NYC_Data_Loader.ipynb

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    "# Open NYC COVID-19 Analysis \n",
    "\n",
    "This notebook is meant to serve as a starter for anyone interested in diving into the most recent data surrounding the NYC outbreak of COVID-19.\n",
    "\n",
    "Datasets:\n",
    "- Epidemiology Data: https://data.humdata.org/dataset/novel-coronavirus-2019-ncov-cases\n",
    "- Population Data: https://population.un.org/wpp/Download/Standard/Population/"
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    "import pandas as pd\n",
    "import cufflinks as cf\n",
    "import plotly.graph_objs as go\n",
    "import plotly.express as px\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy.integrate import odeint\n",
    "from typing import List\n",
    "from IPython.display import display\n",
    "cf.go_offline()"
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   "source": [
    "## Fetch data from NYTimes\n",
    "\n",
    "https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv"
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     "metadata": {},
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   ],
   "source": [
    "nytimes_data = pd.read_csv(\"https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv\")\n",
    "nytimes_data.set_index(\"date\", inplace=True)\n",
    "nytimes_data[nytimes_data[\"county\"] == \"New York City\"][[\"cases\", \"deaths\"]].iplot()\n",
    "nytimes_data.to_csv(\"output/nytime_data.csv\")"
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   "cell_type": "markdown",
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   "source": [
    "## Fetch data from JHU\n",
    "https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports"
   ]
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   "execution_count": 3,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting data from: 01-22-2020\n",
      "Collecting data from: 01-23-2020\n",
      "Collecting data from: 01-24-2020\n",
      "Collecting data from: 01-25-2020\n",
      "Collecting data from: 01-26-2020\n",
      "Collecting data from: 01-27-2020\n",
      "Collecting data from: 01-28-2020\n",
      "Collecting data from: 01-29-2020\n",
      "Collecting data from: 01-30-2020\n",
      "Collecting data from: 01-31-2020\n",
      "Collecting data from: 02-01-2020\n",
      "Collecting data from: 02-02-2020\n",
      "Collecting data from: 02-03-2020\n",
      "Collecting data from: 02-04-2020\n",
      "Collecting data from: 02-05-2020\n",
      "Collecting data from: 02-06-2020\n",
      "Collecting data from: 02-07-2020\n",
      "Collecting data from: 02-08-2020\n",
      "Collecting data from: 02-09-2020\n",
      "Collecting data from: 02-10-2020\n",
      "Collecting data from: 02-11-2020\n",
      "Collecting data from: 02-12-2020\n",
      "Collecting data from: 02-13-2020\n",
      "Collecting data from: 02-14-2020\n",
      "Collecting data from: 02-15-2020\n",
      "Collecting data from: 02-16-2020\n",
      "Collecting data from: 02-17-2020\n",
      "Collecting data from: 02-18-2020\n",
      "Collecting data from: 02-19-2020\n",
      "Collecting data from: 02-20-2020\n",
      "Collecting data from: 02-21-2020\n",
      "Collecting data from: 02-22-2020\n",
      "Collecting data from: 02-23-2020\n",
      "Collecting data from: 02-24-2020\n",
      "Collecting data from: 02-25-2020\n",
      "Collecting data from: 02-26-2020\n",
      "Collecting data from: 02-27-2020\n",
      "Collecting data from: 02-28-2020\n",
      "Collecting data from: 02-29-2020\n",
      "Collecting data from: 03-01-2020\n",
      "Collecting data from: 03-02-2020\n",
      "Collecting data from: 03-03-2020\n",
      "Collecting data from: 03-04-2020\n",
      "Collecting data from: 03-05-2020\n",
      "Collecting data from: 03-06-2020\n",
      "Collecting data from: 03-07-2020\n",
      "Collecting data from: 03-08-2020\n",
      "Collecting data from: 03-09-2020\n",
      "Collecting data from: 03-10-2020\n",
      "Collecting data from: 03-11-2020\n",
      "Collecting data from: 03-12-2020\n",
      "Collecting data from: 03-13-2020\n",
      "Collecting data from: 03-14-2020\n",
      "Collecting data from: 03-15-2020\n",
      "Collecting data from: 03-16-2020\n",
      "Collecting data from: 03-17-2020\n",
      "Collecting data from: 03-18-2020\n",
      "Collecting data from: 03-19-2020\n",
      "Collecting data from: 03-20-2020\n",
      "Collecting data from: 03-21-2020\n",
      "Collecting data from: 03-22-2020\n",
      "Collecting data from: 03-23-2020\n",
      "Collecting data from: 03-24-2020\n",
      "Collecting data from: 03-25-2020\n",
      "Collecting data from: 03-26-2020\n",
      "Collecting data from: 03-27-2020\n"
     ]
    }
   ],
   "source": [
    "daily_jhu_report_url_base = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/%s.csv\"\n",
    "def gather_daily_jhu_reports(date_rng):\n",
    "    collected = pd.DataFrame()\n",
    "    for date in date_rng:\n",
    "        date_str = date.strftime(\"%m-%d-%Y\")\n",
    "        print(\"Collecting data from: %s\" % date_str)\n",
    "        try:\n",
    "            daily_report = pd.read_csv(daily_jhu_report_url_base % date_str)\n",
    "            daily_report.insert(0, \"Date\", date)\n",
    "            daily_report.rename(columns={\n",
    "                'Country_Region':'Country/Region', \n",
    "                \"Province_State\": \"Province/State\", \n",
    "                \"Last_Update\": \"Last Update\",\n",
    "                \"Lat\": \"Latitude\",\n",
    "                \"Long_\": \"Longitude\"\n",
    "            }, inplace=True)\n",
    "            collected = pd.concat([collected, daily_report], axis=0, ignore_index=True)\n",
    "        except:\n",
    "            print(\"FAILED TO FETCH DATA FOR: %s\" % date_str)\n",
    "    return collected\n",
    "report_data = gather_daily_jhu_reports(pd.date_range(\"1-22-2020\", \"03-27-2020\").to_pydatetime())\n",
    "report_data.to_csv(\"output/daily_jhu_report_data.csv\", index=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "      <th>4327</th>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>New York County, NY</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-09T17:13:16</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.712800</td>\n",
       "      <td>-74.006000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7617</th>\n",
       "      <td>2020-03-22</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>3/22/20 23:45</td>\n",
       "      <td>9654.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13101</th>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-23 23:19:34</td>\n",
       "      <td>12305.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16516</th>\n",
       "      <td>2020-03-24</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-24 23:37:31</td>\n",
       "      <td>14904.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19933</th>\n",
       "      <td>2020-03-25</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-25 23:33:19</td>\n",
       "      <td>17856.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23352</th>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-26 23:48:35</td>\n",
       "      <td>21873.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26773</th>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>New York</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-03-27 22:14:55</td>\n",
       "      <td>25573.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.767273</td>\n",
       "      <td>-73.971526</td>\n",
       "      <td>36061.0</td>\n",
       "      <td>New York City</td>\n",
       "      <td>0.0</td>\n",
       "      <td>New York City, New York, US</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date       Province/State Country/Region          Last Update  \\\n",
       "3642   2020-03-06  New York County, NY             US  2020-03-06T19:13:40   \n",
       "3853   2020-03-07  New York County, NY             US  2020-03-07T18:23:05   \n",
       "4084   2020-03-08  New York County, NY             US  2020-03-08T04:13:22   \n",
       "4327   2020-03-09  New York County, NY             US  2020-03-09T17:13:16   \n",
       "7617   2020-03-22             New York             US        3/22/20 23:45   \n",
       "13101  2020-03-23             New York             US  2020-03-23 23:19:34   \n",
       "16516  2020-03-24             New York             US  2020-03-24 23:37:31   \n",
       "19933  2020-03-25             New York             US  2020-03-25 23:33:19   \n",
       "23352  2020-03-26             New York             US  2020-03-26 23:48:35   \n",
       "26773  2020-03-27             New York             US  2020-03-27 22:14:55   \n",
       "\n",
       "       Confirmed  Deaths  Recovered   Latitude  Longitude     FIPS  \\\n",
       "3642        16.0     0.0        0.0  40.712800 -74.006000      NaN   \n",
       "3853        11.0     0.0        0.0  40.712800 -74.006000      NaN   \n",
       "4084        12.0     0.0        0.0  40.712800 -74.006000      NaN   \n",
       "4327        19.0     0.0        0.0  40.712800 -74.006000      NaN   \n",
       "7617      9654.0    63.0        0.0  40.767273 -73.971526  36061.0   \n",
       "13101    12305.0    99.0        0.0  40.767273 -73.971526  36061.0   \n",
       "16516    14904.0   131.0        0.0  40.767273 -73.971526  36061.0   \n",
       "19933    17856.0   199.0        0.0  40.767273 -73.971526  36061.0   \n",
       "23352    21873.0   281.0        0.0  40.767273 -73.971526  36061.0   \n",
       "26773    25573.0   366.0        0.0  40.767273 -73.971526  36061.0   \n",
       "\n",
       "              Admin2  Active                 Combined_Key  \n",
       "3642             NaN     NaN                          NaN  \n",
       "3853             NaN     NaN                          NaN  \n",
       "4084             NaN     NaN                          NaN  \n",
       "4327             NaN     NaN                          NaN  \n",
       "7617   New York City     0.0  New York City, New York, US  \n",
       "13101  New York City     0.0  New York City, New York, US  \n",
       "16516  New York City     0.0  New York City, New York, US  \n",
       "19933  New York City     0.0  New York City, New York, US  \n",
       "23352  New York City     0.0  New York City, New York, US  \n",
       "26773  New York City     0.0  New York City, New York, US  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jhu_data = pd.read_csv(\"output/daily_jhu_report_data.csv\")\n",
    "# Failed attempt at extracting NYC data from JHU, seems to have a big gap in data?\n",
    "selector = np.logical_or(\n",
    "    jhu_data[\"Combined_Key\"] == \"New York City, New York, US\", \n",
    "    jhu_data[\"Province/State\"] == \"New York City, NY\"\n",
    ")\n",
    "selector = np.logical_or(selector, jhu_data[\"Province/State\"] == \"New York County, NY\")\n",
    "selector = np.logical_or(selector, jhu_data[\"Admin2\"] == \"New York City\")\n",
    "jhu_nyc_data = jhu_data[selector]\n",
    "jhu_nyc_data.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract data from covid.direct\n",
    "https://covid-19.direct/county/NY/New%20York%20City"
   ]
  },
  {
   "cell_type": "code",
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       "      <th>2020-03-03</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-04</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-06</th>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-07</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-08</th>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-09</th>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-10</th>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-11</th>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-12</th>\n",
       "      <td>95.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-13</th>\n",
       "      <td>154.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-14</th>\n",
       "      <td>269.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>329.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>463.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>923.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>460.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>1339.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>416.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>3954.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2615.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>4408.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>454.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-21</th>\n",
       "      <td>8115.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>3707.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>9045.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>930.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-23</th>\n",
       "      <td>12305.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>3260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-24</th>\n",
       "      <td>15597.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3292.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            confirmed  death  newcase\n",
       "fulldate                             \n",
       "2020-02-10        0.0    0.0      0.0\n",
       "2020-02-11        0.0    0.0      0.0\n",
       "2020-02-12        0.0    0.0      0.0\n",
       "2020-02-13        0.0    0.0      0.0\n",
       "2020-02-14        0.0    0.0      0.0\n",
       "2020-02-15        0.0    0.0      0.0\n",
       "2020-02-16        0.0    0.0      0.0\n",
       "2020-02-17        0.0    0.0      0.0\n",
       "2020-02-18        0.0    0.0      0.0\n",
       "2020-02-19        0.0    0.0      0.0\n",
       "2020-02-20        0.0    0.0      0.0\n",
       "2020-02-21        0.0    0.0      0.0\n",
       "2020-02-22        0.0    0.0      0.0\n",
       "2020-02-23        0.0    0.0      0.0\n",
       "2020-02-24        0.0    0.0      0.0\n",
       "2020-02-25        0.0    0.0      0.0\n",
       "2020-02-26        0.0    0.0      0.0\n",
       "2020-02-27        0.0    0.0      0.0\n",
       "2020-02-28        0.0    0.0      0.0\n",
       "2020-02-29        0.0    0.0      0.0\n",
       "2020-03-01        0.0    0.0      0.0\n",
       "2020-03-02        1.0    0.0      1.0\n",
       "2020-03-03        1.0    0.0      0.0\n",
       "2020-03-04        1.0    0.0      0.0\n",
       "2020-03-05        4.0    0.0      3.0\n",
       "2020-03-06       16.0    0.0     12.0\n",
       "2020-03-07       11.0    0.0     -5.0\n",
       "2020-03-08       12.0    0.0      1.0\n",
       "2020-03-09       25.0    0.0     13.0\n",
       "2020-03-10       36.0    0.0     11.0\n",
       "2020-03-11       62.0    0.0     26.0\n",
       "2020-03-12       95.0    0.0     33.0\n",
       "2020-03-13      154.0    0.0     59.0\n",
       "2020-03-14      269.0    1.0    115.0\n",
       "2020-03-15      329.0    5.0     60.0\n",
       "2020-03-16      463.0    7.0    134.0\n",
       "2020-03-17      923.0   10.0    460.0\n",
       "2020-03-18     1339.0   10.0    416.0\n",
       "2020-03-19     3954.0   26.0   2615.0\n",
       "2020-03-20     4408.0   26.0    454.0\n",
       "2020-03-21     8115.0   60.0   3707.0\n",
       "2020-03-22     9045.0   60.0    930.0\n",
       "2020-03-23    12305.0  125.0   3260.0\n",
       "2020-03-24    15597.0  192.0   3292.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_pop = 8623000\n",
    "raw_data = pd.read_json(\"covid_direct_3-25-20.json\")\n",
    "clean_nyc_data = raw_data[[\"confirmed\", \"death\", \"fulldate\", \"newcase\"]]\n",
    "clean_nyc_data.dropna(inplace=True)\n",
    "clean_nyc_data[\"fulldate\"] = pd.to_datetime(clean_nyc_data[\"fulldate\"])\n",
    "clean_nyc_data.set_index(\"fulldate\", inplace=True)\n",
    "clean_nyc_data[[\"confirmed\", \"death\"]].iplot(xTitle=\"Date\", yTitle=\"# of Patients\", title=\"NYC COVID-19 Counts (covid.direct)\")\n",
    "(clean_nyc_data[[\"confirmed\", \"death\"]]*100000/nyc_pop).iplot(xTitle=\"Date\", yTitle=\"# of Patients per 100k People\", title=\"NYC COVID-19 Counts per 100k (JHU)\")\n",
    "clean_nyc_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetch data from csbs.org\n",
    "\n",
    "https://github.com/tomquisel/covid19-data/tree/master/data/csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting data from: 2020-03-14\n",
      "Collecting data from: 2020-03-15\n",
      "Collecting data from: 2020-03-16\n",
      "Collecting data from: 2020-03-17\n",
      "Collecting data from: 2020-03-18\n",
      "Collecting data from: 2020-03-19\n",
      "Collecting data from: 2020-03-20\n",
      "Collecting data from: 2020-03-21\n",
      "Collecting data from: 2020-03-22\n",
      "Collecting data from: 2020-03-23\n",
      "Collecting data from: 2020-03-24\n",
      "Collecting data from: 2020-03-25\n",
      "Collecting data from: 2020-03-26\n",
      "Collecting data from: 2020-03-27\n"
     ]
    }
   ],
   "source": [
    "daily_csbs_report_url_base = \"https://raw.githubusercontent.com/tomquisel/covid19-data/master/data/csv/%s.csv\"\n",
    "def gather_daily_csbs_reports(date_rng):\n",
    "    collected = pd.DataFrame()\n",
    "    for date in date_rng:\n",
    "        date_str = date.strftime(\"%Y-%m-%d\")\n",
    "        print(\"Collecting data from: %s\" % date_str)\n",
    "        try:\n",
    "            daily_report = pd.read_csv(daily_csbs_report_url_base % date_str)\n",
    "            daily_report.insert(0, \"Date\", date)\n",
    "            collected = pd.concat([collected, daily_report], axis=0, ignore_index=True)\n",
    "        except:\n",
    "            print(\"FAILED TO FETCH DATA FOR: %s\" % date_str)\n",
    "    return collected\n",
    "report_data = gather_daily_csbs_reports(pd.date_range(\"03-14-2020\", \"03-27-2020\").to_pydatetime())\n",
    "report_data.to_csv(\"output/daily_csbs_report_data.csv\", index=0)\n"
   ]
  },
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   "cell_type": "code",
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    "csbs_data = pd.read_csv(\"output/daily_csbs_report_data.csv\")\n",
    "nyc_csbs_data = csbs_data[csbs_data[\"County_Name\"] == \"New York\"]\n",
    "nyc_csbs_data[\"Date\"] = pd.to_datetime(nyc_csbs_data[\"Date\"])\n",
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    "nyc_csbs_data[[\"Confirmed\", \"Death\"]].iplot(xTitle=\"Date\", yTitle=\"# of Patients\", title=\"NYC COVID-19 Counts (CSBS)\")"
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