnbTWFPtyDvtGv1DyQ2Ke6yLDAAAgDWgXcvqYGntivX08JF32jDyh9Lz7sDYBQYAAMBaOWB2sLQ2xHp6+NS++HPjD6bni7OMiwwAAIBVkY5lda/EtJPGenr4hMHCr1p/ODnvLh6/0AAAAFili83ulZh20lhPD59sn1lgUCwaFxoAAACroR3L6l7JHeEZBZ7Kwc/PfV/wxZP2B0jJ3WJebAAAAKycdiyze6WjXVQ7aaynR478gVtHP0BqoXRfNy82AAAAVk47ltG9Ers11tKjR975/JE/nFxd9h41LzYAAABWLPjeN63uldj5sZYePfIF/JHxAZKrvTvXuuAAAAA4dk23MjpXatpFYy09esKm3i9YHyS93uXWRQcAAMAKaLcyO1da2kVjLT16Dmx1/9j6IKkF7240LzoAAACOWdOtjM6VmnbRWEuXl+CLh60PlJR3941ecAAAAKzYfWbnSkg7aKyjy09duoH1wdJyjxsXHAAAACuh3crsXOloB411dPmRL+Zj1gdLTb6YC8cuOgAAAI5J0E5ldK3kpIPGOrr8SAN/j/nBEgve+dELDwAAgGPTdCqja6Xn3hPr6PKzr3Sn2B8sNbfTuvgAAABYvqCdyuxaaWkHjXV0+dmzuHCC9cFSk+8ODlgXHwAAAMvXdCqja6WmHTTW0WNLVbo7rA+YmnyH8GnrBgAAAODomi5ldKz03B2xhh57gi8+ZX/QtOQ7hKutmwAAAICja7qU0bFS0+4Za+ixJ5QL77Q+aGp1Wdxk3QQAAAAcnRTEm6yOlZp2z1hDjz3B937E+qCphdLttW4CAAAAjq7pUkbHSm3/lt7LYw1dWeSLe9D6wGm574zeAAAAACyTdimzYyUknTPWz5UneHel+cGTc5eM3QQAAAAcmXYos1ulpZ0z1s+Vpy6L91sfPDX5vLaYNwMAAACH1XQoo1ulFqRzxvq58oSy9wbrgyfXL+6xbgYAAACOQDuU1a0SC5t6b4j1c+WpFuePsz54aqF0j5s3AwAAAIfVdCijWyUnnTPWz9VFvsAvm39Bar641LohAAAAsEh3sjpVYsG7L8faufrUvvg/1l+SWlOozZsCAACAUbn+MDJI14y1c/WRD/Zr1l+SnC+CdVMAAABgke5kdarEtGvG2rn67F6cP9n6S3IQvDvXvjEAAAB4StOZjC6VhcH8i2PtXJvIF3u/+RclFnzvOuvmAAAA4OmkMxldKj339Vg31y6hdBfaf1la8nnttG8OAAAAntJ0JqNLpaYdM9bNtUsoi9+1/rLU6rL4hnVzAAAAcEjwxaNWl0pNO2asm2uXPX7+NdZfloMwcOutGwQAAIDm8a3rrQ6VA+2YsW6ubarSPWD9hRnYat0kAAAACO1KdodKzD0Qa+baR/6CC8b/wgwM3NfNmwQAAAB9mECm/8i++GysmWufYd+93fpLs9DvnW3dKAAAgJmmHcnqThmoS/f2WDPXPnvKhR+y/tIchNJdZd4sAACAGSbl8CqrO+Vg73XFD8eaOZnIF3+T9RenFnyxw7pZAAAAs6zpSEZ3Si14d3Osl5OL/CUftP7y5Lx7aPRGAQAAQDqS1Z0S004Z6+XkUvUX/r31l+fBXWLcLAAAgNmk3cjsTOnt6S/8TKyXk8vBg3PfIxfhMesTSC303c3mTQMAAJhBTTcyOlN67rGDfzz3vbFeTjahLDbYn0RagYcLAAAA/J2mGxmdKTXtkrFWTj5D795rfRJ54OECAAAAOT9MoJYuGWvl5PPADcW/sD6JHEiDv8m8eQAAADOk6URGV8rBXl+8NNbK6ST44m7rE0mNhwsAAABk/DAB6ZCxTk4voXQftT6ZPPBwAQAAMMMyfpiAdshYJ6eXUC78J+uTyQEPFwAAALMs54cJaIeMdXJ6qRbnj7M+mRxIkz9g3UQAAIBZ0HQhoyPl4I7B8T8Y6+R0E3xxvfUJ5YGHCwAAgBmU88MEpDvGGjn9VP3i96xPKge15+ECAABg9jQdyOhGWZDuGGvk9FMN5l9sflIZ4OECAABgFuX8MAHtjrFGpklduoH5iWWBhwsAAIAZkvHDBLQzxvqYLvKJZPtwgcDDBQAAwAxpuo/RiTKR7mECT2X34vzJxieWBbl537BuKgAAQBc13cfoRDnQzhjrY9qE0m22PsEcBO+utm4sAABAlzSdx+hCOdCuGGtj+sgnlO3DBapBcY91cwEAADpFO4/VhfKQ/mECT6Xaku/DBZa4deYNBgAA6ALtOmYHyoR0xVgb80goi3wfLlAWW82bDAAA0AXadYwOlAPtiLEu5pOq737f+mSz4N3+sRsMAADQHfvNDpQD6YixLuaTr2864SXmJ5uN3gbjJgMAALSbdhyz++RBO2Ksi3ml8sUW6xPOg7vDvNkAAAAtFrzbaXefDEg3jDUxv1SDfB8uMPTuu5XvnW3dcAAAgHbqnd10HKP7ZEG6YayJ+aXO/OECoXTevukAAADt03Qbo/PkQrthrIl5Rj7JbB8uIDd3aN10AACANmq6jdF5MpHvwwSeilzE9xmfeDZq79aP3nQAAIC2aTqN0XWyIZ0w1sN8Uw3mX2x+8tlwt47eeAAAgNbRTmN2nUwsZvaiA4dL8O4K8wvIgnvMvPkAAABtop3G7DrpaReMtTD/BN/7FeuLyIfbZC4AAACANtAuY3acPGgXjLWwHZELWltfSA5CXz43axEAAAC0QNNljI6TB1fHOtieyCd9hv3F5CF4d6W1EAAAAHLWdBij2+TDnRHrYHuyp7/wY/YXkwnf22UtBgAAgLxJh7G6TSZq6YCxDrYrtXel9QXloi57F9oLAgAAID9NdzE6TS60+8Ua2L6EsvgN64vKh/uqtSgAAACypN3F7DR50O4Xa2D7Mrza/UDw7gnrC8uCbx7req65MAAAADKy1FmMPpMJ7XzDm90PxBrYzgRfnG19cbmQi3yjtTgAAABy0nQWo8vkQjtfrH/tzb7SnWJ9cdnwvUetxQEAAJAX6SxWl8mEdr5Y/9qdyhd5vyQZL0gAAABylvkLDmjXi7Wv/ZEL/j7zi8wEL0gAAABylvcLDgjperH2tT/3DY4/0fwiMxJ4QQIAAJChpqMY3SUn2vVi7etGQumyft4xwQsSAACA/GhHsbtLFrTjxbrXnYR+7xetLzYrfv4ac8EAAAAkId3E6iwZ0Y4X6163Ijdgp/UF58PdOb5gAAAAEtFuYnaWTEi3izWvewm++B3zi85IXbqLxhYNAADAlNVl7yKrq+REu12sed3L7i0nfb98gY9YX3g+3F3W4gEAAJiyu+yukgftdNrtYs3rZoJ3H7S++JzU3q03Fg8AAMBUSF9ab3WUnGini/Wuu6kG8y+2vvicDL2721pEAAAA0xBK6SJGR8mKdLpY77qdqnSfMS9ARuoBP3UFAADT13QQo5vkxX0m1rrupx4svM6+CPmoy4KfugIAgKlrOojRTXKiXS7WutmIfNHXj16E7Hh38ehiAgAAmKCLzU6Sl+tjnZudDPvuzcaFyErwxdeMBQUAADARTfcwOklOtMPFOjdbkRuU+QsSKHfJ6KICAABYc9o5zC6SkS6/4MDRok9aa16UnPjinrGFBQAAsNb60jmsLpIR7W6xxs1e2vGCBIqfugIAgAlqwU9btbN1/gUHjpY2vCBBNeCnrgAAYIK0a1gdJCMz8YIDR0sbXpBgSW+DudAAAABWQzuG2T0yMysvOHC06JPYmhcoJ77YYy42AACAVZGOYXWPrMzQCw4cLW14QQIV+sWiveAAAACOXdMtjM6Rm5l7wYGjpSUPSn7YWnQAAAAr0XQLo3PkxV0S6xp5Kns2teSnrt7daC08AACAY9F0CqNr5EY7Wqxr5OmRm5j9y5zJIvuu/Pczo4sPAABg2aRLxE5h9o1sSDeLNY2MpvILrzEvWmZC6W4fW4AAAADL1HQJo2NkR7pZrGnEinz3cZF54bLDixIAAIAVaMG/61HayWI9I4dLGPReZV283MjN3G0uRgAAgCNoOoTRLXKjnSzWM3Kk1GXxeesCZse7a0YXIwAAwBFcY3aKzGgXi7WMHC2h7P1b6yLmRr5j2m8sSAAAAFPTHYxOkRvtYrGWkeUk+OJz1oXMzdAXN1gLEwAA4OmazmB0idxoB4t1jCw3w757pXUxcyM394kwcOdYCxQAAEBpV9DOYHWJ3GgHi3WMHEvk4l0wejGz5Isd1iIFAABYIl3B6hD5uSDWMHKs2Tco/rVxQTPVu9xeqAAAYKZpRzC7Q360e8UaRlYS+Q7lPOvCZse7fWMLFQAAQDuC1R1yI50r1i+y0uwtF37cvLgZCvqaw/aCBQAAs+lGqzPkSDtXrF9kNalKt866wDkKfXehsWgBAMCMaTqB0RXy5NbF2kVWm/qGE15iX+QMeXff6MIFAAAz6T6zK2RIu1asXWQtEnzxZ9aFzlOvbyxeAAAwK7QLmB0hP9qxYt0ia5WDiz/890NZ7LUueHa8ezx4d+7YIgYAAJ0XO8DjZkfIjHYr7VixbpG1TOWLd1kXPUve7Xz6IgYAADNjp9kNciTdKtYsMonIRd42dtEzJd9xXWUsZgAA0FF1KbPf6ASZ2hbrFZlUht79nHHhsyTF9YC1qAEAQDc1s9/oBDnSThXrFZlkQukusm5Ajoa+uMla2AAAoFuamW90gRxpl4q1ikw6VTn/Cusm5GrYd5dYCxwAAHRDM+uNDpCv+VfEWkWmkWrg/tK+EfkJvqisRQ4AALpCZr3RAbIkHSrWKTKt7N5y0gukED5k3pAMhZKHDAAA0EXNjDdmf460O2mHinWKTDNy8f+7dVNyFQbuSmvBAwCAltLZbsz8XGl3ijWKpIjcgNusG5Mj+Y7s4cr3zjYXPgAAaJne2c1sN2Z+jrQzxfpEUqUui1+ybk62vLtjfOEDAIDWKWWmW7M+U9qZYn0iKRN8u35MX/nienMDAACAVtjri0VzxmdKu1KsTSR19m4ufsK6SbkKvnhCFv15o5sAAAC0wnnNLDdmfK60K8XaRHJIVboPWDcqV/Kdz73GRgAAAPm715rtuRr23Z/GukRySuWLHdYNy9XQFzcYmwEAAGSqmd3GTM+WdKNYk0huqb37OfOmZaweuPXWxgAAAHlpZrYxy3Om3SjWJJJjgi/Osm5cxoK1OQAAQGZ0ZtuzPE/SiWI9Irlmz+LCCcG7B8wbmCleVQsAgLy16dWxlHYh7USxHpGcE/q9d1g3MWd1WVxtbRQAAJBWM6ON2Z0z7UKxFpE2RG7ahtGbmDXvHq/K3gWjmwUAACQkszk0M9qY3fnaEOsQaUv2l+5fGjcyb77YY24aAACQiMxma2ZnbLjoXhbrEGlTgi9Os25o1nxxm71xAADAdMlMtmZ1xmrpPrEGkTYmeHejdWPz5vr2BgIAAFOhs9ic0fnSzhPrD2lrgu+93rq5uasH7mJzIwEAgIlqZrAxm3OnnSfWH9Lm1GXx19YNzpp3+6tBcdboZgIAABMkszfoDLZmc8aCLz4Saw9pew5uX/gHVel2Wzc6Z7Jx7jY3FQAAmIihzl5jJufN7dauE2sP6UJkIf6yfbOzt9XaWAAAYI3pzLVncda048S6Q7oUWZRnWjc8d8G7K8c2FwAAWDNS/q60ZnD2pNvEmkO6lu3b554lJfB288ZnrfdoXbp1o5sMAACs3tKM7T1qz+B8aafRbhNrDuliQtn7aevm504W525rswEAgNVpZqwxe3OnnSbWG9LlVAP3J9YCyJ4vdlgbDgAArJTMVmvm5k66TKw1ZBYSWvjEwg3f22ZvPAAAcGxkplqzNnuuH+sMmZVU5fwr7MXQBr3r7A0IAACWRWepOWPbYP4Vsc6QWcrQu/faCyJ/dVlcam5EAABwRM0MNWZrG9TSXWKNIbOY4N16a2HkTjbdN4alO9/akAAAwKazU2eoNVtzp50l1hcyq9l97QteKAvhAWuBtECoNrtPWBsTAACM0Jmps9OeqVnTrqKdJdYXMssJm3pvsRZJGwz7xT3m5gQAAM/QzExjlrZBKHtvibWFkOYpsj5mLZR2cLdYGxQAAEQ6K80Zmr+hfP6xrhCylIM7XvpsWdR3WAumDULpNpsbFQCAGdfMSGN2toO7QztKrCuEHEooe2+wF01LeLdxdLMCADDjNpozsyW0m8SaQsh4gi9OsxZOG8h3lN+pB+5iY9MCADBzdCbqbLRmZhtoJ4n1hJDDRxbK56wF1AbyuT9S9XsXWBsYAICZIbOwmYnGrGwD7SKxlhBy5FQ75o8Lvr2Pd61Kt1+sMzcyAABdpzOwmYXWjMxf00EW54+LtYSQo6faPP9qazG1hXynVtVl75PmhgYAoKOWZl9RWbOxNaSDxDpCyPITBsVvmguqJaS83l8N7I0NAEDnyMxrZp8xE9tCu0esIYQce0LpPmotrPbo7TI3NwAAHRO8zDxzFraDdo5YPwhZeWQhDawF1hbBu7utDQ4AQFc0s86YgW2hXSPWDkJWl32bF/55m/9lYsO720c3OQAAnVDKjLNmX0tox9CuEWsHIatPXbo3WYutXXhpWABAt8h8bu1LuT5lKB0j1g1C1i5S/D5gLbg2CaX7srXxAQBom2amGbOuTaS0fiDWDELWPsEXl1kLr2W2WgcAAACtobPMnnGtoZ0i1gtCJpPhZtcL3t1rLcA2qb0rzYMAAIDMNTPMmG0ts0s7RawXhEwuoez9tLEAW4fyCgBom46U1oPaJWKtIGTyqUr3bmshto53W0YPBQAAMrXFnGWt494d6wQh00soi/9lL8jW4TGvAIC8deAxrUq7Q6wRhEw/lS/OsxZm24TSfck8KAAASKyZUcbsah3pDLE+EJIuwTtvLtDWcdutAwMAgGR0Npkzq120K8TaQEjaPLD1hSfJovzb0UXaRkNf3GQeHAAATFkzk4xZ1UJ/q10h1gZC0icMeq+ShfntkYXaUrzCFgAgsQ68Ilb0be0IsS4Qkk+68bKwkS9uMw8SAAAmTmaQNZtaSLtBrAmE5JdQFr9rLdx2cl+1DxQAACZEZ485k9pHO0GsB4Tkm2rg/tJawK3k3R1jhwoAAJNxhzmL2ki6QKwFhOSfULqLzIXcQvId493G4QIAwJppZo0xg9pIO0CsA4S0I3ddefJzZPFuG13MLXZ/8O5c67ABAGClmtkiM2Zk5rTZNu0AsQ4Q0p5Ui/Mny3eQe41F3U7e7a/L4vOjhw4AACsRZ8p+c+a0UDPzZfbHGkBI+7KvdKdYi7u93GNV2dswevgAAHBMdJY0M8WaNe2kMz+Of0LaG1nMp44u7rarS3eteRABAHAUzQwxZkvLnRrHPiHtjyzot44s8NYLpdtsHUgAABxOMzuMmdJyb43jnpDupPLFu4zF3mq8RCwAYLk69BKuh8hsj2OekO6l6rvfNxd+iwXvdloHFAAAT2lmhTFDWk1mehzvhHQ3VelONzdAi4W+u6/yvbOtwwoAMMt6Zzczwpgd7eZOj2OdkO5HNvOH7I3QZq4O/d4F44cWAGAWNTNBZoM9M1pMZngc54TMTmThf8zcEG3m3TeDd1c8dWgBAGZTnAXfNGdFm8nsjmOckNmLfCe6ztwYLScHFs84AAAzqpkBxmxoP7cujm9CZjeyES6xN0jbua9aBxoAoMP07DdnQtu5S+LYJoRUA7fR3iitt6ceuPPMww0A0BnNWS9n/sgM6AaZ0XFcE0I01eL8cZUvtpgbpu30MU487hUAuqybj2dVOptlRsdxTQh5KrIxCtkgt5obpwNqXmkLADqnOduNM78TdCbLbI5jmhAymvv7J74oePcVcwN1wYDHvQJAZ+iZbp31HaCzWGdyHM+EkMMl3NBzsmm2jm6izvDFnmHfnW8eggCA7C2d4R19POuSrTqL41gmhBwtD5U/9PyqdN7YTB3RPN/rldaBCADIV3N2yxlun+3tJ19fufuqk14QxzEhZLmJ/2DrOmtjdchW62AEAGSoy/9v4JLr+IdYhKwiB3e89Nl16b5obK4O6e2Sr3GdeUgCAJJrzmg5q+0zvBtC6a7SmRvHLyFkpTl4cO57Kl9cZm20zvDuW81z2RoHJgAgoaWz+Vvm2d0VMmN11saxSwhZi8h3gxeZG65T3C1jhyYAIA09k82zujuCd+vjmCWErHVCWVxgbbxO8UWoy95F5iEKAJi4pTO4COYZ3S0XxPFKCJlU5LvDc43N1zlh4ErrQAUATE5z9hpncteE0n06jlVCyKQTfHGWtRE7x7u75Dv/T44erACAtRXP2rvMs7hrZIbGcUoImVbku8WPmhuyY6SkP1yVzetgm4ctAGCV5IxdOmvtc7hTvDszjlFCyLQz7LszzI3ZSW772GELAFgdPVvNM7eL3BlxfBJCUkUOnv9hb9DuGXo3lIPnkrGDFwBwbOQsXTpT7fO2c2RWxrFJCEmdqu/eZm7UjgrefXnsEAYALEso5Qw1ztbOGri3xXFJCMkldVn8h+CLR8xN20F16epQ9jZYhzIAYJyemXp2WmdqF+lM1NkYxyQhJLfUWxZ+TDbq3dYG7qrg3c3WAQ0AOCQM5Kw0ztCuCmVx995y4cfjeCSE5JqvL77wpFC6gbWRO8u7B6uBu3L0oAaAmbd0Nj5onp0dpTNQZ2Eci4SQ3LN9+9yz5Lvr9daG7rRBsWOfPsetdXgDwAxZOguLHeZZ2WXeXXxQZmAch4SQNkU28Jnmxu6wYb94ZOjdxqcf4AAwYzbO0r95+Ds8Rysh7U9VutPNDd5xwbudYeDOGTnMAaCz9MzTs886E7vPnR7HHiGk7al88S57o3ebHOCP1d6V1gEPAF2iZ52eedZZ2Hky4+K4I4R0JbK5Tw1l8e2xDT8LfBGC7/GysQA6pznbyiKMnXszIM60U+OYI4R0LXvKhdfqU4SMbv6ZMXB3DvvufOvwB4A20bMsyJlmnnUzQGeZzrQ43gghXc3D2048Xjb9htFDYFYEXzxZle5L1iAAgDYIcoaFvp5l9jk3AzboLItjjRAyCwnefdA4DGaGfP0H6oG7xhoKAJAlObP07LLOtFmhsyuOMULIrKUu3dutg2G2uHvlIFxvDgkAyMBQzyg5q+wzbHYMZWbF8UUImdVUfuE1ciDcNXpAzB53SzXonW0NDQBIQs8kPZvMM2t2BJ1Rfv41cWwRQmY99+vjXn1xmXVgzBTvvhV4+iwAGYhn0bfMs2qWyGy6/xoez0oIMVKXxV+YB8fMcQeqQbE4OkgAYOL07NEzyDybZkuQmRTHEyGE2KlL91+tA2QWhdLtG/bdteZwAYA1pGeNnjnWWTSLdBbFsUQIIUdOtXn+1cE7HvcayTAZyiF6lTVsAGA19GzRM8Y6e2aTu1NnUBxHhBCyvDy05aQXBB73OsJ9vSp7l1vDBwCOiZ4lzZlinTUz61KdPXEMEULIsUfKK497HRG8u1cGz6VjgwgAju5SOUd2jZ4rs05nTRw7hBCyulT94o1ysMzka2EfiRy0XwsDngMWwNHpWaFnhnWWzLigMyaOG0IIWZvcNzj+xKp0lxiHzswLfXfn0LuLrWEFYLbp2aBnhHV2wF1S909YiGOGEELWPnIQv88+gCCHsL4K1xWjgwvADCrlLODVrg5PZkkcK4QQMtns2bTwOjl4bh07iNDQfyEcfO+6sUEGoPN07/MsAUd0q86QOE4IIWQ6OXhw7vuag9o+mCCCdwdC3w2qwfhwA9Ahssd1r+uet84CRHKtdHbEMUIIIdNP1Xdvk8Pom+YhhSXefasu3Y0y1M79u0EHoPV0T+vell/z0qxHIjNiKLMijg1CCEmb+wcn/jM5nK4dO6zwDMEXT1a+uE1+/dmnDz8ALdPs4eK2Zk8bex1P0y+urf2J/zSOC0IIySdD7/6neXBhTPDubhl8l5lDEUCmisuavWvsaYzTmRDHAyGE5Jm9m4qflcOdJ9deJn1t8rp0m+uy9yl7UAJISfem7NPNuletPQyDzACdBXEsEEJI3jlw03Of1zye0zrQYAr94km5ZjurAT+FBfLQ/HR1p+5Na8/Cpme/zoA4DgghpD2pS/cmGQD3WYcbDk8O/n1ic+CnsMBU6Z4b6t6TPWjtTRxeKN3uYd+9OR7/hBDSzlSL88dVpTvTOuhwZKEsvisD9I7KF5daQxbAWiku1b2me87aizgaOePlrI/HPiGEtD/D0v28DIad9qGHo3N18zyR/d4n7cEL4FjoXgqlG+jesvccjkrO9H1ytsdjnhBCupWDB+e+d9h3Z5gHIJZFyr/+FPbuuiyuHh3EAI5O947uId1L1h7DcrkzDn6eFxMghMxA9vne62Vo3GQfhlguuYZPyCC+oxq4K0eHM4CnWdojdzR7xthLWD49u0PZ++l4nBNCyOxEvmP/gHUwYiXcNytf7KjK3oaxoQ3MomYv6J7glf3WyrDv/jQe34QQMpup+vOvDmWx2ToksWKPyLC+RXzBHOhAV+mab9a+7gFzb2AFhr7Yomd1PLYJIYQEX5xmHZhYnVC6A8G7r4j15qAHWk7XdrPGZa1bewCro2dzPKYJIYQ8PfdvOvFfyfD5onV4YvVkuEuJLW4L+ni/vvuEVQKA7OnalTXcrGVZ09Zax+rpWaxncjyeCSGEHC5hsPCrMpS+Zh2mWBsy8L8j/90l/y2rsneBWRCAXMgarXWtendvXLvmusbq6dmrZ3A8jgkhhCw3VelOtw5WrD0ZVvvDwN0sBeHysdIApKBrse9u0bVprVlMgjs9Hr+EEEJWknrTCS8ZlsX59iGLSZCi8P+qQXGPFIe+FIjzxgoFMBnn6ZqrZe01a9BYm5gMPWP1rI3HLiGEkNVGhtnPBu9utA5dTJZc932VL26rSndtUy7s0gEcKymquqaax6rus9YeJkvPVD1b4zFLCCFkrVOXvf8WyuIh6xDGdMj1f1gKx50y9Hwo3YVGIQHGxLXim7XTrCF7fWHy9AzVszQeq4QQQiaZPYsLJ8gQ/L/WgYwU3GPy311ia+WLS6uBXVwwQ5o1IGtB10SzNpo1YqwdTJuenXqGxuOUEELItBIGvVfJkNxoHc5IJ+hrwPtijwxIfW7NL8o94uEFHVfLPdZ7rfe8ufe6Boy1gYTkrNQzMx6fhBBCUkUO5bcK/YmffWAjOSk0jy0Vmuaxsv164C6W/33WaAFC7oqz9N7J/ew393LpGxR+mpq3XXv7xX+JxyUhhJBcUvWL35NBWhkHN3Ll3YNSgL5W+d6XpABdVQ346Ww25F7UzU/M5d4098g9aN5D5EnPQjkT4/FICCEkxzx518nPCWXxfvEN8zBH/gbuMSlKe+qyuG3oixvkv1fXZe+iUPY+NVausCp6TfXa6jWO1/o2vfZ6D8x7g+zp2adnoJ6F8VgkhBCSe+4rf+j59aD4MznAeZWdDtH/W7ouXV17fa5Pd7Mohb785+cEDz0Yoddk6droNWqu1c167Sq5hvxf/N2iZ53c6z/Xsy8eg4QQQtqWfYPjTxz64n9bBz066VEpZENxl5SzW4LvbZOypo/HvLryxaWxxJ279K/eW0o+d/0a9GuJX9PVS19jb1vzSlPytes10Gsxcm3QVXLG6VkXjz1CCCFtz+7F+ZOboW8d+phNzUMS3ENScIPQ18DfKW6Wt22V/3opA4tSBq+TdbNRiuAX5ddXSEm8TN73kjBw60NZfF5fQ1/erv+i/tPyZ86pfO/sarP7REN+rb+nb9P30ffVP6N/tvkY8rGaj7n0zAsbl/4u/Tv1uU6bz0F/orxTPzf9HOXXD/F/4eMZ9EyTsy0ec4QQQrqWsKn38qrv1plDAABawa3Tsywea4QQQrqeB7a4V4bSXWQPBQDIj55ZenbFY4wQQsisZVi6U0JZbLCGBADkQM8oPavisUUIIWTWM+y7V+rjEa2hAQAp6JmkZ1M8pgghhJBnphrMv7gq3YdlYDxuDRIAmKSls8d9WM+ieCwRQgghR86Bxec+L/jiNLHHGi4AsJb0rNEzR8+eeAwRQgghx54wKH5TBsuto4MGANbArXrGxOOGEEIIWZvUZfFLoXSbjMEDAMdEzxI9U+LxQgghhEwmwfdeH7w+ibw9kADgcPTs0DMkHieEEELIdFIN5n+0eeWakn/IBeBI5IxoXq53/kfj8UEIIYSkSbU4f9yw794tA2rb+MACMMO2NWeDnBHxuCCEEELySVUuvHboi7+pSveEMcQAdJ57YukMWHhtPBYIIYSQvLNvcPwPDvvuPcG7G+3hBqBLdK/rnte9H48BQgghpH2pBwuvC744K5TFt62BB6CddE/r3tY9Hrc7IYQQ0o08sPUF/3Do3W+F0m23hiCAdtA9rHtZ93Tc3oQQQkh3U28ufjL44mwZgI9ZgxFAXnSv6p7VvRu3MSGEEDJbObh97lnB934leHeRNSwBpKV7U/eo7tW4bQkhhBCi/6ijGri3ybDcMDo8AUzVBt2L/EMrQgghZBnZ64t5ff3yyhfXGEMVwFqTvaZ7Tvde3IaEEEIIOdbc3z/xRaG/8NvBu9IcuABWRPeU7i3dY3G7EUIIIWStUm2ZP3nYd3+gzxlpDWIAR6Z7R/eQ7qW4rQghhBAy6Qw3u5c1A9gX11sDGkAke0T3iu6ZuH0IIYQQkioHFp/7PBnMbw794pNV6e43hzcwM9z9uhd0T+jeiNuEEEIIITlGBvYrZXC/P/TdwB7sQLfoWtc1r2s/bgNCCCGEtC3NMxT44teqvlsXSldbQx9om2Yt65qWtc0zARBCCCEdTeUXXlN59yehLLZZhQDIVbNmZe3qGo7LmRBCCCGzkuFm1wt+4T9KIfiLUPKwAuSlljXZrE1Zo7pW47IlhBBCCJmbu+vKk58zHLh/F3xxmhTZK6Q8HBgtE8AkyJp7qJI1V8va2ydrUNdiXJaEEEIIIcvLnv7Cjw377j1SLs6XYnHvaOEAVqZZS7qm3lPLGovLjRBCCCFk7RLK3j+pfPGfK+/OlOJxyzPLCHBYtzRrRtaOrqG4nAghhBBCppfdW076/qF3/6Ye9N4RyuKvQ99tkoKy3ygumAVy73UN6FrQNaFrQ9dIXC6EEEIIIflluOj+0b7S/XzzeFlffK4q3e1m0UGLudv13uo91nut9zzefkIIIYSQdkd/8vbAFn1xhN47pPj8VeWLxcBPZ7PX3CO5V/Lrv9J7p/eQn6ISQgghZCbzyPaFE/ZuLn5iWLo3VQP3vqp0Z4bSXVV5t1NK0xOjRQprq7nGS9dar/mZeg/0Xug90XsTbxMhhBBCCDla7u+f+KJ6sPA6KVlvDb7447osPiXFdpMUrftGSxhseq30mjXXTq6h/N5b9ZrqtY2XmRBCCCGETDIHF+f+Xr3phJfUm4uflDJ2qpSxX69K94fD0n1Yyto5oSwuF1vF3VLcOvO8tPq16Nckv94qLq8H7hz5uj+sX3soF94pv3eqXhO9NnqN4uUihBBCCCFtyfaPzz2rWpwvhovuZbUvfqoaFG+UAvgbUnj/qPLuQ8EXH5H/frwpvf3iAvnvevm9y+X3Nsqv+5UvbpD/fkX+u0N+/275/fvk10F+74D8+pvye99RS7/W3yuCvs/S++qfaf6sfgz5WPoxpVjr37H0d50jvyd/d/M5fEg/J/3c9HOUIn7KcLN7WbVtvtCvIX45hBAyI5mb+/9ZD6N3rTDbJQAAAABJRU5ErkJggg==\",\"data:image/png;base64,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\"],\"index\":[0,1,1,0,0,2,3,0,0,2,3,0,1,0,3,0,3,0,3,0,4,2,5,0,0,5,5,0,2,2,2,2,2,2,5,5,0,0,0]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 21FLHILL_WQX-101<br>Sample Condition: dry<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: wet<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: wet<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: dry<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: dry<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: dry<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: dry<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: dry<br> Category: 130 - 999 (908/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-109<br>Sample Condition: dry<br> Category: < 35 (1/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-133<br>Sample Condition: dry<br> Category: > 999 (3100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-144<br>Sample Condition: dry<br> Category: 130 - 999 (620/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-2<br>Sample Condition: wet<br> Category: 130 - 999 (280/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-560<br>Sample Condition: dry<br> Category: 130 - 999 (600/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-561<br>Sample Condition: dry<br> Category: > 999 (3500/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-594<br>Sample Condition: dry<br> Category: 130 - 999 (300/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-595<br>Sample Condition: dry<br> Category: > 999 (6100/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-596<br>Sample Condition: dry<br> Category: 130 - 999 (580/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-597<br>Sample Condition: dry<br> Category: > 999 (1350/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-598<br>Sample Condition: dry<br> Category: 130 - 999 (525/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-74<br>Sample Condition: wet<br> Category: 35 - 129 (85/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-32-03<br>Sample Condition: dry<br> Category: < 35 (20/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-44-02<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SC-01<br>Sample Condition: dry<br> Category: 130 - 999 (480/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-112<br>Sample Condition: dry<br> Category: 130 - 999 (220/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-180<br>Sample Condition: dry<br> Category: 35 - 129 (56/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-264<br>Sample Condition: dry<br> Category: 35 - 129 (40/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-592<br>Sample Condition: dry<br> Category: 130 - 999 (320/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLDOH_WQX-MANATEE152<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-22<br>Sample Condition: dry<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-48-03<br>Sample Condition: dry<br> Category: < 35 (31/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-CENTRAL CANAL<br>Sample Condition: dry<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-COSP580<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-NORTH CANAL<br>Sample Condition: dry<br> Category: 35 - 129 (41/100mL)<\\/html>\",\"<html>Station Number: 21FLCOSP_WQX-SOUTH CANAL<br>Sample Condition: dry<br> Category: 130 - 999 (360/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-01<br>Sample Condition: dry<br> Category: 130 - 999 (717/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-39-05<br>Sample Condition: dry<br> Category: 130 - 999 (727/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Dry samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Wet samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.535934301,28.0257081],\"lng\":[-82.74574933,-82.381683]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Old Tampa Bay only show_enteromap(enterodata, yrsel = 2020, mosel = 9, areasel = \"Old Tampa Bay\")  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.862940001,-82.74574933,28.0257081,-82.562595273,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addMarkers\",\"args\":[[28.0257081,28.010599,27.997414662,27.981868039,28.020482621,27.928402531,27.923464624,27.912087245,27.862940001],[-82.63164009099999,-82.607803,-82.586513802,-82.562595273,-82.68955061299999,-82.74574933,-82.717654432,-82.70025344,-82.61633],{\"iconUrl\":{\"data\":[\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEb3SURBVHhe7d0LuOVXfdf/qNVqqdVq1WpVtE2BzFm/E8qQs9YOaVNFba1Si5ZWi/aixabFWq2lWou2tYpSWkWptn8ghABhIAm5EBISchlIMnPWb8/kThKSkAuEW4AkJIFyCYH/93tmAZPf+WRyzplz+f72fr+f5/WkT5OZs8/e67e+38OTyzFERLT5dVc/++mpL6ekPr/cnJVqvsb++MCKlf+7nHXoz5VT/K9tv4yIiIiIKGbdcv5BW17P6/ry5fVY+TX2a9tvQ0REREQUo66Wl3R9vlUtsetjv4f9Xu23JSIiIiLamXbtPfkbU1/26KV14/z39N+7fRkiIiIiou1rYX95ji2ltwyX1E10i3+N9uWIiIiIiLa+hT7/rFhMt4R/rfZliYiIiIi2roV9kxPVQrqV/Gu2L09EREREtPntPrj7G2zxvHm4iG6Dm/1rt5dBRERERLS5pZrPEEvotvCv3V4GEREREdHmdehfIaaX0G3Dv3qMiIiIiDazXf0J35r68mm5fG4jfw3+WtrLIiIiIiI6urqaf08tnjvCXkt7WUREREREGy/1J0zkwrmD/DW1l0dEREREtLFSzRerZXMn+WtqL4+IiIiIaP3ZUvljwyUzkB9rL5OIiIiIaH2lWm4TC2YI/trayyQiIiIiWntdn39VLZix5F9tL5eIiIiI6MlbmD77r6RavqCXyzj8NfprbS+biIiIiOjIdX1+rVosY8qvbS+biIiIiOiJ6/rJ9+iFMrLJ97SXT0RERESkS32+XC+Tcflrbi+fiIiIiGh1tjT+xHCJHJGfaN8GEREREdFhffmYP5T6cpdYIEfBX7t/D+27ISIiIiI6VNfnX1cL5LjkX2/fDhERERGRLbnTk75dL44jZN9L+7aIiIiIaN5LfT5dLo0j5N9L+7aIiIiIaJ7r+slz1cI4bpPntm+PiIiIiOa11Jcr9bI4Xv49tW+PiIiIiOaxbjm/SC2KM8G+t/ZtEhEREdE8dexFx3596su9ckmcAf69+ffYvl0iIiIimpe65fwytSDOFPse27dLRERERPNQ2jd5hlwMZ5B/r+3bJiIiIqJZL9WyRy2Fs8i/1/ZtExEREdEs1y3nv6sWwnWZiv9fZPY9t2+fiIiIiGa11Jcql8H1mk70/z8g/57bt09EREREs1i3nH9OLYIbMr7/Vffn2ttARERERLPUrr0nf2Pq831yCdyoES27/r37e9DeDiIiIiKalWzZe8Vw+ZtDr2hvBxERERHNQt2B0omlb3OM7W9hsPeivS1ERERENPZSX86WS98c8veivS1ERERENOa6af5BtfDNNXtP2ttDRERERGMt9fkauexttnH9g2nXtLeHiIiIiMZYN82/oBY9GHtv2ttERERERGOqu/Gkb059fkAuefD/VfcBf4/a20VEREREYyn15ZVqwcPX+HvU3i4iIiIiGkPdgfIstdhBsPeqvW1EREREFL3Ul/PlUodV/L1qbxsRERERRa6rSz+sFjocgb1n7e0jIiIioqilmm+Sy9x2q+L/F5S/Z+3tIyIiIqKI2XL5ErXIYQ3svWtvIxERERFFKi3nv5Bq/rRc4nZIEv+/qPy98/ewvZ1EREREFKVUy/9TCxzWzt/D9nYSERERUYS6ulTU4oYNsPeyva1EREREtNOlmt8plzasm7+X7W0lIiIiop2sq5N/ohY2HAV7T9vbS0REREQ7Var5fXJZw4b5e9reXiIiIiLaibpa/qNa1LAJ7L1tbzMRERERbWddXfrLtox9Xi5pMX24UX8uHn9v7T1ubzcRERERbVep5tfIBS2o1E/e7tSfi8rf4/Z2ExEREdF21NWl71aLWVSpz+9Lffn/DhnZ31Ns73V724mIiIhoq0s1XyaXsoBsuX0s1ckZX110D/3fj6m/NiJ/r9vbTkRERERb2WItP64WsrBqPvDVJbfx/5/8a4Py97y9/URERES0VaVa7lTLWES21H5quOQe5lPq10Tk73l7+4mIiIhoK7KF69fUIhaVLbOXD5bbw12ufk1U/t63j4GIiIiINrPuqmd/uy1cXxouYFHZInvvYLFV7lW/Nqgv+WfQPg4iIiIi2qxSn08Xy1dYabmcJxbbx7O/Rv3aqPwzaB8HEREREW1GXT95rlq8ArtFLraC/7WDXxvc5LntYyEiIiKio80Wwiv10hVP6vOjC31543ChfSKH/tr8qPq9IrLXfGX7WIiIiIjoaLLl6qeHy1ZwdbjMPhn/NYPfI7qfbh8PEREREW2kXe/d9cdsERzNP7C10JcHhkvsWvmvVb9nRPZ67/XPpn1MRERERLTeUp//m1q0okr95NLhArt2k0vV7xmVfzbtYyIiIiKi9dRNT3y6WrDCqvkDeoFdO/895O8dlX1G7eMiIiIiorWW+vxmuVwFtVDzOWp5XQ//PdTvHZV/Ru3jIiIiIqK1tNiX71eLVWA3qcV1I/z3Gvzeofln1T42IiIiInqybOFbVktVSLV8PvX59OHCunH5dP895dcKyF7zcvvYiIiIiOhILfb5Z9VCFVYt+1cvq0fHf0/5tYLyz6x9fERERESkWrx+8Sm2OH1suEiFVfMn1aK6Gfz3ll8zpo/5Z9c+RiIiIiIalvr8W2KJiuwStaRuBv+9B18rNP/s2sdIRERERIe3OJ0ktUCFVcvdakHdTP415NcOyj/D9nESERER0Veyxe4stTxFZa/37MOX0i1ytvraUdnrPat9nERERETkLU7L89TiFNgNg4V0y/jXGnzt0PyzbB8rEREREdmCdHC4MEWVavmsOU0tpVvCv5Z9TfVagjrYPlYiIiKi+W5hOf+CWJYCm1wtF9It5F9Tv5aY/DNtHy8RERHRfNZdddI3p5ofUMtSSDV/XC2i28G/tnxNAa18pvbZto+ZiIiIaP5KtbxSLUpR2QL3TrWEbgv72uo1ReWfbfuYiYiIiOarbn95llqQorJF8065gG4new3qtYVln3H7uImIiIjmp1TL+XI5iurA5K1y+dxG/hrkawvKP+P2cRMRERHNR4vL+R+pxSisablOLZ47wV+LfI1B+WfdPnYiIiKi2S/VfKNaiiKy1/qZ1E9eq5bOnWGvxV6Teq0R+WfdPnYiIiKi2W6hLv2SWoiiStN8pV44d5C9JvVao/LPvH38RERERLPZ4r7Jn+9qfkQtQyFNy0flohmAvzb5miOyz9w/+3YMiIiIiGavVMv/lYtQVLVcqJbMCPy1ydcclH/27RgQERERzVaLyzmrBSisabldLZiR+GuUrz0oPwPtOBARERHNTraYXaSWn6js9e45fKkMao967VHZ672oHQciIiKi2Whxmv+xWnyiSnVyzWChjMteq/oeovKz0I4FERER0fjr+nyrWnpiyo+k6eTVcqmMyF6rv2b9vUSUb23HgoiIiGjcpWn5Fb3wBFXzu+VCGZi/Zvm9BOVnoh0PIiIionF2/HXl27o+f04tOyHV8mG1SI6Bv3b5PYWUP+dnox0TIiIiovGVpuXVetGJKdV8gVoiR8Feu/qeovKz0Y4JERER0bjq6tJ3qwUnqlTL++QCOSb2PajvLSw7I+24EBEREY2nVPNlcrkJyF7rl1KdnCGXxzHx78G+F/U9RuRnpB0XIiIionG0UMuPq8UmrJoPyMVxhPx7kd9jUH5W2rEhIiIiil+q+U611IS0XB5SC+OY+fckv9eA/Ky0Y0NEREQUu1TLr6mFJqo0LZerZXHU7HtS32tUfmba8SEiIiKK2WJd+utdLeP5e0T7cu+qJXF23Ku+55DszPjZaceIiIiIKF6p5tfLRSYoWwbPGyyHs+Q89T1H5WenHSMiIiKiWC3Wpb+pFpjAbhHL4Uzx73HwPYfmZ6gdJyIiIqI4pZrfo5aXiFKfH13oyxvVcjhLDn2P+VH1HkTkZ6gdJyIiIqIYLdTyL9TiEpUtf71aDGdT7tV7EJWfpXasiIiIiHa23Qd3/9Gulg+qpSUiW/4eWL0MzrwH1HsRkp0lP1PteBERERHtXKmW/yoXlqBSP7lULIIzbnKpei+i8jPVjhcRERHRzrTYn/A0tagE9gG9CM4+/94H70VofrbaMSMiIiLa/lLNZ6glJaqF6eQctQTOA//e1XsSlZ+tdsyIiIiItrfFfvJ9akGJyhan96oFcK7Ye6Dem6j8jLXjRkRERLR9dbXsV8tJUJ9P03y6XP7mib0H/l4M3pu47Iy140ZERES0PdnSdIpcTIKy17v8uIVvvi2r9ygqe72ntGNHREREtLUtXrL4lK6Wj6qlJKRaPjlY9OaevyfyvYrIzpqfuXb8iIiIiLau1OeXy4UkqDQtl6hlb67Ze6Leq6j8zLXjR0RERLQ1Le6bJLWIRGVL3d2rljx8xd3qPYvKz147hkRERESbX1rOZ6klJKpUy9liwYOz90a9Z1H52WvHkIiIiGhzW9xfnqcWkKhSn2+UCx4Ok29U711UfgbbcSQiIiLavLpaDqrlI6jPplpO08sdvsreI3+vBu9dXHYG23EkIiIi2pxSn/+1XDzCmlwtFzus4u+Vfg9j8rPYjiURERHR0XX8dcf/6a7P96ulI6b8cbXQ4Yn5e6bfy4jy/X4m2/EkIiIi2nipz/9LLxwxpZrfqZY5HIG9Z+q9jMrPZDueRERERBtrcTr5LrVoRGUL251ykcOTs/dOvadR+dlsx5SIiIho/dkCdJ5aMuLKZ65a4LAm/t7p9zQme83ntWNKREREtL4WpvkfqgUjrFquGy5vWB9/D+V7G5Sf0XZciYiIiNaeLRI3DBeLsGr5jP3xVLW8Ye38PWzvpX6f47mhHVciIiKitZX6/O/EUhGWLWlXDpc2bNiV6j2Oys9qO7ZERERER+6Z157057o+P6yWiqA+JpY1HAV/TwfvcWD5YT+z7fgSERERPXG26PyuXijCunC4qOHo+Hs6eI9Ds9f8u+34EhEREemOP1CW1CIRVs13DJc0bA5/b+V7HpSf3XaMiYiIiFZnC8O4/pe8Wt6iljRsAntv1Xse2IXtGBMRERE9voVp/lGxPISV+sk1ckHDJppco977qPwMt+NMRERE9LVsUbhluDiEVfMjizW/Ri9n2Cz+Hvt7LT+DmG5px5mIiIjoUKku/YpYGuKq+d1qMcPm8/dafgZB+Vlux5qIiIjmveP3l2+zZeZzamkIqeaPqIUMW8ffc/lZRGRn2c90O95EREQ0z6VaXi0XhqDSNF+gljFsIXvP1WcRlZ/pdryJiIhoXltcziepRSEqW2Buk4sYtp699+ozicrPdjvmRERENI+lmi9VS0JINX8pTSdnyCUMW8/ee/8M5GcTkJ/tdsyJiIho3lqoS/9MLQhhTcsBuYBh2/hnID+boPyMt+NORERE81RX8/vVchDUQ2rxwvbzz2Lw2cRlZ7wddyIiIpqXUi3/WS4GQdmCdcVw4cKOuUJ9RlH5WW/HnoiIiGa945fzX+tqeUwtBRGlablXLFvYSfaZqM8qJDvrfubb8SciIqJZLtVymlwIgrLF6vxVixZ22vnqs4rKz3w7/kRERDSrLdSlv6EWgbgmt4glCwH4Z6M/s5j87LfHgIiIiGaxblT/Odf8RVum3qiWLOw8/2wOfUbqswvIzn57DIiIiGjWSnXyz+UCEFTqc68WLESSe/XZReXPQHsciIiIaFY6ee/JX9fV/AE1/CNKNT+oFyuEY5+V+gxDsmfAn4X2WBAREdEslGr5TTn4g7Ll6TK5VCEe+6zUZxiVPwvtsSAiIqKx98xr83eqgR/YB+RChbD8Mxt8hqH5M9EeDyIiIhpz3TS/SQ37qBaWy7lqmUJc/pmpzzIseyba40FERERjbaE/4fvkoA8q1fxetUhhBOyzU59pVP5stMeEiIiIxljX531qyEeUavmCvd7T5RKF8FY+u5XPUH++8eR97TEhIiKisWXLxyl6wMeUlsvycHnCyNhnqD7bqOw1n9IeFyIiIhpLuw/u/oaulo+q4R5SzfevWpowSv5Zys84IntG/Flpjw0RERGNodTnl8vBHlSalkvU0oQRss9SfcZR+bPSHhsiIiKK3vH9CQtqoEeV+sndcmHCiE3uVp91VP7MtMeHiIiIItf1+Uw1zOOanK2XJYzX5Gz9WUeVz2yPDxEREUVtoZ/8fT3IY0p9vlEvShi/fKP6zKPyZ6c9RkRERBSxrpYDaogH9dk0LafpJQmjZ5+tf8aDzzwue3baY0RERETRsuXi5+UADyrVvG/VcoTZYp+x+uyjstf88+1xIiIioijtPrj7T3W1fFIN76A+vmopwkzyz3rw2cdlz5A/S+2xIiIiogilPv9PObiDStPJO9VShBlkn7U6A1H5s9QeKyIiItrpdvUnPlMN7KhSzXfKhQizyz5zdRai8meqPV5ERES0k3V9PlcN67Cm+Uy5DGFm+Wcuz0JY+dz2eBEREdFOZUvE8/Wgjsle7/WHL0CYK9erMxGVvd7nt8eMiIiIdiIbyONZHmr5jP3x1MHygznhn307A/p8xHN9e8yIiIhou0t9/kUxnMOyZeeq4fKDuXOVOhtR+TPWHjciIiLarnYf3P0tNogfGg7mwD4mlh7MIT8Lg7MR2UP+rLXHjoiIiLajrs+vEkM5rIV+cqFaejB//CyoMxJXflV77IiIiGir27W/LOmBHFW+Qy08mF9+JvRZicmfufb4ERER0VbW1TKy/0WsvEUtO5hffiYGZyQ2e+ba40dERERb1cJy/lE5iINKNV+rFh3Az4Y6M1H5s9ceQyIiItqKulpuUUM4qEcWa36NXHIw9/xs+BkZnJm47NlrjyERERFtdmk5/wc5gMOavFstOMBX+BnRZycmfwbb40hERESb1XddfeJf6mr+rBq+MeWPqMUGGPKzos9QQPYM+rPYHksiIiLajNLyyj/Ao4dvRDVfoJYaYMjPijxDQfmz2B5LIiIiOtoWDpTnqIEbVZqW29RCAzwhOzPqLEXlz2R7PImIiOhossH6ruGgDexLi315s1xmgCfgZ8bPzuAsRfau9ngSERHRRkvT/E/FkI2rlgNqkQGejJ8deaaC8mezPaZERES0kUb1X5CalofUAgOslZ8hebZCyne0x5SIiIjWW+rzf9IDNiZbVK4YLi7AOl2hzlZU/oy2x5WIiIjW2nHXTJ5qQ/SLarhGlGr+kFhagPWzs6TOWET+jPqz2h5bIiIiWks2RF83HKqRLfblfLm0AOvkZ0mdscBe1x5bIiIierIWDuTvFcM0rppvVQsLsFF+puRZC8qf2fb4EhER0ZGywbl3OEjDqvmL5k1qWQE2ys/UytlSZy6mve3xJSIioicqTfNPiSEaVuonvVpUgKM36dWZi8qf3fYYExER0bCT9578dV2f71FDNKJU84N6QQE2iZ0xdfZiyvf4M9weZyIiIjq8VMtv6gEaky0hl8nlBNgsdsbU2YvKn+H2OBMREdFXOm45f6canGHV8kG5mACbzM+aPINB+bPcHmsiIiLyVv7hGzE0AztXLSXAZvOzNjh7sdmz3B5rIiIiWqhLf0cOzKDScrlZLSTAlrEzp85iVP5Mt8ebiIhovutq3qeGZUSpli9008npchkBtsjKmfOzJ85kSPZMt8ebiIhofrPh/TNyUAZlS8fycAkBtsmyOpNR+bPdHnMiIqL5q+wvf6Kr+SNqSMaU7xfLB7Bt/AzqsxmQPdv+jLfHnYiIaL7qavkfckDG9S61fADbxc/g4EzGZs94e9yJiIjmp111aZccjEGlfnK3WjyA7Te5W53RqPxZb489ERHRfNTV/FY1FAN7m146gO3lZ3FwNmOzZ7099kRERLNfqkt/Tw7EoFKfb1QLB7Bz8o3qrEblz3x7/ImIiGa7ruapGoYx5c+laTlNLxvADrEz6WdTn9mA7Jlvjz8REdHslmr5V3IQBpX6vE8uGsCOG8+/f9r5s9+uASIiotnr2Lr0TTbsPqGGYET+WvWCAQQxsufJ74B2HRAREc1WXS2/owZgWLVcLJcLIAg/o/LsRmV3QLsOiIiIZqeFunS8HHxBpT7fqRYLIJ58pzrDUfld0K4FIiKi2air+Rw19KJKy+UsvVQAwdhZVWc4LLsL2rVAREQ0/tL+8nw58IJK03K9XCiAqOzMqrMcVaqTH2rXAxER0bjrpuU6NewiSn3+A/vjqXKZAII6dGZXzq481+HYndCuByIiovFmw/cX5aALKtVylVokgPDs7KozHZXfDe2aICIiGl9PO7j7W2wAP6SGXEQ2eO9btTwAo5LvU2c7Inu9D/kd0a4LIiKicdX1+VVqwMU1uXD14gCMh59hfbajyq9q1wUREdF4WphOTtCDLap8h1ocgLHxs6zPeEx+V7Rrg4iIaBzZsH2HGmqBvUUtDcDY+FkenO3g8jvatUFERBQ/G7Y/ogdaTKnma4fLAjBqdqbVWY/KXvOPtOuDiIgodja4bh4OssAeSdP8mlWLAjBmdqb9bA/OemQ3t+uDiIgobqnP/14MsbBSLe+RiwIwdna21ZmPyu+Odo0QERHF6xkHnvUXbViN519aX/NH5IIAzAg/4/LsB+R3h98h7TohIiKKVdfn31cDLKxpuUAtB8Cs8DMuz35Y+ffbdUJERBSnhenkRD24Ykq13KYWA2Dm2FlXz0BUfpe0a4WIiChGNqAuGQ6ssGr58mJf3iyXAmDG+Fn3My+fhZguadcKERHRzmfD9IViWEV2cLgMALPMz/zgGQjNXvML2/VCRES0s9lQul0Nq6AeOnwBAOaFn/3BsxCWvd7b2/VCRES0c3V9fqkaVFGlWvYOFwBgLtjZV89EXPml7ZohIiLa/o7bN3lq6vOjekjFY6/1Q3IBAOZG/pB6NiLyu8XvmHbdEBERbW9dLa9TAyqqxb6cr4c/MB/8GVDPRlh2x7TrhoiIaPtaWM7fKwdTVDXfqgY/MG/8WZDPSFB+17Rrh4iIaHvqxvT3+9XyWDfNb1JDH5g3/iysPBPqWYnI7pp27RAREW19aTn/lBxIQaVapmrgA3PLngn1rETld067foiIiLawM1/wR1LN96hhFFHq84Ny0ANzLz+onpmI/M7xu6fdQkRERFtTV5f+ixpEUS1O82V6yAPzzZ8N9cyEZXdPu4aIiIg2v137y7FyAMX1QTXgARziz8jgmQnN76B2HREREW1uXS1vVMMnrGk5Vw13AIf4MyKfnajsDmrXERER0eaVlvPfloMnKBviNw+HOgDpZvUMReV3UbuWiIiINqeu5qvV0InIBvcX7I9vGAxzAEJ7VvyZkc9TOHYXtWuJiIjo6LPB8i/lwAkqTcvycJgDOAJ7ZtSzFJbdSe16IiIi2nhP3XvyH099/rAcNiHl++UgB3BE/uzoZyoev5P8bmrXFBER0cbqpuW/q0ET2LvUEAdwZP7sDJ6l2OxuatcUERHR+lu4Jh8nB0xQqc/3qAEOYK3G8x+DcX5HteuKiIhofdkgectwsIRWy9v08AawFv4MyWcrrre064qIiGjtpQP5B8RQCSvVcpMa3ADWyZ4l9YxF5XdVu7aIiIjWVupzr4ZKTPlzqU5eL4c2gPWxZ8mfKf2sxeN3Vbu2iIiInrxuOnmxGihh1bxPDmwAG+LPlHzWorI7q11fRERET9yxdembUp8/LodJQKmWT6hBDeAo2bOlnrmI/M7yu6tdY0RERLqult9RgySsWi6WQxrAUfFnSz5zUdnd1a4xIiKi1S3UpePlAAkqLZe71IAGsEnsGVPPXlR+h7XrjIiI6PF1NZ+jhkdUNojPWjWYAWyms9SzF5bdYe06IyIi+lqpLv2QHBxBLdSlG8RQBrDJ/FlTz2BUfpe1a42IiOhQqebr1NCIyF7rH3QHyqlqKAPYXCvPmj9z4lmMyO+ydq0RERGt/ANo/1YNjMCuUgMZwNbwZ27wDMZmd1q73oiIaJ57Rn/Cn021fEoOi4BSn+9TgxjAVsv3qWcyIr/T/G5r1xwREc1rXc3/Rw2KqGzgXrR6AAPYBhepZzIsu9vaNUdERPNY6k94thwQQaU+3yGGL4Btk+9Qz2ZUfse1646IiOatruYL1HAIq07eqocvgO3gz6B8NqOyO65dd0RENE91/eQFcjAElfp8rRq8ALZbvlY9o3FNXtCuPSIimpdSLe/VQyEee62fTtP8Gj10AWwrfxbtmVTPakR+17Vrj4iI5qGull9WAyGqNC3vkQMXwM6wZ1I9q2HZndeuPyIimuV29Sd8a6rlM3IYBGSv9aNy0ALYWfZsqmc2Ir/z/O5r1yAREc1qXc2/pwZBYO+QQxbAjvJnc/CsxmZ3X7sGiYhoFkv9iRM5AIJK03KbGrAAgrBnVD27Ufkd2K5DIiKatVLNF6vLP6rUL+2RwxVAEEt71LMbld+B7TokIqJZKu0vL1QXf2AH9WAFEIk/q4NnNzS/C9u1SEREs1Kq5XZ16UeU+vywGqgAosoPq2c5Ir8L27VIRESzULecX6ou/MD26mEKICJ/ZgfPcGx2J7brkYiIxtyuq57zV1OfH5WXfUCp5g+rQQogOHt21TMdkd+Jfje2a5KIiMZa1+dT1UUf1WJfzpdDFEBo/uyqZzqufGq7JomIaIyl/eVkfcFHlW9VAxTAOPgzrJ/tmPyObNclERGNLRs8V6jLPaRaHuum+U3DwQlgPPwZXnmW1TMekL3mK9p1SUREY6rr80+qiz2sWqbDoQlgfPxZls94WPkn27VJRESj6MvH/GEbOHfrSz2eNC0PDoclgBGzZ1o96xHZ673b78x2exIRUfS6Pv+GutADu3zVoAQwWv5MD57x4PJvtOuTiIgit3DgxO/QF3lQtXxQDUoA4+bPtnzmg/K7s12jREQUNbuw3zC8wIM7Vw1JAOPmz/bgWY/uDe0aJSKiiHXT8rfE5R2WDcObh8MRwEy5WT37Ydkd2q5TIiKKlg2Vq+TlHVCqK/+1tjcMhiKAGbLyjB961uU9EI295qvadUpERJHq+vwidXGHVUsdDkUAs8efdXkHhJVf1K5VIiKK0LG3f//Xpz5/SF/aEeX71UAEMJv8mdd3QTx+l/qd2q5XIiLa6bp+8jJ1YUeVar5UDUMAM8qeeXUXxDV5WbteiYhoJ1tYzsfpizqm1Od75CAEMOPyPepOiMrv1nbNEhHRTmUX8p7hBR3c2/QQBDDL/Nkf3AXR7WnXLBER7URpOf+AuJzjquUmNQABzAe/A+TdEJTfse26JSKi7S7V3KvLOaSaP5+mk9er4QdgTtgd4HeBvCMC8ju2XbdERLSddXXpxepiDqvm/XLwAZgrfhfIOyIqu2vbtUtERNvR068+8U+mmj8uL+WAUi2fUAMPwJyyO0HdFRH5Xet3brt+iYhoq+tq+W11IYc1LRfLYQdgLvmdIO+KqOzObdcvERFtZWk5L8qLOCgbancNhxwAmLvUnRGV373tGiYioq2qq+P6V/SkaTlLDDgA887uBnVnhGV3b7uGiYhoK+rq0j+QF3BcN8gBBwDG74jBnRGb3cHtOiYios0u1XytvHwDSn3+A/vj69RwAwB36I5YuSvkPRKN38HtOiYios2sq+XfqIs3rGm5Sg02ADic3xXyDonK7uJ2LRMR0Wa0a3/5M6nmB+WlG1Dq831qoAGAlu9Td0lEfhf7ndyuZyIiOtq6Wv63unCjssF10epBBgBP6CJ1l4Rld3K7nomI6Gjqat4tL9qgbGC9fzDAAGAt3q/ulLDsbm7XNBERbbTU57fLSzaqOnmrGGAAcER+d8g7JSi/m9s1TUREG6mrSz+sLtiwar5ODTAAWAu/Q+TdEpXd0e26JiKi9Zb6fJO8XAOyIfVpe72vHQ4uAFi7lTvk0+qOicjv6HZdExHReuqm5SXqYo0q1fKe1UMLANbJ7hJ1x4Rld3W7tomIaC3t6k/4Vrvwx/O/atTy0VXDCgA2yu4UdddEZK/3035nt+ubiIierK7m31MXamDvWDWoAGCD/E4Z3DGx2Z3drm8iIjpSqT9hIi/SqOrS7WpQAcDR8LtF3jlB+d3drnEiInqiUs0Xq0s0KhtIe4YDCgA2wR5150Tld3e7xomISGWX5Y8NL8/gDorhBACbwu+YwZ0T3Y+165yIiIalWm4TF2dIqeaH0wE9nABgU/gdY3eNuoMi8ju8XedERHR4XZ9/VV2cge2VgwkANpHfNYO7J7j8q+1aJyIib2H67L+SavmCvjTjsdf6YTWQAGBL2J2j7qKI/C73O71d70RE1PX5terCjCr1k7fLYQQAW2LydnUXxZVf2653IqL5rusn36MvyqjyrXoQAcDW8btH30lRTb6nXfNERPNb6vPl+pIMqJbHUs1nqCEEAFvK7h6/g+TdFJDf7e2aJyKaz+wy/Inh5RjcVA4gANgGfgcN7qTofqJd90REc9aXj/lDdnHfJS7GkFItnxoOHQDYdnYXqTsqInu9d/ld3259IqL5qevzr6uLMSq7sC9/3LABgJ0xnr/da0X+9XbtExHNR930pG/XF2JMqc/3imEDADsk36vuqrDszm/XPxHR7GeX9OnyMgzKXu95etgAwE7I56m7Kiq/89v1T0Q023X95LnqIgzsZj1oAGDn+N00uKuCmzy3jQEiotnNLugr9SUYT+rzowt9eeNwwADATjt0N+VH1d0Vkb3mK9sYICKazbrl/CJ1AQZWh8MFAKLwO2pwZ8VmM6CNAyKi2erYi479eruYR/MPUKRaHhgOFQAIx+4qdYdFZK/3Xp8FbSwQEc1O9pP8y9TFF1XqJ5euGigAEM7kUnWHhWWzoI0FIqLZKO2bPENeeFHV/AE9UAAgHr+z5F0WlM+ENh6IiMZfqmWPuuwCe5saJgAQkd9ZgzssNJ8JbTwQEY27bjn/XXXRBXaTGiQAEJnfXYO7LDabDW1MEBGNN7uAx/RPBX8+1cnrhwMEAMKzu8vvsMGdFpa95trGBBHROLOf2H9OXXBhTcv+VcMDAEbC7zB5t0VlM6KNCyKicbVr78nfmPp8n7zcArIh8Ynh0ACAEfqEuuMi8hnhs6KNDSKi8WSX2CuGl1ps+RIxMABgVPwu03dcWK9oY4OIaBx1B0onLrO4puUuNTAAYIz8TpN3XVQ2M9r4ICKKn120Z8vLLCh7vWcdPiQAYOTOUnddVPZ6z27jg4godt00/6C6yAK7YTAgAGD0/G4b3HWx2exoY4SIKG6pz9fISywge62ftT++Tg0JABizQ3fbyh0n779ofHa0MUJEFDP7ifwX1AUWVs1XqwEBALPA7zh590VlM6SNEyKiWHU3nvTN9hP5A/LyCshe631qMADAbBnTv+bRZojNkjZWiIjiZBfqK9XFFVWq+Z2rBwIAzBi769QdGJW95le2sUJEFKPuQHmWurDCquX9q4YBAMwov/PkXRiVzZQ2XoiIdj67SM+Xl1VU08lbh4MAAGaV33nyLgzKXvP5bbwQEe1sXV36YXVRhVXLdcMhAACzzu8+eSdGZbOljRkiop0r1XyTvKQCSsv5M2k6ea0aAgAw0/zusztQ3Y0R+WxpY4aIaGfqanmJuqCiStPyHjkAAGAe2B2o7sawbMa0cUNEtL2l5fwX7CfuT8vLKaBUy0flxQ8A88TuQnVHRuQzxmdNGztERNuXXZb/T11MYU3LO+SlDwBzxO9CeUcG5bOmjR0iou2pq0tFXUiB3a4ufACYR34nDu7I2GzmtPFDRLT1jfBfQL5neNEDwBzbo+7KqHzmtPFDRLS1dXXyT9RFFFXq8zXikgeAOZevUXdmWDZ72hgiItq67Cfr98lLKCC7yB9O0/JqfckDwBxbuRvzw+rujMhnTxtDRERbU1fLf1QXUGB75QUPAPC/V3fv4M6MzWZQG0dERJtbV5f+sl0yn5eXT0wfVhc7AOBr/K4c3J1x+QyyWdTGEhHR5pVqfo28eIJK/eTt6lIHABxu8nZ1h0bls6iNJSKizcl+gv5udeFElfr8Pn2hAwBWG88/e7HCZlIbT0RER5/9BH2ZvGwCskv7sVQnZ6y+yAEA0qE78zF1p0bkM6mNJyKio2uxlh9XF01YNR9YdYkDAI7I7055pwbls6mNKSKijZdquVNdMhHZZf2p4eUNAFizT6m7NSKfTW1MERFtLLtIfk1dMFHZJX354NIGAKzd5epujcpnVBtXRETrq7vq2d9uF8mXhhdLVHZB3zu4sAEA63evumOD+pLPqja2iIjWXurz6eJSCSstl/PEhQ0AWA+7S9UdG5XPqja2iIjWVtdPnqsulMBukRc2AGDd/E4d3LHBTZ7bxhcR0ZNnF92V+jKJx36af3ShL28cXtQAgI05dKfmR9WdG5G95ivb+CIiOnJ2afz08BIJrg4vaQDA0fG7dXDXRvfTbYwREel2vXfXH7MLbjT/IMJCXx4YXs4AgM3hd6y6eyOy13uvz7A2zoiIVpf6/N/UBRJV6ieXDi9mAMBmmVyq7t6ofIa1cUZE9Pi66YlPVxdHWDV/QF/MAIDN4netvIOjslnWxhoR0deyn4TfLC+NoBZqPkddygCAzeN3rbqDo/JZ1sYaEdGhFvvy/erCCOwmdSEDADaf37mDOzg0n2ltvBERrfzrxJbVZRFSLZ+3n9hPH17EAICtkk/3u1feyQHZa15u442I5r3FPv+suijCqmX/6ksYALCV/O6Vd3JQPtvamCOieW3x+sWn2IXwseEFEVbNn1QXMABg6/kdLO/mmD7mM66NOyKax1Kff0tcDpFdoi5fAMDW8zt4cCeH5jOujTsimrcWp5OkLoawarlbXbwAgO3jd7G8o4PyWdfGHhHNU3ZhnaUuhajs9Z59+GULANgRZ6s7Oip7vWe1sUdE89LitDxPXQiB3TC4aAEAO8Tv5MEdHZrPvDb+iGgesgf/4PAiiCrV8llzmrpsAQA7wO9ku5vVnR3UwTb+iGjWW1jOvyAugcAmV8uLFgCwY/xu1nd2TD772hgkolmtu+qkb041P6AugZBq/ri6YAEAO8/vaHl3B7Qy+2wGtnFIRLNYquWV6gKIyi6md6rLFQAQgN3R6u6OymdgG4dENGt1+8uz1IMflV2gd8qLFQAQh93V6g4Py2ZhG4tENEvZT7Lny4c+qgOTt8pLFQAQht/V8g4PymdhG4tENCstLud/pB74sKblOnWhAgDi8Ttb3uVB+Uxs45GIZqFU843qYY/IXutnUj95rbpMAQAR2Z1td7e60yPymdjGIxGNvYW69EvqQY8qTfOV+iIFAIRld7e606Py2djGJBGNtcV9kz/f1fyIeshDmpaPygsUABCe3+Hybo/IZqPPyDYuiWiMpVr+r3zAo6rlQnV5AgDi8ztc3u1B+Yxs45KIxtbics7qwQ5rWm5XFycAYDz8Lpd3fFA+K9vYJKIxZRfOReqhjspe757DL0sAwCjtUXd8VPZ6L2pjk4jG0uI0/2P1QEeV6uSawUUJABgru9PVXR+Vz8w2PoloDHV9vlU9zDHlR9J08mp5WQIAxsfudL/b9Z0fUb61jU8iil6all/RD3JQNb9bXpQAgNHyu13e+UH57GxjlIiidvx15dvsJ9PPqYc4pFo+rC5IAMD4+R0v7/6Q8ud8hrZxSkQRs59IX60f4JhSzReoyxEAMAPsjld3f1Q+Q9s4JaJodXXpu9WDG1Wq5X3yYgQAzA6769UMCMtmaRurRBQp+8n5MvnQBmSv9UupTs6QlyIAYHb4XW93vpoFEfksbWOViKK0UMuPqwc2rJoPyAsRADBz/M6XsyAon6ltvBJRhOwn0DvVwxrScnlIXYQAgNnld7+cCQH5TG3jlYh2ulTLr6kHNao0LZerSxAAMMPs7lczISqfrW3MEtFOtViX/npXy3j+3qe+3Lvq8gMAzIt71WwIyWarz9g2boloJ0o1v14+oEHZJXfe4NIDAMyP89RsiMpnbBu3RLTd2U+af1M9mIHdIi49AMAc8VkwmA2h+axtY5eItjP7SfM96qGMKPX50YW+vFFdegCA+XFoFuRH1ayIyGdtG7tEtF0t1PIv1AMZlV1qvbrwAADzKPdqVkTlM7eNXyLa6nYf3P1Hu1o+qB7GiOxSe2D1JQcAmHMPqJkRks1cn71tDBPRVpZq+a/yQQwq9ZNLxQUHAJhrk0vVzIjKZ28bw0S0VS32JzxNPYCBfUBfcACAeeczYjAzQvMZ3MYxEW1FqeYz1MMX1cJ0co663AAA8BmhZkdUPoPbOCaizW6xn3yfevCisgvhvepiAwDgq2xWqBkSlc/iNpaJaDPratmvHrqgPp+m+XR5qQEA8BU2K3xmDGZIXDaL21gmos3KLoNT5AMXlL3e5cddZAAAPLFlNUuistd7ShvPRHS0LV6y+BT7CfKj6mELqZZPDi4wAACOyGeHnCkR2Uz22dzGNBEdTanPL5cPWlBpWi5RlxgAAE/IZoeaKVH5bG5jmog22uK+SVIPWFR2Wd296vICAGBt7lazJSqf0W1cE9FGSsv5LPVwRZVqOVtcXAAAPDmbIWq2ROUzuo1rIlpvi/vL89SDFVXq843y4gIAYM3yjWrGROWzuo1tIlpPXS0H1UMV1GftJ/HT9KUFAMAa2SzxmTKYMXHZrG5jm4jWmv1E+6/lAxXW5Gp5YQEAsE4+U/SsiclndhvfRPRkHX/d8X+66/P96mGKKX9cXVQAAGyUzxY9cyLK9/vsbmOciI6U/WT4v/SDFFOq+Z3qkgIAYMNstqiZE5XP7jbGieiJWpxOvks9QFHZRXSnvKAAADhaNmPU7InKZ3gb50Sksgf7PPXwxJXPXHUxAQCwCXzG6NkTk73m89o4J6JhC9P8D9WDE1Yt1w0vJQAANpPPGjmDgvJZ3sY6ER2ePSA3DB+YsGr5jP3xVHUpAQCwWXzWtJmj51E8N7SxTkRfKfX534mHJSy7fK4cXkYAAGyRK9UsispnehvvRPTMa0/6c12fH1YPS1AfE5cQAABbxmfPYBYFlh/22d7GPNF8Zw/w7+oHJawLhxcQAABbyWfPYBaFZq/5d9uYJ5rfjj9QltQDElbNdwwvHwAAtoPPIDmbgvIZ38Y90XxmD8K4fkKt5S3q8gEAYMvZDFKzKbAL27gnmr8WpvlHxUMRVuon18iLBwCAbTO5Rs2oqHzWt7FPNF/ZA3DL8IEIq+ZHFmt+jb50AADYHj6LfCbJWRXTLW3sE81PqS79ingY4qr53erCAQBgu/lMkrMqKJ/5bfwTzX7H7y/fZg/p59TDEFLNH1EXDQAAO8Vnk5xZEdnM99nf1gCi2S7V8mr5IASVpvkCdckAALBjbDapmRWVz/62BhDNbovL+ST1AERlD+Zt8oIBAGCn2YxSsysq3wHaOkA0m6WaL1WHP6Sav5SmkzPk5QIAwE6zGeWzSs6wgHwHaOsA0ey1UJf+mTr4YU3LAXmxAAAQhM8qOcOC8l2grQVEs5X91Pl+deiDekhdKAAAROMzazDD4rJdoK0FRLNTquU/ywMflF0cVwwvEgAAgrpCzbKofCdo6wHR+Dt+Of+1rpbH1GGPKE3LveISAQAgLptdaqaFZDuB7wZtTSAad/aT22nyoAdlF8b5qy4QAABiO1/NtKh8N2hrAtF4W6hLf0Md8Lgmt4jLAwCA8HyG6dkWk+8IbV0gGmfdqP4zhfmLdkm8UV0eAABE5zPs0CxTMy4g2xHaukA0vlKd/HN5sINKfe7VxQEAwHjkXs24qHxXaGsD0Xg6ee/JX2c/qX1AHeqIUs0P6gsDAICRsZmmZl1Itiv4ztDWB6JxlGr5TXmgg7JL4TJ5WQAAMDY209Ssi8p3hrY+EMXvmdfm71QHObAPyIsCAICR8tk2mHWh+e7Q1gii2HXT/CZ1iKNaWC7nqksCAICx8tmmZl5Ytju0NYIobgv9Cd8nD3BQqeb3qgsCAIDRsxmnZl9UvkO0dYIoZl2f96nDG1Gq5Qv2ek+XlwMAACO3MuNWZp2eg/HkfW2dIIqXPVSn6IMbU1ouy8NLAQCAmWKzTs3AqOw1n9LWCqI47T64+xu6Wj6qDm1INd+/6jIAAGAG+cyTszAi2yV8p2jrBVGMUp9fLg9sUGlaLlGXAQAAM8dmnpqFUflO0dYLop3v+P6EBXVQo0r95G55EQAAMLMmd6uZGJXvFm3NINrZuj6fqQ5pXJOz9SUAAMCsmpytZ2JU+cy2ZhDtXAv95O/rAxpT6vON+gIAAGDW5RvVbIzKd4y2bhDtTF0tB9ThDOqzaVpO0w8/AAAzzmagz8LBbIzLdoy2bhBtf/bQ/Lw8mEGlmveteugBAJgnNgvVjIzKXvPPt7WDaPvafXD3n7KftD6pDmVQH1/1sAMAMId8Jg5mZFy2a/jO0dYPou0p9fl/ygMZVJpO3qkedgAA5o7NRDUro/Kdo60fRFvfrv7EZ6qDGFWq+U75oAMAMK9sNqqZGZXvHm0NIdrauj6fqw5hWNN8pnzIAQCYUz4b5cwMK5/b1hCircsejufrAxiTvd7rD3+wAQDAV12vZmdU9nqf39YRoq3JDtp4HopaPmN/PHXwUAMAAOMzss1KPUfjub6tI0SbX+rzL4pDF5Y9xFcNH2oAAPA4V6kZGpXvIm0tIdq8dh/c/S12wB4aHrjAPiYeZgAAMOAzczBDI3vId5K2nhBtTl2fXyUOW1gL/eRC9TADAIDH85mpZmlc+VVtPSE6+nbtL0v6oEWV71APMgAA0Hx26pkak+8mbU0hOrq6Wkb2k155i3qIAQCA5rNzMEtjs92krSlEG29hOf+oPGBBpZqvVQ8wAAB4EjZD1WyNyneUtq4QbSz7iekWdbiCemSx5tfIhxcAAByRz1CfpYPZGpftKG1dIVp/aTn/B3mwwpq8Wz24AABgbXyW6hkbk+8qbW0hWnvfdfWJf6mr+bPqUMWUP6IeWAAAsD4+U/WsDch2Fd9Z2vpCtLbS8srfmK4PVUQ1X6AeVgAAsD4+U+WsDcp3lra+ED15CwfKc9RBiipNy23qQQUAABtks1XN3Kh8d2lrDNGRswPzruEBCuxLi315s3xIAQDAhvhs9Rk7mLmRvautMURPXJrmfyoOT1y1HFAPKAAAODo+Y+XsDcp3mLbOEOlG9V9GmZaH1IMJAAA2h89aOYNDyne0dYZodanP/0kfnJjsAbxi+EACAIBNdYWawVH5LtPWGqKvddw1k6fa4fiiOjQRpZo/JB5GAACw2Wzmqlkcke8yvtO09YboUHY4Xjc8LJEt9uV8+TACAIBN5TNXzeLAXtfWGyL/14nl7xWHJK6ab1UPIgAA2Bo+e+VMDsp3m7bm0LxnB2Lv8ICEVfMXzZvUQwgAALaGz96VGaxmc0x725pD81ya5p8ShyOs1E969QACAICtNunVbI7Kd5y27tA8dvLek7+u6/M96nBElGp+UD94AABgW9gsVjM6pnyP7zpt7aF5K9Xym/pgxGQP12XyoQMAANvDZrGa0VH5rtPWHpqnjlvO36kORFi1fFA+cAAAYFv5TJazOijfedr6Q/PSyt9ULg5DYOeqhw0AAGwvn8mDGR2b7Txt/aF5aKEu/R15EIJKy+Vm9aABAIAdYrNZzeyofPdpaxDNevaTzT51CCJKtXyhm05Olw8ZAADYESuz2We0mN0h2e7T1iCa5exQ/ow8AEHZw7Q8fLgAAEAIy2p2R+U7UFuHaBYr+8ufsJ9oPqI+/Jjy/eKhAgAAQfis1jM8INuBfBdqaxHNWl0t/0N+8HG9Sz1UAAAgBp/Vg9kdm+1CbS2iWWpXXdolP/CgUj+5Wz1QAAAgmsndapZH5TtRW49oVupqfqv6sAN7m36YAABAJD6zBzM8NtuJ2npEs1CqS39PftBBpT7fqB4kAAAQVb5RzfSofDdqaxKNPfvJZao+5Jjy59K0nKYfIgAAEJLNbp/herYHZLtRW5NozKVa/pX8gIOynwj3yQcIAAAEN55/T7/zHamtSzTGjq1L32Qf4ifUhxuRv1b94AAAgFEY2d7hu1Jbm2hsdbX8jvpgw6rlYvnQAACAUfBZLmd8VLYrtbWJxtRCXTpefqBBpT7fqR4YAAAwNvlONeuj8p2prU80lrqaz1EfZlRpuZylHxYAADAqNtPVrA/Ldqa2PtEYSvvL8+UHGVSaluvlgwIAAMbJZrua+VH57tTWKIpeNy3XqQ8xotTnP7A/niofEgAAMEqHZvvKjJfzPxzbndoaRZGzQ/WL8gMMKtVylXpAAADAyNmMV7M/Kt+h2jpFEXvawd3fYgfrIfXhRWQH6r5VDwUAAJgh+T61A0Rkr/ch36XaWkXR6vr8KvXBxTW5cPUDAQAAZoXPer0DRJVf1dYqitTCdHKC/sCiyneoBwIAAMwWn/l6F4jJd6q2XlGU7BC9Q31Ygb1FPQwAAGC2+Mwf7ADB5Xe09YoiZIfoR/QHFVOq+drhQwAAAGaYzX61E0Rlr/lH2ppFO519IDcPP6DAHknT/JpVDwAAAJhdNvt9BxjsBJHd3NYs2slSn/+9+HDCSrW8Rz4AAABgttkOoHaDqHzHausW7UTPOPCsv2gfwnj+Zcw1f0QefAAAMBd8F5A7QkC+Y/mu1dYu2u66Pv+++mDCmpYL1KEHAADzwXcBuSOElX+/rV20nS1MJyfqDySmVMtt6sADAIA5YzuB2hWi8p2rrV+0Xdkbf8nwgwirli8v9uXN8rADAIC54juB7wZyZ4jpkrZ+0XZkh+SF4kOI7ODwkAMAgPnlu8FgVwjNXvML2xpGW5292berDyGohw4/2AAAAM53hMHOEJa93tvbGkZbWdfnl6oPIKpUy97hwQYAAPAdQe0OceWXtnWMtqLj9k2emvr8qH7z47HX+iF5sAEAAFbkD6kdIiLfwXwXa2sZbXZdLa9Tb3xUi305Xx9qAACAlX8w7Xy1Q4Rlu1hby2gzW1jO3yvf8KhqvlUdaAAAgMP5ziB3iaB8J2vrGW1W9hPEeP4+lloe66b5TeowAwAAHM53hpXdQe0UEdlO1tYz2ozScv4p+UYHlWqZqoMMAAAg2e6gdoqofDdraxodVWe+4I+kmu9Rb3JEqc8PygMMAABwRPlBtVtE5LuZ72htW6ON1tWl/6Le4KgWp/kyfXgBAACemO8QarcIy3a0tq7RRtq1vxwr39i4PqgOLgAAwFr4LjHYLULzXa2tbbTeulreqN7UsKblXHVoAQAA1sJ3CbljRGW7WlvbaD2l5fy35RsalB3Om4eHFQAAYANuVrtGVL6ztfWN1lpX89XqzYzIDuQX7I9vGBxSAACAdWs7he8Wcu8Ix3a2tr7RWrI37F/KNzKoNC3Lw0MKAACwYbZbqJ0jLNvd2hpHR+qpe0/+46nPH5ZvYkj5fnlAAQAAjoLvGHr3iMd3N9/h2jpHT1Q3Lf9dvYGBvUsdTgAAgKPhO8Zg54jNdri2zpFq4Zp8nHzjgrKfXu5RBxMAAGBzjOc/muV8l2trHQ2zN+gtwzcstFrepg8lAADA0fNdQ+4gcb2lrXV0eOlA/gHxZoWVarlJHUgAAIBNZTuH2kWi8p2urXf0lVKfe/VmxZQ/l+rk9fIwAgAAbCbbOXz30DtJPL7TtfWOvG46ebF6o8KqeZ88iAAAAFvAdw+5k0Rlu11b8+a7Y+vSN9nm/3H5JgWUavmEOoAAAABbynYQtZtE5Lud73ht3Zvfulp+R71BYdVysTx8AAAAW8h3ELmbRGU7Xlv35rOFunS8fGOCSsvlLnXwAAAAtoXtImpHicp3vbb2zV9dzeeoNyUqO2BnrTpwAAAA2+cstaOEZbteW/vmq1SXfki+IUHZTyQ3iMMGAACwrXwnUbtKVL7ztfVvfko1X6fejIjstf5Bd6Ccqg4bAADAdlrZSXw3ETtLRL7ztfVvPupq+bfqjQjsKnXQAAAAdoLvJoNdJTbb/doaONs9oz/hz6ZaPiXfhIBSn+9TBwwAAGBn5fvU7hKR736+A7Z1cHbrav4/6g2Iyg7SRasPFgAAwI67SO0uYdkO2NbB2Sz1JzxbfuNB2U9Kd4hDBQAAEES+Q+0wUfku2NbC2cs2+QvUNx1WnbxVHyoAAICd57uK3GGisl2wrYWzVddPXiC/4aDsJ6Rr1YECAACIJV+rdpm4Ji9o6+HslGp5r/5m47HX+uk0za/RhwkAACAQ31lsd1E7TUS+E7b1cDbqavll9Y1GlablPfIgAQAARGS7i9ppwrLdsK2J425Xf8K32ub+GflNBmSv9aPyAAEAAERmO4zabSLy3dB3xLYujreu5t9T32Bg75CHBwAAIDDfYQY7TWy2I7Z1cZyl/sSJ/MaCStNymzo4AAAAo2C7jNpxovJdsa2N4yvVfLH6pqJK/dIeeWgAAABGYWmP2nGi8l2xrY3jKu0vL1TfUGAH9YEBAAAYD99pBjtOaL4ztvVxPKVablffTESpzw+rgwIAADBO+WG180TkO2NbH8dRt5xfqr6RwPbqQwIAADA+vtsMdp3YbHdsa2Tsdl31nL9qP0U8Kr+JgFLNH1YHBAAAYNRsx1G7T0S+O/oO2dbJuHV9PlV9A1Et9uV8eTgAAABGzHcctfvElU9t62TM0v5ysn7hUeVb1cEAAACYBb7r6B0oJt8l21oZL3tDr1AvOqRaHuum+U3DAwEAADArfNdZ2XnULhSQveYr2loZK/uJ4SfVCw6rlunwMAAAAMwa33nkLhRW/sm2Xgbpy8f8YXsj79YvNp40LQ8ODwEAAMDMst1H7UQR2eu923fLtmXufLZ5/4Z6oYFdvuoAAAAAzCjffQa7UHD5N9qaubMtHDjxO/QLDKqWD6oDAAAAMMt8B5K7UVC+Y7Z1c+eyF/KG4QsL7lz14QMAAMwy34EGO1F0b2jr5s7UTcvfEi8qLPuQbx5+6AAAAHPkZrUjhWW7Zls7tz97s66SLyqgVFf+a21vGHzYAAAAc2NlFzq0E8l9KRp7zVe1tXN76/r8IvWCwqqlDj9sAACAeeM7kdyVwsovauvn9nTs7d//9anPH9IvJqJ8v/qgAQAA5pHvRnpnisd3Tt892xq69XX95GXqhUSVar5UfcgAAABzyXYjtTPFNXlZW0O3toXlfJx+ATHZTwH3yA8YAABgruV71O4Ule+gbR3duuwL7Rl+4eDepj9cAACA+eU70mBnim5PW0e3prScf0B80bhquUl9sAAAAFj5B9NukjtUUL6LtrV080s19+qLhlTz59N08nr1oQIAAMDYruQ7k9ylAvJdtK2lm1tXl16svmBYNe+XHygAAAC+yncmuUtFZTtpW083p6dffeKftA364/KLBZRq+YT6IAEAACDY7qR2qoh8J/XdtK2pR19Xy2+rLxTWtFwsP0QAAACs4ruT3Kmist20ralHV1rOi/ILBGUf1l3DDw8AAABP6i61W0XlO2pbVzeebcyj+ldPpGk5S3xwAAAAOBLbodRuFZbtqG1d3VhdXfoH8jcGAAAAdprtqm1tXX+p5mvlbwoAAADsMN9V29q6vrpa/o36DQEAAIAwbGdt6+va2rW//BnbkB+UvxkAAAAQhO+svru2NfbJs834f6vfCAAAAAjHdte2xh65rubd8jcAAAAAorIdtq2zT1zq89vlLwYAAACC8h22rbO6ri79sPqFAAAAQHi2y7a1dnW2Cd8kfxEAAAAQnO+yba19fN20vET9AgAAAGA0bKdt6+3XSjW/T/7FAAAAwEj4TtvW20MtTsvz1F8IAAAAjI3vtm3NXflXip2j/iIAAABgdGy3XVlyFw6c+B3yLwAAAABGynfcY7rp5MXqTwIAAACjZTuu/+d+f1v+SQAAAGCsbMc9JtXyNvknAQAAgJFKfTnb/yMR16g/CQAAAIyV77j+7899QP1JAAAAYKx8x/X/RfdB9ScBAACAsfId1/8X3WvVnwQAAADGyndc/mE0AAAAzJyVfxjN/o9XDP8EAAAAMHKvOKZbzj8n/gQAAAAwXrbjHrPrmnKs/JMAAADASPmOe4zX1XyO+gsAAACA8cnnriy53uL+8jz9FwEAAADjsjgtz2tr7qG6mm9VfyEAAAAwGrbTtvX2ay1MJ78k/2IAAABgJHynbevt40t9frP6BQAAAEB0vsu2tXZ1i5csPiXV8l71CwEAAICoUl9u9l22rbW61J84Ub8YAAAAiMp32LbOHrl0oPyM+g0AAACAaHx3bWvs2tq1nE+yX3jL8DcCAAAAgrhl4UB5Tltf19euvSd/Y+rLHvGbAgAAADsm1bLHd9W2tm68rpZfTjW/T30RAAAAYLus7KS2m7Y1dfPqpvkHU1/OU18UAAAA2CorO6jtom0t3boW+xOeZl/slNTn37I/nmWb9TX2fz+gXhQAAACwVr5THtotbcc8tGue0l397Ke3NXQdHXPM/w+LdBQvQyJLdgAAAABJRU5ErkJggg==\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEbISURBVHhe7d0NuKVXedf/UavVUqvVqtWq1TYtEpnZ615nEkNbTG1VtBYsWlsVra2KpaBSK1SptajUWtrSYlHpPyGEQEISEhJCSEjIKwnJzDzr2TN5f4MQQiCBhCSEEBIIhP+6ZxYk85zfvJwz+5x9P3t/v9f1ueAiM3P22ftZ97qnTSZbiIho9nXbtz67mL2sz+n1vdlZxdK0z/aQ2/vf6//mf81/jP/Y9tOIiIiIiGLWmb2oLrHvqQvtV9ek/hz/ue2XISIiIiKKUZ/zq4ulW+USuwb7fo3Jq9svS0REREQ0n644+uhv7nM6XS2tRyad7r92+zJERERERJtXWZl8f8npFr2oHjn/tf1rtC9HRERERLTx1SX059RyuhH8a7UvS0RERES0cXUpfZ9aSDeSf8325YmIiIiIZl+/svJNJdvNahndSHu/Zv3a7WUQEREREc22YnaaWkQ3g3/t9jKIiIiIiGaX/7FfagHdXPzRY0REREQ0w3Ydc/S310Xz86sXz033eX8t7WURERERER1ZXU5vFkvnXPhraS+LiIiIiGj97TJ7nlo458lfU3t5RERERETrq1i6SC2b8+Svqb08IiIiIqK1V3L6p2rRjMBfW3uZRERERERrq5jdrpbMCPy1tZdJRERERHT41UXyv6gFMxJ/je3lEhEREREdum779r9QLH1JLZeR+Gv019peNhERERHRwatL5FuGS2Vgb2kvm4iIiIjowE3N/rpYJkPz19xePhERERGRrli6TC2Tkflrbi+fiIiIiGh1Jad/oRbJMfDX3r4NIiIiIqKn++qWLb+vLowfHS6QI/JR/x7at0NEREREtK+p2X8Ty+Oo+PfQvh0iIiIior1/nNh3qcVxjPx7ad8WERERES17dUE8Zbgwjtgp7dsiIiIiomVuavbDYlkcNf+e2rdHRERERMva1NJValkcM/+e2rdHRERERMvYrjx5qVoUF4F/b+3bJCIiIqJl6sKjjvrGuhDeM1wQD6aI/y2we/x7bN8uERERES1LxezXxHK4UPx7bN8uERERES1D/crKX1GL4UKq32v7tomIiIho0Ss5nS6XwgXk32v7tomIiIhoketS+rtqIVyTFfG/Bebfc/v2iYiIiGhRK5Z2qmVwLaaN+msR+ffcvn0iIiIiWsT6nF6uFsHlkF7e3gYiIiIiWqRuOvroby7ZPq2XwMXn37u/B+3tICIiIqJFqZj9ploAj8jI/l5dfw/a20FEREREi1DJeata/GZhTH+vrvP3or0tRERERDT2+pzOVkvfckpnt7eFiIiIiMbc1OxFeuFbXv6etLeHiIiIiMZasTRVy95MmfjfAvP3pL09RERERDTG+pxeqRY9uPTK9jYRERER0Zi6YevWb60L3UOrFzw0D/l71N4uIiIiIhpLxeyNYrnbWKP7Wxjsje3tIiIiIqIxVHLOarHDav5etbeNiIiIiKLX53SeWuo2QxH/W2zpvPa2EREREVHkSko/rhc6HIi/Z+3tIyIiIqKoFUs3qmUOB+bvWXv7iIiIiChiXZ68Wi1yODR/79rbSERERESR2vHc5/6Zku3zaomblzH9/br+3vl72N5OIiIiIopSMft/aoGbp6n43yLz97C9nUREREQUoT7n49TihvXIx7W3lYiIiIjmXcnp/Xppw1r5e9neViIiIiKaZyWlf6IWNqyfv6ft7SUiIiKiedVbuk0ta9GM6u/Xre9pe3uJiIiIaB71Of2SXNQwA+mX2ttMRERERJvZ9Vu3/vmS7Yt6SYun5PRJp/5aRP7e+nvc3m4iIiIi2qyK2YlqQYuqLrnvdeqvReXvcXu7iYiIiGgz6nN+vlrM4kq3FUv/n/P/rn9MVPn57W0nIiIioo2uLouX6qUsIEtfKWanfW3R9f/u/5v8sSGlS9vbTkREREQb2e6UfkovZDGVlMrTS25T/zf1Y6Py97y9/URERES0UfVmd6plLCRLn1215Db+1+TPiai+5+3tJyIiIqKNqM/ptXIRC6outJcNF9xnuEz9nLjSa9vHQERERESzrNu+9bvqwvXU6gUsprrI3jNYbJV71M8N6in/DNrHQURERESzqjM7RSxfYXU2eY9YbPfjP0b93Kj8M2gfBxERERHNol1mP6wWr6i6nG5Ri63iP1b9GlH5Z9E+FiIiIiI60upCeJVaukKy9GTJ6R3DhfaA6o/1nyN/rYDqa76qfSxEREREdCTVRfBfq4UrqqnZzlXL7CH4z1G/VlT+mbSPh4iIiIjW001HH/2Hitlo/oGtku0htcgelvpz1a8ZkX8m/tm0j4mIiIiI1lpdqP6nWrSiKnlyiVxiD0f9uerXjMo/m/YxEREREdFa6rZvfbZasKLqLN0tF9g18F9D/dpR+WfUPi4iIiIiOtx6s3eq5SqquqieM1xc1+Ec9WuHVT+j9nERERER0eE0Nfs7crEKK90oltZ18V9Lf42Y/LNqHxsRERERHaq68O1QS1VEJdsXu2ynDBfW9dr7a9VfU32tiOpr3tE+NiIiIiI6WCWnn1MLVVT19V47XFaPWP011deKyj+z9vERERERkeq6bdueVRenTw0XqbjSZ+SiOgP+a+uvGdKn/LNrHyMRERERDZua/YZYosIqOV2sltSZqL+2+ppR+WfXPkYiIiIiembd9u3PVQtUVHURvUsuqLNUv4b62lH5Z9g+TiIiIiL6WnVROmu4OEVWUjpbLqezVL+G+tqBndU+TiIiIiLypmYvFEtTYOl6uZhuAP9a+jXE5J9l+1iJiIiIaJpTr5amkCw93lk6WS2lG8G/ln9N+VoC8s+yfaxEREREy12X0yvVwhRVZ/YhtZBuJP+a6rVE5Z9p+3iJiIiIlrOrt2791pLtIbUsRdRlu18topvBv7Z6TRH5Z+qfbfuYiYiIiJavYvZGtShFVfLk/WoJ3RT1a6vXFJV/tu1jJiIiIlquSs5ZLUhR1WXzzlXL5+a7U722qPwzbh83ERER0fJUcjpPLUdR1SXzzMHSOQ9nqtcWlX/G7eMmIiIiWo46s3+oFqOoSrY9Yumcj/pa1GuMyj/r9rETERERLX51YbtBLUUR1df6WP3Pt+y3bM5Rey3+muTrjaa+1hvax05ERES02PU5vUotRFHVRe2qry2ZgVylXmtc6VXt4yciIiJazK7btu1Pl2yP6mUoILP7xJIZgr82+ZoD8s/cP/v2GBAREREtXsXs/6pFKKouTy5QS2YE/trUa47KP/v2GBAREREtViXnv6YWoLgmd6gFMxJ/jfq1x+TPQHsciIiIiBanuuhcOFx8Ykunq+UyEn+N+rWHdWF7HIiIiIgWo6nZPxZLT1h1iZwOl8rApup7iMqfhfZYEBEREY2/uozdqpaeiPwfnKqv94RnLJLRnTCmf8Cvvt5b22NBRERENO76nF6jFp7ArhwskuH5ax58D8Gl17THg4iIiGic7ZlMvqMuNk+sXnSiSp9Ui+QY+GvX31NIT/iz0R4TIiIiovE1NTtBLDlhdSmdr5bIMfDXrr6nqPzZaI8JERER0bjamfPz1YITVV0WbxsujyN0m/reovJnpD0uREREROOp5HSpWm4i6iw91dnkNLE4jop/D/69qO8xIn9G2uNCRERENI5KSj+lFpuo6ustanEcpfq9qO8xKn9W2mNDREREFL+6cN2plpqI6mt9ZL9FcTE8or7XiOprvbM9NkRERESx63J6rVpooipmlw2WxAVgl6nvNSp/ZtrjQ0RERBSzndu2/eWSbTx/j6jZPXpRXAR2j/qeI/Jnxp+d9hgRERERxas3e5taZMKyyXv0kjh+/r3J7zmq+uy0x4iIiIgoVn3OPyQXmKBKTreoBXGh1O9Rfe9x5R9qjxMRERFRnOpS9UG9vARk6cn6et8hl8NFUr9H/17lexCQP0PtcSIiIiKKUUnpX6nFJarO0i65GC4g/17VexCVP0vtsSIiIiKab/3Kyh/sLX1cLS1BPaQWwkXm3/PgPYjLn6X6TLXHi4iIiGh+9Tn9qlxYwppcopbBRebfs34vokq/2h4vIiIiovl03bZt36sXlZiK2d1qEVwOdrd6T6LyZ6s9ZkRERESbX12eTlNLSlR14Ttn9QK4NM5R70lU/my1x4yIiIhoc+tzfoFaUOJKN4nlb6n4e6Dfm6jyC9rjRkRERLR51aXpWr2chPTFLtspavlbJv4e+HsxeG8CS9e2x42IiIhocypmL9OLSUydpR1q8VtG/l6o9ygqf9baY0dERES0sV28bduzekv3qaUkopLTZ9TCt9Tqe6Leq5Dqs+bPXHv8iIiIiDauPqfXy4UkqGJ2sVz2lppdrN6ruNLr2+NHREREtDF127c9Vy8iMdWF7i696MHfG/WeReXPXnsMiYiIiGZfZ3aWWkKiKimdrZc8+Huj3rOo/NlrjyERERHRbKuLxgvVAhJVZ+kGueDh6/w9Uu9dVP4MtseRiIiIaHaVnHq1fIRk6fG6yJ08XOywysn+Xsn3MCB/BtvjSERERDSbSkr/Xi0eYZl9SCx1EPy9ku9hUP4stseSiIiI6MjaM5n88boQPaiWjohKtvuHyxwOob5n6r2MqL7eB/2ZbI8nERER0fqri8XvqIUjqpIn799vicOh1fdMvZdR1df8O+3xJCIiIlpf3fZtphaNqOoCdOd+CxzW4k71nkblz2Z7TImIiIjWXm/2HrVkhGXpXWKBw2Hw906+p1HVZ7M9pkRERERra2r2D+SCEdcetcDh8Pl7OHhPQ/NntD2uRERERIdfyel6tVxEVJe0x+rrPWm4uGGN9r2Hj6n3OCJ/RtvjSkRERHR41QXiP6rFIqq6nF2138KGI3GVeo+j8me1PbZEREREB293Sn+qN/ucWiqC+pRY1nAE/D0dvMdx1WfVn9n2+BIREREduKml/yMXirAmF6hlDevn76l+r2PyZ7Y9vkRERES6sjI5Vi0SUZWcPqwWNcxAfW/Vex6VP7vtMSYiIiJaXV0YRvV/yduV0xlyScMR8/dWveeBXdAeYyIiIqL9m5r9pFgewio5TdWChhmq77F676PyZ7g9zkRERERP1+d0i1oeIqoL2KNdthPlcoaZ2fse1/dafQYxpVva40xERES0ry6n1+jFIaZidqVazLAR7Er1GUTlz3J7rImIiGjZu3Yy+Y66zDyhloaIOkv36oUMG8Xfc/VZROTPsj/T7fEmIiKiZa4uBieohSGqunidP1zEsOHOV59FVP5Mt8ebiIiIlrV+ZdsPqEUhqrpw3T5YwLB5blefSVj12W6PORERES1jJdslckkIqC5aTxWbnDZYvrBp9r73T6nPJiJ/tttjTkRERMtWZ/bP1YIQVcmprF6+sKnqZ6A+m6j8GW+POxERES1TdXH5iFoOQrL0yKqlC3Phn4X8jAKqr/cj7XEnIiKiZanP6VfUYhBVMbt8uHBhXuxy9RnFlX6lPfZERES06O2ZTP5SyfYVvRQEZHaPXrgwL/6ZyM8qIH/W/Zlvjz8REREtcsXsZLUQRFXy5Dy1bGGO6meiPquo/Jlvjz8REREtaiXnv6EWgbjSLXLRwtyN6V8Z7fzZb8eAiIiIFrF64Y/nX+dq9uW6TL1DLVmYP/9s9n1G4rOL6cp2DIiIiGjRmpr9S3H5B5Z2qQULcfhnpD+7mPwMtONAREREi9IVxx//DXUxuVtd/hGVbA8PlyoEVT8r9RlGVF/v3X4W2rEgIiKiRajP6XXq4o+qy+nSVQsVQvLPSn2GcaXXtWNBREREY293St+jL/yY6vJ093CZQnij+f8WOD8T7XgQERHRmJuanaou+6i6nM4VixQC889MfZZR+Zlox4OIiIjG2q6cX6Au+qhKTjepRQojUD879ZlG5WejHRMiIiIaY/VCv2Z4wUfV2eRLXbZT5BKF8Pyz889QfbZBXdOOCREREY2tYvYycbmHVVLaoRYojEj9DNVnG5WfkXZciIiIaCz1KyvfVBeP+9TlHlF9rQ/utzBhzB5Un3FE9bXe52elHRsiIiIaQ11Or1cXe1TF7OLBsoTRsovVZxyVn5V2bIiIiCh6uyaTv6ou9KjqYnSXXpgwXnaX+qyj8jPTjg8RERFFrjd7l7rMw0rpbL0sYaz8M5WfdVT1zLTjQ0RERFHrc/5ReZEHVZeiG4ZLEhbGDeozjyv/aDtGREREFLGSU9GXeECWHq/L0MmD5QiL42T/jOVnH5CfnXaMiIiIKFrF7N+pCzyq+nqvEcsRFsp4/hxn52eoHSciIiKKUr+y8sd6S59Rl3dQ9+vFCIvGP+vBZx+Xn6F6ltqxIiIiogj1Of22vLjDSu9XSxEWj3/W+hmIKv12O1ZEREQ07/ZMJklf2EGZ3akWIiwu/8zlsxCUn6l2vIiIiGieFbNz1WUdVWfpXWoZwuLyz1w9C1H5mWrHi4iIiOZVn/OL1UUdVcmT69QihCVQP3v1TMSVX9yOGREREc2jeiGPZnmoy85jJaeTVi1AWA77PvvH1LMR1HXtmBEREdFmNzX7BXE5h9VZunrV8oOl4s+Aejai8jPWjhsRERFtVv3Kyrf1lh5Rl3NEJadPqcUHS6g+C+oZCcnPWD1r7dgRERHRZtTn9CZ5Mcd1gVx6sHT8WRg8G8GlN7VjR0RERBtdmUyO1RdyTCWnD6uFB0usPhPqWYnKz1w7fkRERLSRdTau/4tYXWrOkMsOlld9JtSzEpWfuXb8iIiIaKOqF+5Pqos4qrrU7F615AD77FbPTFR+9toxJCIioo2o5HSLuoQjqovMo122EwfLDbBXezYeVc9ORH722jEkIiKiWden9J/VBRyW2ZXD5QZ4Jn9G5LMTVT2D7TgSERHRrJqa/bm6GDwuL9+A6mu995kLDXAQ96pnKKL6Wh/3s9iOJREREc0iXwjUxRtVMTv/GYsMcBB2vnqGovLX3I4lERERHWllZfL96sKNqi4ut69eZoCDsdvVsxSVn8l2PImIiOhI6s0+oC7boJ7qbfJOvcwAmj8ze58d/UzFU89kO55ERES03qZm/0xetGGlohYZ4FD82dHPVEx+NtsxJSIiovU0qn+DlKVH1AIDHC5/huSzFZCfzXZMiYiIaK3Vi/S/qgs2qrqoXD5cXIA1ulw9W1H5GW3HlYiIiA63qdl39pa+rC7XoD4hlhZgzfxZGjxbcdUz6me1HVsiIiI6nPqc3iov1qBKnpynlhZgzeqzpJ6xuNJb27ElIiKiQ1VWJj+oL9SYOku3yoUFWCd/ptSzFpWf2XZ8iYiI6GD1ZleoyzSiku3LdSk5VS0rwHrtfabqs6WeuZDqmW3Hl4iIiA7U1Oxn5EUaVtqlFhXgSPmzpZ+5mPzstmNMREREw644/vhvqJf7x9QlGlHJ9rBaUICZqc+YevZiSh/zM9yOMxERET2zLqfX6Qs0ppLTpXI5AWalPmPq2YvKz3A7zkRERPS1dqT0PerijKouIB+Xiwkwa/VZU89gVH6W27EmIiIir17op6pLM6q6fJy7aiEBNkJ91tQzGFV9zae2Y01EREQlT/62ujCjKmY3r1pGgA1lN6tnMSo/0+14ExERLXcl2zXqsoyoLh1fqv95yupFBNg47ZnzZ08+l9H4mW7Hm4iIaHkrZj+rLsqo6rKx45kLCLCJdqhnMio/2+2YExERLV/XHnfcH6mX973qkgzJ0oODxQPYVP4MymczoPp67/Uz3o47ERHRctXn9OvqggzL7APDxQPYTP4MymczrPTr7bgTEREtT7tTOlpfjGHdpRYPYLP5szh4NkPzs96OPRER0XJUL+wz1aUYVcmTdw8XDmAu6rOontGo6ms+sx17IiKixa9e1H9PXYhR1Yv6hv0WDWD+blDPalR+5tvxJyIiWuzqxdcNL8LAnqhLxcmDJQOYt5P92Rw8q5F17fgTEREtblOzfysuwbBKnlwjlgxg/uqzqZ7ZqPzstzFARES0eO089thvqRf0A+oSjKirr3XVcgEE4s+oenYjqq/3AZ8BbRwQEREtVn1Ob1AXYFR1ibhouFgAkfgzqp7duNIb2jggIiJanHanNNEXX1Bmd6rFAojGn1X5DAfls6CNBSIiosVoaukcdelF1eXJWWqpAKLxZ1U9w1H5LGhjgYiIaPztypMXqwsvqpIn16mFAgirPrPqWQ5rZfJjbTwQERGNu3qx7Vl10QVVzL5QcjpJLhNAVHufWfuCeqaD2tPGAxER0Xirl+8viEsurLo0XL1qiQDG4Wr1TEfls6GNCSIiovHVr6x8W718H1GXXEQlp08PFgdgXOozrJ7tiOrrfcRnRBsXRERE46rL6U3qggvsglWLAzAi/gwPnunQfEa0cUFERDSeupSOURdbVCWnD6vFARid+iyrZzwqnxVtbBAREY2jYvY+danFlc6QSwMwMv4s62c8Jp8VbWwQERHFr8+Tn1AXWliWdquFARgrf6blsx7W5Cfa+CAiIopdyXazvswCsvRoscmJalkAxmtyoj/b8pkPyGdGGx9ERERxK2b/SV1kUZWUPqgXBWDk6rOtnvmofHa0MUJERBSvkvOf7S2N5g+tn1q6Vy4IwILwZ1w9+yHV2eEzpI0TIiKiWPU5/Z68wIKqi8D5w8UAWDDnq2c/rvR7bZwQERHFaXdK36cvrpiK2e1iKQAWkN2uzkBUPkvaWCEiIopRvUwvVpdWRKXqbPJOvRQAi2Xvsz44A5H5LGljhYiIaP71efISdWFFVXLq1UIALKz6zKuzENfkJW28EBERzbd6Md2x+qIKytIjchEAFpw/+/JMxHRHGy9ERETzq5j9srikwuosXaGWAGDR+bOvzkRUPlvamCEiItr8rjH7zt7Sk+qSiqhk+4RaAIClUc+AOhsh1dniM6aNGyIios2t5PRWeUEFVV/vefLyB5ZFPQPqbETlM6aNGyIios2rTCY/qC6mqOolf+uqSx9YTreqMxKVz5o2doiIiDanzmw0f79fyfaVermfOrjsgWV1qp8JdVYi8lnTxg4REdHGVy+en1EXUlQlTzpx2QPLq54JdVai8pnTxg8REdHG9a4tW/5Ayelj6jKKKT0sL3pgyfnZ0GcmHp85PnvaGCIiItqYitn/UBdRXOlSdckDy87Phj4zMfnsaWOIiIho9k3NjlIXUFzp4+qCB7CPnxF9dmLyGdTGERER0WwrOb1DXT5RlWznqssdQFPPiDo7UfkMauOIiIhodpWV9LfUxRNVMbtZXuwABuxmdYai8lnUxhIREdFs6s0+pC6diKaWvlTS5O36Ugewn3pW/MyosxRSnUVtLBERER1505z/jbxwgqqX9g55oQOQ/MyosxSVz6Q2noiIiNbfXccf/4dLTp9Ul01Ilh5UFzmAg/OzI89UQD6TfDa1MUVERLS+itn/UhdNVJ3ZB9QlDuDg/OyoMxWVz6Y2poiIiNbe1Ow56oKJyv9QeXWBAzhMo/qXwez948ae08YVERHR2upzOkNdLlHVS/rd8vIGcHjqGVJnK650RhtXREREh9/ulfQj+mKJqZjdKC9uAGtkN6ozFpXPqja2iIiIDq/ebJe6VCIq2Z7obPI2fWkDWIu9Z6meKXXWQqqzqo0tIiKiQ9fn/Ap5oYQ1uUZd2ADWx8+UPmtR5Ve08UVERHTgdh577LfUi+P+1RdJTPVSfmB4SQOYiQfUmQvqfp9dbYwRERHpupzeIC6RsOplfNHgcgYwGxepMxeVz642xoiIiFa3M6WJukCiKjl9VFzOAGalnjF19qLyGdbGGRER0f7Vi+0cdXkEdtaqixnAzPgZG5y50OprPqeNMyIioqfrVyY/pi6OqLqcrh9eygBmz8+aOoNh1VnWxhoREdG+SrY98tKI6Qt9TiepSxnAbPlZ23fm5FkMx2dZG2tERET+tyzYf1AXRlQlp6vVhQxgg9Qzp85iVD7T2ngjIqJlbtcxx/zJ3tJn1WURUb1wPy0vYgAbq549dSZDqjPNZ1sbc0REtKz1Of2uvCjiulBewgA2lJ+9wVkMLv1uG3NERLSMTc226wsiqvRhdQED2Bx+BvXZjMlnXBt3RES0bNWL63x1OUTVWTpzePEC2Dx+BtXZjKq+5vPbuCMiomWqX0n/SF0MURWz3cNLF8A82G51RsOqs66NPSIiWpbqBXDTqgshqJLt88UmJ+pLF8Dmqmexnkl1VoO6qY09IiJahqZmvygug7BKTh/UFy6AuahnUp3VqHzmtfFHRESL3K5jjvn2elE9pi6DiOprvW+/CxZAFPepMxtRfa2P+exrY5CIiBa1Pqc3q4sgqs7S+waXK4AA/GyqMxtXenMbg0REtIhNzZ6nL4CwblcXLIAY/IwOzmxoPgPbOCQiokVraukiNfyjKnlyurpcAQRRz6g6u1H5DGzjkIiIFqldefISNfijKjn18mIFEEs9q+oMR+WzsI1FIiJalEq2O9TQj6iYfU5eqACCss+psxyRz8I2FomIaBGql9Avq4EflqUr9GUKICI/s/IsB+UzsY1HIiIac/3Kyl+sF9GTathHVHL65PASBTAC9eyqMx1Rfb1P+mxsY5KIiMZavXxOUoM+rnTeqgsUQHh+dvWZjslnYxuTREQ0xrqUjlcDPqp6Wd46vDwBjMqt6mxH5TOyjUsiIhpb9dK5XA33iEq2r0xX0qmDSxPAiOw9w/UsqzMeUX3Nl7dxSUREY6rPk59Wgz2uSTe8NAGMj59lfcajmvx0G5tERDSGvrply+8v2e7SQz2kh9WFCWCc/EwPznhYPit9ZrbxSURE0Stm/10N9Kg6S5epyxLAOPmZVmc9Kp+ZbXwSEVHkSs7frQZ5WJY+ri5KAOPmZ1ue+aB8drYxSkREUetzersa4lEVs3PVJQlg7OxcdebjSm9vY5SIiCK2O6W/qQd4TPUivFlfkAAWg92szn5UPkPbOCUiomjVi+VqNbwjqq/1yZImb9//UgSwUPad8fH8mxnrDG3jlIiIItXnyUvV4I6qXig7v34ZAlhkO9UMiGvy0jZWiYgoQnccddQ31gH9idUDOyizB8VlCGBB+ZmXsyCmT/hMbeOViIjm3dTs18SwDqvY5BJ1GQJYVJNL1CyIymdqG69ERDTPdpg9Rw3qqEpOH9MXIYCFVs++mglR+WxtY5aIiOZVn9PpakhHVS+7d8tLEMBiq2dfzYS40ultzBIR0TwqKf2IHtBBmd0oL0AAS8FngJwNQfmMbeOWiIg2u85slxrOEZVsX+xt8jZ1+QFYDntngM8CMSMi8hnbxi0REW1mXZ68Qg3mqOrrvVZdfACWi88CNSOi8lnbxi4REW1GH3r2s/9oyXa/GsoRdZYeUBcegOXkM0HNioh81vrMbeOXiIg2umL2W2ogRzW1dJG67AAsJ58JalZE5TO3jV8iItrIpmbb1CCOK31UXXQAlpvPBj0zYvLZ28YwERFtVGP7I3q6bGepSw7AcvPZoGZGVD572xgmIqKNqKT099UAjqrL6Xp1wQGA8xmhZkdUPoPbOCYiolnXm+1WwzeiabYvlJzeqi43ANirzgifFWqGhFRncBvHREQ0y/qcf14O3qDqBXa1vNgA4JnqrFAzJK78820sExHRLLrpuKP/RMn2sB668dTL69OrLjMAOLBPq1kSkc9in8ltPBMR0ZFWzP63GrhR1dd7objIAOAA7EI1S6LymdzGMxERHUnTnFfUoI2qXlofWX2JAcAhfUTNlKh8NrcxTURE663P6b1qyEZVL6szB5cXAByOM9VMiSu9t41pIiJaTyWlH9cDNqZitkdcXgBwmGyPmi1R+Yxu45qIiNZab3ajGq4RlWyf72zyFn15AcCh7Z0hdZaoGRNSndFtXBMR0Vrqc361HKxhpQ+qiwsA1sJniZ4xUeVXt7FNRESH065jjv72OkBH9H/VSPepCwsA1sNnipw1MX3eZ3Yb30REdKi6nN4shmlYnaX3qcsKANbDZ4qaNVH5zG7jm4iIDtYus+epQRpVl+0OdVEBwJHw2aJmTlQ+u9sYJyKiA1UH/EVqiMaVTh9eUABwpHy26JkTU33NF7UxTkREqpLTP1UDNKppTv3wcgKAWfEZo2ZPVD7D2zgnIqJhxex2NTwjKtk+14uLCQBmZe+M8VkjZlBEPsPbOCciomdWB+R/UYMzrnSFupgAYJZ81ugZFJPP8jbWiYjI67Zv/wt1oH9JDc2Y0ieHlxEAbBSfOXoWxVNf75d8prfxTkREdTi+ZTgsIys5vXd4EQHAhqkzR82iwN7SxjsR0XI3NfvrYkiGVS+cW+VFBAAbqc4eNZOi8tnexjwR0fJWB/hlakhGVLJ9pct22qoLCAA22N7ZU2eQmk0R1dd8WRvzRETLWcnpX6gBGVW9ZLrh5QMAm6bOIDWbovIZ38Y9EdFy9dUtW35fHYQfHQ7GsCx9Vl48ALCJfBbJGRXTR33Wt7FPRLQ8Tc3+mxiKYdUL5rLhhQMAczCav93L+axvY5+IaDnqtm//LjUQo6oXyz2DiwYA5ukeNaui8pnfxj8R0eJXB98pw0EYWWf2HnHRAMBc+ExSsyqwU9r4JyJa7KZmPyyGYGQ3q4sGAObJZ9NgVoXms79dA0REi9vU0lVqCIZk6cmS0zvUJQMAc1Vnk88oObsC8tnfrgEiosVsV568VA3AqIrZTnnBAEAItlPNrqj8DmjXARHRYnXhUUd9Yx10o/kHKEq2h/TFAgCB1FmlZlhQ9/hd0K4FIqLFqZj9mhh6YZU8uUReKgAQSZ1VaoZF5XdBuxaIiBajfmXlr6iBF1Vn6W55oQBAQD6z1CwLq94J7XogIhp/JafT5bALK71bXSYAEJHPLD3LYvI7oV0PRETjrkvp76pBF9iN6iIBgMh8dg1mWWh+N7RrgohovNUBPKZ/KviL/crkbcMLBACi89m1d4bp2RZOfc072zVBRDTO+pxergZcVCWna4eXBwCMRp1harbFlV7ergsionF109FHf3PJ9mk93OIpZg/IiwMARsUeUDMuIr8j/K5o1wYR0Xiqw/Y31WCLqsvpYn1pAMB4+CxTMy4qvyvatUFENI5KzlvVQIsrfVRdGAAwRj7T9KyLye+Mdn0QEcWvDtmz1TAL7Cx1WQDAGPlMG8y44NLZ7fogIord1OxFepDFVHK6Xl0UADBqdbapmReV3x3tGiEiilsdsFM1xCKqr/XxktJb97scAGAR7Jttj6vZF1F9rdN2jRARxazP6ZVqgIVl9qH9LgYAWCA+4+TsCyu9sl0nRESxumHr1m+tg+qh1YMrKLNPq4sBABaJzzo5A2N6yO+Sdq0QEcWpmL1RDK2wSkrvV5cCACyUOuvUDIzK75J2rRARxajknNXAiqoO/4+sugwAYHF9RM3CqPxOadcLEdH863M6Tw2rqDpLZ4qLAAAWks88NQvjSue164WIaL6VlH5cD6qYitkedREAwGKzPWomRuV3S7tmiIjmVx2gN6ohFVFn6bHeJm9ZfQEAwGLz2bd3BorZGFF9zTe2a4aIaD51efJqNaDiSh8cDn8AWBY+A/VsjMnvmHbdEBFtbjue+9w/U7J9Xg2niIrZfWrwA8BysfvUjIzI7xi/a9q1Q0S0edVh+f/UYIqqDvj3rR74ALB03qdmZFR+17Rrh4hoc+pzPk4NpKhKtjvEsAeA5VRnopqVceXj2vVDRLTxlTyyP4A8p9PlsAeAZVRnopqVUfmd064fIqKNraT0T9QgiqqzNJWDHgCWmM9GNTOj8runXUNERBtXb+k2NYSC+lwd6CcMBzwAIJ3gM3IwM+Oqd0+7hoiINqY+p1+SAyisdIUY7gCAymeknp1RpV9q1xER0Wy7fuvWP1+yfVEPn3hKTp9Ugx0A8Ax1VqoZGpHfQX4XtWuJiGh2FbMT1eCJqg7v98qhDgB4Wp2VaoZG5XdRu5aIiGZTn/Pz1cCJK90mBzoAYBWfmXqWRpWf364nIqIjrw7BS/WwCcjSV+rv+E9TwxwAoNhpPjvlTA0pXdquJyKiI2t3Sj+lB01MJaWiBzkA4IDq7FQzNSq/m9o1RUS0/nqzO9WQCcnSZ+UABwAcks9QOVsjqndTu6aIiNZXn9Nr5YAJqg7qy4aDGwBw2C5TszWu9Np2XRERra1u+9bvqoPkqdWDJaY6oO8ZDGwAwNrdo2ZsUE/5XdWuLSKiw68zO0UMlbA6m7xHDGwAwBr4LFUzNiq/q9q1RUR0eO0y+2E1UKLqcrpFDWwAwNr5TFWzNiq/s9r1RUR06Oqgu0oNk5AsPVlyesdwUAMA1qnOVJ+tcuYGVF/zVe36IiI6eHXA/Ws1SKKamu1cNaQBAEfEZ6uauVH53dWuMSIi3U1HH/2Hitlo/kGEku0hNaABADNQZ6yavRH53eV3WLvOiIhWVwfF/1QDJKqSJ5fI4QwAOHJ1xqrZG5XfYe06IyLav2771merwRFVZ+luOZgBADPjs1bN4Kj8LmvXGhHR0/Vm71RDI6o6gM8ZDmQAwMydo2ZwWPUua9caEdG+pmZ/Rw6MsNKNYhgDADaAz1w9i2PyO61db0REe/84sR1qWERUsn2xy3bKcBADADbG3plbZ6+ayRHV17yjXW9EtOyVnH5ODYqo6uu9djiEAQAbrM5eNZOj8rutXXNEtKxdt23bs+pA+NRwQMSVPiMHMABgw/kM1rM5pE/5HdeuOyJaxqZmvyGGQ1j1d+gXq+ELANgEdQar2RyV33HtuiOiZavbvv25ajBEVQfsXXLwAgA2T53FakZH5Xddu/aIaJmqA+Cs4UCIrKR0thy6AIDNU2exmtGBndWuPSJalqZmLxTDILB0vRy4AIBN5zNZz+qY/M5r1x8RLUPTnHo1DEKy9Hhn6WQ1bAEAm89nss9mObMD8juvXX9EtOh1Ob1SDYKoOrMPqUELAJgfn81qZkfld1+7BoloUbt669ZvLdkeUkMgoi7b/WrAAgDmz2e0mt0R+d3nd2C7DoloEStmb1QDIKqSJ+9XwxUAEECd0Wp2R+V3YLsOiWjRKjlndfCjqkP0zlVDFQAQzZ1qhkfld2G7FolokSo5nacOfVR1eJ45GKYAgHjOVDM8Kr8L27VIRItSZ/YP1YGPqmTbI4YpACCiOrPVLI/K78R2PRLRIlQH0Q3qsEdUX+tj9T/fst8QBQCE1Wa2z24516Opr/WGdj0S0djrc3qVOuhR1QF01deGJwBgNK5SMz2u9Kp2TRLRWLtu27Y/XbI9qg95QGb3ieEJABgBn+Fytgfkd6Pfke26JKIxVsz+rzrgUXV5coEangCA+HyGq9keld+R7bokorFVcv5r6mDHNblDDU4AwHj4LNczPia/K9u1SURjqh7gC4cHOrZ0uhqaAIDx8FmuZ3xYF7Zrk4jG0tTsH4vDHFYdjtPhsAQAjNZUzfqo/M5s1ycRjaE6ZG5Vhzki/wcC6us94RkDEgAwbieM6R+Erq/31nZ9ElH0+pxeow5yYFcOBiQAYOR8tg9mfXDpNe0aJaKo7ZlMvqMe2CdWH+Co0ifVgAQAjJ/PeD37Q3rC79B2nRJRxKZmJ4jDG1aX0vlqOAIAxs9nvJr9Ufkd2q5TIorWzpyfrw5uVHUI3jYcigCAhXObugOi8ru0XatEFKmS06Xq0EbUWXqqs8lpYiACABaIz3qf+eouiMjv0natElGUSko/pQ5sVPX1FjUQAQALqM58dRdE5Xdqu16JKEJ1kNypDmtE9bU+st8ABAAsg0fUnRBRfa13tuuViOZdl9Nr1UGNqphdNhh+AICFZ5epOyEqv1vbNUtE82rntm1/uWQbz9/7ZHaPHoAAgMVn96i7ISK/W/2ObdctEc2j3uxt6oCGZZP36OEHAFh0fgfIuyGqese265aINrs+5x+SBzOoktMtavABAJZIvQvUHRFX/qF27RLRZlaHxQf1oQzI0pP19b5DDj0AwPKod4HfCfKuCMjv2nbtEtFmVVL6V+pARtVZ2iUHHgBg6fidoO6KqPzObdcvEW10/crKH6y/G/64OoxBPaQGHQBgefndMLgr4vI7t9697Romoo2sz+lX5UEMa3KJGnIAgOXld4O+M6JKv9quYSLaqK7btu179QGMqZjdrQYcAAB+R6i7Iyq/g9t1TEQbUR0Kp6nDF1UdZOesHmwAAOx1jro7ovI7uF3HRDTr+pxfoA5eXOkmMdQAAPg6vyv0HRJVfkG7lololtVhcK0+dCF9sct2ihpqAAB8jd8VfmcM7pDA0rXtWiaiWVXMXqYPXEydpR1qoAEAMOR3hrpLovI7uV3PRHSkXbxt27N6S/epwxZRyekzapABAHBA9e5Qd0pI9U72u7ld00R0JPU5vV4etKDq73QvlkMMAIADsovVnRJXen27polovXXbtz1XH7CY6qC6Sw8wAAAOxe5Sd0tUfke365qI1lNndpY6XFGVlM7WwwsAgEOod4i6W6LyO7pd10S01uoBeqE6WFF1lm6QgwsAgMPkd4m6Y6Lyu7pd20S0lkpOvTpUIVl6vA6ok4cDCwCANTrZ7xR51wTkd3W7tonocCsp/Xt1oMIy+5AYVgAArJnfKfKuCcrv7HZ9E9Gh2jOZ/PF60B9Uhymiku3+4ZACAOCI1LtF3TkR1df7oN/d7RonooNVD8zvqIMUVcmT9+83nAAAOFL1blF3TlT1Nf9Ou8aJ6EB127eZOkBR1YN9536DCQCA2blT3T1R+R3ernMiUvVm71GHJyxL7xKDCQCAI+Z3jLx7oqp3eLvOiWjY1OwfyIMT1x41mAAAmBW/awZ3T2h+l7drnYieWcnpenVoIqrD57H6ek8aDiQAAGZq313zmLqLIvK7vF3rRPS16sH4j+rARFWHzlX7DSIAADbOVeouisrv9Ha9E9HulP5Ub/Y5dViC+pQYQgAAbBi/ewZ3UVz1Tve7vV3zRMvd1NL/kQclrMkFaggBALBR/O7Rd1JMfre3a55oeduzMjlWHZCoSk4fVgMIAIANV+8gdTdFVeod3657ouWsHoRR/Q51V05nyOEDAMAG8ztI3U2BXdCue6Lla2r2k+JQhFV/Jz1VgwcAgE1T7yJ1R0Xld3279omWqz6nW9ShiKgOlke7bCfKoQMAwCbZexfVO0ndVTGlW9q1T7Q8dTm9Rh+ImIrZlWrgAACw+exKdVdF5Xd+u/6JFr9rJ5PvqIf0CXUYIuos3asHDQAA8+F3k7qzIvI73+/+tgYQLXb1gT9BHYSo6kA5fzhgAACYs/PVnRWV3/1tDSBa3PqVbT+gDkBUdZDcPhgsAABEcbu6u8KqO0BbB4gWs5LtEvnwB1QHyFPFJqcNhgoAAEHsvaOeUndYRL4DtHWAaPHqzP65evCjKjmV1UMFAIBA6l2l7rCofBdoawHRYlUP5EfUQx+SpUdWDRMAAALyO0veZQHV1/uRthYQLU59Tr+iHvioitnlw0ECAEBMdrm6y+JKv9LWA6Lxt2cy+Usl21f0wx6Q2T16kAAAEJPfXfJOC8h3At8N2ppANO7q7zRPVg96VCVPzlNDBACAsOrdpe60qHw3aGsC0XgrOf8N9YDHlW6RAwQAgODG9K/Wd74jtHWBaJzVB3k8/5pCsy/XIfEONTwAAIjO77B9d5m442K6sq0LRONravYvxUMdWNqlBgcAAGPhd5m+42LyXaGtDUTj6Yrjj/+GeuDuVg91RCXbw8NhAQDAKNU7Td11EdXXe7fvDG19IBpH9XeUr1MPdFRdTpeuGhQAAIyQ32nqrosrva6tD0Tx253S9+gHOaY6FO4eDgkAAEZuNP9fVee7Q1sjiGI3NTtVPcRR1d/5nisGBAAAo+V3m7rzovLdoa0RRHHblfML1AMcVcnpJjUgAAAYvXrHqbsvKt8h2jpBFLP6oF4zfHCj6mzypS7bKXI4AAAwcn7H+V2n7sCgrmnrBFG8itnLxEMbVklphxoMAAAsjHrXqTswKt8l2lpBFKd+ZeWb6oG6Tz20EdXX+uB+gwAAgMX1oLoLI6qv9T7fKdp6QRSjLqfXqwc2qvo7xosHQwAAgAVlF6u7MCrfKdp6QTT/dk0mf1U9qFHVA3+XHgQAACwqu0vdiVH5btHWDKL51pu9Sz2kYaV0th4CAAAsJr/75J0YVd0t2ppBNL/6nH9UPqBB1cN+w/DwAwCwJG5Qd2Nc+UfbukE0n0pORT+cAVl6vB7ykweHHgCAZXGy34XyjgzId4y2bhBtfsXs36kHM6r6eq8Rhx4AgCUynj/v3vmu0dYOos2rX1n5Y/V3hZ9RD2VQ9+sDDwDAcvE7cXBHxuW7Rt052vpBtDn1Of22fCDDSu9Xhx0AgGXjd6K+K6NKv93WD6KNb89kkvSDGJTZneqgAwCwrPxulHdmUL57tDWEaGMrZueqhzCqztK71CEHAGBZ+d2o7syofPdoawjRxtXn/GL1AEZV8uQ6dcABAFh69Y5Ud2dc+cVtHSHamOqDNppDUQ/xYyWnk1YdbAAAUBfdvXfkY+oODeq6to4Qzb6p2S+Ihy6sztLVqw41AAD4Or8r1R0ale8ibS0hml39ysq39ZYeUQ9dRPV3qZ9SBxoAAAzUO1PdpSH5LlJ3kraeEM2mPqc3yQcurgvkYQYAAPvxO3NwhwaX3tTWE6Ijr0wmx+oHLab6O9MPq4MMAAAOoN6d6k6NyneTtqYQHVmdjet3evWwniEPMQAA0Ordqe7UqHw3aWsK0fqrD9JPqgcsqnpYd686vAAA4HDsVndrVL6jtHWFaH3V3+Hdoh6uiOoBfbTLduLg0AIAgMPQ7tBH1R0bke8obV0hWnt9Sv9ZPVhhmV05PLQAAODw+V0q79io6q7S1haiw29q9ufqA/+4fKgCqq/13mceVAAAsG73qrs2ovpaH/edpa0vRIeXP+jqgYqqmJ3/jAMKAADWzc5Xd21U/prb+kJ06MrK5PvVgxRVPZC3rz6kAABg/ex2dedG5btLW2OIDl5v9gH1EAX1VG+Td+pDCgAA1sPv1r13rL5746m7S1tjiA7c1OyfyQcorFTUAQUAAEfG71h998bkO0xbZ4h0o/o3o1h6RB1MAAAwG37Xyjs4IN9h2jpDtLr6gPxX9eBEVQ/g5cMDCQAAZupydQdH5btMW2uInm5q9p31d21fVg9NUJ8QhxEAAMyY37mDOziuusv4TtPWG6J99Tm9VT4wQZU8OU8dRgAAMGP1zlV3cVzprW29Idr7x4n9oH5QYuos3SoPIgAA2BB+96o7OSrfbdqaQ8teb3aFekgiKtm+XA/bqeoQAgCAjbH37q13sLqbQ6q7TVtzaJmbmv2MfEDCSrvUAQQAABvL72B9N8fkO05bd2gZu+L447+hPrQfUw9HRPV3kg+rgwcAADZJvYvVHR1T+pjvOm3toWWry+l1+sGIqeR0qTx0AABgc9S7WN3RUfmu09YeWqZ2pPQ96oGIqh6sj8sDBwAANle9k9VdHZXvPG39oWWpPqinqochqnqozl110AAAwOard7K6q6Oqr/nUtv7QMlTy5G+rByGqYnbzqkMGAADmyG5Wd3ZUvvu0NYgWvZLtGvUQRFQP05fqf56y+oABAIB5aXez39Hy/o7Gd5+2BtEiV38H9rPqAYiqHqIdzzxYAAAgjB3q7o7Kd6C2DtEidu1xx/2R+lDeqz78kCw9ODhQAAAgEL+r5R0eUH299/ou1NYiWrT6nH5dffBhmX1geKAAAEAcflfLOzys9OttLaJFandKR+sPPKy71IECAACx+J09uMND852orUe0KNUH8Uz1YUdV8uTdw4MEAAACqne2usujqq/5zLYe0SJUH8C/pz7oqOoDeMN+BwgAAER3g7rTo/LdqK1JNPbqB9oNP+DAnqiH5eTB4QEAALGd7Hf44E6PrGtrEo25qdm/FR9uWPV3WNeIwwMAAKKrd7i626PyHamtSzTGdh577LfUB+8B9eFG1NXXuurQAACA0fC7XN3xEdXX+4DvSm1torHV5/QG9cFGVQ/HRcMDAwAAxsPvcnXHx5Xe0NYmGlO7U5roDzQoszvVgQEAAOPid7q864PynamtTzSWppbOUR9mVF2enKUOCwAAGBe/09VdH5XvTG19ojG0K09erD7IqEqeXKcOCgAAGKl6t6s7PyrfndoaRdGrH9ie4QcYVTH7QsnpJHlIAADAOO292+0L6u4Pak9boyhy9aH6BfHhhVUPw9WrDgcAAFgEV6u7Pyrfodo6RRHrV1a+rT5Uj6gPL6L6u71PDw4EAABYJPWuVztARPX1PuK7VFurKFpdTm9SH1xgF6w6EAAAYGH4XT+4+0PzXaqtVRSpLqVj1AcWVf0d3ofVgQAAAAum3vlqF4jKd6q2XlGUitn71IcVVzpDHgYAALBQ/M7Xu0BMvlO19Yoi1OfJT6gPKixLu9VBAAAAi8nvfrkThDX5ibZm0bwr2W7WH1JAlh4tNjlRHQIAALCoJif6DiB3g4B8t2prFs2zYvaf1AcUVUnpg/oAAACAhVZ3ALUbROU7Vlu3aB6VnP9s/d3RaP4w5qmle+WDDwAAloLvAmpHCKnuWL5rtbWLNrs+p9+TH0xQ9QE/f/jAAwCApXK+2hHiSr/X1i7azHan9H36A4mpmN0uHnYAALB07Ha1K0TlO1dbv2izqg/JxerDiKhUnU3eqR92AACwTPbuBINdITLfudr6RZtRnycvUR9EVCWnXj3oAABgSdXdQO0McU1e0tYw2ujqG37H6g8gKEuPyAccAAAsNd8R5O4Q0x1tDaONrJj9snjzw+osXaEebgAAsNx8R1C7Q1S+g7V1jDaia8y+s/7u50n15kdUsn1CPdgAAAB71V1B7RAh1R3Md7G2ltGsKzm9Vb7xQdXXe558qAEAAFzdFdQOEZXvYm0to1lWJpMfVG94VPXhvXXVwwwAALDarWqXiMp3srae0azqzEbz97GUbF+pD+2pg4cYAABAOdV3B7VTROQ7WVvPaBbVN/Rn1BsdVcmTTjzEAAAAWt0d1E4Rle9mbU2jI+ldW7b8gZLTx9SbHFF9rQ/LBxgAAOBg6g6hdouIfDfzHa2ta7Teitn/UG9wXOlS+fACAAAchO8QereIyXe0tq7RepqaHaXe2LjSx9WDCwAAcDh8l9A7Rky+q7W1jdZayekd6k2NqmQ7Vz20AAAAh6XuEmrHiMp3tba20VoqK+lvqTc0qmJ2s3xgAQAA1sRuVrtGVL6ztfWNDrfe7EPqzYxoaulLJU3erh9WAACANag7he8WaucIqe5sbX2jw2ma87+Rb2RQ9WHcIR9UAACAdfDdQu0cUfnu1tY4Olh3HX/8Hy45fVK9iSFZelA9oAAAAEfCdwy5ewTku5vvcG2dowNVzP6XegOj6sw+oB5OAACAI+E7hto9ovIdrq1zpJqaPUe9cVH5H5asHkwAAICZGNG/NMv5LtfWOhrW53SGetOiqg/fu+VDCQAAMAt111A7SFzpjLbW0TPbvZJ+RL9hMRWzG+UDCQAAMFN2o9pFovKdrq139LV6s13qzYqoZHuis8nb9MMIAAAwO3t3jrp7qJ0kpLrTtfWOvD7nV8g3KqzJNepBBAAA2Ai+e+idJKr8irbmLXc7jz32W+obcv/qNyim+rA9MHz4AAAANsEDajcJ6n7f8dq6t7x1Ob1BvDlh1YfsosFDBwAAsBkuUrtJVL7jtXVvOduZ0kS9MVGVnD4qHjoAAIDNUXcRtaNE5bteW/uWr/qBnaPelMDOWvXAAQAAbBLfRQa7SWj1NZ/T1r7lql+Z/Jh6Q6Lqcrp++LABAABsNt9J1K4SVt352vq3PJVse+SbEdMX+pxOUg8bAADAZvKdZN9uIneWcHzna+vfclTM/oN6I6IqOV2tHjQAAIC5qLuJ2lmi8t2vrYGL3a5jjvmTvaXPqjchovogfVo+YAAAAPNUdxS1u4RUdz/fAds6uLj1Of2ufAPiulA+XAAAAHPkO8pgZwku/W5bBxezqdl2/Y1HlT6sHiwAAIAIfFfRO0xMvgu2tXDxqh/I+eqbjqqzdObwgQIAAIjCdxW1w0RVX/P5bS1crPqV9I/UNxxVMds9fJgAAADisd1qlwmr7oRtPVyc6jd206pvNKiS7fPFJifqhwkAACCSurPU3UXtNEHd1NbDxWhq9ovimwyr5PRB/SABAAAEVHcXtdNE5bthWxPH3a5jjvn2+gE8pr7JiOprvW+/BwcAAGAc7lO7TUT1tT7mO2JbF8dbn9Ob1TcYVWfpfYOHBgAAIDzfYdRuE1d6c1sXx9nU7Hn6GwvrdvXgAAAAjIHvMoPdJjTfFdvaOL6mli5S31RUJU9OVw8NAADAKNRdRu04Ufmu2NbGcbUrT16ivqGoSk69fGAAAADGpO40ateJynfGtj6Op5LtDvXNRFTMPicfFAAAgFGyz6mdJyLfGdv6OI7qm/vL6hsJy9IV+iEBAAAYH99t5M4TlO+ObY2MXb+y8hfrG/yk+iYiKjl9cvhwAAAAjF7dcdTuE1F9vU/6DtnWybjVN/Uk9Q3Elc5b9WAAAACMnO84eveJyXfItk7GrEvpePXCo6oPwa3DhwIAAGCB3Kp2oKh8l2xrZbzqm3m5etERlWxfma6kUwcPAwAAwMLYu+vUnUftQhHV13x5Wytj1efJT6sXHNekGz4MAAAAi8Z3Hr0LRTX56bZexuirW7b8/vq7hbv0iw3pYfUgAAAALCLffQa7UFi+U/pu2dbM+VfM/rt6oVF1li5TDwEAAMAi8t1H7URR+W7Z1sz5VnL+bvUCw7L0cfUAAAAALDLfgeRuFJTvmG3dnF99Tm9XLy6q+juEc9WHDwAAsNjsXLUbxZXe3tbN+bQ7pb+pX1hM9QO+WX/wAAAAy8BuVjtSVL5rtrVz86tv2NXqRUVUX+uTJU3evv+HDQAAsET27ULj+TfY1l2zrZ2bW58nL1UvKKr6Ru38+ocMAACwvHaqXSmuyUvb+rk53XHUUd9Yv/AnVr+QoMweFB8yAADAUvLdSO5MMX3Cd8+2hm58U7NfEy8irGKTS9SHDAAAsJwml6idKSrfPdsaurHtMHuOegFRlZw+pj9gAACAJVZ3JLU7ReU7aFtHN64+p9PVF4+qfojvlh8uAADAMqs7ktqd4kqnt3V0Yyop/Yj+wkGZ3Sg/WAAAAPjfq3uj3KGC8l20raWzrzPbpb5oRCXbF3ubvE19qAAAAPBFt+5KvjOJXSoi30XbWjrbujx5hfqCUdXXe636QAEAAPA035nULhWV76RtPZ1NH3r2s/9o3fbvV18sos7SA+qDBAAAwGq+O6mdKiLfSX03bWvqkVfMfkt9oaimli5SHyIAAABW891J7VRR+W7a1tQja2q2TX2BuNJH1QcIAACAA/MdSu9WMfmO2tbV9Te2P3qiy3aW+vAAAABwYL5Dqd0qKt9R27q6vkpKf1/9wgAAAMC8+a7a1ta115vtVr8oAAAAMHd1V21r69rqc/55+QsCAAAAYeSfb+vr4XXTcUf/iZLtYf2LAQAAADH4zuq7a1tjD10x+9/qFwIAAACi8d21rbEHb5rzivoFAAAAgKh8h23r7IHrc3qv+skAAABAXOm9bZ3VlZR+XP9EAAAAIDbfZdtau7re7Eb1kwAAAIDw6i7b1tr963N+tfwJAAAAwGjkV7f19ul6S7fpHwwAAACMRN1p23q7r6nZC+UPBAAAAEbGd9u25vqfm5vOUT8IAAAAGBvfbfctuTl/t/oBAAAAwFj5juv/ENor1F8EAAAAxiu/wv91v7+l/yIAAAAwTr7jbik5vVv9RQAAAGC80tn+D6JN9V8EAAAAxsl33C0l20PqLwIAAABj5TuuL7oPq78IAAAAjJXvuFt6s93qLwIAAACjVXdc/mE0AAAALKC9/zCa/ab+iwAAAMA4+Y67pW67L1d/EQAAABiv9PItU7Oj9F8EAAAAxsl33C1esXSO+gEAAADA2NTd9ty9S67Xmb1Q/SAAAABgbKZ1t21r7r7q5nur+oEAAADAWPhO29bbp+tzepX6wQAAAMB4pFe19Xb/6l985+ofDAAAAIzCO9tau7rrtm17Vv0BNw1+AgAAABBayXaz77JtrdVNzZ6nfjIAAAAQle+wbZ09ePUH/qz6BQAAAIBofHdta+zh1a9s+4GS0y3qFwMAAADmzXfVsjL5/ra+rq0rjj76m+svcLr6hQEAAIB58R3Vd9W2tq6/qdkv9pZuU18EAAAA2DRmt/lu2tbU2dWZvaj+4u+RXxQAAADYKHUHrQvui9paunFdd8y27y1mLyuWfqN+4bPqf07rfz6034sBAAAA1u6htlv6jvkbvnN227c+u62ha2jLlv8f3X/f6XnixaUAAAAASUVORK5CYII=\"],\"index\":[0,0,0,0,0,1,2,0,0]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 21FLHILL_WQX-101<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-102<br>Sample Condition: all<br> Category: 130 - 999 (380/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-103<br>Sample Condition: all<br> Category: 130 - 999 (490/100mL)<\\/html>\",\"<html>Station Number: 21FLHILL_WQX-104<br>Sample Condition: all<br> Category: 130 - 999 (725/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-12-02<br>Sample Condition: all<br> Category: 130 - 999 (703/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-19-02<br>Sample Condition: all<br> Category: < 35 (10/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-22-01<br>Sample Condition: all<br> Category: > 999 (1990/100mL)<\\/html>\",\"<html>Station Number: 21FLPDEM_WQX-24-02<br>Sample Condition: all<br> Category: 130 - 999 (171/100mL)<\\/html>\",\"<html>Station Number: 21FLTPA_WQX-G1SW0099<br>Sample Condition: all<br> Category: 130 - 999 (908/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>All samples<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info 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location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"show_fibmap(fibdata, yrsel, mosel, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"fibdata input FIB data.frame returned read_importfib read_importwqp, see details yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"# show selected year, month show_fibmap(fibdata, yrsel = 2023, mosel = 8)  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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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(2/100mL)<\\/html>\",\"<html>Station Number: 96<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 97<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 101<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (412/100mL)<\\/html>\",\"<html>Station Number: 102<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (327/100mL)<\\/html>\",\"<html>Station Number: 103<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (173/100mL)<\\/html>\",\"<html>Station Number: 104<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1020/100mL)<\\/html>\",\"<html>Station Number: 105<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (50/100mL)<\\/html>\",\"<html>Station Number: 106<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (48/100mL)<\\/html>\",\"<html>Station Number: 107<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (150/100mL)<\\/html>\",\"<html>Station Number: 108<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (123/100mL)<\\/html>\",\"<html>Station Number: 109<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 110<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (4/100mL)<\\/html>\",\"<html>Station Number: 111<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: > 999 (1033/100mL)<\\/html>\",\"<html>Station Number: 112<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 113<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (20/100mL)<\\/html>\",\"<html>Station Number: 114<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (140/100mL)<\\/html>\",\"<html>Station Number: 115<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (100/100mL)<\\/html>\",\"<html>Station Number: 116<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (53/100mL)<\\/html>\",\"<html>Station Number: 118<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (33/100mL)<\\/html>\",\"<html>Station Number: 120<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (73/100mL)<\\/html>\",\"<html>Station Number: 129<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (92/100mL)<\\/html>\",\"<html>Station Number: 132<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (467/100mL)<\\/html>\",\"<html>Station Number: 133<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1500/100mL)<\\/html>\",\"<html>Station Number: 135<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (7/100mL)<\\/html>\",\"<html>Station Number: 137<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (80/100mL)<\\/html>\",\"<html>Station Number: 138<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (333/100mL)<\\/html>\",\"<html>Station Number: 139<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (96/100mL)<\\/html>\",\"<html>Station Number: 140<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (273/100mL)<\\/html>\",\"<html>Station Number: 141<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (287/100mL)<\\/html>\",\"<html>Station Number: 142<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (96/100mL)<\\/html>\",\"<html>Station Number: 143<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 144<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (120/100mL)<\\/html>\",\"<html>Station Number: 145<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (20/100mL)<\\/html>\",\"<html>Station Number: 146<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (10/100mL)<\\/html>\",\"<html>Station Number: 147<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (100/100mL)<\\/html>\",\"<html>Station Number: 148<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (30/100mL)<\\/html>\",\"<html>Station Number: 149<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (56/100mL)<\\/html>\",\"<html>Station Number: 151<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (70/100mL)<\\/html>\",\"<html>Station Number: 152<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (144/100mL)<\\/html>\",\"<html>Station Number: 153<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (700/100mL)<\\/html>\",\"<html>Station Number: 154<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (260/100mL)<\\/html>\",\"<html>Station Number: 155<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (110/100mL)<\\/html>\",\"<html>Station Number: 158<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (220/100mL)<\\/html>\",\"<html>Station Number: 160<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (270/100mL)<\\/html>\",\"<html>Station Number: 161<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (187/100mL)<\\/html>\",\"<html>Station Number: 163<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (180/100mL)<\\/html>\",\"<html>Station Number: 164<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (140/100mL)<\\/html>\",\"<html>Station Number: 165<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (60/100mL)<\\/html>\",\"<html>Station Number: 166<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (107/100mL)<\\/html>\",\"<html>Station Number: 167<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (460/100mL)<\\/html>\",\"<html>Station Number: 168<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (40/100mL)<\\/html>\",\"<html>Station Number: 169<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (575/100mL)<\\/html>\",\"<html>Station Number: 170<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (310/100mL)<\\/html>\",\"<html>Station Number: 171<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (42/100mL)<\\/html>\",\"<html>Station Number: 172<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (280/100mL)<\\/html>\",\"<html>Station Number: 173<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (210/100mL)<\\/html>\",\"<html>Station Number: 174<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (34/100mL)<\\/html>\",\"<html>Station Number: 175<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (980/100mL)<\\/html>\",\"<html>Station Number: 176<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (128/100mL)<\\/html>\",\"<html>Station Number: 177<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 178<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (630/100mL)<\\/html>\",\"<html>Station Number: 179<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (240/100mL)<\\/html>\",\"<html>Station Number: 180<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (2/100mL)<\\/html>\",\"<html>Station Number: 181<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (4/100mL)<\\/html>\",\"<html>Station Number: 182<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (32/100mL)<\\/html>\",\"<html>Station Number: 264<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: < 35 (28/100mL)<\\/html>\",\"<html>Station Number: 265<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 266<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (60/100mL)<\\/html>\",\"<html>Station Number: 267<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (340/100mL)<\\/html>\",\"<html>Station Number: 268<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (560/100mL)<\\/html>\",\"<html>Station Number: 269<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (147/100mL)<\\/html>\",\"<html>Station Number: 270<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (117/100mL)<\\/html>\",\"<html>Station Number: 271<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 1510<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 35 - 129 (110/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.53248,28.149932],\"lng\":[-82.783203,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # show selected year, month, and area show_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River')  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P70GxHRFCyJEzHdn/yBaTZaQFdL/4O4LlGw4AbBFfa3zN0e10PVo2vhfFtkQIIXm0WPB8VunmLyJ+laQbDAAs0FWxBqXr05Lhea+EkPU5cLL9vWnL81m1WXxRrtHtbDMBgG3ja5GvSbqdrlfLwvcm36NiuyKELHu6FXu2Foelfz5r19rNq62dodvpJgIA283XJF+bdDtdt5bI7b5XxbZFCFnW6JHsLyULxFLRMbhbCyKvxQqgXo3t9rVKt9N1bFn4nhXbFyFk2aKF8LXZwrAsxvPnkL1b8o0CAOrz7li70nVtKWjvim2MELIMOXiSPalr7eJ0QVgCXWMPafyQZJsCAPTBh2ItS9e5ofM9zPey2NYIIUPNZGTfr0erd2QLwVJoZu8Xfq5kGwEA9Mm5sabl693Q+V6mPS22N0LI0DJt7Xl6hP6VdAEYusbuH7d2iW5niz8A9JavbVrb79ftfP0bMN/TfG+LbY4QMpR0rf1adtEPnX7uB6e8vBWAJeBrna95up2uh0Pme1xsd4SQvkePSF+dXehDp4VsjxbyM3U7XeQBYGh8zfO1T7fTdXHIfK+LbY8Q0tfoYj517cW9BA5qAbtCY7qwA8DQxRp4ULI1cshOje2PENKnHHqxPU4L1wXJRT1sjd26OrLTdTtdzAFgWczWQq2Jup2vl0PV2G7fA2M7JITUnnFr36aL99p1F/OAqaRPJiO7VLfTBRwAlpbWxtkamaydA3at74WxLRJCas3+Hfa9s5cIyS/kQZq29jGN+YINAJiJtTJdR4dIZf2OaWPfE9sjIaS2HGjtP+tiXZ7nNDW2r5u/kUK6SAMAHmu8ojVTa6du5+vq8BzUPvGfY5skhNSS6chemFywg6WF6MMa04UZAHBksYam6+sQTVfshbFdEkJKp2tslF2oQ6TF9j6NF0q6GAMANuzCWFPT9XZofK+MbZMQUipadN6QXaBDpEXnJo3Z4gsA2KRYW9N1d2i6FXtDbJ+EkO2OLsJleY3WA1PerhUAFibW2AOSrcGDoqL+5thGCSHblUkze63S9KIcmNv1s75FY7rYAgC2yHytvV2ytXhQVF5Pj+2UELLodK39SXYhDo1+zms05gssAGAhYu1N1+UhmbZ2VmyrhJBFZTKy87ILcFAau1/jLkkXVQDAwu2KtThfp4eisfNieyWEbHW6xnanF96A6JH+zRqzRRQAsM1iTU7X6wHZFdssIWQrcsjs66atXZRcbIOhxfGLeuR7hW6niycAoBCtzbM1Olm7h6Jr7CLfa2PbJYRsNod22uO1aLwru9AGo7G7tCierdv5ogkAKGq2Rmut1u18HR+Gy3zPje2XEHKs2bvTTtCF9N41F9bQXC/pQgkAqI6v2dlaPghdY+/d++t2QmzDhJCN5tMn2jfpAhryf9n5BT16v1RjtjACAGo1X7u/INna3nvT1q5ePdm+MbZjQsjR8vlX2D/QxTPkR7X3yrmSL4oAgNr5Gu5rebbGD8H192svjm2ZEHK4dCfZt3eNfSS5iIbizyVbBAEA/eNrerbW957vxb4nx/ZMCFmbvSv2LbpQPp5dQEMwbewDGrOFDwDQU7G2p+t+3/me7HtzbNOEkIcT/yHWdWsvmoHw50L5+2Cnix4AoPd8jR/q816v8z06tmtCiGcyfw3T7ILpu3v1aPwcjdlCBwAYiFjrh/m8V+3RsV0TQrrWLkwvlP7j+awAsHwG+bxX36tj2yZkeRMvvJ9eJL3G81kBYHkN9HmvvmfH9k3I8kUX9h9lF0afdQ3PZwUAzFwSe0K6X/SW9u7YxglZnmjyv27dxdB/+yYjO09jtoABAJbNfE/YJ9me0Wevi+2ckOFn2tirk4ug1/So+h6NZ0i+eAEAltUZsUek+0df+V4e2zohw40u3ia7APqsa22PxmyxAgBgJvaKdB/pK9/TY3snZHjRRftr2cTvM/1MH9WYLlIAADxa7BnpftJXvrfHNk/IcDJesV/MJnyfxbulpIsTAACZ2DvSfaWvfI+P7Z6Q/mfa2vOyid5z75F0UQIA4Ch8D8n2lt7yvT62fUL6m+nInptN8L7qGntQF+fFup0tRAAAbIjvJb6n6Ha63/SR7/mx/RPSv+w90Z6qi/Jz2eTuqU7eLukiBADAMfI9xfeWbM/pHd/zfe+PGkBIf3L7S+0Jk8ZuyCZ2H+mR8Wd1QZ6l29nCAwDApvje4nuMbqf7T+9o7/cOEHWAkH5Ek3fXusncU11rd2hMFxwAALZC7DXpPtRDu6IOEFJ/9GjrD5JJ3Et6FHybxnSRAQBgK8Wek+5HvaMuELWAkHrTNbYjncD99OeSLi4AACyI7z3ZntQ73gmiHhBSX7rWfjqbuD11i2QLCgAAi+Z7ULY39Y53g6gJhNSTbsWeqUdWX8kmbd/o57hZY7aQAACwLWIvSvepPvFu4B0h6gIh5TNu7ds0Of9i7WTtIz0y5C1cAQBViD0p3a965i+8K0RtIKRsdGFdnUzS/mnsJo3p4gEAQBHzvSnft3rEu0LUBkLKpWvsnGyC9tCHJF80AAAoy/eobO/qFe8MUR8I2f5oEv7+2knZR7qQrteYLRQAAFQh9qp0H+uZ348aQcj2ZTKy30gmY++MW7tOY7pIAABQk9iz0v2sV9Qhok4QsviMV+yH04nYM9PGrtGYLg4AANQo9q50X+sT7xJRKwhZXO7bYd88aeyubBL2CaUVANBXQyivXWN3e6eIekHIYqKJdlE2AXuF57QCAPpuAM959U4R9YKQrY8m2G9nE69nPiz5IgAAQL/4npbtdb3h3SJqBiFbF3/LtmzC9Yl+Bt4RCwAwKLG3pfteX3jHiLpByPFn/0n2HZpYB9dOtF4Z2Sc0phc9AAC91sz2uHz/64eD+19h3xG1g5DjiybUtWsmWK90jd2hMb/YAQAYgNjr0n2wJ66N2kHI5qML4c3J5OoN3X9/BYT0IgcAYFB6/qo/XWtvjvpByLFHpe9Xs4nVI5+djJILGwCAIfI9r9Hel++JveDdI2oIIRuPHvU8K5tQfTFuba8u3rfodn5xAwAwRNr7Zntgsjf2xQF1kKgjhBw9h3baCXrEc1s2mfpApbubNna2bucXNQAAA+Z7oO+Fup3uk7XzDuJdJGoJIUfOuLG3ZROpJw5ORnaexvRiBgBgKcz3wv6+IpC6SNQSQg4fTZZT1k2entAjtK9qvEDyixgAgOVyQeyN6b7ZA6dEPSFkfVZb+5Fk0vRHY1dozC5cAACW03xvzPfNHhirm0RNIeSRHNppj9cE6e3zWqeNfUBjftECALDEYo9M988e8Oe7Pj7qCiHz6BGNT+5swlRP9523cgUA4Ahir0z30eqN7I+irhBi1q3Yz6UTpQfGjd2pMb1IAQDAI2LPTPfT2nlXidpCljnjE+0fdo2Ns0lSvcbu16OwP9bt9AIFAACP4num753Znlo57yreWaK+kGWNJsLubIL0wOflXMkvTgAAkPG90/fQbG+tmneWqC9kGaNJ8LK1k6Ivpq29Q2N2QQIAgCOIPTTdX3vgZVFjyDJlMrLvTiZDX7xX0osRAABsiO+l2R5bP3WYqDNkWdI19v50MlRO9/sGjdkFCAAAjkHsqel+WzPvMFFnyDJk2thvZhOheo3dqjG9+AAAwCbM99Z8362Yd5moNWTIGa/YD2cToHqNfVpjftEBAIDNm++x+f5bMe80UW/IEHPTi+1xXWOfyE5+1Ub2QNfa2bqdX3AAAGDTZnus9lrdzvfhSnmn8W4TNYcMLTrJp6496b3Q2KUa04sNAABsgflem+/DdTs1ag4ZUvRo6meSk12/xq7XmF9kAABg68z33Hw/rph3nKg7ZAg5tNP+pk5s756/0jV2h8b84gIAAFsu9t50X67Yp73rRO0hfY8m4ZuSk1w1PXrq9MjvdN1OLywAALAA2ntne3CyN9ds2tobo/aQPmd/Yz+UneAeuEDyiwoAACyS78HZ3lw17zxRf0hfo0dNN2Ynt2bd/M0RsgsJAABsg9iL0326Vt55ov6QPkYn8ZS1J7UHbpH0IgIAANtnOt+Ts726ZqdEDSJ9SrfDnp6czNrdK+nFAwAAivC9Oduzq9W19q+iDpG+RI+SLs5OZq00yb40aew83c4uGgAAUIL25tkenezdtdL9vTjqEOlDusZelJ3IqjV2ucb8ogEAAMVM53t0vn9XyrtQ1CJScw6eZE/SyRpnJ7FWemT0UY3pxQIAAMqLvTrdx2vkXcg7UdQjUmvitU/Tk1ilxu7XmF4kAACgIvM9O9/PK6TyenrUI1JjNKF+LDtxNdOk2q0xv0AAAEA9RrM9O93Pq6VuFDWJ1BadnFvTk1YpldYPaswvDgAAUJ3Yu9N9vUrqRlGTSE3pVux30hNWqa61uzWmFwUAAKhX7OHp/l6jaWO/HXWJ1JD9J9v3ZSeqVnq09mVN+nN0O70gAABAvVQEz/G9XLfTfb5G3pWiNpHSGTd2aXaSKnalpBcDAADoBd/Lsz2+St6VojaRkllt7PnZCarVtLXbNGYXAAAA6JHY09P9vkbemaI+kVKZNP15H+GusQPdip2h2+kFAAAA+qNr7Qzf23U73fero84U9YmUiB7pnJSemFqNZk9pSCc/AADoofnenu/7FfLuFDWKbGdWT7Rv0iOH1eykVIp3xwIAYJj6865a6k7eoaJOke2KDvwfpCekQuPW9mrMJjoAABiA2OvTHlAddaioU2Q7MhnZd6cnolJdaxdqTCc6AADov9jr0x5QJXWpqFVk0dEB37XuBFRKE5mnCAAAsARiz0/7QIV2Ra0ii8yksR9LDn6Vxo1NNaaTGwAADE/s/WkvqI46VdQrsqjoIN+QHvwajexdGtOJDQAAhkfF1ff+vBfURp0q6hVZRLoV+7X0wNdpj6STGgAADJp3gKwbVMe7VdQsspU5tNP+hg7w59Ye8Bp1rX1p2tpZup1NZgAAMGDeAbwL6HbaEyrzOe9YUbfIVqVr7HeTg10lTdb3a0wnMwAAGL7oAmlPqI13rKhbZCtyoLGnZQe6Rpqo92hMJzEAAFge0QnSvlAb71pRu8jxRo8Ezs4OcpUaO19jOoEBAMASmXeCvC9UxrtW1C5yPNm/w743O8A10iOrGzXmkxcAACyd6AZpb6iNd66oX2Sz0Qk/Jzu41Wlsv8Z00gIAgCU27wh5f6iId66oX2QzWW3s32YHtkbT1t6pMZ+wAABgaUVHSPtDbbx7RQ0jxxo9QjkvO6jVaexWjelkBQAAiK6Q94iaqHtFDSPHknFrz0gPaGW6xr4sZ+p2PlEBAMDS867gnUG30z5RE+9gUcfIRjNu7G3ZwaxOYx/UmE5SAACAvzLvDHmfqIh3sKhjZCNR0//32YGsTmOdxnxyAgAArDXvDnmvqIh3sahl5GjRAXv72gNYpcberTGfmAAAAGvNu0PeK+ry9qhl5Eg5cLI9Mzl49Wns0xrzSQkAAHA48w6R94uKeCeLekYOl661XdnBq9CFkk9IAACAw/MOkXWLqngni3pGsnQr9uzswNWma+wTGrOJCAAAcFTRJdKeURPvZlHTyNroJF6QHbSajBv7mh6B/D/dTiciAADA0XiX8E6h22nfqIV3s6hp5NGZNPac7IDVZrwye8/hdBICAABsVHSKtG9URR0t6hp5ODowfXi+xwFJJx8AAMAmeLfIOkdNLoy6Rjx9+W1r19pVGrNJBwAAcMyiW6S9oyr81vWRxHNG8wNVj3slnXQAAADHwTtG1j2q4V0tattyZ3XFnpIdoNrohF2sMZtsAAAAmxYdI+0fNfHOFvVteTNu7LXZwalJ19idGtPJBgAAcNzmXSPtIbXwzhb1bTnz0In2DToQB9cemArxZgMAAGCR+vAfqR/07hY1bvmi5n5iclCqwm9bAQDAdojOkfaRWnh3ixq3fNEB2LP2gFSI37YCAIDt0Iffuu6JGrdc0aOKFyQHoypda5/SmE0sAACARfDukfaSWniHizq3PNEPfuXaA1EbnRh/C9psUgEAAGy56B5pL6nIlVHnliM9ecOBOySdVAAAAAvkHSTrJvVYpjckmPbhDQdGtltjNpkAAAAWZ95B8n5SCe9yUeuGnT684UDX8NtWAABQ0LyLpD2lFkvxhgQ9ecMBftsKAADKmXeRtKfUYvBvSNCTNxy4XfJJBAAAsH28k2RdpRbDfkOCPrzhgOySbPIAAABsJ+8kWVepxqDfkEA/YN1vONDYJzVmEwcAAKAE7yZ5b6nDMN+QYLJiP5n8sFWZNnaFxmzSAAAAlPBuSXtLNdTxou4NJ11j56c/bCV0/+7SmE0YAACAYqKjpP2lCup4UfeGkf2NPTn9QWvS2KUa0wkDAABQzLyj5P2lEt71ovb1P92KtdkPWQs9ktmnMZ8sAAAAhUVXSXtMDbzrRe3rf3SwP579kLXoWnufxnSiAAAAlBZdJe0xNfCuF7Wv35mO7LnZD1iRBySdJAAAABXxzpJ1mSp454v6199MGjs9++Fq0a3YjRqzyQEAAFCN6Cxpn6mB7t8ZUf/6mft22N/qGvty9sPVoGvtoWljZ+l2OkEAAABq4Z3Fu4tup72mNO983v2iBvYvOri/kv1g1WjszzWmkwMAAKA68+6S95oKePeLGti/qHlfk/1Q1Zi/tmw+MQAAAGpT/+viXxM1sF/Z19j3ZD9QLXRgecMBAADQO9Fh0n5TA++AUQf7k661N2Q/TDV4wwEAANBH9b8hwRuiDvYnOqjVvlCuHqnwhgMAAKC3osukPac43beog/1I19rPpD9IJXT/eMMBAADQW9Fl0p5TAxXrn41aWH90hy9Z+wPUQgfyQY3pJAAAAOiL6DRp36nAJVEL687qij0lufPV0En2t59NJwAAAEBfRKdJ+04NvBNGPaw3XWttduer0dhujekEAAAA6I15p8n7TgW8E0Y9rDe6o9etveMVuU/ykw8AANA/3m2yzlOD66Ie1pkDjT0tudPVUPO/WmN20gEAAHonuk3ae2rg3TBqYn2ZNtZkd7oG48a+pvEMSU88AABAD50RHSftP6V1KxU/XUB3sNqnCejA7dGYnXAAAIDemrZ2m8a0/1SgzqcL7Kv/aQIXa0xPOAAAQF9Fx0n7Tw28I0ZdrCddxU8T0AntNKYnGwAAoO+i66Q9qDTviFEX68mksQ9kd7YKjV2vMT3RAAAAvTfvOnkPKmzcVPZ0gdWT7anZHa3FtLWzNeYnGgAAoOei66Q9qAbeFaM2lk/VTxNo7E6N6UkGAAAYiug8aR8qraqnC9T8NAEdqMs1picYAABgKKLzpH2oOHXFqI1ls/fEep8m0LX2eY3pyQUAABia6D5pLyrNO2PUx3LRAVrJ7lwN9MjjoxrTEwsAADA00X3SXlSad8aoj+VS9asJtHahpCcWAABggLz7ZJ2ovNJPF1hdsaekd6wCavVTjdkJBQAAGKzoQGk/Ks27Y9TI7U/VTxNoeZoAAABYPtGB0n5UmnfHqJHbH33zK7M7VQPdN54mAAAAlk50oLQflebdMWrk9mZ/Y387u0OV4GkCAABgmVX7dIFDO+2EqJPbl+nI/mt2ZyrB0wQAAMAyq/bpAt4ho05uX7rG3pzdmSqMeJoAAABYYvMulPekwrxDRp3cvuib3pHdmdLGja1qzE8iAADAkohOlPalkrxDRp3cnox32P+X3ZFK8DQBAACAip8uMG7tX0atXHz0DV+29g5UhKcJAAAA1PxmBOqSUSsXn661i5M7UB5PEwAAAHhErU8XUJeMWrnYHNppf00H4cHsTpQ2buxjGvMTBwAAsGSiG6W9qSh1yUOH7OuiXi4uasj/Kb0DdeBpAgAAAI+o9ukC4xX7j1EvFxc15Ndm37y4EU8TAAAAWGfekfL+VNBYnTLq5eLS1fsr51s15icMAABgWc07Ut6fyvpo1MvFZLLD/nHyTevQ2Ls05icMAABgWc07Ut6fShvZP4qaufWZtvZL6TetQNfaGRrzEwYAALCkupVZR0r7U2ljdcuomVsffYM/XfsNa9A19lmN6ckCAABYdtPGPqMx7VFFNXZe1Mytj774OP2m5V0v6YkCAADArCtlHaqoTt0yaubWpluxZ2ffsAb6oXdrzE4SAAAA5l0p7VGleceMurl1UTnckX2z0rrWHtCYnyQAAAA87POS9qmSvGNG3dy6qKmfn32zCuyR7OQAAAAgdPPOlHWpstQxo25uXfRFa31S73s1picIAAAAc928M+V9qiDdr89G3dyarK7YU7JvVAM9ejhLY3qCAAAAMBedKe1Tpe090Z4atfP4M1mxX8i+SQXul/TkAAAAYB3vTlmnKmtkvxC18/jTNfaH6Tcp78OSnRQAAACs590p61RFTVv7w6idx5+u3h/yHRqzkwIAAIA11Om8O6W9qiTvmlE7jy97d9oJ2TeowJckPSkAAAA4LO9QWbcq6pA6Z9TPzWfc2o9kX7y0rrE7NWYnAwAAAIcRHSrtVyV554z6ufnoC71q7ReuxHWSnhAAAAAclneorFuV9qqon5vPpLFLky9cgwslOxkAAAA4PO9QWbcqS50z6ufm0zU2Sb94WV+V7EQAAADg6LxLZR2rGO+cUT83l66178y+cGm6X5/TmJ0EAAAAHEV0qbRnFbVi3xU19Nij5vvi9IsWpoP9UY3piQAAAMCRRZdKe1ZJ3j2jhh579I/fmn3R0nS/LteYnggAAAAcxbxLpT2rJO+eUUOPPfoCt639gjWYtvYnGvMTAQAAgCOKLpX2rMJuixp6bDl4kj0p+WLFjRubakxPAgAAADYmOlXat0ryDhp1dOOZjuy52RcrrWttj8b0BAAAAGDDvFOlfask76BRRzce/cOXrP1CNVBxvVpjdvABAACwQdGp0r5V2Euijm48k8b+KPlC5TV2vsb0BAAAAGCD5p0q71slqYNGHd149A+vXfeFyvuS5AcfAAAAx8q7Vda5Sro26ujGo7Z7IPlCRXWt3aMxO+gAAAA4RtGt0t5VjDpo1NGNZbrD/mn6hQrTwb1RY3rgAQAAcGyiW6W9qyTvolFLj579jf1E9kVKm7b2To3pgQcAAMCxiW6V9q6SvItGLT16Jo29MvsipengnqUxPfAAAAA4NtGt0t5VlLpo1NKjR//g3HVfoLCusS9oTA86AAAANmlkD2hM+1dB50YtPXpUEj+efIGyGvuMxvyAAwAAYHPmHSvvX4V4F41aeuQcer59fdfaQ9kXKUn36WaN+QEHAADApkTHSvtXKd5FvZNGPT18JiP77uwLVOAqSQ84AAAANs07Vta9ylInjXp6+Ewa+/n0H5d3gWQHGwAAAJvnHSvrXmWpk0Y9PXy61n4v/celjex0jdnBBgAAwGbNO1bevwryThr19PDRJ12c/eOSdJ+mGvODDQAAgOMSXSvtYaV4J416evhMGrsr+8dFNXanxvRAAwAA4DjNu1bew0pRJ416mmf6cnti+g8LU+O+SWN+oAEAAHBcomulPawk76ZRU9en1lcU6Bq7QmN6oAEAAHB8omulPayoI72ywP4V+8n0HxU2buxtGtMDDQAAgOMTXSvtYSV5N42auj76hJet/Qelda19RWN6kAEAALA1onOlfaygl0VNXR/d4Tck/6CorrF9GtMDDAAAgK0RnSvtY6V4N42auj6TxnZn/6gk3eE9GtMDDAAAgK0RnSvtY8Wom0ZNXR/d4Q+n/6ikxm7QmB5gAAAAbJF558r7WCHeTaOmro8+2GX/qLD3SH6AAQAAsFW8c2VdrJiusS5q6mMzGdnfzf5BabrDf6YxO7gAAADYItG50j5WlDpq1NVHUu1ruLZ2tsb0AAMAAGBrROdK+1hR2Wu5Thr7ifSTy+KlsAAAALZPfS+JpY4adfWR6AP1vYZrY1ON2UEFAADAFovulfaygta/lmu3Ut9ruMqnJT2wAAAA2HLevbJOVk5jr4+6+kj0l9W9hqvu0yc0ZgcVAAAAW23evfJeVkiXvZZrla/hOuI1XAEAALbNvHvlvayQ9LVc1bDH2ScXxmu4AgAAbJ8aX8t1HHV1Hn99rOwTS4vXE8sOKgAAALZYdK+0lxX16NdynazYd6WfVBiv4QoAALB9qn0tV3XVqK2z57f+p/STCho39lWN6UEFAADAYkQHS/tZKd5Vo7bOiuvPZZ9UUryOWHpAAQAAsBjRwdJ+Vop31aits6cKvDT7pMJ4DVcAAIDtV99ruaqrRm01U7N+dfpJJfEargAAANuvztdyfXXU1llxfVP2SSWtjmavK5sfUAAAACxEdLC0n5XiXTVqq5n+4ty1n1CB6yQ9oAAAAFgY72BZNyvp3Kits9+4Xp58QmlXSnYwAQAAsDjewbJuVox31aits+J6U/ZJRTV2mcbsYAIAAGBBpvMOlvezQryrRm2dFde7sk8qamQXakwPKAAAABZk3sHyflaId9WorSqurR3MPqmk6cjO05gfUAAAACxEdLC0n5XiXXVWWm9/qT0h+4TS1KzP1JgeUAAAACxGdLC0n5V0aKc93vY39uTsgyWpVT+kMT2YAAAAWKzoYmlPK+WBV9q3+tMEvjP7YElq+g9qTA8kAAAAFiu6WNrTSuleYU+36ciem32wJB0sf4/c9EACAABgscbzLpb2tGIa+0Ebr9hPpR8s6z5JDyQAAAAWzrtY1tGKmbb2PH8prBdnHyzMX54rO4gAAABYsK61uzVmHa0YFddf9rd7fcXaD5Smg7VHY3ogAQAAsFjRxdKeVszITrZxa69LP1jQuLGbNaYHEgAAAIsVXSztacU09lp/qsCb0g+W1NgNGtMDCQAAgAWbd7G8pxXindWfKuB3MP2EUrrW3q9x/UEEAADAwkUXS3taQaf5b1yre3cEHayrNKYHEgAAAIsVXSztaaV4Z/XfuJ679gOlrbb2Ho3pgQQAAMBiRRdLe1pB53px3bXmL8tr7AqN6YEEAADAgs27WN7Tytnlb/l6cfKB0i6T/EACAABg0byLZR2tGO+s/hvXy9d+oAKXSHYQAQAAsHjexbKOVtLlXlyre/LttLGLNGYHEQAAAAsWXSztaQVd5cX1ujV/WVzX2J9pTA8kAAAAFiu6WNrTCrrOJo3dlHygKB2s3RrTAwkAAIDFii6W9rRi1Flt3Ngt6QcL0sE6X2N6IAEAALBY0cXSnlaKd1Z/A4JPZh8s7E8lPZAAAABYOO9iWUcrxjurF9e7sg8W5m+KkB1EAAAALF51b1DlndWL6+eyD5Y0be1sjdlBBAAAwIJFF0t7WineWb24jrMPltS1dpbG9EACAABgsaKLpT2tFO+s/nJYB9d+oLjG3qIxPZAAAABYsHkXy3taOQf9N65fTj5Q1Gpr/1djfiABAACwUNHF0p5WindW/41r+sHC0oMIAACAbZN1tKL4jSsAAAAeo+bfuPIcVwAAADyi4ue48qoCAAAA+CvVvqqA/qe613HVweJ1XAEAAAqp+XVcq3vnrDHvnAUAAFBSte+c9cnsg0WtzN4fNzuIAAAAWDzvYnlPK8Q7q40buyX7YEm6Y+drzA4iAAAAFiy6WNrTSvHOapPGbso+WFRjuzWmBxIAAACLpeLqXSzvaaWos/rLYV237gOF6WD9mcb0QAIAAGCxooulPa2g67y4XrXmL4ubNnaRxvRAAgAAYLGii6U9raCrvLhevuYva3CJpAcSAAAAC+ddLOtoJV1uXWsXJx8o7TLJDiIAAAAWz7tY1tGK8c7qv3HdtfYDxTV2hcbsIAIAAGDR5l0s72nl7PLiWt0LzK629h6N+YEEAADAQkUXS3taQef6GxCcmXygqG7+H4ylBxIAAACLFV0s7WmleGf137j6HUw/oRQdrPdrXHcQAQAAsHjRxdKeVtBp/hvXNyUfKKuxGzSmBxIAAAALNu9ieU8rxDurjVt7XfbBksaN3awxP5AAAABYqOhiaU8rprHX+lMFXrHuA4V1re3RmB5IAAAALFZ0sbSnFTOyk/2pAi9OP1iQDtbdGtMDCQAAgIW7S9KeVor64S/beMV+KvtgYfdJdhABAACweN7Fso5WzLS159l0ZM/NPljSuLGpxuwgAgAAYMG6eRdLe1oxjf2gv+Xrd6YfLEgH60GN6YEEAADAYkUXS3taKd0Oe7rtb+zJ2QdLUpl+SGN6IAEAALBY0cXSnlbKA6+0b7XbX2pPyD5Ympq+v6NXejABAACwGNHB0n5W0qGd9njzqFUfzD6hpOnIztOYHlAAAAAsRnSwtJ8VdGBWWj1q1tW95MFkZBdqTA8oAAAAFmTewfJ+Vs5fRG2dFdebkk8oatrYZRrzAwoAAIDFmHewtJ8VdGPU1llxvTz5hNKulPyAAgAAYFG8g2XdrJzG3hW11fxtX89d9wnlXSfZwQQAAMDieAfLulkxXWvnRG2d/cb1TdknlbQ6sg9rzA4mAAAAFiQ6WNrPSpm29saorbPi+ursk4pq7BMa0wMKAACABZl3sLyfFeJdNWqr2WTFXpp9UmGflvyAAgAAYFG8g2XdrJixumrUVvPXcf257JNKUrP298jNDiYAAAAWJDpY2s9K8a4atXVWXP9T9kkljRv7qsb0gAIAAGAxooOl/awU76pRW2dPFfiu7JNK0508W2N6UAEAALC1onulvawoddWorSquI/u76ScV1jX2ZxrTAwsAAICtFd0r7WVFqatGbZ1Hd3ScfmJZ75H0wAIAAGDLeffKOlkx3lGjrj6Srq3vNbvUrm/QmB1UAAAAbLV598p7WSHeUaOuPhK12d3ZJxfFa7kCAABsnzpfw3V31NVHojv6+uyTC+O1XAEAALZPda/h6h016uoj0Qdetu4TC1PD5rVcAQAAtkl0r7SXFfSyqKuPRG32J5JPLO0rkh5YAAAAbDnvXlknK0cdNerqI5mM7LvTTy6M13IFAABYvGpfw1UdNerqI/HXx0o/ubCO13IFAABYuOhcaR8rau1ruD4c3eEu/Qdl8VquAAAAi1fja7h2UVPXp8rXcm14LVcAAICFm3euvI8Vkr6G68PRHa7utVx1h/dozA8wAAAAtkR0rrSPFZO9huvD0R1+Q/qPCuoa26cxPcAAAADYGtG50j5WinfTqKnro0+o77VceUksAACAhYvOlfaxgta/huvD2b9iP5n8g+LGjb1NY3qQAQAAcHyia6U9rCTvplFT16fa13Jt7AqN6YEGAADA8YmulfaworLXcH0405fbE9N/VFjX2k0a0wMNAACA4xNdK+1hJXk3jZqaZ9LYXdk/LKqxOzWmBxoAAADHad618h5Wijpp1NPDR4374vQfF6T7NNWYH2gAAAAcl+haaQ8rxTtp1NPDR5/0e9k/Lm5kp2tMDzYAAAA2ad6x8v5VkHfSqKeHz6Sxn8/+cQUukPyAAwAAYLO8Y2Xdqyx10qinh0+trywgV0l2sAEAALB53rGy7lXWkV5R4OEcer59fdfaQ+kXKEj36WaN2cEGAADAJkXHSvtXKd5FvZNGPT1yusY+nn2Rohr7jMb0gAMAAGCT5h0r71+FeBeNWnr06B+cu/YLFDeyBzTmBxwAAACbopL4BY15/yrn3KilR4+a9yuTL1DctLWzNKYHHQAAAMcmulXau4pSF41aevTsb+wn0i9SmA7uOzWmBx4AAADHJrpV2rtK8i4atfTome6wf5p9kdK61m7UmB54AAAAHJvoVmnvKsm7aNTSjWXS2IHsC5Wkg3uPxvTAAwAA4NhEt0p7VzHqoFFHNx79w2vXfaHyviTpgQcAAMAx826Vda6Sro06uvGo7f5R8oXKa+x8jdmBBwAAwEbNO1Xet0pSB406uvHoH75k3ReqQNfa1RrzEwAAAIANiU6V9q3CXhJ1dOOZjuy5yReqwR5JTwAAAAA2RsXVO1XWtYryDhp1dOM5eJI9KftipY0bm2pMTwAAAAA2JjpV2rdK8g4adfTYon9829ovVoNpa3+iMT0JAAAAOLLoUmnPKuy2qKHHnq6xtyZfsLzGLteYnggAAAAcmTqed6m8ZxXk3TNq6LFH//jF2RctrWvtoxrTEwEAAIAjiy6V9qySvHtGDT32TFbsu7IvWpoO9uc0picCAAAARxZdKu1ZJel+fWfU0M1FzXeSfeHCvirpiQAAAMBReZfKOlYx3jmjfm4+k8Yuzb54BS6U7EQAAADg8LxDZd2qLHXOqJ+bj77Qq9Z94TpcJ9nJAAAAwOF5h8q6VWmvivq5+Yxb+5HkCxfXNXanxuxkAAAA4DCiQ6X9qiTvnFE/N59DO+2E7ItX4EuSnhAAAAAclneorFsVtVedM+rn8aVr7cPZNyhN9+sdGrMTAgAAgDWm8+6U9qqSvGtG7Tz+6If8w+ybVMALdXpiAAAAsE6dv4xs7A+jdh5/JiP7heybVOB+yU4KAAAA1vPulHWqslbsF6J2Hn/2nmhPTb9JBbrWztKYnRgAAACE6ExpnyptdcWeErVza9I19tnsG5Wm+/VejekJAgAAQJh3prRPFdXYZ6Jubl30Rc9Pv1lhevSwR2N+ggAAAPAw70xpnypKHTPq5tala2xH+s3K+7xkJwcAAACha+0BjVmXKso7ZtTNrUu3Ys/OvlkVGtutMT1JAAAAy07l0LtS3qMK844ZdXNrox96nH3DClwv6YkCAADArCtlHaoo75ZRM7c+49b+NPumpU0b+4zG7CQBAAAsPRXEKv8j+0lj50XN3PpMW/ul9JtWoFuxMzSmJwsAAGBZde2sI6X9qbSxumXUzK3PZIf94+ybVqGxd2lMTxgAAMDSmnekvD+VNrJ/FDVzMdE3+ei6b1qDxm7VmJ8wAACAZTXvSHl/KuujUS8Xl3Fjr02+cXkjW9WYnzAAAIBlNe9IeX8qyDtl1MvFZXXF/mP2zStxoeQnDQAAYPl4N8o6U3Fjdcqol4vLoZ321yaNPZjdgdLU3D+mMTtpAAAASye6UdqbilKXPHTIvi7q5WLTtXZxeidKa3i6AAAAwF+Zd6O8NxXkXTJq5eKjb/iytXegIjxdAAAAoOKnCcjLolYuPgdb+5fJHaiFv+pBdvIAAACWSZ2vBCVjdcmolduTrrE7sjtS2pinCwAAAPjzW+t8moA6ZNTJ7Yu+6ZuzO1OFEU8XAAAAS2zehfKeVJh3yKiT25fpyP5rdmcqwdMFAADAMqv2aQLeIaNObl8O7bQTsjtTialkJxEAAGAZeBfKOlJx3iGjTm5vutauzO5QDXTfeLoAAABYOtGB0n5UmnfHqJHbn27FVrI7VQMdGJ4uAAAAlk50oLQflebdMWrk9md1xZ6S3aka6KTxdAEAALB0ogOl/ag0745RI8tEd+LatXeqIjxdAAAALJNqnyYg10Z9LBe1+nqfLtDwdAEAALA8ovukvag074xRH8tl74n21OzO1UAH6PMa0xMLAAAwNNF90l5UmnfGqI9lM2nsA9kdrIEeeVyuMT25AAAAQxGdJ+1DxakrRm0sn2ndTxe4U2N6ggEAAIYiOk/ah0rzrhi1sXxWT6736QJOB+tsjelJBgAA6LvoOmkPqoF3xaiNdaTmpwvovl2vMT3RAAAAvTfvOnkPKq2mpwk8nK6xJr2zFeha6zTmJxoAAKDnouukPag074hRF+vJvsaelt3ZWuiEXqwxPdkAAAB9FR0n7T818I4YdbGu6M5dt/bO1mLa2m0a0xMOAADQV92K7dGY9p8KXBc1sb5MK366wLixr2k8Q9KTDgAA0ENnRMdJ+09p3g2jJtaXA/U/XeBqjdlJBwAA6J3oNmnvqYF3w6iJdUZ3stqnC8h9kp54AACAHvJuk3WeGtT7NIGHo+bfJne8Ho3t1pideAAAgP6Yd5q871TAO2HUw3qzumJPye58LbrGPq4xnwAAAAA9EZ0m7Ts18E4Y9bDu6M5esvbO10In+UGN6QQAAADoi+g0ad+pwCVRC+uPDuTPJj9ANbrW3qcxnQQAAAC1iy6T9pwa6P79TNTCfmTS2L7sB6mBirXft3QiAAAA1C66TNpzitN9izrYn+iOv2HdD1KTxi7VmE4GAACAas07TN5vKtCpA0Yd7E/2NfY92Q9TCz1SuUtjPiEAAAAqFR0m7Tc18A4YdbBf0YG9JvuBqtHY+RrTSQEAAFCdeXfJe00FvPtFDexfutZ+JfuhqtHYn2vMJwYAAEBt5t0l7zUV8O4XNbB/uW+H/S017y9nP1gVmtkjg7N0O58cAAAAlZh1FnUX3a6Sdz7vflED+5luxc7Ifrha6P7dqDGdIAAAALWIzpL2mSo0dnrUv/5mOrLnpj9cJbrWHtCYThAAAIBaRGdJ+0wNvPNF/et3usrfkmzKGxIAAICKRVdJe0wNvOtF7et/uhVrsx+yFjrYvCEBAACoVnSVtMfUwLte1L7+Z39jT85+yJpMR7whAQAAqE90lLS/1MK7XtS+YWRS/+uO8YYEAACgOtFR0v5SA92/86PuDSeTFfvJ7IetzLslnTQAAAAFeDfJOks91PGi7g0r+uH2rPthKzJt7ZMas0kDAABQgneTtLdUYk/UvOFl3NiJyQ9cm12STRwAAIDt5J0k6yrV8G4XNW94eehE+wb9kAfX/tCVuV2yyQMAALCdvJNkXaUWB73bRc0bZtTMX5v84HVpbLfGbAIBAAAsXDfvInlPqYR3uqh3w83qij0l++Froslyh8Z0IgEAACxadJG0p9TCO13Uu2Fn2tr/yw5AVUb81hUAABQw7yB5P6mEd7modcPPpLHnZAehMvzWFQAAlFD9b1u9y0WtW47oh75y3UGoTNfYBRqzCQUAALDlonukvaQiV0adW57oxLwgORC1+ZSkEwsAAGCrdfPukXWSaniHizq3XNEPX/UbEoQLJZ1cAAAAW8g7R9ZFajLcNxw4WvrwhgR6VHGnxmxyAQAAbJnoHGkfqcWg33DgaOnJGxI4fusKAAAWqQ+/bR3+Gw4cLT15QwJ+6woAABamJ79tHf4bDhwtfXhDAte1drHGdLIBAABsVnSMtH/UZGnecOBo0Qmr/w0JWrtX0gkHAABwHLxjZN2jGt7VoraRnrwhgZ+0qzRmEw4AAOCYRbdIe0dVlu0NB44WHZQ+PCn5gKQTDwAAYBO8W2SdoyYXRl0jD6cvv3Udr9iNGrOJBwAAsGHRKdK+URV+25qn68HbnI0b+1o8JzedhAAAAEfjXcI7hW6nfaMW3s2ippG16Vbs2dlBq41O4ic0phMRAADgaKJLpD2jJt7NoqaRLHoEsis7cBXiTQkAAMBm9OG/6/H/KH1X1DNyuBw42Z6ZHbzqNPZpjdlkBAAAOLx5h8j7RUW8k0U9I0eKDtbb1x68KjX2bo35pAQAAFhr3h3yXlGXt0ctI0fLuLV/nxzA+jTWacwnJgAAwFrz7pD3iop4F4taRjaScWNvyw5kdRr7oMZ8cgIAADxs3hnyPlER72BRx8hGo6b/jOxg1qZr7Mtypm7nkxQAACw97wreGXQ77RM18Q4WdYwcS/TI5LzsgFansVs1phMVAAAgukLeI2qi7hU1jBxrVhv7t+lBrdC0tXdqzCcrAABYWtER0v5QG+9eUcPIZtK1dk52YKvT2H6N6YQFAABLbN4R8v5QEe9cUb/IZrN/h31vdnBrpBPu7zmcT1oAALB0ohukvaE23rmifpHjSdfY2dkBrlJj52tMJy8AAFgi806Q94XKeNeK2kWONwcae1p2kGukR1b3aMwnMAAAWBrRCdK+UBvvWlG7yFZEjwR+NzvQNdJEfb/GdBIDAIDhiy6Q9oTaeMeKukW2Kod22t/Qwf3c2oNdI03WL01bO0u308kMAACGyzuAdwHdTntCZT7nHSvqFtnKdCv2a8kBr9UeSSc0AAAYNO8AWTeojnerqFlkEZk0dkN24Gs0buxdGrMJDQAAhmg02/vTXlAddaqoV2RR0UH+sfTgV0jFdaoxn9gAAGBwYu9Pe0F11KmiXpFFRgd717qDX6mutY9qTCc3AAAYjtjz0z5QoV1Rq8iiMxnZdycnoFqayBdqTCc5AADov9jr0x5QJXWpqFVkOzJp7A/SE1GhcWt7NaYTHQAA9F/s9WkPqI46VNQpsl1ZPdG+SQd+NT0hdeIpAwAADFN/niKg7uQdKuoU2c5MWzspPSm1GtmlGrMJDwAA+mi+t+f7foW8O0WNIiWiRw63ZCemRl1jB7oVO0O388kPAAB6o2u1p2tv1+1036+OOlPUJ1Iqq409Pz05ldIjnds0phcAAADoj9jT0/2+Rt6Zoj6Rkhk3/fo1vVwp6UUAAADqp+5xlcZsj6+Sd6WoTaR09p9s35edpFp1jX25a+0c3U4vBgAAUK9pY+f4Xq7b6T5fI+9KUZtIDdEk+u3sRNVKxfVujekFAQAA6hV7eLq/16hbsd+JukRqyqSxW7MTVis9WvugxvSiAAAA9Ym9O93Xq6RuFDWJ1BadnB9LT1rFdAHs1pheHAAAoCKj2Z6d7ufVUjeKmkRqjIrg6emJq1Vj92vMLxAAAFCP+Z6d7+c1UieKekRqzcGT7Ekqr+P0BFaq4121AACoWuzV6T5eI+9C3omiHpGao5P1ouwk1mza2OUa04sFAAAUNN+j0/27Vt6FohaRPkSPjC7OTmStdH+/pAvjPN3OLxoAALD9tDfP9uhk767VVB0o6hDpSzTJ/lV2Mit3r+QXDgAAKMH35mzPrla3w54edYj0KTp5p6w9mbXTo6RbNGYXDgAA2F6+J6f7dcVOiRpE+piutRuTk1q1rrH3a8wuIAAAsA1iL0736Vp554n6Q/qa/Y39UHZye+ACSS8mAACwUL4HZ3tz1bzzRP0hfc60tTdmJ7hmetTU+euv6XZ2QQEAgEXQ3jvbg5O9uWZdY2+K2kP6nkM77W/qpH567UmunSbhHRrzCwsAAGy52HvTfblin/auE7WHDCF69PQzyYmuX2PXa0wvLgAAsIXme26+H1fMO07UHTKk6OSeuvZk90Jjl2rMLzIAAHD85nttvg/X7dSoOWRouenF9riusU8kJ71uI3tAj6bO1u38YgMAAJs222O11+p2vg9XyjuNd5uoOWSIGa/YD2cnv3rN7Dm66QUHAACOw3yPzfffinmniXpDhpxpY7+ZTYDqNXarxvyiAwAAx26+t+b7bsW8y0StIcuQrocvLOx0v2/QmF98AABgw2JPTffbmnmHiTpDliWTkX13Nhl64r2SXoQAAGBDfC/N9tj6qcNEnSHLFJ38l62bDD0xbe0dGrMLEQAAHEHsoen+2gMvixpDljFdY7uTSdEHn5dzJb0oAQBAyvdO30OzvbVq3lmivpBlzfhE+4eaCONsglSvsfsnI/tj3c4uTAAA8Gi+Z/reme2plfOu4p0l6gtZ5nQr9nPZJOmDcWN3aswvUAAA8Fdiz0z309p5V4naQsjsP9b6o2yi9MG4tZs1phcpAABQaZ3vlek+Wjvd99OirhAyz6Gd9nhNjtvWTpa+mDb2AY3pxQoAwDKLPTLdP3vgNu8oUVcIeSR6RPMjyYTpj8au0JhetAAALKX53pjvmz2wqm4SNYWQ9dEkOWXtpOmLrrGvarxA8osXAIDlckHsjem+2QOnRD0h5PDRo7O3JZOnLw5ORnaexuwCBgBgOcz3woOS7ZXVG6uLRC0h5Mg5tNNO0CO03j7ftWutmzZ2tm7nFzMAAAPme6Dvhbqd7pO18w7iXSRqCSFHz4HWnpVNpr4Yt7Z30thbdDu9qAEAGCTtfbM9MNkb+0Kl+1lRRwjZePSI51ezCdUbjX12MkouagAAhmi+531W8n2xB7x7RA0h5NijRz1vziZWbzR2l8b1FzcAAAOj0ud7Xr4f9oDu/5ujfhCy+WgyXbt2cvWJLoQ7NKYXOQAAQxB7XboP9sS1UTsIOb7sf4V9hyZUb//LxJnGPqExvdgBAOi10WyPy/e/fji4/yT7jqgdhBx/utZ+OplovaKfgbeGBQAMSuxt6b7XF94xom4QsnXpGvvtbML1zIclvfgBAOgZ39Oyva43vFtEzSBk66MJdlE28Xqlses1ZgsAAAD9MN/L8n2uJ7xTRL0gZDG5b4d9syba3dkE7JNpY9dozBcDAAAqFntYur/1RmN3eaeIekHI4jJesR9OJ2HPUF4BAH0ziNIq3iWiVhCy+ExG9hvZROybcWvXaUwXBwAAahJ7Vrqf9Yo6RNQJQrYvmny/v24y9lDHc14BAJWLvSrdx3rm96NGELL90YV0TjIp++hDki4WAAAU5ntUtnf1ineGqA+ElEvX2tXZBO2dxm7SmC0YAACUMd+b8n2rR7wrRG0gpGzGrX2bJuVfrJ2kfaQL66Ma88UDAIBtFHtSul/1zF94V4jaQEj5dCv2zK6xrySTtXf0c/AOWwCAomIvSvepPvFu4B0h6gIh9cTfsi2btD11i6SLCQAAC+Z7ULY39Y53g6gJhNQXPbLakU3cnvpzyRYUAAAWxfeebE/qHe8EUQ8IqTeTxv4gm8B9NG3tNo3ZwgIAwJaKPSfdj3pHXSBqASH1R5N217pJ3FNda3doTBcZAAC2Quw16T7UQ7uiDhDSj9z+UnuCHm3dkEzmXtKj4M92jZ2l2+mCAwDAZvje4nuMbqf7T+9o7/cOEHWAkP5k74n2VF2Qn0sndj918nZJFx8AAI6R7ym+t2R7Tu/4nu97f9QAQvqX6ciem03uvtJF+aAeGV+s29kCBADAhvhe4nuKbqf7TR/5nh/bPyH9jS7O52UTvOfeI+liBADAUfgeku0tveV7fWz7hPQ/4xX7xWyi99m0sQ9ozBYkAABSsXek+0pf+R4f2z0hw0nX2q9lE77P9DPxFrEAgA2JPSPdT/rK9/bY5gkZXrrGmmzi95ku2j0a00UKAAAXe0W6j/SV7+mxvRMy3Ewbe3V2AfSZLt57NJ4h6YIFAFhaZ8Qeke4ffeV7eWzrhAw/mvSvW3sRDMC+ycjO05gtXACAZTPfE/ZJtmf02etiOydkeTJp7I+Si6HX9Kj6CxovkXwRAwAsi0tiT0j3i97S3h3bOCHLl661s9MLo+94xQEAWF4DfOUA53t2bN+ELG90IVyYXSAD8OeSL2oAgKHytT/bE3rN9+rYtgkhenR6RXahDMC908bO0ZgtbgCAgYi1/l7J9oJ+0x4d2zUhxLN3p52gi+O6dRfLMPC8VwAYNl/jh/d81rnrfI+O7ZoQ8nD2rti3dI19PLloBiHeLSVb8AAAPRVre7ru953vyb43xzZNCFmb7iT7dl0oH8kuoIHgea8AMByDfD6r873Y9+TYngkhh8v9r7B/oIvm+rUX0YD4c6DOlWwRBADUz9fwYT6fde76z2svjm2ZEHK0rJ5s3zht7erkYhqKL0wau1RjtiACAGo1X7uH+nxW/03rNb4Hx3ZMCNlo9v66naAL6L3ZhTUg/pvlfHEEANRmyP9voL/k1Xt9741tmBByrDm00x4/buxd2QU2GI3dFW/EkC2SAIDCZmu01mrdztfxAfC91vfc2H4JIZvNIbOv6xq7KLvQhkKL4hf9dfJ0O100AQCFaG2erdHJ2j0Uvsf6XhvbLiFkK6ILa3d2wQ2JFsebNeaLJwBgW8WanK7XQ+F7a2yzhJCtjh75npddeIPS2P0ad0m6kAIAFm5XrMX5Oj0U2lNjeyWELCp6BPwn6QU4MPo5r9GYLagAgAWJtTddl4dk2tpZsa0SQhYdPUo8PbsQB+h2/axv0ZgusACALTJfa2+XbC0elE57aGynhJDtii6+U9dejAN1QI+M/X2w88UWAHBcYo09INkaPChda2+ObZQQst3RBfiG7MIcIj1CvkljuugCADYn1tZ03R2absXeENsnIaRUtOiMsgt0iFTU79N4oaQLMABgwy6MNTVdb4fG98rYNgkhpTMd2QuzC3WotNh+WGO2EAMAjiLW0HR9HaLpir0wtktCSC050Np/1gV6cO0FO1iN7Ruv2MW6nS7MAIDHUmG92NdO3c7X1eE56HtjbJOEkNqyf4d9rxalO5KLd7CmrX1MY7pIAwDmYq1M19Eh6rQX+p4Y2yMhpNaMW/s2XbTXrr2Ih0wL1GQyskt1O12wAWBpaW2crZHJ2jlg1/peGNsiIaT2HHqxPU4L1QXJxTxsjd26Opq9xm2+gAPAkpithVoTdTtfLwfK9z7fA2M7JIT0KbqIl+W1Xh/toBauKzSmizkADF2sgcvz3zw84tTY/gghfY0WsFcnF/fgda3tmTZ2pm6nCzsADI2veb726Xa6Lg6Z73Wx7RFC+h4tZL+WXehDp5/7QS3k/r7b6SIPAEPha52vebqdrodD5ntcbHeEkKFk2trz9Ij0K9lFP3T6ue8f87axAAZotrZpjdPtdP0bMt/TfG+LbY4QMrRMRvb9y/ZyWY/R2Cc1nivpBgAAPXJurGn5ejd0vpdpT4vtjRAy1Bw42f5e5y9CnS0ES0CP0B/S+CHJNgIA6IMPxVqWrnND53uY72WxrRFCliF6tPrabEFYFuPGphrfLdmmAAA1enesXem6thS0d8U2RghZtoxb+6V0YVgi09bu1kK4W7ezTQIAiutWbPdsrUrWsGXie1ZsX4SQZY0WxGdrQbh97QKxbLrWbl5t7QzdTjcOANhuvib52qTb6bq1RG73vSq2LULIssefK6RH8xcli8VS6Rr7ovDyWQCK87XI1yTdTterZaFjcBHPZyWEpNEi8Zq1i8Yy0kI5nTR2lW6nGwoALNBVszUoWZuW0GtieyKEkDzTkf2PZPFYSl1r++U9up1tLgCwZXyt8TVHt9P1aNlMG/sfsS0RQsiRc6C1Z2kBXfrnvT7KfZORvUtjuuEAwKbN15b7JFt7ltEntf88K7YjQgjZWFZ32jf5c4uSRWV5NfYZHZN36na+AQHABk1be+dUa4pu5+vNEtIxecfqifZNsQ0RQsixZ8zzXtfpWrtL3qHb6YYEAIfja4cs/UtbreV7TWw7hBByfBmv2E9pYVnK98I+Em0+n+I1YAFsiNaK2ZqRrCVL7n7fY2K7IYSQrcn+xp6sBebCNQsOpGtmz8m6QLfzDQvA0vK1QT6p2+n6scx0XC584JX2rbHNEELI1kcLTZstQJgtwndPR3aJbqcbGIClcoke1PKUgMPoVqyNbYUQQhabSWPP0YL88Wwxwsx9Oj7v1ZhtZgAGLK59XiXgMHzv2Kc9JLYTQgjZnhx6u329FiFfqNPFCXZoPH8R8Wtl3eYGYHCujWs+XQ8wc5rvHbGNEELI9me8Yi+cNPaFZIHCI744GdmNXWNn6Xa24QHoIb+mu9Zu0u2lf2vWI9Ie4XtFbBuEEFI2+xv7F1q8/R2m8kULMzpGD2m8Zdran2pMN0IA9Ytr+Ja4ptPrHXO+Nxw42f55bBeEEFJPtED9VrZwYb2usTum8zd4SDdGAPXxa9avXd1Or2s8VrdivxXbAyGE1Bkt6j8qd2WLGNZT2d8/aewDuv1WSTdLAEW91a/R2bWaXMNYz/cA3wtiWyCEkLoz3WlP1KLlz+dMFzWsp+Pl/5fjHm2O/BYWqIBfi92Krsn5tZlet1jP137fA2I7IISQ/kQL2Avknmxxw+HpmM1+C6uR38IC28ivufH82uO3q8eqsU/ruL0gln9CCOln9u60E7SonbpukcNRaRP4msbbpq29Q2O60QI4ft38Grstrrn0esQRnXpIa30s+4QQ0v9MRvbjWtz2rFnssEHaUPeN/TVhR/YW/TndfAEcg/m1dK1fWxrT6w5HtcfX9ljmCSFkWDn0fPv6rrU3JIsfNqhbsa9po71j0tjl+nO+IQM4PF07fg35taQ/p9cZNuQNvqbH8k4IIcPNtLEfUoH9aLIQ4hho8/3ytLXbJiO7VH/ON2kA/tvVS/1a8WtGf06vJ2yMr93jFfvhWM4JIWR5ogL729nCiE35gjbnW7U5X6zb+eYNLJHZtaBrQrd5Z78t0q3Y78TyTQghyxk9en+W/xf02SKJzdGGfVDH9WaNf6Y/p5s6MEQ+52PuH9Sf0+sDx27c2HW+VseyTQghRIvjKWsXSxw/bTbTrrGPyG79Od3sgT7zuT2b45rr+nN6HeC4nBLLNCGEkEdn30n2b/TI/rJk4cQW0LGdyi2z58Q29sf6u7QIAFXzuas5PG7tFp/T+rt0vuP4+Frsa3Isz4QQQg4XbUw/37X2qWwxxdbQ8f2qRn9bxmu0QZ2n23lJAGqgOTrVXNW8vTvmbjqvcfxma6/W4FiOCSGEbDTaqF6dLazYetqsumlrH1ORfaf+nJcHYBv5XNSDqpt1u5N03mJr+Zobyy8hhJDN5EBjT9OCeu7aBRaLoxL7l5PG7tT4fjlHf5cWC2Ar+VzzORdz7y/1d+n8xEKcu09rbSy7hBBCjjddYz+qzezGZMHFovn7tvtzY1t7j84DRRZbwueSrun3zOaWz7Fs7mGhfE31tTWWWUIIIVudcWv/U5vcarYIY5s0dkA+2a3Y1dr0ztffpcUEeDSfK9PWrva5M5tD2dzC9vA1tLGXx7JKCCFkkTl4kj2pa+3/pAsytl9jD6qU3KXxep2Xd+jv0uKC5TKbCz4n5nPjQf1dPn+wrXztvFdraCynhBBCtisHTrZnakO8IlucUU68B/y9Kiwf0XiZNkqeXjBwcY4vi3N+b8yBdH6gDJ2bK3RenhnLJyGEkFIZt/bfZ7/VSRZrVMJ/K6tCo9v+2pvv13jBZGSna0yLECo1P2cXxDm8ZXZO+W1q1WZr48h+MZZLQgghtUSb6IoW6r1rF25UbaLz5q8b+SHdvmzKf/xVjTgXl/m5mZ0jnSvJziHqtNfXxFgeCSGE1JiHXmpP0IL9Km22n1+ziKMv5r/Bm/12tmvsg/rz5bq9S94qacnCpvkx3aWSerkf66mOuf58r/7Mb1H7ar72vcrXwlgWCSGE1J7Vk+0btfn+bse77AyLP+WgsX267a/1+TG5RufZ38L2bcJTD9byY6Jj48dodqx0zPT3d+rv9gnldEB8rdO18Xu+9sUySAghpG/Z39iTtaD/r2yhxyA9IPfpnN+uTfxmlbMbNPrzMS/X371jMlKJa+0sjXnR6wPd9/gZ/GfxV3Hw35b6C/f7z3qz/+z6u/vEj0V2jDAwvsb5WhfLHiGEkL5n74n2VC3wvvGnCz+Wj//f4eP561ner43f3wN/T/xG0l/W62qNV6kIvlcf91euuGzc2iX680W6faH+brfGt09Hdp4+9xyNf6LicKZun6FC+cfOb/vf+cfic87zfxP/9kL/Wv41/Wv795h9L/+e8+99vd8X3d4jd/t99PvK/4WPNU7ztS2WOUIIIUOLSsB3qiCcnWwAANALvob5WhbLGiGEkKFntbVnaAPw/+An3RgAoEK7fO2KZYwQQsiyZTqy53atXZxsEABQBV+jfK2KZYsQQsiyZ9zaM7rGzsw2DQAowdckX5timSKEEEIem9UVe8qksdd3rX0p20gAYJFma4/WIF+LYlkihBBCjpzpTnviuLVTtJH4C+GnGwwAbKF7fc3xtSeWIUIIIeTY0zX2q/LxZKMBgOPia4uvMbHcEEIIIVuT1cae37X2vmzzAYBj4WuJrymxvBBCCCGLyf7GfiheRD7dkADgsLR2+BoSywkhhBCyPZmu2L/WRuTvxsV/yAXgSHyNOM3XjFg+CCGEkDLZ++t2wv4V+41JYzes2awALDOtCb42+BoRywUhhBBSTyYj+/7xiv1fbVhfTjcyAMOma3+2BmgtiGWBEEIIqTv7G/vb2sRe0rV247qNDcDgxLX+Er/2YxkghBBC+pdJY8/pGjtdvrJ2swPQX35N+7Xt13hc7oQQQsgwMt5pf2eyYi/VRndTtgkC6IfZNaxr2a/puLwJIYSQ4WYysh/oWjtDG+CD2cYIoC5+rfo169duXMaEEELIcuXQafY4bYg/K7uyzRJAWX5t+jXq12pctoQQQgjx/6hjOrIXdq1dnG2gALaHX4N+LfIfWhFCCCEbyMFX2N/vGvtVbaLvXrupAliId/s159deXIaEEEIIOdZ0J9m3j1v7n9pUr0k2WwCb5NfU7NrSNRaXGyGEEEK2Kqsn21MnK3ZyvGZkuhkDOLzZtaNryK+luKwIIYQQsuh0O+zpvgFrM75y7eYM4DGunD3g0zUTlw8hhBBCSmX6cnti19gL5C3apD+7ZtMGls1n/Vrwa8KvjbhMCCGEEFJjxq09Q141buzaZFMHBsfn+mzOa+7HZUAIIYSQvsX/K+nJyH6ha+xs2Zdt+kDf+Fz2Oe1zm1cCIIQQQgaabsWerQ3/N+WGrBAAtfI5O5u7msMxnQkhhBCyLPn8DvvmaWP/RaXgNcLTClAbn5Ov8TnqczWmLSGEEEKI2e0vtSeoJPwHlYVT5JKutWkUCGCxGlvVeImc4nPQ52JMS0IIIYSQjWVfY98zbu0lKhTnqsje/VdFAzgO0/lcOldeoqL6PTHdCCGEEEK2Lqsn2z/b39h/U+E4VUX25oeLCHAkMVdOnWju+ByK6UQIIYQQsn156ET7hvEO+3fTxl6kcvJGeZ90a4sLloOf+5gDb/Q54XPD50hMF0IIIYSQ+jId2T+ZjOzHVWZOGTf2tkljn1hbctBzOqezc+vPida59nMep58QQgghpN/59In2DautPaNr7EXTxv63xqv47Wz9Zr9F1bmKc/YiP4d+LuO0EkIIIYQsTw6eZE9aPdm+TwXpp6ettSpLp44be5fGPSpKX350icLWi2O8J475qX4O/Fz4OfFzE6eJEEIIIYQcLd1J9u2Txp4zGdkvjlvbqXL1VhWr96lw3fNw+cKR+bHyY6bbb50dQx1LP6Z+bOMwE0IIIYSQRebQTvvrBxp7morYD6iQPW/a2i+rnL1i3NjrVdbOlHfK9Sppd6i4DeZ1aWc/i/9M+tn8Z5zqZ/WfWR97hf78Yh2H5/kx8WPjxygOFyGEEEII6UtuerE97oEV+5Zuhz1dxe8Hpyv2UyqBv6KS90qVvtep9L1J42kavQiep8/Z7cVQ4xUa36/xgxo/ovFWjV4c79Ht+zV6kfyCxq+6uO1/5x+7R+6If+P/1r+Gfy3/mv61d/v30u0z43v7fXid3ye/b34f9++w5/p99vvuP0P8OIQQsiQx+/8BZgkVl9tyTt0AAAAASUVORK5CYII=\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\"],\"index\":[0,1,2,1,1,1,1,3,2,4,4,0,3]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: 74<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (168/100mL)<\\/html>\",\"<html>Station Number: 111<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (50/100mL)<\\/html>\",\"<html>Station Number: 114<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (447/100mL)<\\/html>\",\"<html>Station Number: 115<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (80/100mL)<\\/html>\",\"<html>Station Number: 116<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (30/100mL)<\\/html>\",\"<html>Station Number: 139<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (47/100mL)<\\/html>\",\"<html>Station Number: 151<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (90/100mL)<\\/html>\",\"<html>Station Number: 153<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (4000/100mL)<\\/html>\",\"<html>Station Number: 154<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 410 - 999 (433/100mL)<\\/html>\",\"<html>Station Number: 155<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (170/100mL)<\\/html>\",\"<html>Station Number: 166<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (310/100mL)<\\/html>\",\"<html>Station Number: 178<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: 130 - 999 (650/100mL)<\\/html>\",\"<html>Station Number: 179<br>Class: Marine (<i>Enterococcus<\\/i>)<br> Category: > 999 (1010/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,27.937863],\"lng\":[-82.383348,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Manatee County data show_fibmap(mancofibdata, yrsel = 2020, mosel = 7, areasel = 'Little Manatee River')  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\",\"data:image/png;base64,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\"],\"index\":[0,1]},\"iconWidth\":18,\"iconHeight\":18},null,null,{\"interactive\":true,\"draggable\":false,\"keyboard\":true,\"title\":\"\",\"alt\":\"\",\"zIndexOffset\":0,\"opacity\":1,\"riseOnHover\":false,\"riseOffset\":250},null,null,null,null,[\"<html>Station Number: D3<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: < 126 (88/100mL)<\\/html>\",\"<html>Station Number: D1<br>Class: Freshwater (<i>E. coli<\\/i>)<br> Category: 126 - 409 (365/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Marine (<em>Enterococcus<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_green.png?raw=true' style='width:10px;height:10px;'> < 35<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_yellow.png?raw=true' style='width:10px;height:10px;'> 35 - 129<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_orange.png?raw=true' style='width:10px;height:10px;'> 130 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/entero_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"<b>Freshwater (<em>E. Coli<\\/em>)<\\/b><br/>#/100mL<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_green.png?raw=true' style='width:10px;height:10px;'> < 126<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_yellow.png?raw=true' style='width:10px;height:10px;'> 126 - 409<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_orange.png?raw=true' style='width:10px;height:10px;'> 410 - 999<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/ecoli_red.png?raw=true' style='width:10px;height:10px;'> > 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.601944401,27.648594001],\"lng\":[-82.294442,-82.2111111]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"Map Fecal Indicator Bacteria matrix results year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"","code":"show_fibmatmap(   fibdata,   yrsel,   areasel,   indic,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   listout = FALSE,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"fibdata input data frame returned read_importfib,  read_importentero, read_importwqp, see details yrsel numeric value indicating year map areasel vector bay segment area names include, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period listout logical return list simple feature objects data used leaflet map, default FALSE warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"leaflet map selected year area showing station matrix scores listout = FALSE (default).  Bay segment scores also shown input data EPCHC. list simple feature objects returned listout = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"Placing mouse cursor item map reveal additional information segment station. input fibdata EPCHC (read_importfib), valid entries areasel include 'Alafia River', 'Hillsborough River', 'Big Bend', 'Cockroach Bay', 'East Lake Outfall', 'Hillsborough Bay', 'Little Manatee River', 'Lower Tampa Bay', 'McKay Bay', 'Middle Tampa Bay', 'Old Tampa Bay', 'Palm River', 'Tampa Bypass Canal', 'Valrico Lake'.  input data EPCHC (read_importentero), valid entries areasel include 'OTB', 'HB', 'MTB', 'LTB', 'BCB', 'MR'. Input read_importwqp Manatee County (21FLMANA_WQX) FIB data can also used.  function tested organizations.  Valid entries areasel include 'Big Slough', 'Bowlees Creek', 'Braden River', 'Bud Slough',  'Cedar Creek', 'Clay Gully', 'Cooper Creek', 'Curiosity Creek', 'Frog Creek', 'Gamble Creek', 'Gap Creek', 'Gates Creek', 'Gilley Creek', 'Hickory Hammock Creek', 'Lake Manatee', 'Little Manatee River', 'Lower Manatee River', 'Lower Tampa Bay', 'Manatee River Estuary', 'Mcmullen Creek', 'Mill Creek', 'Mud Lake Slough', 'Myakka River', 'Nonsense Creek', 'Palma Sola Bay', 'Piney Point Creek', 'Rattlesnake Slough', 'Sugarhouse Creek', 'Upper Manatee River', 'Ward Lake', 'Williams Creek' Bay segment matrix categories can shown input data read_importentero).  Stations data chosen specifically downstream endpoints bay segment, whereas datasets appropriate estimating bay segment outcomes.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria matrix results by year — show_fibmatmap","text":"","code":"# non-EPCHC, non Manatee County data show_fibmatmap(enterodata, yrsel = 2020, indic = 'entero', areasel = 'OTB') #> Warning: Stations with insufficient data for lagyr: 21FLHILL_WQX-619, 21FLTPA_WQX-G1SW0095  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Number: 2<br>Category: A\",\"<html>Station Number: 74<br>Category: A\",\"<html>Station Number: 105<br>Category: A\",\"<html>Station Number: 106<br>Category: A\",\"<html>Station Number: 108<br>Category: A\",\"<html>Station Number: 114<br>Category: B\",\"<html>Station Number: 115<br>Category: A\",\"<html>Station Number: 116<br>Category: A\",\"<html>Station Number: 137<br>Category: A\",\"<html>Station Number: 139<br>Category: A\",\"<html>Station Number: 152<br>Category: B\",\"<html>Station Number: 153<br>Category: A\",\"<html>Station Number: 165<br>Category: A\",\"<html>Station Number: 166<br>Category: B\",\"<html>Station Number: 176<br>Category: B\",\"<html>Station Number: 178<br>Category: A\",\"<html>Station Number: 179<br>Category: A\",\"<html>Station Number: 548<br>Category: A\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"<b>Report card<br/>categories<\\/b><br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_green.png?raw=true' style='width:10px;height:10px;'> A<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_yellow.png?raw=true' style='width:10px;height:10px;'> B<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_orange.png?raw=true' style='width:10px;height:10px;'> C<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_red.png?raw=true' style='width:10px;height:10px;'> D<br/><img src='https://github.com/tbep-tech/tbeptools/blob/master/inst/fibmat_purple.png?raw=true' style='width:10px;height:10px;'> E\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,28.149932],\"lng\":[-82.474942,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # Manatee County data show_fibmatmap(mancofibdata, yrsel = 2020, indic = 'fcolif', areasel = 'Lower Manatee River')  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segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"","code":"show_fibmatrix(   fibdata,   yrrng = NULL,   stas = NULL,   bay_segment = NULL,   indic = NULL,   threshold = NULL,   lagyr = 3,   subset_wetdry = c(\"all\", \"wet\", \"dry\"),   precipdata = NULL,   temporal_window = NULL,   wet_threshold = NULL,   txtsz = 3,   asreact = FALSE,   nrows = 10,   family = NA,   angle = 90,   size = 10,   hjust = 0,   plotly = FALSE,   width = NULL,   height = NULL,   warn = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"fibdata input data frame returned read_importfib, read_importentero, read_importwqp, see details yrrng numeric vector indicating min, max years include, defaults range years data, see details stas optional vector stations include, see details bay_segment optional vector bay segment names include, supercedes stas provided, see details indic character choice fecal indicator. Allowable options fcolif fecal coliform, entero Enterococcus. numeric column data frame must name. threshold optional numeric threshold calculate exceedances indicator bacteria choice. provided, defaults 400 fcolif 130 entero. lagyr numeric year lag calculate categories, see details subset_wetdry character, subset data frame wet dry samples defined wet_threshold temporal_window? Defaults \"\", subset. \"wet\" \"dry\" specified, anlz_fibwetdry called using specified parameters, data frame subsetted accordingly. precipdata input data frame returned read_importrain. columns : station, date (yyyy-mm-dd), rain (inches). object catchprecip data 1995-2023 select Enterococcus stations. NULL, defaults catchprecip. temporal_window numeric; required subset_wetdry \"\". number days precipitation summed (1 = day sample ; 2 = day sample + day ; etc.) wet_threshold numeric; required subset_wetdry \"\". inches accumulated defined temporal window, sample defined 'wet' time period txtsz numeric size text plot, applies tab = FALSE.  Use txtsz = NULL suppress. asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table family optional chr string indicating font family text labels angle numeric angle x-axis text labels size numeric size x-axis text labels hjust numeric horizontal justification x-axis text labels plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE warn logical print warnings stations insufficient data, default TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"static ggplot object returned default. reactable table returned asreact = TRUE.  interactive plotly object returned plotly = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL Fecal Coliform 130 CFU / 100 mL Enterococcus.  Bay segments used instead stations bay_segment NULL input data read_importentero.  likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3).  Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 document http://publicfiles.dep.state.fl.us/DEAR/BMAP/Tampa/MST%20Report/Fecal%20BMAP%20DST%20Final%20Report%20--%20June%202008.pdf Morrison et al. 2009 BASIS 5 proceedings. default stations fecal coliform data used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins bay_segment NULL input data read_importfib.  include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137).  stations can plotted using stas argument.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station or bay segment — show_fibmatrix","text":"","code":"show_fibmatrix(fibdata)   # change the threshold show_fibmatrix(fibdata, threshold = 200)   # change the indicator show_fibmatrix(fibdata, indic = 'entero')   # show matrix for only dry samples show_fibmatrix(enterodata, indic = 'entero', lagyr = 1, subset_wetdry = \"dry\",                temporal_window = 2, wet_threshold = 0.5) #> Warning: Stations with insufficient data for lagyr: 21FLPDEM_WQX-05-06"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Show Habitat Master Plan progress report card — show_hmpreport","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"Show Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"show_hmpreport(   acres,   subtacres,   hmptrgs,   typ,   twocol = FALSE,   strata = c(\"Subtidal\", \"Intertidal\", \"Supratidal\"),   ycollapse = FALSE,   text = 2.5,   xang = 25,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals typ character string indicating \"targets\" \"goals\" twocol logical indicating two colors shown target goals met symbols indicate likelihood attaining targets goals, see details strata character string indicating strata plot, one many \"Subtidal\", \"Intertidal\", \"Supratidal\" ycollapse logical indicating y-axis collapsed year data, see details text numeric indicating text size proportion target goal met habitat types shown cell types symbols twocol = T, use NULL suppress xang numeric angle habitat labels x-axis (top) family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"ggplot2 object showing overall progress attaining Habitat Master Plan targets goals.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"twocol = F, colors indicate target/goal met likelihood attaining target/goal 2030/2050.  Red indicates target/goal met likely met 2030/2050 (trending target/goal), yellow indicates target/goal met although likely met 2030/2050 (trending target/goal), light green indicates target/goal met although likely met 2030/2050 (trending target/goal), green indicates target/goal met likely met 2030/2050 (trending target/goal).  Numbers cell show proportion target goal met year data available.  twocol = T, colors indicate goal met (green) met (red) symbols cell indicate goal likely met (arrow) (arrow) 2030/2050.  cases, colors trends relative 2030 targets 2050 goals using typ argument. report card provides information artificial reefs, living shorelines, hard bottom habitats.  habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan. subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District.  years dataset typically match dataset collected approximate 2 3 year intervals.  default, year y-axis shown continuous variable, gaps shown years dataset unavailable.  Use ycollapse = TRUE remove years without data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"# view summarized data for report card, targets show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\")   # view summarized data for report card, goals show_hmpreport(acres, subtacres, hmptrgs, typ = \"goals\")   # remove empty years show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE)   # select only subtidal show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE, strata = 'Subtidal')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for indicator reporting — show_matrix","title":"Create a colorized table for indicator reporting — show_matrix","text":"Create colorized table indicator reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(   epcdata,   txtsz = 3,   trgs = NULL,   yrrng = NULL,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   asreact = FALSE,   nrows = 10,   abbrev = FALSE,   family = NA,   historic = TRUE,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for indicator reporting — show_matrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include, defaults range years epcdata bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for indicator reporting — show_matrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly matrix from any matrix function input — show_matrixplotly","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"Creates plotly matrix matrix function input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"show_matrixplotly(   mat,   family = NA,   tooltip = \"Result\",   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"mat input matrix output show_matrix, show_segmatrix, show_wqmatrix, show_tbnimatrix family optional chr string indicating font family text labels tooltip chr string indicating column name tooltip width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"mat <- show_wqmatrix(epcdata) show_matrixplotly(mat)  {\"x\":{\"data\":[{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 10.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 10.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 10.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 10.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 11, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 11.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 11.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 11.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 11.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 11.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 12, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Below (Average: 12.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 12.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 12.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 12.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 13, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 13.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 13.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 13.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 14.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5],\"text\":\"Result: Below (Average: 14.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 14.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 2.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 2.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 2.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 3.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 3.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 3.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 3.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 3.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1991.5,-1990.5,-1990.5,-1991.5,-1991.5,null,-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 3.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 3.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-1986.5,-1985.5,-1985.5,-1986.5,-1986.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5,null,-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2015.5,-2014.5,-2014.5,-2015.5,-2015.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 3.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 4.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 4.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 4.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 4.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 4.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 4.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 4.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 4.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Below (Average: 4.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 5.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 5.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2016.5,-2015.5,-2015.5,-2016.5,-2016.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 5.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 5.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5,null,-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 6.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 6.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 6.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 6.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 7.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 7.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 7.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5,null,-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 8.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 8.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 8.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 9.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 9.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 9.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 9.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 9.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 10.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 10.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Above (Average: 10.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 11, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 11.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 11.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 11.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Above (Average: 11.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Above (Average: 11.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 12, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Above (Average: 12.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 12.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 13, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 13, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 13.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 13.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 13.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 13.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 14.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 16.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 17.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 17.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 18, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 18.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 18.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 20.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 22, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 22.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 25.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 27.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 29.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 29.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 31.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 32.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 36.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 5.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 5.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 5.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5,null,-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 6.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Above (Average: 6.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5,null,-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 7.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5],\"text\":\"Result: Above (Average: 8.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5],\"text\":\"Result: Above (Average: 8.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Above (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Above (Average: 9.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-2017.5,-2016.5,-2016.5,-2017.5,-2017.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Above (Average: 9.5, Threshold: 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data recent year approximated five year monthly averages parameter outtxt1 optional text NMC action 1, added outcome column outtxt2 optional text NMC action 2, added outcome column outtxt3 optional text NMC action 3, added outcome column outtxt45 optional text NMC actions 4 5, added outcome column txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"flextable object showing reasonable assurance compliance bay segment selected year within five-year period.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Choosing bay_segment = 'RALTB' work epcdata additional data needed use option.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2)    years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years    years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/   necessary due observed water 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1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-94062d34{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Bay Segment Reasonable Assurance Assessment StepsDATA USED TO ASSESS ANNUAL REASONABLE ASSURANCEOUTCOMEYear 1 (2022)Year 2 (2023)Year 3 (2024)Year 4 (2025)Year 5 (2026)NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/LNo (7.1)No (6.2)All years below threshold so far, not necessary for NMC Actions 2-5NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive yearsNoNoAll years met threshold, not necessary for NMC Actions 3-5NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/yearN/AN/ANot necessary due to observed water quality and seagrass conditions in the bay segmentNMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation periodNot necessary when chlorophyll-a threshold met"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":null,"dir":"Reference","previous_headings":"","what":"Create reactable table from matrix data — show_reactable","title":"Create reactable table from matrix data — show_reactable","text":"Create reactable table matrix data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create reactable table from matrix data — show_reactable","text":"","code":"show_reactable(totab, colfun, nrows = 10, txtsz = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create reactable table from matrix data — show_reactable","text":"totab data frame wide format summarized results colfun Function specifying colors treated cell background nrows numeric specifying number rows table txtsz numeric indicating text size cells, use txtsz = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create reactable table from matrix data — show_reactable","text":"reactable table","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create reactable table from matrix data — show_reactable","text":"function used internally within show_matrix show_wqmatrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create reactable table from matrix data — show_reactable","text":"","code":"data(targets) data(epcdata)  library(tidyr) library(dplyr) #>  #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #>  #>     filter, lag #> The following objects are masked from ‘package:base’: #>  #>     intersect, setdiff, setequal, union  # data totab <- anlz_avedat(epcdata) %>%   .$ann %>%   filter(var %in% 'mean_chla') %>%   left_join(targets, by = 'bay_segment') %>%   select(bay_segment, yr, val, chla_thresh) %>%   mutate(     bay_segment = factor(bay_segment, levels = c('OTB', 'HB', 'MTB', 'LTB')),      outcome = case_when(       val < chla_thresh ~ 'green',       val >= chla_thresh ~ 'red'     )   ) %>%   select(bay_segment, yr, outcome) %>%   spread(bay_segment, outcome)  # color function colfun <- function(x){    out <- case_when(     x == 'red' ~ '#FF3333',     x == 'green' ~ '#33FF3B'   )    return(out)  }  show_reactable(totab, colfun)  {\"x\":{\"tag\":{\"name\":\"Reactable\",\"attribs\":{\"data\":{\"yr\":[1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"OTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"green\"],\"HB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"MTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"LTB\":[\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"]},\"columns\":[{\"id\":\"yr\",\"name\":\"Year\",\"type\":\"numeric\",\"style\":{\"fontSize\":\"16px\"}},{\"id\":\"OTB\",\"name\":\"OTB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"}]},{\"id\":\"HB\",\"name\":\"HB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"}]},{\"id\":\"MTB\",\"name\":\"MTB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\"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a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"Create barplot seagrass coverage time Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(   seagrass,   maxyr = 2022,   family = NA,   lastlab = \"acres\",   axsbrk = c(0.08, 0.1) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"seagrass input data.frame included package seagrass maxyr numeric maximum year plot family optional chr string indicating font family text labels lastlab chr string text append label last bar barplot axsbrk numeric vector length two indicating x-axis break occurs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"grid object showing acres total seagrass coverage Tampa Bay time.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"function creates flagship seagrass coverage graphic report coverage changes time.  data pre-processed included package seagrass dataset.  Original data Southwest Florida Water Management District available online https://data-swfwmd.opendata.arcgis.com/.  function data used create plot distinct used transect monitoring program.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(seagrass)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot metal concentrations against aluminum — show_sedimentalratio","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Plot metal concentrations aluminum","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot, must metal yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"ggplot object plotly object plotly = TRUE showing ratio selected parameter plotted aluminum concentrations collected site. Black lines show linear fit log-log model 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"plot shows selected contaminant concentration relative aluminum, latter present common metal Earth's crust.  elevated ratio metal parameter relative aluminum suggests higher background concentrations. Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Schropp, S. J., Graham Lewis, F., Windom, H. L., Ryan, J. D., Calder, F. D., & Burney, L. C. 1990. Interpretation metal concentrations estuarine sediments Florida using aluminum reference element. Estuaries. 13:227-235.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(sedimentdata, param = 'Arsenic') #> Warning: log-10 transformation introduced infinite values. #> Warning: log-10 transformation introduced infinite values."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sediment concentration averages by bay segment — show_sedimentave","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Plot sediment concentration averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(   sedimentdata,   param,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"ggplot object plotly object plotly = TRUE showing sediment averages 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(sedimentdata, param = 'Arsenic')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"Make map sediment contaminants stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(   sedimentdata,   param,   yrrng = c(1993, 2022),   funding_proj = \"TBEP\",   weight = 1.5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" weight numeric outline width station points map","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"map shows sediment contaminant concentrations selected parameter relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available.  Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend.  TEL PEL thresholds available, map sediment concentrations shown warning returned console.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(sedimentdata, param = 'Arsenic')  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mg/kg\",\"StationNumber: 93LTB39, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93LTB40, Year: 1993, Value: 10.3 mg/kg\",\"StationNumber: 93MTB41, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB42, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB43, Year: 1993, Value: 2.2 mg/kg\",\"StationNumber: 93MTB44, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB45, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93MTB47, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB48, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93MTB49, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93MTB50, Year: 1993, Value: 0.4 mg/kg\",\"StationNumber: 93MTB51, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB52, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB53, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB54, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB55, Year: 1993, Value: 5.4 mg/kg\",\"StationNumber: 93MTB56, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB57, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB58, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB59, Year: 1993, Value: 1.7 mg/kg\",\"StationNumber: 93MTB60, Year: 1993, Value: 2.4 mg/kg\",\"StationNumber: 93MTB61, Year: 1993, Value: 3.6 mg/kg\",\"StationNumber: 93OTB63, Year: 1993, Value: 5.5 mg/kg\",\"StationNumber: 93OTB64, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93OTB65, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB66, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB67, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB68, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB69, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB70, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93OTB71, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB72, Year: 1993, Value: 1.3 mg/kg\",\"StationNumber: 93OTB73, Year: 1993, Value: 0.7 mg/kg\",\"StationNumber: 93OTB76, Year: 1993, Value: 1.8 mg/kg\",\"StationNumber: 93OTB77, Year: 1993, Value: 0.3 mg/kg\",\"StationNumber: 93OTB78, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93OTB79, Year: 1993, Value: 3.7 mg/kg\",\"StationNumber: 93OTB80, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB83, Year: 1993, Value: 0.6 mg/kg\",\"StationNumber: 94HB03, Year: 1994, Value: 11.53 mg/kg\",\"StationNumber: 94HB04, Year: 1994, Value: 8.831 mg/kg\",\"StationNumber: 94HB05, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB06, Year: 1994, Value: 0.469 mg/kg\",\"StationNumber: 94HB07, Year: 1994, Value: 18.34 mg/kg\",\"StationNumber: 94HB08, Year: 1994, Value: 6.249 mg/kg\",\"StationNumber: 94HB09, Year: 1994, Value: 3.867 mg/kg\",\"StationNumber: 94HB10, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB12, Year: 1994, Value: 2.244 mg/kg\",\"StationNumber: 94HB13, Year: 1994, Value: 0.523 mg/kg\",\"StationNumber: 94HB14, Year: 1994, Value: 1.158 mg/kg\",\"StationNumber: 94HB15, Year: 1994, Value: 1.3 mg/kg\",\"StationNumber: 94HB16, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB18, Year: 1994, Value: 0.785 mg/kg\",\"StationNumber: 94HB19, Year: 1994, Value: 2.992 mg/kg\",\"StationNumber: 94HB20, Year: 1994, Value: 6.697 mg/kg\",\"StationNumber: 94HB21, Year: 1994, Value: 4.794 mg/kg\",\"StationNumber: 94HB22, Year: 1994, Value: 0.559 mg/kg\",\"StationNumber: 94HB23, Year: 1994, Value: 5.137 mg/kg\",\"StationNumber: 94LTB24, Year: 1994, Value: 2.557 mg/kg\",\"StationNumber: 94LTB25, Year: 1994, Value: 10.23 mg/kg\",\"StationNumber: 94LTB26, Year: 1994, Value: 0.982 mg/kg\",\"StationNumber: 94LTB27, Year: 1994, Value: 2.211 mg/kg\",\"StationNumber: 94LTB28, Year: 1994, Value: 3.464 mg/kg\",\"StationNumber: 94LTB29, Year: 1994, Value: 2.906 mg/kg\",\"StationNumber: 94LTB30, Year: 1994, Value: 3.515 mg/kg\",\"StationNumber: 94LTB31, Year: 1994, Value: 1.09 mg/kg\",\"StationNumber: 94LTB32, Year: 1994, Value: 0.538 mg/kg\",\"StationNumber: 94LTB33, Year: 1994, Value: 4.454 mg/kg\",\"StationNumber: 94LTB34, Year: 1994, Value: 1.975 mg/kg\",\"StationNumber: 94LTB35, Year: 1994, Value: 0.164 mg/kg\",\"StationNumber: 94LTB36, Year: 1994, Value: 4.695 mg/kg\",\"StationNumber: 94LTB37, Year: 1994, Value: 5.033 mg/kg\",\"StationNumber: 94LTB38, Year: 1994, Value: 2.197 mg/kg\",\"StationNumber: 94LTB39, Year: 1994, Value: 12.93 mg/kg\",\"StationNumber: 94LTB40, Year: 1994, Value: 8.954 mg/kg\",\"StationNumber: 94MR23, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR24, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR26, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR27, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR28, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR29, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR31, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR32, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR34, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR43, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MTB41, Year: 1994, Value: 0.465 mg/kg\",\"StationNumber: 94MTB42, Year: 1994, Value: 0.074 mg/kg\",\"StationNumber: 94MTB43, Year: 1994, Value: 6.242 mg/kg\",\"StationNumber: 94MTB44, Year: 1994, Value: 3.975 mg/kg\",\"StationNumber: 94MTB45, Year: 1994, Value: 0.417 mg/kg\",\"StationNumber: 94MTB47, Year: 1994, Value: 6.591 mg/kg\",\"StationNumber: 94MTB48, Year: 1994, Value: 0.209 mg/kg\",\"StationNumber: 94MTB49, Year: 1994, Value: 9.619 mg/kg\",\"StationNumber: 94MTB50, Year: 1994, Value: 1.634 mg/kg\",\"StationNumber: 94MTB51, Year: 1994, Value: 1.203 mg/kg\",\"StationNumber: 94MTB52, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB53, Year: 1994, Value: 0.173 mg/kg\",\"StationNumber: 94MTB54, Year: 1994, Value: 2.975 mg/kg\",\"StationNumber: 94MTB55, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB56, Year: 1994, Value: 0.028 mg/kg\",\"StationNumber: 94MTB57, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB58, Year: 1994, Value: 11.58 mg/kg\",\"StationNumber: 94MTB59, Year: 1994, Value: 1.603 mg/kg\",\"StationNumber: 94MTB60, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB61, Year: 1994, Value: 2.096 mg/kg\",\"StationNumber: 94OTB63, Year: 1994, Value: 8.811 mg/kg\",\"StationNumber: 94OTB64, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB65, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB66, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB67, Year: 1994, Value: 1.513 mg/kg\",\"StationNumber: 94OTB68, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB69, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB70, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB71, Year: 1994, Value: 1.415 mg/kg\",\"StationNumber: 94OTB72, Year: 1994, Value: 0.159 mg/kg\",\"StationNumber: 94OTB73, Year: 1994, Value: 1.64 mg/kg\",\"StationNumber: 94OTB76, Year: 1994, Value: 0.683 mg/kg\",\"StationNumber: 94OTB77, Year: 1994, Value: 0.111 mg/kg\",\"StationNumber: 94OTB78, Year: 1994, Value: 4.152 mg/kg\",\"StationNumber: 94OTB79, Year: 1994, Value: 0.086 mg/kg\",\"StationNumber: 94OTB80, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB83, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94TCB22, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB37, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB38, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB39, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB40, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB41, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB42, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 95BCB01, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB02, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB03, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB04, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB05, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB06, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB07, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB08, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB09, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB10, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB11, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB12, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB13, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB14, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB15, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB16, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB17, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB18, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB19, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB20, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB21, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95HB14, Year: 1995, Value: 0.565 mg/kg\",\"StationNumber: 95HB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB17, Year: 1995, Value: 0.844 mg/kg\",\"StationNumber: 95HB18, Year: 1995, Value: 2.685 mg/kg\",\"StationNumber: 95HB19, Year: 1995, Value: 0.011 mg/kg\",\"StationNumber: 95HB22, Year: 1995, Value: 0.134 mg/kg\",\"StationNumber: 95HB23, Year: 1995, Value: 2.499 mg/kg\",\"StationNumber: 95HB24, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB25, Year: 1995, Value: 0.258 mg/kg\",\"StationNumber: 95HB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB28, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB37, Year: 1995, Value: 1.482 mg/kg\",\"StationNumber: 95HB38, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB40, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB41, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB42, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB43, Year: 1995, Value: 0.432 mg/kg\",\"StationNumber: 95HB44, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB45, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB46, Year: 1995, Value: 3.023 mg/kg\",\"StationNumber: 95HB48, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB49, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB51, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB52, Year: 1995, Value: 1.696 mg/kg\",\"StationNumber: 95HB54, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB55, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB56, Year: 1995, Value: 4.81 mg/kg\",\"StationNumber: 95LTB01, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB02, Year: 1995, Value: 0.076 mg/kg\",\"StationNumber: 95LTB04, Year: 1995, Value: 1.513 mg/kg\",\"StationNumber: 95LTB05, Year: 1995, Value: 1.347 mg/kg\",\"StationNumber: 95LTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB07, Year: 1995, Value: 0.876 mg/kg\",\"StationNumber: 95LTB08, Year: 1995, Value: 2.389 mg/kg\",\"StationNumber: 95LTB09, Year: 1995, Value: 1.187 mg/kg\",\"StationNumber: 95LTB10, Year: 1995, Value: 1.839 mg/kg\",\"StationNumber: 95LTB11, Year: 1995, Value: 2.845 mg/kg\",\"StationNumber: 95LTB12, Year: 1995, Value: 0.953 mg/kg\",\"StationNumber: 95LTB13, Year: 1995, Value: 1.192 mg/kg\",\"StationNumber: 95LTB15, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB17, Year: 1995, Value: 1.678 mg/kg\",\"StationNumber: 95LTB18, Year: 1995, Value: 1.29 mg/kg\",\"StationNumber: 95LTB19, Year: 1995, Value: 0.872 mg/kg\",\"StationNumber: 95LTB20, Year: 1995, Value: 0.139 mg/kg\",\"StationNumber: 95LTB21, Year: 1995, Value: 0.009 mg/kg\",\"StationNumber: 95LTB23, Year: 1995, Value: 1.475 mg/kg\",\"StationNumber: 95LTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB29, Year: 1995, Value: 0.225 mg/kg\",\"StationNumber: 95MR23, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR24, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR25, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR26, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR27, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR28, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR29, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR31, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR32, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR34, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR43, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MTB03, Year: 1995, Value: 0.098 mg/kg\",\"StationNumber: 95MTB04, Year: 1995, Value: 0.296 mg/kg\",\"StationNumber: 95MTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB07, Year: 1995, Value: 2.145 mg/kg\",\"StationNumber: 95MTB08, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB10, Year: 1995, Value: 0.254 mg/kg\",\"StationNumber: 95MTB15, Year: 1995, Value: 0.107 mg/kg\",\"StationNumber: 95MTB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB17, Year: 1995, Value: 9.688 mg/kg\",\"StationNumber: 95MTB18, Year: 1995, Value: 5.681 mg/kg\",\"StationNumber: 95MTB19, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB21, Year: 1995, Value: 0.19 mg/kg\",\"StationNumber: 95MTB24, Year: 1995, Value: 0.144 mg/kg\",\"StationNumber: 95MTB25, Year: 1995, Value: 0.264 mg/kg\",\"StationNumber: 95MTB26, Year: 1995, Value: 0.067 mg/kg\",\"StationNumber: 95MTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB30, Year: 1995, Value: 0.738 mg/kg\",\"StationNumber: 95MTB31, Year: 1995, Value: 0.483 mg/kg\",\"StationNumber: 95MTB32, Year: 1995, Value: 0.445 mg/kg\",\"StationNumber: 95MTB34, Year: 1995, Value: 1.065 mg/kg\",\"StationNumber: 95MTB35, Year: 1995, Value: 0.129 mg/kg\",\"StationNumber: 95OTB02, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB03, Year: 1995, Value: 0.259 mg/kg\",\"StationNumber: 95OTB05, Year: 1995, Value: 0.772 mg/kg\",\"StationNumber: 95OTB06, Year: 1995, Value: 0.84 mg/kg\",\"StationNumber: 95OTB07, Year: 1995, Value: 0.274 mg/kg\",\"StationNumber: 95OTB08, Year: 1995, Value: 0.087 mg/kg\",\"StationNumber: 95OTB11, Year: 1995, Value: 0.214 mg/kg\",\"StationNumber: 95OTB12, Year: 1995, Value: 0.344 mg/kg\",\"StationNumber: 95OTB13, Year: 1995, Value: 0.269 mg/kg\",\"StationNumber: 95OTB14, Year: 1995, Value: 0.451 mg/kg\",\"StationNumber: 95OTB15, Year: 1995, Value: 7.62 mg/kg\",\"StationNumber: 95OTB17, Year: 1995, Value: 0.59 mg/kg\",\"StationNumber: 95OTB18, Year: 1995, Value: 0.356 mg/kg\",\"StationNumber: 95OTB19, Year: 1995, Value: 3.07 mg/kg\",\"StationNumber: 95OTB20, Year: 1995, Value: 0.314 mg/kg\",\"StationNumber: 95OTB22, Year: 1995, Value: 0.522 mg/kg\",\"StationNumber: 95OTB23, Year: 1995, Value: 0.135 mg/kg\",\"StationNumber: 95OTB24, Year: 1995, Value: 0.476 mg/kg\",\"StationNumber: 95OTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB26, Year: 1995, Value: 0.226 mg/kg\",\"StationNumber: 95OTB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB30, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95TCB22, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB37, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB38, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB39, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB40, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB41, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB42, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 96BCB02, Year: 1996, Value: 1.681 mg/kg\",\"StationNumber: 96BCB04, Year: 1996, Value: 4.387 mg/kg\",\"StationNumber: 96BCB07, Year: 1996, Value: 1.51 mg/kg\",\"StationNumber: 96BCB08, Year: 1996, Value: 2.112 mg/kg\",\"StationNumber: 96BCB12, Year: 1996, Value: 1.308 mg/kg\",\"StationNumber: 96BCB13, Year: 1996, Value: 5.299 mg/kg\",\"StationNumber: 96BCB15, Year: 1996, Value: 3.323 mg/kg\",\"StationNumber: 96BCB19, Year: 1996, Value: 0.7 mg/kg\",\"StationNumber: 96BCB24, Year: 1996, Value: 0.754 mg/kg\",\"StationNumber: 96BCB26, Year: 1996, Value: 0.16 mg/kg\",\"StationNumber: 96BCB27, Year: 1996, Value: 0.783 mg/kg\",\"StationNumber: 96BCB30, Year: 1996, Value: 0.546 mg/kg\",\"StationNumber: 96BCB31, Year: 1996, Value: 0.256 mg/kg\",\"StationNumber: 96BCB34, Year: 1996, Value: 0.29 mg/kg\",\"StationNumber: 96BCB36, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96BCB39, Year: 1996, Value: 0.25 mg/kg\",\"StationNumber: 96BCB40, Year: 1996, Value: 1.148 mg/kg\",\"StationNumber: 96BCB41, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96BCB44, Year: 1996, Value: 0.98 mg/kg\",\"StationNumber: 96BCB46, Year: 1996, Value: 0.339 mg/kg\",\"StationNumber: 96BCB49, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96HB13, Year: 1996, Value: 2.778 mg/kg\",\"StationNumber: 96HB16, Year: 1996, Value: 0.534 mg/kg\",\"StationNumber: 96HB18, Year: 1996, Value: 1.303 mg/kg\",\"StationNumber: 96HB20, Year: 1996, Value: 4.202 mg/kg\",\"StationNumber: 96HB22, Year: 1996, Value: 3.994 mg/kg\",\"StationNumber: 96HB23, Year: 1996, Value: 2.264 mg/kg\",\"StationNumber: 96HB24, Year: 1996, Value: 0.182 mg/kg\",\"StationNumber: 96HB26, Year: 1996, Value: 0.077 mg/kg\",\"StationNumber: 96HB27, Year: 1996, Value: 2.885 mg/kg\",\"StationNumber: 96HB29, Year: 1996, Value: 1.112 mg/kg\",\"StationNumber: 96HB36, Year: 1996, Value: 1.771 mg/kg\",\"StationNumber: 96HB37, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96HB38, Year: 1996, Value: 2.504 mg/kg\",\"StationNumber: 96HB39, Year: 1996, Value: 1.465 mg/kg\",\"StationNumber: 96HB42, Year: 1996, Value: 2.318 mg/kg\",\"StationNumber: 96HB43, Year: 1996, Value: 2.562 mg/kg\",\"StationNumber: 96HB44, Year: 1996, Value: 1.521 mg/kg\",\"StationNumber: 96HB45, Year: 1996, Value: 0.167 mg/kg\",\"StationNumber: 96HB46, Year: 1996, Value: 7.157 mg/kg\",\"StationNumber: 96HB47, Year: 1996, Value: 0.464 mg/kg\",\"StationNumber: 96HB48, Year: 1996, Value: 4.527 mg/kg\",\"StationNumber: 96HB50, Year: 1996, Value: 0.914 mg/kg\",\"StationNumber: 96HB51, Year: 1996, Value: 0.333 mg/kg\",\"StationNumber: 96HB52, Year: 1996, Value: 0.158 mg/kg\",\"StationNumber: 96HB53, Year: 1996, Value: 0.597 mg/kg\",\"StationNumber: 96HB54, Year: 1996, Value: 0.378 mg/kg\",\"StationNumber: 96HB56, Year: 1996, Value: 5.858 mg/kg\",\"StationNumber: 96LTB01, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB02, Year: 1996, Value: 1.027 mg/kg\",\"StationNumber: 96LTB03, Year: 1996, Value: 1.366 mg/kg\",\"StationNumber: 96LTB04, Year: 1996, Value: 2.045 mg/kg\",\"StationNumber: 96LTB05, Year: 1996, Value: 1.675 mg/kg\",\"StationNumber: 96LTB06, Year: 1996, Value: 0.221 mg/kg\",\"StationNumber: 96LTB07, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB08, Year: 1996, Value: 0.48 mg/kg\",\"StationNumber: 96LTB09, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB10, Year: 1996, Value: 11.04 mg/kg\",\"StationNumber: 96LTB11, Year: 1996, Value: 1.949 mg/kg\",\"StationNumber: 96LTB12, Year: 1996, Value: 0.571 mg/kg\",\"StationNumber: 96LTB13, Year: 1996, Value: 2.568 mg/kg\",\"StationNumber: 96LTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB17, Year: 1996, Value: 6.999 mg/kg\",\"StationNumber: 96LTB18, Year: 1996, Value: 2.186 mg/kg\",\"StationNumber: 96LTB19, Year: 1996, Value: 2.416 mg/kg\",\"StationNumber: 96LTB20, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB21, Year: 1996, Value: 0.131 mg/kg\",\"StationNumber: 96LTB23, Year: 1996, Value: 2.988 mg/kg\",\"StationNumber: 96LTB24, Year: 1996, Value: 1.609 mg/kg\",\"StationNumber: 96LTB25, Year: 1996, Value: 0.876 mg/kg\",\"StationNumber: 96LTB26, Year: 1996, Value: 0.241 mg/kg\",\"StationNumber: 96LTB27, Year: 1996, Value: 2.428 mg/kg\",\"StationNumber: 96MR20, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MR21, Year: 1996, Value: 0.319 mg/kg\",\"StationNumber: 96MR23, Year: 1996, Value: 0.042 mg/kg\",\"StationNumber: 96MR24, Year: 1996, Value: 0.449 mg/kg\",\"StationNumber: 96MR25, Year: 1996, Value: 0.192 mg/kg\",\"StationNumber: 96MR26, Year: 1996, Value: 0.486 mg/kg\",\"StationNumber: 96MR27, Year: 1996, Value: 0.302 mg/kg\",\"StationNumber: 96MR28, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR29, Year: 1996, Value: 0.596 mg/kg\",\"StationNumber: 96MR30, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR31, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR32, Year: 1996, Value: 0.716 mg/kg\",\"StationNumber: 96MR43, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB04, Year: 1996, Value: 0.503 mg/kg\",\"StationNumber: 96MTB05, Year: 1996, Value: 0.329 mg/kg\",\"StationNumber: 96MTB07, Year: 1996, Value: 0.458 mg/kg\",\"StationNumber: 96MTB09, Year: 1996, Value: 2.141 mg/kg\",\"StationNumber: 96MTB10, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96MTB11, Year: 1996, Value: 1.049 mg/kg\",\"StationNumber: 96MTB12, Year: 1996, Value: 0.633 mg/kg\",\"StationNumber: 96MTB13, Year: 1996, Value: 0 mg/kg\",\"StationNumber: 96MTB14, Year: 1996, Value: 6.52 mg/kg\",\"StationNumber: 96MTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB16, Year: 1996, Value: 0.063 mg/kg\",\"StationNumber: 96MTB17, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96MTB18, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB19, Year: 1996, Value: 0.119 mg/kg\",\"StationNumber: 96MTB20, Year: 1996, Value: 4.526 mg/kg\",\"StationNumber: 96MTB23, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB24, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MTB25, Year: 1996, Value: 0.756 mg/kg\",\"StationNumber: 96MTB26, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB30, Year: 1996, Value: 0.024 mg/kg\",\"StationNumber: 96MTB31, Year: 1996, Value: 0.827 mg/kg\",\"StationNumber: 96MTB32, Year: 1996, Value: 5.666 mg/kg\",\"StationNumber: 96MTB34, Year: 1996, Value: 0.664 mg/kg\",\"StationNumber: 96MTB35, Year: 1996, Value: 0.206 mg/kg\",\"StationNumber: 96OTB07, Year: 1996, Value: 0.477 mg/kg\",\"StationNumber: 96OTB11, Year: 1996, Value: 0.239 mg/kg\",\"StationNumber: 96OTB12, Year: 1996, Value: 1.951 mg/kg\",\"StationNumber: 96OTB13, Year: 1996, Value: 0.721 mg/kg\",\"StationNumber: 96OTB14, Year: 1996, Value: 1.631 mg/kg\",\"StationNumber: 96OTB17, Year: 1996, Value: 1.716 mg/kg\",\"StationNumber: 96OTB18, Year: 1996, Value: 1.202 mg/kg\",\"StationNumber: 96OTB19, Year: 1996, Value: 1.134 mg/kg\",\"StationNumber: 96OTB20, Year: 1996, Value: 1.832 mg/kg\",\"StationNumber: 96OTB23, Year: 1996, Value: 0.698 mg/kg\",\"StationNumber: 96OTB24, Year: 1996, Value: 0.749 mg/kg\",\"StationNumber: 96OTB26, Year: 1996, Value: 0.526 mg/kg\",\"StationNumber: 96OTB27, Year: 1996, Value: 0.629 mg/kg\",\"StationNumber: 96OTB29, Year: 1996, Value: 0.574 mg/kg\",\"StationNumber: 96OTB30, Year: 1996, Value: 0.106 mg/kg\",\"StationNumber: 96TCB22, Year: 1996, Value: 3.557 mg/kg\",\"StationNumber: 96TCB36, Year: 1996, Value: 1.001 mg/kg\",\"StationNumber: 96TCB37, Year: 1996, Value: 5.738 mg/kg\",\"StationNumber: 96TCB38, Year: 1996, Value: 2.784 mg/kg\",\"StationNumber: 96TCB39, Year: 1996, Value: 1.919 mg/kg\",\"StationNumber: 96TCB40, Year: 1996, Value: 1.242 mg/kg\",\"StationNumber: 96TCB41, Year: 1996, Value: 1.244 mg/kg\",\"StationNumber: 96TCB42, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 97BCB02, Year: 1997, Value: 0.9 mg/kg\",\"StationNumber: 97BCB08, Year: 1997, Value: 3.79 mg/kg\",\"StationNumber: 97BCB10, Year: 1997, Value: 1.504 mg/kg\",\"StationNumber: 97BCB13, Year: 1997, Value: 1.11 mg/kg\",\"StationNumber: 97BCB17, Year: 1997, Value: 3.833 mg/kg\",\"StationNumber: 97BCB18, Year: 1997, Value: 0.053 mg/kg\",\"StationNumber: 97BCB27, Year: 1997, Value: 7.606 mg/kg\",\"StationNumber: 97BCB30, Year: 1997, Value: 1.439 mg/kg\",\"StationNumber: 97BCB31, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97BCB36, Year: 1997, Value: 0.548 mg/kg\",\"StationNumber: 97BCB37, Year: 1997, Value: 0.041 mg/kg\",\"StationNumber: 97BCB40, Year: 1997, Value: 2.312 mg/kg\",\"StationNumber: 97BCB46, Year: 1997, Value: 1.153 mg/kg\",\"StationNumber: 97BCB50, Year: 1997, Value: 3.046 mg/kg\",\"StationNumber: 97BCB57-1, Year: 1997, Value: 4.964 mg/kg\",\"StationNumber: 97BCB58-1, Year: 1997, Value: 8.192 mg/kg\",\"StationNumber: 97BCB58-2, Year: 1997, Value: 1.739 mg/kg\",\"StationNumber: 97BCB59-1, Year: 1997, Value: 1.017 mg/kg\",\"StationNumber: 97BCB59-2, Year: 1997, Value: 1.042 mg/kg\",\"StationNumber: 97BCB60-2, Year: 1997, Value: 0.932 mg/kg\",\"StationNumber: 97BCB60-4, Year: 1997, Value: 1.016 mg/kg\",\"StationNumber: 97HB10, Year: 1997, Value: 2.262 mg/kg\",\"StationNumber: 97HB13, Year: 1997, Value: 3.367 mg/kg\",\"StationNumber: 97HB18, Year: 1997, Value: 0.393 mg/kg\",\"StationNumber: 97HB22, Year: 1997, Value: 1.588 mg/kg\",\"StationNumber: 97HB23, Year: 1997, Value: 0.17 mg/kg\",\"StationNumber: 97HB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB29, Year: 1997, Value: 1.632 mg/kg\",\"StationNumber: 97HB36, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB37, Year: 1997, Value: 1.131 mg/kg\",\"StationNumber: 97HB38, Year: 1997, Value: 0.753 mg/kg\",\"StationNumber: 97HB39, Year: 1997, Value: 1.737 mg/kg\",\"StationNumber: 97HB43, Year: 1997, Value: 0.107 mg/kg\",\"StationNumber: 97HB44, Year: 1997, Value: 0.576 mg/kg\",\"StationNumber: 97HB45, Year: 1997, Value: 0.888 mg/kg\",\"StationNumber: 97HB46, Year: 1997, Value: 0.424 mg/kg\",\"StationNumber: 97HB48, Year: 1997, Value: 0.494 mg/kg\",\"StationNumber: 97HB50, Year: 1997, Value: 2.002 mg/kg\",\"StationNumber: 97HB53, Year: 1997, Value: 0.349 mg/kg\",\"StationNumber: 97HB54, Year: 1997, Value: 0.918 mg/kg\",\"StationNumber: 97HB55, Year: 1997, Value: 0.597 mg/kg\",\"StationNumber: 97HB56, Year: 1997, Value: 0.564 mg/kg\",\"StationNumber: 97LTB01, Year: 1997, Value: 0.364 mg/kg\",\"StationNumber: 97LTB02, Year: 1997, Value: 0.667 mg/kg\",\"StationNumber: 97LTB03, Year: 1997, Value: 1.481 mg/kg\",\"StationNumber: 97LTB06, Year: 1997, Value: 1.145 mg/kg\",\"StationNumber: 97LTB07, Year: 1997, Value: 1.822 mg/kg\",\"StationNumber: 97LTB09, Year: 1997, Value: 5.154 mg/kg\",\"StationNumber: 97LTB10, Year: 1997, Value: 9.854 mg/kg\",\"StationNumber: 97LTB11, Year: 1997, Value: 10.221 mg/kg\",\"StationNumber: 97LTB12, Year: 1997, Value: 2.644 mg/kg\",\"StationNumber: 97LTB13, Year: 1997, Value: 1.991 mg/kg\",\"StationNumber: 97LTB15, Year: 1997, Value: 0.607 mg/kg\",\"StationNumber: 97LTB17, Year: 1997, Value: 3.416 mg/kg\",\"StationNumber: 97LTB18, Year: 1997, Value: 2.814 mg/kg\",\"StationNumber: 97LTB19, Year: 1997, Value: 2.16 mg/kg\",\"StationNumber: 97LTB20, Year: 1997, Value: 0.558 mg/kg\",\"StationNumber: 97LTB21, Year: 1997, Value: 1.584 mg/kg\",\"StationNumber: 97LTB23, Year: 1997, Value: 2.302 mg/kg\",\"StationNumber: 97LTB24, Year: 1997, Value: 0.57 mg/kg\",\"StationNumber: 97LTB25, Year: 1997, Value: 0.538 mg/kg\",\"StationNumber: 97LTB26, Year: 1997, Value: 0.1 mg/kg\",\"StationNumber: 97LTB28, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MR09, Year: 1997, Value: 0.458 mg/kg\",\"StationNumber: 97MR10, Year: 1997, Value: 0.672 mg/kg\",\"StationNumber: 97MR11, Year: 1997, Value: 2.184 mg/kg\",\"StationNumber: 97MR12, Year: 1997, Value: 1.339 mg/kg\",\"StationNumber: 97MR13, Year: 1997, Value: 1.416 mg/kg\",\"StationNumber: 97MR14, Year: 1997, Value: 1.886 mg/kg\",\"StationNumber: 97MR15, Year: 1997, Value: 1.079 mg/kg\",\"StationNumber: 97MR16, Year: 1997, Value: 1.293 mg/kg\",\"StationNumber: 97MR17, Year: 1997, Value: 0.902 mg/kg\",\"StationNumber: 97MR18, Year: 1997, Value: 1.223 mg/kg\",\"StationNumber: 97MR19, Year: 1997, Value: 1.164 mg/kg\",\"StationNumber: 97MR20, Year: 1997, Value: 1.285 mg/kg\",\"StationNumber: 97MR21, Year: 1997, Value: 1.766 mg/kg\",\"StationNumber: 97MTB02, Year: 1997, Value: 0.086 mg/kg\",\"StationNumber: 97MTB03, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB04, Year: 1997, Value: 0.531 mg/kg\",\"StationNumber: 97MTB05, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB07, Year: 1997, Value: 1.425 mg/kg\",\"StationNumber: 97MTB09, Year: 1997, Value: 0.514 mg/kg\",\"StationNumber: 97MTB10, Year: 1997, Value: 1.592 mg/kg\",\"StationNumber: 97MTB12, Year: 1997, Value: 0.718 mg/kg\",\"StationNumber: 97MTB14, Year: 1997, Value: 1.277 mg/kg\",\"StationNumber: 97MTB15, Year: 1997, Value: 0.612 mg/kg\",\"StationNumber: 97MTB16, Year: 1997, Value: 1.06 mg/kg\",\"StationNumber: 97MTB17, Year: 1997, Value: 1.021 mg/kg\",\"StationNumber: 97MTB18, Year: 1997, Value: 0.336 mg/kg\",\"StationNumber: 97MTB19, Year: 1997, Value: 0.112 mg/kg\",\"StationNumber: 97MTB23, Year: 1997, Value: 0.992 mg/kg\",\"StationNumber: 97MTB24, Year: 1997, Value: 6.807 mg/kg\",\"StationNumber: 97MTB25, Year: 1997, Value: 1.392 mg/kg\",\"StationNumber: 97MTB26, Year: 1997, Value: 0.193 mg/kg\",\"StationNumber: 97MTB30, Year: 1997, Value: 0.442 mg/kg\",\"StationNumber: 97MTB31, Year: 1997, Value: 0.756 mg/kg\",\"StationNumber: 97MTB32, Year: 1997, Value: 8.261 mg/kg\",\"StationNumber: 97MTB35, Year: 1997, Value: 0.47 mg/kg\",\"StationNumber: 97OTB03, Year: 1997, Value: 3.828 mg/kg\",\"StationNumber: 97OTB06, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB07, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB11, Year: 1997, Value: 0.142 mg/kg\",\"StationNumber: 97OTB12, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB13, Year: 1997, Value: 0.724 mg/kg\",\"StationNumber: 97OTB17, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB18, Year: 1997, Value: 0.029 mg/kg\",\"StationNumber: 97OTB19, Year: 1997, Value: 0.012 mg/kg\",\"StationNumber: 97OTB20, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB22, Year: 1997, Value: 0.13 mg/kg\",\"StationNumber: 97OTB23, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB26, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB29, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97TCB01, Year: 1997, Value: 2.943 mg/kg\",\"StationNumber: 97TCB02, Year: 1997, Value: 2.221 mg/kg\",\"StationNumber: 97TCB03, Year: 1997, Value: 4.341 mg/kg\",\"StationNumber: 97TCB04, Year: 1997, Value: 3.585 mg/kg\",\"StationNumber: 97TCB05, Year: 1997, Value: 2.998 mg/kg\",\"StationNumber: 97TCB06, Year: 1997, Value: 1.551 mg/kg\",\"StationNumber: 97TCB07, Year: 1997, Value: 3.303 mg/kg\",\"StationNumber: 97TCB08, Year: 1997, Value: 0.787 mg/kg\",\"StationNumber: 98BCB06, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB09, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB11, Year: 1998, Value: 0.445 mg/kg\",\"StationNumber: 98BCB12, Year: 1998, Value: 2.509 mg/kg\",\"StationNumber: 98BCB15, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98BCB17, Year: 1998, Value: 1.517 mg/kg\",\"StationNumber: 98BCB21, Year: 1998, Value: 0.54 mg/kg\",\"StationNumber: 98BCB27, Year: 1998, Value: 0.102 mg/kg\",\"StationNumber: 98BCB28, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB32, Year: 1998, Value: 0.09 mg/kg\",\"StationNumber: 98BCB38, Year: 1998, Value: 0.595 mg/kg\",\"StationNumber: 98BCB40, Year: 1998, Value: 0.392 mg/kg\",\"StationNumber: 98BCB43, Year: 1998, Value: 0.065 mg/kg\",\"StationNumber: 98BCB46, Year: 1998, Value: 1.568 mg/kg\",\"StationNumber: 98BCB57/1, Year: 1998, Value: 4.454 mg/kg\",\"StationNumber: 98BCB58/1, Year: 1998, Value: 4.341 mg/kg\",\"StationNumber: 98BCB58/2, Year: 1998, Value: 3.761 mg/kg\",\"StationNumber: 98BCB59/1, Year: 1998, Value: 0.088 mg/kg\",\"StationNumber: 98BCB59/2, Year: 1998, Value: 1.103 mg/kg\",\"StationNumber: 98BCB60/2, Year: 1998, Value: 0.999 mg/kg\",\"StationNumber: 98BCB60/4, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98HB003, Year: 1998, Value: 0.036 mg/kg\",\"StationNumber: 98HB006, Year: 1998, Value: 3.089 mg/kg\",\"StationNumber: 98HB014, Year: 1998, Value: 2.09 mg/kg\",\"StationNumber: 98HB016, Year: 1998, Value: 1.995 mg/kg\",\"StationNumber: 98HB017, Year: 1998, Value: 0.072 mg/kg\",\"StationNumber: 98HB024, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB030, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB049, Year: 1998, Value: 2.146 mg/kg\",\"StationNumber: 98HB052, Year: 1998, Value: 0.64 mg/kg\",\"StationNumber: 98HB056, Year: 1998, Value: 1.656 mg/kg\",\"StationNumber: 98HB059, Year: 1998, Value: 0.534 mg/kg\",\"StationNumber: 98HB069, Year: 1998, Value: 0.785 mg/kg\",\"StationNumber: 98HB080, Year: 1998, Value: 3.475 mg/kg\",\"StationNumber: 98HB089, Year: 1998, Value: 0.435 mg/kg\",\"StationNumber: 98HB130, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98HB153, Year: 1998, Value: 0.777 mg/kg\",\"StationNumber: 98HB171, Year: 1998, Value: 0.842 mg/kg\",\"StationNumber: 98HB180, Year: 1998, Value: 1.348 mg/kg\",\"StationNumber: 98HB224, Year: 1998, Value: 1.942 mg/kg\",\"StationNumber: 98HB237, Year: 1998, Value: 0.471 mg/kg\",\"StationNumber: 98HB245, Year: 1998, Value: 0.642 mg/kg\",\"StationNumber: 98HB252, Year: 1998, Value: 1.898 mg/kg\",\"StationNumber: 98HB280, Year: 1998, Value: 0.134 mg/kg\",\"StationNumber: 98HB789, Year: 1998, Value: 2.42 mg/kg\",\"StationNumber: 98HBDIcanal, Year: 1998, Value: 0.931 mg/kg\",\"StationNumber: 98HBspark, Year: 1998, Value: 0.258 mg/kg\",\"StationNumber: 98LTB0014, Year: 1998, Value: 2.93 mg/kg\",\"StationNumber: 98LTB0025, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0049, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0095, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0123, Year: 1998, Value: 0.56 mg/kg\",\"StationNumber: 98LTB0144, Year: 1998, Value: 0.476 mg/kg\",\"StationNumber: 98LTB0151, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0168, Year: 1998, Value: 0.441 mg/kg\",\"StationNumber: 98LTB0183, Year: 1998, Value: 0.828 mg/kg\",\"StationNumber: 98LTB0223, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0244, Year: 1998, Value: 0.078 mg/kg\",\"StationNumber: 98LTB0273, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0307, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0364, Year: 1998, Value: 0.105 mg/kg\",\"StationNumber: 98LTB0393, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98LTB0762, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB1057, Year: 1998, Value: 0.673 mg/kg\",\"StationNumber: 98MR09, Year: 1998, Value: 0.125 mg/kg\",\"StationNumber: 98MR10, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR11, Year: 1998, Value: 0.99 mg/kg\",\"StationNumber: 98MR12, Year: 1998, Value: 0.198 mg/kg\",\"StationNumber: 98MR13, Year: 1998, Value: 1.029 mg/kg\",\"StationNumber: 98MR14, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR15, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR16, Year: 1998, Value: 0.352 mg/kg\",\"StationNumber: 98MR17, Year: 1998, Value: 0.36 mg/kg\",\"StationNumber: 98MR18, Year: 1998, Value: 0.322 mg/kg\",\"StationNumber: 98MR19, Year: 1998, Value: 0.176 mg/kg\",\"StationNumber: 98MR20, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR21, Year: 1998, Value: 2.438 mg/kg\",\"StationNumber: 98MTB0032, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0035, Year: 1998, Value: 0.482 mg/kg\",\"StationNumber: 98MTB0052, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0067, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98MTB0090, Year: 1998, Value: 0.747 mg/kg\",\"StationNumber: 98MTB0103, Year: 1998, Value: 0.073 mg/kg\",\"StationNumber: 98MTB0133, Year: 1998, Value: 0.164 mg/kg\",\"StationNumber: 98MTB0187, Year: 1998, Value: 1.46 mg/kg\",\"StationNumber: 98MTB0191, Year: 1998, Value: 0.192 mg/kg\",\"StationNumber: 98MTB0208, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0270, Year: 1998, Value: 0.016 mg/kg\",\"StationNumber: 98MTB0275, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0283, Year: 1998, Value: 0.376 mg/kg\",\"StationNumber: 98MTB0322, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0331, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0416, Year: 1998, Value: 3.312 mg/kg\",\"StationNumber: 98MTB0460, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0688, Year: 1998, Value: 0.769 mg/kg\",\"StationNumber: 98MTB0694, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB1036, Year: 1998, Value: 0.018 mg/kg\",\"StationNumber: 98OTB0036, Year: 1998, Value: 0.256 mg/kg\",\"StationNumber: 98OTB0039, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0048, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0056, Year: 1998, Value: 0.499 mg/kg\",\"StationNumber: 98OTB0125, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0177, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0185, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0199, Year: 1998, Value: 2.325 mg/kg\",\"StationNumber: 98OTB0232, Year: 1998, Value: 0.301 mg/kg\",\"StationNumber: 98OTB0239, Year: 1998, Value: 1.557 mg/kg\",\"StationNumber: 98OTB0274, Year: 1998, Value: 2.028 mg/kg\",\"StationNumber: 98OTB0425, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0596, Year: 1998, Value: 8.041 mg/kg\",\"StationNumber: 98OTB0721, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98OTB1140, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB1227, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB01, Year: 1998, Value: 1.816 mg/kg\",\"StationNumber: 98TCB02, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB04, Year: 1998, Value: 1.3 mg/kg\",\"StationNumber: 98TCB05, Year: 1998, Value: 0.903 mg/kg\",\"StationNumber: 98TCB06, Year: 1998, Value: 1.118 mg/kg\",\"StationNumber: 98TCB07, Year: 1998, Value: 0.966 mg/kg\",\"StationNumber: 98TCB08, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2025, Year: 1999, Value: 0.194 mg/kg\",\"StationNumber: 99BCB2041, Year: 1999, Value: 0.553 mg/kg\",\"StationNumber: 99BCB2063, Year: 1999, Value: 1.16 mg/kg\",\"StationNumber: 99BCB2069, Year: 1999, Value: 0.715 mg/kg\",\"StationNumber: 99BCB2070, Year: 1999, Value: 0.693 mg/kg\",\"StationNumber: 99BCB2086, Year: 1999, Value: 0.348 mg/kg\",\"StationNumber: 99BCB2094, Year: 1999, Value: 1.893 mg/kg\",\"StationNumber: 99BCB2115, Year: 1999, Value: 1.48 mg/kg\",\"StationNumber: 99BCB2132, Year: 1999, Value: 0.09 mg/kg\",\"StationNumber: 99BCB2295, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2358, Year: 1999, Value: 0.627 mg/kg\",\"StationNumber: 99BCB2423, Year: 1999, Value: 0.758 mg/kg\",\"StationNumber: 99BCB2514, Year: 1999, Value: 0.18 mg/kg\",\"StationNumber: 99BCB2585, Year: 1999, Value: 0.374 mg/kg\",\"StationNumber: 99BCB57/1, Year: 1999, Value: 3.215 mg/kg\",\"StationNumber: 99BCB58/1, Year: 1999, Value: 2.112 mg/kg\",\"StationNumber: 99BCB58/2, Year: 1999, Value: 1.224 mg/kg\",\"StationNumber: 99BCB59/1, Year: 1999, Value: 0.044 mg/kg\",\"StationNumber: 99BCB59/2, Year: 1999, Value: 0.787 mg/kg\",\"StationNumber: 99BCB60/2, Year: 1999, Value: 0.589 mg/kg\",\"StationNumber: 99BCB60/4, Year: 1999, Value: 1.162 mg/kg\",\"StationNumber: 99HB2001, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2012, Year: 1999, Value: 1.721 mg/kg\",\"StationNumber: 99HB2013, Year: 1999, Value: 0.197 mg/kg\",\"StationNumber: 99HB2019, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2040, Year: 1999, Value: 0.331 mg/kg\",\"StationNumber: 99HB2041, Year: 1999, Value: 0.988 mg/kg\",\"StationNumber: 99HB2043, Year: 1999, Value: 0.235 mg/kg\",\"StationNumber: 99HB2044, Year: 1999, Value: 0.82 mg/kg\",\"StationNumber: 99HB2051, Year: 1999, Value: 0.847 mg/kg\",\"StationNumber: 99HB2055, Year: 1999, Value: 1.08 mg/kg\",\"StationNumber: 99HB2058, Year: 1999, Value: 3.832 mg/kg\",\"StationNumber: 99HB2061, Year: 1999, Value: 5.185 mg/kg\",\"StationNumber: 99HB2085, Year: 1999, Value: 3.395 mg/kg\",\"StationNumber: 99HB2094, Year: 1999, Value: 0.205 mg/kg\",\"StationNumber: 99HB2124, Year: 1999, Value: 2.804 mg/kg\",\"StationNumber: 99HB2157, Year: 1999, Value: 0.252 mg/kg\",\"StationNumber: 99HB2176, Year: 1999, Value: 0.468 mg/kg\",\"StationNumber: 99HB2207, Year: 1999, Value: 2.127 mg/kg\",\"StationNumber: 99HB2214, Year: 1999, Value: 0.649 mg/kg\",\"StationNumber: 99HB2233, Year: 1999, Value: 2.896 mg/kg\",\"StationNumber: 99HB2393, Year: 1999, Value: 1.265 mg/kg\",\"StationNumber: 99HB2445, Year: 1999, Value: 1.072 mg/kg\",\"StationNumber: 99HB2757, Year: 1999, Value: 1.051 mg/kg\",\"StationNumber: 99LTB2014, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99LTB2021, Year: 1999, Value: 11.552 mg/kg\",\"StationNumber: 99LTB2041, Year: 1999, Value: 4.997 mg/kg\",\"StationNumber: 99LTB2071, Year: 1999, Value: 5.805 mg/kg\",\"StationNumber: 99LTB2112, Year: 1999, Value: 3.993 mg/kg\",\"StationNumber: 99LTB2124, Year: 1999, Value: 0.035 mg/kg\",\"StationNumber: 99LTB2203, Year: 1999, Value: 0.664 mg/kg\",\"StationNumber: 99LTB2214, Year: 1999, Value: 0.098 mg/kg\",\"StationNumber: 99LTB2247, Year: 1999, Value: 0.297 mg/kg\",\"StationNumber: 99LTB2267, Year: 1999, Value: 1.444 mg/kg\",\"StationNumber: 99LTB2277, Year: 1999, Value: 0.692 mg/kg\",\"StationNumber: 99LTB2290, Year: 1999, Value: 1.374 mg/kg\",\"StationNumber: 99LTB2327, Year: 1999, Value: 0.362 mg/kg\",\"StationNumber: 99LTB2546, Year: 1999, Value: 0.994 mg/kg\",\"StationNumber: 99LTB2617, Year: 1999, Value: 3.167 mg/kg\",\"StationNumber: 99LTB3020, Year: 1999, Value: 0.368 mg/kg\",\"StationNumber: 99MR09, Year: 1999, Value: 0.375 mg/kg\",\"StationNumber: 99MR10, Year: 1999, Value: 0.445 mg/kg\",\"StationNumber: 99MR11, Year: 1999, Value: 1.258 mg/kg\",\"StationNumber: 99MR12, Year: 1999, Value: 0.538 mg/kg\",\"StationNumber: 99MR13, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MR14, Year: 1999, Value: 0.402 mg/kg\",\"StationNumber: 99MR15, Year: 1999, Value: 0.668 mg/kg\",\"StationNumber: 99MR16, Year: 1999, Value: 0.087 mg/kg\",\"StationNumber: 99MR17, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR18, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR19, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR20, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR21, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2029, Year: 1999, Value: 1.088 mg/kg\",\"StationNumber: 99MTB2059, Year: 1999, Value: 0.528 mg/kg\",\"StationNumber: 99MTB2060, Year: 1999, Value: 0.709 mg/kg\",\"StationNumber: 99MTB2108, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MTB2109, Year: 1999, Value: 0.25 mg/kg\",\"StationNumber: 99MTB2116, Year: 1999, Value: 0.479 mg/kg\",\"StationNumber: 99MTB2129, Year: 1999, Value: 1.833 mg/kg\",\"StationNumber: 99MTB2149, Year: 1999, Value: 0.968 mg/kg\",\"StationNumber: 99MTB2165, Year: 1999, Value: 0.712 mg/kg\",\"StationNumber: 99MTB2240, Year: 1999, Value: 0.188 mg/kg\",\"StationNumber: 99MTB2243, Year: 1999, Value: 1.994 mg/kg\",\"StationNumber: 99MTB2244, Year: 1999, Value: 2.396 mg/kg\",\"StationNumber: 99MTB2253, Year: 1999, Value: 1.24 mg/kg\",\"StationNumber: 99MTB2268, Year: 1999, Value: 1.218 mg/kg\",\"StationNumber: 99MTB2274, Year: 1999, Value: 2.485 mg/kg\",\"StationNumber: 99MTB2291, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2358, Year: 1999, Value: 0.699 mg/kg\",\"StationNumber: 99MTB2385, Year: 1999, Value: 0.269 mg/kg\",\"StationNumber: 99MTB2554, Year: 1999, Value: 0.524 mg/kg\",\"StationNumber: 99MTB2598, Year: 1999, Value: 1.573 mg/kg\",\"StationNumber: 99MTB2642, Year: 1999, Value: 0.016 mg/kg\",\"StationNumber: 99OTB2002, Year: 1999, Value: 0.452 mg/kg\",\"StationNumber: 99OTB2005, Year: 1999, Value: 0.022 mg/kg\",\"StationNumber: 99OTB2009, Year: 1999, Value: 0.41 mg/kg\",\"StationNumber: 99OTB2010, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2022, Year: 1999, Value: 0.836 mg/kg\",\"StationNumber: 99OTB2045, Year: 1999, Value: 0.166 mg/kg\",\"StationNumber: 99OTB2067, Year: 1999, Value: 0.055 mg/kg\",\"StationNumber: 99OTB2111, Year: 1999, Value: 0.071 mg/kg\",\"StationNumber: 99OTB2121, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2225, Year: 1999, Value: 0.203 mg/kg\",\"StationNumber: 99OTB2296, Year: 1999, Value: 0.839 mg/kg\",\"StationNumber: 99OTB2313, Year: 1999, Value: 0.875 mg/kg\",\"StationNumber: 99OTB2316, Year: 1999, Value: 1.126 mg/kg\",\"StationNumber: 99OTB2331, Year: 1999, Value: 0.353 mg/kg\",\"StationNumber: 99OTB2395, Year: 1999, Value: 0.233 mg/kg\",\"StationNumber: 99OTB2482, Year: 1999, Value: 1.236 mg/kg\",\"StationNumber: 99OTB2908, Year: 1999, Value: 0.307 mg/kg\",\"StationNumber: 99OTB2994, Year: 1999, Value: 0.038 mg/kg\",\"StationNumber: 99OTB3046, Year: 1999, Value: 0.397 mg/kg\",\"StationNumber: 99TCB01, Year: 1999, Value: 1.95 mg/kg\",\"StationNumber: 99TCB02, Year: 1999, Value: 0.225 mg/kg\",\"StationNumber: 99TCB03, Year: 1999, Value: 4.578 mg/kg\",\"StationNumber: 99TCB04, Year: 1999, Value: 2.024 mg/kg\",\"StationNumber: 99TCB05, Year: 1999, Value: 1.134 mg/kg\",\"StationNumber: 99TCB06, Year: 1999, Value: 1.082 mg/kg\",\"StationNumber: 99TCB07, Year: 1999, Value: 1.652 mg/kg\",\"StationNumber: 99TCB08, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 00BCB4000, Year: 2000, Value: 7.05 mg/kg\",\"StationNumber: 00BCB4001, Year: 2000, Value: 8.917 mg/kg\",\"StationNumber: 00BCB4004, Year: 2000, Value: 5.717 mg/kg\",\"StationNumber: 00BCB4033, Year: 2000, Value: 6.44 mg/kg\",\"StationNumber: 00BCB4034, Year: 2000, Value: 6.595 mg/kg\",\"StationNumber: 00BCB4037, Year: 2000, Value: 5.573 mg/kg\",\"StationNumber: 00BCB4038, Year: 2000, Value: 7.398 mg/kg\",\"StationNumber: 00BCB4041, Year: 2000, Value: 8.081 mg/kg\",\"StationNumber: 00BCB4042, Year: 2000, Value: 8.315 mg/kg\",\"StationNumber: 00BCB4046, Year: 2000, Value: 7.3 mg/kg\",\"StationNumber: 00BCB4079, Year: 2000, Value: 5.898 mg/kg\",\"StationNumber: 00BCB4084, Year: 2000, Value: 6.968 mg/kg\",\"StationNumber: 00BCB4090, Year: 2000, Value: 8.108 mg/kg\",\"StationNumber: 00BCB4100, Year: 2000, Value: 7.966 mg/kg\",\"StationNumber: 00BCB4124, Year: 2000, Value: 5.814 mg/kg\",\"StationNumber: 00BCB4165, Year: 2000, Value: 5.405 mg/kg\",\"StationNumber: 00BCB4174, Year: 2000, Value: 8.747 mg/kg\",\"StationNumber: 00BCB4207, Year: 2000, Value: 7.704 mg/kg\",\"StationNumber: 00BCB4268, Year: 2000, Value: 7.855 mg/kg\",\"StationNumber: 00BCB4299, Year: 2000, Value: 8.06 mg/kg\",\"StationNumber: 00BCB4312, Year: 2000, Value: 8.316 mg/kg\",\"StationNumber: 00BCB58/1, Year: 2000, Value: 5.498 mg/kg\",\"StationNumber: 00BCB58/2, Year: 2000, Value: 4.644 mg/kg\",\"StationNumber: 00BCB59/1, Year: 2000, Value: 6.148 mg/kg\",\"StationNumber: 00BCB59/2, Year: 2000, Value: 5.036 mg/kg\",\"StationNumber: 00BCB60/2, Year: 2000, Value: 5.003 mg/kg\",\"StationNumber: 00BCB60/4, Year: 2000, Value: 4.842 mg/kg\",\"StationNumber: 00HB4002, Year: 2000, Value: 5.886 mg/kg\",\"StationNumber: 00HB4006, Year: 2000, Value: 6.219 mg/kg\",\"StationNumber: 00HB4019, Year: 2000, Value: 3.684 mg/kg\",\"StationNumber: 00HB4023, Year: 2000, Value: 5.729 mg/kg\",\"StationNumber: 00HB4032, Year: 2000, Value: 5.767 mg/kg\",\"StationNumber: 00HB4033, Year: 2000, Value: 4.768 mg/kg\",\"StationNumber: 00HB4038, Year: 2000, Value: 6.182 mg/kg\",\"StationNumber: 00HB4047, Year: 2000, Value: 5.84 mg/kg\",\"StationNumber: 00HB4058, Year: 2000, Value: 3.097 mg/kg\",\"StationNumber: 00HB4077, Year: 2000, Value: 6.608 mg/kg\",\"StationNumber: 00HB4082, Year: 2000, Value: 6.717 mg/kg\",\"StationNumber: 00HB4083, Year: 2000, Value: 7.399 mg/kg\",\"StationNumber: 00HB4093, Year: 2000, Value: 1.936 mg/kg\",\"StationNumber: 00HB4094, Year: 2000, Value: 2.189 mg/kg\",\"StationNumber: 00HB4100, Year: 2000, Value: 4.324 mg/kg\",\"StationNumber: 00HB4106, Year: 2000, Value: 2.128 mg/kg\",\"StationNumber: 00HB4144, Year: 2000, Value: 1.909 mg/kg\",\"StationNumber: 00HB4152, Year: 2000, Value: 7.008 mg/kg\",\"StationNumber: 00HB4267, Year: 2000, Value: 4.486 mg/kg\",\"StationNumber: 00HB4291, Year: 2000, Value: 4.846 mg/kg\",\"StationNumber: 00HB4316, Year: 2000, Value: 6.769 mg/kg\",\"StationNumber: 00HB4505, Year: 2000, Value: 4.805 mg/kg\",\"StationNumber: 00LTB4039, Year: 2000, Value: 2.434 mg/kg\",\"StationNumber: 00LTB4051, Year: 2000, Value: 4.039 mg/kg\",\"StationNumber: 00LTB4066, Year: 2000, Value: 1.702 mg/kg\",\"StationNumber: 00LTB4117, Year: 2000, Value: 3.904 mg/kg\",\"StationNumber: 00LTB4151, Year: 2000, Value: 5.587 mg/kg\",\"StationNumber: 00LTB4185, Year: 2000, Value: 3.635 mg/kg\",\"StationNumber: 00LTB4286, Year: 2000, Value: 5.878 mg/kg\",\"StationNumber: 00LTB4340, Year: 2000, Value: 2.792 mg/kg\",\"StationNumber: 00LTB4484, Year: 2000, Value: 2.7 mg/kg\",\"StationNumber: 00LTB4487, Year: 2000, Value: 1.721 mg/kg\",\"StationNumber: 00LTB4513, Year: 2000, Value: 1.915 mg/kg\",\"StationNumber: 00LTB4529, Year: 2000, Value: 5.51 mg/kg\",\"StationNumber: 00LTB4536, Year: 2000, Value: 6.17 mg/kg\",\"StationNumber: 00LTB4637, Year: 2000, Value: 9.27 mg/kg\",\"StationNumber: 00LTB4677, Year: 2000, Value: 1.76 mg/kg\",\"StationNumber: 00LTB4730, Year: 2000, Value: 9.63 mg/kg\",\"StationNumber: 00LTB4749, Year: 2000, Value: 1.727 mg/kg\",\"StationNumber: 00MR09, Year: 2000, Value: 7.262 mg/kg\",\"StationNumber: 00MR10, Year: 2000, Value: 7.28 mg/kg\",\"StationNumber: 00MR11, Year: 2000, Value: 7.022 mg/kg\",\"StationNumber: 00MR12, Year: 2000, Value: 6.682 mg/kg\",\"StationNumber: 00MR13, Year: 2000, Value: 6.746 mg/kg\",\"StationNumber: 00MR14, Year: 2000, Value: 5.791 mg/kg\",\"StationNumber: 00MR15, Year: 2000, Value: 5.559 mg/kg\",\"StationNumber: 00MR16, Year: 2000, Value: 4.961 mg/kg\",\"StationNumber: 00MR17, Year: 2000, Value: 5.02 mg/kg\",\"StationNumber: 00MR18, Year: 2000, Value: 5.104 mg/kg\",\"StationNumber: 00MR19, Year: 2000, Value: 7.434 mg/kg\",\"StationNumber: 00MR20, Year: 2000, Value: 2.837 mg/kg\",\"StationNumber: 00MR21, Year: 2000, Value: 4.022 mg/kg\",\"StationNumber: 00MTB4030, Year: 2000, Value: 4.501 mg/kg\",\"StationNumber: 00MTB4032, Year: 2000, Value: 8.919 mg/kg\",\"StationNumber: 00MTB4041, Year: 2000, Value: 2.068 mg/kg\",\"StationNumber: 00MTB4061, Year: 2000, Value: 2.284 mg/kg\",\"StationNumber: 00MTB4072, Year: 2000, Value: 1.826 mg/kg\",\"StationNumber: 00MTB4086, Year: 2000, Value: 1.935 mg/kg\",\"StationNumber: 00MTB4090, Year: 2000, Value: 9.376 mg/kg\",\"StationNumber: 00MTB4098, Year: 2000, Value: 19.11 mg/kg\",\"StationNumber: 00MTB4100, Year: 2000, Value: 5.523 mg/kg\",\"StationNumber: 00MTB4106, Year: 2000, Value: 2.373 mg/kg\",\"StationNumber: 00MTB4159, Year: 2000, Value: 2.926 mg/kg\",\"StationNumber: 00MTB4181, Year: 2000, Value: 5.332 mg/kg\",\"StationNumber: 00MTB4193, Year: 2000, Value: 2.564 mg/kg\",\"StationNumber: 00MTB4201, Year: 2000, Value: 5.145 mg/kg\",\"StationNumber: 00MTB4249, Year: 2000, Value: 5.123 mg/kg\",\"StationNumber: 00MTB4265, Year: 2000, Value: 18.11 mg/kg\",\"StationNumber: 00MTB4310, Year: 2000, Value: 4.749 mg/kg\",\"StationNumber: 00MTB4363, Year: 2000, Value: 5.988 mg/kg\",\"StationNumber: 00MTB4504, Year: 2000, Value: 1.819 mg/kg\",\"StationNumber: 00MTB4584, Year: 2000, Value: 4.649 mg/kg\",\"StationNumber: 00MTB4653, Year: 2000, Value: 6.862 mg/kg\",\"StationNumber: 00MTB4845, Year: 2000, Value: 6.98 mg/kg\",\"StationNumber: 00MTB5125, Year: 2000, Value: 6.297 mg/kg\",\"StationNumber: 00OTB4011, Year: 2000, Value: 6.398 mg/kg\",\"StationNumber: 00OTB4019, Year: 2000, Value: 5.242 mg/kg\",\"StationNumber: 00OTB4037, Year: 2000, Value: 5.554 mg/kg\",\"StationNumber: 00OTB4040, Year: 2000, Value: 6.998 mg/kg\",\"StationNumber: 00OTB4044, Year: 2000, Value: 6.455 mg/kg\",\"StationNumber: 00OTB4096, Year: 2000, Value: 6.509 mg/kg\",\"StationNumber: 00OTB4105, Year: 2000, Value: 4.904 mg/kg\",\"StationNumber: 00OTB4123, Year: 2000, Value: 6.756 mg/kg\",\"StationNumber: 00OTB4132, Year: 2000, Value: 4.869 mg/kg\",\"StationNumber: 00OTB4138, Year: 2000, Value: 5.793 mg/kg\",\"StationNumber: 00OTB4149, Year: 2000, Value: 6.974 mg/kg\",\"StationNumber: 00OTB4192, Year: 2000, Value: 4.798 mg/kg\",\"StationNumber: 00OTB4217, Year: 2000, Value: 6.639 mg/kg\",\"StationNumber: 00OTB4254, Year: 2000, Value: 8.763 mg/kg\",\"StationNumber: 00OTB4278, Year: 2000, Value: 2.048 mg/kg\",\"StationNumber: 00OTB4402, Year: 2000, Value: 7.662 mg/kg\",\"StationNumber: 00OTB4407, Year: 2000, Value: 8.601 mg/kg\",\"StationNumber: 00OTB4650, Year: 2000, Value: 8.558 mg/kg\",\"StationNumber: 00OTB4946, Year: 2000, Value: 7.083 mg/kg\",\"StationNumber: 00TCB01, Year: 2000, Value: 5.933 mg/kg\",\"StationNumber: 00TCB02, Year: 2000, Value: 3.519 mg/kg\",\"StationNumber: 00TCB03, Year: 2000, Value: 9.862 mg/kg\",\"StationNumber: 00TCB04, Year: 2000, Value: 4.401 mg/kg\",\"StationNumber: 00TCB05, Year: 2000, Value: 6.928 mg/kg\",\"StationNumber: 00TCB06, Year: 2000, Value: 6.186 mg/kg\",\"StationNumber: 00TCB07, Year: 2000, Value: 6.023 mg/kg\",\"StationNumber: 00TCB08, Year: 2000, Value: 5.912 mg/kg\",\"StationNumber: 01BCB57/1, Year: 2001, Value: 2.985 mg/kg\",\"StationNumber: 01BCB58/1, Year: 2001, Value: 4.108 mg/kg\",\"StationNumber: 01BCB58/2, Year: 2001, Value: 4.081 mg/kg\",\"StationNumber: 01BCB59/1, Year: 2001, Value: 2.709 mg/kg\",\"StationNumber: 01BCB59/2, Year: 2001, Value: 2.059 mg/kg\",\"StationNumber: 01BCB60/2, Year: 2001, Value: 3.449 mg/kg\",\"StationNumber: 01BCB60/4, Year: 2001, Value: 0.432 mg/kg\",\"StationNumber: 01BCB6001, Year: 2001, Value: 4.072 mg/kg\",\"StationNumber: 01BCB6009, Year: 2001, Value: 3.178 mg/kg\",\"StationNumber: 01BCB6018, Year: 2001, Value: 2.845 mg/kg\",\"StationNumber: 01BCB6019, Year: 2001, Value: 3.296 mg/kg\",\"StationNumber: 01BCB6031, Year: 2001, Value: 3.409 mg/kg\",\"StationNumber: 01BCB6063, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01BCB6072, Year: 2001, Value: 3.246 mg/kg\",\"StationNumber: 01BCB6089, Year: 2001, Value: 2.207 mg/kg\",\"StationNumber: 01BCB6109, Year: 2001, Value: 2.415 mg/kg\",\"StationNumber: 01BCB6114, Year: 2001, Value: 2.628 mg/kg\",\"StationNumber: 01BCB6152, Year: 2001, Value: 2.854 mg/kg\",\"StationNumber: 01BCB6178, Year: 2001, Value: 2.596 mg/kg\",\"StationNumber: 01BCB6190, Year: 2001, Value: 2.145 mg/kg\",\"StationNumber: 01BCB6230, Year: 2001, Value: 3.755 mg/kg\",\"StationNumber: 01BCB6263, Year: 2001, Value: 1.707 mg/kg\",\"StationNumber: 01BCB6359, Year: 2001, Value: 1.433 mg/kg\",\"StationNumber: 01HB6019, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6022, Year: 2001, Value: 1.909 mg/kg\",\"StationNumber: 01HB6032, Year: 2001, Value: 2.588 mg/kg\",\"StationNumber: 01HB6035, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6045, Year: 2001, Value: 0.325 mg/kg\",\"StationNumber: 01HB6064, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6066, Year: 2001, Value: 1.155 mg/kg\",\"StationNumber: 01HB6087, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6093, Year: 2001, Value: 2.265 mg/kg\",\"StationNumber: 01HB6102, Year: 2001, Value: 2.313 mg/kg\",\"StationNumber: 01HB6108, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6131, Year: 2001, Value: 0.71 mg/kg\",\"StationNumber: 01HB6140, Year: 2001, Value: 2.982 mg/kg\",\"StationNumber: 01HB6145, Year: 2001, Value: 2.677 mg/kg\",\"StationNumber: 01HB6159, Year: 2001, Value: 2.869 mg/kg\",\"StationNumber: 01HB6186, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6187, Year: 2001, Value: 3.434 mg/kg\",\"StationNumber: 01HB6249, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6261, Year: 2001, Value: 3.626 mg/kg\",\"StationNumber: 01HB6264, Year: 2001, Value: 1.742 mg/kg\",\"StationNumber: 01HB6283, Year: 2001, Value: 1.357 mg/kg\",\"StationNumber: 01HB6305, Year: 2001, Value: 2.006 mg/kg\",\"StationNumber: 01HB6374, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6453, Year: 2001, Value: 2.977 mg/kg\",\"StationNumber: 01HB6537, Year: 2001, Value: 3.517 mg/kg\",\"StationNumber: 01LTB6026, Year: 2001, Value: 14.165 mg/kg\",\"StationNumber: 01LTB6027, Year: 2001, Value: 1.328 mg/kg\",\"StationNumber: 01LTB6050, Year: 2001, Value: 0.606 mg/kg\",\"StationNumber: 01LTB6104, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6120, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6122, Year: 2001, Value: 0.66 mg/kg\",\"StationNumber: 01LTB6158, Year: 2001, Value: 5.092 mg/kg\",\"StationNumber: 01LTB6302, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6346, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01LTB6380, Year: 2001, Value: 0.874 mg/kg\",\"StationNumber: 01LTB6595, Year: 2001, Value: 3.852 mg/kg\",\"StationNumber: 01LTB6869, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MR09, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR12, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR13, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR14, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR17, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR18, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR19, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR20, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR21, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MTB6002, Year: 2001, Value: 0.981 mg/kg\",\"StationNumber: 01MTB6011, Year: 2001, Value: 0.416 mg/kg\",\"StationNumber: 01MTB6014, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MTB6049, Year: 2001, Value: 0.168 mg/kg\",\"StationNumber: 01MTB6059, Year: 2001, Value: 5.14 mg/kg\",\"StationNumber: 01MTB6064, Year: 2001, Value: 3.241 mg/kg\",\"StationNumber: 01MTB6068, Year: 2001, Value: 5.837 mg/kg\",\"StationNumber: 01MTB6080, Year: 2001, Value: 3.556 mg/kg\",\"StationNumber: 01MTB6133, Year: 2001, Value: 2.453 mg/kg\",\"StationNumber: 01MTB6154, Year: 2001, Value: 0.963 mg/kg\",\"StationNumber: 01MTB6188, Year: 2001, Value: 0.797 mg/kg\",\"StationNumber: 01MTB6189, Year: 2001, Value: 2.868 mg/kg\",\"StationNumber: 01MTB6196, Year: 2001, Value: 2.703 mg/kg\",\"StationNumber: 01MTB6229, Year: 2001, Value: 2.698 mg/kg\",\"StationNumber: 01MTB6257, Year: 2001, Value: 0.988 mg/kg\",\"StationNumber: 01MTB6265, Year: 2001, Value: 4.324 mg/kg\",\"StationNumber: 01MTB6290, Year: 2001, Value: 3.339 mg/kg\",\"StationNumber: 01MTB6325, Year: 2001, Value: 2.765 mg/kg\",\"StationNumber: 01MTB6327, Year: 2001, Value: 4.862 mg/kg\",\"StationNumber: 01MTB6328, Year: 2001, Value: 3.179 mg/kg\",\"StationNumber: 01MTB6464, Year: 2001, Value: 3.707 mg/kg\",\"StationNumber: 01MTB6495, Year: 2001, Value: 3.297 mg/kg\",\"StationNumber: 01MTB6527, Year: 2001, Value: 3.538 mg/kg\",\"StationNumber: 01MTB6638, Year: 2001, Value: 4.338 mg/kg\",\"StationNumber: 01MTB6699, Year: 2001, Value: 4.171 mg/kg\",\"StationNumber: 01MTB7153, Year: 2001, Value: 3.938 mg/kg\",\"StationNumber: 01OTB6010, Year: 2001, Value: 3.892 mg/kg\",\"StationNumber: 01OTB6017, Year: 2001, Value: 3.183 mg/kg\",\"StationNumber: 01OTB6021, Year: 2001, Value: 2.793 mg/kg\",\"StationNumber: 01OTB6022, Year: 2001, Value: 1.206 mg/kg\",\"StationNumber: 01OTB6025, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6028, Year: 2001, Value: 5.384 mg/kg\",\"StationNumber: 01OTB6078, Year: 2001, Value: 3.845 mg/kg\",\"StationNumber: 01OTB6103, Year: 2001, Value: 5.634 mg/kg\",\"StationNumber: 01OTB6135, Year: 2001, Value: 2.772 mg/kg\",\"StationNumber: 01OTB6152, Year: 2001, Value: 28.868 mg/kg\",\"StationNumber: 01OTB6178, Year: 2001, Value: 9.713 mg/kg\",\"StationNumber: 01OTB6186, Year: 2001, Value: 5.55 mg/kg\",\"StationNumber: 01OTB6234, Year: 2001, Value: 5.199 mg/kg\",\"StationNumber: 01OTB6239, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6441, Year: 2001, Value: 5.652 mg/kg\",\"StationNumber: 01OTB6784, Year: 2001, Value: 10.207 mg/kg\",\"StationNumber: 01OTB6830, Year: 2001, Value: 5.184 mg/kg\",\"StationNumber: 01SAFHAB, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01TCB02, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB03, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB04, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB06, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB07, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 02BCB05, Year: 2002, Value: 5.202 mg/kg\",\"StationNumber: 02BCB20, Year: 2002, Value: 1.257 mg/kg\",\"StationNumber: 02BCB32, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB52, Year: 2002, Value: 0.407 mg/kg\",\"StationNumber: 02BCB62, Year: 2002, Value: 3.401 mg/kg\",\"StationNumber: 02BCB69, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB74, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB83, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB90, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-1, Year: 2002, Value: 0.426 mg/kg\",\"StationNumber: 02DH07-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH09-1, Year: 2002, Value: 2.957 mg/kg\",\"StationNumber: 02DH09-2, Year: 2002, Value: 1.154 mg/kg\",\"StationNumber: 02DH09-3, Year: 2002, Value: 3.812 mg/kg\",\"StationNumber: 02DH11A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH14-1, Year: 2002, Value: 1.74 mg/kg\",\"StationNumber: 02DH14-3, Year: 2002, Value: 1.197 mg/kg\",\"StationNumber: 02DH14-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-3, Year: 2002, Value: 0.146 mg/kg\",\"StationNumber: 02DH20-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-3, Year: 2002, Value: 0.323 mg/kg\",\"StationNumber: 02DH21B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB20, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB21, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB39, Year: 2002, Value: 0.328 mg/kg\",\"StationNumber: 02HB42, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB51, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB55, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB01, Year: 2002, Value: 3.105 mg/kg\",\"StationNumber: 02LTB02, Year: 2002, Value: 4.432 mg/kg\",\"StationNumber: 02LTB03, Year: 2002, Value: 0.925 mg/kg\",\"StationNumber: 02LTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB06, Year: 2002, Value: 0.657 mg/kg\",\"StationNumber: 02LTB07, Year: 2002, Value: 0.376 mg/kg\",\"StationNumber: 02LTB08, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR06, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR08, Year: 2002, Value: 0.022 mg/kg\",\"StationNumber: 02MR10, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR11, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB11, Year: 2002, Value: 0.563 mg/kg\",\"StationNumber: 02MTB12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB18, Year: 2002, Value: 1.634 mg/kg\",\"StationNumber: 02MTB19, Year: 2002, Value: 6.859 mg/kg\",\"StationNumber: 02MTB21, Year: 2002, Value: 0.379 mg/kg\",\"StationNumber: 02MTB23, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB29, Year: 2002, Value: 4.363 mg/kg\",\"StationNumber: 02MTB32, Year: 2002, Value: 0.595 mg/kg\",\"StationNumber: 02MTB34, Year: 2002, Value: 0.126 mg/kg\",\"StationNumber: 02OTB02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB52, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB60, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB66, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB03, Year: 2002, Value: 1.409 mg/kg\",\"StationNumber: 02TCB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB07, Year: 2002, Value: 3.347 mg/kg\",\"StationNumber: 02TCB09, Year: 2002, Value: 0.612 mg/kg\",\"StationNumber: 03BCB107, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB120, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB126, Year: 2003, Value: 0.086 mg/kg\",\"StationNumber: 03BCB190, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB230, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB242, Year: 2003, Value: 2.439 mg/kg\",\"StationNumber: 03BCB278, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB287, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB338, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB439, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB02, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB09, Year: 2003, Value: 5.878 mg/kg\",\"StationNumber: 03HB10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB12, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB14, Year: 2003, Value: 0.176 mg/kg\",\"StationNumber: 03HB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB18, Year: 2003, Value: 1.028 mg/kg\",\"StationNumber: 03HB21, Year: 2003, Value: 3.834 mg/kg\",\"StationNumber: 03HB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB37, Year: 2003, Value: 0.988 mg/kg\",\"StationNumber: 03HB38, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB41, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB42, Year: 2003, Value: 1.908 mg/kg\",\"StationNumber: 03HB44, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB47, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB50, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB51, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB52, Year: 2003, Value: 3.438 mg/kg\",\"StationNumber: 03HB53, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB02, Year: 2003, Value: 7.824 mg/kg\",\"StationNumber: 03LTB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB05, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB08, Year: 2003, Value: 1.746 mg/kg\",\"StationNumber: 03LTB09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB10, Year: 2003, Value: 3.726 mg/kg\",\"StationNumber: 03LTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB12, Year: 2003, Value: 5.634 mg/kg\",\"StationNumber: 03MR02, Year: 2003, Value: 0.283 mg/kg\",\"StationNumber: 03MR04, Year: 2003, Value: 0.17 mg/kg\",\"StationNumber: 03MR06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR08, Year: 2003, Value: 0.608 mg/kg\",\"StationNumber: 03MR09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB03, Year: 2003, Value: 1.161 mg/kg\",\"StationNumber: 03MTB08, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB10, Year: 2003, Value: 1.265 mg/kg\",\"StationNumber: 03MTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB13, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB14, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB15, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB17, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB18, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB19, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB21, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB24, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB25, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB31, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB35, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB157, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB200, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB413, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB414, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB507, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB623, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB706, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB794, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB929, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB05, Year: 2003, Value: 3.05 mg/kg\",\"StationNumber: 04BCB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB03, Year: 2004, Value: 2.501 mg/kg\",\"StationNumber: 04BCB04, Year: 2004, Value: 0.51 mg/kg\",\"StationNumber: 04BCB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB06, Year: 2004, Value: 0.839 mg/kg\",\"StationNumber: 04BCB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB10, Year: 2004, Value: 2.332 mg/kg\",\"StationNumber: 04HB01, Year: 2004, Value: 0.523 mg/kg\",\"StationNumber: 04HB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB03, Year: 2004, Value: 0.552 mg/kg\",\"StationNumber: 04HB04, Year: 2004, Value: 1.214 mg/kg\",\"StationNumber: 04HB05, Year: 2004, Value: 0.346 mg/kg\",\"StationNumber: 04HB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB07, Year: 2004, Value: 1.338 mg/kg\",\"StationNumber: 04HB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB10, Year: 2004, Value: 2.967 mg/kg\",\"StationNumber: 04HB11, Year: 2004, Value: 0.026 mg/kg\",\"StationNumber: 04HB12, Year: 2004, Value: 0.348 mg/kg\",\"StationNumber: 04HB13, Year: 2004, Value: 0.431 mg/kg\",\"StationNumber: 04HB14, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB15, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB16, Year: 2004, Value: 0.477 mg/kg\",\"StationNumber: 04HB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB18, Year: 2004, Value: 2.08 mg/kg\",\"StationNumber: 04HB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB20, Year: 2004, Value: 0.117 mg/kg\",\"StationNumber: 04HB21, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB23, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB24, Year: 2004, Value: 0.37 mg/kg\",\"StationNumber: 04HB25, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB26, Year: 2004, Value: 0.004 mg/kg\",\"StationNumber: 04LTB01, Year: 2004, Value: 3.535 mg/kg\",\"StationNumber: 04LTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB03, Year: 2004, Value: 0.715 mg/kg\",\"StationNumber: 04LTB04, Year: 2004, Value: 2.723 mg/kg\",\"StationNumber: 04LTB05, Year: 2004, Value: 0.562 mg/kg\",\"StationNumber: 04LTB06, Year: 2004, Value: 3.492 mg/kg\",\"StationNumber: 04LTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB08, Year: 2004, Value: 4.848 mg/kg\",\"StationNumber: 04LTB09, Year: 2004, Value: 0.25 mg/kg\",\"StationNumber: 04LTB10, Year: 2004, Value: 1.579 mg/kg\",\"StationNumber: 04LTB11, Year: 2004, Value: 1.156 mg/kg\",\"StationNumber: 04MR01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR10, Year: 2004, Value: 0.32 mg/kg\",\"StationNumber: 04MR11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB01, Year: 2004, Value: 2.748 mg/kg\",\"StationNumber: 04MTB02, Year: 2004, Value: 2.306 mg/kg\",\"StationNumber: 04MTB04, Year: 2004, Value: 0.557 mg/kg\",\"StationNumber: 04MTB05, Year: 2004, Value: 1.049 mg/kg\",\"StationNumber: 04MTB06, Year: 2004, Value: 1.363 mg/kg\",\"StationNumber: 04MTB07, Year: 2004, Value: 0.169 mg/kg\",\"StationNumber: 04MTB08, Year: 2004, Value: 0.219 mg/kg\",\"StationNumber: 04MTB09, Year: 2004, Value: 1.226 mg/kg\",\"StationNumber: 04MTB10, Year: 2004, Value: 1.518 mg/kg\",\"StationNumber: 04MTB11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB12, Year: 2004, Value: 1.075 mg/kg\",\"StationNumber: 04MTB13, Year: 2004, Value: 0.444 mg/kg\",\"StationNumber: 04MTB14, Year: 2004, Value: 0.936 mg/kg\",\"StationNumber: 04MTB15, Year: 2004, Value: 0.83 mg/kg\",\"StationNumber: 04MTB16, Year: 2004, Value: 1.378 mg/kg\",\"StationNumber: 04MTB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB18, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB20, Year: 2004, Value: 0.469 mg/kg\",\"StationNumber: 04MTB21, Year: 2004, Value: 16.571 mg/kg\",\"StationNumber: 04MTB22, Year: 2004, Value: 0.19 mg/kg\",\"StationNumber: 04MTB24, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04TCB07, Year: 2004, Value: 1.789 mg/kg\",\"StationNumber: 05BCB01, Year: 2005, Value: 0.505 mg/kg\",\"StationNumber: 05BCB02, Year: 2005, Value: 0.245 mg/kg\",\"StationNumber: 05BCB03, Year: 2005, Value: 0.638 mg/kg\",\"StationNumber: 05BCB04, Year: 2005, Value: 0.791 mg/kg\",\"StationNumber: 05BCB05, Year: 2005, Value: 6.022 mg/kg\",\"StationNumber: 05BCB06, Year: 2005, Value: 2.432 mg/kg\",\"StationNumber: 05BCB07, Year: 2005, Value: 0.357 mg/kg\",\"StationNumber: 05BCB08, Year: 2005, Value: 1.489 mg/kg\",\"StationNumber: 05BCB09, Year: 2005, Value: 0.987 mg/kg\",\"StationNumber: 05BCB10, Year: 2005, Value: 0.021 mg/kg\",\"StationNumber: 05HB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB06, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB07, Year: 2005, Value: 0.733 mg/kg\",\"StationNumber: 05HB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB10, Year: 2005, Value: 0.598 mg/kg\",\"StationNumber: 05HB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB12, Year: 2005, Value: 3.811 mg/kg\",\"StationNumber: 05HB13, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB14, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB16, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB17, Year: 2005, Value: 0.036 mg/kg\",\"StationNumber: 05HB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB19, Year: 2005, Value: 0.322 mg/kg\",\"StationNumber: 05HB20, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB21, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB22, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB23, Year: 2005, Value: 0.616 mg/kg\",\"StationNumber: 05HB24, Year: 2005, Value: 2.172 mg/kg\",\"StationNumber: 05LTB01, Year: 2005, Value: 5.537 mg/kg\",\"StationNumber: 05LTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05LTB03, Year: 2005, Value: 2.554 mg/kg\",\"StationNumber: 05LTB04, Year: 2005, Value: 2.548 mg/kg\",\"StationNumber: 05LTB05, Year: 2005, Value: 1.008 mg/kg\",\"StationNumber: 05LTB06, Year: 2005, Value: 2.134 mg/kg\",\"StationNumber: 05LTB07, Year: 2005, Value: 3.24 mg/kg\",\"StationNumber: 05LTB08, Year: 2005, Value: 2.144 mg/kg\",\"StationNumber: 05LTB09, Year: 2005, Value: 4.455 mg/kg\",\"StationNumber: 05LTB10, Year: 2005, Value: 0.116 mg/kg\",\"StationNumber: 05LTB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR06, Year: 2005, Value: 1.085 mg/kg\",\"StationNumber: 05MR08, Year: 2005, Value: 0.372 mg/kg\",\"StationNumber: 05MR09, Year: 2005, Value: 0.97 mg/kg\",\"StationNumber: 05MR11, Year: 2005, Value: 0.271 mg/kg\",\"StationNumber: 05MTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB06, Year: 2005, Value: 0.691 mg/kg\",\"StationNumber: 05MTB07, Year: 2005, Value: 0.685 mg/kg\",\"StationNumber: 05MTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB10, Year: 2005, Value: 0.871 mg/kg\",\"StationNumber: 05MTB11, Year: 2005, Value: 0.609 mg/kg\",\"StationNumber: 05MTB12, Year: 2005, Value: 0.585 mg/kg\",\"StationNumber: 05MTB13, Year: 2005, Value: 1.943 mg/kg\",\"StationNumber: 05MTB14, Year: 2005, Value: 8.527 mg/kg\",\"StationNumber: 05MTB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB16, Year: 2005, Value: 0.45 mg/kg\",\"StationNumber: 05MTB17, Year: 2005, Value: 0.043 mg/kg\",\"StationNumber: 05MTB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB19, Year: 2005, Value: 0.177 mg/kg\",\"StationNumber: 05MTB20, Year: 2005, Value: 2.689 mg/kg\",\"StationNumber: 05MTB21, Year: 2005, Value: 0.156 mg/kg\",\"StationNumber: 05MTB22, Year: 2005, Value: 0.31 mg/kg\",\"StationNumber: 05OTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB02, Year: 2005, Value: 0.308 mg/kg\",\"StationNumber: 05OTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB04, Year: 2005, Value: 0.154 mg/kg\",\"StationNumber: 05OTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB06, Year: 2005, Value: 0.727 mg/kg\",\"StationNumber: 05OTB07, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB10, Year: 2005, Value: 0.348 mg/kg\",\"StationNumber: 05TCB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05TCB03, Year: 2005, Value: 1.689 mg/kg\",\"StationNumber: 05TCB05, Year: 2005, Value: 1.313 mg/kg\",\"StationNumber: 05TCB07, Year: 2005, Value: 0.98 mg/kg\",\"StationNumber: 05TCB10, Year: 2005, Value: 2.404 mg/kg\",\"StationNumber: 06BCB01, Year: 2006, Value: 10.76 mg/kg\",\"StationNumber: 06BCB02, Year: 2006, Value: 7.6 mg/kg\",\"StationNumber: 06BCB03, Year: 2006, Value: 6.966 mg/kg\",\"StationNumber: 06BCB04, Year: 2006, Value: 6.49 mg/kg\",\"StationNumber: 06BCB05, Year: 2006, Value: 1.041 mg/kg\",\"StationNumber: 06BCB06, Year: 2006, Value: 5.932 mg/kg\",\"StationNumber: 06BCB07, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06BCB08, Year: 2006, Value: 2.144 mg/kg\",\"StationNumber: 06BCB09, Year: 2006, Value: 6.173 mg/kg\",\"StationNumber: 06HB01, Year: 2006, Value: 0.768 mg/kg\",\"StationNumber: 06HB02, Year: 2006, Value: 6.388 mg/kg\",\"StationNumber: 06HB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB04, Year: 2006, Value: 5.29 mg/kg\",\"StationNumber: 06HB05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB06, Year: 2006, Value: 8.423 mg/kg\",\"StationNumber: 06HB08, Year: 2006, Value: 4.515 mg/kg\",\"StationNumber: 06HB09, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB10, Year: 2006, Value: 9.296 mg/kg\",\"StationNumber: 06HB11, Year: 2006, Value: 9.144 mg/kg\",\"StationNumber: 06HB12, Year: 2006, Value: 1.668 mg/kg\",\"StationNumber: 06HB13, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB14, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB15, Year: 2006, Value: 3.641 mg/kg\",\"StationNumber: 06HB16, Year: 2006, Value: 3.091 mg/kg\",\"StationNumber: 06HB17, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB18, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB19, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB20, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB21, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB22, Year: 2006, Value: 0.958 mg/kg\",\"StationNumber: 06HB23, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB24, Year: 2006, Value: 0.867 mg/kg\",\"StationNumber: 06HB25, Year: 2006, Value: 3.199 mg/kg\",\"StationNumber: 06LTB01, Year: 2006, Value: 5.442 mg/kg\",\"StationNumber: 06LTB02, Year: 2006, Value: 6.614 mg/kg\",\"StationNumber: 06LTB03, Year: 2006, Value: 13.302 mg/kg\",\"StationNumber: 06LTB04, Year: 2006, Value: 9.592 mg/kg\",\"StationNumber: 06LTB05, Year: 2006, Value: 6.313 mg/kg\",\"StationNumber: 06LTB06, Year: 2006, Value: 8.886 mg/kg\",\"StationNumber: 06LTB07, Year: 2006, Value: 7.536 mg/kg\",\"StationNumber: 06LTB08, Year: 2006, Value: 6.973 mg/kg\",\"StationNumber: 06MR05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MR06, Year: 2006, Value: 6.076 mg/kg\",\"StationNumber: 06MR07, Year: 2006, Value: 1.121 mg/kg\",\"StationNumber: 06MR08, Year: 2006, Value: 6.41 mg/kg\",\"StationNumber: 06MR10, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB01, Year: 2006, Value: 21.691 mg/kg\",\"StationNumber: 06MTB02, Year: 2006, Value: 7.887 mg/kg\",\"StationNumber: 06MTB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB04, Year: 2006, Value: 5.141 mg/kg\",\"StationNumber: 06MTB05, Year: 2006, Value: 6.599 mg/kg\",\"StationNumber: 06MTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB07, Year: 2006, Value: 8.465 mg/kg\",\"StationNumber: 06MTB08, Year: 2006, Value: 7.305 mg/kg\",\"StationNumber: 06MTB09, Year: 2006, Value: 9.749 mg/kg\",\"StationNumber: 06MTB10, Year: 2006, Value: 7.082 mg/kg\",\"StationNumber: 06MTB11, Year: 2006, Value: 4.9 mg/kg\",\"StationNumber: 06MTB12, Year: 2006, Value: 5.42 mg/kg\",\"StationNumber: 06MTB13, Year: 2006, Value: 2.843 mg/kg\",\"StationNumber: 06MTB14, Year: 2006, Value: 6.476 mg/kg\",\"StationNumber: 06MTB15, Year: 2006, Value: 6.64 mg/kg\",\"StationNumber: 06MTB16, Year: 2006, Value: 5.146 mg/kg\",\"StationNumber: 06MTB17, Year: 2006, Value: 8.46 mg/kg\",\"StationNumber: 06MTB18, Year: 2006, Value: 1.724 mg/kg\",\"StationNumber: 06MTB19, Year: 2006, Value: 5.701 mg/kg\",\"StationNumber: 06OTB01, Year: 2006, Value: 5.045 mg/kg\",\"StationNumber: 06OTB02, Year: 2006, Value: 6.294 mg/kg\",\"StationNumber: 06OTB03, Year: 2006, Value: 5.32 mg/kg\",\"StationNumber: 06OTB04, Year: 2006, Value: 5.697 mg/kg\",\"StationNumber: 06OTB05, Year: 2006, Value: 2.581 mg/kg\",\"StationNumber: 06OTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06OTB07, Year: 2006, Value: 2.085 mg/kg\",\"StationNumber: 06OTB08, Year: 2006, Value: 5.097 mg/kg\",\"StationNumber: 06TCB01, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB02, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB04, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB09, Year: 2006, Value: 0.189 mg/kg\",\"StationNumber: 07BCB06, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB09, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB15, Year: 2007, Value: 7.27 mg/kg\",\"StationNumber: 07BCB28, Year: 2007, Value: 6.46 mg/kg\",\"StationNumber: 07BCB29, Year: 2007, Value: 0.61 mg/kg\",\"StationNumber: 07BCB30, Year: 2007, Value: 9.62 mg/kg\",\"StationNumber: 07BCB41, Year: 2007, Value: 6.85 mg/kg\",\"StationNumber: 07BCB42, Year: 2007, Value: 11.82 mg/kg\",\"StationNumber: 07BCB44, Year: 2007, Value: 7.13 mg/kg\",\"StationNumber: 07BCB45, Year: 2007, Value: 8.32 mg/kg\",\"StationNumber: 07HB13, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB21, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB34, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB37, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB38, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB41, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB53, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07LTB91, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR09, Year: 2007, Value: 0.11 mg/kg\",\"StationNumber: 07MR28, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR46, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR50, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB34, Year: 2007, Value: 9.44 mg/kg\",\"StationNumber: 07MTB39, Year: 2007, Value: 4.6 mg/kg\",\"StationNumber: 07MTB40, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB43, Year: 2007, Value: 0.51 mg/kg\",\"StationNumber: 07MTB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB47, Year: 2007, Value: 10.84 mg/kg\",\"StationNumber: 07MTB54, Year: 2007, Value: 13.61 mg/kg\",\"StationNumber: 07OTB04, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB08, Year: 2007, Value: 7.25 mg/kg\",\"StationNumber: 07OTB18, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB21, Year: 2007, Value: 2.99 mg/kg\",\"StationNumber: 07OTB24, Year: 2007, Value: 3.72 mg/kg\",\"StationNumber: 07OTB25, Year: 2007, Value: 7.21 mg/kg\",\"StationNumber: 07OTB31, Year: 2007, Value: 10.48 mg/kg\",\"StationNumber: 07TCB14, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB15, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB20, Year: 2007, Value: 8.27 mg/kg\",\"StationNumber: 07TCB22, Year: 2007, Value: 1.55 mg/kg\",\"StationNumber: 08BCB02, Year: 2008, Value: 2.25 mg/kg\",\"StationNumber: 08BCB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB12, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB15, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB16, Year: 2008, Value: 4.4 mg/kg\",\"StationNumber: 08BCB17, Year: 2008, Value: 3.34 mg/kg\",\"StationNumber: 08BCB23, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB26, Year: 2008, Value: 9.9 mg/kg\",\"StationNumber: 08BCB29, Year: 2008, Value: 7.8 mg/kg\",\"StationNumber: 08BCB35, Year: 2008, Value: 7.83 mg/kg\",\"StationNumber: 08BCB38, Year: 2008, Value: 6.95 mg/kg\",\"StationNumber: 08HB13, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB14, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB17, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB21, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB27, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB34, Year: 2008, Value: 4.62 mg/kg\",\"StationNumber: 08HB43, Year: 2008, Value: 4.15 mg/kg\",\"StationNumber: 08HB44, Year: 2008, Value: 6.35 mg/kg\",\"StationNumber: 08HB48, Year: 2008, Value: 7.51 mg/kg\",\"StationNumber: 08LTB69, Year: 2008, Value: 9.07 mg/kg\",\"StationNumber: 08LTB79, Year: 2008, Value: 22.19 mg/kg\",\"StationNumber: 08LTB82, Year: 2008, Value: 9.06 mg/kg\",\"StationNumber: 08MR08, Year: 2008, Value: 11.03 mg/kg\",\"StationNumber: 08MR35, Year: 2008, Value: 6.78 mg/kg\",\"StationNumber: 08MR40, Year: 2008, Value: 2.73 mg/kg\",\"StationNumber: 08MR43, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08MR53, Year: 2008, Value: 4.18 mg/kg\",\"StationNumber: 08MR54, Year: 2008, Value: 5.54 mg/kg\",\"StationNumber: 08MTB37, Year: 2008, Value: 6.6 mg/kg\",\"StationNumber: 08MTB47, Year: 2008, Value: 8.06 mg/kg\",\"StationNumber: 08MTB53, Year: 2008, Value: 0 mg/kg\",\"StationNumber: 08MTB62, Year: 2008, Value: 11.22 mg/kg\",\"StationNumber: 08MTB73, Year: 2008, Value: 4.04 mg/kg\",\"StationNumber: 08OTB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08OTB07, Year: 2008, Value: 0.46 mg/kg\",\"StationNumber: 08OTB13, Year: 2008, Value: 6.98 mg/kg\",\"StationNumber: 08OTB15, Year: 2008, Value: 3.77 mg/kg\",\"StationNumber: 08OTB17, Year: 2008, Value: 8.33 mg/kg\",\"StationNumber: 08OTB23, Year: 2008, Value: 11.18 mg/kg\",\"StationNumber: 08OTB27, Year: 2008, Value: 9.44 mg/kg\",\"StationNumber: 08TCB01, Year: 2008, Value: 1.91 mg/kg\",\"StationNumber: 08TCB07, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08TCB26, Year: 2008, Value: 0.07 mg/kg\",\"StationNumber: 10BCB06, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB11, Year: 2010, Value: 5.82 mg/kg\",\"StationNumber: 10BCB17, Year: 2010, Value: 5.65 mg/kg\",\"StationNumber: 10BCB25, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB28, Year: 2010, Value: 7.31 mg/kg\",\"StationNumber: 10BCB30, Year: 2010, Value: 8.9 mg/kg\",\"StationNumber: 10BCB37, Year: 2010, Value: 5.2 mg/kg\",\"StationNumber: 10BCB41, Year: 2010, Value: 4.55 mg/kg\",\"StationNumber: 10BCB46, Year: 2010, Value: 5.05 mg/kg\",\"StationNumber: 10BCB47, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB49, Year: 2010, Value: 6.65 mg/kg\",\"StationNumber: 10HB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB22, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB25, Year: 2010, Value: 10.85 mg/kg\",\"StationNumber: 10HB26, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB34, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB44, Year: 2010, Value: 6.34 mg/kg\",\"StationNumber: 10HB46, Year: 2010, Value: 5.15 mg/kg\",\"StationNumber: 10HB48, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB54, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB71, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB76, Year: 2010, Value: 4.59 mg/kg\",\"StationNumber: 10LTB89, Year: 2010, Value: 9.22 mg/kg\",\"StationNumber: 10MR25, Year: 2010, Value: 7.48 mg/kg\",\"StationNumber: 10MR29, Year: 2010, Value: 9.82 mg/kg\",\"StationNumber: 10MR33, Year: 2010, Value: 4.36 mg/kg\",\"StationNumber: 10MR40, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MR44, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB30, Year: 2010, Value: 9.2 mg/kg\",\"StationNumber: 10MTB35, Year: 2010, Value: 5.93 mg/kg\",\"StationNumber: 10MTB43, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB53, Year: 2010, Value: 9.06 mg/kg\",\"StationNumber: 10MTB56, Year: 2010, Value: 9.26 mg/kg\",\"StationNumber: 10OTB04, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB05, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB07, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB08, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB09, Year: 2010, Value: 4.65 mg/kg\",\"StationNumber: 10OTB12, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB14, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB15, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB16, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB18, Year: 2010, Value: 8.82 mg/kg\",\"StationNumber: 10OTB19, Year: 2010, Value: 4.94 mg/kg\",\"StationNumber: 10OTB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB24, Year: 2010, Value: 6.72 mg/kg\",\"StationNumber: 10OTB25, Year: 2010, Value: 7.91 mg/kg\",\"StationNumber: 10OTB26, Year: 2010, Value: 8.22 mg/kg\",\"StationNumber: 10OTB28, Year: 2010, Value: 10.09 mg/kg\",\"StationNumber: 10OTB29, Year: 2010, Value: 9.46 mg/kg\",\"StationNumber: 10OTB96, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB97, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB98, Year: 2010, Value: 9.71 mg/kg\",\"StationNumber: 10TCB01, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB11, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 11BCB05, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB20, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB22, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB42, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB48, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB13, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB29, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB31, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB36, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB38, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB40, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB47, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB69, Year: 2011, Value: 4.07 mg/kg\",\"StationNumber: 11LTB75, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB80, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR37, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR45, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR52, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB39, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB46, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB54, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB72, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB08, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB24, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB31, Year: 2011, Value: 4.24 mg/kg\",\"StationNumber: 11OTB32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB10, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 12BCB06, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB23, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB25, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB35, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB44, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB49, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB28, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB31, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB32, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB38, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB45, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB78, Year: 2012, Value: 10.58 mg/kg\",\"StationNumber: 12LTB84, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB93, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR17, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR33, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR36, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR43, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB47, Year: 2012, Value: 4.25 mg/kg\",\"StationNumber: 12MTB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB58, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB63, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB64, Year: 2012, Value: 4.45 mg/kg\",\"StationNumber: 12OTB04, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB18, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB20, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB05, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 13BCB05, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB07, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB10, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB17, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB22, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB30, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB43, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB13, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB25, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB26, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB36, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB79, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB82, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB86, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR24, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR31, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB34, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB55, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB12, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB15, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB16, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB21, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB27, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB28, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB29, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB01, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB14, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 14BCB03, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14BCB12, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB17, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB26, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB43, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB44, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB71, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB81, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB90, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR37, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR38, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14MR47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB39, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB63, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB04, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB08, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB14, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB18, Year: 2014, Value: 463.9 mg/kg\",\"StationNumber: 14OTB19, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB22, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 15BCB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB31, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB34, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB43, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB47, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB14, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB27, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB36, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB37, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB41, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB70, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB76, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB94, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR08, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR33, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR42, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB49, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB55, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB62, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB20, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB24, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB29, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB01, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB11, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 16BCB20, Year: 2016, Value: 3.32 mg/kg\",\"StationNumber: 16BCB22, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB25, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB29, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB34, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB35, Year: 2016, Value: 3.05 mg/kg\",\"StationNumber: 16BCB36, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB41, Year: 2016, Value: 2.42 mg/kg\",\"StationNumber: 16BCB42, Year: 2016, Value: 1.18 mg/kg\",\"StationNumber: 16BCB43, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16DH01-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-4, Year: 2016, Value: 3.25 mg/kg\",\"StationNumber: 16DH03-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-4, Year: 2016, Value: 0.76 mg/kg\",\"StationNumber: 16DH04-1, Year: 2016, Value: 2.53 mg/kg\",\"StationNumber: 16DH04-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-4, Year: 2016, Value: 3.5 mg/kg\",\"StationNumber: 16DH05-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-3, Year: 2016, Value: 1.87 mg/kg\",\"StationNumber: 16DH05-4, Year: 2016, Value: 2.91 mg/kg\",\"StationNumber: 16DH06-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-4, Year: 2016, Value: 1.85 mg/kg\",\"StationNumber: 16DH08-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-2, Year: 2016, Value: 2.25 mg/kg\",\"StationNumber: 16DH10-3, Year: 2016, Value: 1.16 mg/kg\",\"StationNumber: 16DH10-4, Year: 2016, Value: 3.43 mg/kg\",\"StationNumber: 16HB19, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB21, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB27, Year: 2016, Value: 2.44 mg/kg\",\"StationNumber: 16HB28, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB32, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16LTB71, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16LTB79, Year: 2016, Value: 8.12 mg/kg\",\"StationNumber: 16LTB85, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR17, Year: 2016, Value: 2.41 mg/kg\",\"StationNumber: 16MR25, Year: 2016, Value: 1.84 mg/kg\",\"StationNumber: 16MR29, Year: 2016, Value: 0.62 mg/kg\",\"StationNumber: 16MR33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR43, Year: 2016, Value: 2.1 mg/kg\",\"StationNumber: 16MR44, Year: 2016, Value: 0.09 mg/kg\",\"StationNumber: 16MR45, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB41, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB47, Year: 2016, Value: 3.95 mg/kg\",\"StationNumber: 16MTB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB53, Year: 2016, Value: 4.34 mg/kg\",\"StationNumber: 16MTB72, Year: 2016, Value: 1.69 mg/kg\",\"StationNumber: 16OTB08, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB09, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB13, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB18, Year: 2016, Value: 1.78 mg/kg\",\"StationNumber: 16OTB22, Year: 2016, Value: 3.79 mg/kg\",\"StationNumber: 16OTB25, Year: 2016, Value: 1.02 mg/kg\",\"StationNumber: 16TCB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16TCB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 17BCB15, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB27, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB30, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB36, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB40, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB44, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB10, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB15, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 17HB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB34, Year: 2017, Value: 524.32 mg/kg\",\"StationNumber: 17HB36, Year: 2017, Value: 8.91 mg/kg\",\"StationNumber: 17HB41, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB70, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB83, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB89, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR09, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR18, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR24, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR37, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB34, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB46, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB55, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB63, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB04, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB07, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB19, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB28, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP01, Year: 2017, Value: 20.64 mg/kg\",\"StationNumber: 17TCP02, Year: 2017, Value: 17.43 mg/kg\",\"StationNumber: 17TCP03, Year: 2017, Value: 15.42 mg/kg\",\"StationNumber: 17TCP04, Year: 2017, Value: 14.89 mg/kg\",\"StationNumber: 17TCP05, Year: 2017, Value: 9.77 mg/kg\",\"StationNumber: 17TCP06, Year: 2017, Value: 27.33 mg/kg\",\"StationNumber: 17TCP07, Year: 2017, Value: 11.7 mg/kg\",\"StationNumber: 17TCP08, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP09, Year: 2017, Value: 8.06 mg/kg\",\"StationNumber: 17TCP10, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 18BCB11, Year: 2018, Value: 24.7 mg/kg\",\"StationNumber: 18BCB15, Year: 2018, Value: 1.51 mg/kg\",\"StationNumber: 18BCB19, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB20, Year: 2018, Value: 1.19 mg/kg\",\"StationNumber: 18BCB22, Year: 2018, Value: 1.43 mg/kg\",\"StationNumber: 18BCB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB26, Year: 2018, Value: 1.76 mg/kg\",\"StationNumber: 18BCB37, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB42, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB44, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB46, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18HB14, Year: 2018, Value: 2.7 mg/kg\",\"StationNumber: 18HB20, Year: 2018, Value: 4.74 mg/kg\",\"StationNumber: 18HB21, Year: 2018, Value: 1.96 mg/kg\",\"StationNumber: 18HB26, Year: 2018, Value: 2.48 mg/kg\",\"StationNumber: 18HB29, Year: 2018, Value: 1.98 mg/kg\",\"StationNumber: 18HB33, Year: 2018, Value: 3.56 mg/kg\",\"StationNumber: 18HB38, Year: 2018, Value: 3.23 mg/kg\",\"StationNumber: 18HB41, Year: 2018, Value: 1.26 mg/kg\",\"StationNumber: 18HB46, Year: 2018, Value: 1.05 mg/kg\",\"StationNumber: 18LTB75, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB79, Year: 2018, Value: 14.24 mg/kg\",\"StationNumber: 18LTB81, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB82, Year: 2018, Value: 0.1 mg/kg\",\"StationNumber: 18MR25, Year: 2018, Value: 7.31 mg/kg\",\"StationNumber: 18MR37, Year: 2018, Value: 0.78 mg/kg\",\"StationNumber: 18MR46, Year: 2018, Value: 0.07 mg/kg\",\"StationNumber: 18MTB41, Year: 2018, Value: 1.08 mg/kg\",\"StationNumber: 18MTB42, Year: 2018, Value: 2.2 mg/kg\",\"StationNumber: 18MTB48, Year: 2018, Value: 1.01 mg/kg\",\"StationNumber: 18MTB56, Year: 2018, Value: 1.63 mg/kg\",\"StationNumber: 18OTB04, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB08, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB13, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB14, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB15, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB21, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18TCB05, Year: 2018, Value: 9.11 mg/kg\",\"StationNumber: 18TCB11, Year: 2018, Value: 6.79 mg/kg\",\"StationNumber: 18TCB14, Year: 2018, Value: 5.34 mg/kg\",\"StationNumber: 18TCB15, Year: 2018, Value: 6.28 mg/kg\",\"StationNumber: 18TCB21, Year: 2018, Value: 15.39 mg/kg\",\"StationNumber: 18TCB22, Year: 2018, Value: 5.61 mg/kg\",\"StationNumber: 19BCB27, Year: 2019, Value: 5.22 mg/kg\",\"StationNumber: 19BCB29, Year: 2019, Value: 5.87 mg/kg\",\"StationNumber: 19BCB30, Year: 2019, Value: 12.82 mg/kg\",\"StationNumber: 19BCB34, Year: 2019, Value: 0.26 mg/kg\",\"StationNumber: 19BCB35, Year: 2019, Value: 5.29 mg/kg\",\"StationNumber: 19BCB36, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19BCB40, Year: 2019, Value: 0.86 mg/kg\",\"StationNumber: 19BCB41, Year: 2019, Value: 0.61 mg/kg\",\"StationNumber: 19BCB43, Year: 2019, Value: 0.3 mg/kg\",\"StationNumber: 19BCB49, Year: 2019, Value: 1.28 mg/kg\",\"StationNumber: 19BCB50, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19HB09, Year: 2019, Value: 0.5 mg/kg\",\"StationNumber: 19HB16, Year: 2019, Value: 15.28 mg/kg\",\"StationNumber: 19HB25, Year: 2019, Value: 0.59 mg/kg\",\"StationNumber: 19HB27, Year: 2019, Value: 3.02 mg/kg\",\"StationNumber: 19HB32, Year: 2019, Value: 3.82 mg/kg\",\"StationNumber: 19HB37, Year: 2019, Value: 3.57 mg/kg\",\"StationNumber: 19HB39, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19HB40, Year: 2019, Value: 1.14 mg/kg\",\"StationNumber: 19HB47, Year: 2019, Value: 0.06 mg/kg\",\"StationNumber: 19LTB76, Year: 2019, Value: 1.06 mg/kg\",\"StationNumber: 19LTB78, Year: 2019, Value: 0.74 mg/kg\",\"StationNumber: 19LTB88, Year: 2019, Value: 6.12 mg/kg\",\"StationNumber: 19LTB90, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19MR17, Year: 2019, Value: 1.46 mg/kg\",\"StationNumber: 19MR18, Year: 2019, Value: 1.44 mg/kg\",\"StationNumber: 19MR29, Year: 2019, Value: 2.28 mg/kg\",\"StationNumber: 19MR33, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19MR43, Year: 2019, Value: 5.07 mg/kg\",\"StationNumber: 19MR44, Year: 2019, Value: 6.22 mg/kg\",\"StationNumber: 19MR52, Year: 2019, Value: 1.98 mg/kg\",\"StationNumber: 19MTB36, Year: 2019, Value: 2.26 mg/kg\",\"StationNumber: 19MTB47, Year: 2019, Value: 0.31 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 1.61 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 2.2 mg/kg\",\"StationNumber: 19MTB62, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19OTB07, Year: 2019, Value: 1.5 mg/kg\",\"StationNumber: 19OTB18, Year: 2019, Value: 1.2 mg/kg\",\"StationNumber: 19OTB20, Year: 2019, Value: 0.38 mg/kg\",\"StationNumber: 19OTB23, Year: 2019, Value: 0.9 mg/kg\",\"StationNumber: 19OTB25, Year: 2019, Value: 0.94 mg/kg\",\"StationNumber: 19OTB29, Year: 2019, Value: 1.32 mg/kg\",\"StationNumber: 19OTB31, Year: 2019, Value: 2.03 mg/kg\",\"StationNumber: 19TCB01, Year: 2019, Value: 4.92 mg/kg\",\"StationNumber: 19TCB20, Year: 2019, Value: 3.89 mg/kg\",\"StationNumber: 20BCB10, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB17, Year: 2020, Value: 0.92 mg/kg\",\"StationNumber: 20BCB22, Year: 2020, Value: 15.76 mg/kg\",\"StationNumber: 20BCB23, Year: 2020, Value: 0.99 mg/kg\",\"StationNumber: 20BCB35, Year: 2020, Value: 3.19 mg/kg\",\"StationNumber: 20BCB37, Year: 2020, Value: 1.91 mg/kg\",\"StationNumber: 20BCB40, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB43, Year: 2020, Value: 1.81 mg/kg\",\"StationNumber: 20BCB47, Year: 2020, Value: 1.65 mg/kg\",\"StationNumber: 20BCB48, Year: 2020, Value: 0.78 mg/kg\",\"StationNumber: 20BCB49, Year: 2020, Value: 1.3 mg/kg\",\"StationNumber: 20HB09, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB10, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB26, Year: 2020, Value: 8.35 mg/kg\",\"StationNumber: 20HB38, Year: 2020, Value: 3.49 mg/kg\",\"StationNumber: 20HB41, Year: 2020, Value: 3.54 mg/kg\",\"StationNumber: 20HB46, Year: 2020, Value: 1.16 mg/kg\",\"StationNumber: 20HB47, Year: 2020, Value: 0.34 mg/kg\",\"StationNumber: 20HB52, Year: 2020, Value: 2.28 mg/kg\",\"StationNumber: 20LTB70, Year: 2020, Value: 0.79 mg/kg\",\"StationNumber: 20LTB71, Year: 2020, Value: 0.96 mg/kg\",\"StationNumber: 20LTB77, Year: 2020, Value: 2.21 mg/kg\",\"StationNumber: 20LTB85, Year: 2020, Value: 10.94 mg/kg\",\"StationNumber: 20MR08, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR09, Year: 2020, Value: 1.22 mg/kg\",\"StationNumber: 20MR33, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR36, Year: 2020, Value: 1.24 mg/kg\",\"StationNumber: 20MR44, Year: 2020, Value: 6.25 mg/kg\",\"StationNumber: 20MR49, Year: 2020, Value: 0.94 mg/kg\",\"StationNumber: 20MTB35, Year: 2020, Value: 3.65 mg/kg\",\"StationNumber: 20MTB46, Year: 2020, Value: 0.23 mg/kg\",\"StationNumber: 20MTB52, Year: 2020, Value: 1.12 mg/kg\",\"StationNumber: 20MTB63, Year: 2020, Value: 0.48 mg/kg\",\"StationNumber: 20OTB13, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB14, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB15, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB19, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB24, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB32, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20TCB10, Year: 2020, Value: 4.53 mg/kg\",\"StationNumber: 20TCB12, Year: 2020, Value: 3.28 mg/kg\",\"StationNumber: 20TCB20, Year: 2020, Value: 3.03 mg/kg\",\"StationNumber: 21BCB09, Year: 2021, Value: 11.03 mg/kg\",\"StationNumber: 21BCB12, Year: 2021, Value: 4.15 mg/kg\",\"StationNumber: 21BCB15, Year: 2021, Value: 8.58 mg/kg\",\"StationNumber: 21BCB22, Year: 2021, Value: 1.46 mg/kg\",\"StationNumber: 21BCB25, Year: 2021, Value: 3.25 mg/kg\",\"StationNumber: 21BCB26, Year: 2021, Value: 5.19 mg/kg\",\"StationNumber: 21BCB29, Year: 2021, Value: 2.06 mg/kg\",\"StationNumber: 21BCB36, Year: 2021, Value: 0.98 mg/kg\",\"StationNumber: 21BCB41, Year: 2021, Value: 1.48 mg/kg\",\"StationNumber: 21BCB44, Year: 2021, Value: 4.08 mg/kg\",\"StationNumber: 21BCB50, Year: 2021, Value: 0.79 mg/kg\",\"StationNumber: 21HB13, Year: 2021, Value: 3.05 mg/kg\",\"StationNumber: 21HB19, Year: 2021, Value: 3.23 mg/kg\",\"StationNumber: 21HB20, Year: 2021, Value: 0.39 mg/kg\",\"StationNumber: 21HB27, Year: 2021, Value: 2.12 mg/kg\",\"StationNumber: 21HB34, Year: 2021, Value: 0.2 mg/kg\",\"StationNumber: 21HB36, Year: 2021, Value: 1.6 mg/kg\",\"StationNumber: 21HB37, Year: 2021, Value: 2.04 mg/kg\",\"StationNumber: 21HB40, Year: 2021, Value: 1.21 mg/kg\",\"StationNumber: 21HB43, Year: 2021, Value: 1.09 mg/kg\",\"StationNumber: 21LTB78, Year: 2021, Value: 3.26 mg/kg\",\"StationNumber: 21LTB83, Year: 2021, Value: 1.43 mg/kg\",\"StationNumber: 21LTB84, Year: 2021, Value: 5.27 mg/kg\",\"StationNumber: 21LTB89, Year: 2021, Value: 0.38 mg/kg\",\"StationNumber: 21MR24, Year: 2021, Value: 1.29 mg/kg\",\"StationNumber: 21MR29, Year: 2021, Value: 1.72 mg/kg\",\"StationNumber: 21MR45, Year: 2021, Value: 4.29 mg/kg\",\"StationNumber: 21MR47, Year: 2021, Value: 1.64 mg/kg\",\"StationNumber: 21MR52, Year: 2021, Value: 1.92 mg/kg\",\"StationNumber: 21MTB40, Year: 2021, Value: 0.15 mg/kg\",\"StationNumber: 21MTB43, Year: 2021, Value: 3.11 mg/kg\",\"StationNumber: 21MTB48, Year: 2021, Value: 1.12 mg/kg\",\"StationNumber: 21MTB62, Year: 2021, Value: 3.19 mg/kg\",\"StationNumber: 21OTB08, Year: 2021, Value: 0.22 mg/kg\",\"StationNumber: 21OTB12, Year: 2021, Value: 4.8 mg/kg\",\"StationNumber: 21OTB13, Year: 2021, Value: 0.45 mg/kg\",\"StationNumber: 21OTB18, Year: 2021, Value: 2.44 mg/kg\",\"StationNumber: 21OTB21, Year: 2021, Value: 0.24 mg/kg\",\"StationNumber: 21OTB25, Year: 2021, Value: 0.32 mg/kg\",\"StationNumber: 21OTB28, Year: 2021, Value: 0.16 mg/kg\",\"StationNumber: 21TCB02, Year: 2021, Value: 11.5 mg/kg\",\"StationNumber: 21TCB13, Year: 2021, Value: 7.11 mg/kg\",\"StationNumber: 21TCB22, Year: 2021, Value: 4.36 mg/kg\",\"StationNumber: 21TCB26, Year: 2021, Value: 2.49 mg/kg\",\"StationNumber: 22BCB02, Year: 2022, Value: 5.83 mg/kg\",\"StationNumber: 22BCB05, Year: 2022, Value: 1.17 mg/kg\",\"StationNumber: 22BCB11, Year: 2022, Value: 1.49 mg/kg\",\"StationNumber: 22BCB12, Year: 2022, Value: 1.1 mg/kg\",\"StationNumber: 22BCB17, Year: 2022, Value: 2.31 mg/kg\",\"StationNumber: 22BCB27, Year: 2022, Value: 1.33 mg/kg\",\"StationNumber: 22BCB30, Year: 2022, Value: 0.91 mg/kg\",\"StationNumber: 22BCB34, Year: 2022, Value: 0.62 mg/kg\",\"StationNumber: 22BCB35, Year: 2022, Value: 0.48 mg/kg\",\"StationNumber: 22BCB45, Year: 2022, Value: 1.24 mg/kg\",\"StationNumber: 22BCB47, Year: 2022, Value: 3.19 mg/kg\",\"StationNumber: 22HB10, Year: 2022, Value: 0.54 mg/kg\",\"StationNumber: 22HB19, Year: 2022, Value: 0.13 mg/kg\",\"StationNumber: 22HB21, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22HB25, Year: 2022, Value: 1.8 mg/kg\",\"StationNumber: 22HB26, Year: 2022, Value: 4.73 mg/kg\",\"StationNumber: 22HB28, Year: 2022, Value: 0.27 mg/kg\",\"StationNumber: 22HB32, Year: 2022, Value: 3.93 mg/kg\",\"StationNumber: 22HB40, Year: 2022, Value: 0.56 mg/kg\",\"StationNumber: 22HB46, Year: 2022, Value: 0.97 mg/kg\",\"StationNumber: 22LTB70, Year: 2022, Value: 2.91 mg/kg\",\"StationNumber: 22LTB79, Year: 2022, Value: 10.38 mg/kg\",\"StationNumber: 22LTB81, Year: 2022, Value: 0.9 mg/kg\",\"StationNumber: 22LTB90, Year: 2022, Value: 0.01 mg/kg\",\"StationNumber: 22MR17, Year: 2022, Value: 1.62 mg/kg\",\"StationNumber: 22MR25, Year: 2022, Value: 1.11 mg/kg\",\"StationNumber: 22MR32, Year: 2022, Value: 2.35 mg/kg\",\"StationNumber: 22MR37, Year: 2022, Value: 1.94 mg/kg\",\"StationNumber: 22MR42, Year: 2022, Value: 0.87 mg/kg\",\"StationNumber: 22MR44, Year: 2022, Value: 1.16 mg/kg\",\"StationNumber: 22MR46, Year: 2022, Value: 0.24 mg/kg\",\"StationNumber: 22MR52, Year: 2022, Value: 4.05 mg/kg\",\"StationNumber: 22MTB35, Year: 2022, Value: 1.69 mg/kg\",\"StationNumber: 22MTB37, Year: 2022, Value: 0.46 mg/kg\",\"StationNumber: 22MTB41, Year: 2022, Value: 2.4 mg/kg\",\"StationNumber: 22MTB55, Year: 2022, Value: 0.8 mg/kg\",\"StationNumber: 22OTB02, Year: 2022, Value: 1.05 mg/kg\",\"StationNumber: 22OTB07, Year: 2022, Value: 2.48 mg/kg\",\"StationNumber: 22OTB19, Year: 2022, Value: 1.75 mg/kg\",\"StationNumber: 22OTB22, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22OTB28, Year: 2022, Value: 0.25 mg/kg\",\"StationNumber: 22OTB29, Year: 2022, Value: 0.19 mg/kg\",\"StationNumber: 22OTB32, Year: 2022, Value: 0.15 mg/kg\",\"StationNumber: 22TCB20, Year: 2022, Value: 2.86 mg/kg\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.343422]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot summary of PEL averages by bay segment — show_sedimentpelave","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Plot summary PEL averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(   sedimentdata,   yrrng = c(1993, 2022),   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"),   funding_proj = \"TBEP\",   alph = 1,   ylim = c(0, 0.4),   lnsz = 1,   base_size = 12,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" alph numeric indicating alpha value score category colors ylim numeric y axis limits lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"ggplot object plotly object plotly = TRUE showing PEL averages (average averages) 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Lines grades shown plot. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(sedimentdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"Creates plotly object average PEL plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"show_sedimentpelaveplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"p ggplot object output show_sedimentpelave width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"p <- show_sedimentpelave(sedimentdata) show_sedimentpelaveplotly(p)  {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,0.0075599999999999999,0.0075599999999999999,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.0075599999999999999,0.02052,0.02052,0.0075599999999999999,0.0075599999999999999],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(162,253,122,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.02052,0.085669999999999996,0.085669999999999996,0.02052,0.02052],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.085669999999999996,0.28026000000000001,0.28026000000000001,0.085669999999999996,0.085669999999999996],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(238,118,0,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.28026000000000001,null,null,0.28026000000000001,0.28026000000000001],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: 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C\",\"StationNumber: 94LTB35, Year: 1994, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 94LTB36, Year: 1994, PEL ratio: 0.04666, Grade: C\",\"StationNumber: 94LTB37, Year: 1994, PEL ratio: 0.10165, Grade: D\",\"StationNumber: 94LTB38, Year: 1994, PEL ratio: 0.02221, Grade: C\",\"StationNumber: 94LTB39, Year: 1994, PEL ratio: 0.08637, Grade: D\",\"StationNumber: 94LTB40, Year: 1994, PEL ratio: 0.06117, Grade: C\",\"StationNumber: 94MR23, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR24, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR26, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR27, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR28, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR29, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR31, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR32, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR34, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR43, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MTB41, Year: 1994, PEL ratio: 0.00869, Grade: B\",\"StationNumber: 94MTB42, Year: 1994, PEL ratio: 0.00546, Grade: A\",\"StationNumber: 94MTB43, Year: 1994, PEL ratio: 0.07634, Grade: C\",\"StationNumber: 94MTB44, Year: 1994, PEL ratio: 0.09942, Grade: D\",\"StationNumber: 94MTB45, Year: 1994, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 94MTB47, Year: 1994, PEL ratio: 0.03786, Grade: C\",\"StationNumber: 94MTB48, Year: 1994, PEL ratio: 0.00958, Grade: B\",\"StationNumber: 94MTB49, Year: 1994, PEL ratio: 0.08992, Grade: D\",\"StationNumber: 94MTB50, Year: 1994, PEL ratio: 0.04484, Grade: C\",\"StationNumber: 94MTB51, Year: 1994, PEL ratio: 0.01764, Grade: B\",\"StationNumber: 94MTB52, Year: 1994, PEL ratio: 0.01808, Grade: B\",\"StationNumber: 94MTB53, Year: 1994, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 94MTB54, Year: 1994, PEL ratio: 0.05744, Grade: C\",\"StationNumber: 94MTB55, Year: 1994, PEL ratio: 0.00805, Grade: B\",\"StationNumber: 94MTB56, Year: 1994, PEL ratio: 0.03262, Grade: C\",\"StationNumber: 94MTB57, Year: 1994, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 94MTB58, Year: 1994, PEL ratio: 0.10823, Grade: D\",\"StationNumber: 94MTB59, Year: 1994, PEL ratio: 0.0237, Grade: C\",\"StationNumber: 94MTB60, Year: 1994, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 94MTB61, Year: 1994, PEL ratio: 0.14417, Grade: D\",\"StationNumber: 94OTB63, Year: 1994, PEL ratio: 0.16877, Grade: D\",\"StationNumber: 94OTB64, Year: 1994, PEL ratio: 0.01051, Grade: B\",\"StationNumber: 94OTB65, Year: 1994, PEL ratio: 0.02364, Grade: C\",\"StationNumber: 94OTB66, Year: 1994, PEL ratio: 0.0106, Grade: B\",\"StationNumber: 94OTB67, Year: 1994, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 94OTB68, Year: 1994, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 94OTB69, Year: 1994, PEL ratio: 0.01953, Grade: B\",\"StationNumber: 94OTB70, Year: 1994, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 94OTB71, Year: 1994, PEL ratio: 0.0663, Grade: C\",\"StationNumber: 94OTB72, Year: 1994, PEL ratio: 0.01765, Grade: B\",\"StationNumber: 94OTB73, Year: 1994, PEL ratio: 0.09561, Grade: D\",\"StationNumber: 94OTB76, Year: 1994, PEL ratio: 0.01769, Grade: B\",\"StationNumber: 94OTB77, Year: 1994, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 94OTB78, Year: 1994, PEL ratio: 0.15079, Grade: D\",\"StationNumber: 94OTB79, Year: 1994, PEL ratio: 0.02344, Grade: C\",\"StationNumber: 94OTB80, Year: 1994, PEL ratio: 0.02606, Grade: C\",\"StationNumber: 94OTB83, Year: 1994, PEL ratio: 0.01552, Grade: B\",\"StationNumber: 94TCB22, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB37, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB38, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB39, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB40, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB41, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB42, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB01, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB02, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB03, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB04, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB05, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB06, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB07, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB08, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB09, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB10, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB11, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB12, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB13, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB14, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB15, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB16, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB17, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB18, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB19, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB20, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB21, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95HB14, Year: 1995, PEL ratio: 0.27004, Grade: D\",\"StationNumber: 95HB16, Year: 1995, PEL ratio: 0.46027, Grade: F\",\"StationNumber: 95HB17, Year: 1995, PEL ratio: 0.04182, Grade: C\",\"StationNumber: 95HB18, Year: 1995, PEL ratio: 0.25744, Grade: D\",\"StationNumber: 95HB19, Year: 1995, PEL ratio: 0.02669, Grade: C\",\"StationNumber: 95HB22, Year: 1995, PEL ratio: 0.08766, Grade: D\",\"StationNumber: 95HB23, Year: 1995, PEL ratio: 0.17389, Grade: D\",\"StationNumber: 95HB24, Year: 1995, PEL ratio: 0.00709, Grade: A\",\"StationNumber: 95HB25, Year: 1995, PEL ratio: 0.10295, Grade: D\",\"StationNumber: 95HB26, Year: 1995, PEL ratio: 0.00947, Grade: B\",\"StationNumber: 95HB27, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB28, Year: 1995, PEL ratio: 0.00784, Grade: B\",\"StationNumber: 95HB29, Year: 1995, PEL ratio: 0.06887, Grade: C\",\"StationNumber: 95HB37, Year: 1995, PEL ratio: 0.07591, Grade: C\",\"StationNumber: 95HB38, Year: 1995, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 95HB40, Year: 1995, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 95HB41, Year: 1995, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 95HB42, Year: 1995, PEL ratio: 0.00695, Grade: A\",\"StationNumber: 95HB43, Year: 1995, PEL ratio: 0.07978, Grade: C\",\"StationNumber: 95HB44, Year: 1995, PEL ratio: 0.00487, Grade: A\",\"StationNumber: 95HB45, Year: 1995, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 95HB46, Year: 1995, PEL ratio: 0.11769, Grade: D\",\"StationNumber: 95HB48, Year: 1995, PEL ratio: 0.01232, Grade: B\",\"StationNumber: 95HB49, Year: 1995, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 95HB51, Year: 1995, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 95HB52, Year: 1995, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 95HB54, Year: 1995, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 95HB55, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB56, Year: 1995, PEL ratio: 0.19484, Grade: D\",\"StationNumber: 95LTB01, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95LTB02, Year: 1995, PEL ratio: 0.00483, Grade: A\",\"StationNumber: 95LTB04, Year: 1995, PEL ratio: 0.01579, Grade: B\",\"StationNumber: 95LTB05, Year: 1995, PEL ratio: 0.02646, Grade: C\",\"StationNumber: 95LTB06, Year: 1995, PEL ratio: 0.00405, Grade: A\",\"StationNumber: 95LTB07, Year: 1995, PEL ratio: 0.00392, Grade: A\",\"StationNumber: 95LTB08, Year: 1995, PEL ratio: 0.00633, Grade: A\",\"StationNumber: 95LTB09, Year: 1995, PEL ratio: 0.00764, Grade: B\",\"StationNumber: 95LTB10, Year: 1995, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 95LTB11, Year: 1995, PEL ratio: 0.01854, Grade: B\",\"StationNumber: 95LTB12, Year: 1995, PEL ratio: 0.05258, Grade: C\",\"StationNumber: 95LTB13, Year: 1995, PEL ratio: 0.03364, Grade: C\",\"StationNumber: 95LTB15, Year: 1995, PEL ratio: 0.00223, Grade: A\",\"StationNumber: 95LTB17, Year: 1995, PEL ratio: 0.00912, Grade: B\",\"StationNumber: 95LTB18, Year: 1995, PEL ratio: 0.00937, Grade: B\",\"StationNumber: 95LTB19, Year: 1995, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 95LTB20, Year: 1995, PEL ratio: 0.00586, Grade: A\",\"StationNumber: 95LTB21, Year: 1995, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 95LTB23, Year: 1995, PEL ratio: 0.01403, Grade: B\",\"StationNumber: 95LTB25, Year: 1995, PEL ratio: 0.002, Grade: A\",\"StationNumber: 95LTB26, Year: 1995, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 95LTB29, Year: 1995, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 95MR23, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR24, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR25, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR26, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR27, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR28, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR29, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR31, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR32, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR34, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR43, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MTB03, Year: 1995, PEL ratio: 0.00465, Grade: A\",\"StationNumber: 95MTB04, Year: 1995, PEL ratio: 0.008, Grade: B\",\"StationNumber: 95MTB06, Year: 1995, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 95MTB07, Year: 1995, PEL ratio: 0.12807, Grade: D\",\"StationNumber: 95MTB08, Year: 1995, PEL ratio: 0.00916, Grade: B\",\"StationNumber: 95MTB10, Year: 1995, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 95MTB15, Year: 1995, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 95MTB16, Year: 1995, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 95MTB17, Year: 1995, PEL ratio: 0.01668, Grade: B\",\"StationNumber: 95MTB18, Year: 1995, PEL ratio: 0.03443, Grade: C\",\"StationNumber: 95MTB19, Year: 1995, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 95MTB21, Year: 1995, PEL ratio: 0.02294, Grade: C\",\"StationNumber: 95MTB24, Year: 1995, PEL ratio: 0.00408, Grade: A\",\"StationNumber: 95MTB25, Year: 1995, PEL ratio: 0.0049, Grade: A\",\"StationNumber: 95MTB26, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95MTB29, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB30, Year: 1995, PEL ratio: 0.00748, Grade: A\",\"StationNumber: 95MTB31, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB32, Year: 1995, PEL ratio: 0.00689, Grade: A\",\"StationNumber: 95MTB34, Year: 1995, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 95MTB35, Year: 1995, PEL ratio: 0.00817, Grade: B\",\"StationNumber: 95OTB02, Year: 1995, PEL ratio: 0.01655, Grade: B\",\"StationNumber: 95OTB03, Year: 1995, PEL ratio: 0.00572, Grade: A\",\"StationNumber: 95OTB05, Year: 1995, PEL ratio: 0.02432, Grade: C\",\"StationNumber: 95OTB06, Year: 1995, PEL ratio: 0.00961, Grade: B\",\"StationNumber: 95OTB07, Year: 1995, PEL ratio: 0.00772, Grade: B\",\"StationNumber: 95OTB08, Year: 1995, PEL ratio: 0.00541, Grade: A\",\"StationNumber: 95OTB11, Year: 1995, PEL ratio: 0.01187, Grade: B\",\"StationNumber: 95OTB12, Year: 1995, PEL ratio: 0.01178, Grade: B\",\"StationNumber: 95OTB13, Year: 1995, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 95OTB14, Year: 1995, PEL ratio: 0.00796, Grade: B\",\"StationNumber: 95OTB15, Year: 1995, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 95OTB17, Year: 1995, PEL ratio: 0.00668, Grade: A\",\"StationNumber: 95OTB18, Year: 1995, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 95OTB19, Year: 1995, PEL ratio: 0.04972, Grade: C\",\"StationNumber: 95OTB20, Year: 1995, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 95OTB22, Year: 1995, PEL ratio: 0.01855, Grade: B\",\"StationNumber: 95OTB23, Year: 1995, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 95OTB24, Year: 1995, PEL ratio: 0.00477, Grade: A\",\"StationNumber: 95OTB25, Year: 1995, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 95OTB26, Year: 1995, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 95OTB27, Year: 1995, PEL ratio: 0.0039, Grade: A\",\"StationNumber: 95OTB29, Year: 1995, PEL ratio: 0.00722, Grade: A\",\"StationNumber: 95OTB30, Year: 1995, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 95TCB22, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB37, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB38, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB39, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB40, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB41, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB42, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 96BCB02, Year: 1996, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 96BCB04, Year: 1996, PEL ratio: 0.21792, Grade: D\",\"StationNumber: 96BCB07, Year: 1996, PEL ratio: 0.04432, Grade: C\",\"StationNumber: 96BCB08, Year: 1996, PEL ratio: 0.02026, Grade: B\",\"StationNumber: 96BCB12, Year: 1996, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 96BCB13, Year: 1996, PEL ratio: 0.31368, Grade: F\",\"StationNumber: 96BCB15, Year: 1996, PEL ratio: 0.18237, Grade: D\",\"StationNumber: 96BCB19, Year: 1996, PEL ratio: 0.01925, Grade: B\",\"StationNumber: 96BCB24, Year: 1996, PEL ratio: 0.03429, Grade: C\",\"StationNumber: 96BCB26, Year: 1996, PEL ratio: 0.01638, Grade: B\",\"StationNumber: 96BCB27, Year: 1996, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 96BCB30, Year: 1996, PEL ratio: 0.01775, Grade: B\",\"StationNumber: 96BCB31, Year: 1996, PEL ratio: 0.26305, Grade: D\",\"StationNumber: 96BCB34, Year: 1996, PEL ratio: 0.01272, Grade: B\",\"StationNumber: 96BCB36, Year: 1996, PEL ratio: 0.00987, Grade: B\",\"StationNumber: 96BCB39, Year: 1996, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 96BCB40, Year: 1996, PEL ratio: 0.01665, Grade: B\",\"StationNumber: 96BCB41, Year: 1996, PEL ratio: 0.00563, Grade: A\",\"StationNumber: 96BCB44, Year: 1996, PEL ratio: 0.02696, Grade: C\",\"StationNumber: 96BCB46, Year: 1996, PEL ratio: 0.00262, Grade: A\",\"StationNumber: 96BCB49, Year: 1996, PEL ratio: 0.00173, Grade: A\",\"StationNumber: 96HB13, Year: 1996, PEL ratio: 0.28424, Grade: F\",\"StationNumber: 96HB16, Year: 1996, PEL ratio: 0.01524, Grade: B\",\"StationNumber: 96HB18, Year: 1996, PEL ratio: 0.52049, Grade: F\",\"StationNumber: 96HB20, Year: 1996, PEL ratio: 0.14092, Grade: D\",\"StationNumber: 96HB22, Year: 1996, PEL ratio: 0.16443, Grade: D\",\"StationNumber: 96HB23, Year: 1996, PEL ratio: 0.07935, Grade: C\",\"StationNumber: 96HB24, Year: 1996, PEL ratio: 0.00728, Grade: A\",\"StationNumber: 96HB26, Year: 1996, PEL ratio: 0.00701, Grade: A\",\"StationNumber: 96HB27, Year: 1996, PEL ratio: 0.05771, Grade: C\",\"StationNumber: 96HB29, Year: 1996, PEL ratio: 0.01207, Grade: B\",\"StationNumber: 96HB36, Year: 1996, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 96HB37, Year: 1996, PEL ratio: 0.03752, Grade: C\",\"StationNumber: 96HB38, Year: 1996, PEL ratio: 0.10492, Grade: D\",\"StationNumber: 96HB39, Year: 1996, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 96HB42, Year: 1996, PEL ratio: 0.05108, Grade: C\",\"StationNumber: 96HB43, Year: 1996, PEL ratio: 0.08509, Grade: C\",\"StationNumber: 96HB44, Year: 1996, PEL ratio: 0.02579, Grade: C\",\"StationNumber: 96HB45, Year: 1996, PEL ratio: 0.00593, Grade: A\",\"StationNumber: 96HB46, Year: 1996, PEL ratio: 11.28998, Grade: F\",\"StationNumber: 96HB47, Year: 1996, PEL ratio: 0.01428, Grade: B\",\"StationNumber: 96HB48, Year: 1996, PEL ratio: 0.1139, Grade: D\",\"StationNumber: 96HB50, Year: 1996, PEL ratio: 0.02802, Grade: C\",\"StationNumber: 96HB51, Year: 1996, PEL ratio: 0.00781, Grade: B\",\"StationNumber: 96HB52, Year: 1996, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 96HB53, Year: 1996, PEL ratio: 0.00529, Grade: A\",\"StationNumber: 96HB54, Year: 1996, PEL ratio: 0.00646, Grade: A\",\"StationNumber: 96HB56, Year: 1996, PEL ratio: 0.15168, Grade: D\",\"StationNumber: 96LTB01, Year: 1996, PEL ratio: 0.07215, Grade: C\",\"StationNumber: 96LTB02, Year: 1996, PEL ratio: 0.01176, Grade: B\",\"StationNumber: 96LTB03, Year: 1996, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 96LTB04, Year: 1996, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 96LTB05, Year: 1996, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 96LTB06, Year: 1996, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 96LTB07, Year: 1996, PEL ratio: 0.01085, Grade: B\",\"StationNumber: 96LTB08, Year: 1996, PEL ratio: 0.00503, Grade: A\",\"StationNumber: 96LTB09, Year: 1996, PEL ratio: 0.00497, Grade: A\",\"StationNumber: 96LTB10, Year: 1996, PEL ratio: 0.01922, Grade: B\",\"StationNumber: 96LTB11, Year: 1996, PEL ratio: 0.02443, Grade: C\",\"StationNumber: 96LTB12, Year: 1996, PEL ratio: 0.01365, Grade: B\",\"StationNumber: 96LTB13, Year: 1996, PEL ratio: 0.05548, Grade: C\",\"StationNumber: 96LTB15, Year: 1996, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 96LTB17, Year: 1996, PEL ratio: 0.01376, Grade: B\",\"StationNumber: 96LTB18, Year: 1996, PEL ratio: 0.01093, Grade: B\",\"StationNumber: 96LTB19, Year: 1996, PEL ratio: 0.00533, Grade: A\",\"StationNumber: 96LTB20, Year: 1996, PEL ratio: 0.00274, Grade: A\",\"StationNumber: 96LTB21, Year: 1996, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 96LTB23, Year: 1996, PEL ratio: 0.00883, Grade: B\",\"StationNumber: 96LTB24, Year: 1996, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 96LTB25, Year: 1996, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 96LTB26, Year: 1996, PEL ratio: 0.00167, Grade: A\",\"StationNumber: 96LTB27, Year: 1996, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 96MR20, Year: 1996, PEL ratio: 0.0375, Grade: C\",\"StationNumber: 96MR21, Year: 1996, PEL ratio: 0.01873, Grade: B\",\"StationNumber: 96MR23, Year: 1996, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 96MR24, Year: 1996, PEL ratio: 0.04434, Grade: C\",\"StationNumber: 96MR25, Year: 1996, PEL ratio: 0.0361, Grade: C\",\"StationNumber: 96MR26, Year: 1996, PEL ratio: 0.02689, Grade: C\",\"StationNumber: 96MR27, Year: 1996, PEL ratio: 0.02357, Grade: C\",\"StationNumber: 96MR28, Year: 1996, PEL ratio: 0.00874, Grade: B\",\"StationNumber: 96MR29, Year: 1996, PEL ratio: 0.04221, Grade: C\",\"StationNumber: 96MR30, Year: 1996, PEL ratio: 0.03112, Grade: C\",\"StationNumber: 96MR31, Year: 1996, PEL ratio: 0.01702, Grade: B\",\"StationNumber: 96MR32, Year: 1996, PEL ratio: 0.0686, Grade: C\",\"StationNumber: 96MR43, Year: 1996, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 96MTB04, Year: 1996, PEL ratio: 0.00399, Grade: A\",\"StationNumber: 96MTB05, Year: 1996, PEL ratio: 0.00738, Grade: A\",\"StationNumber: 96MTB07, Year: 1996, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 96MTB09, Year: 1996, PEL ratio: 0.04135, Grade: C\",\"StationNumber: 96MTB10, Year: 1996, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 96MTB11, Year: 1996, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 96MTB12, Year: 1996, PEL ratio: 0.01296, Grade: B\",\"StationNumber: 96MTB13, Year: 1996, PEL ratio: 0.00054, Grade: A\",\"StationNumber: 96MTB14, Year: 1996, PEL ratio: 0.21228, Grade: D\",\"StationNumber: 96MTB15, Year: 1996, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 96MTB16, Year: 1996, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 96MTB17, Year: 1996, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 96MTB18, Year: 1996, PEL ratio: 0.00511, Grade: A\",\"StationNumber: 96MTB19, Year: 1996, PEL ratio: 0.00327, Grade: A\",\"StationNumber: 96MTB20, Year: 1996, PEL ratio: 0.07168, Grade: C\",\"StationNumber: 96MTB23, Year: 1996, PEL ratio: 0.00289, Grade: A\",\"StationNumber: 96MTB24, Year: 1996, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 96MTB25, Year: 1996, PEL ratio: 0.00302, Grade: A\",\"StationNumber: 96MTB26, Year: 1996, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 96MTB30, Year: 1996, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 96MTB31, Year: 1996, PEL ratio: 0.01583, Grade: B\",\"StationNumber: 96MTB32, Year: 1996, PEL ratio: 0.02658, Grade: C\",\"StationNumber: 96MTB34, Year: 1996, PEL ratio: 0.01453, Grade: B\",\"StationNumber: 96MTB35, Year: 1996, PEL ratio: 0.00178, Grade: A\",\"StationNumber: 96OTB07, Year: 1996, PEL ratio: 0.00525, Grade: A\",\"StationNumber: 96OTB11, Year: 1996, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 96OTB12, Year: 1996, PEL ratio: 0.01689, Grade: B\",\"StationNumber: 96OTB13, Year: 1996, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 96OTB14, Year: 1996, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 96OTB17, Year: 1996, PEL ratio: 0.00886, Grade: B\",\"StationNumber: 96OTB18, Year: 1996, PEL ratio: 0.01434, Grade: B\",\"StationNumber: 96OTB19, Year: 1996, PEL ratio: 0.01141, Grade: B\",\"StationNumber: 96OTB20, Year: 1996, PEL ratio: 0.09948, Grade: D\",\"StationNumber: 96OTB23, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB24, Year: 1996, PEL ratio: 0.00798, Grade: B\",\"StationNumber: 96OTB26, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB27, Year: 1996, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 96OTB29, Year: 1996, PEL ratio: 0.00299, Grade: A\",\"StationNumber: 96OTB30, Year: 1996, PEL ratio: 0.01598, Grade: B\",\"StationNumber: 96TCB22, Year: 1996, PEL ratio: 0.03815, Grade: C\",\"StationNumber: 96TCB36, Year: 1996, PEL ratio: 0.0182, Grade: B\",\"StationNumber: 96TCB37, Year: 1996, PEL ratio: 0.06747, Grade: C\",\"StationNumber: 96TCB38, Year: 1996, PEL ratio: 0.04811, Grade: C\",\"StationNumber: 96TCB39, Year: 1996, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 96TCB40, Year: 1996, PEL ratio: 0.02086, Grade: C\",\"StationNumber: 96TCB41, Year: 1996, PEL ratio: 0.02591, Grade: C\",\"StationNumber: 96TCB42, Year: 1996, PEL ratio: 0.01431, Grade: B\",\"StationNumber: 97BCB02, Year: 1997, PEL ratio: 0.02654, Grade: C\",\"StationNumber: 97BCB08, Year: 1997, PEL ratio: 0.06243, Grade: C\",\"StationNumber: 97BCB10, Year: 1997, PEL ratio: 0.07472, Grade: C\",\"StationNumber: 97BCB13, Year: 1997, PEL ratio: 0.02112, Grade: C\",\"StationNumber: 97BCB17, Year: 1997, PEL ratio: 0.06466, Grade: C\",\"StationNumber: 97BCB18, Year: 1997, PEL ratio: 0.03013, Grade: C\",\"StationNumber: 97BCB27, Year: 1997, PEL ratio: 0.25161, Grade: D\",\"StationNumber: 97BCB30, Year: 1997, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 97BCB31, Year: 1997, PEL ratio: 0.00973, Grade: B\",\"StationNumber: 97BCB36, Year: 1997, PEL ratio: 0.01281, Grade: B\",\"StationNumber: 97BCB37, Year: 1997, PEL ratio: 0.01861, Grade: B\",\"StationNumber: 97BCB40, Year: 1997, PEL ratio: 0.03448, Grade: C\",\"StationNumber: 97BCB46, Year: 1997, PEL ratio: 0.01276, Grade: B\",\"StationNumber: 97BCB50, Year: 1997, PEL ratio: 0.0087, Grade: B\",\"StationNumber: 97BCB57-1, Year: 1997, PEL ratio: 0.12797, Grade: D\",\"StationNumber: 97BCB58-1, Year: 1997, PEL ratio: 0.29199, Grade: F\",\"StationNumber: 97BCB58-2, Year: 1997, PEL ratio: 0.04357, Grade: C\",\"StationNumber: 97BCB59-1, Year: 1997, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 97BCB59-2, Year: 1997, PEL ratio: 0.02798, Grade: C\",\"StationNumber: 97BCB60-2, Year: 1997, PEL ratio: 0.00469, Grade: A\",\"StationNumber: 97BCB60-4, Year: 1997, PEL ratio: 0.00523, Grade: A\",\"StationNumber: 97HB10, Year: 1997, PEL ratio: 1.45751, Grade: F\",\"StationNumber: 97HB13, Year: 1997, PEL ratio: 0.20993, Grade: D\",\"StationNumber: 97HB18, Year: 1997, PEL ratio: 0.0395, Grade: C\",\"StationNumber: 97HB22, Year: 1997, PEL ratio: 0.23185, Grade: D\",\"StationNumber: 97HB23, Year: 1997, PEL ratio: 0.01374, Grade: B\",\"StationNumber: 97HB24, Year: 1997, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 97HB27, Year: 1997, PEL ratio: 0.00494, Grade: A\",\"StationNumber: 97HB29, Year: 1997, PEL ratio: 0.18186, Grade: D\",\"StationNumber: 97HB36, Year: 1997, PEL ratio: 0.00827, Grade: B\",\"StationNumber: 97HB37, Year: 1997, PEL ratio: 0.06009, Grade: C\",\"StationNumber: 97HB38, Year: 1997, PEL ratio: 0.04075, Grade: C\",\"StationNumber: 97HB39, Year: 1997, PEL ratio: 0.08084, Grade: C\",\"StationNumber: 97HB43, Year: 1997, PEL ratio: 0.0066, Grade: A\",\"StationNumber: 97HB44, Year: 1997, PEL ratio: 0.01905, Grade: B\",\"StationNumber: 97HB45, Year: 1997, PEL ratio: 0.03887, Grade: C\",\"StationNumber: 97HB46, Year: 1997, PEL ratio: 0.00974, Grade: B\",\"StationNumber: 97HB48, Year: 1997, PEL ratio: 0.00871, Grade: B\",\"StationNumber: 97HB50, Year: 1997, PEL ratio: 0.08114, Grade: C\",\"StationNumber: 97HB53, Year: 1997, PEL ratio: 0.00914, Grade: B\",\"StationNumber: 97HB54, Year: 1997, PEL ratio: 0.01088, Grade: B\",\"StationNumber: 97HB55, Year: 1997, PEL ratio: 0.02004, Grade: B\",\"StationNumber: 97HB56, Year: 1997, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 97LTB01, Year: 1997, PEL ratio: 0.0117, Grade: B\",\"StationNumber: 97LTB02, Year: 1997, PEL ratio: 0.01631, Grade: B\",\"StationNumber: 97LTB03, Year: 1997, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 97LTB06, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97LTB07, Year: 1997, PEL ratio: 0.00826, Grade: B\",\"StationNumber: 97LTB09, Year: 1997, PEL ratio: 0.01935, Grade: B\",\"StationNumber: 97LTB10, Year: 1997, PEL ratio: 0.02574, Grade: C\",\"StationNumber: 97LTB11, Year: 1997, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 97LTB12, Year: 1997, PEL ratio: 0.01318, Grade: B\",\"StationNumber: 97LTB13, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97LTB15, Year: 1997, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 97LTB17, Year: 1997, PEL ratio: 0.00975, Grade: B\",\"StationNumber: 97LTB18, Year: 1997, PEL ratio: 0.00942, Grade: B\",\"StationNumber: 97LTB19, Year: 1997, PEL ratio: 0.00972, Grade: B\",\"StationNumber: 97LTB20, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97LTB21, Year: 1997, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 97LTB23, Year: 1997, PEL ratio: 0.01146, Grade: B\",\"StationNumber: 97LTB24, Year: 1997, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 97LTB25, Year: 1997, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 97LTB26, Year: 1997, PEL ratio: 0.00218, Grade: A\",\"StationNumber: 97LTB28, Year: 1997, PEL ratio: 0.00444, Grade: A\",\"StationNumber: 97MR09, Year: 1997, PEL ratio: 0.01198, Grade: B\",\"StationNumber: 97MR10, Year: 1997, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 97MR11, Year: 1997, PEL ratio: 0.04743, Grade: C\",\"StationNumber: 97MR12, Year: 1997, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 97MR13, Year: 1997, PEL ratio: 0.0476, Grade: C\",\"StationNumber: 97MR14, Year: 1997, PEL ratio: 0.08134, Grade: C\",\"StationNumber: 97MR15, Year: 1997, PEL ratio: 0.02453, Grade: C\",\"StationNumber: 97MR16, Year: 1997, PEL ratio: 0.05074, Grade: C\",\"StationNumber: 97MR17, Year: 1997, PEL ratio: 0.02537, Grade: C\",\"StationNumber: 97MR18, Year: 1997, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 97MR19, Year: 1997, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 97MR20, Year: 1997, PEL ratio: 0.05581, Grade: C\",\"StationNumber: 97MR21, Year: 1997, PEL ratio: 0.04083, Grade: C\",\"StationNumber: 97MTB02, Year: 1997, PEL ratio: 0.02552, Grade: C\",\"StationNumber: 97MTB03, Year: 1997, PEL ratio: 0.00549, Grade: A\",\"StationNumber: 97MTB04, Year: 1997, PEL ratio: 0.0071, Grade: A\",\"StationNumber: 97MTB05, Year: 1997, PEL ratio: 0.00589, Grade: A\",\"StationNumber: 97MTB07, Year: 1997, PEL ratio: 0.01701, Grade: B\",\"StationNumber: 97MTB09, Year: 1997, PEL ratio: 0.01016, Grade: B\",\"StationNumber: 97MTB10, Year: 1997, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 97MTB12, Year: 1997, PEL ratio: 0.01224, Grade: B\",\"StationNumber: 97MTB14, Year: 1997, PEL ratio: 0.04718, Grade: C\",\"StationNumber: 97MTB15, Year: 1997, PEL ratio: 0.00923, Grade: B\",\"StationNumber: 97MTB16, Year: 1997, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 97MTB17, Year: 1997, PEL ratio: 0.01049, Grade: B\",\"StationNumber: 97MTB18, Year: 1997, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 97MTB19, Year: 1997, PEL ratio: 0.00548, Grade: A\",\"StationNumber: 97MTB23, Year: 1997, PEL ratio: 0.01245, Grade: B\",\"StationNumber: 97MTB24, Year: 1997, PEL ratio: 0.01036, Grade: B\",\"StationNumber: 97MTB25, Year: 1997, PEL ratio: 0.0052, Grade: A\",\"StationNumber: 97MTB26, Year: 1997, PEL ratio: 0.00284, Grade: A\",\"StationNumber: 97MTB30, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97MTB31, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97MTB32, Year: 1997, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 97MTB35, Year: 1997, PEL ratio: 0.00417, Grade: A\",\"StationNumber: 97OTB03, Year: 1997, PEL ratio: 0.08428, Grade: C\",\"StationNumber: 97OTB06, Year: 1997, PEL ratio: 0.00508, Grade: A\",\"StationNumber: 97OTB07, Year: 1997, PEL ratio: 0.04147, Grade: C\",\"StationNumber: 97OTB11, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97OTB12, Year: 1997, PEL ratio: 0.00901, Grade: B\",\"StationNumber: 97OTB13, Year: 1997, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 97OTB17, Year: 1997, PEL ratio: 0.02135, Grade: C\",\"StationNumber: 97OTB18, Year: 1997, PEL ratio: 0.01639, Grade: B\",\"StationNumber: 97OTB19, Year: 1997, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 97OTB20, Year: 1997, PEL ratio: 0.0108, Grade: B\",\"StationNumber: 97OTB22, Year: 1997, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 97OTB23, Year: 1997, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 97OTB24, Year: 1997, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 97OTB26, Year: 1997, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 97OTB27, Year: 1997, PEL ratio: 0.0027, Grade: A\",\"StationNumber: 97OTB29, Year: 1997, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 97TCB01, Year: 1997, PEL ratio: 0.03736, Grade: C\",\"StationNumber: 97TCB02, Year: 1997, PEL ratio: 0.05752, Grade: C\",\"StationNumber: 97TCB03, Year: 1997, PEL ratio: 0.07413, Grade: C\",\"StationNumber: 97TCB04, Year: 1997, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 97TCB05, Year: 1997, PEL ratio: 0.03402, Grade: C\",\"StationNumber: 97TCB06, Year: 1997, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 97TCB07, Year: 1997, PEL ratio: 0.06132, Grade: C\",\"StationNumber: 97TCB08, Year: 1997, PEL ratio: 0.0461, Grade: C\",\"StationNumber: 98BCB06, Year: 1998, PEL ratio: 0.00538, Grade: A\",\"StationNumber: 98BCB09, Year: 1998, PEL ratio: 0.00305, Grade: A\",\"StationNumber: 98BCB11, Year: 1998, PEL ratio: 0.00393, Grade: A\",\"StationNumber: 98BCB12, Year: 1998, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 98BCB15, Year: 1998, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 98BCB17, Year: 1998, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 98BCB21, Year: 1998, PEL ratio: 0.0041, Grade: A\",\"StationNumber: 98BCB27, Year: 1998, PEL ratio: 0.01015, Grade: B\",\"StationNumber: 98BCB28, Year: 1998, PEL ratio: 0.0098, Grade: B\",\"StationNumber: 98BCB32, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98BCB38, Year: 1998, PEL ratio: 0.00578, Grade: A\",\"StationNumber: 98BCB40, Year: 1998, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 98BCB43, Year: 1998, PEL ratio: 0.00199, Grade: A\",\"StationNumber: 98BCB46, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98BCB57/1, Year: 1998, PEL ratio: 0.06999, Grade: C\",\"StationNumber: 98BCB58/1, Year: 1998, PEL ratio: 0.1367, Grade: D\",\"StationNumber: 98BCB58/2, Year: 1998, PEL ratio: 0.02526, Grade: C\",\"StationNumber: 98BCB59/1, Year: 1998, PEL ratio: 0.00363, Grade: A\",\"StationNumber: 98BCB59/2, Year: 1998, PEL ratio: 0.02915, Grade: C\",\"StationNumber: 98BCB60/2, Year: 1998, PEL ratio: 0.00939, Grade: B\",\"StationNumber: 98BCB60/4, Year: 1998, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 98HB003, Year: 1998, PEL ratio: 0.0024, Grade: A\",\"StationNumber: 98HB006, Year: 1998, PEL ratio: 0.97324, Grade: F\",\"StationNumber: 98HB014, Year: 1998, PEL ratio: 0.0317, Grade: C\",\"StationNumber: 98HB016, Year: 1998, PEL ratio: 0.11511, Grade: D\",\"StationNumber: 98HB017, Year: 1998, PEL ratio: 0.00283, Grade: A\",\"StationNumber: 98HB024, Year: 1998, PEL ratio: 0.03375, Grade: C\",\"StationNumber: 98HB030, Year: 1998, PEL ratio: 0.00478, Grade: A\",\"StationNumber: 98HB049, Year: 1998, PEL ratio: 0.00685, Grade: A\",\"StationNumber: 98HB052, Year: 1998, PEL ratio: 0.04381, Grade: C\",\"StationNumber: 98HB056, Year: 1998, PEL ratio: 0.00367, Grade: A\",\"StationNumber: 98HB059, Year: 1998, PEL ratio: 0.00786, Grade: B\",\"StationNumber: 98HB069, Year: 1998, PEL ratio: 0.01266, Grade: B\",\"StationNumber: 98HB080, Year: 1998, PEL ratio: 0.10159, Grade: D\",\"StationNumber: 98HB089, Year: 1998, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 98HB130, Year: 1998, PEL ratio: 0.00708, Grade: A\",\"StationNumber: 98HB153, Year: 1998, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 98HB171, Year: 1998, PEL ratio: 0.07363, Grade: C\",\"StationNumber: 98HB180, Year: 1998, PEL ratio: 0.02965, Grade: C\",\"StationNumber: 98HB224, Year: 1998, PEL ratio: 0.0387, Grade: C\",\"StationNumber: 98HB237, Year: 1998, PEL ratio: 0.00906, Grade: B\",\"StationNumber: 98HB245, Year: 1998, PEL ratio: 0.02123, Grade: C\",\"StationNumber: 98HB252, Year: 1998, PEL ratio: 0.04475, Grade: C\",\"StationNumber: 98HB280, Year: 1998, PEL ratio: 0.01676, Grade: B\",\"StationNumber: 98HB789, Year: 1998, PEL ratio: 0.07519, Grade: C\",\"StationNumber: 98HBDIcanal, Year: 1998, PEL ratio: 0.0396, Grade: C\",\"StationNumber: 98HBspark, Year: 1998, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 98LTB0014, Year: 1998, PEL ratio: 0.01019, Grade: B\",\"StationNumber: 98LTB0025, Year: 1998, PEL ratio: 0.00349, Grade: A\",\"StationNumber: 98LTB0049, Year: 1998, PEL ratio: 0.0015, Grade: A\",\"StationNumber: 98LTB0095, Year: 1998, PEL ratio: 0.00272, Grade: A\",\"StationNumber: 98LTB0123, Year: 1998, PEL ratio: 0.0128, Grade: B\",\"StationNumber: 98LTB0144, Year: 1998, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 98LTB0151, Year: 1998, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 98LTB0168, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98LTB0183, Year: 1998, PEL ratio: 0.00534, Grade: A\",\"StationNumber: 98LTB0223, Year: 1998, PEL ratio: 0.00257, Grade: A\",\"StationNumber: 98LTB0244, Year: 1998, PEL ratio: 0.00145, Grade: A\",\"StationNumber: 98LTB0273, Year: 1998, PEL ratio: 0.00217, Grade: A\",\"StationNumber: 98LTB0307, Year: 1998, PEL ratio: 0.00156, Grade: A\",\"StationNumber: 98LTB0364, Year: 1998, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 98LTB0393, Year: 1998, PEL ratio: 0.00144, Grade: A\",\"StationNumber: 98LTB0762, Year: 1998, PEL ratio: 0.00278, Grade: A\",\"StationNumber: 98LTB1057, Year: 1998, PEL ratio: 0.00277, Grade: A\",\"StationNumber: 98MR09, Year: 1998, PEL ratio: 0.00264, Grade: A\",\"StationNumber: 98MR10, Year: 1998, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 98MR11, Year: 1998, PEL ratio: 0.02354, Grade: C\",\"StationNumber: 98MR12, Year: 1998, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 98MR13, Year: 1998, PEL ratio: 0.04647, Grade: C\",\"StationNumber: 98MR14, Year: 1998, PEL ratio: 0.01126, Grade: B\",\"StationNumber: 98MR15, Year: 1998, PEL ratio: 0.01005, Grade: B\",\"StationNumber: 98MR16, Year: 1998, PEL ratio: 0.0221, Grade: C\",\"StationNumber: 98MR17, Year: 1998, PEL ratio: 0.01136, Grade: B\",\"StationNumber: 98MR18, Year: 1998, PEL ratio: 0.00778, Grade: B\",\"StationNumber: 98MR19, Year: 1998, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 98MR20, Year: 1998, PEL ratio: 0.00821, Grade: B\",\"StationNumber: 98MR21, Year: 1998, PEL ratio: 0.18896, Grade: D\",\"StationNumber: 98MTB0032, Year: 1998, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 98MTB0035, Year: 1998, PEL ratio: 0.02315, Grade: C\",\"StationNumber: 98MTB0052, Year: 1998, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 98MTB0067, Year: 1998, PEL ratio: 0.00681, Grade: A\",\"StationNumber: 98MTB0090, Year: 1998, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 98MTB0103, Year: 1998, PEL ratio: 0.00342, Grade: A\",\"StationNumber: 98MTB0133, Year: 1998, PEL ratio: 0.00293, Grade: A\",\"StationNumber: 98MTB0187, Year: 1998, PEL ratio: 0.0175, Grade: B\",\"StationNumber: 98MTB0191, Year: 1998, PEL ratio: 0.29254, Grade: F\",\"StationNumber: 98MTB0208, Year: 1998, PEL ratio: 0.00527, Grade: A\",\"StationNumber: 98MTB0270, Year: 1998, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 98MTB0275, Year: 1998, PEL ratio: 0.00228, Grade: A\",\"StationNumber: 98MTB0283, Year: 1998, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 98MTB0322, Year: 1998, PEL ratio: 0.00756, Grade: B\",\"StationNumber: 98MTB0331, Year: 1998, PEL ratio: 0.00226, Grade: A\",\"StationNumber: 98MTB0416, Year: 1998, PEL ratio: 0.01759, Grade: B\",\"StationNumber: 98MTB0460, Year: 1998, PEL ratio: 0.00109, Grade: A\",\"StationNumber: 98MTB0688, Year: 1998, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 98MTB0694, Year: 1998, PEL ratio: 0.00183, Grade: A\",\"StationNumber: 98MTB1036, Year: 1998, PEL ratio: 0.00193, Grade: A\",\"StationNumber: 98OTB0036, Year: 1998, PEL ratio: 0.0377, Grade: C\",\"StationNumber: 98OTB0039, Year: 1998, PEL ratio: 0.01561, Grade: B\",\"StationNumber: 98OTB0048, Year: 1998, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 98OTB0056, Year: 1998, PEL ratio: 0.01204, Grade: B\",\"StationNumber: 98OTB0125, Year: 1998, PEL ratio: 0.00279, Grade: A\",\"StationNumber: 98OTB0177, Year: 1998, PEL ratio: 0.00429, Grade: A\",\"StationNumber: 98OTB0185, Year: 1998, PEL ratio: 0.00276, Grade: A\",\"StationNumber: 98OTB0199, Year: 1998, PEL ratio: 0.0051, Grade: A\",\"StationNumber: 98OTB0232, Year: 1998, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 98OTB0239, Year: 1998, PEL ratio: 0.00934, Grade: B\",\"StationNumber: 98OTB0274, Year: 1998, PEL ratio: 0.00653, Grade: A\",\"StationNumber: 98OTB0425, Year: 1998, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 98OTB0596, Year: 1998, PEL ratio: 0.13969, Grade: D\",\"StationNumber: 98OTB0721, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98OTB1140, Year: 1998, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 98OTB1227, Year: 1998, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 98TCB01, Year: 1998, PEL ratio: 0.00905, Grade: B\",\"StationNumber: 98TCB02, Year: 1998, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 98TCB04, Year: 1998, PEL ratio: 0.0067, Grade: A\",\"StationNumber: 98TCB05, Year: 1998, PEL ratio: 0.00686, Grade: A\",\"StationNumber: 98TCB06, Year: 1998, PEL ratio: 0.00741, Grade: A\",\"StationNumber: 98TCB07, Year: 1998, PEL ratio: 0.0084, Grade: B\",\"StationNumber: 98TCB08, Year: 1998, PEL ratio: 0.02781, Grade: C\",\"StationNumber: 99BCB2025, Year: 1999, PEL ratio: 0.005, Grade: A\",\"StationNumber: 99BCB2041, Year: 1999, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 99BCB2063, Year: 1999, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 99BCB2069, Year: 1999, PEL ratio: 0.00888, Grade: B\",\"StationNumber: 99BCB2070, Year: 1999, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 99BCB2086, Year: 1999, PEL ratio: 0.00471, Grade: A\",\"StationNumber: 99BCB2094, Year: 1999, PEL ratio: 0.02788, Grade: C\",\"StationNumber: 99BCB2115, Year: 1999, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 99BCB2132, Year: 1999, PEL ratio: 0.00326, Grade: A\",\"StationNumber: 99BCB2295, Year: 1999, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 99BCB2358, Year: 1999, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 99BCB2423, Year: 1999, PEL ratio: 0.00676, Grade: A\",\"StationNumber: 99BCB2514, Year: 1999, PEL ratio: 0.00801, Grade: B\",\"StationNumber: 99BCB2585, Year: 1999, PEL ratio: 0.00657, Grade: A\",\"StationNumber: 99BCB57/1, Year: 1999, PEL ratio: 0.05417, Grade: C\",\"StationNumber: 99BCB58/1, Year: 1999, PEL ratio: 0.09826, Grade: D\",\"StationNumber: 99BCB58/2, Year: 1999, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 99BCB59/1, Year: 1999, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 99BCB59/2, Year: 1999, PEL ratio: 0.02713, Grade: C\",\"StationNumber: 99BCB60/2, Year: 1999, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 99BCB60/4, Year: 1999, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 99HB2001, Year: 1999, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 99HB2012, Year: 1999, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 99HB2013, Year: 1999, PEL ratio: 0.01091, Grade: B\",\"StationNumber: 99HB2019, Year: 1999, PEL ratio: 0.01342, Grade: B\",\"StationNumber: 99HB2040, Year: 1999, PEL ratio: 0.00861, Grade: B\",\"StationNumber: 99HB2041, Year: 1999, PEL ratio: 0.00984, Grade: B\",\"StationNumber: 99HB2043, Year: 1999, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 99HB2044, Year: 1999, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 99HB2051, Year: 1999, PEL ratio: 0.04843, Grade: C\",\"StationNumber: 99HB2055, Year: 1999, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 99HB2058, Year: 1999, PEL ratio: 0.1295, Grade: D\",\"StationNumber: 99HB2061, Year: 1999, PEL ratio: 0.66795, Grade: F\",\"StationNumber: 99HB2085, Year: 1999, PEL ratio: 0.11485, Grade: D\",\"StationNumber: 99HB2094, Year: 1999, PEL ratio: 0.00687, Grade: A\",\"StationNumber: 99HB2124, Year: 1999, PEL ratio: 0.08012, Grade: C\",\"StationNumber: 99HB2157, Year: 1999, PEL ratio: 0.01348, Grade: B\",\"StationNumber: 99HB2176, Year: 1999, PEL ratio: 0.07747, Grade: C\",\"StationNumber: 99HB2207, Year: 1999, PEL ratio: 0.09551, Grade: D\",\"StationNumber: 99HB2214, Year: 1999, PEL ratio: 0.00568, Grade: A\",\"StationNumber: 99HB2233, Year: 1999, PEL ratio: 0.04361, Grade: C\",\"StationNumber: 99HB2393, Year: 1999, PEL ratio: 0.01757, Grade: B\",\"StationNumber: 99HB2445, Year: 1999, PEL ratio: 0.0179, Grade: B\",\"StationNumber: 99HB2757, Year: 1999, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 99LTB2014, Year: 1999, PEL ratio: 0.00357, Grade: A\",\"StationNumber: 99LTB2021, Year: 1999, PEL ratio: 0.02082, Grade: C\",\"StationNumber: 99LTB2041, Year: 1999, PEL ratio: 0.01184, Grade: B\",\"StationNumber: 99LTB2071, Year: 1999, PEL ratio: 0.04983, Grade: C\",\"StationNumber: 99LTB2112, Year: 1999, PEL ratio: 0.01, Grade: B\",\"StationNumber: 99LTB2124, Year: 1999, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 99LTB2203, Year: 1999, PEL ratio: 0.03476, Grade: C\",\"StationNumber: 99LTB2214, Year: 1999, PEL ratio: 0.00338, Grade: A\",\"StationNumber: 99LTB2247, Year: 1999, PEL ratio: 0.00398, Grade: A\",\"StationNumber: 99LTB2267, Year: 1999, PEL ratio: 0.00762, Grade: B\",\"StationNumber: 99LTB2277, Year: 1999, PEL ratio: 0.00489, Grade: A\",\"StationNumber: 99LTB2290, Year: 1999, PEL ratio: 0.00641, Grade: A\",\"StationNumber: 99LTB2327, Year: 1999, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 99LTB2546, Year: 1999, PEL ratio: 0.00355, Grade: A\",\"StationNumber: 99LTB2617, Year: 1999, PEL ratio: 0.0074, Grade: A\",\"StationNumber: 99LTB3020, Year: 1999, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 99MR09, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99MR10, Year: 1999, PEL ratio: 0.00816, Grade: B\",\"StationNumber: 99MR11, Year: 1999, PEL ratio: 0.01449, Grade: B\",\"StationNumber: 99MR12, Year: 1999, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 99MR13, Year: 1999, PEL ratio: 0.00522, Grade: A\",\"StationNumber: 99MR14, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99MR15, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MR16, Year: 1999, PEL ratio: 0.00967, Grade: B\",\"StationNumber: 99MR17, Year: 1999, PEL ratio: 0.00407, Grade: A\",\"StationNumber: 99MR18, Year: 1999, PEL ratio: 0.00432, Grade: A\",\"StationNumber: 99MR19, Year: 1999, PEL ratio: 0.007, Grade: A\",\"StationNumber: 99MR20, Year: 1999, PEL ratio: 0.00696, Grade: A\",\"StationNumber: 99MR21, Year: 1999, PEL ratio: 0.00917, Grade: B\",\"StationNumber: 99MTB2029, Year: 1999, PEL ratio: 0.00978, Grade: B\",\"StationNumber: 99MTB2059, Year: 1999, PEL ratio: 0.00849, Grade: B\",\"StationNumber: 99MTB2060, Year: 1999, PEL ratio: 0.00498, Grade: A\",\"StationNumber: 99MTB2108, Year: 1999, PEL ratio: 0.01361, Grade: B\",\"StationNumber: 99MTB2109, Year: 1999, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 99MTB2116, Year: 1999, PEL ratio: 0.01071, Grade: B\",\"StationNumber: 99MTB2129, Year: 1999, PEL ratio: 0.00543, Grade: A\",\"StationNumber: 99MTB2149, Year: 1999, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 99MTB2165, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MTB2240, Year: 1999, PEL ratio: 0.00258, Grade: A\",\"StationNumber: 99MTB2243, Year: 1999, PEL ratio: 0.00684, Grade: A\",\"StationNumber: 99MTB2244, Year: 1999, PEL ratio: 0.00704, Grade: A\",\"StationNumber: 99MTB2253, Year: 1999, PEL ratio: 0.00506, Grade: A\",\"StationNumber: 99MTB2268, Year: 1999, PEL ratio: 0.00697, Grade: A\",\"StationNumber: 99MTB2274, Year: 1999, PEL ratio: 0.00654, Grade: A\",\"StationNumber: 99MTB2291, Year: 1999, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 99MTB2358, Year: 1999, PEL ratio: 0.02137, Grade: C\",\"StationNumber: 99MTB2385, Year: 1999, PEL ratio: 0.00448, Grade: A\",\"StationNumber: 99MTB2554, Year: 1999, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 99MTB2598, Year: 1999, PEL ratio: 0.00643, Grade: A\",\"StationNumber: 99MTB2642, Year: 1999, PEL ratio: 0.00161, Grade: A\",\"StationNumber: 99OTB2002, Year: 1999, PEL ratio: 0.00876, Grade: B\",\"StationNumber: 99OTB2005, Year: 1999, PEL ratio: 0.00294, Grade: A\",\"StationNumber: 99OTB2009, Year: 1999, PEL ratio: 0.00343, Grade: A\",\"StationNumber: 99OTB2010, Year: 1999, PEL ratio: 0.00216, Grade: A\",\"StationNumber: 99OTB2022, Year: 1999, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 99OTB2045, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99OTB2067, Year: 1999, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 99OTB2111, Year: 1999, PEL ratio: 0.00613, Grade: A\",\"StationNumber: 99OTB2121, Year: 1999, PEL ratio: 0.00637, Grade: A\",\"StationNumber: 99OTB2225, Year: 1999, PEL ratio: 0.00677, Grade: A\",\"StationNumber: 99OTB2296, Year: 1999, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 99OTB2313, Year: 1999, PEL ratio: 0.01389, Grade: B\",\"StationNumber: 99OTB2316, Year: 1999, PEL ratio: 0.02452, Grade: C\",\"StationNumber: 99OTB2331, Year: 1999, PEL ratio: 0.00962, Grade: B\",\"StationNumber: 99OTB2395, Year: 1999, PEL ratio: 0.00307, Grade: A\",\"StationNumber: 99OTB2482, Year: 1999, PEL ratio: 0.02893, Grade: C\",\"StationNumber: 99OTB2908, Year: 1999, PEL ratio: 0.00461, Grade: A\",\"StationNumber: 99OTB2994, Year: 1999, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 99OTB3046, Year: 1999, PEL ratio: 0.01179, Grade: B\",\"StationNumber: 99TCB01, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99TCB02, Year: 1999, PEL ratio: 0.00618, Grade: A\",\"StationNumber: 99TCB03, Year: 1999, PEL ratio: 0.01419, Grade: B\",\"StationNumber: 99TCB04, Year: 1999, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 99TCB05, Year: 1999, PEL ratio: 0.00868, Grade: B\",\"StationNumber: 99TCB06, Year: 1999, PEL ratio: 0.01238, Grade: B\",\"StationNumber: 99TCB07, Year: 1999, PEL ratio: 0.01057, Grade: B\",\"StationNumber: 99TCB08, Year: 1999, PEL ratio: 0.00285, Grade: A\",\"StationNumber: 00BCB4000, Year: 2000, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 00BCB4001, Year: 2000, PEL ratio: 0.03269, Grade: C\",\"StationNumber: 00BCB4004, Year: 2000, PEL ratio: 0.02038, Grade: B\",\"StationNumber: 00BCB4033, Year: 2000, PEL ratio: 0.08678, Grade: D\",\"StationNumber: 00BCB4034, Year: 2000, PEL ratio: 0.03197, Grade: C\",\"StationNumber: 00BCB4037, Year: 2000, PEL ratio: 0.02797, Grade: C\",\"StationNumber: 00BCB4038, Year: 2000, PEL ratio: 0.81297, Grade: F\",\"StationNumber: 00BCB4041, Year: 2000, PEL ratio: 0.03473, Grade: C\",\"StationNumber: 00BCB4042, Year: 2000, PEL ratio: 0.03588, Grade: C\",\"StationNumber: 00BCB4046, Year: 2000, PEL ratio: 0.03579, Grade: C\",\"StationNumber: 00BCB4079, Year: 2000, PEL ratio: 0.02888, Grade: C\",\"StationNumber: 00BCB4084, Year: 2000, PEL ratio: 0.03169, Grade: C\",\"StationNumber: 00BCB4090, Year: 2000, PEL ratio: 0.0329, Grade: C\",\"StationNumber: 00BCB4100, Year: 2000, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 00BCB4124, Year: 2000, PEL ratio: 0.0309, Grade: C\",\"StationNumber: 00BCB4165, Year: 2000, PEL ratio: 0.03378, Grade: C\",\"StationNumber: 00BCB4174, Year: 2000, PEL ratio: 0.03618, Grade: C\",\"StationNumber: 00BCB4207, Year: 2000, PEL ratio: 0.03283, Grade: C\",\"StationNumber: 00BCB4268, Year: 2000, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 00BCB4299, Year: 2000, PEL ratio: 0.04446, Grade: C\",\"StationNumber: 00BCB4312, Year: 2000, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 00BCB58/1, Year: 2000, PEL ratio: 0.18329, Grade: D\",\"StationNumber: 00BCB58/2, Year: 2000, PEL ratio: 0.04382, Grade: C\",\"StationNumber: 00BCB59/1, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00BCB59/2, Year: 2000, PEL ratio: 0.06279, Grade: C\",\"StationNumber: 00BCB60/2, Year: 2000, PEL ratio: 0.04105, Grade: C\",\"StationNumber: 00BCB60/4, Year: 2000, PEL ratio: 0.04149, Grade: C\",\"StationNumber: 00HB4002, Year: 2000, PEL ratio: 0.04724, Grade: C\",\"StationNumber: 00HB4006, Year: 2000, PEL ratio: 0.04834, Grade: C\",\"StationNumber: 00HB4019, Year: 2000, PEL ratio: 0.10805, Grade: D\",\"StationNumber: 00HB4023, Year: 2000, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 00HB4032, Year: 2000, PEL ratio: 0.04776, Grade: C\",\"StationNumber: 00HB4033, Year: 2000, PEL ratio: 0.05791, Grade: C\",\"StationNumber: 00HB4038, Year: 2000, PEL ratio: 0.04416, Grade: C\",\"StationNumber: 00HB4047, Year: 2000, PEL ratio: 0.04742, Grade: C\",\"StationNumber: 00HB4058, Year: 2000, PEL ratio: 0.01604, Grade: B\",\"StationNumber: 00HB4077, Year: 2000, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 00HB4082, Year: 2000, PEL ratio: 0.04468, Grade: C\",\"StationNumber: 00HB4083, Year: 2000, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 00HB4093, Year: 2000, PEL ratio: 0.06406, Grade: C\",\"StationNumber: 00HB4094, Year: 2000, PEL ratio: 0.06062, Grade: C\",\"StationNumber: 00HB4100, Year: 2000, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 00HB4106, Year: 2000, PEL ratio: 0.09251, Grade: D\",\"StationNumber: 00HB4144, Year: 2000, PEL ratio: 0.53451, Grade: F\",\"StationNumber: 00HB4152, Year: 2000, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 00HB4267, Year: 2000, PEL ratio: 0.06204, Grade: C\",\"StationNumber: 00HB4291, Year: 2000, PEL ratio: 0.05424, Grade: C\",\"StationNumber: 00HB4316, Year: 2000, PEL ratio: 0.05501, Grade: C\",\"StationNumber: 00HB4505, Year: 2000, PEL ratio: 0.06045, Grade: C\",\"StationNumber: 00LTB4039, Year: 2000, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 00LTB4051, Year: 2000, PEL ratio: 0.19124, Grade: D\",\"StationNumber: 00LTB4066, Year: 2000, PEL ratio: 0.05414, Grade: C\",\"StationNumber: 00LTB4117, Year: 2000, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 00LTB4151, Year: 2000, PEL ratio: 0.03939, Grade: C\",\"StationNumber: 00LTB4185, Year: 2000, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 00LTB4286, Year: 2000, PEL ratio: 0.05463, Grade: C\",\"StationNumber: 00LTB4340, Year: 2000, PEL ratio: 0.05064, Grade: C\",\"StationNumber: 00LTB4484, Year: 2000, PEL ratio: 0.0517, Grade: C\",\"StationNumber: 00LTB4487, Year: 2000, PEL ratio: 0.04958, Grade: C\",\"StationNumber: 00LTB4513, Year: 2000, PEL ratio: 0.05351, Grade: C\",\"StationNumber: 00LTB4529, Year: 2000, PEL ratio: 0.049, Grade: C\",\"StationNumber: 00LTB4536, Year: 2000, PEL ratio: 0.05145, Grade: C\",\"StationNumber: 00LTB4637, Year: 2000, PEL ratio: 0.04148, Grade: C\",\"StationNumber: 00LTB4677, Year: 2000, PEL ratio: 0.04906, Grade: C\",\"StationNumber: 00LTB4730, Year: 2000, PEL ratio: 0.04835, Grade: C\",\"StationNumber: 00LTB4749, Year: 2000, PEL ratio: 0.04495, Grade: C\",\"StationNumber: 00MR09, Year: 2000, PEL ratio: 0.04919, Grade: C\",\"StationNumber: 00MR10, Year: 2000, PEL ratio: 0.06403, Grade: C\",\"StationNumber: 00MR11, Year: 2000, PEL ratio: 0.05939, Grade: C\",\"StationNumber: 00MR12, Year: 2000, PEL ratio: 0.05823, Grade: C\",\"StationNumber: 00MR13, Year: 2000, PEL ratio: 0.06481, Grade: C\",\"StationNumber: 00MR14, Year: 2000, PEL ratio: 0.0737, Grade: C\",\"StationNumber: 00MR15, Year: 2000, PEL ratio: 0.0527, Grade: C\",\"StationNumber: 00MR16, Year: 2000, PEL ratio: 0.08249, Grade: C\",\"StationNumber: 00MR17, Year: 2000, PEL ratio: 0.08444, Grade: C\",\"StationNumber: 00MR18, Year: 2000, PEL ratio: 0.08809, Grade: D\",\"StationNumber: 00MR19, Year: 2000, PEL ratio: 0.08127, Grade: C\",\"StationNumber: 00MR20, Year: 2000, PEL ratio: 0.11393, Grade: D\",\"StationNumber: 00MR21, Year: 2000, PEL ratio: 0.07841, Grade: C\",\"StationNumber: 00MTB4030, Year: 2000, PEL ratio: 0.07289, Grade: C\",\"StationNumber: 00MTB4032, Year: 2000, PEL ratio: 0.04097, Grade: C\",\"StationNumber: 00MTB4041, Year: 2000, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 00MTB4061, Year: 2000, PEL ratio: 0.05053, Grade: C\",\"StationNumber: 00MTB4072, Year: 2000, PEL ratio: 0.04819, Grade: C\",\"StationNumber: 00MTB4086, Year: 2000, PEL ratio: 0.03955, Grade: C\",\"StationNumber: 00MTB4090, Year: 2000, PEL ratio: 0.33753, Grade: F\",\"StationNumber: 00MTB4098, Year: 2000, PEL ratio: 0.0477, Grade: C\",\"StationNumber: 00MTB4100, Year: 2000, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 00MTB4106, Year: 2000, PEL ratio: 0.04444, Grade: C\",\"StationNumber: 00MTB4159, Year: 2000, PEL ratio: 0.0458, Grade: C\",\"StationNumber: 00MTB4181, Year: 2000, PEL ratio: 0.05132, Grade: C\",\"StationNumber: 00MTB4193, Year: 2000, PEL ratio: 0.03968, Grade: C\",\"StationNumber: 00MTB4201, Year: 2000, PEL ratio: 0.05155, Grade: C\",\"StationNumber: 00MTB4249, Year: 2000, PEL ratio: 0.033, Grade: C\",\"StationNumber: 00MTB4265, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB4310, Year: 2000, PEL ratio: 0.04594, Grade: C\",\"StationNumber: 00MTB4363, Year: 2000, PEL ratio: 0.07539, Grade: C\",\"StationNumber: 00MTB4504, Year: 2000, PEL ratio: 0.04349, Grade: C\",\"StationNumber: 00MTB4584, Year: 2000, PEL ratio: 0.04498, Grade: C\",\"StationNumber: 00MTB4653, Year: 2000, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 00MTB4845, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB5125, Year: 2000, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 00OTB4011, Year: 2000, PEL ratio: 0.03964, Grade: C\",\"StationNumber: 00OTB4019, Year: 2000, PEL ratio: 0.04292, Grade: C\",\"StationNumber: 00OTB4037, Year: 2000, PEL ratio: 0.05343, Grade: C\",\"StationNumber: 00OTB4040, Year: 2000, PEL ratio: 0.04909, Grade: C\",\"StationNumber: 00OTB4044, Year: 2000, PEL ratio: 0.04244, Grade: C\",\"StationNumber: 00OTB4096, Year: 2000, PEL ratio: 0.03974, Grade: C\",\"StationNumber: 00OTB4105, Year: 2000, PEL ratio: 0.04131, Grade: C\",\"StationNumber: 00OTB4123, Year: 2000, PEL ratio: 0.06385, Grade: C\",\"StationNumber: 00OTB4132, Year: 2000, PEL ratio: 0.06645, Grade: C\",\"StationNumber: 00OTB4138, Year: 2000, PEL ratio: 0.05762, Grade: C\",\"StationNumber: 00OTB4149, Year: 2000, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 00OTB4192, Year: 2000, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 00OTB4217, Year: 2000, PEL ratio: 0.05579, Grade: C\",\"StationNumber: 00OTB4254, Year: 2000, PEL ratio: 0.0437, Grade: C\",\"StationNumber: 00OTB4278, Year: 2000, PEL ratio: 0.25534, Grade: D\",\"StationNumber: 00OTB4402, Year: 2000, PEL ratio: 0.0459, Grade: C\",\"StationNumber: 00OTB4407, Year: 2000, PEL ratio: 0.04964, Grade: C\",\"StationNumber: 00OTB4650, Year: 2000, PEL ratio: 0.04792, Grade: C\",\"StationNumber: 00OTB4946, Year: 2000, PEL ratio: 0.05067, Grade: C\",\"StationNumber: 00TCB01, Year: 2000, PEL ratio: 0.04699, Grade: C\",\"StationNumber: 00TCB02, Year: 2000, PEL ratio: 0.04205, Grade: C\",\"StationNumber: 00TCB03, Year: 2000, PEL ratio: 0.03651, Grade: C\",\"StationNumber: 00TCB04, Year: 2000, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 00TCB05, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00TCB06, Year: 2000, PEL ratio: 0.04342, Grade: C\",\"StationNumber: 00TCB07, Year: 2000, PEL ratio: 0.04274, Grade: C\",\"StationNumber: 00TCB08, Year: 2000, PEL ratio: 0.04303, Grade: C\",\"StationNumber: 01BCB57/1, Year: 2001, PEL ratio: 0.05374, Grade: C\",\"StationNumber: 01BCB58/1, Year: 2001, PEL ratio: 0.12193, Grade: D\",\"StationNumber: 01BCB58/2, Year: 2001, PEL ratio: 0.027, Grade: C\",\"StationNumber: 01BCB59/1, Year: 2001, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 01BCB59/2, Year: 2001, PEL ratio: 0.04048, Grade: C\",\"StationNumber: 01BCB60/2, Year: 2001, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 01BCB60/4, Year: 2001, PEL ratio: 0.01424, Grade: B\",\"StationNumber: 01BCB6001, Year: 2001, PEL ratio: 0.0563, Grade: C\",\"StationNumber: 01BCB6009, Year: 2001, PEL ratio: 0.04348, Grade: C\",\"StationNumber: 01BCB6018, Year: 2001, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 01BCB6019, Year: 2001, PEL ratio: 0.01532, Grade: B\",\"StationNumber: 01BCB6031, Year: 2001, PEL ratio: 0.02161, Grade: C\",\"StationNumber: 01BCB6063, Year: 2001, PEL ratio: 0.0077, Grade: B\",\"StationNumber: 01BCB6072, Year: 2001, PEL ratio: 0.03264, Grade: C\",\"StationNumber: 01BCB6089, Year: 2001, PEL ratio: 0.02463, Grade: C\",\"StationNumber: 01BCB6109, Year: 2001, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 01BCB6114, Year: 2001, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 01BCB6152, Year: 2001, PEL ratio: 0.0269, Grade: C\",\"StationNumber: 01BCB6178, Year: 2001, PEL ratio: 0.02377, Grade: C\",\"StationNumber: 01BCB6190, Year: 2001, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 01BCB6230, Year: 2001, PEL ratio: 0.05637, Grade: C\",\"StationNumber: 01BCB6263, Year: 2001, PEL ratio: 0.04428, Grade: C\",\"StationNumber: 01BCB6359, Year: 2001, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 01HB6019, Year: 2001, PEL ratio: 0.13163, Grade: D\",\"StationNumber: 01HB6022, Year: 2001, PEL ratio: 0.07712, Grade: C\",\"StationNumber: 01HB6032, Year: 2001, PEL ratio: 0.03892, Grade: C\",\"StationNumber: 01HB6035, Year: 2001, PEL ratio: 0.06366, Grade: C\",\"StationNumber: 01HB6045, Year: 2001, PEL ratio: 0.04136, Grade: C\",\"StationNumber: 01HB6064, Year: 2001, PEL ratio: 0.08868, Grade: D\",\"StationNumber: 01HB6066, Year: 2001, PEL ratio: 0.04113, Grade: C\",\"StationNumber: 01HB6087, Year: 2001, PEL ratio: 0.07944, Grade: C\",\"StationNumber: 01HB6093, Year: 2001, PEL ratio: 0.0345, Grade: C\",\"StationNumber: 01HB6102, Year: 2001, PEL ratio: 0.04233, Grade: C\",\"StationNumber: 01HB6108, Year: 2001, PEL ratio: 0.07274, Grade: C\",\"StationNumber: 01HB6131, Year: 2001, PEL ratio: 0.03937, Grade: C\",\"StationNumber: 01HB6140, Year: 2001, PEL ratio: 0.03728, Grade: C\",\"StationNumber: 01HB6145, Year: 2001, PEL ratio: 0.03711, Grade: C\",\"StationNumber: 01HB6159, Year: 2001, PEL ratio: 0.05123, Grade: C\",\"StationNumber: 01HB6186, Year: 2001, PEL ratio: 0.11466, Grade: D\",\"StationNumber: 01HB6187, Year: 2001, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 01HB6249, Year: 2001, PEL ratio: 0.02319, Grade: C\",\"StationNumber: 01HB6261, Year: 2001, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 01HB6264, Year: 2001, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 01HB6283, Year: 2001, PEL ratio: 0.03557, Grade: C\",\"StationNumber: 01HB6305, Year: 2001, PEL ratio: 0.0378, Grade: C\",\"StationNumber: 01HB6374, Year: 2001, PEL ratio: 0.09193, Grade: D\",\"StationNumber: 01HB6453, Year: 2001, PEL ratio: 0.05442, Grade: C\",\"StationNumber: 01HB6537, Year: 2001, PEL ratio: 0.03766, Grade: C\",\"StationNumber: 01LTB6026, Year: 2001, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 01LTB6027, Year: 2001, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 01LTB6050, Year: 2001, PEL ratio: 0.04404, Grade: C\",\"StationNumber: 01LTB6104, Year: 2001, PEL ratio: 0.0209, Grade: C\",\"StationNumber: 01LTB6120, Year: 2001, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 01LTB6122, Year: 2001, PEL ratio: 0.05444, Grade: C\",\"StationNumber: 01LTB6158, Year: 2001, PEL ratio: 0.09951, Grade: D\",\"StationNumber: 01LTB6302, Year: 2001, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 01LTB6346, Year: 2001, PEL ratio: 0.00189, Grade: A\",\"StationNumber: 01LTB6380, Year: 2001, PEL ratio: 0.04602, Grade: C\",\"StationNumber: 01LTB6595, Year: 2001, PEL ratio: 0.04587, Grade: C\",\"StationNumber: 01LTB6869, Year: 2001, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 01MR09, Year: 2001, PEL ratio: 0.00085, Grade: A\",\"StationNumber: 01MR12, Year: 2001, PEL ratio: 0.00214, Grade: A\",\"StationNumber: 01MR13, Year: 2001, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 01MR14, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR17, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR18, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR19, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR20, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR21, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MTB6002, Year: 2001, PEL ratio: 0.04429, Grade: C\",\"StationNumber: 01MTB6011, Year: 2001, PEL ratio: 0.03017, Grade: C\",\"StationNumber: 01MTB6014, Year: 2001, PEL ratio: 0.03931, Grade: C\",\"StationNumber: 01MTB6049, Year: 2001, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 01MTB6059, Year: 2001, PEL ratio: 0.03202, Grade: C\",\"StationNumber: 01MTB6064, Year: 2001, PEL ratio: 0.02866, Grade: C\",\"StationNumber: 01MTB6068, Year: 2001, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 01MTB6080, Year: 2001, PEL ratio: 0.03134, Grade: C\",\"StationNumber: 01MTB6133, Year: 2001, PEL ratio: 0.03877, Grade: C\",\"StationNumber: 01MTB6154, Year: 2001, PEL ratio: 0.03081, Grade: C\",\"StationNumber: 01MTB6188, Year: 2001, PEL ratio: 0.04865, Grade: C\",\"StationNumber: 01MTB6189, Year: 2001, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 01MTB6196, Year: 2001, PEL ratio: 0.03661, Grade: C\",\"StationNumber: 01MTB6229, Year: 2001, PEL ratio: 0.03253, Grade: C\",\"StationNumber: 01MTB6257, Year: 2001, PEL ratio: 0.04035, Grade: C\",\"StationNumber: 01MTB6265, Year: 2001, PEL ratio: 0.03247, Grade: C\",\"StationNumber: 01MTB6290, Year: 2001, PEL ratio: 0.03227, Grade: C\",\"StationNumber: 01MTB6325, Year: 2001, PEL ratio: 0.03135, Grade: C\",\"StationNumber: 01MTB6327, Year: 2001, PEL ratio: 0.0343, Grade: C\",\"StationNumber: 01MTB6328, Year: 2001, PEL ratio: 0.0383, Grade: C\",\"StationNumber: 01MTB6464, Year: 2001, PEL ratio: 0.03323, Grade: C\",\"StationNumber: 01MTB6495, Year: 2001, PEL ratio: 0.03374, Grade: C\",\"StationNumber: 01MTB6527, Year: 2001, PEL ratio: 0.0365, Grade: C\",\"StationNumber: 01MTB6638, Year: 2001, PEL ratio: 0.03712, Grade: C\",\"StationNumber: 01MTB6699, Year: 2001, PEL ratio: 0.03196, Grade: C\",\"StationNumber: 01MTB7153, Year: 2001, PEL ratio: 0.02961, Grade: C\",\"StationNumber: 01OTB6010, Year: 2001, PEL ratio: 0.0366, Grade: C\",\"StationNumber: 01OTB6017, Year: 2001, PEL ratio: 0.0392, Grade: C\",\"StationNumber: 01OTB6021, Year: 2001, PEL ratio: 0.035, Grade: C\",\"StationNumber: 01OTB6022, Year: 2001, PEL ratio: 0.03556, Grade: C\",\"StationNumber: 01OTB6025, Year: 2001, PEL ratio: 0.0835, Grade: C\",\"StationNumber: 01OTB6028, Year: 2001, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 01OTB6078, Year: 2001, PEL ratio: 0.03835, Grade: C\",\"StationNumber: 01OTB6103, Year: 2001, PEL ratio: 0.04375, Grade: C\",\"StationNumber: 01OTB6135, Year: 2001, PEL ratio: 0.1479, Grade: D\",\"StationNumber: 01OTB6152, Year: 2001, PEL ratio: 0.17372, Grade: D\",\"StationNumber: 01OTB6178, Year: 2001, PEL ratio: 0.04426, Grade: C\",\"StationNumber: 01OTB6186, Year: 2001, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 01OTB6234, Year: 2001, PEL ratio: 0.03095, Grade: C\",\"StationNumber: 01OTB6239, Year: 2001, PEL ratio: 0.07735, Grade: C\",\"StationNumber: 01OTB6441, Year: 2001, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 01OTB6784, Year: 2001, PEL ratio: 0.03879, Grade: C\",\"StationNumber: 01OTB6830, Year: 2001, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 01SAFHAB, Year: 2001, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 01TCB02, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB03, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB04, Year: 2001, PEL ratio: 0.00149, Grade: A\",\"StationNumber: 01TCB06, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB07, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 02BCB05, Year: 2002, PEL ratio: 0.09921, Grade: D\",\"StationNumber: 02BCB20, Year: 2002, PEL ratio: 0.03895, Grade: C\",\"StationNumber: 02BCB32, Year: 2002, PEL ratio: 0.02428, Grade: C\",\"StationNumber: 02BCB52, Year: 2002, PEL ratio: 0.03041, Grade: C\",\"StationNumber: 02BCB62, Year: 2002, PEL ratio: 0.07542, Grade: C\",\"StationNumber: 02BCB69, Year: 2002, PEL ratio: 0.02783, Grade: C\",\"StationNumber: 02BCB74, Year: 2002, PEL ratio: 0.02301, Grade: C\",\"StationNumber: 02BCB83, Year: 2002, PEL ratio: 0.02746, Grade: C\",\"StationNumber: 02BCB90, Year: 2002, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 02DH09-1, Year: 2002, PEL ratio: 0.19807, Grade: D\",\"StationNumber: 02DH09-2, Year: 2002, PEL ratio: 0.12272, Grade: D\",\"StationNumber: 02DH09-3, Year: 2002, PEL ratio: 0.30626, Grade: F\",\"StationNumber: 02DH11A-1, Year: 2002, PEL ratio: 0.10175, Grade: D\",\"StationNumber: 02DH11A-2, Year: 2002, PEL ratio: 0.11172, Grade: D\",\"StationNumber: 02DH11A-3, Year: 2002, PEL ratio: 0.14465, Grade: D\",\"StationNumber: 02DH11B-1, Year: 2002, PEL ratio: 0.10113, Grade: D\",\"StationNumber: 02DH11B-4, Year: 2002, PEL ratio: 0.12537, Grade: D\",\"StationNumber: 02DH11B-5, Year: 2002, PEL ratio: 0.13789, Grade: D\",\"StationNumber: 02HB09, Year: 2002, PEL ratio: 0.16733, Grade: D\",\"StationNumber: 02HB20, Year: 2002, PEL ratio: 0.02678, Grade: C\",\"StationNumber: 02HB21, Year: 2002, PEL ratio: 0.02244, Grade: C\",\"StationNumber: 02HB27, Year: 2002, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 02HB39, Year: 2002, PEL ratio: 0.21706, Grade: D\",\"StationNumber: 02HB42, Year: 2002, PEL ratio: 0.02683, Grade: C\",\"StationNumber: 02HB49, Year: 2002, PEL ratio: 0.03845, Grade: C\",\"StationNumber: 02HB50, Year: 2002, PEL ratio: 0.32514, Grade: F\",\"StationNumber: 02HB51, Year: 2002, PEL ratio: 0.06603, Grade: C\",\"StationNumber: 02HB55, Year: 2002, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 02LTB01, Year: 2002, PEL ratio: 0.02663, Grade: C\",\"StationNumber: 02LTB02, Year: 2002, PEL ratio: 0.02978, Grade: C\",\"StationNumber: 02LTB03, Year: 2002, PEL ratio: 0.02042, Grade: B\",\"StationNumber: 02LTB04, Year: 2002, PEL ratio: 0.02782, Grade: C\",\"StationNumber: 02LTB05, Year: 2002, PEL ratio: 0.02348, Grade: C\",\"StationNumber: 02LTB06, Year: 2002, PEL ratio: 0.04038, Grade: C\",\"StationNumber: 02LTB07, Year: 2002, PEL ratio: 0.03048, Grade: C\",\"StationNumber: 02LTB08, Year: 2002, PEL ratio: 0.02061, Grade: C\",\"StationNumber: 02LTB09, Year: 2002, PEL ratio: 0.02023, Grade: B\",\"StationNumber: 02MR02, Year: 2002, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 02MR04, Year: 2002, PEL ratio: 0.03337, Grade: C\",\"StationNumber: 02MR06, Year: 2002, PEL ratio: 0.14519, Grade: D\",\"StationNumber: 02MR08, Year: 2002, PEL ratio: 0.02507, Grade: C\",\"StationNumber: 02MR10, Year: 2002, PEL ratio: 0.04251, Grade: C\",\"StationNumber: 02MR11, Year: 2002, PEL ratio: 0.03906, Grade: C\",\"StationNumber: 02MR12, Year: 2002, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 02DH08-1, Year: 2002, PEL ratio: 0.09017, Grade: D\",\"StationNumber: 02DH08-2, Year: 2002, PEL ratio: 0.10363, Grade: D\",\"StationNumber: 02DH08-3, Year: 2002, PEL ratio: 0.08051, Grade: C\",\"StationNumber: 02DH14-1, Year: 2002, PEL ratio: 0.18895, Grade: D\",\"StationNumber: 02DH14-3, Year: 2002, PEL ratio: 0.12398, Grade: D\",\"StationNumber: 02DH14-4, Year: 2002, PEL ratio: 0.13475, Grade: D\",\"StationNumber: 02DH15-1, Year: 2002, PEL ratio: 0.03722, Grade: C\",\"StationNumber: 02DH15-2, Year: 2002, PEL ratio: 0.03193, Grade: C\",\"StationNumber: 02DH15-5, Year: 2002, PEL ratio: 0.10865, Grade: D\",\"StationNumber: 02MTB11, Year: 2002, PEL ratio: 0.03207, Grade: C\",\"StationNumber: 02MTB12, Year: 2002, PEL ratio: 0.03458, Grade: C\",\"StationNumber: 02MTB18, Year: 2002, PEL ratio: 0.06402, Grade: C\",\"StationNumber: 02MTB19, Year: 2002, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 02MTB21, Year: 2002, PEL ratio: 0.07645, Grade: C\",\"StationNumber: 02MTB23, Year: 2002, PEL ratio: 0.04157, Grade: C\",\"StationNumber: 02MTB27, Year: 2002, PEL ratio: 0.03517, Grade: C\",\"StationNumber: 02MTB29, Year: 2002, PEL ratio: 0.03409, Grade: C\",\"StationNumber: 02MTB32, Year: 2002, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 02MTB34, Year: 2002, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 02DH03-2, Year: 2002, PEL ratio: 0.15, Grade: D\",\"StationNumber: 02DH03-4, Year: 2002, PEL ratio: 0.15355, Grade: D\",\"StationNumber: 02DH03-5, Year: 2002, PEL ratio: 0.18194, Grade: D\",\"StationNumber: 02DH05-3, Year: 2002, PEL ratio: 0.02701, Grade: C\",\"StationNumber: 02DH05-4, Year: 2002, PEL ratio: 0.08347, Grade: C\",\"StationNumber: 02DH05-5, Year: 2002, PEL ratio: 0.03648, Grade: C\",\"StationNumber: 02DH07-1, Year: 2002, PEL ratio: 0.08738, Grade: D\",\"StationNumber: 02DH07-2, Year: 2002, PEL ratio: 0.09842, Grade: D\",\"StationNumber: 02DH07-3, Year: 2002, PEL ratio: 0.09265, Grade: D\",\"StationNumber: 02DH18-1, Year: 2002, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 02DH18-2, Year: 2002, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 02DH18-3, Year: 2002, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 02DH20-3, Year: 2002, PEL ratio: 0.09118, Grade: D\",\"StationNumber: 02DH20-4, Year: 2002, PEL ratio: 0.0982, Grade: D\",\"StationNumber: 02DH20-5, Year: 2002, PEL ratio: 0.08451, Grade: C\",\"StationNumber: 02DH21A-1, Year: 2002, PEL ratio: 0.08952, Grade: D\",\"StationNumber: 02DH21A-3, Year: 2002, PEL ratio: 0.10866, Grade: D\",\"StationNumber: 02DH21A-5, Year: 2002, PEL ratio: 0.11684, Grade: D\",\"StationNumber: 02DH21B-1, Year: 2002, PEL ratio: 0.13203, Grade: D\",\"StationNumber: 02DH21B-3, Year: 2002, PEL ratio: 0.12143, Grade: D\",\"StationNumber: 02DH21B-4, Year: 2002, PEL ratio: 0.1119, Grade: D\",\"StationNumber: 02OTB02, Year: 2002, PEL ratio: 0.02894, Grade: C\",\"StationNumber: 02OTB04, Year: 2002, PEL ratio: 0.03118, Grade: C\",\"StationNumber: 02OTB27, Year: 2002, PEL ratio: 0.02515, Grade: C\",\"StationNumber: 02OTB49, Year: 2002, PEL ratio: 0.0374, Grade: C\",\"StationNumber: 02OTB50, Year: 2002, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 02OTB52, Year: 2002, PEL ratio: 0.03468, Grade: C\",\"StationNumber: 02OTB60, Year: 2002, PEL ratio: 0.0399, Grade: C\",\"StationNumber: 02OTB66, Year: 2002, PEL ratio: 0.04346, Grade: C\",\"StationNumber: 02TCB03, Year: 2002, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 02TCB05, Year: 2002, PEL ratio: 0.05723, Grade: C\",\"StationNumber: 02TCB07, Year: 2002, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 02TCB09, Year: 2002, PEL ratio: 0.041, Grade: C\",\"StationNumber: 03BCB107, Year: 2003, PEL ratio: 0.04845, Grade: C\",\"StationNumber: 03BCB120, Year: 2003, PEL ratio: 0.07755, Grade: C\",\"StationNumber: 03BCB126, Year: 2003, PEL ratio: 0.05955, Grade: C\",\"StationNumber: 03BCB190, Year: 2003, PEL ratio: 0.07526, Grade: C\",\"StationNumber: 03BCB230, Year: 2003, PEL ratio: 0.04192, Grade: C\",\"StationNumber: 03BCB242, Year: 2003, PEL ratio: 0.1701, Grade: D\",\"StationNumber: 03BCB278, Year: 2003, PEL ratio: 0.04954, Grade: C\",\"StationNumber: 03BCB287, Year: 2003, PEL ratio: 0.0426, Grade: C\",\"StationNumber: 03BCB338, Year: 2003, PEL ratio: 0.05523, Grade: C\",\"StationNumber: 03BCB439, Year: 2003, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 03HB01, Year: 2003, PEL ratio: 0.05953, Grade: C\",\"StationNumber: 03HB02, Year: 2003, PEL ratio: 0.09513, Grade: D\",\"StationNumber: 03HB04, Year: 2003, PEL ratio: 0.05264, Grade: C\",\"StationNumber: 03HB06, Year: 2003, PEL ratio: 0.2787, Grade: D\",\"StationNumber: 03HB09, Year: 2003, PEL ratio: 2.62709, Grade: F\",\"StationNumber: 03HB10, Year: 2003, PEL ratio: 0.07527, Grade: C\",\"StationNumber: 03HB11, Year: 2003, PEL ratio: 0.05917, Grade: C\",\"StationNumber: 03HB12, Year: 2003, PEL ratio: 0.08962, Grade: D\",\"StationNumber: 03HB14, Year: 2003, PEL ratio: 0.05233, Grade: C\",\"StationNumber: 03HB16, Year: 2003, PEL ratio: 0.08913, Grade: D\",\"StationNumber: 03HB18, Year: 2003, PEL ratio: 0.07056, Grade: C\",\"StationNumber: 03HB21, Year: 2003, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 03HB27, Year: 2003, PEL ratio: 0.11208, Grade: D\",\"StationNumber: 03HB28, Year: 2003, PEL ratio: 0.13538, Grade: D\",\"StationNumber: 03HB30, Year: 2003, PEL ratio: 0.05101, Grade: C\",\"StationNumber: 03HB32, Year: 2003, PEL ratio: 0.08584, Grade: D\",\"StationNumber: 03HB33, Year: 2003, PEL ratio: 0.04992, Grade: C\",\"StationNumber: 03HB34, Year: 2003, PEL ratio: 0.05096, Grade: C\",\"StationNumber: 03HB37, Year: 2003, PEL ratio: 0.17023, Grade: D\",\"StationNumber: 03HB38, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03HB41, Year: 2003, PEL ratio: 0.07016, Grade: C\",\"StationNumber: 03HB42, Year: 2003, PEL ratio: 0.11971, Grade: D\",\"StationNumber: 03HB44, Year: 2003, PEL ratio: 0.04723, Grade: C\",\"StationNumber: 03HB47, Year: 2003, PEL ratio: 0.0484, Grade: C\",\"StationNumber: 03HB50, Year: 2003, PEL ratio: 0.04892, Grade: C\",\"StationNumber: 03HB51, Year: 2003, PEL ratio: 0.07784, Grade: C\",\"StationNumber: 03HB52, Year: 2003, PEL ratio: 0.10156, Grade: D\",\"StationNumber: 03HB53, Year: 2003, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 03LTB01, Year: 2003, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 03LTB02, Year: 2003, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 03LTB03, Year: 2003, PEL ratio: 0.04888, Grade: C\",\"StationNumber: 03LTB04, Year: 2003, PEL ratio: 0.05672, Grade: C\",\"StationNumber: 03LTB05, Year: 2003, PEL ratio: 0.03249, Grade: C\",\"StationNumber: 03LTB06, Year: 2003, PEL ratio: 0.04582, Grade: C\",\"StationNumber: 03LTB07, Year: 2003, PEL ratio: 0.05602, Grade: C\",\"StationNumber: 03LTB08, Year: 2003, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 03LTB09, Year: 2003, PEL ratio: 0.04842, Grade: C\",\"StationNumber: 03LTB10, Year: 2003, PEL ratio: 0.03141, Grade: C\",\"StationNumber: 03LTB11, Year: 2003, PEL ratio: 0.05041, Grade: C\",\"StationNumber: 03LTB12, Year: 2003, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 03MR02, Year: 2003, PEL ratio: 0.07551, Grade: C\",\"StationNumber: 03MR04, Year: 2003, PEL ratio: 0.06186, Grade: C\",\"StationNumber: 03MR06, Year: 2003, PEL ratio: 0.11177, Grade: D\",\"StationNumber: 03MR07, Year: 2003, PEL ratio: 0.04271, Grade: C\",\"StationNumber: 03MR08, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03MR09, Year: 2003, PEL ratio: 0.04126, Grade: C\",\"StationNumber: 03MR10, Year: 2003, PEL ratio: 0.05761, Grade: C\",\"StationNumber: 03MTB03, Year: 2003, PEL ratio: 0.05627, Grade: C\",\"StationNumber: 03MTB08, Year: 2003, PEL ratio: 0.06744, Grade: C\",\"StationNumber: 03MTB10, Year: 2003, PEL ratio: 0.04607, Grade: C\",\"StationNumber: 03MTB11, Year: 2003, PEL ratio: 0.0679, Grade: C\",\"StationNumber: 03MTB13, Year: 2003, PEL ratio: 0.08571, Grade: D\",\"StationNumber: 03MTB14, Year: 2003, PEL ratio: 0.07424, Grade: C\",\"StationNumber: 03MTB15, Year: 2003, PEL ratio: 0.07661, Grade: C\",\"StationNumber: 03MTB16, Year: 2003, PEL ratio: 0.07141, Grade: C\",\"StationNumber: 03MTB17, Year: 2003, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 03MTB18, Year: 2003, PEL ratio: 0.06047, Grade: C\",\"StationNumber: 03MTB19, Year: 2003, PEL ratio: 0.0635, Grade: C\",\"StationNumber: 03MTB21, Year: 2003, PEL ratio: 0.06752, Grade: C\",\"StationNumber: 03MTB24, Year: 2003, PEL ratio: 0.05516, Grade: C\",\"StationNumber: 03MTB25, Year: 2003, PEL ratio: 0.06373, Grade: C\",\"StationNumber: 03MTB27, Year: 2003, PEL ratio: 0.05651, Grade: C\",\"StationNumber: 03MTB28, Year: 2003, PEL ratio: 0.06933, Grade: C\",\"StationNumber: 03MTB30, Year: 2003, PEL ratio: 0.43636, Grade: F\",\"StationNumber: 03MTB31, Year: 2003, PEL ratio: 0.07005, Grade: C\",\"StationNumber: 03MTB32, Year: 2003, PEL ratio: 0.05667, Grade: C\",\"StationNumber: 03MTB33, Year: 2003, PEL ratio: 0.07011, Grade: C\",\"StationNumber: 03MTB34, Year: 2003, PEL ratio: 0.06682, Grade: C\",\"StationNumber: 03MTB35, Year: 2003, PEL ratio: 0.07621, Grade: C\",\"StationNumber: 03OTB157, Year: 2003, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 03OTB200, Year: 2003, PEL ratio: 0.16694, Grade: D\",\"StationNumber: 03OTB413, Year: 2003, PEL ratio: 0.05894, Grade: C\",\"StationNumber: 03OTB414, Year: 2003, PEL ratio: 0.04976, Grade: C\",\"StationNumber: 03OTB507, Year: 2003, PEL ratio: 0.07151, Grade: C\",\"StationNumber: 03OTB623, Year: 2003, PEL ratio: 0.19749, Grade: D\",\"StationNumber: 03OTB706, Year: 2003, PEL ratio: 0.11944, Grade: D\",\"StationNumber: 03OTB794, Year: 2003, PEL ratio: 0.05991, Grade: C\",\"StationNumber: 03OTB929, Year: 2003, PEL ratio: 0.09521, Grade: D\",\"StationNumber: 03TCB01, Year: 2003, PEL ratio: 0.03963, Grade: C\",\"StationNumber: 03TCB03, Year: 2003, PEL ratio: 0.04315, Grade: C\",\"StationNumber: 03TCB05, Year: 2003, PEL ratio: 0.04569, Grade: C\",\"StationNumber: 04BCB01, Year: 2004, PEL ratio: 0.03545, Grade: C\",\"StationNumber: 04BCB02, Year: 2004, PEL ratio: 0.03051, Grade: C\",\"StationNumber: 04BCB03, Year: 2004, PEL ratio: 0.1299, Grade: D\",\"StationNumber: 04BCB04, Year: 2004, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 04BCB05, Year: 2004, PEL ratio: 0.02806, Grade: C\",\"StationNumber: 04BCB06, Year: 2004, PEL ratio: 0.05131, Grade: C\",\"StationNumber: 04BCB07, Year: 2004, PEL ratio: 0.02049, Grade: B\",\"StationNumber: 04BCB08, Year: 2004, PEL ratio: 0.03435, Grade: C\",\"StationNumber: 04BCB09, Year: 2004, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 04BCB10, Year: 2004, PEL ratio: 0.03223, Grade: C\",\"StationNumber: 04HB01, Year: 2004, PEL ratio: 0.01651, Grade: B\",\"StationNumber: 04HB02, Year: 2004, PEL ratio: 0.0358, Grade: C\",\"StationNumber: 04HB03, Year: 2004, PEL ratio: 0.12867, Grade: D\",\"StationNumber: 04HB04, Year: 2004, PEL ratio: 0.08639, Grade: D\",\"StationNumber: 04HB05, Year: 2004, PEL ratio: 0.02012, Grade: B\",\"StationNumber: 04HB06, Year: 2004, PEL ratio: 0.02029, Grade: B\",\"StationNumber: 04HB07, Year: 2004, PEL ratio: 0.02572, Grade: C\",\"StationNumber: 04HB08, Year: 2004, PEL ratio: 0.02404, Grade: C\",\"StationNumber: 04HB09, Year: 2004, PEL ratio: 0.04005, Grade: C\",\"StationNumber: 04HB10, Year: 2004, PEL ratio: 0.18388, Grade: D\",\"StationNumber: 04HB11, Year: 2004, PEL ratio: 0.02011, Grade: B\",\"StationNumber: 04HB12, Year: 2004, PEL ratio: 0.11403, Grade: D\",\"StationNumber: 04HB13, Year: 2004, PEL ratio: 0.14349, Grade: D\",\"StationNumber: 04HB14, Year: 2004, PEL ratio: 0.02109, Grade: C\",\"StationNumber: 04HB15, Year: 2004, PEL ratio: 0.02016, Grade: B\",\"StationNumber: 04HB16, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04HB17, Year: 2004, PEL ratio: 0.18354, Grade: D\",\"StationNumber: 04HB18, Year: 2004, PEL ratio: 0.4013, Grade: F\",\"StationNumber: 04HB19, Year: 2004, PEL ratio: 0.12724, Grade: D\",\"StationNumber: 04HB20, Year: 2004, PEL ratio: 0.02398, Grade: C\",\"StationNumber: 04HB21, Year: 2004, PEL ratio: 0.02873, Grade: C\",\"StationNumber: 04HB23, Year: 2004, PEL ratio: 0.02633, Grade: C\",\"StationNumber: 04HB24, Year: 2004, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 04HB25, Year: 2004, PEL ratio: 0.05102, Grade: C\",\"StationNumber: 04HB26, Year: 2004, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 04LTB01, Year: 2004, PEL ratio: 0.01329, Grade: B\",\"StationNumber: 04LTB02, Year: 2004, PEL ratio: 0.02081, Grade: C\",\"StationNumber: 04LTB03, Year: 2004, PEL ratio: 0.02025, Grade: B\",\"StationNumber: 04LTB04, Year: 2004, PEL ratio: 0.01177, Grade: B\",\"StationNumber: 04LTB05, Year: 2004, PEL ratio: 0.0211, Grade: C\",\"StationNumber: 04LTB06, Year: 2004, PEL ratio: 0.01694, Grade: B\",\"StationNumber: 04LTB07, Year: 2004, PEL ratio: 0.01745, Grade: B\",\"StationNumber: 04LTB08, Year: 2004, PEL ratio: 0.03084, Grade: C\",\"StationNumber: 04LTB09, Year: 2004, PEL ratio: 0.02538, Grade: C\",\"StationNumber: 04LTB10, Year: 2004, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 04LTB11, Year: 2004, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 04MR01, Year: 2004, PEL ratio: 0.08777, Grade: D\",\"StationNumber: 04MR02, Year: 2004, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 04MR03, Year: 2004, PEL ratio: 0.01966, Grade: B\",\"StationNumber: 04MR04, Year: 2004, PEL ratio: 0.04362, Grade: C\",\"StationNumber: 04MR05, Year: 2004, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 04MR06, Year: 2004, PEL ratio: 0.01585, Grade: B\",\"StationNumber: 04MR08, Year: 2004, PEL ratio: 0.06183, Grade: C\",\"StationNumber: 04MR09, Year: 2004, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 04MR10, Year: 2004, PEL ratio: 0.02989, Grade: C\",\"StationNumber: 04MR11, Year: 2004, PEL ratio: 0.04141, Grade: C\",\"StationNumber: 04MTB01, Year: 2004, PEL ratio: 0.0143, Grade: B\",\"StationNumber: 04MTB02, Year: 2004, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 04MTB04, Year: 2004, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 04MTB05, Year: 2004, PEL ratio: 0.02789, Grade: C\",\"StationNumber: 04MTB06, Year: 2004, PEL ratio: 0.01916, Grade: B\",\"StationNumber: 04MTB07, Year: 2004, PEL ratio: 0.01837, Grade: B\",\"StationNumber: 04MTB08, Year: 2004, PEL ratio: 0.02226, Grade: C\",\"StationNumber: 04MTB09, Year: 2004, PEL ratio: 0.0162, Grade: B\",\"StationNumber: 04MTB10, Year: 2004, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 04MTB11, Year: 2004, PEL ratio: 0.02662, Grade: C\",\"StationNumber: 04MTB12, Year: 2004, PEL ratio: 0.0287, Grade: C\",\"StationNumber: 04MTB13, Year: 2004, PEL ratio: 0.03236, Grade: C\",\"StationNumber: 04MTB14, Year: 2004, PEL ratio: 0.03029, Grade: C\",\"StationNumber: 04MTB15, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04MTB16, Year: 2004, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 04MTB17, Year: 2004, PEL ratio: 0.02028, Grade: B\",\"StationNumber: 04MTB18, Year: 2004, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 04MTB19, Year: 2004, PEL ratio: 0.03315, Grade: C\",\"StationNumber: 04MTB20, Year: 2004, PEL ratio: 0.02831, Grade: C\",\"StationNumber: 04MTB21, Year: 2004, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 04MTB22, Year: 2004, PEL ratio: 0.02665, Grade: C\",\"StationNumber: 04MTB24, Year: 2004, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 04OTB01, Year: 2004, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 04OTB02, Year: 2004, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 04OTB03, Year: 2004, PEL ratio: 0.03106, Grade: C\",\"StationNumber: 04OTB04, Year: 2004, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 04OTB05, Year: 2004, PEL ratio: 0.12197, Grade: D\",\"StationNumber: 04OTB06, Year: 2004, PEL ratio: 0.02194, Grade: C\",\"StationNumber: 04OTB07, Year: 2004, PEL ratio: 0.10091, Grade: D\",\"StationNumber: 04OTB08, Year: 2004, PEL ratio: 0.0248, Grade: C\",\"StationNumber: 04OTB09, Year: 2004, PEL ratio: 0.0243, Grade: C\",\"StationNumber: 04TCB07, Year: 2004, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05BCB01, Year: 2005, PEL ratio: 0.02056, Grade: C\",\"StationNumber: 05BCB02, Year: 2005, PEL ratio: 0.01422, Grade: B\",\"StationNumber: 05BCB03, Year: 2005, PEL ratio: 0.0279, Grade: C\",\"StationNumber: 05BCB04, Year: 2005, PEL ratio: 0.01565, Grade: B\",\"StationNumber: 05BCB05, Year: 2005, PEL ratio: 0.94385, Grade: F\",\"StationNumber: 05BCB06, Year: 2005, PEL ratio: 0.03608, Grade: C\",\"StationNumber: 05BCB07, Year: 2005, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 05BCB08, Year: 2005, PEL ratio: 0.0183, Grade: B\",\"StationNumber: 05BCB09, Year: 2005, PEL ratio: 0.02383, Grade: C\",\"StationNumber: 05BCB10, Year: 2005, PEL ratio: 0.01397, Grade: B\",\"StationNumber: 05HB01, Year: 2005, PEL ratio: 0.02071, Grade: C\",\"StationNumber: 05HB02, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05HB03, Year: 2005, PEL ratio: 0.01997, Grade: B\",\"StationNumber: 05HB04, Year: 2005, PEL ratio: 0.0672, Grade: C\",\"StationNumber: 05HB05, Year: 2005, PEL ratio: 0.10587, Grade: D\",\"StationNumber: 05HB06, Year: 2005, PEL ratio: 0.07366, Grade: C\",\"StationNumber: 05HB07, Year: 2005, PEL ratio: 0.01737, Grade: B\",\"StationNumber: 05HB08, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05HB09, Year: 2005, PEL ratio: 0.03392, Grade: C\",\"StationNumber: 05HB10, Year: 2005, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 05HB11, Year: 2005, PEL ratio: 0.01724, Grade: B\",\"StationNumber: 05HB12, Year: 2005, PEL ratio: 1.00876, Grade: F\",\"StationNumber: 05HB13, Year: 2005, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05HB14, Year: 2005, PEL ratio: 0.15213, Grade: D\",\"StationNumber: 05HB15, Year: 2005, PEL ratio: 0.07682, Grade: C\",\"StationNumber: 05HB16, Year: 2005, PEL ratio: 0.11966, Grade: D\",\"StationNumber: 05HB17, Year: 2005, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 05HB18, Year: 2005, PEL ratio: 0.02303, Grade: C\",\"StationNumber: 05HB19, Year: 2005, PEL ratio: 0.01643, Grade: B\",\"StationNumber: 05HB20, Year: 2005, PEL ratio: 0.01686, Grade: B\",\"StationNumber: 05HB21, Year: 2005, PEL ratio: 0.0478, Grade: C\",\"StationNumber: 05HB22, Year: 2005, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 05HB23, Year: 2005, PEL ratio: 0.02946, Grade: C\",\"StationNumber: 05HB24, Year: 2005, PEL ratio: 0.01751, Grade: B\",\"StationNumber: 05LTB01, Year: 2005, PEL ratio: 0.02599, Grade: C\",\"StationNumber: 05LTB02, Year: 2005, PEL ratio: 0.01545, Grade: B\",\"StationNumber: 05LTB03, Year: 2005, PEL ratio: 0.01154, Grade: B\",\"StationNumber: 05LTB04, Year: 2005, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 05LTB05, Year: 2005, PEL ratio: 0.01619, Grade: B\",\"StationNumber: 05LTB06, Year: 2005, PEL ratio: 0.0193, Grade: B\",\"StationNumber: 05LTB07, Year: 2005, PEL ratio: 0.01402, Grade: B\",\"StationNumber: 05LTB08, Year: 2005, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 05LTB09, Year: 2005, PEL ratio: 0.02347, Grade: C\",\"StationNumber: 05LTB10, Year: 2005, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 05LTB11, Year: 2005, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 05MR02, Year: 2005, PEL ratio: 0.01442, Grade: B\",\"StationNumber: 05MR04, Year: 2005, PEL ratio: 0.02173, Grade: C\",\"StationNumber: 05MR06, Year: 2005, PEL ratio: 0.01537, Grade: B\",\"StationNumber: 05MR08, Year: 2005, PEL ratio: 0.01574, Grade: B\",\"StationNumber: 05MR09, Year: 2005, PEL ratio: 0.01971, Grade: B\",\"StationNumber: 05MR11, Year: 2005, PEL ratio: 0.08271, Grade: C\",\"StationNumber: 05MTB01, Year: 2005, PEL ratio: 0.02214, Grade: C\",\"StationNumber: 05MTB02, Year: 2005, PEL ratio: 0.0218, Grade: C\",\"StationNumber: 05MTB03, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05MTB04, Year: 2005, PEL ratio: 0.01475, Grade: B\",\"StationNumber: 05MTB05, Year: 2005, PEL ratio: 0.01741, Grade: B\",\"StationNumber: 05MTB06, Year: 2005, PEL ratio: 0.01714, Grade: B\",\"StationNumber: 05MTB07, Year: 2005, PEL ratio: 0.03643, Grade: C\",\"StationNumber: 05MTB08, Year: 2005, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 05MTB09, Year: 2005, PEL ratio: 0.01427, Grade: B\",\"StationNumber: 05MTB10, Year: 2005, PEL ratio: 0.01804, Grade: B\",\"StationNumber: 05MTB11, Year: 2005, PEL ratio: 0.01786, Grade: B\",\"StationNumber: 05MTB12, Year: 2005, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 05MTB13, Year: 2005, PEL ratio: 0.01404, Grade: B\",\"StationNumber: 05MTB14, Year: 2005, PEL ratio: 0.02263, Grade: C\",\"StationNumber: 05MTB15, Year: 2005, PEL ratio: 0.10298, Grade: D\",\"StationNumber: 05MTB16, Year: 2005, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 05MTB17, Year: 2005, PEL ratio: 0.01324, Grade: B\",\"StationNumber: 05MTB18, Year: 2005, PEL ratio: 0.01423, Grade: B\",\"StationNumber: 05MTB19, Year: 2005, PEL ratio: 0.01217, Grade: B\",\"StationNumber: 05MTB20, Year: 2005, PEL ratio: 0.01481, Grade: B\",\"StationNumber: 05MTB21, Year: 2005, PEL ratio: 0.03798, Grade: C\",\"StationNumber: 05MTB22, Year: 2005, PEL ratio: 0.0196, Grade: B\",\"StationNumber: 05OTB01, Year: 2005, PEL ratio: 0.01507, Grade: B\",\"StationNumber: 05OTB02, Year: 2005, PEL ratio: 0.02508, Grade: C\",\"StationNumber: 05OTB03, Year: 2005, PEL ratio: 0.01587, Grade: B\",\"StationNumber: 05OTB04, Year: 2005, PEL ratio: 0.02237, Grade: C\",\"StationNumber: 05OTB05, Year: 2005, PEL ratio: 0.0268, Grade: C\",\"StationNumber: 05OTB06, Year: 2005, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 05OTB07, Year: 2005, PEL ratio: 0.02997, Grade: C\",\"StationNumber: 05OTB08, Year: 2005, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 05OTB09, Year: 2005, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 05OTB10, Year: 2005, PEL ratio: 0.01673, Grade: B\",\"StationNumber: 05TCB01, Year: 2005, PEL ratio: 0.02249, Grade: C\",\"StationNumber: 05TCB03, Year: 2005, PEL ratio: 0.01896, Grade: B\",\"StationNumber: 05TCB05, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05TCB07, Year: 2005, PEL ratio: 0.11125, Grade: D\",\"StationNumber: 05TCB10, Year: 2005, PEL ratio: 0.01684, Grade: B\",\"StationNumber: 06BCB01, Year: 2006, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 06BCB02, Year: 2006, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 06BCB03, Year: 2006, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 06BCB04, Year: 2006, PEL ratio: 0.04285, Grade: C\",\"StationNumber: 06BCB05, Year: 2006, PEL ratio: 0.02977, Grade: C\",\"StationNumber: 06BCB06, Year: 2006, PEL ratio: 0.03224, Grade: C\",\"StationNumber: 06BCB07, Year: 2006, PEL ratio: 0.05354, Grade: C\",\"StationNumber: 06BCB08, Year: 2006, PEL ratio: 0.03691, Grade: C\",\"StationNumber: 06BCB09, Year: 2006, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 06HB01, Year: 2006, PEL ratio: 0.05456, Grade: C\",\"StationNumber: 06HB02, Year: 2006, PEL ratio: 0.07105, Grade: C\",\"StationNumber: 06HB03, Year: 2006, PEL ratio: 0.09993, Grade: D\",\"StationNumber: 06HB04, Year: 2006, PEL ratio: 0.04056, Grade: C\",\"StationNumber: 06HB05, Year: 2006, PEL ratio: 0.05604, Grade: C\",\"StationNumber: 06HB06, Year: 2006, PEL ratio: 0.05301, Grade: C\",\"StationNumber: 06HB08, Year: 2006, PEL ratio: 0.04385, Grade: C\",\"StationNumber: 06HB09, Year: 2006, PEL ratio: 0.326, Grade: F\",\"StationNumber: 06HB10, Year: 2006, PEL ratio: 0.03664, Grade: C\",\"StationNumber: 06HB11, Year: 2006, PEL ratio: 0.04268, Grade: C\",\"StationNumber: 06HB12, Year: 2006, PEL ratio: 0.04913, Grade: C\",\"StationNumber: 06HB13, Year: 2006, PEL ratio: 0.03765, Grade: C\",\"StationNumber: 06HB14, Year: 2006, PEL ratio: 0.04626, Grade: C\",\"StationNumber: 06HB15, Year: 2006, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 06HB16, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06HB17, Year: 2006, PEL ratio: 0.04712, Grade: C\",\"StationNumber: 06HB18, Year: 2006, PEL ratio: 0.14179, Grade: D\",\"StationNumber: 06HB19, Year: 2006, PEL ratio: 0.05858, Grade: C\",\"StationNumber: 06HB20, Year: 2006, PEL ratio: 0.10134, Grade: D\",\"StationNumber: 06HB21, Year: 2006, PEL ratio: 0.08326, Grade: C\",\"StationNumber: 06HB22, Year: 2006, PEL ratio: 0.033, Grade: C\",\"StationNumber: 06HB23, Year: 2006, PEL ratio: 0.02427, Grade: C\",\"StationNumber: 06HB24, Year: 2006, PEL ratio: 0.04327, Grade: C\",\"StationNumber: 06HB25, Year: 2006, PEL ratio: 0.01783, Grade: B\",\"StationNumber: 06LTB01, Year: 2006, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 06LTB02, Year: 2006, PEL ratio: 0.0323, Grade: C\",\"StationNumber: 06LTB03, Year: 2006, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 06LTB04, Year: 2006, PEL ratio: 0.03755, Grade: C\",\"StationNumber: 06LTB05, Year: 2006, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 06LTB06, Year: 2006, PEL ratio: 0.0252, Grade: C\",\"StationNumber: 06LTB07, Year: 2006, PEL ratio: 0.02677, Grade: C\",\"StationNumber: 06LTB08, Year: 2006, PEL ratio: 0.034, Grade: C\",\"StationNumber: 06MR05, Year: 2006, PEL ratio: 0.06293, Grade: C\",\"StationNumber: 06MR06, Year: 2006, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 06MR07, Year: 2006, PEL ratio: 0.03329, Grade: C\",\"StationNumber: 06MR08, Year: 2006, PEL ratio: 0.02817, Grade: C\",\"StationNumber: 06MR10, Year: 2006, PEL ratio: 0.0606, Grade: C\",\"StationNumber: 06MTB01, Year: 2006, PEL ratio: 0.0429, Grade: C\",\"StationNumber: 06MTB02, Year: 2006, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 06MTB03, Year: 2006, PEL ratio: 0.07411, Grade: C\",\"StationNumber: 06MTB04, Year: 2006, PEL ratio: 0.03457, Grade: C\",\"StationNumber: 06MTB05, Year: 2006, PEL ratio: 0.04597, Grade: C\",\"StationNumber: 06MTB06, Year: 2006, PEL ratio: 0.04758, Grade: C\",\"StationNumber: 06MTB07, Year: 2006, PEL ratio: 0.03733, Grade: C\",\"StationNumber: 06MTB08, Year: 2006, PEL ratio: 0.02422, Grade: C\",\"StationNumber: 06MTB09, Year: 2006, PEL ratio: 0.03151, Grade: C\",\"StationNumber: 06MTB10, Year: 2006, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 06MTB11, Year: 2006, PEL ratio: 0.05121, Grade: C\",\"StationNumber: 06MTB12, Year: 2006, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 06MTB13, Year: 2006, PEL ratio: 0.04635, Grade: C\",\"StationNumber: 06MTB14, Year: 2006, PEL ratio: 0.02936, Grade: C\",\"StationNumber: 06MTB15, Year: 2006, PEL ratio: 0.04074, Grade: C\",\"StationNumber: 06MTB16, Year: 2006, PEL ratio: 0.02985, Grade: C\",\"StationNumber: 06MTB17, Year: 2006, PEL ratio: 0.04129, Grade: C\",\"StationNumber: 06MTB18, Year: 2006, PEL ratio: 0.02464, Grade: C\",\"StationNumber: 06MTB19, Year: 2006, PEL ratio: 0.03277, Grade: C\",\"StationNumber: 06OTB01, Year: 2006, PEL ratio: 0.03793, Grade: C\",\"StationNumber: 06OTB02, Year: 2006, PEL ratio: 0.03026, Grade: C\",\"StationNumber: 06OTB03, Year: 2006, PEL ratio: 0.02375, Grade: C\",\"StationNumber: 06OTB04, Year: 2006, PEL ratio: 0.03499, Grade: C\",\"StationNumber: 06OTB05, Year: 2006, PEL ratio: 0.03108, Grade: C\",\"StationNumber: 06OTB06, Year: 2006, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 06OTB07, Year: 2006, PEL ratio: 0.03414, Grade: C\",\"StationNumber: 06OTB08, Year: 2006, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 06TCB01, Year: 2006, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 06TCB02, Year: 2006, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 06TCB03, Year: 2006, PEL ratio: 0.02258, Grade: C\",\"StationNumber: 06TCB04, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06TCB09, Year: 2006, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 07BCB06, Year: 2007, PEL ratio: 0.03022, Grade: C\",\"StationNumber: 07BCB09, Year: 2007, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 07BCB15, Year: 2007, PEL ratio: 0.03284, Grade: C\",\"StationNumber: 07BCB28, Year: 2007, PEL ratio: 0.0147, Grade: B\",\"StationNumber: 07BCB29, Year: 2007, PEL ratio: 0.03304, Grade: C\",\"StationNumber: 07BCB30, Year: 2007, PEL ratio: 0.02747, Grade: C\",\"StationNumber: 07BCB41, Year: 2007, PEL ratio: 0.02363, Grade: C\",\"StationNumber: 07BCB42, Year: 2007, PEL ratio: 0.03369, Grade: C\",\"StationNumber: 07BCB44, Year: 2007, PEL ratio: 0.02609, Grade: C\",\"StationNumber: 07BCB45, Year: 2007, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 07HB13, Year: 2007, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 07HB21, Year: 2007, PEL ratio: 0.64118, Grade: F\",\"StationNumber: 07HB34, Year: 2007, PEL ratio: 0.02191, Grade: C\",\"StationNumber: 07HB37, Year: 2007, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 07HB38, Year: 2007, PEL ratio: 0.01243, Grade: B\",\"StationNumber: 07HB41, Year: 2007, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 07HB42, Year: 2007, PEL ratio: 0.04791, Grade: C\",\"StationNumber: 07HB44, Year: 2007, PEL ratio: 0.05993, Grade: C\",\"StationNumber: 07HB53, Year: 2007, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 07LTB91, Year: 2007, PEL ratio: 0.01736, Grade: B\",\"StationNumber: 07MR09, Year: 2007, PEL ratio: 0.00426, Grade: A\",\"StationNumber: 07MR28, Year: 2007, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 07MR42, Year: 2007, PEL ratio: 0.01369, Grade: B\",\"StationNumber: 07MR46, Year: 2007, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 07MR50, Year: 2007, PEL ratio: 0.00928, Grade: B\",\"StationNumber: 07MTB34, Year: 2007, PEL ratio: 0.03749, Grade: C\",\"StationNumber: 07MTB39, Year: 2007, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 07MTB40, Year: 2007, PEL ratio: 0.03116, Grade: C\",\"StationNumber: 07MTB43, Year: 2007, PEL ratio: 0.03052, Grade: C\",\"StationNumber: 07MTB44, Year: 2007, PEL ratio: 0.0747, Grade: C\",\"StationNumber: 07MTB47, Year: 2007, PEL ratio: 0.04289, Grade: C\",\"StationNumber: 07MTB54, Year: 2007, PEL ratio: 0.03469, Grade: C\",\"StationNumber: 07OTB04, Year: 2007, PEL ratio: 0.0814, Grade: C\",\"StationNumber: 07OTB08, Year: 2007, PEL ratio: 0.03439, Grade: C\",\"StationNumber: 07OTB18, Year: 2007, PEL ratio: 0.03309, Grade: C\",\"StationNumber: 07OTB21, Year: 2007, PEL ratio: 0.05054, Grade: C\",\"StationNumber: 07OTB24, Year: 2007, PEL ratio: 0.03054, Grade: C\",\"StationNumber: 07OTB25, Year: 2007, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 07OTB31, Year: 2007, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 07TCB14, Year: 2007, PEL ratio: 0.02992, Grade: C\",\"StationNumber: 07TCB15, Year: 2007, PEL ratio: 0.0222, Grade: C\",\"StationNumber: 07TCB20, Year: 2007, PEL ratio: 0.01955, Grade: B\",\"StationNumber: 07TCB22, Year: 2007, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 08BCB02, Year: 2008, PEL ratio: 0.02083, Grade: C\",\"StationNumber: 08BCB05, Year: 2008, PEL ratio: 0.02657, Grade: C\",\"StationNumber: 08BCB12, Year: 2008, PEL ratio: 0.02728, Grade: C\",\"StationNumber: 08BCB15, Year: 2008, PEL ratio: 0.06515, Grade: C\",\"StationNumber: 08BCB16, Year: 2008, PEL ratio: 0.03082, Grade: C\",\"StationNumber: 08BCB17, Year: 2008, PEL ratio: 0.09679, Grade: D\",\"StationNumber: 08BCB23, Year: 2008, PEL ratio: 0.1008, Grade: D\",\"StationNumber: 08BCB26, Year: 2008, PEL ratio: 0.0274, Grade: C\",\"StationNumber: 08BCB29, Year: 2008, PEL ratio: 0.0277, Grade: C\",\"StationNumber: 08BCB35, Year: 2008, PEL ratio: 0.03788, Grade: C\",\"StationNumber: 08BCB38, Year: 2008, PEL ratio: 0.02984, Grade: C\",\"StationNumber: 08HB13, Year: 2008, PEL ratio: 0.07748, Grade: C\",\"StationNumber: 08HB14, Year: 2008, PEL ratio: 0.03813, Grade: C\",\"StationNumber: 08HB17, Year: 2008, PEL ratio: 0.24554, Grade: D\",\"StationNumber: 08HB21, Year: 2008, PEL ratio: 0.15288, Grade: D\",\"StationNumber: 08HB27, Year: 2008, PEL ratio: 0.05295, Grade: C\",\"StationNumber: 08HB34, Year: 2008, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 08HB43, Year: 2008, PEL ratio: 0.02778, Grade: C\",\"StationNumber: 08HB44, Year: 2008, PEL ratio: 0.02327, Grade: C\",\"StationNumber: 08HB48, Year: 2008, PEL ratio: 0.02752, Grade: C\",\"StationNumber: 08LTB69, Year: 2008, PEL ratio: 0.02295, Grade: C\",\"StationNumber: 08LTB79, Year: 2008, PEL ratio: 0.04396, Grade: C\",\"StationNumber: 08LTB82, Year: 2008, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 08MR08, Year: 2008, PEL ratio: 0.03334, Grade: C\",\"StationNumber: 08MR35, Year: 2008, PEL ratio: 0.02726, Grade: C\",\"StationNumber: 08MR40, Year: 2008, PEL ratio: 0.03952, Grade: C\",\"StationNumber: 08MR43, Year: 2008, PEL ratio: 0.08724, Grade: D\",\"StationNumber: 08MR53, Year: 2008, PEL ratio: 0.02561, Grade: C\",\"StationNumber: 08MR54, Year: 2008, PEL ratio: 0.02649, Grade: C\",\"StationNumber: 08MTB37, Year: 2008, PEL ratio: 0.02715, Grade: C\",\"StationNumber: 08MTB47, Year: 2008, PEL ratio: 0.02945, Grade: C\",\"StationNumber: 08MTB53, Year: 2008, PEL ratio: 0, Grade: A\",\"StationNumber: 08MTB62, Year: 2008, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 08MTB73, Year: 2008, PEL ratio: 0.085, Grade: C\",\"StationNumber: 08OTB05, Year: 2008, PEL ratio: 0.02469, Grade: C\",\"StationNumber: 08OTB07, Year: 2008, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 08OTB13, Year: 2008, PEL ratio: 0.02418, Grade: C\",\"StationNumber: 08OTB15, Year: 2008, PEL ratio: 0.03404, Grade: C\",\"StationNumber: 08OTB17, Year: 2008, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 08OTB23, Year: 2008, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 08OTB27, Year: 2008, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 08TCB01, Year: 2008, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 08TCB07, Year: 2008, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 08TCB26, Year: 2008, PEL ratio: 0.03977, Grade: C\",\"StationNumber: 09BCB06, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB07, Year: 2009, PEL ratio: 0.22765, Grade: D\",\"StationNumber: 09BCB10, Year: 2009, PEL ratio: 0.22887, Grade: D\",\"StationNumber: 09BCB18, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09BCB20, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB22, Year: 2009, PEL ratio: 0.22745, Grade: D\",\"StationNumber: 09BCB25, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB31, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB34, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB36, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB43, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB05, Year: 2009, PEL ratio: 0.2648, Grade: D\",\"StationNumber: 09HB11, Year: 2009, PEL ratio: 0.23926, Grade: D\",\"StationNumber: 09HB15, Year: 2009, PEL ratio: 0.2285, Grade: D\",\"StationNumber: 09HB23, Year: 2009, PEL ratio: 0.22717, Grade: D\",\"StationNumber: 09HB24, Year: 2009, PEL ratio: 0.22751, Grade: D\",\"StationNumber: 09HB32, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB35, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB53, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB56, Year: 2009, PEL ratio: 0.24223, Grade: D\",\"StationNumber: 09LTB77, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09LTB90, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR17, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR30, Year: 2009, PEL ratio: 0.22715, Grade: D\",\"StationNumber: 09MR36, Year: 2009, PEL ratio: 0.23016, Grade: D\",\"StationNumber: 09MR46, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR49, Year: 2009, PEL ratio: 0.22727, Grade: D\",\"StationNumber: 09MTB42, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB44, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB48, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB50, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB63, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB72, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB09, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB10, Year: 2009, PEL ratio: 0.23279, Grade: D\",\"StationNumber: 09OTB14, Year: 2009, PEL ratio: 0.22724, Grade: D\",\"StationNumber: 09OTB16, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09OTB20, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09OTB28, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB29, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB10, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB13, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB14, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB22, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 10BCB06, Year: 2010, PEL ratio: 0.05418, Grade: C\",\"StationNumber: 10BCB11, Year: 2010, PEL ratio: 0.06776, Grade: C\",\"StationNumber: 10BCB17, Year: 2010, PEL ratio: 0.05636, Grade: C\",\"StationNumber: 10BCB25, Year: 2010, PEL ratio: 0.04525, Grade: C\",\"StationNumber: 10BCB28, Year: 2010, PEL ratio: 0.058, Grade: C\",\"StationNumber: 10BCB30, Year: 2010, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 10BCB37, Year: 2010, PEL ratio: 0.05759, Grade: C\",\"StationNumber: 10BCB41, Year: 2010, PEL ratio: 0.16956, Grade: D\",\"StationNumber: 10BCB46, Year: 2010, PEL ratio: 0.04398, Grade: C\",\"StationNumber: 10BCB47, Year: 2010, PEL ratio: 0.05076, Grade: C\",\"StationNumber: 10BCB49, Year: 2010, PEL ratio: 0.04946, Grade: C\",\"StationNumber: 10HB21, Year: 2010, PEL ratio: 0.11698, Grade: D\",\"StationNumber: 10HB22, Year: 2010, PEL ratio: 0.1448, Grade: D\",\"StationNumber: 10HB25, Year: 2010, PEL ratio: 0.06694, Grade: C\",\"StationNumber: 10HB26, Year: 2010, PEL ratio: 0.09827, Grade: D\",\"StationNumber: 10HB34, Year: 2010, PEL ratio: 0.05702, Grade: C\",\"StationNumber: 10HB44, Year: 2010, PEL ratio: 0.05266, Grade: C\",\"StationNumber: 10HB46, Year: 2010, PEL ratio: 0.05934, Grade: C\",\"StationNumber: 10HB48, Year: 2010, PEL ratio: 0.05189, Grade: C\",\"StationNumber: 10HB54, Year: 2010, PEL ratio: 0.06254, Grade: C\",\"StationNumber: 10LTB71, Year: 2010, PEL ratio: 0.03978, Grade: C\",\"StationNumber: 10LTB76, Year: 2010, PEL ratio: 0.04208, Grade: C\",\"StationNumber: 10LTB89, Year: 2010, PEL ratio: 0.04389, Grade: C\",\"StationNumber: 10MR25, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR29, Year: 2010, PEL ratio: 0.04883, Grade: C\",\"StationNumber: 10MR33, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR40, Year: 2010, PEL ratio: 0.05975, Grade: C\",\"StationNumber: 10MR44, Year: 2010, PEL ratio: 0.05334, Grade: C\",\"StationNumber: 10MTB30, Year: 2010, PEL ratio: 0.11699, Grade: D\",\"StationNumber: 10MTB35, Year: 2010, PEL ratio: 0.0404, Grade: C\",\"StationNumber: 10MTB43, Year: 2010, PEL ratio: 0.05591, Grade: C\",\"StationNumber: 10MTB53, Year: 2010, PEL ratio: 0.05385, Grade: C\",\"StationNumber: 10MTB56, Year: 2010, PEL ratio: 0.04796, Grade: C\",\"StationNumber: 10OTB04, Year: 2010, PEL ratio: 0.06327, Grade: C\",\"StationNumber: 10OTB05, Year: 2010, PEL ratio: 0.04514, Grade: C\",\"StationNumber: 10OTB07, Year: 2010, PEL ratio: 0.0966, Grade: D\",\"StationNumber: 10OTB08, Year: 2010, PEL ratio: 0.05185, Grade: C\",\"StationNumber: 10OTB09, Year: 2010, PEL ratio: 0.0499, Grade: C\",\"StationNumber: 10OTB12, Year: 2010, PEL ratio: 0.04749, Grade: C\",\"StationNumber: 10OTB13, Year: 2010, PEL ratio: 0.09096, Grade: D\",\"StationNumber: 10OTB14, Year: 2010, PEL ratio: 0.05743, Grade: C\",\"StationNumber: 10OTB15, Year: 2010, PEL ratio: 0.0503, Grade: C\",\"StationNumber: 10OTB16, Year: 2010, PEL ratio: 0.04904, Grade: C\",\"StationNumber: 10OTB18, Year: 2010, PEL ratio: 0.04797, Grade: C\",\"StationNumber: 10OTB19, Year: 2010, PEL ratio: 0.04649, Grade: C\",\"StationNumber: 10OTB20, Year: 2010, PEL ratio: 0.05188, Grade: C\",\"StationNumber: 10OTB21, Year: 2010, PEL ratio: 0.09696, Grade: D\",\"StationNumber: 10OTB24, Year: 2010, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 10OTB25, Year: 2010, PEL ratio: 0.04516, Grade: C\",\"StationNumber: 10OTB26, Year: 2010, PEL ratio: 0.06229, Grade: C\",\"StationNumber: 10OTB28, Year: 2010, PEL ratio: 0.05494, Grade: C\",\"StationNumber: 10OTB29, Year: 2010, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 10OTB96, Year: 2010, PEL ratio: 0.09566, Grade: D\",\"StationNumber: 10OTB97, Year: 2010, PEL ratio: 0.0741, Grade: C\",\"StationNumber: 10OTB98, Year: 2010, PEL ratio: 0.057, Grade: C\",\"StationNumber: 10TCB01, Year: 2010, PEL ratio: 0.03856, Grade: C\",\"StationNumber: 10TCB11, Year: 2010, PEL ratio: 0.04704, Grade: C\",\"StationNumber: 10TCB13, Year: 2010, PEL ratio: 0.04199, Grade: C\",\"StationNumber: 10TCB20, Year: 2010, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 11BCB05, Year: 2011, PEL ratio: 0.03406, Grade: C\",\"StationNumber: 11BCB09, Year: 2011, PEL ratio: 0.07696, Grade: C\",\"StationNumber: 11BCB12, Year: 2011, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 11BCB20, Year: 2011, PEL ratio: 0.0708, Grade: C\",\"StationNumber: 11BCB22, Year: 2011, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 11BCB26, Year: 2011, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 11BCB35, Year: 2011, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 11BCB42, Year: 2011, PEL ratio: 0.05499, Grade: C\",\"StationNumber: 11BCB43, Year: 2011, PEL ratio: 0.03362, Grade: C\",\"StationNumber: 11BCB44, Year: 2011, PEL ratio: 0.03382, Grade: C\",\"StationNumber: 11BCB48, Year: 2011, PEL ratio: 0.03412, Grade: C\",\"StationNumber: 11HB09, Year: 2011, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 11HB13, Year: 2011, PEL ratio: 0.05996, Grade: C\",\"StationNumber: 11HB29, Year: 2011, PEL ratio: 0.0821, Grade: C\",\"StationNumber: 11HB31, Year: 2011, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 11HB35, Year: 2011, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 11HB36, Year: 2011, PEL ratio: 0.04301, Grade: C\",\"StationNumber: 11HB38, Year: 2011, PEL ratio: 0.03229, Grade: C\",\"StationNumber: 11HB40, Year: 2011, PEL ratio: 0.04344, Grade: C\",\"StationNumber: 11HB47, Year: 2011, PEL ratio: 0.07343, Grade: C\",\"StationNumber: 11LTB69, Year: 2011, PEL ratio: 0.03431, Grade: C\",\"StationNumber: 11LTB75, Year: 2011, PEL ratio: 0.03175, Grade: C\",\"StationNumber: 11LTB80, Year: 2011, PEL ratio: 0.02849, Grade: C\",\"StationNumber: 11MR18, Year: 2011, PEL ratio: 0.03158, Grade: C\",\"StationNumber: 11MR32, Year: 2011, PEL ratio: 0.08626, Grade: D\",\"StationNumber: 11MR35, Year: 2011, PEL ratio: 0.2895, Grade: F\",\"StationNumber: 11MR37, Year: 2011, PEL ratio: 0.04922, Grade: C\",\"StationNumber: 11MR43, Year: 2011, PEL ratio: 0.22016, Grade: D\",\"StationNumber: 11MR45, Year: 2011, PEL ratio: 0.05964, Grade: C\",\"StationNumber: 11MR52, Year: 2011, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 11MTB39, Year: 2011, PEL ratio: 0.03658, Grade: C\",\"StationNumber: 11MTB44, Year: 2011, PEL ratio: 0.03276, Grade: C\",\"StationNumber: 11MTB46, Year: 2011, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 11MTB54, Year: 2011, PEL ratio: 0.03421, Grade: C\",\"StationNumber: 11MTB72, Year: 2011, PEL ratio: 0.03547, Grade: C\",\"StationNumber: 11OTB08, Year: 2011, PEL ratio: 0.05594, Grade: C\",\"StationNumber: 11OTB09, Year: 2011, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 11OTB18, Year: 2011, PEL ratio: 0.03456, Grade: C\",\"StationNumber: 11OTB24, Year: 2011, PEL ratio: 0.03411, Grade: C\",\"StationNumber: 11OTB26, Year: 2011, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 11OTB31, Year: 2011, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 11OTB32, Year: 2011, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 11TCB10, Year: 2011, PEL ratio: 0.02871, Grade: C\",\"StationNumber: 11TCB12, Year: 2011, PEL ratio: 0.03385, Grade: C\",\"StationNumber: 12BCB06, Year: 2012, PEL ratio: 0.04452, Grade: C\",\"StationNumber: 12BCB14, Year: 2012, PEL ratio: 0.38368, Grade: F\",\"StationNumber: 12BCB19, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12BCB23, Year: 2012, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 12BCB25, Year: 2012, PEL ratio: 0.03922, Grade: C\",\"StationNumber: 12BCB27, Year: 2012, PEL ratio: 0.07968, Grade: C\",\"StationNumber: 12BCB35, Year: 2012, PEL ratio: 0.04033, Grade: C\",\"StationNumber: 12BCB40, Year: 2012, PEL ratio: 0.04044, Grade: C\",\"StationNumber: 12BCB44, Year: 2012, PEL ratio: 0.03462, Grade: C\",\"StationNumber: 12BCB46, Year: 2012, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 12BCB49, Year: 2012, PEL ratio: 0.04079, Grade: C\",\"StationNumber: 12HB27, Year: 2012, PEL ratio: 0.04713, Grade: C\",\"StationNumber: 12HB28, Year: 2012, PEL ratio: 0.0439, Grade: C\",\"StationNumber: 12HB31, Year: 2012, PEL ratio: 0.13887, Grade: D\",\"StationNumber: 12HB32, Year: 2012, PEL ratio: 0.04521, Grade: C\",\"StationNumber: 12HB38, Year: 2012, PEL ratio: 0.05609, Grade: C\",\"StationNumber: 12HB40, Year: 2012, PEL ratio: 0.03976, Grade: C\",\"StationNumber: 12HB45, Year: 2012, PEL ratio: 0.07001, Grade: C\",\"StationNumber: 12HB53, Year: 2012, PEL ratio: 0.045, Grade: C\",\"StationNumber: 12HB54, Year: 2012, PEL ratio: 0.04384, Grade: C\",\"StationNumber: 12LTB78, Year: 2012, PEL ratio: 0.04261, Grade: C\",\"StationNumber: 12LTB84, Year: 2012, PEL ratio: 0.03384, Grade: C\",\"StationNumber: 12LTB93, Year: 2012, PEL ratio: 0.03901, Grade: C\",\"StationNumber: 12MR08, Year: 2012, PEL ratio: 0.03605, Grade: C\",\"StationNumber: 12MR17, Year: 2012, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 12MR33, Year: 2012, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 12MR36, Year: 2012, PEL ratio: 0.0414, Grade: C\",\"StationNumber: 12MR43, Year: 2012, PEL ratio: 0.04657, Grade: C\",\"StationNumber: 12MR46, Year: 2012, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 12MR54, Year: 2012, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 12MTB47, Year: 2012, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 12MTB53, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12MTB58, Year: 2012, PEL ratio: 0.05309, Grade: C\",\"StationNumber: 12MTB63, Year: 2012, PEL ratio: 0.03957, Grade: C\",\"StationNumber: 12MTB64, Year: 2012, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 12OTB04, Year: 2012, PEL ratio: 0.13065, Grade: D\",\"StationNumber: 12OTB08, Year: 2012, PEL ratio: 0.03843, Grade: C\",\"StationNumber: 12OTB13, Year: 2012, PEL ratio: 0.04154, Grade: C\",\"StationNumber: 12OTB14, Year: 2012, PEL ratio: 0.03612, Grade: C\",\"StationNumber: 12OTB18, Year: 2012, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 12OTB19, Year: 2012, PEL ratio: 0.03486, Grade: C\",\"StationNumber: 12OTB20, Year: 2012, PEL ratio: 0.04146, Grade: C\",\"StationNumber: 12TCB05, Year: 2012, PEL ratio: 0.03318, Grade: C\",\"StationNumber: 12TCB13, Year: 2012, PEL ratio: 0.03331, Grade: C\",\"StationNumber: 13BCB05, Year: 2013, PEL ratio: 0.16727, Grade: D\",\"StationNumber: 13BCB07, Year: 2013, PEL ratio: 0.04534, Grade: C\",\"StationNumber: 13BCB09, Year: 2013, PEL ratio: 0.04449, Grade: C\",\"StationNumber: 13BCB10, Year: 2013, PEL ratio: 0.03598, Grade: C\",\"StationNumber: 13BCB11, Year: 2013, PEL ratio: 0.1881, Grade: D\",\"StationNumber: 13BCB17, Year: 2013, PEL ratio: 0.10487, Grade: D\",\"StationNumber: 13BCB22, Year: 2013, PEL ratio: 0.0432, Grade: C\",\"StationNumber: 13BCB30, Year: 2013, PEL ratio: 0.03594, Grade: C\",\"StationNumber: 13BCB41, Year: 2013, PEL ratio: 0.03671, Grade: C\",\"StationNumber: 13BCB43, Year: 2013, PEL ratio: 0.03609, Grade: C\",\"StationNumber: 13BCB48, Year: 2013, PEL ratio: 0.04681, Grade: C\",\"StationNumber: 13HB09, Year: 2013, PEL ratio: 0.07695, Grade: C\",\"StationNumber: 13HB13, Year: 2013, PEL ratio: 0.0831, Grade: C\",\"StationNumber: 13HB25, Year: 2013, PEL ratio: 0.03306, Grade: C\",\"StationNumber: 13HB26, Year: 2013, PEL ratio: 0.05412, Grade: C\",\"StationNumber: 13HB35, Year: 2013, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 13HB36, Year: 2013, PEL ratio: 0.18861, Grade: D\",\"StationNumber: 13HB41, Year: 2013, PEL ratio: 0.03847, Grade: C\",\"StationNumber: 13HB44, Year: 2013, PEL ratio: 0.09625, Grade: D\",\"StationNumber: 13HB48, Year: 2013, PEL ratio: 0.0373, Grade: C\",\"StationNumber: 13LTB79, Year: 2013, PEL ratio: 0.03872, Grade: C\",\"StationNumber: 13LTB82, Year: 2013, PEL ratio: 0.03513, Grade: C\",\"StationNumber: 13LTB86, Year: 2013, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 13MR09, Year: 2013, PEL ratio: 0.03565, Grade: C\",\"StationNumber: 13MR24, Year: 2013, PEL ratio: 0.03695, Grade: C\",\"StationNumber: 13MR31, Year: 2013, PEL ratio: 0.34066, Grade: F\",\"StationNumber: 13MR44, Year: 2013, PEL ratio: 0.09108, Grade: D\",\"StationNumber: 13MR45, Year: 2013, PEL ratio: 0.06721, Grade: C\",\"StationNumber: 13MR48, Year: 2013, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 13MTB34, Year: 2013, PEL ratio: 0.03171, Grade: C\",\"StationNumber: 13MTB35, Year: 2013, PEL ratio: 0.05215, Grade: C\",\"StationNumber: 13MTB41, Year: 2013, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 13MTB45, Year: 2013, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 13MTB55, Year: 2013, PEL ratio: 0.06478, Grade: C\",\"StationNumber: 13OTB12, Year: 2013, PEL ratio: 0.04515, Grade: C\",\"StationNumber: 13OTB15, Year: 2013, PEL ratio: 0.03702, Grade: C\",\"StationNumber: 13OTB16, Year: 2013, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 13OTB21, Year: 2013, PEL ratio: 0.04235, Grade: C\",\"StationNumber: 13OTB27, Year: 2013, PEL ratio: 0.03527, Grade: C\",\"StationNumber: 13OTB28, Year: 2013, PEL ratio: 0.03653, Grade: C\",\"StationNumber: 13OTB29, Year: 2013, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 13TCB01, Year: 2013, PEL ratio: 0.03209, Grade: C\",\"StationNumber: 13TCB11, Year: 2013, PEL ratio: 0.03349, Grade: C\",\"StationNumber: 13TCB14, Year: 2013, PEL ratio: 0.03452, Grade: C\",\"StationNumber: 14BCB03, Year: 2014, PEL ratio: 0.07223, Grade: C\",\"StationNumber: 14BCB12, Year: 2014, PEL ratio: 0.03971, Grade: C\",\"StationNumber: 14BCB15, Year: 2014, PEL ratio: 0.12267, Grade: D\",\"StationNumber: 14BCB17, Year: 2014, PEL ratio: 0.03495, Grade: C\",\"StationNumber: 14BCB20, Year: 2014, PEL ratio: 0.04709, Grade: C\",\"StationNumber: 14BCB25, Year: 2014, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 14BCB29, Year: 2014, PEL ratio: 0.01869, Grade: B\",\"StationNumber: 14BCB33, Year: 2014, PEL ratio: 0.03039, Grade: C\",\"StationNumber: 14BCB35, Year: 2014, PEL ratio: 0.08684, Grade: D\",\"StationNumber: 14BCB41, Year: 2014, PEL ratio: 0.03173, Grade: C\",\"StationNumber: 14BCB47, Year: 2014, PEL ratio: 0.02445, Grade: C\",\"StationNumber: 14HB20, Year: 2014, PEL ratio: 0.02692, Grade: C\",\"StationNumber: 14HB21, Year: 2014, PEL ratio: 0.11022, Grade: D\",\"StationNumber: 14HB26, Year: 2014, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 14HB33, Year: 2014, PEL ratio: 0.04596, Grade: C\",\"StationNumber: 14HB43, Year: 2014, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 14HB44, Year: 2014, PEL ratio: 0.02425, Grade: C\",\"StationNumber: 14HB46, Year: 2014, PEL ratio: 0.02682, Grade: C\",\"StationNumber: 14HB47, Year: 2014, PEL ratio: 0.02598, Grade: C\",\"StationNumber: 14HB54, Year: 2014, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 14LTB71, Year: 2014, PEL ratio: 0.02041, Grade: B\",\"StationNumber: 14LTB81, Year: 2014, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 14LTB90, Year: 2014, PEL ratio: 0.01877, Grade: B\",\"StationNumber: 14MR29, Year: 2014, PEL ratio: 0.01907, Grade: B\",\"StationNumber: 14MR35, Year: 2014, PEL ratio: 0.0555, Grade: C\",\"StationNumber: 14MR37, Year: 2014, PEL ratio: 0.09494, Grade: D\",\"StationNumber: 14MR38, Year: 2014, PEL ratio: 0.1108, Grade: D\",\"StationNumber: 14MR47, Year: 2014, PEL ratio: 0.01791, Grade: B\",\"StationNumber: 14MTB39, Year: 2014, PEL ratio: 0.02273, Grade: C\",\"StationNumber: 14MTB41, Year: 2014, PEL ratio: 0.03062, Grade: C\",\"StationNumber: 14MTB46, Year: 2014, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 14MTB54, Year: 2014, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 14MTB63, Year: 2014, PEL ratio: 0.02282, Grade: C\",\"StationNumber: 14OTB04, Year: 2014, PEL ratio: 0.02755, Grade: C\",\"StationNumber: 14OTB08, Year: 2014, PEL ratio: 0.03792, Grade: C\",\"StationNumber: 14OTB14, Year: 2014, PEL ratio: 0.04277, Grade: C\",\"StationNumber: 14OTB18, Year: 2014, PEL ratio: 2.41188, Grade: F\",\"StationNumber: 14OTB19, Year: 2014, PEL ratio: 0.01969, Grade: B\",\"StationNumber: 14OTB21, Year: 2014, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 14OTB25, Year: 2014, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 14TCB15, Year: 2014, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 14TCB20, Year: 2014, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 14TCB21, Year: 2014, PEL ratio: 0.0283, Grade: C\",\"StationNumber: 14TCB22, Year: 2014, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 15BCB09, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15BCB12, Year: 2015, PEL ratio: 0.04372, Grade: C\",\"StationNumber: 15BCB15, Year: 2015, PEL ratio: 0.04656, Grade: C\",\"StationNumber: 15BCB26, Year: 2015, PEL ratio: 0.05585, Grade: C\",\"StationNumber: 15BCB30, Year: 2015, PEL ratio: 0.04815, Grade: C\",\"StationNumber: 15BCB31, Year: 2015, PEL ratio: 0.13946, Grade: D\",\"StationNumber: 15BCB34, Year: 2015, PEL ratio: 0.03182, Grade: C\",\"StationNumber: 15BCB39, Year: 2015, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 15BCB43, Year: 2015, PEL ratio: 0.03861, Grade: C\",\"StationNumber: 15BCB47, Year: 2015, PEL ratio: 0.06181, Grade: C\",\"StationNumber: 15BCB48, Year: 2015, PEL ratio: 0.03381, Grade: C\",\"StationNumber: 15HB09, Year: 2015, PEL ratio: 0.15218, Grade: D\",\"StationNumber: 15HB14, Year: 2015, PEL ratio: 0.08241, Grade: C\",\"StationNumber: 15HB27, Year: 2015, PEL ratio: 0.07462, Grade: C\",\"StationNumber: 15HB36, Year: 2015, PEL ratio: 0.04156, Grade: C\",\"StationNumber: 15HB37, Year: 2015, PEL ratio: 0.03697, Grade: C\",\"StationNumber: 15HB39, Year: 2015, PEL ratio: 0.03681, Grade: C\",\"StationNumber: 15HB40, Year: 2015, PEL ratio: 0.03913, Grade: C\",\"StationNumber: 15HB41, Year: 2015, PEL ratio: 0.03531, Grade: C\",\"StationNumber: 15HB48, Year: 2015, PEL ratio: 0.038, Grade: C\",\"StationNumber: 15LTB70, Year: 2015, PEL ratio: 0.03226, Grade: C\",\"StationNumber: 15LTB76, Year: 2015, PEL ratio: 0.03036, Grade: C\",\"StationNumber: 15LTB94, Year: 2015, PEL ratio: 0.03816, Grade: C\",\"StationNumber: 15MR08, Year: 2015, PEL ratio: 0.03832, Grade: C\",\"StationNumber: 15MR28, Year: 2015, PEL ratio: 0.03623, Grade: C\",\"StationNumber: 15MR30, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15MR33, Year: 2015, PEL ratio: 0.15657, Grade: D\",\"StationNumber: 15MR42, Year: 2015, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 15MR52, Year: 2015, PEL ratio: 0.03954, Grade: C\",\"StationNumber: 15MTB40, Year: 2015, PEL ratio: 0.0354, Grade: C\",\"StationNumber: 15MTB49, Year: 2015, PEL ratio: 0.04217, Grade: C\",\"StationNumber: 15MTB52, Year: 2015, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 15MTB55, Year: 2015, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 15MTB62, Year: 2015, PEL ratio: 0.03246, Grade: C\",\"StationNumber: 15OTB12, Year: 2015, PEL ratio: 0.04593, Grade: C\",\"StationNumber: 15OTB15, Year: 2015, PEL ratio: 0.05137, Grade: C\",\"StationNumber: 15OTB20, Year: 2015, PEL ratio: 0.05337, Grade: C\",\"StationNumber: 15OTB24, Year: 2015, PEL ratio: 0.04, Grade: C\",\"StationNumber: 15OTB26, Year: 2015, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 15OTB28, Year: 2015, PEL ratio: 0.03812, Grade: C\",\"StationNumber: 15OTB29, Year: 2015, PEL ratio: 0.05653, Grade: C\",\"StationNumber: 15TCB01, Year: 2015, PEL ratio: 0.02764, Grade: C\",\"StationNumber: 15TCB11, Year: 2015, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 15TCB12, Year: 2015, PEL ratio: 0.04456, Grade: C\",\"StationNumber: 16BCB20, Year: 2016, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 16BCB22, Year: 2016, PEL ratio: 0.01314, Grade: B\",\"StationNumber: 16BCB25, Year: 2016, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 16BCB29, Year: 2016, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 16BCB34, Year: 2016, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 16BCB35, Year: 2016, PEL ratio: 0.01331, Grade: B\",\"StationNumber: 16BCB36, Year: 2016, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 16BCB37, Year: 2016, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 16BCB41, Year: 2016, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 16BCB42, Year: 2016, PEL ratio: 0.01254, Grade: B\",\"StationNumber: 16BCB43, Year: 2016, PEL ratio: 0.0166, Grade: B\",\"StationNumber: 16DH07-1, Year: 2016, PEL ratio: 0.18391, Grade: D\",\"StationNumber: 16DH07-2, Year: 2016, PEL ratio: 0.13524, Grade: D\",\"StationNumber: 16DH07-3, Year: 2016, PEL ratio: 0.20542, Grade: D\",\"StationNumber: 16DH07-4, Year: 2016, PEL ratio: 0.01549, Grade: B\",\"StationNumber: 16HB19, Year: 2016, PEL ratio: 0.05887, Grade: C\",\"StationNumber: 16HB20, Year: 2016, PEL ratio: 0.04907, Grade: C\",\"StationNumber: 16HB21, Year: 2016, PEL ratio: 0.0132, Grade: B\",\"StationNumber: 16HB27, Year: 2016, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 16HB28, Year: 2016, PEL ratio: 0.9678, Grade: F\",\"StationNumber: 16HB32, Year: 2016, PEL ratio: 0.08862, Grade: D\",\"StationNumber: 16HB33, Year: 2016, PEL ratio: 0.01043, Grade: B\",\"StationNumber: 16HB37, Year: 2016, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 16HB48, Year: 2016, PEL ratio: 0.00834, Grade: B\",\"StationNumber: 16DH04-1, Year: 2016, PEL ratio: 0.01392, Grade: B\",\"StationNumber: 16DH04-2, Year: 2016, PEL ratio: 0.01391, Grade: B\",\"StationNumber: 16DH04-3, Year: 2016, PEL ratio: 0.0173, Grade: B\",\"StationNumber: 16DH04-4, Year: 2016, PEL ratio: 0.01483, Grade: B\",\"StationNumber: 16DH08-1, Year: 2016, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 16DH08-2, Year: 2016, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 16DH08-3, Year: 2016, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 16DH08-4, Year: 2016, PEL ratio: 0.0073, Grade: A\",\"StationNumber: 16DH09-1, Year: 2016, PEL ratio: 0.0417, Grade: C\",\"StationNumber: 16DH09-2, Year: 2016, PEL ratio: 0.0163, Grade: B\",\"StationNumber: 16DH09-3, Year: 2016, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 16DH09-4, Year: 2016, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 16LTB71, Year: 2016, PEL ratio: 0.02031, Grade: B\",\"StationNumber: 16LTB79, Year: 2016, PEL ratio: 0.03301, Grade: C\",\"StationNumber: 16LTB85, Year: 2016, PEL ratio: 0.01936, Grade: B\",\"StationNumber: 16MR17, Year: 2016, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 16MR25, Year: 2016, PEL ratio: 0.01518, Grade: B\",\"StationNumber: 16MR29, Year: 2016, PEL ratio: 0.02155, Grade: C\",\"StationNumber: 16MR33, Year: 2016, PEL ratio: 0.04406, Grade: C\",\"StationNumber: 16MR43, Year: 2016, PEL ratio: 0.03343, Grade: C\",\"StationNumber: 16MR44, Year: 2016, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 16MR45, Year: 2016, PEL ratio: 0.09741, Grade: D\",\"StationNumber: 16DH06-1, Year: 2016, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 16DH06-2, Year: 2016, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 16DH06-3, Year: 2016, PEL ratio: 0.0963, Grade: D\",\"StationNumber: 16DH06-4, Year: 2016, PEL ratio: 0.04943, Grade: C\",\"StationNumber: 16DH10-1, Year: 2016, PEL ratio: 0.0172, Grade: B\",\"StationNumber: 16DH10-2, Year: 2016, PEL ratio: 0.0164, Grade: B\",\"StationNumber: 16DH10-3, Year: 2016, PEL ratio: 0.01826, Grade: B\",\"StationNumber: 16DH10-4, Year: 2016, PEL ratio: 0.01494, Grade: B\",\"StationNumber: 16MTB41, Year: 2016, PEL ratio: 0.04661, Grade: C\",\"StationNumber: 16MTB47, Year: 2016, PEL ratio: 0.01915, Grade: B\",\"StationNumber: 16MTB48, Year: 2016, PEL ratio: 0.02853, Grade: C\",\"StationNumber: 16MTB53, Year: 2016, PEL ratio: 0.01875, Grade: B\",\"StationNumber: 16MTB72, Year: 2016, PEL ratio: 0.01874, Grade: B\",\"StationNumber: 16DH01-1, Year: 2016, PEL ratio: 0.12523, Grade: D\",\"StationNumber: 16DH01-2, Year: 2016, PEL ratio: 0.02653, Grade: C\",\"StationNumber: 16DH01-3, Year: 2016, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 16DH01-4, Year: 2016, PEL ratio: 0.02374, Grade: C\",\"StationNumber: 16DH02-1, Year: 2016, PEL ratio: 0.02317, Grade: C\",\"StationNumber: 16DH02-2, Year: 2016, PEL ratio: 0.01762, Grade: B\",\"StationNumber: 16DH02-3, Year: 2016, PEL ratio: 0.14359, Grade: D\",\"StationNumber: 16DH02-4, Year: 2016, PEL ratio: 0.015, Grade: B\",\"StationNumber: 16DH03-1, Year: 2016, PEL ratio: 0.08286, Grade: C\",\"StationNumber: 16DH03-2, Year: 2016, PEL ratio: 0.12405, Grade: D\",\"StationNumber: 16DH03-3, Year: 2016, PEL ratio: 0.08808, Grade: D\",\"StationNumber: 16DH03-4, Year: 2016, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 16DH05-1, Year: 2016, PEL ratio: 0.05878, Grade: C\",\"StationNumber: 16DH05-2, Year: 2016, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 16DH05-3, Year: 2016, PEL ratio: 0.02045, Grade: B\",\"StationNumber: 16DH05-4, Year: 2016, PEL ratio: 0.01988, Grade: B\",\"StationNumber: 16OTB08, Year: 2016, PEL ratio: 0.02621, Grade: C\",\"StationNumber: 16OTB09, Year: 2016, PEL ratio: 0.03233, Grade: C\",\"StationNumber: 16OTB13, Year: 2016, PEL ratio: 0.04697, Grade: C\",\"StationNumber: 16OTB14, Year: 2016, PEL ratio: 0.02479, Grade: C\",\"StationNumber: 16OTB18, Year: 2016, PEL ratio: 0.01902, Grade: B\",\"StationNumber: 16OTB22, Year: 2016, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 16OTB25, Year: 2016, PEL ratio: 0.01921, Grade: B\",\"StationNumber: 16TCB14, Year: 2016, PEL ratio: 0.01957, Grade: B\",\"StationNumber: 16TCB20, Year: 2016, PEL ratio: 0.01605, Grade: B\",\"StationNumber: 17BCB15, Year: 2017, PEL ratio: 0.05574, Grade: C\",\"StationNumber: 17BCB26, Year: 2017, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 17BCB27, Year: 2017, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 17BCB30, Year: 2017, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 17BCB35, Year: 2017, PEL ratio: 0.0452, Grade: C\",\"StationNumber: 17BCB36, Year: 2017, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 17BCB40, Year: 2017, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 17BCB42, Year: 2017, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 17BCB43, Year: 2017, PEL ratio: 0.0479, Grade: C\",\"StationNumber: 17BCB44, Year: 2017, PEL ratio: 0.04568, Grade: C\",\"StationNumber: 17BCB48, Year: 2017, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 17HB10, Year: 2017, PEL ratio: 0.07514, Grade: C\",\"StationNumber: 17HB13, Year: 2017, PEL ratio: 0.09007, Grade: D\",\"StationNumber: 17HB15, Year: 2017, PEL ratio: 0.20221, Grade: D\",\"StationNumber: 17HB26, Year: 2017, PEL ratio: 0.04364, Grade: C\",\"StationNumber: 17HB34, Year: 2017, PEL ratio: 2.58424, Grade: F\",\"StationNumber: 17HB36, Year: 2017, PEL ratio: 0.06844, Grade: C\",\"StationNumber: 17HB41, Year: 2017, PEL ratio: 0.04206, Grade: C\",\"StationNumber: 17HB42, Year: 2017, PEL ratio: 0.04424, Grade: C\",\"StationNumber: 17HB43, Year: 2017, PEL ratio: 0.04021, Grade: C\",\"StationNumber: 17LTB70, Year: 2017, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 17LTB83, Year: 2017, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 17LTB89, Year: 2017, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 17TCP01, Year: 2017, PEL ratio: 0.05508, Grade: C\",\"StationNumber: 17TCP02, Year: 2017, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 17TCP03, Year: 2017, PEL ratio: 0.05051, Grade: C\",\"StationNumber: 17TCP04, Year: 2017, PEL ratio: 0.05089, Grade: C\",\"StationNumber: 17TCP05, Year: 2017, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 17TCP06, Year: 2017, PEL ratio: 0.07589, Grade: C\",\"StationNumber: 17TCP07, Year: 2017, PEL ratio: 0.051, Grade: C\",\"StationNumber: 17TCP08, Year: 2017, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 17TCP09, Year: 2017, PEL ratio: 0.04474, Grade: C\",\"StationNumber: 17TCP10, Year: 2017, PEL ratio: 0.04683, Grade: C\",\"StationNumber: 17MR09, Year: 2017, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 17MR18, Year: 2017, PEL ratio: 0.04076, Grade: C\",\"StationNumber: 17MR24, Year: 2017, PEL ratio: 0.03902, Grade: C\",\"StationNumber: 17MR32, Year: 2017, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 17MR35, Year: 2017, PEL ratio: 0.0913, Grade: D\",\"StationNumber: 17MR37, Year: 2017, PEL ratio: 0.04193, Grade: C\",\"StationNumber: 17MTB34, Year: 2017, PEL ratio: 0.03827, Grade: C\",\"StationNumber: 17MTB35, Year: 2017, PEL ratio: 0.05891, Grade: C\",\"StationNumber: 17MTB46, Year: 2017, PEL ratio: 0.04189, Grade: C\",\"StationNumber: 17MTB55, Year: 2017, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 17MTB63, Year: 2017, PEL ratio: 0.04197, Grade: C\",\"StationNumber: 17OTB04, Year: 2017, PEL ratio: 0.0536, Grade: C\",\"StationNumber: 17OTB07, Year: 2017, PEL ratio: 0.05219, Grade: C\",\"StationNumber: 17OTB12, Year: 2017, PEL ratio: 0.10245, Grade: D\",\"StationNumber: 17OTB19, Year: 2017, PEL ratio: 0.04286, Grade: C\",\"StationNumber: 17OTB21, Year: 2017, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 17OTB28, Year: 2017, PEL ratio: 0.04793, Grade: C\",\"StationNumber: 17OTB32, Year: 2017, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 17TCB12, Year: 2017, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 17TCB13, Year: 2017, PEL ratio: 0.04488, Grade: C\",\"StationNumber: 17TCB21, Year: 2017, PEL ratio: 0.04358, Grade: C\",\"StationNumber: 18BCB11, Year: 2018, PEL ratio: 0.37337, Grade: F\",\"StationNumber: 18BCB15, Year: 2018, PEL ratio: 0.21905, Grade: D\",\"StationNumber: 18BCB19, Year: 2018, PEL ratio: 0.00266, Grade: A\",\"StationNumber: 18BCB20, Year: 2018, PEL ratio: 0.21369, Grade: D\",\"StationNumber: 18BCB22, Year: 2018, PEL ratio: 0.17683, Grade: D\",\"StationNumber: 18BCB24, Year: 2018, PEL ratio: 0.01165, Grade: B\",\"StationNumber: 18BCB26, Year: 2018, PEL ratio: 0.28634, Grade: F\",\"StationNumber: 18BCB37, Year: 2018, PEL ratio: 0.00425, Grade: A\",\"StationNumber: 18BCB42, Year: 2018, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 18BCB44, Year: 2018, PEL ratio: 0.00316, Grade: A\",\"StationNumber: 18BCB46, Year: 2018, PEL ratio: 0.01455, Grade: B\",\"StationNumber: 18HB14, Year: 2018, PEL ratio: 0.04307, Grade: C\",\"StationNumber: 18HB20, Year: 2018, PEL ratio: 0.05365, Grade: C\",\"StationNumber: 18HB21, Year: 2018, PEL ratio: 0.03344, Grade: C\",\"StationNumber: 18HB26, Year: 2018, PEL ratio: 0.03348, Grade: C\",\"StationNumber: 18HB29, Year: 2018, PEL ratio: 0.0738, Grade: C\",\"StationNumber: 18HB33, Year: 2018, PEL ratio: 0.05804, Grade: C\",\"StationNumber: 18HB38, Year: 2018, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 18HB41, Year: 2018, PEL ratio: 0.00774, Grade: B\",\"StationNumber: 18HB46, Year: 2018, PEL ratio: 1.04973, Grade: F\",\"StationNumber: 18LTB75, Year: 2018, PEL ratio: 0.12361, Grade: D\",\"StationNumber: 18LTB79, Year: 2018, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 18LTB81, Year: 2018, PEL ratio: 0.09621, Grade: D\",\"StationNumber: 18LTB82, Year: 2018, PEL ratio: 0.0782, Grade: C\",\"StationNumber: 18MR25, Year: 2018, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 18MR37, Year: 2018, PEL ratio: 0.06345, Grade: C\",\"StationNumber: 18MR46, Year: 2018, PEL ratio: 0.03519, Grade: C\",\"StationNumber: 18MTB41, Year: 2018, PEL ratio: 0.01539, Grade: B\",\"StationNumber: 18MTB42, Year: 2018, PEL ratio: 0.18686, Grade: D\",\"StationNumber: 18MTB48, Year: 2018, PEL ratio: 0.00879, Grade: B\",\"StationNumber: 18MTB56, Year: 2018, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 18OTB04, Year: 2018, PEL ratio: 0.06233, Grade: C\",\"StationNumber: 18OTB08, Year: 2018, PEL ratio: 0.003, Grade: A\",\"StationNumber: 18OTB13, Year: 2018, PEL ratio: 0.01252, Grade: B\",\"StationNumber: 18OTB14, Year: 2018, PEL ratio: 0.04092, Grade: C\",\"StationNumber: 18OTB15, Year: 2018, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 18OTB21, Year: 2018, PEL ratio: 0.00898, Grade: B\",\"StationNumber: 18OTB24, Year: 2018, PEL ratio: 0.00579, Grade: A\",\"StationNumber: 18TCB05, Year: 2018, PEL ratio: 0.03777, Grade: C\",\"StationNumber: 18TCB11, Year: 2018, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 18TCB14, Year: 2018, PEL ratio: 0.05688, Grade: C\",\"StationNumber: 18TCB15, Year: 2018, PEL ratio: 0.05947, Grade: C\",\"StationNumber: 18TCB21, Year: 2018, PEL ratio: 0.11579, Grade: D\",\"StationNumber: 18TCB22, Year: 2018, PEL ratio: 0.02805, Grade: C\",\"StationNumber: 19BCB27, Year: 2019, PEL ratio: 0.04772, Grade: C\",\"StationNumber: 19BCB29, Year: 2019, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 19BCB30, Year: 2019, PEL ratio: 0.1321, Grade: D\",\"StationNumber: 19BCB34, Year: 2019, PEL ratio: 0.51859, Grade: F\",\"StationNumber: 19BCB35, Year: 2019, PEL ratio: 0.05839, Grade: C\",\"StationNumber: 19BCB36, Year: 2019, PEL ratio: 0.11644, Grade: D\",\"StationNumber: 19BCB40, Year: 2019, PEL ratio: 0.00368, Grade: A\",\"StationNumber: 19BCB41, Year: 2019, PEL ratio: 0.0436, Grade: C\",\"StationNumber: 19BCB43, Year: 2019, PEL ratio: 0.09295, Grade: D\",\"StationNumber: 19BCB49, Year: 2019, PEL ratio: 0.05207, Grade: C\",\"StationNumber: 19BCB50, Year: 2019, PEL ratio: 0.0513, Grade: C\",\"StationNumber: 19HB09, Year: 2019, PEL ratio: 0.01191, Grade: B\",\"StationNumber: 19HB16, Year: 2019, PEL ratio: 0.69077, Grade: F\",\"StationNumber: 19HB25, Year: 2019, PEL ratio: 0.0126, Grade: B\",\"StationNumber: 19HB27, Year: 2019, PEL ratio: 0.05811, Grade: C\",\"StationNumber: 19HB32, Year: 2019, PEL ratio: 0.03805, Grade: C\",\"StationNumber: 19HB37, Year: 2019, PEL ratio: 0.06339, Grade: C\",\"StationNumber: 19HB39, Year: 2019, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 19HB40, Year: 2019, PEL ratio: 0.0131, Grade: B\",\"StationNumber: 19HB47, Year: 2019, PEL ratio: 0.00395, Grade: A\",\"StationNumber: 19LTB76, Year: 2019, PEL ratio: 0.00985, Grade: B\",\"StationNumber: 19LTB78, Year: 2019, PEL ratio: 0.01215, Grade: B\",\"StationNumber: 19LTB88, Year: 2019, PEL ratio: 0.11037, Grade: D\",\"StationNumber: 19LTB90, Year: 2019, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 19MR17, Year: 2019, PEL ratio: 0.01119, Grade: B\",\"StationNumber: 19MR18, Year: 2019, PEL ratio: 0.02367, Grade: C\",\"StationNumber: 19MR29, Year: 2019, PEL ratio: 0.02627, Grade: C\",\"StationNumber: 19MR33, Year: 2019, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 19MR43, Year: 2019, PEL ratio: 0.17714, Grade: D\",\"StationNumber: 19MR44, Year: 2019, PEL ratio: 0.15675, Grade: D\",\"StationNumber: 19MR52, Year: 2019, PEL ratio: 0.0116, Grade: B\",\"StationNumber: 19MTB36, Year: 2019, PEL ratio: 0.08261, Grade: C\",\"StationNumber: 19MTB47, Year: 2019, PEL ratio: 0.01131, Grade: B\",\"StationNumber: 19MTB54, Year: 2019, PEL ratio: 0.00976, Grade: B\",\"StationNumber: 19MTB62, Year: 2019, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 19OTB07, Year: 2019, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 19OTB18, Year: 2019, PEL ratio: 0.05206, Grade: C\",\"StationNumber: 19OTB20, Year: 2019, PEL ratio: 0.02767, Grade: C\",\"StationNumber: 19OTB23, Year: 2019, PEL ratio: 0.01054, Grade: B\",\"StationNumber: 19OTB25, Year: 2019, PEL ratio: 0.04412, Grade: C\",\"StationNumber: 19OTB29, Year: 2019, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 19OTB31, Year: 2019, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 19TCB01, Year: 2019, PEL ratio: 0.01901, Grade: B\",\"StationNumber: 19TCB20, Year: 2019, PEL ratio: 0.01996, Grade: B\",\"StationNumber: 20BCB10, Year: 2020, PEL ratio: 0.02055, Grade: C\",\"StationNumber: 20BCB17, Year: 2020, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 20BCB22, Year: 2020, PEL ratio: 0.20992, Grade: D\",\"StationNumber: 20BCB23, Year: 2020, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 20BCB35, Year: 2020, PEL ratio: 0.04529, Grade: C\",\"StationNumber: 20BCB37, Year: 2020, PEL ratio: 0.01213, Grade: B\",\"StationNumber: 20BCB40, Year: 2020, PEL ratio: 0.00479, Grade: A\",\"StationNumber: 20BCB43, Year: 2020, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 20BCB47, Year: 2020, PEL ratio: 0.01811, Grade: B\",\"StationNumber: 20BCB48, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20BCB49, Year: 2020, PEL ratio: 0.01004, Grade: B\",\"StationNumber: 20HB09, Year: 2020, PEL ratio: 0.04899, Grade: C\",\"StationNumber: 20HB10, Year: 2020, PEL ratio: 0.06714, Grade: C\",\"StationNumber: 20HB21, Year: 2020, PEL ratio: 0.1516, Grade: D\",\"StationNumber: 20HB26, Year: 2020, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 20HB38, Year: 2020, PEL ratio: 0.04319, Grade: C\",\"StationNumber: 20HB41, Year: 2020, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 20HB46, Year: 2020, PEL ratio: 0.01143, Grade: B\",\"StationNumber: 20HB47, Year: 2020, PEL ratio: 0.00625, Grade: A\",\"StationNumber: 20HB52, Year: 2020, PEL ratio: 0.0242, Grade: C\",\"StationNumber: 20LTB70, Year: 2020, PEL ratio: 0.01567, Grade: B\",\"StationNumber: 20LTB71, Year: 2020, PEL ratio: 0.03189, Grade: C\",\"StationNumber: 20LTB77, Year: 2020, PEL ratio: 0.01505, Grade: B\",\"StationNumber: 20LTB85, Year: 2020, PEL ratio: 0.02098, Grade: C\",\"StationNumber: 20MR08, Year: 2020, PEL ratio: 0.07608, Grade: C\",\"StationNumber: 20MR09, Year: 2020, PEL ratio: 0.09408, Grade: D\",\"StationNumber: 20MR33, Year: 2020, PEL ratio: 0.18328, Grade: D\",\"StationNumber: 20MR36, Year: 2020, PEL ratio: 0.01558, Grade: B\",\"StationNumber: 20MR44, Year: 2020, PEL ratio: 0.10315, Grade: D\",\"StationNumber: 20MR49, Year: 2020, PEL ratio: 0.12139, Grade: D\",\"StationNumber: 20MTB35, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20MTB46, Year: 2020, PEL ratio: 0.00585, Grade: A\",\"StationNumber: 20MTB52, Year: 2020, PEL ratio: 0.0217, Grade: C\",\"StationNumber: 20MTB63, Year: 2020, PEL ratio: 0.00437, Grade: A\",\"StationNumber: 20OTB13, Year: 2020, PEL ratio: 0.11907, Grade: D\",\"StationNumber: 20OTB14, Year: 2020, PEL ratio: 0.09905, Grade: D\",\"StationNumber: 20OTB15, Year: 2020, PEL ratio: 0.00718, Grade: A\",\"StationNumber: 20OTB19, Year: 2020, PEL ratio: 0.01134, Grade: B\",\"StationNumber: 20OTB21, Year: 2020, PEL ratio: 0.00212, Grade: A\",\"StationNumber: 20OTB24, Year: 2020, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 20OTB32, Year: 2020, PEL ratio: 0.00435, Grade: A\",\"StationNumber: 20TCB10, Year: 2020, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 20TCB12, Year: 2020, PEL ratio: 0.03948, Grade: C\",\"StationNumber: 20TCB20, Year: 2020, PEL ratio: 0.058, Grade: C\",\"StationNumber: 21BCB09, Year: 2021, PEL ratio: 0.11558, Grade: D\",\"StationNumber: 21BCB12, Year: 2021, PEL ratio: 0.01683, Grade: B\",\"StationNumber: 21BCB15, Year: 2021, PEL ratio: 0.05873, Grade: C\",\"StationNumber: 21BCB22, Year: 2021, PEL ratio: 0.01386, Grade: B\",\"StationNumber: 21BCB25, Year: 2021, PEL ratio: 0.00971, Grade: B\",\"StationNumber: 21BCB26, Year: 2021, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 21BCB29, Year: 2021, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 21BCB36, Year: 2021, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 21BCB41, Year: 2021, PEL ratio: 0.00501, Grade: A\",\"StationNumber: 21BCB44, Year: 2021, PEL ratio: 0.01104, Grade: B\",\"StationNumber: 21BCB50, Year: 2021, PEL ratio: 0.00475, Grade: A\",\"StationNumber: 21HB13, Year: 2021, PEL ratio: 0.05335, Grade: C\",\"StationNumber: 21HB19, Year: 2021, PEL ratio: 0.08665, Grade: D\",\"StationNumber: 21HB20, Year: 2021, PEL ratio: 0.02175, Grade: C\",\"StationNumber: 21HB27, Year: 2021, PEL ratio: 0.04735, Grade: C\",\"StationNumber: 21HB34, Year: 2021, PEL ratio: 0.01341, Grade: B\",\"StationNumber: 21HB36, Year: 2021, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 21HB37, Year: 2021, PEL ratio: 0.04959, Grade: C\",\"StationNumber: 21HB40, Year: 2021, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 21HB43, Year: 2021, PEL ratio: 0.03012, Grade: C\",\"StationNumber: 21LTB78, Year: 2021, PEL ratio: 0.02074, Grade: C\",\"StationNumber: 21LTB83, Year: 2021, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 21LTB84, Year: 2021, PEL ratio: 0.01135, Grade: B\",\"StationNumber: 21LTB89, Year: 2021, PEL ratio: 0.01185, Grade: B\",\"StationNumber: 21MR24, Year: 2021, PEL ratio: 0.0078, Grade: B\",\"StationNumber: 21MR29, Year: 2021, PEL ratio: 0.01739, Grade: B\",\"StationNumber: 21MR45, Year: 2021, PEL ratio: 0.06525, Grade: C\",\"StationNumber: 21MR47, Year: 2021, PEL ratio: 0.01081, Grade: B\",\"StationNumber: 21MR52, Year: 2021, PEL ratio: 0.01768, Grade: B\",\"StationNumber: 21MTB40, Year: 2021, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 21MTB43, Year: 2021, PEL ratio: 0.03909, Grade: C\",\"StationNumber: 21MTB48, Year: 2021, PEL ratio: 0.01998, Grade: B\",\"StationNumber: 21MTB62, Year: 2021, PEL ratio: 0.01841, Grade: B\",\"StationNumber: 21OTB08, Year: 2021, PEL ratio: 0.00752, Grade: A\",\"StationNumber: 21OTB12, Year: 2021, PEL ratio: 0.05583, Grade: C\",\"StationNumber: 21OTB13, Year: 2021, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 21OTB18, Year: 2021, PEL ratio: 0.01239, Grade: B\",\"StationNumber: 21OTB21, Year: 2021, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 21OTB25, Year: 2021, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 21OTB28, Year: 2021, PEL ratio: 0.00379, Grade: A\",\"StationNumber: 21TCB02, Year: 2021, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 21TCB13, Year: 2021, PEL ratio: 0.04086, Grade: C\",\"StationNumber: 21TCB22, Year: 2021, PEL ratio: 0.01641, Grade: B\",\"StationNumber: 21TCB26, Year: 2021, PEL ratio: 0.01436, Grade: B\",\"StationNumber: 22BCB02, Year: 2022, PEL ratio: 0.10158, Grade: D\",\"StationNumber: 22BCB05, Year: 2022, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 22BCB11, Year: 2022, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 22BCB12, Year: 2022, PEL ratio: 0.01548, Grade: B\",\"StationNumber: 22BCB17, Year: 2022, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 22BCB27, Year: 2022, PEL ratio: 0.02323, Grade: C\",\"StationNumber: 22BCB30, Year: 2022, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 22BCB34, Year: 2022, PEL ratio: 0.00532, Grade: A\",\"StationNumber: 22BCB35, Year: 2022, PEL ratio: 0.00406, Grade: A\",\"StationNumber: 22BCB45, Year: 2022, PEL ratio: 0.011, Grade: 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data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"Create colorized table water quality outcomes segment includes management action chlorophyll, light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(   epcdata,   txtsz = 3,   trgs = NULL,   yrrng = c(1975, 2023),   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   abbrev = FALSE,   family = NA,   historic = TRUE,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"function provides combined output show_wqmatrix show_matrix functions. one bay segment can plotted function call.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"Plot chlorophyll secchi data together matrix outcomes","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(   epcdata,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   yrrng = c(1975, 2023),   family = NULL,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" yrrng numeric year range plot family optional chr string indicating font family text labels partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"interactive plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"function combines outputs show_thrplot show_segmatrix selected bay segment. plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(epcdata)  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3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1975.5,1976.5,1976.5,1975.5,1975.5,null,1976.5,1977.5,1977.5,1976.5,1976.5,null,1977.5,1978.5,1978.5,1977.5,1977.5,null,1978.5,1979.5,1979.5,1978.5,1978.5,null,1979.5,1980.5,1980.5,1979.5,1979.5,null,1980.5,1981.5,1981.5,1980.5,1980.5,null,1981.5,1982.5,1982.5,1981.5,1981.5,null,1982.5,1983.5,1983.5,1982.5,1982.5,null,1984.5,1985.5,1985.5,1984.5,1984.5,null,1985.5,1986.5,1986.5,1985.5,1985.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: 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3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1988.5,1989.5,1989.5,1988.5,1988.5,null,1989.5,1990.5,1990.5,1989.5,1989.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1997.5,1998.5,1998.5,1997.5,1997.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2010.5,2011.5,2011.5,2010.5,2010.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,1974.5,1975.5,1975.5,1974.5,1974.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: large (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5,null,1975.5,1976.5,1976.5,1975.5,1975.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 3, Exceedance: large (size), NA 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Outcome: 3, Exceedance: large (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1987.5,1988.5,1988.5,1987.5,1987.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1996.5,1997.5,1997.5,1996.5,1996.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1992.5,1993.5,1993.5,1992.5,1992.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998.5,1999.5,1999.5,1998.5,1998.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 0, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"name\":\"yellow\",\"legendgroup\":\"yellow\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2015.5,2016.5,2016.5,2015.5,2015.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Caution (chla: 1, la: 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1975<br />yval: 0.9780952<br />\",\"yr: 1976<br />yval: 1.1759318<br />\",\"yr: 1977<br />yval: 1.1896016<br />\",\"yr: 1978<br />yval: 1.1682173<br />\",\"yr: 1979<br />yval: 1.7595230<br />\",\"yr: 1980<br />yval: 1.3836268<br />\",\"yr: 1981<br />yval: 1.0469025<br />\",\"yr: 1982<br />yval: 1.0583860<br />\",\"yr: 1983<br />yval: 1.1152678<br />\",\"yr: 1984<br />yval: 1.1617502<br />\",\"yr: 1985<br />yval: 0.9534905<br />\",\"yr: 1986<br />yval: 0.8929313<br />\",\"yr: 1987<br />yval: 0.8536198<br />\",\"yr: 1988<br />yval: 0.8558599<br />\",\"yr: 1989<br />yval: 0.9374651<br />\",\"yr: 1990<br />yval: 0.8353229<br />\",\"yr: 1991<br />yval: 0.8031788<br />\",\"yr: 1992<br />yval: 0.8166729<br />\",\"yr: 1993<br />yval: 0.9133746<br />\",\"yr: 1994<br />yval: 0.7481484<br />\",\"yr: 1995<br />yval: 0.9379637<br />\",\"yr: 1996<br />yval: 0.9202700<br />\",\"yr: 1997<br />yval: 0.8473840<br />\",\"yr: 1998<br />yval: 1.0612729<br />\",\"yr: 1999<br />yval: 0.8801655<br />\",\"yr: 2000<br />yval: 0.7328166<br />\",\"yr: 2001<br />yval: 0.9512714<br />\",\"yr: 2002<br />yval: 0.9272802<br />\",\"yr: 2003<br />yval: 1.0370998<br />\",\"yr: 2004<br />yval: 0.8777406<br />\",\"yr: 2005<br />yval: 0.7693579<br />\",\"yr: 2006<br />yval: 0.6204267<br />\",\"yr: 2007<br />yval: 0.6771304<br />\",\"yr: 2008<br />yval: 0.6962244<br />\",\"yr: 2009<br />yval: 0.8076962<br />\",\"yr: 2010<br />yval: 0.8419635<br />\",\"yr: 2011<br />yval: 0.9122183<br />\",\"yr: 2012<br />yval: 0.6867633<br />\",\"yr: 2013<br />yval: 0.5674502<br />\",\"yr: 2014<br />yval: 0.6056886<br />\",\"yr: 2015<br />yval: 0.5604978<br />\",\"yr: 2016<br />yval: 0.5747356<br />\",\"yr: 2017<br />yval: 0.6821210<br />\",\"yr: 2018<br />yval: 0.6780425<br />\",\"yr: 2019<br />yval: 0.7396049<br />\",\"yr: 2020<br />yval: 0.7686231<br />\",\"yr: 2021<br />yval: 0.7783039<br />\",\"yr: 2022<br />yval: 0.7871073<br />\",\"yr: 2023<br />yval: 0.7344259<br 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Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"Map site bay segment attainment categories selected year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(   epcdata,   yrsel,   param = c(\"chla\", \"la\"),   trgs = NULL,   thrs = FALSE,   partialyr = FALSE,   base_size = 12,   family = NA )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"epcdata data frame epc data returned read_importwq yrsel numeric year plot param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation trgs optional data.frame annual bay segment water quality targets, defaults targets thrs logical indicating attainment category relative targets (default) thresholds, passed anlz_attainsite partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter base_size numeric indicating text scaling size plot family optional chr string indicating font family text labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"map similar returned show_sitemap addition polygons bay segment colored annual attainment category site points sized relative selected parameter param.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(epcdata, yrsel = 2023) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Plot matrix Tampa Bay Benthic Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"show_tbbimatrix(   tbbiscr,   bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"),   yrrng = c(1993, 2022),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"ggplot object showing trends time TBBI scores bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\").","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) show_tbbimatrix(tbbiscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"Plot matrix Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"show_tbnimatrix(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   perc = c(32, 46),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"ggplot object showing trends time TBNI scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbnimatrix(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"Plot Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"show_tbniscr(   tbniscr,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   perc = c(32, 46),   alph = 1,   ylim = c(22, 58),   rev = FALSE,   plotly = FALSE,   family = NA,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"tbniscr input dat frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscr(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"Plot Tampa Bay Nekton Index scores time average across bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"show_tbniscrall(   tbniscr,   perc = c(32, 46),   alph = 1,   ylim = c(22, 58),   rev = FALSE,   plotly = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"tbniscr input dat frame returned anlz_tbniscr perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscrall(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"Creates plotly object TBNI score plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"show_tbniscrplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"p ggplot object output show_tbniscr show_tbniscrall width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) p <- show_tbniscrall(tbniscr) show_tbniscrplotly(p)  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2010<br />TBNI_Score - seval: 47.60934<br />TBNI_Score + seval: 50.39066\",\"Year: 2011<br />TBNI_Score - seval: 46.50183<br />TBNI_Score + seval: 49.49817\",\"Year: 2012<br />TBNI_Score - seval: 43.50750<br />TBNI_Score + seval: 46.49250\",\"Year: 2013<br />TBNI_Score - seval: 45.54410<br />TBNI_Score + seval: 48.45590\",\"Year: 2014<br />TBNI_Score - seval: 47.54311<br />TBNI_Score + seval: 50.45689\",\"Year: 2015<br />TBNI_Score - seval: 50.54042<br />TBNI_Score + seval: 53.45958\",\"Year: 2016<br />TBNI_Score - seval: 50.54140<br />TBNI_Score + seval: 53.45860\",\"Year: 2017<br />TBNI_Score - seval: 47.53068<br />TBNI_Score + seval: 50.46932\",\"Year: 2018<br />TBNI_Score - seval: 46.51340<br />TBNI_Score + seval: 49.48660\",\"Year: 2019<br />TBNI_Score - seval: 44.52515<br />TBNI_Score + seval: 47.47485\",\"Year: 2020<br />TBNI_Score - seval: 46.47367<br />TBNI_Score + seval: 49.52633\",\"Year: 2021<br />TBNI_Score - seval: 40.58822<br />TBNI_Score + seval: 43.41178\",\"Year: 2022<br />TBNI_Score - seval: 40.63419<br />TBNI_Score + seval: 43.36581\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2023<br />TBNI_Score - seval: 42.70511<br />TBNI_Score + seval: 45.29489\",\"Year: 2022<br />TBNI_Score - seval: 40.63419<br />TBNI_Score + seval: 43.36581\",\"Year: 2021<br />TBNI_Score - seval: 40.58822<br />TBNI_Score + seval: 43.41178\",\"Year: 2020<br />TBNI_Score - seval: 46.47367<br />TBNI_Score + seval: 49.52633\",\"Year: 2019<br />TBNI_Score - seval: 44.52515<br />TBNI_Score + seval: 47.47485\",\"Year: 2018<br />TBNI_Score - seval: 46.51340<br />TBNI_Score + seval: 49.48660\",\"Year: 2017<br />TBNI_Score - seval: 47.53068<br />TBNI_Score + seval: 50.46932\",\"Year: 2016<br />TBNI_Score - seval: 50.54140<br />TBNI_Score + seval: 53.45860\",\"Year: 2015<br />TBNI_Score - seval: 50.54042<br />TBNI_Score + seval: 53.45958\",\"Year: 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49\",\"Year: 2011<br />TBNI_Score: 48\",\"Year: 2012<br />TBNI_Score: 45\",\"Year: 2013<br />TBNI_Score: 47\",\"Year: 2014<br />TBNI_Score: 49\",\"Year: 2015<br />TBNI_Score: 52\",\"Year: 2016<br />TBNI_Score: 52\",\"Year: 2017<br />TBNI_Score: 49\",\"Year: 2018<br />TBNI_Score: 48\",\"Year: 2019<br />TBNI_Score: 46\",\"Year: 2020<br />TBNI_Score: 48\",\"Year: 2021<br />TBNI_Score: 42\",\"Year: 2022<br />TBNI_Score: 42\",\"Year: 2023<br />TBNI_Score: 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show_tdlcrk","text":"Make map tidal creek report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"show_tdlcrk(dat, weight = 1.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for tidal creek report card — show_tdlcrk","text":"dat input creek score data returned anlz_tdlcrk weight numeric weight polylines, passed addPolylines","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for tidal creek report card — show_tdlcrk","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrk(dat)  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MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addLegend\",\"args\":[{\"colors\":[\"#ADD8E6\",\"#2DC938\",\"#E9C318\",\"#EE7600\",\"#FF4040\"],\"labels\":[\"No Data\",\"Monitor\",\"Caution\",\"Investigate\",\"Prioritize\"],\"na_color\":null,\"na_label\":\"NA\",\"opacity\":1,\"position\":\"topright\",\"type\":\"factor\",\"title\":\"Creek scores\",\"extra\":null,\"layerId\":null,\"className\":\"info 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Monitor\",\"WBID: 2073, JEI: CC110, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2074B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2077, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC15, Name: Rock Creek, Creek score: No Data\",\"WBID: 2045, JEI: CC15, Name: Rock Creek, Creek score: Monitor\",\"WBID: 1991B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2010B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2025, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2043, JEI: CC16, Name: Apollo Waterway, Creek score: Monitor\",\"WBID: 1991A, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC18, Name: Sam Knight Creek, Creek score: Monitor\",\"WBID: 2055, JEI: CC18, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC25, Name: NA, Creek score: Investigate\",\"WBID: 2060A1, JEI: CC26, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC28, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2046, JEI: CC31, Name: NA, Creek score: Monitor\",\"WBID: 2056D, JEI: CC34, Name: Little Alligator Creek, Creek score: No Data\",\"WBID: 2056E, JEI: CC34, Name: Little Alligator Creek, Creek score: Monitor\",\"WBID: 2056D, JEI: CC36, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC36, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC37, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC40, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC41, Name: NA, Creek score: No Data\",\"WBID: 2056B, JEI: CC42, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC42, Name: NA, Creek score: Monitor\",\"WBID: 2056C2, JEI: CC44, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC45, Name: NA, Creek score: Prioritize\",\"WBID: 2056E, JEI: CC45, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC46, Name: NA, Creek score: No Data\",\"WBID: 2056C1, JEI: CC47, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2080, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2087, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC49, Name: NA, Creek score: No Data\",\"WBID: 1991A, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2053, JEI: CC50, Name: NA, Creek score: Monitor\",\"WBID: 2055, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC51, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC52, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC53, Name: Myrtle Slough, Creek score: No Data\",\"WBID: 2054, JEI: CC53, Name: Myrtle Slough, Creek score: Monitor\",\"WBID: 2041A, JEI: CC54, Name: NA, Creek score: No Data\",\"WBID: 2059, JEI: CC55, Name: NA, Creek score: Monitor\",\"WBID: 2059, JEI: CC56, Name: NA, Creek score: Investigate\",\"WBID: 2062, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2063, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2065A, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC62, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2063, JEI: CC64, Name: North Fork Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC64, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2074, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2077, JEI: CC65, Name: Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2074B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2077, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2081, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2081, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2084, JEI: CC67, Name: South Silcox Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2086, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2088, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC70, Name: Pirate Canal, Creek score: No Data\",\"WBID: 2082A, JEI: CC70, Name: Pirate Canal, Creek score: Monitor\",\"WBID: 2065B, JEI: CC71, Name: NA, Creek score: No Data\",\"WBID: 2094, JEI: CC72, Name: Bear Branch, Creek score: No Data\",\"WBID: 2093A, JEI: CC73, Name: Hog Branch, Creek score: No Data\",\"WBID: 2079, JEI: CC74, Name: Whidden Creek, Creek score: Monitor\",\"WBID: 2065B, JEI: CC75, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 1983B, JEI: CC77, Name: Lemon Creek, Creek score: Monitor\",\"WBID: 2076, JEI: CC77, Name: Lemon Creek, Creek score: Prioritize\",\"WBID: 2089, JEI: CC78, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC80, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC81, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC82, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC83, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC84, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC85, Name: NA, Creek score: No Data\",\"WBID: 2065A, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC87, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC88, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC89, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC90, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048C, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC95, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC96, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC97, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC99, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC01, Name: NA, Creek score: No Data\",\"WBID: 2033, JEI: DC01, Name: NA, Creek score: Monitor\",\"WBID: 1623A, JEI: DC02, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC03, Name: NA, Creek score: No Data\",\"WBID: 2028, JEI: DC03, Name: NA, Creek score: Prioritize\",\"WBID: 1623A, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC07, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC08, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2035, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2056C1, JEI: DC11, Name: NA, Creek score: No Data\",\"WBID: 1513E, JEI: HC01, Name: Double Branch Creek, Creek score: Monitor\",\"WBID: 1513F, JEI: HC01, Name: Double Branch Creek, Creek score: No Data\",\"WBID: 1513E, JEI: HC02, Name: NA, Creek score: Monitor\",\"WBID: 1513F, JEI: HC02, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC03, Name: Channel A, Creek score: No Data\",\"WBID: 1507A, JEI: HC03, Name: Channel A, Creek score: Monitor\",\"WBID: 1563, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1581, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1516, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1558I, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1563, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1558I, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1563, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1587A, JEI: HC06, Name: Woods Creek, Creek score: Monitor\",\"WBID: 1558I, JEI: HC07, Name: Peppermound Creek, Creek score: No Data\",\"WBID: 1577A, JEI: HC07, Name: Peppermound Creek, Creek score: Monitor\",\"WBID: 1570, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1570A, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1601A, JEI: HC08, Name: Sweetwater Creek, Creek score: No Data\",\"WBID: 1594, JEI: HC09, Name: Fish Creek, Creek score: Monitor\",\"WBID: 1606, JEI: HC10, Name: Lemon Street Ditch, Creek score: No Data\",\"WBID: 1536E, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1584A1, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1536A, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC16, Name: Ironhead Creek, Creek score: Prioritize\",\"WBID: 1605, JEI: HC17, Name: Delaney Creek, Creek score: Monitor\",\"WBID: 1605D, JEI: HC17, Name: Delaney Creek, Creek score: Investigate\",\"WBID: 1636, JEI: HC18, Name: Port Sutton Ditch, Creek score: Prioritize\",\"WBID: 1637, JEI: HC18, Name: Port Sutton Ditch, Creek score: No Data\",\"WBID: 1636, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1605, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1628, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1632, JEI: HC20, Name: Delaney Creek Popoff, Creek score: Monitor\",\"WBID: 1558E, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628A, JEI: HC21, Name: North Archie Creek, Creek score: Monitor\",\"WBID: 1632, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC22, Name: South Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC22, Name: South Archie Creek, Creek score: Investigate\",\"WBID: 1628A, JEI: HC22, Name: South Archie Creek, Creek score: Monitor\",\"WBID: 1635B, JEI: HC23, Name: Buckhorn Creek, Creek score: Monitor\",\"WBID: 1659, JEI: HC24, Name: Rice Creek, Creek score: Monitor\",\"WBID: 1558D, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1666, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1666A, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1686, JEI: HC25, Name: Bullfrog Creek, Creek score: Prioritize\",\"WBID: 1688, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1693, JEI: HC26, Name: Jackson Branch, Creek score: No Data\",\"WBID: 1693, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1708, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1712, JEI: HC28, Name: Beever Creek, Creek score: No Data\",\"WBID: 1719, JEI: HC29, Name: NA, Creek score: Prioritize\",\"WBID: 1725, JEI: HC30, Name: NA, Creek score: No Data\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1736, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1558C, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1725, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1736, JEI: HC32, Name: Wolf Branch, Creek score: Monitor\",\"WBID: 1742A1, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747A, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747B, JEI: HC33, Name: Marsh Branch, Creek score: Prioritize\",\"WBID: 1742C1, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC34, Name: Curiosity Creek, Creek score: Investigate\",\"WBID: 1798, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC35, Name: NA, Creek score: Caution\",\"WBID: 1779, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1742C1, JEI: HC37, Name: Sun City Slough, Creek score: No Data\",\"WBID: 1771, JEI: HC37, Name: Sun City Slough, Creek score: Caution\",\"WBID: 1778, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1788, JEI: HC38, Name: Cockroach Creek, Creek score: Prioritize\",\"WBID: 1789, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1789, JEI: HC39, Name: Piney Point Creek, Creek score: Prioritize\",\"WBID: 1797B, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1816, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC40, Name: Coon Hammock Creek\\r\\n, Creek score: No Data\",\"WBID: 1621G, JEI: HC41, Name: NA, Creek score: No Data\",\"WBID: 1558I, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1566, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1609, JEI: HC44, Name: Gun Branch, Creek score: No Data\",\"WBID: 1558G, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1609, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1584A1, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1584B, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1664, JEI: HC48, Name: Gibsonton Creek, Creek score: No Data\",\"WBID: 1558D, JEI: HC49, Name: Dug Creek, Creek score: No Data\",\"WBID: 1676A, JEI: HC49, Name: Dug Creek, Creek score: Caution\",\"WBID: 1682, JEI: HC50, Name: Kitchen Branch, Creek score: Monitor\",\"WBID: 1691, JEI: HC51, Name: Sims Branch, Creek score: No Data\",\"WBID: 1778, JEI: HC52, Name: Andrews Creek, Creek score: No Data\",\"WBID: 1682, JEI: HC53, Name: NA, Creek score: Monitor\",\"WBID: 1558C, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 2065D, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2082B, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B1, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2093A, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B, JEI: LC02, Name: Yucca Pen Creek, Creek score: Prioritize\",\"WBID: 2082B2, JEI: LC02, Name: Yucca Pen Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC03, Name: Durden Creek, Creek score: No Data\",\"WBID: 2082C, JEI: LC03, Name: Durden Creek, Creek score: Investigate\",\"WBID: 2082C1, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2082C2, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2082C1, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2065F, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC07, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC08, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC10, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240A1, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240EA, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240E1, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240EB, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240B, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240EA, JEI: LC21, Name: Powell Creek, Creek score: Investigate\",\"WBID: 3240L, JEI: LC21, Name: Powell Creek, Creek score: Monitor\",\"WBID: 2082C, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240B, JEI: LC22, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC23, Name: Daughtrey Creek, Creek score: No Data\",\"WBID: 3240F, JEI: LC23, Name: Daughtrey Creek, Creek score: Monitor\",\"WBID: 3240B1, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240F, JEI: LC24, Name: NA, Creek score: No Data\",\"WBID: 3240B1, JEI: LC25, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC25, Name: NA, Creek score: No Data\",\"WBID: 3240Q, JEI: LC26, Name: Popash Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240M, JEI: LC27, Name: Stroud Creek, Creek score: Monitor\",\"WBID: 3240Q, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240C, JEI: LC28, Name: Palm Creek, Creek score: No Data\",\"WBID: 3240C1, JEI: LC28, Name: Palm Creek, Creek score: Monitor\",\"WBID: 3240G, JEI: LC29, Name: Owl Creek, Creek score: No Data\",\"WBID: 3240N, JEI: LC29, Name: Owl Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC30, Name: Trout Creek, Creek score: No Data\",\"WBID: 3240G, JEI: LC30, Name: Trout Creek, Creek score: Monitor\",\"WBID: 3236A, JEI: LC31, Name: Telegraph Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC33, Name: Orange River, Creek score: No Data\",\"WBID: 3240K, JEI: LC33, Name: Orange River, Creek score: Monitor\",\"WBID: 3240B, JEI: LC35, Name: Billy Creek, Creek score: No Data\",\"WBID: 3240J1, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J2, JEI: LC35, Name: Billy Creek, Creek score: Investigate\",\"WBID: 3240J3, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J4, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC36, Name: Manuel Branch, Creek score: No Data\",\"WBID: 3240V, JEI: LC36, Name: Manuel Branch, Creek score: Monitor\",\"WBID: 3240H1, JEI: LC39, Name: Whiskey Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC40, Name: NA, Creek score: Monitor\",\"WBID: 3240A4, JEI: LC40, Name: NA, Creek score: Caution\",\"WBID: 3240A4, JEI: LC43, Name: NA, Creek score: No Data\",\"WBID: 3240O, JEI: LC44, Name: NA, Creek score: No Data\",\"WBID: 3258A1, JEI: LC45, Name: Cow Creek, Creek score: No Data\",\"WBID: 3258B2, JEI: LC46, Name: Hendry Creek, Creek score: Caution\",\"WBID: 3258X, JEI: LC46, Name: Hendry Creek, Creek score: No Data\",\"WBID: 3258C2, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258C4, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC47, Name: Mullock Creek, Creek score: No Data\",\"WBID: 3258D1, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258H2, JEI: LC49, Name: NA, Creek score: No Data\",\"WBID: 3258H2, JEI: LC50, Name: Spring Creek, Creek score: Caution\",\"WBID: 3258H3, JEI: LC50, Name: Spring Creek, Creek score: Monitor\",\"WBID: 3258EB, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EC, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258ED, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EG, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: No Data\",\"WBID: 3258F, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 2065F, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC54, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC55, Name: Underhill Creek, Creek score: No Data\",\"WBID: 2065F, JEI: LC56, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC58, Name: NA, Creek score: No Data\",\"WBID: 3258C4, JEI: LC59, Name: Mud Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC59, Name: Mud Creek, Creek score: No Data\",\"WBID: 3258C4, JEI: LC60, Name: NA, Creek score: No Data\",\"WBID: 1792, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1823, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1825A, JEI: MC02, Name: Frog Creek, Creek score: Investigate\",\"WBID: 1825B, JEI: MC02, Name: Frog Creek, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC04, Name: McMullen Creek, Creek score: No Data\",\"WBID: 1841, JEI: MC04, Name: McMullen Creek, Creek score: Monitor\",\"WBID: 1797A, JEI: MC05, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC06, Name: Palmetto Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC07, Name: King Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC08, Name: Memphis Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC09, Name: NA, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC09, Name: NA, Creek score: No Data\",\"WBID: 1848A, JEI: MC10, Name: NA, Creek score: Prioritize\",\"WBID: 1848B, JEI: MC10, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1850, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1872B, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1909, JEI: MC13, Name: Mill Creek, Creek score: No Data\",\"WBID: 1872A, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC14, Name: Gates Creek, Creek score: No Data\",\"WBID: 1874, JEI: MC14, Name: Gates Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC15, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC16, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC20, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1875, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1876, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1848B, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC26, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC27, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC28, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1876A, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1899, JEI: MC29, Name: Gap Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D2, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1876, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1887, JEI: MC30, Name: Sugarhouse Creek, Creek score: Monitor\",\"WBID: 1876, JEI: MC31, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848D2, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC33, Name: NA, Creek score: No Data\",\"WBID: 1885A, JEI: MC34, Name: Wares Creek, Creek score: Caution\",\"WBID: 1888A, JEI: MC34, Name: Wares Creek, Creek score: No Data\",\"WBID: 1888B, JEI: MC35, Name: Palma Sola Creek, Creek score: No Data\",\"WBID: 1883, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC37, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC38, Name: Cedar Hammock Creek, Creek score: No Data\",\"WBID: 1896, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1899, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1888A, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC41, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC42, Name: NA, Creek score: No Data\",\"WBID: 1868, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1883, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1901, JEI: MC44, Name: Williams Creek, Creek score: Monitor\",\"WBID: 1797B, JEI: MC45, Name: Little Redfish Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC46, Name: Peterson Creek, Creek score: No Data\",\"WBID: 1888A, JEI: MC47, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1618C, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1618D, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1625, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1641, JEI: PC02, Name: Cross Bayou, Creek score: Caution\",\"WBID: 1662, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1662, JEI: PC03, Name: NA, Creek score: Caution\",\"WBID: 1662A, JEI: PC03, Name: NA, Creek score: Monitor\",\"WBID: 1641, JEI: PC04, Name: Saint Joes Creek, Creek score: No Data\",\"WBID: 1668A, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668B, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668D, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668E, JEI: PC04, Name: Saint Joes Creek, Creek score: Prioritize\",\"WBID: 1701A, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1701B, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1716B, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716D, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716A, JEI: PC07, Name: NA, Creek score: Investigate\",\"WBID: 1716C1, JEI: PC07, Name: NA, Creek score: No Data\",\"WBID: 1716D, JEI: PC07, Name: NA, Creek score: Monitor\",\"WBID: 1731, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1731A, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1716C1, JEI: PC08, Name: NA, Creek score: Caution\",\"WBID: 1716D, JEI: PC08, Name: NA, Creek score: Monitor\",\"WBID: 1709D, JEI: PC09, Name: Bayou Creek, Creek score: Investigate\",\"WBID: 1558B, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1709, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731B, JEI: PC10, Name: Salt Creek, Creek score: Monitor\",\"WBID: 1696, JEI: PC12, Name: Booker Creek, Creek score: Monitor\",\"WBID: 1709B, JEI: PC12, Name: Booker Creek, Creek score: No Data\",\"WBID: 1661B, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661G, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661A, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661H, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661I, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661D, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1625, JEI: PC16, Name: Cross Bayou, Creek score: Monitor\",\"WBID: 1627, JEI: PC17, Name: Long Branch, Creek score: Monitor\",\"WBID: 1627B, JEI: PC17, Name: Long Branch, Creek score: Caution\",\"WBID: 1558H, JEI: PC18, Name: Allen Creek, Creek score: No Data\",\"WBID: 1604, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B1, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B2, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1575, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1575A, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1569, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1569A, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1546, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1558I, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1528B, JEI: PC22, Name: NA, Creek score: No Data\",\"WBID: 1668F, JEI: PC23, Name: NA, Creek score: Monitor\",\"WBID: 1694B, JEI: PC23, Name: NA, Creek score: No Data\",\"WBID: 1530, JEI: PC24, Name: Moccasin Creek, Creek score: Caution\",\"WBID: 1558H, JEI: PC25, Name: Grassy Creek, Creek score: No Data\",\"WBID: 1541A, JEI: PC26, Name: Briar Creek, Creek score: No Data\",\"WBID: 1541C, JEI: PC26, Name: Briar Creek, Creek score: Monitor\",\"WBID: 1479, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 8045G, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 1538, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1538A, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1550, JEI: PC28, Name: Curlew Creek, Creek score: No Data\",\"WBID: 1556, JEI: PC29, Name: Cedar Creek, Creek score: Caution\",\"WBID: 1556A, JEI: PC29, Name: Cedar Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1567C, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1633, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1633E, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1643, JEI: PC32, Name: Church Creek, Creek score: Prioritize\",\"WBID: 1508, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1508A, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1527A, JEI: PC34, Name: Bee Branch, Creek score: No Data\",\"WBID: 1527B, JEI: PC34, Name: Bee Branch, Creek score: Monitor\",\"WBID: 1535, JEI: PC35, Name: Minnow Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC36, Name: Spring Branch, Creek score: No Data\",\"WBID: 1567B, JEI: PC36, Name: Spring Branch, Creek score: Monitor\",\"WBID: 1528, JEI: PC37, Name: Rattlesnake Creek, Creek score: No Data\",\"WBID: 1614, JEI: PC37, Name: Rattlesnake Creek, Creek score: Prioritize\",\"WBID: 1936, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1936A, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1953, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1953A, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1968C, JEI: SC02, Name: Hudson Bayou, Creek score: No Data\",\"WBID: 1937, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1947, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1975D, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975C, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975A, JEI: SC06, Name: Clower Creek, Creek score: Investigate\",\"WBID: 1984A, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984AB, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984B, JEI: SC07, Name: Catfish/North Creek, Creek score: Monitor\",\"WBID: 1982, JEI: SC08, Name: South Creek, Creek score: Investigate\",\"WBID: 1982A, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1982B, JEI: SC08, Name: South Creek, Creek score: Prioritize\",\"WBID: 1985, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1924, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924B, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994B, JEI: SC12, Name: Shakett Creek, Creek score: Monitor\",\"WBID: 2002, JEI: SC12, Name: Shakett Creek, Creek score: Caution\",\"WBID: 2009B, JEI: SC14, Name: Curry Creek, Creek score: Caution\",\"WBID: 2009C, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2016, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2018A, JEI: SC14, Name: Curry Creek, Creek score: Monitor\",\"WBID: 2015, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 2015A, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 1983A1, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: No Data\",\"WBID: 2030, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: Caution\",\"WBID: 1983A1, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2042, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2039, JEI: SC22, Name: Forked Creek, Creek score: Monitor\",\"WBID: 1983B, JEI: SC25, Name: Gottfried Creek, Creek score: No Data\",\"WBID: 2049, JEI: SC25, Name: Gottfried Creek, Creek score: Caution\",\"WBID: 1991C, JEI: SC26, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC27, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 2038, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 2037, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 2036, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 2034, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC32, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC32, Name: NA, Creek score: Investigate\",\"WBID: 1991E, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2029, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 1991G, JEI: SC34, Name: NA, Creek score: No Data\",\"WBID: 2011, JEI: SC34, Name: NA, Creek score: Monitor\",\"WBID: 2006, JEI: SC35, Name: NA, Creek score: No Data\",\"WBID: 1978, JEI: SC36, Name: Deer Prairie Creek, Creek score: Monitor\",\"WBID: 1991E, JEI: SC36, Name: Deer Prairie Creek, Creek score: No Data\",\"WBID: 1991C, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991C, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2014, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2026, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 2026A, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 1991C, JEI: SC39, Name: NA, Creek score: No Data\",\"WBID: 1976B, JEI: SC40, Name: Big Slough Canal, Creek score: Investigate\",\"WBID: 1976C, JEI: SC40, Name: Big Slough Canal, Creek score: Monitor\",\"WBID: 2014, JEI: SC40, Name: Big Slough Canal, Creek score: No Data\",\"WBID: 1991B, JEI: SC41, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC42, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC43, Name: NA, Creek score: No Data\",\"WBID: 2057, JEI: SC43, Name: NA, Creek score: No Data\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[26.32829183658335,28.12975168603929],\"lng\":[-82.83757582032332,-81.68445583408415]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"Plotly barplots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"show_tdlcrkindic(   id,   cntdat,   yr = 2023,   thrsel = FALSE,   pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindic(id, cntdat, thrsel = TRUE)  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empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"Plotly empirical CDF plots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"show_tdlcrkindiccdf(   id,   cntdat,   yr = 2023,   thrsel = FALSE,   pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"function returns several empirical cumulative distribution plots tidal creek context indicators.  Points plot indicate observed values percentiles creek specified id. percentiles CDF values defined \"population\" creeks cntdat.  Points plots color-coded sample year evaluate temporal trends, .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindiccdf(id, cntdat, thrsel = TRUE)  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a line or annotation to a plotly graph — show_tdlcrkline","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"Add line annotation plotly graph tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"show_tdlcrkline(   varin = c(\"CHLAC\", \"TN\", \"chla_tn_ratio\", \"DO\", \"tsi\", \"no23_ratio\"),   thrsel = FALSE,   horiz = TRUE,   annotate = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"varin chr string indicator thrsel logical something returned, otherwise NULL, hack working plotly output horiz logical indicating output horizontal vertical annotate logical indicating output line annotation text","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"list object passed layout argument plotly, either shapes annotate depending user input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"function used internally within show_tdlcrkindic show_tdlcrkindiccdf","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"# code for vertical line output, chloropyll show_tdlcrkline('CHLAC', thrsel = TRUE) #> [[1]] #> [[1]]$type #> [1] \"line\" #>  #> [[1]]$x0 #> [1] 0 #>  #> [[1]]$x1 #> [1] 1 #>  #> [[1]]$xref #> [1] \"paper\" #>  #> [[1]]$y0 #> [1] 11 #>  #> [[1]]$y1 #> [1] 11 #>  #> [[1]]$line #> [[1]]$line$color #> [1] \"red\" #>  #> [[1]]$line$dash #> [1] 10 #>  #>  #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"Plot tidal creek report card matrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"show_tdlcrkmatrix(   dat,   class = c(\"3M\", \"2\"),   score = c(\"Prioritize\", \"Investigate\", \"Caution\", \"Monitor\"),   family = NA,   size = 11 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"dat input creek score data returned anlz_tdlcrk class character vector indicating creek classes show, one many '3M', '2', '3F', '1'.  Defaults marine ('3M', '2'). score character vector score categories include, one many 'Prioritize', 'Investigate', 'Caution', 'Monitor'. Defaults . family optional chr string indicating font family text labels size numeric text line scaling","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"static ggplot object returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"plot shows matrix rows individual creeks columns overall creek score.  columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories.  Number years mapped cell transparency.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkmatrix(dat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":null,"dir":"Reference","previous_headings":"","what":"Radar plots for tidal creek indicators — show_tdlcrkradar","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"Radar plots tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"show_tdlcrkradar(   id,   cntdat,   col = \"#338080E6\",   ptsz = 1,   lbsz = 0.8,   valsz = 1,   brdwd = 5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic col color input polygon line portions ptsz numeric size points lbsz numeric size text labels valsz numeric size numeric value labels brdwd numeric polygon border width","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"radar plot","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"See details anlz_tdlcrkindic explanation indicators Internal code borrowed heavily radarchart function fmsb package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = TRUE)  set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id, cntdat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"Plot annual water quality values, targets, thresholds bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(   epcdata,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   thr = c(\"chla\", \"la\"),   trgs = NULL,   yrrng = c(1975, 2023),   family = NA,   labelexp = TRUE,   txtlab = TRUE,   thrs = FALSE,   partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" thr chr string indicating water quality value appropriate target/threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets/thresholds, defaults targets yrrng numeric vector indicating min, max years include family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot thrs logical indicating reference lines shown regulatory threshold partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(epcdata, bay_segment = 'OTB', thr = 'chl')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot results for a seagrass transect by time and location — show_transect","title":"Plot results for a seagrass transect by time and location — show_transect","text":"Plot results seagrass transect time location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"show_transect(   transect,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   yrrng = c(1998, 2023),   varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"),   base_size = 12,   facet = FALSE,   ncol = NULL,   plotly = FALSE,   width = NULL,   height = NULL,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot results for a seagrass transect by time and location — show_transect","text":"transect data frame returned read_transect site chr string indicating site results plot species chr string indicating one many species plot yrrng numeric indicating year ranges evaluate varplo chr string indicating variable plot base_size numeric indicating text scaling size plot facet logical indicating plots separated facets species ncol numeric indicating number columns facet = TRUE plotly logical plot created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot results for a seagrass transect by time and location — show_transect","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot results for a seagrass transect by time and location — show_transect","text":"sites along transect surveyed shown plot, including selected species found.  latter colored grey hollow points.  Species options include Halodule, Syringodium, Thalassia, Halophila, Ruppia, Caulerpa (attached macroalgae), /Dapis (cyanobacteria). Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. Note plotly = TRUE, size legend shown.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # }  # one species show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance')   # multiple species, one plot show_transect(transect, site = 'S3T10',   species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia',     'Caulerpa', 'Dapis'),   varplo = 'Abundance')   # multiple species, multiple plots show_transect(transect, site = 'S3T10',   species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia',     'Caulerpa', 'Dapis'),   varplo = 'Abundance', facet = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Show annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"show_transectavespp(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   yrrng = c(1998, 2023),   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   total = TRUE,   alph = 1,   family = NA,   plotly = FALSE,   asreact = FALSE,   width = NULL,   height = NULL,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned, applies asreact = FALSE alph numeric indicating alpha value score category colors family optional chr string indicating font family text labels plotly logical matrix created using plotly asreact logical reactable table returned instead plot width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"asreact = F, ggplot plotly (plotly = T) object returned showing trends time species selected bay segments.  asreact = T, reactable table showing results year, segment, species returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Results based averages across species date transect bay segment. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"plot representation figure 2 Johansson, R. (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida. table representation table 2, p. 163 Yarbro, L. ., P. R. Carlson, Jr., eds. 2016. Seagrass Integrated Mapping Monitoring Program: Mapping Monitoring Report . 2. Fish Wildlife Research Institute Technical Report TR-17 version 2. vi + 281 p.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectavespp(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Show matrix seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"show_transectmatrix(   transectocc,   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"),   total = TRUE,   neutral = FALSE,   yrrng = c(1998, 2023),   alph = 1,   txtsz = 3,   family = NA,   rev = FALSE,   position = \"top\",   plotly = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments neutral logical indicating neutral continuous color scheme used yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"ggplot object showing trends time bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Results based averages across species date transect bay segment color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence.  necessarily translate ecological breakpoints.  Use neutral = TRUE use neutral continuous color palette.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"plot representation Table 1 R. Johansson (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectmatrix(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"Plot frequency occurrence seagrass transect time species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"show_transectsum(   transectocc,   site,   species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\",     \"Dapis\"),   yrrng = c(1998, 2023),   abund = FALSE,   sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"transectocc data frame returned anlz_transectocc site chr string indicating site results plot species chr string indicating species plot yrrng numeric indicating year ranges evaluate abund logical indicating abundance averages plotted instead frequency occurrence sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"if (FALSE) { # \\dontrun{ transect <- read_transect() } # } transectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10')  {\"x\":{\"visdat\":{\"1ab428e46349\":[\"function () 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a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"Create colorized table chlorophyll light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(   epcdata,   param = c(\"chla\", \"la\"),   txtsz = 3,   trgs = NULL,   yrrng = c(1975, 2023),   bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"),   asreact = FALSE,   nrows = 10,   abbrev = FALSE,   family = NA,   plotly = FALSE,   partialyr = FALSE,   width = NULL,   height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay stations by segment — stations","title":"Bay stations by segment — stations","text":"Bay stations segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay stations by segment — stations","text":"","code":"stations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay stations by segment — stations","text":"data frame 45 rows 4 variables: bay_segment chr epchc_station num Latitude num Longitude num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay subtidal cover — subtacres","title":"Tampa Bay subtidal cover — subtacres","text":"Tampa Bay subtidal cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"subtacres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay subtidal cover — subtacres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"if (FALSE) { # \\dontrun{ load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/subtacres.RData\"))  save(subtacres, file = 'data/subtacres.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"Spatial data object SWFWMD Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"swfwmdtbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"simple features sf object (MULTIPOLYGON) 7 features 1 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  levs <- c('oldTampaBay', 'hillsboroughBay', 'middleTampaBay',   'lowerTampaBay', 'bocaCiegaBay', 'terraCieaBay', 'manateeRiver') labs <- c('Old Tampa Bay', 'Hillsborough Bay', 'Middle Tampa Bay',   'Lower Tampa Bay', 'Boca Ciega Bay', 'Terra Ceia Bay', 'Manatee River')  swfwmdtbseg <- st_read(     dsn = 'T:/05_GIS/SWFWMD/Seagrass/2022_Seagrass/DraftMaps2022_1130.gdb',     layer = 'suncoastSeagrassSegments'   ) %>%   filter(waterbodyName %in% levs) %>%   mutate(     waterbodyName = factor(waterbodyName, levels = levs, labels = labs)   ) %>%   select(segment = waterbodyName) %>%   st_transform(crs = 4326)  save(swfwmdtbseg, file = 'data/swfwmdtbseg.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay segment targets — targets","title":"Bay segment targets — targets","text":"Bay segment specific management targets including low high magnitude exceedance thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay segment targets — targets","text":"","code":"targets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay segment targets — targets","text":"data frame 4 rows 8 variables: bay_segment chr name chr chla_target num chla_smallex num chla_thresh num la_target num la_smallex num la_thresh num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bay segment targets — targets","text":"","code":"if (FALSE) { # \\dontrun{  targets <- structure(list(    bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCBN\", \"BCBS\", \"TCB\", \"MR\", \"RALTB\"),    name = c(\"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\",       \"Boca Ciega Bay North\", \"Boca Ciega Bay South\", \"Terra Ceia Bay\", \"Manatee River\",       \"Remainder Lower Tampa Bay\"),    chla_target = c(8.5, 13.2, 7.4, 4.6, 7.7, 6.1, 7.5, 7.3, NaN),    chla_smallex = c(8.9, 14.1, 7.9, 4.8, NaN, NaN, NaN, NaN, NaN),    chla_thresh = c(9.3, 15, 8.5, 5.1, 8.3, 6.3, 8.7, 8.8, 5.1),    la_target = c(0.83, 1.58, 0.83, 0.63, NaN, NaN, NaN, NaN, NaN),    la_smallex = c(0.86, 1.63, 0.87, 0.66, NaN, NaN, NaN, NaN, NaN),    la_thresh = c(0.88, 1.67, 0.91, 0.68, NaN, NaN, NaN, NaN, NaN)),    class = \"data.frame\", row.names = c(NA, -9L)    )  save(targets, file = 'data/targets.RData') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"Reference conditions Tampa Bay Nekton Index metrics","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"tbniref"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"data frame 16 rows 12 variables: bay_segment chr Season chr NumTaxa_P5 num NumTaxa_P95 num BenthicTaxa_P5 num BenthicTaxa_P95 num TaxaSelect_P5 num TaxaSelect_P95 num NumGuilds_P5 num NumGuilds_P95 num Shannon_P5 num Shannon_P95 num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"if (FALSE) { # \\dontrun{  library(tbeptools)  tbniref <- anlz_tbnimet(fimdata) %>%   dplyr::filter(between(Year, 1998, 2015)) %>%   dplyr::select(Season, bay_segment, NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon) %>%   dplyr::group_by(bay_segment, Season) %>%   dplyr::summarize(NumTaxa_P5 = round(quantile(NumTaxa, probs = 0.05)),                    NumTaxa_P95 = round(quantile(NumTaxa, probs = 0.95)),                    BenthicTaxa_P5 = round(quantile(BenthicTaxa, probs = 0.05)),                    BenthicTaxa_P95 = round(quantile(BenthicTaxa, probs = 0.95)),                    TaxaSelect_P5 = round(quantile(TaxaSelect, probs = 0.05)),                    TaxaSelect_P95 = round(quantile(TaxaSelect, probs = 0.95)),                    NumGuilds_P5 = round(quantile(NumGuilds, probs = 0.05)),                    NumGuilds_P95 = round(quantile(NumGuilds, probs = 0.95)),                    Shannon_P5 = quantile(Shannon, probs = 0.05),                    Shannon_P95 = quantile(Shannon, probs = 0.95))  save(tbniref, file = 'data/tbniref.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"Reference table Tampa Bay Nekton Index species classifications","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"tbnispp"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"data frame 196 rows 10 variables: TSN int NODCCODE chr ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr)  # import and clean tbnispp <- read.csv('../tbni-proc/data/TBIndex_spp_codes.csv',     header = TRUE, stringsAsFactors = FALSE) %>%   mutate(     NODCCODE = as.character(NODCCODE),     NODCCODE = case_when(NODCCODE == \"9.998e+09\" ~ \"9998000000\",                              TRUE ~ NODCCODE)   )  save(tbnispp, file = 'data/tbnispp.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments — tbseg","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Note boundaries used formal analysis used visual aids mapping.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"tbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments — tbseg","text":"simple features sf object (POLYGON) 4 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Spatial data object Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE plot(st_geometry(tbseg))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"Note boundaries used formal analysis used visual aids mapping. data object differs tbseg including Boca Ciega Bay, Terra Ceia Bay, Manatee River. boundaries also detailed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"","code":"tbsegdetail"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"Spatial data object detailed Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegdetail.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of detailed Tampa Bay segments — tbsegdetail","text":"","code":"library(sf) plot(st_geometry(tbsegdetail))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"Spatial data object lines defining major Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"tbseglines"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"simple features sf object (LINESTRING) 3 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"library(sf) plot(st_geometry(tbseglines))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"Spatial data object Tampa Bay segments plus waterhseds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"tbsegshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"library(sf) plot(st_geometry(tbsegshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay watershed — tbshed","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"Spatial data object Tampa Bay watershed, includes bay proper","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"tbshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"simple features sf object (POLYGON) 1 feature 0 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"library(sf) if (FALSE) { # \\dontrun{ library(dplyr) tbshed <- st_read('T:/05_GIS/BOUNDARIES/TBEP_Watershed_Correct_Projection.shp') %>%   select(-Id, -Name, -Area_m, -Hectares) %>%   st_transform(crs = 4326)  save(tbshed, file = 'data/tbshed.RData', compress = 'xz') } # } plot(st_geometry(tbshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"tidalcreeks"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"simple features sf object (MULTILINESTRING) 615 features  fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs id num wbid chr JEI chr class chr name chr Creek_Length_m num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"File created using workflow <https://tbep-tech.github.io/tidalcreek-stats/Creek_select_tbeptools>, example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  prj <- 4326  # create sf object of creek population, join with creek length data tidalcreeks <- st_read(   dsn = '../../02_DOCUMENTS/tidal_creeks/TidalCreek_ALL_Line_WBID61.shp',   drivers = 'ESRI Shapefile'   ) %>%   st_transform(crs = prj) %>%   mutate(     id = 1:nrow(.)   ) %>%   select(id, name = Name, JEI = CreekID, wbid = WBID, class = CLASS, Creek_Length_m = Total_m)  # save save(tidalcreeks, file = 'data/tidalcreeks.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidal creek nitrogen targets — tidaltargets","title":"Tidal creek nitrogen targets — tidaltargets","text":"Tidal creek nitrogen targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidal creek nitrogen targets — tidaltargets","text":"","code":"tidaltargets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tidal creek nitrogen targets — tidaltargets","text":"data frame 2 rows 4 variables: region chr prioritize num investigate num caution num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"Seagrass transect data Tampa Bay current 04122024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"transect"},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"data frame 152580 rows 11 variables: Crew chr MonitoringAgency chr Date Date Transect chr Site chr Depth int Savspecies chr SeagrassEdge num var chr aveval num sdval num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"if (FALSE) { # \\dontrun{  transect <- read_transect()  save(transect, file = 'data/transect.RData', compress = 'xz')  } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect locations — trnlns","title":"Seagrass transect locations — trnlns","text":"Seagrass transect locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect locations — trnlns","text":"","code":"trnlns"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect locations — trnlns","text":"sf LINESTRING object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect locations — trnlns","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr)  trnlns <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/transect_routes.shp') %>%    st_transform(crs = 4326) %>%    dplyr::filter(!as.character(Site) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) %>%    dplyr::mutate_if(is.factor, as.character) %>%    dplyr::filter(Site %in% trnpts$TRAN_ID)  # add bearing, positive counter-clockwise from east bearing <- lapply(trnlns$geometry, function(x) geosphere::bearing(x[, c(1:2)])[[1]]) %>%   unlist()  trnlns$bearing <- bearing  save(trnlns, file = 'data/trnlns.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect starting locations — trnpts","title":"Seagrass transect starting locations — trnpts","text":"Seagrass transect starting locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect starting locations — trnpts","text":"","code":"trnpts"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect starting locations — trnpts","text":"sf POINT object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect starting locations — trnpts","text":"","code":"if (FALSE) { # \\dontrun{ library(sf) library(dplyr) library(tbeptools)  trnpts <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/TransectBasics2019.shp') %>%    st_transform(crs = 4326) %>%    dplyr::rename(MonAgency = 'MON_AGENCY') %>%    dplyr::filter(!as.character(TRAN_ID) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2'))  # s4t10 is slightly outside boundary for lower tampa bay s4t10 <- trnpts %>%    dplyr::filter(TRAN_ID %in% 'S4T10') %>%    dplyr::mutate(bay_segment = 'LTB')  trnpts <- trnpts %>%    sf::st_intersection(sf::st_make_valid(tbsegshed)) %>%    dplyr::select(-long_name) %>%    dplyr::mutate_if(is.factor, as.character) %>%    dplyr::bind_rows(s4t10)  save(trnpts, file = 'data/trnpts.RData', compress = 'xz') } # }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":null,"dir":"Reference","previous_headings":"","what":"Return leaflet icon set for FIB maps — util_fibicons","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"Return leaflet icon set FIB maps","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"","code":"util_fibicons(indic)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"indic character indicating \"entero\", \"fcolif\", \"fibmat\" Enterococcus, Fecal Coliform, FIB matrix maps, respectively","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"leaflet icon set returned iconList.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"Used internally show_enteromap wet/dry icons Enterococcus, show_fibmap E. Coli/Enterococcus icons (EPCHC data), show_fibmatmap matrix annual score category icons EPCHC non-EPCHC data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fibicons.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return leaflet icon set for FIB maps — util_fibicons","text":"","code":"util_fibicons(indic = 'entero') #> $entero_green_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red_wet #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_green_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red_dry #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\" util_fibicons(indic = 'fcolif') #> $ecoli_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $ecoli_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/ecoli_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $entero_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/entero_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\" util_fibicons(indic = 'fibmat') #> $fibmat_green #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_green.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_yellow #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_yellow.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_orange #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_orange.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_red #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_red.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> $fibmat_purple #> $iconUrl #> [1] \"/home/runner/work/_temp/Library/tbeptools/fibmat_purple.png\" #>  #> $iconWidth #> [1] 18 #>  #> $iconHeight #> [1] 18 #>  #> attr(,\"class\") #> [1] \"leaflet_icon\" #>  #> attr(,\"class\") #> [1] \"leaflet_icon_set\""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":null,"dir":"Reference","previous_headings":"","what":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"list Fecal Indicator Bacteria (FIB) factor levels labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"","code":"util_fiblevs()"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"list levels (often cutpoints) labels FIB categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A list of Fecal Indicator Bacteria (FIB) factor levels and labels — util_fiblevs","text":"","code":"util_fiblevs() #> $ecolilev #> [1] -Inf  126  410 1000  Inf #>  #> $ecolilbs #> [1] \"< 126\"     \"126 - 409\" \"410 - 999\" \"> 999\"     #>  #> $enterolev #> [1] -Inf   35  130 1000  Inf #>  #> $enterolbs #> [1] \"< 35\"      \"35 - 129\"  \"130 - 999\" \"> 999\"     #>  #> $fibmatlev #> [1] \"A\" \"B\" \"C\" \"D\" \"E\" #>  #> $fibmatlbs #> [1] \"A\" \"B\" \"C\" \"D\" \"E\" #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert character string to html class — util_html","title":"Convert character string to html class — util_html","text":"Convert character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert character string to html class — util_html","text":"","code":"util_html(text)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert character string to html class — util_html","text":"text character string input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert character string to html class — util_html","text":"input character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert character string to html class — util_html","text":"Adapted HTML","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert character string to html class — util_html","text":"","code":"util_html('abd') #> abd"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an empty leaflet map from sf input — util_map","title":"Create an empty leaflet map from sf input — util_map","text":"Create empty leaflet map sf input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"util_map(tomap, minimap = \"bottomleft\")"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an empty leaflet map from sf input — util_map","text":"tomap sf input object minimap character string indicating location minimap, use minimap = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an empty leaflet map from sf input — util_map","text":"leaflet object optional minimap ESRI provider tiles","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"tomap <- tibble::tibble(   lon = -82.6365,   lat = 27.75822   ) tomap <- sf::st_as_sf(tomap, coords = c('lon', 'lat'), crs = 4326) util_map(tomap)  {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.75822,-82.6365,27.75822,-82.6365,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]}]},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n  return (\\n      function(el, x) {\\n        var myMap = this;\\n        myMap.on('baselayerchange',\\n          function (e) {\\n            myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n          })\\n      }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":null,"dir":"Reference","previous_headings":"","what":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"Get organization name organization identifier USEPA Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin(org, stanm = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"org chr string indicating organization identifier, see read_importwqp valid entries stanm logical indicating character string column name specific organization returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"character string organization name corresponds organization identifier column name station identifier specific organization stanm = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin('21FLHILL_WQX') #> [1] \"Hillsborough\" util_orgin('21FLPASC_WQX', stanm = TRUE) #> [1] \"pasco_station\""}]