WeatherPy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# WeatherPy\n",
    "----\n",
    "\n",
    "#### Note\n",
    "* Instructions have been included for each segment. You do not have to follow them exactly, but they are included to help you think through the steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Dependencies and Setup\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "import time\n",
    "from scipy.stats import linregress\n",
    "from datetime import datetime\n",
    "\n",
    "# Import API key\n",
    "from api_keys import weather_api_key\n",
    "\n",
    "# Incorporated citipy to determine city based on latitude and longitude\n",
    "from citipy import citipy\n",
    "\n",
    "# Output File (CSV)\n",
    "output_data_file = \"output_data/cities.csv\"\n",
    "\n",
    "# Range of latitudes and longitudes\n",
    "lat_range = (-90, 90)\n",
    "lng_range = (-180, 180)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Cities List"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "644"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List for holding lat_lngs and cities\n",
    "lat_lngs = []\n",
    "cities = []\n",
    "\n",
    "# Create a set of random lat and lng combinations\n",
    "lats = np.random.uniform(lat_range[0], lat_range[1], size=1500)\n",
    "lngs = np.random.uniform(lng_range[0], lng_range[1], size=1500)\n",
    "lat_lngs = zip(lats, lngs)\n",
    "\n",
    "# Identify nearest city for each lat, lng combination\n",
    "for lat_lng in lat_lngs:\n",
    "    city = citipy.nearest_city(lat_lng[0], lat_lng[1]).city_name\n",
    "    \n",
    "    # If the city is unique, then add it to a our cities list\n",
    "    if city not in cities:\n",
    "        cities.append(city)\n",
    "\n",
    "# Print the city count to confirm sufficient count\n",
    "len(cities)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Perform API Calls\n",
    "* Perform a weather check on each city using a series of successive API calls.\n",
    "* Include a print log of each city as it'sbeing processed (with the city number and city name).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "City found: tasiilaq\n",
      "City found: blagodatnoye\n",
      "City found: rikitea\n",
      "City found: busselton\n",
      "City found: khed\n",
      "City found: vaini\n",
      "City found: faanui\n",
      "City found: north bend\n",
      "City NOT found: saleaula, 'coord'\n",
      "City found: jamestown\n",
      "City found: tiksi\n",
      "City found: mataura\n",
      "City found: albany\n",
      "City found: punta arenas\n",
      "City NOT found: taolanaro, 'coord'\n",
      "City found: ibra\n",
      "City found: port alfred\n",
      "City found: hithadhoo\n",
      "City NOT found: belushya guba, 'coord'\n",
      "City found: adrar\n",
      "City found: torbay\n",
      "City found: avarua\n",
      "City found: lagoa\n",
      "City found: hervey bay\n",
      "City found: river falls\n",
      "City found: port elizabeth\n",
      "City found: saint-philippe\n",
      "City NOT found: illoqqortoormiut, 'coord'\n",
      "City found: ushuaia\n",
      "City NOT found: mys shmidta, 'coord'\n",
      "City found: ravar\n",
      "City found: pyaozerskiy\n",
      "City found: madras\n",
      "City found: bethel\n",
      "City found: okitipupa\n",
      "City found: arlit\n",
      "City found: nalut\n",
      "City found: kabanjahe\n",
      "City found: choix\n",
      "City found: kajaani\n",
      "City NOT found: tsihombe, 'coord'\n",
      "City found: atuona\n",
      "City found: guerrero negro\n",
      "City found: umm lajj\n",
      "City found: clyde river\n",
      "City found: manta\n",
      "City found: atambua\n",
      "City found: puerto leguizamo\n",
      "City found: victoria\n",
      "City found: pangkalanbuun\n",
      "City found: klaksvik\n",
      "City found: ponta do sol\n",
      "City found: bathsheba\n",
      "City found: sao felix do xingu\n",
      "City found: khatanga\n",
      "City found: ryotsu\n",
      "City found: mahebourg\n",
      "City found: bosilegrad\n",
      "City found: mar del plata\n",
      "City found: livingstone\n",
      "City found: thetford mines\n",
      "City found: lasa\n",
      "City found: damghan\n",
      "City found: cabo san lucas\n",
      "City found: vestmanna\n",
      "City found: suntar\n",
      "City found: bahia blanca\n",
      "City found: juneau\n",
      "City found: phalaborwa\n",
      "City found: namibe\n",
      "City found: palmer\n",
      "City found: batemans bay\n",
      "City found: muros\n",
      "City found: georgetown\n",
      "City found: georgiyevka\n",
      "City found: graaff-reinet\n",
      "City found: new norfolk\n",
      "City found: bongor\n",
      "City found: kodiak\n",
      "City found: vardo\n",
      "City found: kapaa\n",
      "City found: adolfo lopez mateos\n",
      "City NOT found: lalomanu, 'coord'\n",
      "City found: tura\n",
      "City found: lebu\n",
      "City found: cidreira\n",
      "City found: deori khas\n",
      "City found: arraial do cabo\n",
      "City found: inongo\n",
      "City found: eyl\n",
      "City found: okha\n",
      "City found: yellowknife\n",
      "City found: tuktoyaktuk\n",
      "City found: kargopol\n",
      "City found: mondeville\n",
      "City found: cape town\n",
      "City found: port blair\n",
      "City found: san cristobal\n",
      "City NOT found: amderma, 'coord'\n",
      "City found: kalininskaya\n",
      "City found: barrow\n",
      "City found: constitucion\n",
      "City found: butaritari\n",
      "City found: severo-kurilsk\n",
      "City found: jumla\n",
      "City found: cobija\n",
      "City found: ust-tsilma\n",
      "City found: hobart\n",
      "City found: araouane\n",
      "City NOT found: tidore, 'coord'\n",
      "City NOT found: attawapiskat, 'coord'\n",
      "City found: foltesti\n",
      "City found: ierapetra\n",
      "City found: bredasdorp\n",
      "City found: marica\n",
      "City NOT found: rolim de moura, 'coord'\n",
      "City found: talnakh\n",
      "City NOT found: longlac, 'coord'\n",
      "City found: castro\n",
      "City found: carutapera\n",
      "City NOT found: tubruq, 'coord'\n",
      "City found: sitka\n",
      "City found: carballo\n",
      "City found: port hardy\n",
      "City found: atar\n",
      "City found: maltahohe\n",
      "City found: codrington\n",
      "City found: ribeira grande\n",
      "City found: glenluce\n",
      "City found: berlevag\n",
      "City found: hermanus\n",
      "City found: bullhead city\n",
      "City found: never\n",
      "City NOT found: rungata, 'coord'\n",
      "City NOT found: barentsburg, 'coord'\n",
      "City found: hilo\n",
      "City found: campbell river\n",
      "City found: matara\n",
      "City found: carnarvon\n",
      "City found: taguatinga\n",
      "City NOT found: ye, 'coord'\n",
      "City found: hobbs\n",
      "City found: san mateo del mar\n",
      "City found: bambous virieux\n",
      "City found: faya\n",
      "City found: porto velho\n",
      "City found: east london\n",
      "City found: qaanaaq\n",
      "City found: wasilla\n",
      "City found: qaqortoq\n",
      "City found: kisangani\n",
      "City found: nancha\n",
      "City found: puerto ayora\n",
      "City found: touros\n",
      "City found: villa del rosario\n",
      "City found: beringovskiy\n",
      "City found: neiafu\n",
      "City found: epe\n",
      "City NOT found: podbelsk, 'coord'\n",
      "City found: tuatapere\n",
      "City found: ahipara\n",
      "City found: airai\n",
      "City found: shenjiamen\n",
      "City found: jabinyanah\n",
      "City found: ushtobe\n",
      "City found: sao filipe\n",
      "City found: sola\n",
      "City found: komsomolskiy\n",
      "City found: vostok\n",
      "City found: taksimo\n",
      "City found: yeppoon\n",
      "City found: bengkulu\n",
      "City found: baoding\n",
      "City found: pevek\n",
      "City found: yerofey pavlovich\n",
      "City found: bluff\n",
      "City NOT found: scottsburgh, 'coord'\n",
      "City found: north battleford\n",
      "City found: olen\n",
      "City found: vermilion\n",
      "City found: biak\n",
      "City found: esperance\n",
      "City found: slochteren\n",
      "City found: acapulco\n",
      "City found: bad laasphe\n",
      "City found: piranshahr\n",
      "City found: gerash\n",
      "City found: kavieng\n",
      "City found: kamaishi\n",
      "City found: dunedin\n",
      "City found: jiayuguan\n",
      "City found: tyrma\n",
      "City NOT found: vaitupu, 'coord'\n",
      "City NOT found: ambodifototra, 'coord'\n",
      "City found: waterloo\n",
      "City found: dayong\n",
      "City found: koroni\n",
      "City found: ilhabela\n",
      "City found: raudeberg\n",
      "City found: karangasem\n",
      "City NOT found: samusu, 'coord'\n",
      "City found: slave lake\n",
      "City found: deputatskiy\n",
      "City found: hargeysa\n",
      "City found: turayf\n",
      "City found: tommot\n",
      "City found: bonavista\n",
      "City found: fort wayne\n",
      "City found: monywa\n",
      "City found: tianpeng\n",
      "City found: piacabucu\n",
      "City found: sao joao da barra\n",
      "City found: maniitsoq\n",
      "City found: nikolskoye\n",
      "City found: santiago\n",
      "City found: tocopilla\n",
      "City found: alice springs\n",
      "City found: ballina\n",
      "City found: nanortalik\n",
      "City found: baraut\n",
      "City found: canton\n",
      "City found: hohhot\n",
      "City found: abha\n",
      "City found: pulandian\n",
      "City found: gorontalo\n",
      "City found: shache\n",
      "City NOT found: qabis, 'coord'\n",
      "City found: minab\n",
      "City found: chunhuhub\n",
      "City found: columbus\n",
      "City found: saint-leu\n",
      "City found: katsuura\n",
      "City found: arbazh\n",
      "City found: caicedo\n",
      "City found: luwuk\n",
      "City found: aksu\n",
      "City found: tooele\n",
      "City found: wajir\n",
      "City found: dikson\n",
      "City found: santa cruz\n",
      "City found: chilca\n",
      "City found: kyshtovka\n",
      "City found: kahului\n",
      "City found: carlos barbosa\n",
      "City found: elmina\n",
      "City found: burnie\n",
      "City found: ayan\n",
      "City found: lompoc\n",
      "City found: cabedelo\n",
      "City found: whitianga\n",
      "City found: souillac\n",
      "City found: kirakira\n",
      "City found: asau\n",
      "City NOT found: dzhusaly, 'coord'\n",
      "City found: makinsk\n",
      "City found: ostrovnoy\n",
      "City found: sosua\n",
      "City found: aranos\n",
      "City NOT found: grand centre, 'coord'\n",
      "City found: muisne\n",
      "City found: ancud\n",
      "City found: watsa\n",
      "City found: ridgeland\n",
      "City found: tarakan\n",
      "City found: grindavik\n",
      "City found: marzuq\n",
      "City NOT found: marcona, 'coord'\n",
      "City found: frolovo\n",
      "City found: stony plain\n",
      "City found: maceio\n",
      "City found: takaungu\n",
      "City found: longyearbyen\n",
      "City found: bacolod\n",
      "City found: jardim\n",
      "City NOT found: crab hill, 'coord'\n",
      "City found: saint george\n",
      "City found: pochutla\n",
      "City found: saldanha\n",
      "City found: laguna\n",
      "City found: campeche\n",
      "City found: bungoma\n",
      "City found: toora-khem\n",
      "City found: abnub\n",
      "City found: tual\n",
      "City found: provideniya\n",
      "City found: chokurdakh\n",
      "City found: broken hill\n",
      "City found: tezu\n",
      "City found: walvis bay\n",
      "City found: beloha\n",
      "City found: perth\n",
      "City found: bagotville\n",
      "City found: bhuj\n",
      "City found: san martin\n",
      "City found: imeni poliny osipenko\n",
      "City found: vila franca do campo\n",
      "City found: fort nelson\n",
      "City found: jalu\n",
      "City found: tanout\n",
      "City found: ugoofaaru\n",
      "City found: xacmaz\n",
      "City found: hasaki\n",
      "City found: micheweni\n",
      "City found: bull savanna\n",
      "City found: vila velha\n",
      "City found: sabha\n",
      "City found: emerald\n",
      "City found: mount gambier\n",
      "City found: kendari\n",
      "City found: birin\n",
      "City found: coihaique\n",
      "City found: ilulissat\n",
      "City found: togur\n",
      "City found: richards bay\n",
      "City found: bom jesus\n",
      "City found: isangel\n",
      "City found: massakory\n",
      "City found: frontera\n",
      "City found: salalah\n",
      "City found: san policarpo\n",
      "City found: liwale\n",
      "City found: aykhal\n",
      "City found: evensk\n",
      "City found: thompson\n",
      "City found: yulara\n",
      "City NOT found: sahrak, 'coord'\n",
      "City found: arrifes\n",
      "City found: broome\n",
      "City found: tahe\n",
      "City found: mufumbwe\n",
      "City found: kangavar\n",
      "City NOT found: samalaeulu, 'coord'\n",
      "City found: pafos\n",
      "City found: hofn\n",
      "City found: pangnirtung\n",
      "City found: horsham\n",
      "City found: asekeyevo\n",
      "City found: prince rupert\n",
      "City found: pisco\n",
      "City found: xixiang\n",
      "City found: mwense\n",
      "City found: tucurui\n",
      "City found: petawawa\n",
      "City found: dera bugti\n",
      "City found: port hedland\n",
      "City found: bilibino\n",
      "City found: agirish\n",
      "City found: dunda\n",
      "City found: narsaq\n",
      "City found: vao\n",
      "City found: esso\n",
      "City found: gallup\n",
      "City found: wurzburg\n",
      "City found: saskylakh\n",
      "City found: elat\n",
      "City found: iseyin\n",
      "City found: batagay-alyta\n",
      "City found: axim\n",
      "City found: pyapon\n",
      "City found: porto santo\n",
      "City NOT found: ngukurr, 'coord'\n",
      "City found: tabou\n",
      "City found: nagykanizsa\n",
      "City NOT found: umzimvubu, 'coord'\n",
      "City found: pitimbu\n",
      "City found: cajamar\n",
      "City found: shubarshi\n",
      "City found: necochea\n",
      "City found: rio brilhante\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "City found: upernavik\n",
      "City found: rocha\n",
      "City found: khorixas\n",
      "City found: norman wells\n",
      "City found: sistranda\n",
      "City found: geraldton\n",
      "City found: vilhena\n",
      "City found: baillif\n",
      "City found: olafsvik\n",
      "City found: luderitz\n",
      "City found: tiarei\n",
      "City found: luena\n",
      "City found: le mars\n",
      "City found: wladyslawowo\n",
      "City found: loandjili\n",
      "City found: portland\n",
      "City found: athens\n",
      "City found: coquimbo\n",
      "City NOT found: tabulbah, 'coord'\n",
      "City found: gao\n",
      "City found: sokolac\n",
      "City found: wajid\n",
      "City found: aksarka\n",
      "City found: gwadar\n",
      "City found: mandurah\n",
      "City found: shingu\n",
      "City found: jhudo\n",
      "City found: zhangye\n",
      "City found: passos\n",
      "City found: suba\n",
      "City found: shimoda\n",
      "City found: umarizal\n",
      "City found: cockburn town\n",
      "City found: zhezkazgan\n",
      "City found: finschhafen\n",
      "City found: tungor\n",
      "City found: dubbo\n",
      "City found: acarau\n",
      "City found: cap-aux-meules\n",
      "City found: miri\n",
      "City found: hami\n",
      "City found: rio negrinho\n",
      "City found: takoradi\n",
      "City found: shamkhal\n",
      "City found: oyama\n",
      "City NOT found: sentyabrskiy, 'coord'\n",
      "City found: havelock\n",
      "City found: crossville\n",
      "City found: kouango\n",
      "City found: chuy\n",
      "City found: fort collins\n",
      "City found: albacete\n",
      "City found: cherskiy\n",
      "City found: zaraza\n",
      "City NOT found: lolua, 'coord'\n",
      "City found: qostanay\n",
      "City found: alamosa\n",
      "City found: taitung\n",
      "City found: talaya\n",
      "City NOT found: tarudant, 'coord'\n",
      "City found: demirci\n",
      "City found: leningradskiy\n",
      "City found: bilma\n",
      "City found: vanderhoof\n",
      "City found: labuhan\n",
      "City found: ust-nera\n",
      "City found: japura\n",
      "City found: noshiro\n",
      "City found: riyadh\n",
      "City found: cooma\n",
      "City found: barsovo\n",
      "City found: brokopondo\n",
      "City found: ambon\n",
      "City found: ngorongoro\n",
      "City found: arman\n",
      "City found: amahai\n",
      "City found: mocuba\n",
      "City found: kedougou\n",
      "City NOT found: santa eulalia del rio, 'coord'\n",
      "City found: srednekolymsk\n",
      "City found: bara\n",
      "City found: netanya\n",
      "City found: cap malheureux\n",
      "City found: nueva helvecia\n",
      "City found: henties bay\n",
      "City NOT found: mergui, 'coord'\n",
      "City found: eston\n",
      "City found: ternate\n",
      "City NOT found: armacao dos buzios, 'coord'\n",
      "City found: santa maria\n",
      "City found: christchurch\n",
      "City found: sur\n",
      "City NOT found: naftah, 'coord'\n",
      "City found: porto walter\n",
      "City found: jeremie\n",
      "City found: zasheyek\n",
      "City found: mekhe\n",
      "City found: skelleftea\n",
      "City found: springfield\n",
      "City found: ashland\n",
      "City found: nome\n",
      "City found: manaure\n",
      "City found: makakilo city\n",
      "City found: kaeo\n",
      "City found: sitia\n",
      "City NOT found: tabiauea, 'coord'\n",
      "City found: zlynka\n",
      "City found: boguchany\n",
      "City found: bathurst\n",
      "City NOT found: nizhneyansk, 'coord'\n",
      "City found: ilebo\n",
      "City found: ferrol\n",
      "City found: helong\n",
      "City found: doha\n",
      "City found: fortuna\n",
      "City found: taoudenni\n",
      "City found: garden city\n",
      "City found: maua\n",
      "City NOT found: saint combs, 'coord'\n",
      "City found: iqaluit\n",
      "City found: athabasca\n",
      "City found: phangnga\n",
      "City found: port pirie\n",
      "City found: kandalaksha\n",
      "City found: teluk nibung\n",
      "City found: college\n",
      "City found: egvekinot\n",
      "City found: yoichi\n",
      "City found: alofi\n",
      "City NOT found: ketchenery, 'coord'\n",
      "City found: kaitangata\n",
      "City found: huarmey\n",
      "City found: singkang\n",
      "City found: rawson\n",
      "City found: birjand\n",
      "City found: jaru\n",
      "City found: nortelandia\n",
      "City found: sisimiut\n",
      "City found: skibbereen\n",
      "City found: porto novo\n",
      "City found: kutoarjo\n",
      "City found: sudak\n",
      "City NOT found: yialos, 'coord'\n",
      "City found: dali\n",
      "City found: ligayan\n",
      "City NOT found: grand river south east, 'coord'\n",
      "City NOT found: al, 'coord'\n",
      "City found: ambilobe\n",
      "City found: andenes\n",
      "City found: salaga\n",
      "City found: krasnyy yar\n",
      "City found: yatou\n",
      "City found: sarangani\n",
      "City found: buturugeni\n",
      "City found: ishigaki\n",
      "City found: basco\n",
      "City found: guthrie\n",
      "City NOT found: vestbygda, 'coord'\n",
      "City found: kodinar\n",
      "City found: lorengau\n",
      "City found: los llanos de aridane\n",
      "City found: san joaquin\n",
      "City found: praya\n",
      "City found: pangody\n",
      "City found: dawlatabad\n",
      "City NOT found: palabuhanratu, 'coord'\n",
      "City found: noumea\n",
      "City found: xinyu\n",
      "City found: itaituba\n",
      "City found: gat\n",
      "City found: smithers\n",
      "City found: mbanza-ngungu\n",
      "City found: gubkinskiy\n",
      "City found: walcz\n",
      "City found: saint anthony\n",
      "City found: eunice\n",
      "City found: erbaa\n",
      "City found: key west\n",
      "City found: dingle\n",
      "City NOT found: warqla, 'coord'\n",
      "City found: narino\n",
      "City found: kembe\n",
      "City found: las vegas\n",
      "City found: aktash\n",
      "City found: te anau\n",
      "City found: ukiah\n",
      "City found: gamba\n",
      "City found: dinar\n",
      "City NOT found: bac can, 'coord'\n",
      "City found: jinxi\n",
      "City found: kieta\n",
      "City found: padang\n",
      "City found: port lincoln\n",
      "City found: honiara\n",
      "City found: maragogi\n",
      "City found: arica\n",
      "City found: bukachacha\n",
      "City found: vossevangen\n",
      "City found: bonthe\n",
      "City found: lusambo\n",
      "City found: lavrentiya\n",
      "City found: tufanganj\n",
      "City found: nipawin\n",
      "City found: ramona\n",
      "City found: kudahuvadhoo\n",
      "City found: surin\n",
      "City found: lamar\n",
      "City NOT found: paradwip, 'coord'\n",
      "City found: gizo\n",
      "City found: russell\n",
      "City found: azanka\n",
      "City found: launceston\n",
      "City found: puri\n",
      "City found: tautira\n",
      "City found: emba\n",
      "City found: zhuhai\n",
      "City found: cruzeiro\n",
      "City found: hobyo\n",
      "City found: bitam\n",
      "City found: dalby\n",
      "City found: murchison\n",
      "City NOT found: mahadday weyne, 'coord'\n",
      "City found: ahtopol\n",
      "City found: moussoro\n",
      "City found: valparaiso\n",
      "City found: usinsk\n",
      "City found: nizwa\n",
      "City found: thunder bay\n",
      "City found: smoky lake\n",
      "City found: klyuchi\n",
      "City found: sinnamary\n",
      "City NOT found: wulanhaote, 'coord'\n",
      "City found: san luis\n",
      "City found: norashen\n",
      "City found: winslow\n",
      "City found: lata\n",
      "City found: teguldet\n",
      "City NOT found: shchuchye, 'coord'\n",
      "City found: aklavik\n",
      "City found: koszalin\n",
      "City found: gilgit\n",
      "City found: coro\n",
      "City found: bintulu\n",
      "City found: cape coast\n",
      "City found: qasigiannguit\n",
      "City found: yuzhno-kurilsk\n",
      "City found: nioro\n",
      "City NOT found: tumannyy, 'coord'\n",
      "City found: staraya mayna\n",
      "City found: wanaka\n",
      "City found: sayansk\n",
      "City found: mwinilunga\n",
      "City found: inuvik\n",
      "City found: karratha\n",
      "City found: jinchang\n",
      "City NOT found: tiruvottiyur, 'coord'\n",
      "City NOT found: kegayli, 'coord'\n",
      "City found: armeria\n",
      "City found: ailigandi\n",
      "City found: praia da vitoria\n",
      "City found: anchorage\n",
      "City found: khrebtovaya\n",
      "City found: livezi\n",
      "City found: husavik\n",
      "City found: matay\n",
      "City found: antalaha\n",
      "City found: bira\n",
      "City found: yinchuan\n",
      "City found: solnechnyy\n",
      "City NOT found: sumbawa, 'coord'\n",
      "City found: kavaratti\n",
      "City found: teya\n",
      "City found: ngong\n",
      "City found: hamilton\n",
      "City found: oranjemund\n"
     ]
    }
   ],
   "source": [
    "# Creating querly url with unit as imperial\n",
    "url = \"http://api.openweathermap.org/data/2.5/weather?id=524901\"\n",
    "unit = \"imperial\"\n",
    "query_url_api = f\"{url}&appid={weather_api_key}&units={unit}&q=\"\n",
    "\n",
    "# List for results\n",
    "lon = []\n",
    "lat = []\n",
    "cities_found = []\n",
    "cloudiness = []\n",
    "temp = []\n",
    "humidity = []\n",
    "wind_speed = []\n",
    "date = []\n",
    "country = []\n",
    "\n",
    "\n",
    "for city in cities:\n",
    "    \n",
    "    query_url = query_url_api + city\n",
    "    response = requests.get(query_url)\n",
    "    response_json = response.json()\n",
    "    try:\n",
    "        #response = requests.get(query_url + city).json()\n",
    "        lat.append( response_json[\"coord\"][\"lat\"])\n",
    "        lon.append( response_json[\"coord\"][\"lon\"])\n",
    "        temp.append( response_json[\"main\"][\"temp_max\"])\n",
    "        humidity.append( response_json[\"main\"][\"humidity\"])\n",
    "        cloudiness.append( response_json[\"clouds\"][\"all\"])\n",
    "        wind_speed.append( response_json[\"wind\"][\"speed\"])\n",
    "        country.append(response_json[\"sys\"][\"country\"])\n",
    "        date.append( response_json[\"dt\"])\n",
    "        cities_found.append(city)\n",
    "        print(f\"City found: {city}\")\n",
    "    except Exception as err:\n",
    "        print(f\"City NOT found: {city}, {err}\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert Raw Data to DataFrame\n",
    "* Export the city data into a .csv.\n",
    "* Display the DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "city_data = pd.DataFrame({\"City\": cities_found,\n",
    "                         \"Max Temp\":temp,\n",
    "                         \"Cloudiness\":cloudiness,\n",
    "                         \"Humidity\":humidity,\n",
    "                         \"Wind Speed\":wind_speed,\n",
    "                         \"Lat\":lat,\n",
    "                         \"Lng\":lon,\n",
    "                         \"Country\":country,\n",
    "                         \"Date\":date,\n",
    "                          \n",
    "                         })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tasiilaq</td>\n",
       "      <td>39.20</td>\n",
       "      <td>99</td>\n",
       "      <td>93</td>\n",
       "      <td>9.17</td>\n",
       "      <td>65.61</td>\n",
       "      <td>-37.64</td>\n",
       "      <td>GL</td>\n",
       "      <td>1593123181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>blagodatnoye</td>\n",
       "      <td>66.20</td>\n",
       "      <td>35</td>\n",
       "      <td>52</td>\n",
       "      <td>6.71</td>\n",
       "      <td>45.40</td>\n",
       "      <td>42.59</td>\n",
       "      <td>RU</td>\n",
       "      <td>1593123181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rikitea</td>\n",
       "      <td>74.44</td>\n",
       "      <td>61</td>\n",
       "      <td>83</td>\n",
       "      <td>22.32</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td>PF</td>\n",
       "      <td>1593123182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>busselton</td>\n",
       "      <td>51.01</td>\n",
       "      <td>62</td>\n",
       "      <td>76</td>\n",
       "      <td>12.15</td>\n",
       "      <td>-33.65</td>\n",
       "      <td>115.33</td>\n",
       "      <td>AU</td>\n",
       "      <td>1593123146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>khed</td>\n",
       "      <td>79.90</td>\n",
       "      <td>83</td>\n",
       "      <td>87</td>\n",
       "      <td>2.01</td>\n",
       "      <td>17.72</td>\n",
       "      <td>73.38</td>\n",
       "      <td>IN</td>\n",
       "      <td>1593123182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>kavaratti</td>\n",
       "      <td>81.09</td>\n",
       "      <td>100</td>\n",
       "      <td>79</td>\n",
       "      <td>25.55</td>\n",
       "      <td>10.57</td>\n",
       "      <td>72.64</td>\n",
       "      <td>IN</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>teya</td>\n",
       "      <td>57.24</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>2.64</td>\n",
       "      <td>60.38</td>\n",
       "      <td>92.63</td>\n",
       "      <td>RU</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>ngong</td>\n",
       "      <td>55.40</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "      <td>6.93</td>\n",
       "      <td>-1.36</td>\n",
       "      <td>36.66</td>\n",
       "      <td>KE</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>hamilton</td>\n",
       "      <td>84.99</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>9.17</td>\n",
       "      <td>39.18</td>\n",
       "      <td>-84.53</td>\n",
       "      <td>US</td>\n",
       "      <td>1593123168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>oranjemund</td>\n",
       "      <td>58.80</td>\n",
       "      <td>42</td>\n",
       "      <td>79</td>\n",
       "      <td>8.84</td>\n",
       "      <td>-28.55</td>\n",
       "      <td>16.43</td>\n",
       "      <td>NA</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>587 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             City  Max Temp  Cloudiness  Humidity  Wind Speed    Lat     Lng  \\\n",
       "0        tasiilaq     39.20          99        93        9.17  65.61  -37.64   \n",
       "1    blagodatnoye     66.20          35        52        6.71  45.40   42.59   \n",
       "2         rikitea     74.44          61        83       22.32 -23.12 -134.97   \n",
       "3       busselton     51.01          62        76       12.15 -33.65  115.33   \n",
       "4            khed     79.90          83        87        2.01  17.72   73.38   \n",
       "..            ...       ...         ...       ...         ...    ...     ...   \n",
       "582     kavaratti     81.09         100        79       25.55  10.57   72.64   \n",
       "583          teya     57.24           0        83        2.64  60.38   92.63   \n",
       "584         ngong     55.40          25        93        6.93  -1.36   36.66   \n",
       "585      hamilton     84.99          40        37        9.17  39.18  -84.53   \n",
       "586    oranjemund     58.80          42        79        8.84 -28.55   16.43   \n",
       "\n",
       "    Country        Date  \n",
       "0        GL  1593123181  \n",
       "1        RU  1593123181  \n",
       "2        PF  1593123182  \n",
       "3        AU  1593123146  \n",
       "4        IN  1593123182  \n",
       "..      ...         ...  \n",
       "582      IN  1593123266  \n",
       "583      RU  1593123266  \n",
       "584      KE  1593123266  \n",
       "585      US  1593123168  \n",
       "586      NA  1593123266  \n",
       "\n",
       "[587 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tasiilaq</td>\n",
       "      <td>39.20</td>\n",
       "      <td>99</td>\n",
       "      <td>93</td>\n",
       "      <td>9.17</td>\n",
       "      <td>65.61</td>\n",
       "      <td>-37.64</td>\n",
       "      <td>GL</td>\n",
       "      <td>1593123181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>blagodatnoye</td>\n",
       "      <td>66.20</td>\n",
       "      <td>35</td>\n",
       "      <td>52</td>\n",
       "      <td>6.71</td>\n",
       "      <td>45.40</td>\n",
       "      <td>42.59</td>\n",
       "      <td>RU</td>\n",
       "      <td>1593123181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rikitea</td>\n",
       "      <td>74.44</td>\n",
       "      <td>61</td>\n",
       "      <td>83</td>\n",
       "      <td>22.32</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td>PF</td>\n",
       "      <td>1593123182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>busselton</td>\n",
       "      <td>51.01</td>\n",
       "      <td>62</td>\n",
       "      <td>76</td>\n",
       "      <td>12.15</td>\n",
       "      <td>-33.65</td>\n",
       "      <td>115.33</td>\n",
       "      <td>AU</td>\n",
       "      <td>1593123146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>khed</td>\n",
       "      <td>79.90</td>\n",
       "      <td>83</td>\n",
       "      <td>87</td>\n",
       "      <td>2.01</td>\n",
       "      <td>17.72</td>\n",
       "      <td>73.38</td>\n",
       "      <td>IN</td>\n",
       "      <td>1593123182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>kavaratti</td>\n",
       "      <td>81.09</td>\n",
       "      <td>100</td>\n",
       "      <td>79</td>\n",
       "      <td>25.55</td>\n",
       "      <td>10.57</td>\n",
       "      <td>72.64</td>\n",
       "      <td>IN</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>teya</td>\n",
       "      <td>57.24</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>2.64</td>\n",
       "      <td>60.38</td>\n",
       "      <td>92.63</td>\n",
       "      <td>RU</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>ngong</td>\n",
       "      <td>55.40</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "      <td>6.93</td>\n",
       "      <td>-1.36</td>\n",
       "      <td>36.66</td>\n",
       "      <td>KE</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>hamilton</td>\n",
       "      <td>84.99</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>9.17</td>\n",
       "      <td>39.18</td>\n",
       "      <td>-84.53</td>\n",
       "      <td>US</td>\n",
       "      <td>1593123168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>oranjemund</td>\n",
       "      <td>58.80</td>\n",
       "      <td>42</td>\n",
       "      <td>79</td>\n",
       "      <td>8.84</td>\n",
       "      <td>-28.55</td>\n",
       "      <td>16.43</td>\n",
       "      <td>NA</td>\n",
       "      <td>1593123266</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>587 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             City  Max Temp  Cloudiness  Humidity  Wind Speed    Lat     Lng  \\\n",
       "0        tasiilaq     39.20          99        93        9.17  65.61  -37.64   \n",
       "1    blagodatnoye     66.20          35        52        6.71  45.40   42.59   \n",
       "2         rikitea     74.44          61        83       22.32 -23.12 -134.97   \n",
       "3       busselton     51.01          62        76       12.15 -33.65  115.33   \n",
       "4            khed     79.90          83        87        2.01  17.72   73.38   \n",
       "..            ...       ...         ...       ...         ...    ...     ...   \n",
       "582     kavaratti     81.09         100        79       25.55  10.57   72.64   \n",
       "583          teya     57.24           0        83        2.64  60.38   92.63   \n",
       "584         ngong     55.40          25        93        6.93  -1.36   36.66   \n",
       "585      hamilton     84.99          40        37        9.17  39.18  -84.53   \n",
       "586    oranjemund     58.80          42        79        8.84 -28.55   16.43   \n",
       "\n",
       "    Country        Date  \n",
       "0        GL  1593123181  \n",
       "1        RU  1593123181  \n",
       "2        PF  1593123182  \n",
       "3        AU  1593123146  \n",
       "4        IN  1593123182  \n",
       "..      ...         ...  \n",
       "582      IN  1593123266  \n",
       "583      RU  1593123266  \n",
       "584      KE  1593123266  \n",
       "585      US  1593123168  \n",
       "586      NA  1593123266  \n",
       "\n",
       "[587 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data.to_csv('../output_data/cities_original.csv', index=False)\n",
    "city_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspect the data and remove the cities where the humidity > 100%.\n",
    "----\n",
    "Skip this step if there are no cities that have humidity > 100%. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [City, Max Temp, Cloudiness, Humidity, Wind Speed, Lat, Lng, Country, Date]\n",
       "Index: []"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "remove_humidity_df = city_data[(city_data['Humidity']>100)]\n",
    "remove_humidity_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a new DataFrame equal to the city data to drop all humidity outliers by index.\n",
    "# Passing \"inplace=False\" will make a copy of the city_data DataFrame, which we call \"clean_city_data\".\n",
    "\n",
    "clean_city_data = city_data.loc[list(set(city_data.index) - set(remove_humidity_df.index))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Date</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Country</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Max Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tasiilaq</td>\n",
       "      <td>93</td>\n",
       "      <td>65.61</td>\n",
       "      <td>-37.64</td>\n",
       "      <td>1593123181</td>\n",
       "      <td>99</td>\n",
       "      <td>GL</td>\n",
       "      <td>9.17</td>\n",
       "      <td>39.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>blagodatnoye</td>\n",
       "      <td>52</td>\n",
       "      <td>45.40</td>\n",
       "      <td>42.59</td>\n",
       "      <td>1593123181</td>\n",
       "      <td>35</td>\n",
       "      <td>RU</td>\n",
       "      <td>6.71</td>\n",
       "      <td>66.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rikitea</td>\n",
       "      <td>83</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td>1593123182</td>\n",
       "      <td>61</td>\n",
       "      <td>PF</td>\n",
       "      <td>22.32</td>\n",
       "      <td>74.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>busselton</td>\n",
       "      <td>76</td>\n",
       "      <td>-33.65</td>\n",
       "      <td>115.33</td>\n",
       "      <td>1593123146</td>\n",
       "      <td>62</td>\n",
       "      <td>AU</td>\n",
       "      <td>12.15</td>\n",
       "      <td>51.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>khed</td>\n",
       "      <td>87</td>\n",
       "      <td>17.72</td>\n",
       "      <td>73.38</td>\n",
       "      <td>1593123182</td>\n",
       "      <td>83</td>\n",
       "      <td>IN</td>\n",
       "      <td>2.01</td>\n",
       "      <td>79.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           City  Humidity    Lat     Lng        Date  Cloudiness Country  \\\n",
       "0      tasiilaq        93  65.61  -37.64  1593123181          99      GL   \n",
       "1  blagodatnoye        52  45.40   42.59  1593123181          35      RU   \n",
       "2       rikitea        83 -23.12 -134.97  1593123182          61      PF   \n",
       "3     busselton        76 -33.65  115.33  1593123146          62      AU   \n",
       "4          khed        87  17.72   73.38  1593123182          83      IN   \n",
       "\n",
       "   Wind Speed  Max Temp  \n",
       "0        9.17     39.20  \n",
       "1        6.71     66.20  \n",
       "2       22.32     74.44  \n",
       "3       12.15     51.01  \n",
       "4        2.01     79.90  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract relevant fields from the data frame\n",
    "\n",
    "relevant_fields = city_data[[\"City\",\"Humidity\",\"Lat\",\"Lng\",\"Date\",\"Cloudiness\",\"Country\",\"Wind Speed\", \"Max Temp\"]]\n",
    "\n",
    "\n",
    "# Export the City_Data into a csv\n",
    "relevant_fields.to_csv(\"../output_data/cities.csv\", index=False)\n",
    "\n",
    "relevant_fields.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the Data\n",
    "* Use proper labeling of the plots using plot titles (including date of analysis) and axes labels.\n",
    "* Save the plotted figures as .pngs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latitude vs. Temperature Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2lw6M67xtw3wCnq8grJlPs34KW3MgLcQ3NVEFoShdIMpU4720//L8V/LRWzYz4XM0iLvcT1jeQVABhdHMqH/5WQsa9hucsShTB1UQitIFkphqwmYHR88ZTzTqD1NAQeJG/VHRShrFdHCgCkJRukBSU01wdrBu3bpE+4+bHcSN+uN6SKhCODhQJ7WidIEkzuVWiJodDA6U63wdYWi0kgI6g1CUjuI32wz0lzhkWoFd1VrmphqbryBOMXhotJICqiAUpSMMj1S49o6tjPrqKe0cq1EuFbnxolMyN9m06ivQaCUFVEEoStuJiiiKCjcNLZud4rit+Ao0WkkBVRCK0hTBGcHs/hLXnHNS6As5LqIozGwT5iS+fM1mlr9ynNGRSuSLPyr6yL9uVrmECIyONZq4NFpJAVUQipKa4ZEKy2/dQs2XoLBzrMby27YAjVVU4+z2YWYbm1KZMIblt4Yfx5PNFn0E1K3zm7vCqsBqtJKiUUyKkpJVa7fVKQeP2rgJjfKJstvbzDZRSqU2EX4cTzZb9FHcTEajlJQgqiAUJSVRL++wdbZCfLP7S9aoojhncNoooydHq4kikDRKSfGjJiZFSYktwsdbF6QZe/7ysxZwxZrN1nLeNgUSF31kkztuv0HS+GCU3kUVhJJ78tagZvlZCxp8EAClolijfKLs+bbz2/joDr5x32Ohn6mMVjl95T2Tx/M7nktFoTZ+QDbPjLXx0R3cdN9jVqWTNEoprQ9G6V1UQSi5Jq7kQzfwjpvFCDrq/K4fWsiS4+Zw3Z1b2TnW2I+6Mlp1XsqGyZf1aLVGqSDM7i/VRScB3L6p0qAcZvQVGds3nkrxRvlgLl+zmVVrt3VdiSvZoApCyTVJqp52g6wifOLOz3+c01feA7xQt61/pjC5bMLQ3zeNkavfNLns9JX3hDqoB/r72PrpM1PJHOenyIMSV7JBFYSSa3q95EOceSzN+T05WoVjkh03+PlWr6P/PAoijBubocohD0pcaR1VEEqu6eWSD3HmseGRivVlG3Z+zrIXGpaHURBh/oq7JpVSK9cxeB5xysHDr3xGqzVOX3lPnaIETcTLOxrmquSadlc9bSdR5iPvpRv2srWd3/KzFlAQSXTscWPq2osuO+GIpq+jLX8iThRP+QyPVKjsrNa1PF1+2xaW37olkzaoSvtQBaHkmqFFg9xw/sK6Xs1JK5J2myizju2lWxSxnt/QokEGZ5cpRryZw9ZVa+Pc++BzTV9HqxnKwCMrz+YLF50SqXxWrd3GREAR1sZNg6NbE/Xyh5qYlNzTqyUfosw6tpfuhDGR5zpQLjFh9oWuE/fzYTw5Wm36OsaZp+LyPFrxnSjdRRWE0hPkLRciCVEVUVet3Rb60jUwmd/gPz/v/C8+5gUKUgo1TRmgv1RgrDbRsG6gv1T3f5rrmaSya5TySeM7AZi34i5Ak+/ygJqYlNzj2et7zV4dZR6zld+AxvPznz9EO4nHahOEGaB2VWuh+0tyPVs186XxnfjPzEu+y/v3PJXRGYSSe/KaC5EE28jab5YJm0n4zy+uyF6QMPUxYeC6O7da9xd3PdOap4IzlD89ocTs/mJowl8UXgHEvH/PUxWdQSi5p9dzIWwMLRpk/YozQ0f8cOD8sjrPnWNOqKmtHlNWxwmboewYq7F77/6m9tfr33MvozMIJffYnKTBWP/gKDNYUG5GX5FS0dcD+uTko3Jvf834QbzP+c+hKMIlrzmG64cWxjqBo4oDpiVyP+LIGtZcKG0pjuAMxZjGqCU/xYjkO3+4bK/5oXodVRBK7glzksIBW3xYaYewgnJ79o0DB5LWntg5XvdCjKLZmlC2dqPjxkwW4rM5gZedcETkiD9rjGGy4B4Q2XiomexwG+VSkQsWD7Lmx49bCyDmsSbXwYAqCCX3BMMow7KPq7Vxrrtza6pyEMaYSbu8h22UGme3T/M5PzdveJzrhxbWnd9RA2WWnXAEt2+qpPI9ZIG/6VHY+V5351b21iYiX9RpZjz+vI8lx82xFkAMqyXVK36oXkYVhJI7wl62fmwv/p1jtUknaNJyEH6n6VXD99eVw/Zefhsf3RFpt48a3caNpj05g05gW3G9Zhkol+pajEYRJXOYk7laG+djtxwo9W2b8QUpl4p10VBRjvCp6ofKO6oglEwZHqnUlaceKJe49tzksexhL9vlt24BCa9cmqXcYb0SqrVxa08GcEbLttnFdXduRcQx3UThz3sI81e0SlGEt518ZOIZSdLmQn7GjWmYSdjKlHtMGKc8+OVrNsfeJ71ck6uX0SgmJTOGRyosv21L3UthtFpj+a3JY9nDXra1CdM25TBQLk0eN+0RvGQx2yh251iNCL/sJN6M46rh++vyHbJi3Bhu31ThgsWDk7kMs/tLoQ+/Z/MPy9MQoFyyvzL8pTKGFg3S3xc9/nxx/4GEPv99MjxS4fSV9zB/xV2cvvIe577q4ZpcvYwqCCUzVq3dZu1PkLTGTlqTgZe45b3oG9ZH5GcJwrXnntTUcQFOPXZWU4oljGptnJs3PN42n4NXj2n9ijN5eOXZjFz9Jv76olPqrptIvQ/igsWDdSG4Btg/YSgV7BfVfx3TXtPahOMTCkviA3q2JlcvoyYmJTOiXghJXhZR5a/DGBwos37FmZOfDYsE8r9Egr6No+eMN+VY9fjvX+7IRDl4JD3vZgmen2fzt/lQppcKDedXGzfM7i/xfHV/bJnyZq6pzcexau021q84c0oqhDyH76qCUDIj6oXgf3HYnNC28telgjT4IEpFYc+L+5m34q7JGPqBconppUJdq03/gxZ0gq5bt27y76SOVT/tfZ1nj0BDT4aoCC3btRgdq3HjRafE1mdaftYCrlizOZPrNFWd0XkP31UFoWTG8rMWsPy2LQ1mplJBJl8ctkihQ6YVrOWvV739ZOBAGOhAf4nde/dPRuV4SmW0WqNcKnLjRaekfriCobTeMaKSu5ohidO6XXgmG6h/EaUd5R81UI6t4ArONd346I5IJ38QW7TVVHVG572MTDoFITIAHA1UMGZnFgKIyBXAH+Lcv/cD7wGOBFYDc4CfAP+PMZYax0puCIte8UenREUK2Uar/vLX/t7MtuiYNA9XWJczz2QFzujuY7dsycz08wWf4lr06e+nrkvk9XoYdPMk7vrpU6n34ce7VlFZzEH8s4Qk9ZmuH1rIXT99Cogvs3Hpacey5Lg5sTOTqUTew3eTKQiROcBXgXNwZqoGkTuB92LMb5o9uIgMAh8GTjTGVEXkFuBi4K3AjcaY1SLyD8B7gb9v9jhK54h6aTTj0A0rfx338CT1dzhdzpzImLCp/dCiQS5fszmxrOVSMdJE5b8uoylf7KWisOrCkxnYtZ0PvWsp4Lx8vcixZqO8nnSdwXEING0fT3Kus/tLLDluTqKZyVQi7+G7SWcQ/+hu+0rgEWA+8Jfu8gszkKEsIjWgH3gKOBN4p7v+68C1qILoeaJe3LP7S3UZun6CL+845+escsnq+PPnGXxsYXhHM//LKKlJaNA9hj8T2E8wyiqtA3dG3zSGFg2ybt32yWXeuQSVQ3+pwPmLj+beB5+bPP+xfftDZxtJch78wQBBkjhYbf0gnJGmw86xWt13PFUVQpAkvTa6iZgkd7/IDmAexjzvWzYAPIwxs1sSQOQjwGeAKvB94CPAfcaY33bXHwN8zxjzipDPvg94H8DcuXMXr169GoDdu3czc+bMVsTqCr0q9+jzL/DUHsN+115fLMjki+eZXXvZNz5BX7HAhDmwTZBj5vTXbW+jr1jg0OnT+M2edBbHggj9fUV2v3jA1DG3DM+EvBeLBWF8wtBXLETK4u13cPaBMNvRao0ndlQxgXG5d03821V2Vq0d4MJYODhr8h6J+nxQJtvxvO2ASFleMqOvbkQ7Wq1ZvyfbsWvVMZ5OoA/7igUWvOzQ+A0j8MvXVywwd9Z0axh0HK08k0nlyFLeZuRetmzZJmPMkrB1SWcQvwnZtgj8OuHnQxGR2cB5ODOSUeBW4C0hm4beucaYLwNfBliyZIlZunQp4ESneH/3Er0o9/BIhSee3MTnflqfxFSQfRRFqE0U8NJtwqKRwBnxVmv73BpE82KdmuWScOqxL20yzPTAbfyxhfv5/P1xj4A9VciryPrNLc/x5OgeV/6XcfuDT1AN6epWLo1zw/knNoTdVkark34Amz9gcKDMh961dPIecYr4hTcccrYvsn7F0rplUaP96AzuCWb37+Oac5yckU/efT/V2oHvNdGxv/cDVv+iOHls24xFgIdXLg1dl4ThkUqDfMHrnoZmn8ms5UhLVu+SpAriM8AaRD4FPArMwzH7fMb1TzgYsyPl8d8APGyMeQ5ARL4FvBYYEJFpxpj9OE7xJ1PuV+kQThvMxhfahGnsj1ybcEJRZxwyrS5SyGuRWRmtclOCiJdqbZz7frWz62GmXoayP0QxSrkFTVhhphRbPkfQ5NCMHybKdOOts1WP9UxAtmizuGMPlEt1SsN2nFZt73mJCsqLHK2SVEF81f39epzRvJdK+Ubf/wZnVpGGx4DTRKQfx8T0emAjcC+Ob2M1cBnwnZT7VTpEmob04LS+3HzNm4DwaKSkL/12J5UlJW3mc9yLPamTNs6HEZd3YqtAGyVfVLSZ7dg22mV7z0tUUF7kaJWkCuJ323FwY8wGEbkNJ5R1PzCCYzK6C1gtIte7y/65HcdXorlq+H6+ueGxyXpC5VKBG85/Zd3LKm1Dev/Lo9celixI8uJO4qSNSuzzv2htiVgbH93RMPv55Lfup1wqTM7omsFLYPQ3cgJ45ukXeE9Icyd/SPQh05qv/ONdS9uwoSCSuPdHFuQ9OikpyRSEMckK6TSBMeYa4JrA4l8Br27XMZV4rhq+v8FcUq1N8FE37NN70JaftYAnHtjU8PmC4PogDjyywRGi7SHyR7dMNeJe3JAsgzbY09rzXQwGXsA2U8fNGx4P7anRCv2lArVxMxnFVRmtOg2IDHz4pAkMhYbGQ3tr9QX7mskitjVl8hNWbbad5D06KSnJE+VEhoBXAfUhBsZ8OFuRlDxw84bHQ5dPQIMdffjpnzO73zQkx0G0qSQs87pUFC561TGhL7BeZ3Z/KfbFncZGnWSmYZultePaVmsTobWbGrcb5/I1m0Md8v6KsElzIeKaMvn37e9bkQVRs8A055BXkibKfQknge1HwFg7BVLyQdQLJPjSGSiXGLl6aei2sQ9E8DAGlhw3J9JZ3YszjHKpOBkFBJ2zUWfZzzqOtN+J7R7zZhlJZ1dprlmWM4m4WeBUyOdIavS7GDgVY87DmEvqfpQpSTGiTrYB5q24a/LnZ5Xnmeer3Z+UVWu3NdQ68kqDR9lqe005+NtqetjOL2sbta2vQ96xza7CSHvNovaVhqhZ4FQhqYLYiYaaHlRc8prkoUleUpg3gkqqJGwjv8polT0vxtfu6QXKpSKff8fJDSPJ5WctoFSsf1V7zXqywjN/VGvjkwp/dn+p5xSsh+1+WXbCEZntK4t9TKXgi6QK4jrg84jMaKcwSn5YctycyO5hNtKMoGwjP4HE/ZM9omY8naYokqypTYh5LSs884dnXho3TqOf3W1WvOVSoeXvwvZ52/1y74PPpT7GQH9rmcqQbBYY1h2vl0j6Bvgx8GbgeUTqf5QpxwHbanPhjklHUDbzRzPvyTQlK9rNhDE8vPLsyAY3Uea1LOh061aPvbWJyO8i+H2Hrb/kNcekai/azIh99979Lb+s49qg+pW0vzteLymJpArimzj5CBcCbw/8KFOMpFEhNpLahIcWDTa0kWz29TW9VLDa1r0R/UC5xOz+0mRvZfGtv/S0YzObhXgVaKNeBFHmtSxGm90ycxw1ULZ+/96Myv99X3rasQ1tRK8fWli33UC5REHg8jWbmbfiLk657vt118Z2vIFyiUHLuiyUcdj9658xTgUfRdIw198BXo1T+kKZ4rTyckkb6x2M9LCVYIjjxf2NIZYefh+APyyxVCzU9WgAUjW3iSIu8iYquijYi7mZSJhmopcG3c/YZnGlooAhsonS2L79nP3KI+uS8MBJVAuGgPrxvpcr1mxm1dptk705wsqZj1ZrLL/1QLhqWM5BqSCItN4G1y9bWK3fuYYAACAASURBVLhqVKTSVPBRJJ1BbAKObacgSn5oJZLmgsWthfaFTduTkKTxW3DKv298gsvXbJ4ckV4/tLBuJiHiJH81S9RoMcl5tjLaDNt/qWCfIRVFWL/iTB5ZeTY3XnTK5Mjb36Ro1YUnc9Grj4mMgto5VuP2TRUuWDxYN7IenF223hdRppiwcuZQPwMIjuQHyiUQR5ao2yLJfe4l7zVjJupUpFo7STqD+HfgDjcf4um6NcZ8K2uhlO4SV8Zheqlg7WTWjMPQj/cSSdOoB4jsiuYln9lMZ/4M3uuHHBOHn/kr7mra9GUbLQYTqWz7b3a0aUvUunXjY6z/ZWNNTX/UWqtNn7xM7QljJo87sGu7dSRuM8XEdfPzXxu/zKevvCc2yCHpTPeZXXvdiqz1siVJaJwK2dRJFcTl7u9PBZYbQBXEFCNYxsFPbTy8qY9HFtNn76WR1ERSLhU59dhZoS8+cEZ9caarqIe+lWSzqNFi8KUWdgwv58TLTh9IceywF/3QosGGvuAz+oosOW5O4w5CSHodvBe7N+L+1GLDX9xdn1R2+ZrNdbWYbPuwMatcamgZO7RoMPYenN1f4ppzTko003V6XjTOIv3HmMrZ1Mnmz8Ycafk5qs3yKV3Cs+0GzRK2hj8eWU2fk5qaiiJcsHiQnzy2K3I7z7Yehe3FEmquKUqkyQbSjRbjztezu6cN/w1jyXFzmO471p5944nMJsMjlaaS7Kq1cXbsqYUOLHaO1ZraZwHYs29/qOkn7h7sd7vzJaGvGP6K9I4RF6k0tGiQ9SvOjI1qyyvpDKwicxBZ1CZZlJwRFooZR1bT56Bd2caEMdz74HOJoq78derDsL1YwqJVVl14MqvefnJsRE6aukreMWzUJgzP7NqbaH9RNBtd00xPcY9gh736demyuwfKJWb1lxp8E945xCnbNLPcubOmR4ayToVIpSiS1mJ6CfCvON3eqsAMRN4OnI4xl0d+VulZmjEXZTlCSmKCOWqgnEpOg2NiCJo1bKP9oPngxkDUUzvON8rnEdcCNQnNRte0Yj6UGBXgbypjw98be/6Ku0K3eXK0Ovmd2HwYaWa5A+USN5x/otVMNBUilaJIOoP4Ik570WMArxnwfwJvbYdQSj5Iay5qRzazl4kaZiLyXuqzUvTvLYowcvWb+MJFp9BXLESO9ruV6BR13W0mjyz2H/d929Yn+d5nHFKMNRlGKYewUvFRMg4tGuTz7zg5VcKdjSgz0VSIVIoi6d32BuD9GFPB+x6NeRaY2ya5lBwQ5oOIIk39piQEy0X4TRHeSx0cW3RSvBHl0KJBFrzs0EjbcLfMB2F1msAJU507a3om+0/y4hweqXDKdd+fLMo4Orav4X6wZT4H2f3i/pay3YO3YdQ5eIOKK9ZsZnqpwEC51JTZLwlJr2WvkjSKaT9BM6HIAE4RP6WLDI9UuPaOrZPOyzQRGnEMLRpk46M7YpPHBCcTORgeGiZrmoiOsBe0od7UcPrKe0Lj5AsSnhsRZeMP0i3zQVi3tckopl3bM9t/1HcxPFJh+a1b6nxQe/aNUxBff2E3QOD6oYUsOW5O3X0Yxov7mzePeY50T/6whknV2jjX3rGVPfv2T94TO8dqlEvFBtNgVmQRqZT2uegkSRXED4HPIvIR37KrgP/IXiQlKWEP8c6xmtPFi2zs41F5DaWCsOrtJzOwazsfXBqvHNJ2UEvygrZtM2GckVySGHTbA9rNtpG2XIR161pXEFH797AFKPgXjRvD7ZsqLDluzmRochZRVja8RkOeI9qT339fhR0/bSOmtLTS96HVzoLtJqmJaTlOC9DfAIch8ixwOnBluwRT4rE9xLXx7Iq+RY2WaxOG6+7cmmg/zZhrkth309T9SetnWHbCEVa/x1Qn6SzJ+w6HRyoda0wUzLROEsGWV6dx3qOgkvakfg6R04DXAvOBR4H1GNN6SIXSNFEPZFYPRFyS2M6xGqPVeD9FM+aaJJmoUdskGdnZHtDr7tzK3kALTaH1UiK9QprkwGCf6WYYKJd4cX90EqYfbzaRlKMGyrGmnLD1aRIT4wjbf96joKJnECIHvnVjDMasx5hvYMyPVDl0l7ikpSwT1uJe/0li85uJ9oirlpl0myhsD+LOscbELkPrpUR6heVnLUhsXvDs/81SLhW59tyTJoMOsqZcKrLshCMiI9JsM8msTGa2/dsi8PISBRU3g5jXCSGU9EQlLWXZmSyJozpJbH7YSF84UAbD5phLMgtoxQactoxGXkZ27WZo0WBkGQw/cSUxohgMjOTTlFixUSoIM6dPY3SsNjlSv/aOrVZTTlQ9qGd2ZaMgbPufXiok9pV1g7hBQn66sCh1RL2oVl3Y2OISmu9udf3QQr5w0SlEhbvH7SuYKexPigrLL+hUJy5bmOJAzkd2nWA0gXJoBYGGEONmq/l6+xscKLPq7SczcvWbJkOYwd6h0HuObM9TFomJUfsfHau1NANuN3EziEMQuTpyC2M+nZ04SlJsI9/BgfCyykmiJeLq3gNcsWZz6KghLkrEv++wyqv+0VwwOqsyWq2r/58ltjBFoOcrcbaK7R6Lqpybdv9BvBnrzRseT3UMf+izh3fPRc1IPBls5yoIwyOVlu+7qIi4VmbA7SZuBlEAzoj4eV1bpVOspE3QiYuWSJI1PLRosKmy1MF92x58bx/X3rE1tB3ntXcki5hKS1imbKu+jamA7R7LQjlEhRzfvqmS6hi2JD9/kqUN73O2mYvBZJI936sJdXEziCrGvLEjkiipSJugExctEaVA/PscjBgJ2Ugaiujtw2YOaGeMfRh5Htl1Ats91qqfICqZM8m9Mru/RH/ftMj7Pul+gjPksPpNWeRR9Grp76SJckoOSfMCi0v6Shput/ysBQ3JeUK0UzyJY9dfJkHJD8F7bHikwliK0iZh7K3Z7fpxiqdcKkZWCkhiVvLvx8/QokGusITOxs2Qk7z4e3HAEacgsq++pnSFuJyCVFnDwbtCYOOjO+rKHowbMxmhEmXL9ncdG1o0yOkr77Gew+z+5EX5lOwJ+rGaJTgiT/pS98qN2F6ywUZINoR686p/fwMhlX7BPkMOHrMyWuWKNZu5fM3myfsfem/m4BGnIE7siBRK24mb4iZtjxjWI9gYU/eQBLuJXbB4sKGJvbjbBcMco0ZqwRGfEk3WNX6SmgqT4H3PaZROVC2n4ZFKIuUAjdFzwGRwxO69jbMjW9i47Zj+/S+/dQsIk89M3kppxBGtIIx5vENyKB0gaoqb1EZqe4HbHsxqbZx7H3yOG85fODlKDAtx9WSwzTYGyqWOPFB5LpyWhnbU+MkyB8QbkadROlG+gGabGXkF/rxciLDSNTMsHeiSHDNsf+2uDZUl6oNQJkliI22mP7PXxMUzIQU/739gbDOZa89t/+wh74XT0pA06CANrfTmDrLshCOaqt9k6wXdSlzVaLXG8EjFnqtQrbHo09/HGOfvLMJ8eyXhsvXuI8pBRTOJTH77re3B8DKqga6Fl+a9cFoa4q5zM8EAzfbmDuObGx7joylqKXkUxMlLCIZOt8qqtdsiI/GcmmOOb6JdOSB5JGnLUcGEXBWRMsb0hipUMiHMFPWSGS9SLoXX4wnrBGYbNXoj9hvOX9iQ9NQJ8l44LQ1JrjOkmxlFJxX+lGpEdFKQJK3Ow1qQjhsnL2F6qZCZPwSca9KOIIgCEHZVlp1wRObHagdJZxA/RKT+jEROAjZmLpESSbtLUCTZfzCx7ChfaW040IIybPQfNwPp5oh9KrWPbNd1tiUVPvAXb+HS047NpO1sQeCRlWdz40WnhO6vWhtPVCPKo79UiA3HFEi1zzCK4jTO8s9+Z1mUTq8UfUzqg3gE2ILIJRjzn4i8B/gC8Nm2SaY00G4beSv7TxrjnaQoW7dG7EkjuXqBblzn64cWcv3QwlA/Uxq82UVUXkIaxtyZjec7CM5MwmYqzTBhTENXxfkr7grdtldmpclmEMa8F1gBfAeRe4G/AM7FmL9so2xKgHbbyDtlg/dGobb2n90asU+18hrdus6tFNwLkqWM48ZQLhV5V2CUn1VF0jBZe31WmsZJvQF4Bvg94H+AH7dFIsVKlE05Czptg+9mfZrhkQrbnn6hwZQWZkLpdTp9ncMq9/oZKJe49LRjE+0rS2UDB8KuvQROr3hkGAPlEsWEDnjb9ezVGkweSZ3U7wL+Dvhr4B+BrwP/i8iFGPNgKwKIyADwFeAVODO9PwC2AWtw+lE8ArzDGLOzleNMBWzhdVnYfSFlNnUGdKs+jWdK+5MTJjAUejqcNQnduM5Bk+O6det45F1L67a566dPhdr9/TOeLPtEeHjftzdbDnumvNDqgV3b+cIJxzccX4D+viJj+8Zjy2t48vdibk1SH8TngQsw5m4ARN4CfAq4D1ruyvdF4D+MMReKSB/QD/w5cLcxZqWIrMAxb32ixeP0PLbwuizC7iDaBp82gSzP9WnakSOQd/JWB2h4pELYbRs2uo7KoYFGH0K5VOSG8xeGFt7zCIuACiv9sm7d9snr5n82DI6v5MaLTmlrQ6tuk9TEtGhSOYDXfvTTwFArBxeRw4D/A/yzu9t9xphR4DycWQru75aOM1Ww2ZJty9Nis8EDsaXA/SQpHd5NplI4ay/i9fsIVued3V+K9PnYzDVBn4K3j7QDpwljrKbFqZQjkwYJS2/o2MFFTgG+DPwcOBnYBHwEqBhjBnzb7TTGzA75/PuA9wHMnTt38erVqwHYvXs3M2fObP8JZEyY3KPVGs/s2su+8QmmFYTxCadGfRBBMBj6igXmzpo+2RHN//liQRBg/0TjdlFse/qF0M5afcUCC152aIPccdt3G0++uWV4xqcT8iJfFFPh3v75U88zHpIIUSwIJx552OT//nvXu1+BhmW2e9h2H3rPSpCw79+T+/7KLuu5LRycZZU3yfPVDtLcJ8uWLdtkjFkSti6ZghApA1cBrweOwO93MubliaQI3a0swTFTnW6M2SAiXwSeBz6UREH4WbJkidm40UnLWLduHUuXLm1WrK4RlDuskFmpKMzom8ZotWYNz/Om2NDYFS1su7jp7/wVd4UeR4CHV57dIHfc9t3mgA/iRT5/v2NlTXotus1UuLfnWUI/wcl/gPB7P+13ZNvHqcfOYv0vdzRsf+lpxzaEqXpy28xbXie7LOTNkjT3iYhYFURSE9ONOGaffwPm4vgkXgS+mvDzNp4AnjDGbHD/vw04FXhGRI4EcH8/2+JxepKwaW1t3DDjkGmR4Xne1DeuEJq3XVxyXNpQvbyH9nmmtL5iYUqEs05FsjDp2Eymj/wm3JR484bHrc9AXDTSVDVBJXVSnwOcgTG/QuQzGPN3bj7E/wtc3+zBjTFPi8jjIrLAGLMNZ4byc/fnMmCl+/s7zR6jl2nFVp7Unh6M6AiL6EmbQNaOhLOsq6wOLRpk3a7tPLxyadP7UJpjtqXngr/URVwtqaT3QZiD2JZ8FyxTDwcicOKikaaqXyupgpiJMb9y/96HSB/G/ByRV2Ugw4eAm9wIpl8B78GZ2dwiIu8FHgPensFxeo64sNOosL8B92GLKx9QkMaIjmptnOvu3Fr3MFyweJB7H3wu0YOZdWjfVKqyqjh9PZbftqWur0ipKHX9Pmz3vnDgvvfug42P7kh8b0bt249XBvwDC17kPSvumtyvrUbYrHIptCVuXmbNzZJUQTyMyO9izAPAg8AfIDIK2D03CTHGbAbC7F+vb3XfvU7cSDzKv7CrWuOQadEWxGJBQp2F4CgWT7lURqvcvqmSygwTFdqXZjYwPFJpW59gpTv9L5IMIJadcATfuO+xhs8G79ZqbbxuuyRKI+y5CmO0WmPfeHyuzPBIhT0hbVgL7rF6maQK4gbgWOABnDIb3wYOAT7QJrkUkj1ItljvCUNsdc2JJCU1XbJ6IaeZDXjb2sIVe3363m26OTOLyw1opZidTWkEj5s2+c72DIR1WQSniqvXircXk+QgqYIwZo3v7x8gMhvow5g9bZJLcbE9SN7Ir5UkubSfrIxWmbfiroY2oWlIk6QW52Tv9el7t8lzwmDWyj94XmHJb83KFSVrsF91r5lGm+soZ0wNaK02rtI0wyOVBhuujVJRrNvZSnfEVbds5UZP48yLevDSOr3DTCmtlgDodfLsWM2ye51HZbTKfJ8/wTYAKYpwWHlaqP/OVpDPJmuYSexjt2zhijWbe2JGEW2kFvlV7I/Sca67c2si5QAwzVJsrFQQLnnNMdbM1LgCabYQvixDZm3bFkWaiocPZnaHORUPJvIcjpx1kT4P//dve6lPGMM155yUuMje8rMWxPab8DNuTC4rDIQRlwcxDxjDKdT3KcuP0mHSNDax+SFmTp/G9UMLQ+PEveVxBEeaSUpspKluadv28+84OdWoy2ZKeWbX3sT7mIrkudJoWA5Dlh3fqrVxa5HLowbKiXNlvJlps4bevOdKxJmYTgP+CLgSWAf8E/Afoe1HlZ5i1FUyNh/H0KLBWCdecKSZxKadJgQ2q3BZm8kkrAzDwUTeK40G782wbOVW8PpD2KIE43JlwuRppvlQHkx6NqIVhDE/Bn6MyBXAJcCngX9A5CvA32BMy2GuSnoGLDHXQcqlItNLhdAZhwGuGr6/obSA31Y/q1yy+jBKRWHPi/uZv+IuVpwywehIJbFNO0wp2cIts6iEabMR9xXTtEOZmnSq0uhotZYqwS2MMIW27IQjuH1TJbQcza5qjaMGyozt228tK+75IqLkst2bYQOiZkbOeTDp2UgaxbQb+CdEvopjVroGWA/c0z7RFBvXnnsSy2/dQi0iTHWgXOLac53EI5tD2wsF9JRE0Pk9Wq1RkAOZr55Te3Z/id17908qqX3jE3zyW/c3nSzU7nBLWz7J3Fl9Le9biWd4pEJlZ5XKqGPOauX7DVNoS46b06A07n3wOXa59+KJRx4aWntpx54XJ53F/rLdfoXw8ZPHWbV282Qb1MpoleW3bQGyGfmXCpILk56NpA2D5gF/CLwbeNT9e32bZFJiSBLHPeOQaZPbXXvHVuuM4+YNj08qiDDnt/dgPOIrsnf6ynsaRmTV2jjTS4XIKbuNdodb2kwpA7u2t7xvJZ5Va7dx8THpEx2b6SkSHORURqvWZ8Tzz/kVFtSHvu6fMATHYbVxw3V3bs0k0qo2YSZ9EHkx7fmJVhAiF+L4IBYBNwFnYczWDsilxOA9FLbKqf7Rza4Ic5Q/zNXm/A4ut42cRsdq3HjRKalt2u1upQrhI89161RBdIInR6twjGW5hWZnlWki/Pz4ncVJfBw7x2pcc85JmfhE8pwfETeDuAWncN4/AHuB8xA5r24LY/6yPaIpNvwjq4Ill8HgjPS93ru2l23SdqX+BLmoGlHN2LTb3UpV6S6OifEFy/Jwmp1VponwC5J2QBKcmdqexSTkJUExSJyX7r+A54AzgDeG/LyhrdIpDQRDSaNuSG9ksuyEI7D1Xr/kNQeGdnHNTfz7yzI8st2tVJXusvysBRQCyj7ufslzEh8ceFaGFg2yfsWZPLzybD7/jpNbyt3Iy7n5iVYQxizFmGURP+GlDZW2EVd+Iki1Ns69Dz7HX7/jFPpLB75ukcYGKW87+cjE+/PHqPcVCy31U2h3K1WluwwtGmRwdjm0LaiNNEl8/uTMTsw5SwWZDADxE8zdSDsDzmM0U3OlNpSu0Yxd/snRaqzpZ3ikwu2bkmV0Bve3bt06lrYwNW5H/wglXwyUS6xfsTR0XZgzOuk9kXVuRJC+YoFLTzvWWhk2THavJPj8iM55zQRzdANVEB0gq5LKwyOVphJxkoxM0sxMsh7p5D1hS2kfNmf0Dec72fxx90RUPaUJY6x+AZvfy8/gQJkFLyvwx0udWfZVw/dz84bHuXzNZj52yxZOe/lsfvLYLqsjPcr355e5KMIFizuTj5IWVRBtJssY/2ZS+pOOTJLaP739+ZWelyjXaoe3PD4gSnuJckavX3Fm7D1hu28njOHhlWdbe0VfsHiwIcEufN8zAEc5+EuIjxsTmlvhdzYn7Tsxbgw3BXKS8oKmkraZLHvVpnFipe21bJsVDJRLDbZjoM5R7iXK5bnomJJPWnVGx/kqbH2p/XXIkuz75g2PJ5LHL7t37CS+CINTGjxvz5DOINpMltEYaRJzHvYltiXBZvO99tyTGhTM6SvvyW0fAaW3iGurG0cSX0VUvbGhRYPWWcbysxaAm0yZJqLOL/vQokFrD+wgBnL3DOkMos1kWVI5aQnkuHDVMGwjrbCbNe8hiHElx5X80GpF2TT3bSv7SBqPJDjtUv2kedYro9Vc3a86g8iYoEM6tJhYQRjbt7+ueUlU1zi/k85z3EXNJJrNL0vqB2h11NdOutlGU0lPFgEKWfivovYxPFKhYOnfXhTwJ24b4PZNFZYcNyd1D2yPPN2vOoPIkLB+CLdvqnDB4sHJ0clAuQTiZHxGNQ2x9VYAWL/izLraSEG8Ut7tIs99BLL0+SidwZ9slsQx3WlWrd0WqhygXjl4BO83/wwFsCat2j7fTXQGkSHX3rE19OV074PPTcZGn77ynobCed4N8ZnTDujruFIDwyMVa6heViP5qBLcnoxPjlZbTpTLkrybv5Teo5l7J9je1P/cnL7ynlhfYl7uV1UQGTE8UrFWTPV/2dEvsBmJtvNmF2HKIauRfJypJstEuSzJs/lL6U2ardoanPl7z0uSl39e7lc1MWVE1JTQ/2UndVpHbReVHJTVSL5XTTV5Nn8pvUmr/bGDz03cyz/N/drugAxVEBkRNSrwf9lJXmDDIxXG9u1v2I+3XVRyUFZmnl411WQR1aIofoI+hGZiQPzPTdg7wNtnmvs1SQ/4VlETU0bYpqGz+0t1X3ZU1Ma6dduttWW8DnFRvaKznJb2sqlGs7KVONKWv/HuqST+gzCCuRHQemmZqFm+35/ZCqogMsKWsHPNOY1VH6O47s5GRzc4oatRYXPNmFGiHhItoKdMVVoJhW5mBh323GQxiEnqz2wFVRAZkWRUMDxSaWj/WdfusFqL7Oo27NY7ymIEksQJ3eoxFCWP2Ebel6/ZzKq12+ru8ydHq/zWJ/+dcWMoilAuFRhzW5Xa8BfUnN1f4ppzGqsReLRSyLMTs3xVEBkSl2xjS5ap1sb52C1b+Ngr9wN2Z1iWafhJOnapqUaZikTNAvwDpY2P7mDunn2MG+c1OW4MYzVDQWjoU+3Hv2pvhDJpNakzcpafUb91dVJ3iLhy2uPGWJNxPLwbOwvnVK86oRUlKbYIn7gRtjdQshXomzDJqxVERf61GinYiYAMnUF0iCxevN6N3Wy/3uC+etUJrShxRI3Ok5S+eNIdfNlI0w037WAszbui3bN8nUF0iFZfvH5Hl+0GqoxWE8dCa76AMpWxVTXwBlFJSn2nbRkata8slncDVRAdImmyzez+0uSN692gwalj1A2U1Nyk+QLKVCWqqoE3a/bqP33holMoBYojlQrC8rMWcMlrjslEHtugqxcGaWpi6hBDiwbZ+OgObt7wOOPGINBQIbIgEhnx4BE3RU5qblIntDIVibLhh04Kgsvc/68fWsg3h58Awh3NA+USMw6ZxpOjVSTCce3JE3zWeiFSUBVEhxgeqXD7pspk/SSDM307rL/E6FiNowbKDM4eT3Rz+G8sW9KOOpuVg5Woez/oO1i1dhu1QEnW2rjhuju3smrtNi4+Zh8D5TJ79u2v287fTGt4pMLyW7cwYXFMREUn5X2QpgqiQ4Q5lmsThv6+aYxc/SbAKXoXRVjMtE1JGJyqkXkbkShKu0lTXM+mTHaOuTlJx8BotUapIMz2Deb8z9WqtduoxUQgVmvjfPSWzVzudpfzV0bIM+qD6BCtRizYQluXnXCE1bfRjtosipJ3omz4s/vruy0mdQh7g7mwnhVJn2G/Dhmt1lh+65bcP5u5UBAiUhSRERH5rvv/fBHZICLbRWSNiPR1W8ZWaTViwRbaeu+Dz0VGZPRCBVZFyZKhRYNcetqxDctLRWkofZOmUqtNETQbdVSbMLl/NnOhIICPAA/4/v8scKMx5nhgJ/DerkiVIa1GLESFtnpmp7SfVZSpyvVDC/nCRafURemtuvDkUB9AMJrP1tPdpghaKQee92ez6z4IETkaOBv4DPBRERHgTOCd7iZfB64F/r4rAmbI9FJhchaQ1gZps6sKxNpb8xRXrSidIqkDOLhdWFmcqMGc99nr7txaV0vNK8lh6/wI+X82u64ggC8AHwcOdf9/CTBqjPEaIjwB5NuTg3NTXfnt+9mzr94MNDhQZtkJR3D7pkrdDffi/uiCX0HCQlv9RcFs5C2uWlGypJVidzb8zmd4gcEE+9346I6GXvCHTCtyw/kLAVh+25aGaCkv36IZ2nHeYYhJkzOe9cFF3ga81RjzJyKyFPgz4D3A/xhjftvd5hjg340xC0M+/z7gfQBz585dvHr1agB2797NzJkzO3MSOA6nJ3ZUMbGv63r6igUWvOzQyf/j5B6t1nhm1172jU/QVyywbzxayfQVC8ydNd06Zc6KTl/vrOhFuXtRZmiP3KPVGpWd1brw0oIIg7PtZqK0JJF7tFrj8R1joeu8Z3y0WuOp0Sr7XU91sSAcFWHOijte3Hmnud7Lli3bZIxZErau2zOI04FzReStwHTgMJwZxYCITHNnEUcDT4Z92BjzZeDLAEuWLDFLly4F3B7J7t+dwGkikt4GKcDDK5dO/r9u3TpGZx2feGRga14yOFBm/YozU8vTLJ2+3lnRi3L3oszQHrltz93gQJH1K7I5VhK5HTnsr9JHfM94FiQ576yud1ed1MaYTxpjjjbGzAMuBu4xxrwLuBe40N3sMuA7XRIxEc06moL2x9FqLVWV1l5I1VeUdpGXisRRxxPIPJS1k+edlyimIJ/AcVg/hOOT+OcuyxNJEkdTMJu/VBDG9u2vK0X8zK69oaGsc0NOkgAACjhJREFUH7slPF7ai8DwT1P37ncanzTTwLzdDdAVJUvyUuwu6niG6NIffpI+f50879woCGPMOmPM29y/f2WMebUx5reNMW83xrzYbfmiWH7WAooFe+XHcqnIu047djKUbqBcAnGyNf0zBZtPYdyYyJmE3+HtmSXTJsl1ogG6omRJXmbQcWGuSUb2aZ6/Tp53bhRELzO0aJDPv/1kZvSF2QWdKqnXDy1k/YozeXjl2cw4ZFpDREO1No40zDPq14eNRKIaEaVJkmu1eYmidJq8VCT25LCVB08ysk/z/HXyvLvtpJ4ypCm6ZRtRGAzlUtH6wg/7XNzoJKldMi/2XEVJQ16K3XkypMmf8BOVCOv1og8erxPnfVDPINphc0+yT9uIoq9YSD0SiRudJLVL5sWeqyi9Sisj+6jnrJum3oNWQbTD5h62z8vXbGbRp79ft1+bDXHurOmOueodJye2MUbZP9PYJfNiz1WUXsZrRBRW1C+KqOe4m6beg9bElEVf5yT7BMcZ7a8Hb2sUMrBr++Q2YevD5Ar2hvDS+pNkf9r2k9fmJYrSy0RlP3u/vXLgQbpl6j1oFUQ7bO5Rnw0qnzAb4rp12yf/TmNjzMoemRd7rqJMNYL1nSqjVa5Ys5mNj+7g+iGnSMTQokFrf5dumXoPWhNTO2zucZ9Vh6+iHJyEWRcMcNN9jyUyP3fL1HvQKoh2fBFx8dDq8FWUgxN75GJ9Il1eQnc9DloTUzts7t5nr71jK6PV+sqO6vBVlIOXqDaoQeWRJ1PvQasgoD1fhLfPTpXjVRQl/yw/awFXrNkcWu85z5aFg1pBBMnypZ6nUUAzqIJTlOwYWjTIxkd3cNN9j9UpibxbFlRBuIRFGfhDUw8m9FooSvZcP7SQJcfN6amBlyoIl3bkRfQqei0UpT30mmXhoI1iCqK1iA6g10JRFFAFMYnWIjqAXgtFUUAVxCR5S1DpJnotFEUB9UFMorWIDqDXQlEUUAVRR685kNqJXgtFUdTEpCiKooSiCkJRFEUJRRWEoiiKEooqCEVRFCUUVRCKoihKKKogFEVRlFBUQSiKoiihqIJQFEVRQlEFoSiKooSimdQ9gjbwURSl06iC6AG0gY+iKN1ATUw9QFQDH0VRlHahCqIH0AY+iqJ0A1UQPYA28FEUpRuogugBtIGPoijdQJ3UPYA28FEUpRuogugRtIGPoiidRk1MiqIoSiiqIBRFUZRQVEEoiqIooaiCUBRFUUJRBaEoiqKEIsaYbsuQCSLyHPCo++/hwK+7KE6zqNydpRfl7kWZQeXuNGnkPs4Yc0TYiimjIPyIyEZjzJJuy5EWlbuz9KLcvSgzqNydJiu51cSkKIqihKIKQlEURQllqiqIL3dbgCZRuTtLL8rdizKDyt1pMpF7SvogFEVRlNaZqjMIRVEUpUVUQSiKoiihTDkFISIfEpFtIrJVRP7Kt/yTIvKQu+6sbspoQ0T+TESMiBzu/i8i8jeu3D8VkVO7LaMfEVklIg+6sn1bRAZ863J7vUXkza5cD4nIim7LY0NEjhGRe0XkAfd+/oi7fI6I/EBEtru/Z3db1iAiUhSRERH5rvv/fBHZ4Mq8RkT6ui1jEBEZEJHb3Hv6ARH5vR651le498fPRORmEZme2fU2xkyZH2AZ8EPgEPf/l7q/TwS2AIcA84FfAsVuyxuQ/RhgLU6y3+HusrcC3wMEOA3Y0G05AzK/CZjm/v1Z4LN5v95A0ZXn5UCfK+eJ3ZbLIuuRwKnu34cCv3Cv7V8BK9zlK7zrnqcf4KPAN4Hvuv/fAlzs/v0PwAe6LWOIzF8H/tD9uw8YyPu1BgaBh4Gy7zq/O6vrPdVmEB8AVhpjXgQwxjzrLj8PWG2MedEY8zDwEPDqLslo40bg44A/auA84F+Nw33AgIgc2RXpQjDGfN8Ys9/99z7gaPfvPF/vVwMPGWN+ZYzZB6zGkTd3GGOeMsb8xP37BeABnBfCeTgvM9zfQ92RMBwRORo4G/iK+78AZwK3uZvkUebDgP8D/DOAMWafMWaUnF9rl2lAWUSmAf3AU2R0vaeagvgd4Ax3avWfIvIqd/kg8LhvuyfcZblARM4FKsaYLYFVuZY7wB/gzHYg33LnWTYrIjIPWARsAOYaY54CR4kAL+2eZKF8AWewM+H+/xJg1DeYyOM1fznwHPAvrmnsKyIyg5xfa2NMBfgc8BiOYtgFbCKj691zHeVE5IfAy0JWXYlzPrNxzDGvAm4RkZfjmGiCdDS+N0buP8cx1zR8LGRZbuQ2xnzH3eZKYD9wk/exkO3zEk+dZ9lCEZGZwO3A5caY550BeT4RkbcBzxpjNonIUm9xyKZ5u+bTgFOBDxljNojIF3FMSrnG9Ymch2PKHQVuBd4SsmlT17vnFIQx5g22dSLyAeBbxjG8/VhEJnCKVj2BY+P3OBp4sq2CBrDJLSILcb7cLe6DfzTwExF5NTmW20NELgPeBrzeve6QA7kjyLNsDYhICUc53GSM+Za7+BkROdIY85RrcnzWvoeOczpwroi8FZgOHIYzoxgQkWnuqDaP1/wJ4AljzAb3/9twFESerzXAG4CHjTHPAYjIt4DXktH1nmompmEc2xsi8js4jqZfA3cAF4vIISIyHzge+HHXpPRhjLnfGPNSY8w8Y8w8nBv1VGPM0zhy/74bzXQasMub7uYBEXkz8AngXGPMmG9Vbq838L/A8W6URx9wMY68ucO13f8z8IAx5q99q+4ALnP/vgz4Tqdls2GM+aQx5mj3Xr4YuMcY8y7gXuBCd7NcyQzgPm+Pi8gCd9HrgZ+T42vt8hhwmoj0u/eLJ3c217vbXviMPfp9wDeAnwE/Ac70rbsSJ3plG/CWbssacQ6PcCCKSYC/c+W+H1jSbfkCsj6EY8/f7P78Qy9cb5zosF+48l3ZbXki5Hwdjmngp75r/FYcm/7dwHb395xuy2qRfykHophejjNIeAjHDHJIt+ULkfcUYKN7vYdxzNW5v9bAdcCD7nvv33CiBzO53lpqQ1EURQllqpmYFEVRlIxQBaEoiqKEogpCURRFCUUVhKIoihKKKghFURQlFFUQiqIoSiiqIBSlVUTWIXJVxz6nKB1CFYSiKIoSiioIRWkXIhcjsgWR5xF5CpF/xKkQCiJ/C5wBfAqR3Yhs66qsihKCKghFaR+7gHfiNJ45w/1xTErGfBD4EfAXGDMTYxbYdqIo3aLnqrkqSs9gzPd8/z2EyJeA3++WOIqSFlUQitIuRN4IXA2cgFNArUj+ykUrihU1MSlKO3BKiQ/jtDQ9FmMOwymN7m+eMxH2UUXJCzqDUJRsmIbI9Lr/nYY5OzGmisiJwAcDn3ka+O1OCagoadEZhKJkwzVA1ffzAk6d/r9CZDdOX49vBj5zI7AEkVFEtnZSWEVJgvaDUBRFUULRGYSiKIoSiioIRVEUJRRVEIqiKEooqiAURVGUUFRBKIqiKKGoglAURVFCUQWhKIqihKIKQlEURQnl/wfJjE8iPUGYIQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_date = relevant_fields[\"Date\"].max()\n",
    "date = datetime.utcfromtimestamp(run_date).strftime('%Y-%m-%d')\n",
    "\n",
    "# Setting a scatter plot\n",
    "x = relevant_fields[\"Lat\"]\n",
    "y = relevant_fields[\"Max Temp\"]\n",
    "plt.scatter(x,y)\n",
    "\n",
    "# Adding Titles\n",
    "\n",
    "plt.title(\"Latitude vs. Temperature on {date}\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.xlabel(\"Lat\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.ylabel(\"Max Temp\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.grid()\n",
    "\n",
    "plt.savefig(f'../output_data/Latitude vs Temperature on {date}.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observation : Max Temp is higher at the equator and lower at the Northern and Southern Hemisphere."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latitude vs. Humidity Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "humid = relevant_fields[\"Humidity\"]\n",
    "plt.scatter(x,humid)\n",
    "\n",
    "# Adding Titles\n",
    "plt.title(\"Latitude vs. Humidity on {date}\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.xlabel(\"Lat\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.ylabel(\"Humidity (%)\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.grid()\n",
    "# Saving the image\n",
    "plt.savefig(f'../output_data/Latitude vs Humidity on {date}.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latitude vs. Cloudiness Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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m6Vflktu2cln3Vi65bWv0AwFxQLJ3r73JjBxx0ITItJLWQZoU2UHcDpxn/30e1glZzvX3icUCYJeq1p/01SIsmdvF1e+eTVdnB4KlCcRZcPJ77toz5/h+6F42rsLk8ZW6+K9aMptzF0ynXYY3YncYv3RWnH4Mk8dX6tLxcu6C6YFWTL5rGwPKhLFjUimLoOeCwt7wkdf7lkWjJI3LG7Krs4NzF0wflHPy+AqdHfV1GMSSuV2B9dTZUeHaM+fElnHy+EpgW0i6OHqIPRIJoquzgxVnHMOX3zOHCWPrP4zucujsqAzmz8mHU25++eqr9XPj+u2x1w+CcJeDG3eK7SKcu2A6Zx87LbKMg25X2uCeTyyqK3N3u2ikDtIkLyumG4FFWIeU78A69rAb69D06VhHGp6hqjttM9d/wTq6cg/wAb/1By9ltWJKQly5G7UGSsLMZXcGLtp60/KTO+h5AR5bfnIqMjaKU35/P+ulYZY1CLEWft3miXEszSrtworTj0mlbppp23m0myDroS8saOO9S7zHRzdOWPtshsc9bTOsvOPU/8LDp/CLR3bm/i6kZcWUy+Saqp4dcOsEn7AK/EO2EhVLs7bmYdYmab3oh3R2+M5Ht4vE+qAEPR+lYaaN2xbeu3djx7b7EFsmZwjvrpfePXvr7PQBHv+TlS+nDNzP9LzwEntqw23Aav2aat00ip+8jdjYh7XfNQ8+5/vM8y/ua054D2HtM2zdLQzviCEIJ/9x1oAe/1Nfad6FRih+9WWU4dU6qr19g3OmnWEPugia540z/xuXpSce2ZS2GfR8nnOpXm22X3Xw/6uWzGbtrod4bPmiYc+48zbD3iDlxf2yO1MzDjMDnkmzbprBK29Swtrvkrldgfnc2x/XcDoeQe3rtHldrPrVdmoB5qdOmFs3Vhtqm0n2J4FV7185c07h70KjGFcbOZOGrXmQ5pGmRhI0Hw2WpcrMZXeycPlqujdVEz2fpxYdZAsftXeje1OVhctXB94Pm3POo278cGSOqpdmiWq/QfkUJFXZgtrXVUtmM3FcsN7bV+tnzYPPNdw2k+yRAKs8yvAuNIoZQeRMuPYf7wSovLRzr7YZpD1e/QZ/K4xmtdVmCZpqCJuCiKMhhj1fxMgpSqtPk6jRq1/+ARQdtGZLS7ag9tXrY0rtptrb13DbTDISdNd70e9Co5gRRM6koWEWpZEEaY87dr2YabqNEqTph40A4miIzly1n9ZeRN2ktQM6DlHt15v/IGujLHcGR71LfjLFHYGFxe21wBpXaeOiVZszHdFljRlB5EyohrnrodjxFKGR5DW/nBZnHzfN16ImbH9IlIZYaROWnnhkpNaeZ93ksSblsHjWgb5lunjW0JHG7vwXsSYTNIpx8I4Ak6wLxlmby3NElzWmg8iZMEuStWvjdxBu0vLAGUWQNcbY9vIMRL1lsfDwKdz7aI+vFZMfQXl0mDhuDEvmdrFw+erMLcnikqeVTJCVkve6Uw9Bk3FZrsk45X/xTVt8pwO91kphI7DPLxjetv3e38WzDmTFXdu4cNXmQCuqotpGs5gOogDS1DDz1FaCtKepk8ammk6j+JXFzhf2cs174u9BiNI+nfntoE4kTfcXcclz3SPOaCVqHScPCx6nvuOUS9J1Qff7681r2PpUWSzZkmA6iBYnjz0RDkGjn84EU2NZEGaXnrQsorRPR/MN0hTT2qmdhLT2N8QhzmglbB0n7nkMSQgaQcctl2ZGYEmsmtrEsuQq+oyHJJgOosXJc/4Z/Ec/jU6NpUEcq6OkZRFH+2zEQipL8lr3iDNaCSpvAdYtOz5VeeKsBUWVSzPrgknaltM2WmlNojyTx4aGKMruvizE0eAaKYsoa6SgXbdxd+O2KnGstPJsk2lYcDVjeRYnT0VYcqWFGUG0OGXYsVwkceb8Gy2LMO1zNJd7lFbuVzZtIoWticSh0RFY2JqVY9100Sp/1+OtsCZhOoiMyMuyKO48q/eMYOfc4rgyxc1PnHDuMB2VNvr2DaDa2DnXUb53HE+lzeKXr6vfPTu185udNRT32cve+Lo3VdnxzPN8IIN57EbrN+z8ZHe4rsn9iWSNK0+c9YPuTdVh56uLgOrQ+de9fbVhx/YmfTfGVdoGOwj3sbX7jWljwxPBJxke0tmR23eiUUwHkQF520FHaT9+ZwT39tVYevOWWDLFzU+ccN4wbsd2Xl9JcQjrHDoq7Vz+zqNjxRNG4A7yd89uek49yArGW3ZDHmgHUNpSbVPN1K97T0TYXpC1a9emLg9Ej+S6N1VZevOWYb6ZnCbjPrzK7brJ/W6E+UfzW/9yt8bevlrgudiVNmHxrANLv1/CrEFkQJ47W+PK4+fGujagsWSKm5844eKsGSQ55zpozj+u19k4xM1/I/6QwsrDnUaWbaqZ+g2TOWt5IHr9YMVd2wId94UR591I6pfJzcRxY1jz4HOl+k74YUYQGZC3ZVEUYenGkSlufuKEi5NeEkugZr3OxiHOnodGR41R5eHcz7JNNVu/acuUNK9hI+hmZKlG+EdrJu7ePbVAn1FlWpswI4gMKJtlUVi6cWSKm5844Rq1+ggiD99HcXw6NarhR5WHcz/LNtVs/aYtU5p5bUaWqHbYTNyHdHaU7jvhh+kgMiCNs33Tlsfv/GLHr1Cc5+PkJ064OOf9hvlK8mPJ3C7WLTuex5afzLplx6c+fxtnz0OjGn5YebjLLss21Uz9hsmctTxx46o0eG501Eg2ydnVbirtktoZ4FljpphSxrFK6Kv1h1qk5ImTbqNWTHEtpeKE84Zp1oopD7oCLGW6PCOjRnbjusvDz4oJrPM3/tDbx6SOCmPaZNgpeGm0qWbqN8yKKWt5ksQVZcXkR9Selqhd9360CXXHzxorplGCn0WKoxEUXenN7rSN+3yccEV4om2GOHsemtkXEVQe3vbU21djQOErZ87JxI1KWvWbpzxpxBV0VnecndRBu+6DUB2+JlX2d8FMMaVIWpYmeZ0OZohHnHWOLNZC/NrTgMazPDPEp9m683t+8viKb9gyrS/EwYwgUiQNS5OR5Et+JFHEyKhs1nAjmbRH2KGjkhbCdBApkoZf/jy9sxrSJ82dsXme81D2Hb1lJcqTrHvdb78xrTdh03oSl5g0rBKM1ti6OFpjtbdv2PnLjU4R+rWnLHwapS33aCFOub3o8hTQ21druXI1HUSKpDEPHaQdKpj1iJKT9m5nv/bUNbkjdc2+bDv//SjjulxUubVCuUZhpphSptm5zDDvkGY9otxkMfprxqdRXMo+ai3rulxUuZW9XONgOoiS4bWL92LWI8pJ96YqbQGeZZOuGeS9HpDnWkcjlGFdzq9Oosqt7OUaBzPFVEKcncFB+z9bSQMZDTgarl/nkHQNqoj1gLLv6C1aEw+qk8WzDgwtt7KXaxzMCKLEFKGBFGnNkmba3jMAJo+vcPk7/XeOR6UbdT/Iq2cSj7JpnqudlDR3LmdBGu9BM20raASz5sHnQs8E8ZZrp71z+6JVm1lx17ZSlXEQpoMoMXmfWlbkXG+aafudAdCzp8bSW+rPv4hKN45cQZrsgGrsziHtc7WTUuYdvc2+B822rbARTFS5OffLuo4ShZliKjF5eCp1U6TVRZppB50BUOsf2oXcvanKtmee58JVm5u2RGnWK2dW52qPFJp9D5ptW2l4XW1ViyYzgig5eWp2Rc71ppl21PkX7tPZgnSkJJYozWq4UXlstXnrLGjmPWi2baUxki96HaVRCh9BiMhFInK/iPxWRG4UkXEiMlNE1ovIQyKySkTGFi3naKBI//R5nQFwSGdHIo09jlzNarhh8mY9aoRy7jFIkzTa1rjK0Keys6OS2v6mso8MC+0gRKQL+BgwX1VfA7QDZwFfBL6iqkcAPcCHipNy9FCk1UUeZwA4fviTaOxx5WrmTIqgNK49c04m51u4GQ27qJtpW87uZ/f51S/tGwh5In0ZiqQMU0xjgA4RqQHjgaeB44H32ve/BVwB/Fsh0o0iirRmiZN2EmujzvEVXqz102e7OnBbMQVZCwF1Z3fkUSZFlnvRewyysprzxnvavK5Y51Z4nzv3sD76asM/7I2UT9ktxYIQTXD+byYCiHwc+DzQB9wNfBy4V1VfZd+fBvzYHmF4nz0fOB9g6tSp81auXAnA7t27mThxYj4ZSBEjdzC9fTWqPX0MuNprmwhdkzvo7KhE3veL68Bxyo6+8LBlI+2y3lrdFXhvdtek1NLxkztJnSWh0Xj9npvawWAb8ZJm+aRNknayePHijao63+9eoSMIEZkMnArMBHqBm4G3+wT17cVU9WvA1wDmz5+vixYtAix3BM7frYSRO5iFy1dT7a0/3rGrs511yxZF3vfSvanKjm338eWtbS2jzUH6ZX3p8tWBp+VdcE566fjJnbTO4tJovH7PXTx7H9dsrf9Mpl0+aZNWOyl6iuktwGOq+hyAiNwGvAHoFJExqroPOBT4Q4EyGkpA2n5vlsztYu2uh3hs+aJU5GtV8t5r4yYry55G442bbiusHaRF0R3Ek8ACERmPNcV0ArABWAOcDqwEzgN+UJiEhlIQtJvW8XI7yZ5m8nuulamboz8m+ljLJBQ5N97oDmlvmXjPxe4cXxm2qBw33iB5OjsqTNhvTEutHaRFoR2Eqq4XkVuA+4B9wCasKaM7gZUicpV97evFSWkoA1FebivtQqVNhm2Qa3VNz2/3bbWnn+5N1dQXyYv44DUyevErk+/e++Tg/WpvH5U2odIu1PqTtQU/edpEuOIUfxcto4GiRxCo6uXA5Z7LjwLHFiCOIQZZa7V+RHm5rfXr4DnArXyCl5uwM6lHwgerkdFLnD0stQFtSOv3k6drcv+IKOtGKbyDMLQWeWm1fjia7sxld/paLfTsqQ2zNXds2J1nW41W3X2bhKSjl7h539VXY/Plb21anizO32glTAeRMnl6Q03isTQtrrzjfl+t9sJVm7lw1WYAhCGzs86OSt0QvdkyCporbhfJ1KbfT25ofv4+qDzC5uiD5uGrvX202+dSuPd0ZO0p9+TXHjyYvrv+J4xtp9Lexode1cely1fXyePOX7sIZx83jauWzPYtl8WzDgw8c8OvjBrJl7eMOqnfX6NqdUCTOirs3dfPntrwjXPeNh/0fBrfh6y/N6aDSJE8PTYm8ViaZpp+i39e3K9vb1+NpTcPyZRGGQXNXQdNPaShcfvJvfTmLSAMznU3kpew8lg868Bh8+sOM17eEToP73xAnbg2PLGTWzdWM/WU607fXf8v7O0HhqfrlccttxPP/MOmhOYxisWzDkycL796+PQ85XM/Gbrubv9+RhHOdafNA8PidT/f7PchrO10Jo7Nn9aepC0ZeXpsjOOxNIs0G6E2MCRTGmUU5PuoK8LfjdfnUNAL7oef3LUBHbYQ2khewspjzYPP+T5z76M9kfPw7rhuXL+96TJ3yu7CVZt9211cguRxc+P67bHWGsIIKrsgguph5wu1huRw2nxUPpr5PuTxvTEjiBTJc844ymNpFjQTb9rn9AbNXQdZxTS7dpJEvjTChsURZ4olTvi4csY5ryINedz3s9oLkTS8+u/RTVWGRvMa3nYmNBSnFzOCSJE8PTZGeSzNgmbiTeIdtVHCvKqGWQTFIYl8aYQ9pLMj8F67BB1G609Q+DTPq0hDHvf9ZttD0ueDwkvgwb/x4owjR6N5zeN7YzqIFMnTY2OUx9Is8MtfHCptQzJlXUZBXlXTOBPAK7djb+8maV7CysPvXpu9kBu3Hjoq7b7h0zyvIglB8rg5+7hpDbc1J42k7SmoHqZMqDTV5qPy0Uzbz+N7Ez3FJDIRyyXG64ApwE6szWv/g+rzqUkyAshzV6oTZ55WTH75WzzrQNr7HhsWLsyKqaidu82eaxwkt9+1tL18eu3y/+Hts5l/2JREVkze8EnkDCo7hzhWTLDPV54wKyZv3r07pqPynISgeujc9RBXv/uIpqyY3PGmacUU1nbWrn2ooTi9BHtzFZmC5Wb7A8Afga3An4GXAa8BDgC+CVyJ6p9SkaYJ5s+frxs2bACM07u8aQW5/ebRl762n66/mNdSeySKKGu/suuotCc6NKcV2ogfo0FuEWnIm+t9wA3AXFQf9vJsdkMAACAASURBVIn1VcAHsXwnzYwlicFQEGntks1zn0tZaNWzDAzNE9ZBzEf1j4F3rU7jU4hck7pUBkMGNLtLNs99LmWjKH9NhmIJXqQO6xyGhyt8eslgSEr3pirbnnk+0TnMee5zMRjKQDIrJpGDEPkuIr9FpBuRV2ckl8GQGc5IYG//QKJzmEeDbySDwU1SM9d/AX4KnAb8L/C91CUyGDKm0ZFAnvtcDIYyEN5BiFyDiLv1HwRcj+o24F+BwzOUzWDIhEZHAkH+fZL6/TEYWoWofRDPAb9C5KOo/hT4CXAPIuuBRcD3M5bPYAilEauiRvdEBPn3Ser3x2BoFcI7CNXliHwf+E9EfgcsBdYDxwDXAN2ZS2gwBNCoVZHjDdY6xNAizg5UswZhMRpNfUdjniHOGoTqNlTfDNyP1Tm0o7oC1dtQHYh42mDIjEbXEhyfTWPb2+p8NoVh1iCGOuVqb1+iBf5WZjTm2SG6gxCZg8jpwN3A24ELEfkOIpOzFs5gCKMZjX7J3C6OfMX+dT6bwsjT11ZZKZupr9eFexYf7bLlOU+iFqk/C9yGZbV0J/BWVE8E1gC/sDsOg6EQ8tbow7zFjhbKNM2Wl2ZfpjznTdQi9d8BR6Dai8jLsUYR/4nqfyHyYyxLpluyFtIQzWicIw06Wc5Pow86TjIpo31HcbNOD9MkTLNPs47KlOe8iZpi2gm8AZEK8EZgaNe06tOovitD2QwxGa1zpHE1+qDySXKinMGiTNNseWn2Zcpz3kSNID6INUq4GdgCfChziQyJyUuTypO4I6I4Gn1Q+ezYZTqIpJTJcV9emn2Z8pw3UWau67BMWg0lZqTNkabtFC+oHPb2GyO8RijLNFuSKcZmKUue8ya4gxBpRzX6nMG44QyZMdLmSJsZEfmNPILKZ2y7OVCxlRnNmn1ehI0g7kfkamAVqi/W3RXZDzgL+CRwVDbiGeKQpyaVB42OiIJGHqfN6+LWjdW68pk6aWx6QhsKYbRq9nkR1kGcBqwArkPkF8DvGDpR7ijg9cAvgTOyFtIQjKMx99X6mz52sSw0OiIKGnmsefA5rn73bN/jJEcro9HqLQhTFsEEdxCq9wMnIXIkcCrWmdSTgR4sj66fQPXBPIQ0+OPVmPtVB0cOrdzAGx0RhY08/DTNtM7tbTVG88FHXkxZhBNlxYTtufVL2YtiSEoe1ktFaFeNzi0HjTwUWLh8dct3nGkxEq3e3CRpsyO9LJoluoMwlJasrZeK1K4amVv2G3k4GM1wiJFm9eYmaZsdyWWRBoWbcYhIp4jcIiIPisgDIvJ6EZkiIveIyEP2b+P3yYesXU2EaVduHzjbnnm+FJvy3Bvn/Bgt/nOiGMlOB5P6TRrJZZEGhXcQwHXAf6vqLKw9Fw8Ay4CfqOoRWGdQLCtQvtKS9Q7PIC3K0cqcncl7+wdKs3N7ydwu1i07Hgm4bzTDkb0zOOmIYCSXRRoUOsUkIi8D3gy8H0BV9wJ7ReRUrAOJAL4FrMUypx01xJlHbdYOPCqNoDn9dpHSz9uOtL0haTKS9w8krfeRXBZpIKrawFOyCNiH6s+bSlxkDvA1LBPaY4CNwMeBqqp2usL1qGrdNJOInA+cDzB16tR5K1euBGD37t1MnDixGdEKwZG7t69GtaePAVfdtInQNbmDzo5KKmnFSSMozICnzUztgB32Ozm7a1Iq8jVLnPy1YjtpRZkhP7nTfndGQ3kvXrx4o6rO97sXr4MQuRv4PKo/ReTjwNVAP/AZVL8SW+q6aGU+cC+wUFXXi8h1WHstLojTQbiZP3++btiwAYC1a9eyaNGiRsUqDEfuhctX+2pBXZ0drFt2fCppxU3Db5Sx4q5tw569ePY+rtk6JlX50iBqhNSK7aQVZYZoudO0lnPiqvb2Nb03aKSWtxsRCewg4k4xzQF+Yf/9EeCtQC/WkaMNdxDAU8BTqrre/v8WrPWGHSJysKo+LSIHA882kUbLkYdlRdw0gqyJWmHnttll2xqkbS3nPGP2NzRP3A5iLKo1RKYCBw1OLYkc1EziqvqMiGwXkSPV2m9xAtZ00++A84Dl9u8fNJNOq5HH/HkzaXjnbce2t6V6cI7Z2VpesqibLPYitNL+hjK397gdxKOInAccDqwGsA8QqvfRlJwLgBtEZCzwKPABLOuqm0TkQ8CTjDJ3Hnn4Vmo2Dbd2vnbtWhal2DkYza+cZFU3WYyYW2V/Q9nbe9wO4v9iWRO9hOV2A+Bk4NfNCqCqmwG/+a8Tmo27VcnDsqKs1hutpPmNNrKqmyxGzGnGmaWGX/b2Hq+DUP0fwCvtjfaPIQPymD8v4xx9q2h+o5Gs6iaLEXNacfb21bjkJ9lp+GVv7/E2yokcgciB9t/jEbkCa19Ce9hjBkNSgjQ8x59SGTbjjVay2nUc9+jYIuLcsevFRDuz3bi9DQS13bLv5I47xfQ9rLWB57AWjhcBe4FDgb/NRDLDqMT4UyovWa6NZTGaTSNO69TBej260bNJHLkcyn6WS1xXG4cD99t/nwacApxo/zYYUsP4U8qPOBqumyw0/bITdOpgo2eTeNtu2cs07ghCgHZEXgXsQfVx66rsn5FchlGMo/nNXHYnfts4yzI/28o0aj1TxnWrLJk6aRwdlf5UzybxUuYyjdtBrAe+CrwC+BEAIjOAnVkIZTBAuCVKmW3HW4GirWdapf46Oypc/e6jhu3Mdo8EgmROYkVV5rKIO8X0N8BErA7hs/a1Y7HWJgyGTFg860Df6zNe3jHMm6yj/ZoF7PgUaT3jjF5apf6WzO0a9Prab7smipI5rpfYspdFvA5C9QlUz0H1A6j+yb52E6qXZCmcYXSz5sHnfK/f+2hPw5YlBossrWei1jaSntlQBpLKHHdtoexlEd/dt8gbgfcBB6P6TkTmARNQ/d+shDOMboK02f4AB5NmbSI+WVnPBK1tXP2GIW267Lb/fjQic5y1hbKXRdx9EO8FbsdyrfFm+6oyNN1kMKROkDbbLv7HAZXFdrwVyMp6Jkgj3rFryCtP2W3//chK5rKXRdw1iEuBt6L6MWDAvvZb4OhMpDIYCJ7HPfu4aeYUsBRwTt97bPnJrFt2fKY7g639BBateIpbVjKXvSziTjEdguoG+29nfL8Ps5PakCFh/qLmHzYlE8uPMluUtAJB1jvu/QRl9QMWRlYyl70s4nYQjyDyBlR/4br2BqAcKymGEUvQPG4WtuNl96zZCgStbUydNHZYuDLb/geRlcxlLou4HcRVwA+wTnyrIHIxcCH2cZ8GQ5kIGwW47y2bM0DvpuowLa5MnjX98tEZ/VihBGnEnbseKliyctBqI9S43ly7EXkB+BjwBHA88EFU78lQNoMhMWGjABh+ytje/oFhI4QyWZTEsQYqK34a8dq1poNoxRFqfDNXqzMwHcIoJ2+tNqnGFWVXHjZCyOMkv7gE5ePp3r0sXL66ZTRQL0nqs9W07SiC6vTim7YA5ewk4loxgcg4RGYj8oZhP4ZRQ9Cuz96+Wq7phe0yDRsFRI0QymRREiTrvgEt7a7bKJLUZ9l3GDdC2L6esuYt7j6IU4CngS3Az10/P8tMMkNpcHbGXrhqc6SNe5o0sss0zK48yua8TJ41445ayrTrNoqg+rxw1ea6Hddl32HcCGF1Wta8xR1BXANcCUxEtc31U/4JUUNTuDW5INw27mnSyJpA2Cggzgghi70BjeAnaxBl2XUbRZic3hFCmdaD0iKqTsuYt7gdxFRUr0V1T6bSGEqHnybnJchnfhBxzyFoZJdp1ChgXGVI1vY2KZXvfTd++ejsqPiGLcuu2yii5HRr0WntME565kWWOHXaSp4A4i5S343IAlTvzVQaQ+mI0mr8bNzDSGLJ0ai/ID8rGm+6AAEunUqDNx/dm6pUH9g4LEyZdt1GEXZaoIN7PahZX1FltBpy0i3zKXJu4nYQjwO3I7IKay1iCNUvpCyTISZ5WHkEWfaApdUmtXFPstcgzV2mfukOqBa2xyGKoLrtfuZ3dHW2p1bnWbWhuniP6WfJoqH6DGpT7vUgJ2yjspVtX4tD2XdPu4nbQczDOnL0NfaPgwKmgyiAvLSjIE3OPTWTxMY96dxyWrtMW2lOO6xuOzsqrFu2KPN0mu10vPFWe/rptjclLpnb5Tui81sPakaOMtd5mXdPu4l7HsTigJ/jM5bPEEBeVh5pW/YU5b2y7F4z3eRVt1mlEzZac8jKYsy95tDWQnP9ZSX+RjlDqchTO0pT28nqHIIoFs86kO/e+6Tv9bIRXrcTckon+3jT1qK9oxK/c0PKOtdfVoI7CJFNqM61/34IfM+PB9VXZyGYIZwy7fpNQlHzr0Gn0wVdL5K86jardIpqm0EWd+0iDKjm0tZG2u7vsBHECtffV2UtiCEZRWniaVDE/GuZ56O9hNZtik7vsmpDfvG2iWTeNoPqckCVx5afnGnaUE6rqWYJ7iBUv+f6+1t5CGOITyOaeB7aTZ4aVJK0WmnEFVa3aTq9y/OMg67J/Zl/JIuu47JaTTVD2BTTmwPvuTFnUhdGEk08D+0mTw0qaVpFabWNktcoK68zDtauXZt6Gl6KHlW30ig1LmFTTD/x/N8GuM0CFOgH4u+SMhRGHtpNnhpU0rTy0mqjRjUjbY66TBS9v6DoEUwWhE0xDe3rF3kfcCrwSeAx4JVY+x9uz1Y8Q1rkod3kqUE1klbWWm3UqGYkzlGXjSL3FxQ9gsmCuGauVwKvRfV5+/+HEPkQlnfX7zQrhIi0AxuAqqq+Q0RmAiuBKcB9wF+r6t5m0/FSlDbXvanKFbffP+gme/L4Cpe/8+hh5yqkLVva2s05//lL1j2yE4CLZ+/j819eS5uIr2lhsxqUX1kE5UeBhctXJyovd/yd4yuowq6+GpM6KohA757aYLowtBNYZMhdx+Txlj4V5K10xV3b6N2zN/S+O/6geu/tq7Fw+WqqvX20CQy4ittpR43k2y8tdx0D7Demjb37BhKvd3WOr/DhV73I+5fdOXi/s6PCFacczYYndnLDvU8OmkhOGNvOu17XxZoHnxuUa/GsA7nzN0/Ts6c27FnvyMz7Tp382oOHxZPV++3Oa0elbbBdtItw2rxk08BlG13G7SBeBowDnnddGwdMSkmOjwMP2OkAfBH4iqquFJF/Bz4E/FtKaQHFWRx0b6qy9OYt1Fxvds+eGktv2cKKN1Yyky1N7cb74QB46NkXfMM2q0EFlcVp87q4dWPV16wxSXl543c+QsCwcy6qvX0svXkLCNT6rbpz94Xu5/wI84Y7GP8tW0AZbBt+I5BqTx/VXssj6ICnL3bakRM+jKg25lfHL+0b8A0bFXfPnhoDHsWht6/GRas219nOv7C3f9h+lWpvX93+ld6+mlUXDJWL3zvljSeL99ub1z21Ic/G/arcurHK/MOmNF0fRRHXDecPge8jsgiRmYgsBm4B7mhWABE5FDgZuN7+X7CONL3FDvItYEmz6Xgpyt/8iru2DWvIDrV+HTxXIQvZ0tq52r2pWvfhCKJdmveWGlQWax58bjA/fsQtrzjeah1qAzrYOWRBrV/r2oY7Hyvu2lb3ofWLo9F8u9OKquOw8o1bps2UZG1Ah5WL3zvlJa/d6I2kWdbzL0TjuLQUmQhcB7wX2A/YC3wP+Lhr2qkxAURuAa4G9gf+EXg/cK+qvsq+Pw34saq+xufZ84HzAaZOnTpv5cqVAOzevZuJEyeGpru1uivw3uyutAZGydKd2gEHTZlUmGxR9PbVqPb01X2kpnbAjgAFuVl545RFo+W1e/duHtsVr3MomtldVrsIK2tv+DCiyizsflQ6fs/GlTspSWR1PxOXqG9JM+UUN55G3qE430CHxYsXb1TV+X734nUQg6FFgAOB50j0YGB07wBOUtW/F5FFWB3EB4BfejqIH6nq7LC45s+frxs2bACsxcdFixaFpu3M43rp6uxg3bLsXEwFpQtwyZwB/uasdxYmWxRBcl08ex/XbK2frUxD3jhlkaS83PO8y+YM8G/b9kv1yNTOjgoT9hsTOaWUBCcfC5ev5qxpz/uWtV/4MKLKbIZrvSBpOn5xB7WRZnCXS9zyTtomo74lcz97d+T0Yhr1kZQ430AHEQnsIJKd9KKqqD6bRudgsxA4RUQex1qUPh64FugUEac1HQr8IaX0Binq/OGlJx5Jpa3eiVilXZg6aVyhskWRxBopLXnjlEXc8vKec7y3f4AX9u7zrQ8/Km1CpT04bKVduOKUo1m37HiuPXNO7BPh3M97ZXHnY+mJRwY6oHPHEafco8ps4eFTQp8Pq9+4p+HFK3V/Km0yrFzi1GHa71D3piq7X9yXSpplfefjnkldQ2Sv708TqOolqnqoqs4AzgJWq+o5wBrgdDvYecAPmknHj6LOH14yt4sVZxwz7HSwyeMrrDh96FqZzkZ2E2aNdMRBE1KT97LurRx+yY+YsexOLr5pC6+bPmlY3KfN62LFXdsGTwkDYpWX3zxvrV+ZOG7M4LOTx1fo7KggWKOByeMrg3GuOOMYVpx+zOC6h/tbPb7SxsT9xnCRfb6yn0znLpge+v+K049hxRnHBOZjydwuuiZ3DKbv902cMNbSq6JOUotqYzd85PV1ncR+Y9pi1a837snjK3UdmwDnLJjOuQumD+soJoxt9y0nx0oMu15WnHHMsPQn7Dd8dDJ5fKUunrTfoaC1DxEC0wyql7K+83HXIP7Sc6ULuAj4Bqr/moog9hSTbeb6SobMXDcB56rqS2HPJ51iKiNllzvIh//Vb2hnydv/KpU0Luve6ut19dwF07lqyexgGWK8TDOX3TlsYdSZ9hBoyldPMzIlxdtG/NKutMkwa6ss5YlL94/v4ZJf9KdeRlmXfdg76W1PDkHtqch2EkbzU0yqP/X8fA84A3hfTHljJKFrVfUd9t+PquqxqvoqVT0jqnMYjRRx1m6QlhN0VnIj3Lh+e+j1Zqw9sjoTokgLFN9RkY+1VdEWMTt2vZjb2RN55TVpeyqrpVIYzawaVYGj0hLEEJ8ibab9dqqm6UDOb6Od+3ozu7Wz2ulapA+eJGkU6RNob/8AfvpoXmdPZEHS9tSKvpridRAib/BcmYC1NvBA2gIZohmJXiMd2gN2Y7fbc9jN7Aj3+uoZ296WyvA+ax88XsurXvvozrC0g+QsirHt/pMVfjIFeRrwq6ci/R8l9f3Uir6a4lox/dzzcxvWOsQHM5LLEEIraiJxOfu4aaHXm7X2WDK3i3XLjuex5Sdz5Cv2T6VDzdICxc/y6pLbtg5OKfql7WdtVbRFzNRJ42Jbmi29ecsw02Nnh7jfNGrR1j/u9rRu2fGh7aloWRsh7hpEm+dnf/tM6vszls/gQyudr5yUq5bM5twF0wdHDO0igwvUYL2Qp83rGnY/ib+bLGjEAiXuGlLUvLVf2m5rq7JYxHR2VCLLqHtTlYtv2hLoacBvrr6s1j9+tJKsDsnXIEQOQPWPGchiiMlI9Brp5qolswc7BC/dm6rcurE6OA2VxN9NlmR1Nkec0WJQ2mX78ISVkVMmQWtQEFwWRXpwTUoryQrx90GMQ+RfEHkB2IHIC4j8P0TGZSuewY9W1ETSohUtQbwkycNIHi26ieO/aaTluRWIO4K4GjgWeBfwCHA48Fn7+kXZiGYIo9U0kbQYCesvSfIw0keLDlH1F3eHuCFd4i5Svxs4FdW7UX0E1bvta6dlJ5rBUM9I0KiT5ME7WkzL8qpshNWf42lgpOW5FYjbQYwHejzXeoDWeSsNI4JWtATxkjQPWVhelY2gMrn2zDls+sxbR2SeW4G4U0zrgC8j8glUX7TXHv4J+GV2ohlGM0GnaxV97nAaOLK6bf3HVZL5zRxpjIR6HYnE7SA+BtwJ9CDyLHAQ8DDwjqwEM4xeoqx8Rsr6i3NCG1i2/mU4QaxIRkq9jiTidRCqTyIyBzgOy/32duBXqLbGaSs5UcSZsnmn6ZdeZ/RjiRjJO8UdRkMeDa1P/H0QVmfwi+xEaW2K8I+Ud5pB6V39hmTnHkQxEiyVohgNeTS0PsEdhMjXYsWgen5awrQyRWiEeacZlN6OXemdyAbBPmvaRJi57M4RMT/din55RhJFjPZbkbCVsUrMHwPFaIR5pxkUr+WpMz2CTiTrV0UZGrnk4eI8K0aCNVar4vVvNRLaU1YEjyBUP5CjHC1P3hph96YqbQGeT7NKMyiPQZ46G8Vr0eKXz1afrzdWO8Vh1n/iE74GITIV+EtUb/K5dwbwU1SfzUa01iLPHa9hfmuy1EKD8jh10tjU03JbtMxcdqdvmFafrzdWO8Vg1n/iE7VI/UngTwH3DgcWABenKlGLkqdGGOS3pl0k0122QXns3JXegUF+mPn6ctIq8/heOTvHV+jZU79uZtpTPVEdxEmA9zxqh/8CfobpIAbJSyMM0nQGVFv+RDk/Ros/olaiyFMNk+Anp3NehvfMbtOe6omaPH4Fqjt871hTS69IXSJDJCPBH1ESyngGRFH09tVyP4vcj1bxqht0ZveEsWNGpTfkpESNIPYicjCqT9fdETkYSNe+0RCLIjTqIqcTkpwBESRnHhv8sqZ7U5VqTx/VXsv6KUxrz7q+WmUeP0ieXX01Nl/+1pylaT2iRhDrgAsC7v0D1hSTIWfyPg+iaLPAuNpqkJyXdW/1ve4+1rIVWHHXNgYCrLnc5FFfrTKKbRU5y0rUCOLzwM8QORC4EahinUV9NnAO8MZsxTME4V4LcLTFi1ZtzkRbLNosMK62GiTnjeu3+5rJpr3BL2v+0NsHPkd2V3v7hm0gzKO+shzFpjn6MetXzRHeQahuQOQU4KvAhwAFBMtR3ymo3pe5hIZQ8lgsLHo6Ia4VU5A8QcdYpr3BL2us/D7ve889Ugg6mS3N+srKai/t9mz2mzRHtC8m1XuAVyNyBHAg8Byq2ZqtjECymhPOQ1ss2sw0rhYYJGd7wIbCtDf4Zc3SE4+k+sDG0DB9tf7A/KZdX1lY7SVpz3HfKbPfpHHivyGqD6H6C9M5JCfLOeE8tPui3ULEXXMJkvPs46b5Xp86qbWOVF8yt4uuyR2D5RBEv2rLuvGI256LXhcbLcT35mpomCy1/Dy0+zIM0+NogWFyzj9sSu4b/LKgs6PCumWLAFi4fLVv3Xe51iJabVolbnsuel1stGA6iBzIUsvPaxGuVYbpQXIWscEva8LqvlXqy0vc9lz0uthowXQQOZBEy0+6VlEG7d7gT9Z7EUbi0aVx23PR62Kt4makWUwHkQNxtaLevhqX/CS5BUeraosjmTxdUYy0o0vjtOcizVdbxc1IGhTaQYjINODbWC47BoCvqep1IjIFWAXMAB4H3qOqPUXJ2SxOo7nyjvsHnYTtN6Ze09ux60X6asOvJ51X9dNsoDVHGJd1b63bw9DlI3/c3dOLZx3ImgefGwp3TH/d85M6KohA755aU+UXNEd+4arNXLhqM50dFa445ejY9eCUxYWvqfGhS37E2cdN46olswPTufKO+0PbgV8+/ayE3KOTyeMrnPzag4eXoR2vOxxYtvDnLJjOVUtmA5byM/ezd9c5yWsXGcyLlzAtvZGRc1paf1CZX3H7/U29p2V8J4seQewDLlbV+0Rkf2CjiNwDvB/4iaouF5FlwDIsz7ItzYu1IU2vt69e07Ps8us7jrjzqn6azdKbt4Aw6JisVbSdy7q38t17n6y77pU/SJvb8MRObt1YHXbdHV+1t49qTz+XdW8dFs79kav29rH0li2glv8ev/SDiKqz3r6aVTcR8fiVRb/q4P9B6fTsqQ1+jP3agTef3jx1b6qy9OYtg/l24vSW4dJbttDfr3h3lCgMhp1/2BSe6umjZ4//IVBOOHcnEUdLTzJyTlPrDyrz3r4a3ZuqkfG10gik0AlLVX1a7c12qvo88ADWTu1TgW/Zwb4FLClGwvSI4y4iyC4/7rxqkGMyt9dKv3TLyI3rtwfec8sftns6aMOYw4BqZLhavw77SHrTDyJOndUGNDKe7k1V344SrDKK2zb82oEbb55W3LWtLt++8fp0Dl4ZV9y1DQ3YrOgO5yZtZ4BpxhdW5nHiaxVHhwASVXF5ISIzgP8FXgM8qaqdrns9qjrZ55nzgfMBpk6dOm/lypUA7N69m4kTJ+YgdXy2VncF3pvdNQmA3j8/T3W3DvO30yZC1+QOOjuiT3cNSyMs3WbJorzj5GV216TEeXYztQN2NGH0ElZ+vX01qj19db6TksTjF4dX5mlTxsdOJw6OLM2Uqx9xytpdDnHelyQ0Gp9f2+7tq7F9556G5Us7b34keScXL168UVXn+90rRQchIhOBnwKfV9XbRKQ3TgfhZv78+bphwwYA1q5dy6JFi7IUOTFhNuvrlh0PWHL3Tjqi4bnJoDT8cKfbLFmU9+GX/CjQRQYMyR+U56DdxG4unr2Pa39biQwXln4YzjxzWJ20izCg6lvXfnm7ePY+rtk6ZvDZR64+qW4++4WX9jXkiNCdpyRtKQzHRfuFr6kNyh0U7pGrTxr8P877koRG4wtq237rKXHlSztvfiR5J0UksIMo3CZORCrArcANqnqbfXmHWO7EsX+3/LGmcXcjL5nbxbplx/PY8pNZt+z4RHOSfmk4h6NEpVs2zj7OxyudjVv+JLunvbTZC6Rh4SrtQqWtsfJz6vLaM+fU1YFDv2rgTuCodQynjLxt5opTjo7VDsLytPTEI+vy3QhnHzctVgfsre+0d++nHd/l76wv47jxFe2ZIAlFWzEJ8HXgAVX9suvW7cB5wHL79w8KEC9V8tivEJRG1ulmgbNgGWXFlGT3tNeKqWtyP//w9tnDwqVlxeTGz4pNBLzfTa/FWpCtP8C5LguhoPSasWLy22PRJuC3LDF5fAVVAq2Y1jz4HEFOBoOsmNJ+X8oUXyvtXSp0iklE3oh1psRWGFzr+hSwHrgJmA48CZyhqjvD4ir7FFMcjNz5UqTcM5fd6K3LDQAAEpRJREFUid+bJ8Bjy08G6q1dAJa+tp+uv5hXyMfET56OSnvkWSTdm6pUH9jIit+0J3quDIyGth02xVToCEJVfw6BfsdOyFOWkUKr2FePduLsBPbTNLsm9xdWn41qvkvmdtH9zO/o6mwvrF2a96Ixit4HYUiRVrKvHu3E3QnstfVfu3ZtXiL60uiufbeTwbwx70XjFL5IbUiPK++4v2Xsq0c7S+Z2cdq8rkErn3YRTps38lymdG+qsnD5arZWd7Fw+epC3HGH7Ttw5Ju57M7C5CszpoMYIXRvqvqa3YHxcFlGujdVuXVjdXABvl+VWzdWR9QHyn1mAxR3ZkNQ+3fkMWdKBGM6iBFC2CjBHNBePlppN22jFJVH76igc7z/JtN2kRFfB81i1iBGCGGjhDLaV492RsN5BkXk0W+9wdkD4nY10lFpz+Xs7lbHdBAumrV0cO+cdXby+nkfzYIgq5jOjsqIm9ceCRR9nkEeFJHHIH9knR0VJuw3Zti7HbTLPUi+0WgJZaaYbJo949Y73+rMLec1rxm0O/OKU47ONF1DY7TSbtpGKSKPQdr/rr5anYeCJPKN1jOwzQjCptkzbv2ebySeRmnURj1PrWg0amBBtNJu2kZx5xGez2U0nWTUkqQORusZ2KaDsGl2vjQqXB7zmklt1PO0Dze26PWMhpMAnTyuXbuWC85ZlHl6SU+ai1sHo2HNyA8zxWQTNO8Yd740KlwZ55bztDJJkpaxTR+dpFHvS+Z2cfW7Z9PV2YFg+e5Kw6VHs9+HVsWMIGyaPePW7/lG4smTPLWiuGmZkcboJM16z2JkVuQZ2EViOgibZueE3c8XYcXUCHlamcRNq+i5XrNOUgxx672o+hkNa0Z+mA7CRbOaR6vNKeepFcVNq8i5XjN6KY449V50/bTa+50GZg1iFJPVfG0zaRU51zsadjeXlTj1buonf8wIYpSTp1YUJ60i53pHq6VKGYhT76Z+8sd0EIZSUeRc72jY3VwGwtYRwurd1M8Qea3FmA7CUDqKmusdrZYqeRK1jhBW76Z+LPJcizEdhKHlSUubGq2WKnkSx1opqD5bqX6y1PDztPQzHYShpUlbmxqNlip5ErWOEGeEUfb6yVrDz3MtxlgxGVoaY9nSWkRZKzVan2XafZ91m8zT0s90EIaWxli2tBZRHlQbqc+yeVrNuk3m6SXXTDGNAEbz7t+RZNnSaD0mfS4qfJbtKWwdoXtTlTbbA4GXsPpsdk4+7fxm3SbzXIsxHUSLU/Tu0qIZKZYtjdZj0ueiwufRnvzWEZx0/TqHqPpsRmPPIr95tMm81mLMFFOLM9rn4PPcDZ4ljdZj0ueiwmfRnro3Vdn2zPOh6wNB56m0i0TWZzNz8lnkd6S0STAjiJbHzMGPDMujRusx6XNR19NuT46G/vezBlDaAjX0oPgHVDPdfZ/V+zMS2iSYEUTLMxr91JfJYiUtGq3HpM9FXU+7PcXV0JtJtxmNvaj3p1XasOkgWpzRcLaxm7JZrKRFo/WY9Lmo8Gm3p7gaerPpLpnbVXfmdByKeH9aqQ2bKaYWxGt1cdq8LtY8+FzuVkyOHGdNe55Ll69uKt24liRRFiutatHVqGVK0ueiwqdtIRPXoietdJPWfxG7s4s+8yQJpoNoMfysLm7dWM19EWyYHNOas/5IYkkSppG2ukVXo/PWSZ+LCp/m/LmzPgD7Bq8FaejNptto/ee9XtBK64amg0iJvDTXIO3jwlWbWXHXttB005QxTS0oSVxhGmkraWZJSTJac8L6nWwI8bXl7k1Vrrzjfnr21ADo7KhwxSlHAwy77lBpg30DMKmjwt59/eypDfjG21frZ+nNm7lw1ebBa5PHV7j8nUdHyhflCbbRdyOMoHJIe1TVOb7SUHxZYjqIFMhTcw3TMsLSTVvGNLWgJHGFWaxc5PrgNCtTmUgyWvPWs7OvoNrbx9JbtoBCbWDoWlg8S2/ZQq1/aF9Cb1+NT6zajLQJ/QP1+xWc/qC3r1Z3LyisQ8+eGp+4aTPtbTKYZtI9Go2+G2H09tVYek99OSy9eUviuByWnnhkXdkC7H5xH92bqqVSZkrbQYjI24DrgHbgelVdXrBIgQRpLlfecX+o9rN41oHD1w6O6Q/UkBwtpv61HE6QxhRHuz7nP3/Jukd2Rua3s6MSKIcztxyVV+d/P03KoU2EGcvuHKYFL551IOMqbYN5cWtzjtYcJFMRNLM7+lO3/SZUC7/4pi2D/ztpBO1EBuo+SE48F66ytHkRUAWBwPodAPDpHNJgQGHAI6OffH73L75pS6x3w73fI6hOLuveyo3rt9OvysWz91Hrr/9M1gY0lgdaP5bM7eKK2++v60i9cZaBUnYQItIOfBX4K+Ap4Ncicruq/q5YyfwJ0lx69tQGNQI/7ee79z45GLba28dTPf1c97MtdRrehid2surX231f8CC8GlPQh9i5HrdzgGANsb1NWHrikbHy6v4/COdD59aCvc+9tG/oA1q2XdXN7I7+xE2bI7/D/aqWJitDH/+gziEOzqPZfP6bJyxrcfPt1EFQnVzWvTVW24T4Hmj92BXwDpVttFtWM9djgYdV9VFV3QusBE4tWKZAovzEOL/9doq6UdXBzsGhr9bPjeuTdQ7uZ53020V8wzjX43YOYQwM6KAmH5XXtHDnsWw7WJvZHR1XSa8NaENtYzQTVic3rt8eO55mPNC2yv4l0SY0jqwQkdOBt6nqh+3//xo4TlU/6gl3PnA+wNSpU+etXLkSgN27dzNx4sTc5O3tq7F9557A+7O7JrG1uisynqkdsCMDBSIq/bjyBeGWu9m4GmV216TEz2TdTqLKvJHnsmojWdMKcvu13SC5BeHQKR10dlQaqufevhrVnj4GXN/fNhG6JltxNkuStr148eKNqjrf715ZO4gzgBM9HcSxqnpB0DPz58/XDRs2ALB27VoWLVqUh6iDzLnybt+pl67ODtYtO56Fy1eHzrcDXDx7H9dsrZ/1aw+ZV44iKn3n/oxldzYUPwzJ3S7CI1efFCuvaeLkISlZt5OoMk/6HAS3kbITV+7OjgoT9huTWfsJepecOjn8kh8Nu+8nt9eKqdF6ztLyMUnbFpHADqKsU0xPAdNc/x8K/KEgWWJxxSlHJ96h6kVEqLQNnwrqqLRz9nHTqLT7TxGFkWSH7MLDpySO38vZx00LTCsryrxrvJnd0W0B1e29XGmThtpGUXRU2rn2zDlce+Yc37K54pSjWbfseK49c07q+aq0CWcfNy20Tpw2HMS5C6az+fK3DvuQN1rPje7+zpOydhC/Bo4QkZkiMhY4C7i9YJlCiZr/9rt/7oLpw/4/dHIHK844pi6Oq5bMZsXpxzDZZSfdUWljwtjgj3Cc9N33b/jI62N3Ep0dFfYbM7zpnLtgOlctmR07r87/MLQO4vwOuu8XT5m9ZDa6JrJkbhdffs8cxleGyljEKuNDp4wfFt+KM45hxenH1JWtu610dlQ4d8F0OirD68xbh84ylfuzPL7SxuTxlWFxj6809tlw5z/O++Jt804+nGcmj68MTsd428hkz56Czo4KK844hquWzA5N96olszl3wfS6Nbt2kWFt3E3Z1r5SRVVL+QOcBPweeAS4NCr8vHnz1GHNmjXaihi586UV5W5FmVWN3HmTRG5ggwZ8V0s7mamqPwJ+VLQcBoPBMFop6xSTwWAwGArGdBAGg8Fg8MV0EAaDwWDwxXQQBoPBYPCllBvlGkFEngOesP89APhjgeI0ipE7X1pR7laUGYzceZNE7sNU9UC/GyOmg3AjIhs0YGdgmTFy50sryt2KMoORO2/SkttMMRkMBoPBF9NBGAwGg8GXkdpBfK1oARrEyJ0vrSh3K8oMRu68SUXuEbkGYTAYDIbmGakjCIPBYDA0iekgDAaDweDLiOsgROQCEdkmIveLyJdc1y8RkYfteycWKWMQIvKPIqIicoD9v4jIP9ty/0ZEXle0jG5EZIWIPGjL9n0R6XTdK215i8jbbLkeFpFlRcsThIhME5E1IvKA3Z4/bl+fIiL3iMhD9u/JRcvqRUTaRWSTiPzQ/n+miKy3ZV5lu/EvFSLSKSK32G36ARF5fYuU9UV2+/itiNwoIuNSK+8gN6+t+AMsBv4H2M/+/yD791HAFmA/YCaWC/H2ouX1yD4NuAtrs98BOuTy/MdYLvoXAOuLltMj81uBMfbfXwS+WPbyBtpteV4JjLXlPKpouQJkPRh4nf33/lju748CvgQss68vc8q9TD/AJ4DvAT+0/78JOMv++9+BvytaRh+ZvwV82P57LNBZ9rIGuoDHgA5XOb8/rfIeaSOIvwOWq+pLAKr6rH39VGClqr6kqo8BDwPHFiRjEF8B/i/gtho4Ffi2WtwLdIrIwYVI54Oq3q2q++x/78U6+Q/KXd7HAg+r6qOquhdYiSVv6VDVp1X1Pvvv54EHsD4Ip2J9zLB/LylGQn9E5FDgZOB6+38BjgdusYOUUeaXAW8Gvg6gqntVtZeSl7XNGKBDRMYA44GnSam8R1oH8WrgTfbQ6qci8n/s613Adle4p+xrpUBETgGqqrrFc6vUcnv4INZoB8otd5llC0REZgBzgfXAVFV9GqxOBDioOMl8uRZL2Rmw/3850OtSJspY5q8EngO+YU+NXS8iEyh5WatqFfgn4EmsjmEXsJGUyru0BwYFISL/A7zC59alWPmZjDUd83+Am0TkldQf5QvDNfXMiZD7U1jTNXWP+Vwrjdyq+gM7zKXAPuAG5zGf8GWxpy6zbL6IyETgVuBCVf2ziF8WyoGIvAN4VlU3isgi57JP0LKV+RjgdcAFqrpeRK7DmlIqNfaayKlYU7m9wM3A232CNlTeLddBqOpbgu6JyN8Bt6k18fYrERnAclr1FNYcv8OhwB8yFdRDkNwiMhurcrfYL/6hwH0iciwllttBRM4D3gGcYJc7lEDuEMosWx0iUsHqHG5Q1dvsyztE5GBVfdqecnw2OIbcWQicIiInAeOAl2GNKDpFZIyt1ZaxzJ8CnlLV9fb/t2B1EGUua4C3AI+p6nMAInIb8AZSKu+RNsXUjTX3hoi8Gmuh6Y/A7cBZIrKfiMwEjgB+VZiULlR1q6oepKozVHUGVkN9nao+gyX3+2xrpgXALme4WwZE5G3AJ4FTVHWP61Zpyxv4NXCEbeUxFjgLS97SYc/dfx14QFW/7Lp1O3Ce/fd5wA/yli0IVb1EVQ+12/JZwGpVPQdYA5xuByuVzAD2+7ZdRI60L50A/I4Sl7XNk8ACERlvtxdH7nTKu+hV+JRX9McC3wV+C9wHHO+6dymW9co24O1FyxqSh8cZsmIS4Ku23FuB+UXL55H1Yaz5/M32z7+3QnljWYf93pbv0qLlCZHzjVhTA79xlfFJWHP6PwEesn9PKVrWAPkXMWTF9EosJeFhrGmQ/YqWz0feOcAGu7y7saarS1/WwJXAg/Z37ztY1oOplLdxtWEwGAwGX0baFJPBYDAYUsJ0EAaDwWDwxXQQBoPBYPDFdBAGg8Fg8MV0EAaDwWDwxXQQBkNaiHwKkTsyiPd6RL6ZerwGQwSmgzCMbkTWInJZKs+pfgHVdzYdt8FQEkwHYTAYDAZfTAdhMPghchYiWxD5MyJPI/IfWN49QeRfgDcBn0ZkNyLb7OtXYDk3DAvzTUSu96T1OCLnuv7/ICKP2Gl/B8unkTv8dERuseV6GpGvIbJ/FsVgGN2YDsJg8GcX8F6sQ2PeZP9Y00WqHwV+BnwO1YmoHln3dJwwfoi8Ccu9yt8CU4B7gDNd98cBq7H87bwS6wChQ4HrkmfRYAjHdBAGgx+qP0b1flQHUH0Y+FcsR2hZ8z7gFlTvQXUfqt9muKPDdwCC6mdQ7UO1B/g0cA4i7TnIZxhFtJy7b4MhF0T+CvgMMAvL+Vk7+bh6PhTLYZybx1x/zwSmI9LrCaNY53ZUM5TNMMowIwiDwYvlBrwb6zjS6ai+DMutufvgmwG/Rz34hdkNTHClNYbhp5RVgRmeZ2a6/n4C+D2qnZ6fcVinixkMqWE6CIMBxiAybvDHchs/DuhBtQ+Ro4CPep55BnhVRLx+YTYAJyAyE5H9gM8DFdf9bwOnI3ICImPsxWv3ed4/BCr2nov9ERFEuhB5V6IcGwwxMB2EwQCXA32un+exfOx/CZHdWIvG3/M88xVgPiK9iNwfEK9fmBuwDqG5D+s8iidxTwup/i9wAXA9sBN4G7DKdX8P1lrIUVhnAOzCOqdgTgP5NhhCMedBGAwGg8EXM4IwGAwGgy+mgzAYDAaDL6aDMBgMBoMvpoMwGAwGgy+mgzAYDAaDL6aDMBgMBoMvpoMwGAwGgy+mgzAYDAaDL/8fR9XpAE7AozYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cloud = relevant_fields[\"Cloudiness\"]\n",
    "plt.scatter(x,cloud)\n",
    "\n",
    "# Adding Titles\n",
    "plt.title(\"Latitude vs. Cloudiness on {date}\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.xlabel(\"Latitude\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.ylabel(\"Cloudiness (%)\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.grid()\n",
    "\n",
    "# Saving the image\n",
    "plt.savefig(f'../output_data/Latitude vs Cloudiness on {date}.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latitude vs. Wind Speed Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wind = relevant_fields[\"Wind Speed\"]\n",
    "plt.scatter(x,wind)\n",
    "\n",
    "# Adding Titles\n",
    "plt.title(\"Latitude vs. Windspeed on {date}\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.xlabel(\"Lat\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.ylabel(\"wind(mph)\",fontsize=13, fontweight = 'normal', color= 'red')\n",
    "plt.grid()\n",
    "\n",
    "# Saving the image\n",
    "plt.savefig(f'../output_data/Latitude vs Windspeed on {date}.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# OPTIONAL: Create a function to create Linear Regression plots\n",
    "\n",
    "def linearRegression(x_values,y_values,reg_x,reg_y,y_label):\n",
    "    (slope, intercept, rvalue, pvalue, stderr) = linregress(x_values, y_values)\n",
    "    regression_value = slope * x_values + intercept\n",
    "    line_eq = \"y = \" + str(round(slope,2)) + \"x + \" + str(round(intercept,2))\n",
    "    plt.scatter(x_values,y_values)\n",
    "    plt.plot(x_values, regression_value,\"r-\")\n",
    "    print(f' r squared is: {rvalue}')\n",
    "    print(line_eq)\n",
    "    plt.annotate(line_eq,(reg_x,reg_y),fontsize=20,color=\"red\")\n",
    "    plt.xlabel(\"Latitude\")\n",
    "    plt.ylabel(f'{y_label}')\n",
    "    plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Northern and Southern Hemisphere DataFrames\n",
    "northern_hemisphere_df = city_data.loc[city_data[\"Lat\"]> 0]\n",
    "southern_hemisphere_df = city_data.loc[city_data[\"Lat\"]< 0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Northern Hemisphere - Max Temp vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: -0.6874983597400258\n",
      "y = -0.5x + 89.94\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = northern_hemisphere_df[\"Lat\"]\n",
    "y_values = northern_hemisphere_df[\"Max Temp\"]\n",
    "reg_x = 0\n",
    "reg_y = 40\n",
    "y_label = \"Temperature (F)\"\n",
    "plt.title(f'Northern Hemisphere Latitude vs. Max Temp on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Northern Hemisphere Latitude vs Max Temp on {date}.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Southern Hemisphere - Max Temp vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: 0.7901188858734988\n",
      "y = 0.86x + 81.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = southern_hemisphere_df[\"Lat\"]\n",
    "y_values = southern_hemisphere_df[\"Max Temp\"]\n",
    "reg_x = -30\n",
    "reg_y =40\n",
    "y_label = \"Temperature (F)\"\n",
    "plt.title(f'Southern Hemisphere Latitude vs. Max Temp on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Southern Hemisphere Latitude vs Max Temp on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Northern Hemisphere - Humidity (%) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: 0.019518105493918556\n",
      "y = 0.02x + 66.17\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = northern_hemisphere_df[\"Lat\"]\n",
    "y_values = northern_hemisphere_df[\"Humidity\"]\n",
    "reg_x = 0\n",
    "reg_y = 20\n",
    "y_label = \"Humidity (%)\"\n",
    "plt.title(f'Northern Hemisphere Latitude vs. Humidity on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Northern Hemisphere Latitude vs Humidity on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Southern Hemisphere - Humidity (%) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: -0.012860480922123375\n",
      "y = -0.02x + 75.1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = southern_hemisphere_df[\"Lat\"]\n",
    "y_values = southern_hemisphere_df[\"Humidity\"]\n",
    "reg_x = -40\n",
    "reg_y = 30\n",
    "y_label = \"Humidity (%)\"\n",
    "plt.title(f'Southern Hemisphere Latitude vs. Humidity on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Southern Hemisphere Latitude vs Humidity on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Northern Hemisphere - Cloudiness (%) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: -0.0017388923554546138\n",
      "y = -0.0x + 53.23\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = northern_hemisphere_df[\"Lat\"]\n",
    "y_values = northern_hemisphere_df[\"Cloudiness\"]\n",
    "reg_x = 0\n",
    "reg_y = 20\n",
    "y_label = \"Cloudiness (%)\"\n",
    "plt.title(f'Northern Hemisphere Latitude vs. Cloudiness on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Northern Hemisphere Latitude vs Cloudiness on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Southern Hemisphere - Cloudiness (%) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: 0.12288411716543689\n",
      "y = 0.34x + 53.74\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = southern_hemisphere_df[\"Lat\"]\n",
    "y_values = southern_hemisphere_df[\"Cloudiness\"]\n",
    "reg_x = -40\n",
    "reg_y =20\n",
    "y_label = \"Cloudiness (%)\"\n",
    "plt.title(f'Southern Hemisphere Latitude vs. Cloudiness on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Southern Hemisphere Latitude vs Cloudiness on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Northern Hemisphere - Wind Speed (mph) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: -0.09694834641660335\n",
      "y = -0.03x + 9.43\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = northern_hemisphere_df[\"Lat\"]\n",
    "y_values = northern_hemisphere_df[\"Wind Speed\"]\n",
    "reg_x = 0\n",
    "reg_y = 20\n",
    "y_label = \"Windspeed (mph)\"\n",
    "plt.title(f'Northern Hemisphere Latitude vs. Windspeed on {date}', fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Northern Hemisphere Latitude vs Windspeed on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Southern Hemisphere - Wind Speed (mph) vs. Latitude Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " r squared is: -0.06762928462615947\n",
      "y = -0.02x + 6.74\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = southern_hemisphere_df[\"Lat\"]\n",
    "y_values = southern_hemisphere_df[\"Wind Speed\"]\n",
    "reg_x =-30\n",
    "reg_y =20\n",
    "y_label = \"Windspeed (mph)\"\n",
    "plt.title(f'Southern Hemisphere Latitude vs. Windspeed on {date}',fontsize=13, fontweight = 'bold')\n",
    "linearRegression(x_values,y_values,reg_x,reg_y,y_label)\n",
    "plt.savefig(f'../output_data/Southern Hemisphere Latitude vs Windspeed on {date}.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernel_info": {
   "name": "python3"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "nteract": {
   "version": "0.12.3"
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 },
 "nbformat": 4,
 "nbformat_minor": 2
}