COVID19_Analysis-Updated.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# COVID-19 Analysis & Prediction on World and USA Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This notebook visualizes and predicts the spread of the novel coronavirus, also known as SARS-CoV-2. It is a contagious respiratory virus that first started in Wuhan in December 2019. On 11 February 2020, the disease is officially named COVID-19 by the World Health Organization. \n",
    "<br>\n",
    "\n",
    "In this project, the COVID-19 data by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) is used for analysis and visualizations.\n",
    "\n",
    "<br>Data: <a href='https://github.com/CSSEGISandData/COVID-19'>https://github.com/CSSEGISandData/COVID-19</a>\n",
    "    \n",
    "***Note: This data is updated on a regular basis. For updated visualizations please run the notebook* <br>\n",
    "*Last Updated: 5th of May, 2020***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import Required Libraries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt \n",
    "import matplotlib.colors as mcolors\n",
    "import pandas as pd \n",
    "import scipy as sp\n",
    "import random\n",
    "import math\n",
    "import time\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import RandomizedSearchCV, train_test_split\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "import datetime\n",
    "import operator \n",
    "plt.style.use('fivethirtyeight')\n",
    "%matplotlib inline \n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmed_df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')\n",
    "deaths_df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv')\n",
    "recoveries_df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv')\n",
    "latest_data = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/04-30-2020.csv')\n",
    "us_medical_data = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports_us/04-30-2020.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>Last_Update</th>\n",
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       "      <th>Combined_Key</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45001.0</td>\n",
       "      <td>Abbeville</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:28</td>\n",
       "      <td>34.223334</td>\n",
       "      <td>-82.461707</td>\n",
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       "      <td>31</td>\n",
       "      <td>Abbeville, South Carolina, US</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22001.0</td>\n",
       "      <td>Acadia</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:28</td>\n",
       "      <td>30.295065</td>\n",
       "      <td>-92.414197</td>\n",
       "      <td>130</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>Acadia, Louisiana, US</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51001.0</td>\n",
       "      <td>Accomack</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:28</td>\n",
       "      <td>37.767072</td>\n",
       "      <td>-75.632346</td>\n",
       "      <td>264</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>260</td>\n",
       "      <td>Accomack, Virginia, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16001.0</td>\n",
       "      <td>Ada</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:28</td>\n",
       "      <td>43.452658</td>\n",
       "      <td>-116.241552</td>\n",
       "      <td>671</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>655</td>\n",
       "      <td>Ada, Idaho, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19001.0</td>\n",
       "      <td>Adair</td>\n",
       "      <td>Iowa</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:28</td>\n",
       "      <td>41.330756</td>\n",
       "      <td>-94.471059</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Adair, Iowa, US</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      FIPS     Admin2  Province_State Country_Region          Last_Update  \\\n",
       "0  45001.0  Abbeville  South Carolina             US  2020-05-01 02:32:28   \n",
       "1  22001.0     Acadia       Louisiana             US  2020-05-01 02:32:28   \n",
       "2  51001.0   Accomack        Virginia             US  2020-05-01 02:32:28   \n",
       "3  16001.0        Ada           Idaho             US  2020-05-01 02:32:28   \n",
       "4  19001.0      Adair            Iowa             US  2020-05-01 02:32:28   \n",
       "\n",
       "         Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "0  34.223334  -82.461707         31       0          0      31   \n",
       "1  30.295065  -92.414197        130      10          0     120   \n",
       "2  37.767072  -75.632346        264       4          0     260   \n",
       "3  43.452658 -116.241552        671      16          0     655   \n",
       "4  41.330756  -94.471059          1       0          0       1   \n",
       "\n",
       "                    Combined_Key  \n",
       "0  Abbeville, South Carolina, US  \n",
       "1          Acadia, Louisiana, US  \n",
       "2         Accomack, Virginia, US  \n",
       "3                 Ada, Idaho, US  \n",
       "4                Adair, Iowa, US  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latest_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**View Data Samples**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Long</th>\n",
       "      <th>1/22/20</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>36</td>\n",
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       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
       "0            NaN    Afghanistan  33.0000  65.0000        0        0        0   \n",
       "1            NaN        Albania  41.1533  20.1683        0        0        0   \n",
       "2            NaN        Algeria  28.0339   1.6596        0        0        0   \n",
       "3            NaN        Andorra  42.5063   1.5218        0        0        0   \n",
       "4            NaN         Angola -11.2027  17.8739        0        0        0   \n",
       "\n",
       "   1/25/20  1/26/20  1/27/20  ...  4/26/20  4/27/20  4/28/20  4/29/20  \\\n",
       "0        0        0        0  ...     1531     1703     1828     1939   \n",
       "1        0        0        0  ...      726      736      750      766   \n",
       "2        0        0        0  ...     3382     3517     3649     3848   \n",
       "3        0        0        0  ...      738      743      743      743   \n",
       "4        0        0        0  ...       26       27       27       27   \n",
       "\n",
       "   4/30/20  5/1/20  5/2/20  5/3/20  5/4/20  5/5/20  \n",
       "0     2171    2335    2469    2704    2894    3224  \n",
       "1      773     782     789     795     803     820  \n",
       "2     4006    4154    4295    4474    4648    4838  \n",
       "3      745     745     747     748     750     751  \n",
       "4       27      30      35      35      35      36  \n",
       "\n",
       "[5 rows x 109 columns]"
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     },
     "execution_count": 4,
     "metadata": {},
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    }
   ],
   "source": [
    "confirmed_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <td>465</td>\n",
       "      <td>470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>42.5063</td>\n",
       "      <td>1.5218</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>43</td>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>-11.2027</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2</td>\n",
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       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 109 columns</p>\n",
       "</div>"
      ],
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       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
       "0            NaN    Afghanistan  33.0000  65.0000        0        0        0   \n",
       "1            NaN        Albania  41.1533  20.1683        0        0        0   \n",
       "2            NaN        Algeria  28.0339   1.6596        0        0        0   \n",
       "3            NaN        Andorra  42.5063   1.5218        0        0        0   \n",
       "4            NaN         Angola -11.2027  17.8739        0        0        0   \n",
       "\n",
       "   1/25/20  1/26/20  1/27/20  ...  4/26/20  4/27/20  4/28/20  4/29/20  \\\n",
       "0        0        0        0  ...       50       57       58       60   \n",
       "1        0        0        0  ...       28       28       30       30   \n",
       "2        0        0        0  ...      425      432      437      444   \n",
       "3        0        0        0  ...       40       40       41       42   \n",
       "4        0        0        0  ...        2        2        2        2   \n",
       "\n",
       "   4/30/20  5/1/20  5/2/20  5/3/20  5/4/20  5/5/20  \n",
       "0       64      68      72      85      90      95  \n",
       "1       31      31      31      31      31      31  \n",
       "2      450     453     459     463     465     470  \n",
       "3       42      43      44      45      45      46  \n",
       "4        2       2       2       2       2       2  \n",
       "\n",
       "[5 rows x 109 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deaths_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <td>NaN</td>\n",
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       "      <td>20.1683</td>\n",
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       "      <td>519</td>\n",
       "      <td>531</td>\n",
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       "      <th>2</th>\n",
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       "      <td>1558</td>\n",
       "      <td>1651</td>\n",
       "      <td>1702</td>\n",
       "      <td>1779</td>\n",
       "      <td>1821</td>\n",
       "      <td>1872</td>\n",
       "      <td>1936</td>\n",
       "      <td>1998</td>\n",
       "      <td>2067</td>\n",
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       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>Angola</td>\n",
       "      <td>-11.2027</td>\n",
       "      <td>17.8739</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
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       "</table>\n",
       "<p>5 rows × 109 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
       "0            NaN    Afghanistan  33.0000  65.0000        0        0        0   \n",
       "1            NaN        Albania  41.1533  20.1683        0        0        0   \n",
       "2            NaN        Algeria  28.0339   1.6596        0        0        0   \n",
       "3            NaN        Andorra  42.5063   1.5218        0        0        0   \n",
       "4            NaN         Angola -11.2027  17.8739        0        0        0   \n",
       "\n",
       "   1/25/20  1/26/20  1/27/20  ...  4/26/20  4/27/20  4/28/20  4/29/20  \\\n",
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       "\n",
       "[5 rows x 109 columns]"
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "recoveries_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Province_State</th>\n",
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       "      <th>UID</th>\n",
       "      <th>ISO3</th>\n",
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       "      <th>Hospitalization_Rate</th>\n",
       "    </tr>\n",
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       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>US</td>\n",
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       "      <td>32.3182</td>\n",
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       "      <td>USA</td>\n",
       "      <td>1859.627115</td>\n",
       "      <td>13.797968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:32</td>\n",
       "      <td>61.3707</td>\n",
       "      <td>-152.4044</td>\n",
       "      <td>355</td>\n",
       "      <td>9</td>\n",
       "      <td>252</td>\n",
       "      <td>94.0</td>\n",
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       "      <td>19119.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.535211</td>\n",
       "      <td>84000002</td>\n",
       "      <td>USA</td>\n",
       "      <td>3198.499705</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:32</td>\n",
       "      <td>-14.2710</td>\n",
       "      <td>-170.1320</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>60</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>ASM</td>\n",
       "      <td>5.391708</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:32</td>\n",
       "      <td>33.7298</td>\n",
       "      <td>-111.4312</td>\n",
       "      <td>7655</td>\n",
       "      <td>320</td>\n",
       "      <td>1499</td>\n",
       "      <td>5836.0</td>\n",
       "      <td>4</td>\n",
       "      <td>105.169634</td>\n",
       "      <td>71786.0</td>\n",
       "      <td>1169.0</td>\n",
       "      <td>4.180274</td>\n",
       "      <td>84000004</td>\n",
       "      <td>USA</td>\n",
       "      <td>986.245241</td>\n",
       "      <td>15.271065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-01 02:32:32</td>\n",
       "      <td>34.9697</td>\n",
       "      <td>-92.3731</td>\n",
       "      <td>3281</td>\n",
       "      <td>61</td>\n",
       "      <td>1305</td>\n",
       "      <td>1915.0</td>\n",
       "      <td>5</td>\n",
       "      <td>126.727145</td>\n",
       "      <td>48379.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>1.859189</td>\n",
       "      <td>84000005</td>\n",
       "      <td>USA</td>\n",
       "      <td>1868.617052</td>\n",
       "      <td>12.252362</td>\n",
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      "text/plain": [
       "   Province_State Country_Region          Last_Update      Lat     Long_  \\\n",
       "0         Alabama             US  2020-05-01 02:32:32  32.3182  -86.9023   \n",
       "1          Alaska             US  2020-05-01 02:32:32  61.3707 -152.4044   \n",
       "2  American Samoa             US  2020-05-01 02:32:32 -14.2710 -170.1320   \n",
       "3         Arizona             US  2020-05-01 02:32:32  33.7298 -111.4312   \n",
       "4        Arkansas             US  2020-05-01 02:32:32  34.9697  -92.3731   \n",
       "\n",
       "   Confirmed  Deaths  Recovered  Active  FIPS  Incident_Rate  People_Tested  \\\n",
       "0       7088     272          0  6816.0     1     151.165615        87196.0   \n",
       "1        355       9        252    94.0     2      59.389476        19119.0   \n",
       "2          0       0          0     0.0    60       0.000000            3.0   \n",
       "3       7655     320       1499  5836.0     4     105.169634        71786.0   \n",
       "4       3281      61       1305  1915.0     5     126.727145        48379.0   \n",
       "\n",
       "   People_Hospitalized  Mortality_Rate       UID ISO3  Testing_Rate  \\\n",
       "0                978.0        3.837472  84000001  USA   1859.627115   \n",
       "1                  NaN        2.535211  84000002  USA   3198.499705   \n",
       "2                  NaN             NaN        16  ASM      5.391708   \n",
       "3               1169.0        4.180274  84000004  USA    986.245241   \n",
       "4                402.0        1.859189  84000005  USA   1868.617052   \n",
       "\n",
       "   Hospitalization_Rate  \n",
       "0             13.797968  \n",
       "1                   NaN  \n",
       "2                   NaN  \n",
       "3             15.271065  \n",
       "4             12.252362  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_medical_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = confirmed_df.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Get the dates and number of cases associated with that date**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmed = confirmed_df.loc[:, cols[4]:cols[-1]]\n",
    "deaths = deaths_df.loc[:, cols[4]:cols[-1]]\n",
    "recoveries = recoveries_df.loc[:, cols[4]:cols[-1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = confirmed.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next cell is for storing the data into different lists for making it easy to visualize. Of the different lists, one is for storing mortality rate and another is for storing recovery rate.\n",
    "\n",
    "<br>Mortality rate can be defined as the ratio of number of deaths recorded against the total number of cases recorded and this is calculated using the following formula:<br>\n",
    "\n",
    "$$mortality\\;rate = \\frac{no.\\:of\\:deaths}{no.\\:of\\:confirmed\\:cases}$$\n",
    "\n",
    "<br>Recovery rate can be defined as the ratio of number of recovered patients recorded against the total number of cases recorded and this is calculated using the following formula:<br>\n",
    "\n",
    "$$recovery\\:rate = \\frac{no.\\:of\\:recovered\\:cases}{no.\\:of\\:confirmed\\:cases}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# storing world data\n",
    "world_cases = [] # to store total cases\n",
    "total_deaths = [] # to store total deaths\n",
    "mortality_rate = [] # to store mortality rate\n",
    "recovery_rate = [] # to store recovery rate\n",
    "total_recovered = [] \n",
    "total_active = [] \n",
    "\n",
    "# storing US data\n",
    "us_cases = [] \n",
    "us_deaths = [] \n",
    "us_recoveries = []\n",
    "\n",
    "\n",
    "for i in dates:\n",
    "    # calculate sums\n",
    "    confirmed_sum = confirmed[i].sum()\n",
    "    death_sum = deaths[i].sum()\n",
    "    recovered_sum = recoveries[i].sum()\n",
    "\n",
    "    # confirmed, deaths, recovered, and active\n",
    "    world_cases.append(confirmed_sum)\n",
    "    total_deaths.append(death_sum)\n",
    "    total_recovered.append(recovered_sum)\n",
    "    total_active.append(confirmed_sum-death_sum-recovered_sum)\n",
    "\n",
    "    # calculate rates\n",
    "    mortality_rate.append(death_sum/confirmed_sum)\n",
    "    recovery_rate.append(recovered_sum/confirmed_sum)\n",
    "\n",
    "    # case studies \n",
    "    us_cases.append(confirmed_df[confirmed_df['Country/Region']=='US'][i].sum())    \n",
    "    us_deaths.append(deaths_df[deaths_df['Country/Region']=='US'][i].sum())\n",
    "    us_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='US'][i].sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have all the data of the recorded cases, let us calculate the day-wise change in count of cases, deaths, and recoveries. The function in the following cell helps to calculate this change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_daily_increase(data):\n",
    "    '''\n",
    "    INPUT - a list containing day by day case counts\n",
    "    \n",
    "    OUTPUT - a list containing the day by day increment of count \n",
    "    \n",
    "    Function to count the daily increment in figures\n",
    "    '''\n",
    "    increment_count = [] \n",
    "    for i in range(len(data)):\n",
    "        if i == 0:\n",
    "            increment_count.append(data[0])\n",
    "        else:\n",
    "            increment_count.append(data[i]-data[i-1])\n",
    "    return increment_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# confirmed cases\n",
    "world_daily_increase = get_daily_increase(world_cases)\n",
    "us_daily_increase = get_daily_increase(us_cases)\n",
    "\n",
    "# deaths\n",
    "world_daily_death = get_daily_increase(total_deaths)\n",
    "us_daily_death = get_daily_increase(us_deaths)\n",
    "\n",
    "# recoveries\n",
    "world_daily_recovery = get_daily_increase(total_recovered)\n",
    "us_daily_recovery = get_daily_increase(us_recoveries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# days from the first day in the dataset i.e. Jan 22, 2020 (1/22/2020)\n",
    "days = np.array([i for i in range(len(dates))]).reshape(-1, 1)\n",
    "\n",
    "# reshaping the data\n",
    "world_cases = np.array(world_cases).reshape(-1, 1)\n",
    "total_deaths = np.array(total_deaths).reshape(-1, 1)\n",
    "total_recovered = np.array(total_recovered).reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Days for Future Forecast**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_days_future = 15\n",
    "forecast_future = np.array([i for i in range(len(dates)+num_days_future)]).reshape(-1, 1)\n",
    "adjusted_dates = forecast_future[:-15]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dates in dataset are in int64 format. Convert these into date-time format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = '1/22/2020'\n",
    "start_date = datetime.datetime.strptime(start, '%m/%d/%Y')\n",
    "dates_for_forecast_future = []\n",
    "for i in range(len(forecast_future)):\n",
    "    dates_for_forecast_future.append((start_date + datetime.timedelta(days=i)).strftime('%m/%d/%Y'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_stats(x_data, y_data, title, y_label):\n",
    "    '''\n",
    "    INPUT - data to be plotted on X-axis and Y-axis and a strings for title, and y-axis label\n",
    "    \n",
    "    OUTPUT - function doesn't return anything but prints required plots\n",
    "    '''\n",
    "    plt.plot(x_data, y_data)\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Days Since Jan 22, 2020')\n",
    "    plt.ylabel(y_label)\n",
    "    plt.xticks(size=10)\n",
    "    plt.yticks(size=10)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "adjusted_dates = adjusted_dates.reshape(1, -1)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**World wide COVID-19 data trends**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": [
    "plot_stats(adjusted_dates, world_cases,'Number of COVID-19 Cases Over Time','Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oNMdunbzrfkGDFgBFJA8X/O5T1ccAVHVdYPntwD/8ywpgUmDzicBq/zxe+gagVERyfS0wuH7HvipEJBcYCVQO4FszxhiToIa2CKfNr+LpmNsb8kMw55DRfPVLhYOWl8HqBSrAncBiVb0xkD4+sNo3gff98yeB43wPzilAGfAG8CZQ5nt85uM6yjypqgo8Dxzrt58NPBHY12z//FjgOb++McaYQbSxOczXnt6wSfArzhUePnzMoAY/GLwa4P7AicB7IrLQp12E68U5DdckuQI4A0BVPxCRh4EPcT1Iz1LVMICInA08A+QAd6nqB35/vwIeFJGrgXdwARf/9x4RWYar+R2XzDdqjDFmU20ROOG5ShZubItKH18U4sGvjGG3MfldbJk8gxIAVXUB8a/FPdXNNtcA18RJfyredqr6Ca6XaGx6M/Cd3uTXGGPMwFFVrvs4n1fXtUal7zw6j4e+MoYJxTkpydeg9wI1xhiTXf6yuIEn1kWHm/3G5fPQ4WMYkeRbHbpjQ6EZY4xJmudXNXPRGzVRaZNH5HDvoaNTGvzAAqAxxpgk+aS2nZNfqCQ4s9GIPOGBw8Ywelhqmj2DLAAaY4wZcHVtEb7/7EaqWzujnwC3HzyKHUblpS5jARYAjTHGDKiIKme8WMVH1dHz+V22RwkzJw3urQ7dsQBojDFmQF27sI6nPou+1++Ise2cu8vwFOUoPguAxhhjBsy8imauX1gXlbbr6DwuLWtN6swOfWEB0BhjzIBY1RDmjBejpzUaOyzEfYeNJg36vGzCAqAxxph+a48op75QSWVL5Iu0kLjxPScNT89bzi0AGmOM6bdr/lvLa+ujR3q5ZHoJB2xRkKIc9cwCoDHGmH6Zv7qFm96rj0o7bEJB2nV6iWUB0BhjTJ81tys/fzX6ut+WRSH+ctAoQmnW6SWWBUBjjDF9duN7dXxcG/7itbvZfTRj07HXSwwLgMYYY/pkaXUbv18UfcvDKVOL2T+Nr/sFWQA0xhjTa6rKz16tprWz0yfjCkNcOr0kdZnqJQuAxhhjeu3+ZY28vDa61+f/7jWS0oKhE1aGTk6NMcakhdUN4U2mODpsQgHfnJI+43wmwgKgMcaYhKkq57xcRU1glodhOXDDvqVpN9RZTywAGmOMSdi95Y3MW9USlXbZHiOZPCI9R3vpjgVAY4wxCVlZ387FMU2f+47L58wdi1OUo/6xAGiMMaZHze1ujr/ats6mz6Jc4ZYD0v+G965YADTGGNOttohyyvxKXlkX3evz13uWMKVk6DV9drAAaIwxpksRVc5aULXJBLcHjS/g1KlDs+mzgwVAY4wxcUVU+cWrNTz8cVNU+tTSXP46Y+g2fXYYunVXY4wxSdPUrpz5UiVPrIiu+W01PIe/HTmWMUNgrM+eWAA0xhgTZUNzmO//p5I3Po++5je+KMQTM8cyvmjoBz+wAGiMMSZgdUOYrz/9OZ/UhaPSxxWG+NuRY4fk/X5dyZx3Yowxpl8iqpz+YuUmwW9qaS4PHz6GLw3PrJCRWe/GGGNMn936YQMLYga4Pmh8AXcfMnpIDXKdqEF5RyIySUSeF5HFIvKBiJzj00eLyDwRKfd/R/l0EZGbRWSZiCwSkemBfc3265eLyOxA+h4i8p7f5mbxg9J1dQxjjDGdFle1ceXb0aO8HDy+gEcOH5ORwQ8G7zaIduA8Vd0B2Ac4S0R2BC4AnlXVMuBZ/xrgKKDMP04HbgUXzIDLgb2BvYDLAwHtVr9ux3YzfXpXxzDGGAO0ht0oLy2Bls+R+cKtB44iP2do3+rQnUEJgKq6RlX/65/XAYuBCcDRwFy/2lzgGP/8aOBudV4DSkVkPHAkME9VK1W1CpgHzPTLSlT1VVVV4O6YfcU7hjHGGOD6d+tYVNkWlXbDvqVsWZwZvT27Muj1WhGZDOwOvA6MU9U14IIksLlfbQKwMrBZhU/rLr0iTjrdHMMYY7Lefz9v5aZFdVFp35pSyLFbF6UoR4NnUDvBiMhw4FHgXFWt7WbuqHgLtA/pvVJeXt7bTZKyj6HOysCxcnCsHNK3DFoicOo7wwhrZ11obH6EH2++kfLyjQN+vMEuh7Kysm6XJxQAReQQYIWqLvfNjdcCYeAiVV2b4D7ycMHvPlV9zCevE5HxqrrG73e9T68AJgU2nwis9ukzYtJf8OkT46zf3TE20VNh9aS8vLzf+xjqrAwcKwfHyiG9y+CyN2tY3lQflXbrwZux58RhA36sdCyHRJtAb8EFPIAbgDxcDeu2RDb2PTLvBBar6o2BRU8CHT05ZwNPBNJn+d6g+wA1vvnyGeAIERnlO78cATzjl9WJyD7+WLNi9hXvGMYYk7VeX9fCH9+PDn4nlhVxeBKCX7pKtAl0gqp+JiK5uI4oWwGtdNayerI/cCLwnogs9GkX4WqSD4vIqcBnwHf8sqeArwLLgEbgZABVrRSRq4A3/XpXqmqlf/4jYA5QCDztH3RzDGOMyUpN7cqPF1RFXSeaWJzD1XuNTFmeUiHRAFgrIuOAnYEPVbVeRPJxNcEeqeoC4l+nAzgszvoKnNXFvu4C7oqT/pbPX2z6xnjHMMaYbPXbd2v5uDZ6tJc/HVDKyPzMvN+vK4kGwD/ial35wLk+bX/go2RkyhhjTHK8X9nGze9FN32esn0xM7bMnqbPDgkFQFW9TkT+BoRV9WOfvAo4LWk5M8YYM6DCEeXcV6poD7R9blkU4oo9S1KXqRRK+DYIVV0KICIddeRlScmRMcaYpLjjowbe+jz6hvff7lNKSZY1fXZI6F2LyHQReVVEGoA2/2j3f40xxqS5ivp2rnq7NirtG1sN42tbFaYoR6mXaA1wLvB34BRcr0xjjDFDhKpy3ms11AfaPkvyhOv2Lk1hrlIv0QC4FXCx751pjDFmCHl8RRPPrGyOSrtsj5KMH+uzJ4k2/P4Nd9O5McaYIaSqJcL5r0VPc7T35vmcMrU4RTlKH13WAEXkHjrH0ywA/iYiC4Cooc9UdVbysmeMMaY/Lnmzhs+bI1+8zg/BH/YvJdT1WMxZo7sm0Nhenh8mMyPGGGMG1vzVLdxXHt1t4+e7jmBqaUJjmGS8LgOgqv6647mIbBFv0GsR2SJZGTPGGNN3LWHlvFero9Kmlubys11HpChH6SfRa4BLu0i3WqExxqShWz6oZ1lt+xevBfjDfqUUZPAM772VaADcpMREpASIxFnXGGNMClXUt/Pbd6MnuZ29XRF7jytIUY7SU7e3QYjISlxHmEIR+Sxm8RjggWRlzBhjTN9c/GYNjYF7/kYVCJftkZ3DnXWnp/sAT8DV/p7CTWfUQYF1qrokWRkzxhjTey+sbuaJFdH3/F2+x0hGD8vue/7i6TYAqup8ABEZq6o2AowxxqSx6pYIP3sluuPL9LF5nFhWlKIcpbdEZ4NoFJFpwIHAWALXBFX1siTlzRhjTILCEeWH8ytZXtc5z58Av9unlJyQdXyJJ9HBsE8HXgYOBX4F7AKcB2ybvKwZY4xJ1G/eqWXeqpaotNOmFjN9s/wU5Sj9JdoL9Hxgpqp+E2jyf4/FZoMwxpiUe3x5Ezcsip7k9sub5XH1XiNTlKOhIdEAuLmqvuSfR0QkpKpPA99IUr6MMcYk4M31rfx4QVVU2rjCEHcfOsbu+etBorNBVIjIZFVdgbsp/mgR2QC0Ji1nxhhjuvV+ZRvHztsQdctDXgjuPmQ044us12dPEg2A1wM7ACuAK4FHgHzgp8nJljHGmO58UtvOt/69gZrW6FnqfrtPqd3wnqBEe4HOCTx/WkRGAfmqWt/1VsYYY5JhbWOYo5/ZwPqm6MG4zp82gpO2t2mOEpXoNUBEZIyInCgi56tqK1AiIhOTmDdjjDExVJWzFlSxsj4clX7GDsVcOM0Guu6NRG+DOBhYAvwAuNQnlwG3Jilfxhhj4rinvJFnY253OH7bIv5375GIzfHXK4nWAH8PfE9VZwIdw4u/DuyVlFwZY4zZREV9O5e8ET27+77j8vmjTXDbJ4kGwMmq+qx/3nHFtZXEO9EYY4zpB1XlnFeqqW3r7PRSmCPccsAocm2klz5JNAB+KCJHxqR9BXhvgPNjjDEmjnvjNH1evmcJU0qsHtJXiZbcecA/ROSfuKmR/oK7Cf7opOXMGGMMAI3tEa58uzYqbb9x+Zy+g/X47I+EaoCq+hqwG/ABcBewHNhLVd9MYt6MMcYAdy9t5PPmzlseCnOEPx8wyq779VPCt0Go6ipVvV5Vz1LVa1W1ItFtReQuEVkvIu8H0q4QkVUistA/vhpYdqGILBORJcGmVxGZ6dOWicgFgfQpIvK6iJSLyEMiku/TC/zrZX755ETzbIwx6aAlrPzxvehbrs/YsdiaPgdAjwFQRHYUkYdFZI2ItPi/D4nIjr04zhxgZpz0m1R1mn881XE84DhgJ7/NLSKSIyI5wJ+Bo4AdgeMDebjO76sMqAJO9emnAlWqui1wk1/PGGOGjAeXNbKqsfOev2E58OOdhqcwR5mj2wAoImXAa0AhcBHwP8DFQDHwmohsn8hBVPVFoDLBPB0NPKiqLaq6HFiGu91iL2CZqn7ib8R/EDcmqeCmaXrEbz8XOCawr7n++SPAYWI3yhhjhoj2iHLTe3VRabO3K2bzQhvncyD0VAO8ELhHVb+hqn9V1WdU9S5V/TousFzQw/Y9OVtEFvkm0lE+bQKwMrBOhU/rKn0MUK2q7THpUfvyy2v8+sYYk/YeXd7EisAEt3kh+OkuNtrLQOmpEflg3O0O8dwAPN+PY98KXIW7r/Aqv79TCMw2H6DED9bazfr0sGwT5eXl3WQ3MQOxj6HOysCxcnCsHPpWBmGFa/87jOBX39c2a6dx9ScM1RId7HOhrKys2+U9BcDNcDNAxPMZMLb3WXJUdV3HcxG5HfiHf1kBTAqsOhFY7Z/HS98AlIpIrq/lBdfv2FeFiOQCI+mmKbanwupJeXl5v/cx1FkZOFYOjpVD38tgzpIGljdVf/E6R+CKAycwecTQ7PySjudCj51gVDVujUlVI3RTm+qJiIwPvPwm0NFD9EngON+DcwpuzNE3gDeBMt/jMx/XUeZJn7/ncTPUA8wGngjsa7Z/fizwXFfvxxhj0kV1y6b3/R27deGQDX7pqqfSLBKRF7tYJrjOMT0SkQeAGcBYEakALgdmiMg0XBBdAZwBoKofiMjDwIe4cUfPUtWw38/ZwDNADnCXqn7gD/Er4EERuRp4B7jTp98J3CMiy3A1v+MSya8xxqTSb96ppbKl876/olzh0uklKcxRZuopAJ7aw/I7EjmIqh4fJ/nOOGkd618DXBMn/SngqTjpnxBnYG5VbQa+k0gejTEmHXxQ2cadHzVEpf181xFMHG61v4HWbYmq6tzulhtjjBk4qsoFr1cTDlyomTwih7Ptvr+kSHgkGGOMMcn1j8+aeWlta1Tab/YaybBcu305GSwAGmNMGghHlKtjOr4cNqGAoyYNS1GOMp8FQGOMSQP/90kTS2rav3gdErhmL5vlPZm6DIAi8lrg+eWDkx1jjMk+bRHl2oXRtb/vbl3I1NK8FOUoO3RXA9xORDrq3ucNRmaMMSYb3bu0cZMhzy7Y3W57SLbueoE+ASwVkRW4SXDj3g+oqgclI2PGGJMNmtqV374bXfubtV2x3fQ+CLosYVU9WUQOACYDX6ab+/aMMcb0zR0f1bO6sfOm92E58IvdbMDrwdDTfYALgAUikm/3BBpjzMBa3RDm+oXR0x2dNnU444tsuqPBkFAdW1XvEpFDgBNxUwytAu5V1eeSmTljjMlkF7xeTV1b513vJXnCz3a1m94HS0K3QYjIacBDwFrgMWANcL+I/DCJeTPGmIz1zMpmnvy0OSrt0j1KGDPMan+DJdGrrOcDh6vqux0JIvIQ8ChwezIyZowxmaqhLcIvXquOSps+No9Tti9OUY6yU6I3wo/Bzc4QtAQYPbDZMcaYzHf9wjpW1nfe9hASuGm/UnJCdtP7YEo0AC4AbhSRIgARKQZ+C7ySrIwZY0wmmr+6hZvfr49KO3PHYnYbk5+iHGWvRAPgmcCuQI2IrAOqgd3wc/gZY4zp2brGMD98sTJqJvEJRTlcZDe9p0SivUDXAAeLyERgS2C1qlYkNWfGGJNBwr9K6pUAAB4kSURBVBHl9BerWN/Uec+fAH8+sJTheTYscyr0aqgBH/Qs8BljTC/9blEd89e0RKX9YrcRzNjSZntIFfvZYYwxSfbimhaui7nh/YAt8rlgmo34kkoWAI0xJok2tsIP51cSCVz4GzssxO0Hj7ZenynWYwAUkZCIHCoi1kXJGGN6IRxRLltawLqY6363HTTKhjtLAz0GQFWNAE+oausg5McYYzLGDYvqeKM6OtCdt9sIDp1g1/3SQaJNoC+KyD5JzYkxxmSQBWtbuDbmut/+dt0vrSTaC/RT4GkReQJYCZ23sajqZcnImDHGDFXVLRHOfLFqk+t+dxw8mly77pc2Eg2AhcDj/vnEJOXFGGOGPFXl569WU9EQjkq3637pJ9Eb4U9OdkaMMSYTPPRxE48tb4pK+8nOw+26XxpK+EZ4EdkBOBYYp6pni8j2QIGqLkpa7owxZghZUdfOL2NmediuOMIl022os3SU6HyA3wFexE2GO8snjwBuTFK+jDFmSFFVzl5QFTXB7bAcuHr7Fgpy7LpfOkq0F+iVuPkAzwQ6GrbfxQ2IbYwxWe+x5U0sWBt9t9jVXx7JlCLtYguTaokGwM1xAQ86e4Bq4LkxxmSt+rYIl75ZE5V26JYFnDrVJrhNZ4kGwLeBE2PSjgPeGNjsGGPM0HPDu3Wsbuwc7SUvBNfvMxIRa/pMZ4kGwJ8CV4vIfKBYRJ4BrgJ+lsjGInKXiKwXkfcDaaNFZJ6IlPu/o3y6iMjNIrJMRBaJyPTANrP9+uUiMjuQvoeIvOe3uVn8WdfVMYwxZqB8XNPOnz6InuD2rJ2Gs+3IvBTlyCQqoQCoqh8BU4E/A5cAfwV2UdXyBI8zB5gZk3YB8KyqlgHP+tcARwFl/nE6cCu4YAZcDuwN7AVcHghot/p1O7ab2cMxjDFmQFz4RjVtnZU/xheF+MVuNtrLUJDwbBCq2gi8DLwAvKSq9d1vEbXti0BlTPLRwFz/fC5wTCD9bnVeA0pFZDxwJDBPVStVtQqYB8z0y0pU9VVVVeDumH3FO4YxxvTbvIpm/l0RPcfflXuOtAluh4hEb4P4koi8BKwA/gmsEJEFIrJVP449zs803zHj/OY+fQJuuLUOFT6tu/SKOOndHcMYY/qlLaJc/EZ0x5d9x+Vz7NaFKcqR6a1Eb4Sfi+sIM1NVG0RkOO4a4FxgxgDnKd5VY+1Deq+VlyfaopvcfQx1VgaOlYOTqeXw8OpcltZ0zhInKGeNr2HZsupN1s3UMuitwS6HsrKybpcnGgD3AI5Q1TYAVa0XkV8BG/uRt3UiMl5V1/hmzPU+vQKYFFhvIrDap8+ISX/Bp0+Ms353x4irp8LqSXl5eb/3MdRZGThWDk6mlkN1S4Q73lxL8Lf2D8qK+frumw6VnKll0FvpWA6JNlS/hut4ErQn8Go/jv0k0NGTczbwRCB9lu8Nug9Q45svnwGOEJFRvvPLEcAzflmdiOzje3/OitlXvGMYY0yfXbewlqqWzuA3PFdsuLMhqMsaoIhcGXj5MfCUiPwTdx1uEvBV4P5EDiIiD+Bqb2NFpALXm/Na4GERORX4DPiOX/0pv+9lQCNwMoCqVorIVcCbfr0rVbWjY82PcD1NC4Gn/YNujmGMMX1SXtPG7YsbotJ+tusItrCZHoac7ppAJ8W8fsz/3RxoAf4GJDS8uaoe38Wiw+Ksq8BZXeznLuCuOOlvATvHSd8Y7xjGGNMXEVXOfaWa9kAvg0nDc/jxTsNTlynTZ10GQJsCyRhjot1b3sjLMeN9XrlnCYW5NuLLUNSb6ZCKgG2BqJ86qvrKQGfKGGPSzdrGMJfEjPf5lQkFHDPZbnsYqhIKgCIyC/gT0AoEZ3pU4EtJyJcxxqSVX71eTW1rZ9tnUa5ww76lNt7nEJZoDfB64NuqOi+ZmTHGmHT0z0+beGJFc1TaJdNL2GpEwo1oJg0lehtEK+6eO2OMySqtYeXimKbP6WPzOGMHm+poqEs0AF4K3CgiY5OZGWOMSTdzljSwoi78xescgT/sP4qckDV9DnWJBsClwP/gRlYJ+0dERMI9bWiMMUNVbWuE69+ti0o7aftidhltUx1lgkQbsO/BzbLwENGdYIwxJmP98f16NjR3znVUnCucb1MdZYxEA+AY4DJ/k7oxxmS8dY1h/hw70e3OwxlnI75kjESbQP8KnJjMjBhjTDq5dmEtjYEhX8YOC/GTnW3El0ySaA1wL+BsEbkYWBdcoKoHDXiujDEmhf5T0cxflzRGpZ2/2whG2ES3GSXRAHi7fxhjTEZb1RDmjBerotKmjMjhpO3ttodMk1AAVNW5yc6IMcakWntEOW1+JRtbOju+hAT+dMAo8nPstodMk+hQaKd0tczP0GCMMUPeb96p5dV10YNdX7x7CftvUZCiHJlkSrQJNLYDzBbANsDLxJmeyBhjhponVjRx46LoXp+HblnAz3a1ji+ZKtEm0ENi03ytcIcBz5Exxgyydza0cmbMdb/xRSH+ctAoQjbYdcbqT5emOcCpA5QPY4xJidUNYb7/7Eaawp23POQK3HnwaDYrtHv+Mlmi1wBjA2URcAJQPeA5MsaYQdLYHuH4ZzeypjESlX7jfqXsZ9f9Ml6i1wDbcXP/Ba0Cfjiw2THGmMFz0es1vLuxLSrtrJ2GM2s7u+UhGyQaAKfEvG5Q1Q0DnRljjBks/1rZxJyl0Te7HzlpGFfuWZKiHJnBlmgnmE+TnRFjjBksG5rD/PTl6Cs425bkcsfBNs1RNuk2AIrI82za9BmkqnrYwGbJGGOSR1U59+Vq1jd1XvfLEbjtoFE21FmW6akGeG8X6ROAn+I6wxhjzJDxwLJG/vFZc1TaL3cbwfTN8lOUI5Mq3QZAVb0z+FpExgAX4jq/PARcmbysGWPMwFpR186vXq+JSps+No/zbI6/rJRQfV9ESkTkKmAZMA6Yrqqnq2pFUnNnjDEDpD2i/HB+JXVtnVd1CnOEvxw0ijy77peVug2AIlIoIhcCn+BGfTlAVU9U1Y8HJXfGGDNArn+3jjc/j77l4eq9SigbmZeiHJlU6+ka4HIgB7geeAsYJyLjgiuo6nNJypsxxgyIV9e18Lt366LSZk4axik2xVFW6ykANuN6gf6oi+UKbD2gOTLGmAFU2xrh9BeriAT6s48rDPGnA0oRG+czq/XUCWbyIOXDGGOS4lev17CyPhyVdsuBoxg7zMb5zHYpv+lFRFaIyHsislBE3vJpo0VknoiU+7+jfLqIyM0iskxEFonI9MB+Zvv1y0VkdiB9D7//ZX5b+8lnTJZ4YkUTDyyLHu3lzB2LOWzCsBTlyKSTlAdA7xBVnaaqe/rXFwDPqmoZ8Kx/DXAUUOYfpwO3gguYwOXA3sBewOUdQdOvc3pgu5nJfzvGmFRb2xjmZ69Ej/YytTSXK/YYmaIcmXSTLgEw1tHAXP98LnBMIP1udV4DSkVkPHAkME9VK1W1CpgHzPTLSlT1VVVV4O7AvowxGUpV+cmCKipbOkd7yQu50V6G5VojkHHSIQAq8G8ReVtETvdp41R1DYD/u7lPnwCsDGxb4dO6S6+Ik26MyWB/+qCeeataotIu3r2EXcfYaC+mU6KzQSTT/qq6WkQ2B+aJyEfdrBvvp5v2IT2u8vLybjOaiIHYx1BnZeBYOTiDXQ5vV4e44v0Cgv/+00rCzBy2lvLytYOalw52LjiDXQ5lZWXdLk95AFTV1f7vehH5G+4a3joRGa+qa3wz5nq/egUwKbD5RGC1T58Rk/6CT58YZ/24eiqsnpSXl/d7H0OdlYFj5eAMdjmsaghzyVvrCdPZ9DkyX5hzxJZMHpGarzs7F5x0LIeUNoGKSLGIjOh4DhwBvA88CXT05JwNPOGfPwnM8r1B9wFqfBPpM8ARIjLKd345AnjGL6sTkX18789ZgX0ZYzJIS1iZ/fxGNjRHz+5+20GjUxb8THpL9VkxDvibvzMhF7hfVf8lIm8CD4vIqcBnwHf8+k8BX8WNSdoInAygqpV+rNI3/XpXqmqlf/4jYA5QCDztH8aYDKKqnPNyFW/FDHV2wbQRHDnJbnkw8aU0AKrqJ8BucdI3ApvMM+h7cp7Vxb7uAu6Kk/4WsHO/M2uMSVtX/7eWBz9uiko7cmIB50+zWR5M19KhF6gxxvTZHYvruWFRfVTalBE5/OWg0YRs3AvTDQuAxpgh68kVTfzytej5/cYOC/HoEWMpLbCvN9M9O0OMMUPS48ubOOWFyqj7mopyhYe+MoatS1LdvcEMBRYAjTFDzkMfN3LK/EraA9EvR+CvM0azx2Z2s7tJjAVAY8yQMmdJA2fGTG8kwB/2L7Uen6ZXrJ3AGDMkhCPKFW/X8sf3ozu8hARuPXAU39umKEU5M0OVBUBjTNqrbY1w2vxK/l0RPb5nrsCdM0Zz9OTCFOXMDGUWAI0xae2T2naO/89GltS0R6UX5MCcGaM56ksW/EzfWAA0xqSt+aubmf18JdWt0WPYb1EY4v7DxjDdOryYfrAAaIxJO6rKbYsbuOiNGsIx87fsPjaP+w4dw5bFOanJnMkYFgCNMWmlNaz84rVq7l7auMmyY7cu5I/7j6LQJrU1A8ACoDEmbaxvCjPruUpeW98alS7AZXuUcO4uwxEb3swMEAuAxpi0sHBDKyc8V0lFQzgqfXiucPvBo6yzixlwFgCNMSkVUeVP79dz1X9raYueyo8pI3K4/7Ax7DAqLzWZMxnNAqAxJmUq6ts586UqFqxt3WTZweMLmHPIaEbZoNYmSSwAGmMGXUSVu5c2ctmbNdS26SbLz9ihmGv2GkluyK73meSxAGiMGVSf1Lbz05fj1/pK84U/7D/KRnYxg8ICoDFmUFQ2h/n9e/Xctrie5vCmy2dsWcAtB4yy+/vMoLEAaIxJqtrWCH/5sJ4/vl8ft7mzKFe4bI8STt+h2GZwN4PKAqAxJikq6tv5w/I8nnx9bdzAB3DIlgX8fr9SthphX0Vm8NlZZ4wZMBFVXlrTwpwljfz90ybaNQ/YNPhtURjisj1KOH7bIrux3aSMBUBjTL+tbwpzf3kjc5c2sLwuzgU+rzRf+PmuIzhth2KKcu32BpNaFgCNMX3SHlFeXNPC3KUN/PPTZtrjt3ICMHZYiB/uUMwZOwyn1O7rM2nCAqAxJmHhiPLm5608uryJx5c38XlzpNv1tyqM8PPdR/PdbYpsAGuTdiwAGmO61BZRPqxq4/V1rcxf08KCtS3UtHZT1QPyQ3D05EJmbVfMuLrP2G674kHKrTG9YwHQGANAU7uyuKqNRZVtvFfZxsINrbxf1UZL15f0omw3MpfZ2xdz3DaFjBnm7uUrr09iho3pJwuAxmQRVWV9U4Ty2nY+rmmnvKadpTVtLK1p59O6cJz+mt0ryRO+vlUhJ5QVse+4fOvRaYYUC4DGZICGtghVLRFawtAaUZrDyvLadpbUtLO0up2VDe2sbYywvilMa/eX7Xo0qkA4ZMthfGtKIV+ZMIxhdm3PDFEWAI1JsnBEaYtAmyptYfe8NaK0R6AlorR0pIWV1ojSGobmsFLXFqGuTalrjdDQrjS0KQ3tSm1rhJrWCDWtSmVLhI3NEZrCva27JW7LohC7jcln33H5HDS+gF3H5NmILSYjWAA0aUtVaY24YNDc7mo1HQGio5bTGlaaw+4G7A6tEahvi9DQpjSFlYhfpLh9NbW7/bX4wNTug1FYlXZ1ASusEFEIq0sPK4T9Om0RaFf1r/1zdfvpCG5t7YWEX1lFWyTebeDpSYCtRuSwy+g8dh2dxy5j8pg2Jp8timxsTpOZsiIAishM4A9ADnCHql6b4iyljYi6L/92/8X+RW0l4oJBa7jz9Rdf7j4ItURcjaY1kL56XS6btbmeD2GFutYItW0R6lqVxnYXkJo7/gYCW8e+W8PB46S4cPolfWtIJXnClJJcti3JZZuRuWznH9uOzLWb001WyfgAKCI5wJ+Bw4EK4E0ReVJVPxzI4zy7qpn7l+VRuqEajfnJryiqriagsMnziCpKdI0juI/gMlX94nmE2NqKC0YdQaldAzWbQK2l3ddW2v12AysfPqkZ6J2aHuSHYHRBiMJcIT8k5OcIWxSG2K40j+1Lc9m6JJcti3IYVxiiOM+CnDGQBQEQ2AtYpqqfAIjIg8DRwIAGwEUb23h0bR6sbRjI3ZoMkR+CvJCQG4KCHBekckN8EawKQpCfI+SF5It1R+QLI/NCjMgXinNDFOcJRbnCiDyhND9EaUGI0vwQY4aFGJEn1gPTmF7KhgA4AVgZeF0B7B1vxfLy8j4fZMOGXCC/z9ub+HJFKQhBQQjyQkq+QF4I8gXyQ+qDhWvbDm5TlANFucqwEHxR3xEoECjIcfvMF7dubghyBHLF/Q0BOaKIuP2GfHrHstyQkvvFej7db58rblleYJ8hYEBjU7t/NLo/6/wjXfXn/ypTWBk4g10OZWVl3S7PhgAY76snbsNfT4XVnbFNdfBpbZ+3TyX3hS3uC7ujJiKuhpIXEvJCkBsSCnJ8LUZ8LSZHKPDL832tpr62mtLSUsAV/Ii8ECX5Qkl+iOJcYViuUJjT+bcgRxiW07l9cF95IYZsb8Py8vJ+nU+ZwsrByqBDOpZDNgTACmBS4PVEYPVAH+SQLQtoqm5l8802Azb9xS8I4tMlsFxwtQcBcnwQcjWK6B2EfE3C1Ubki1pJyK/b8bzAN6Pl+ea1nJBbv6NGkhMIbLl+m4FsOisv/5yystIB258xxiRLNgTAN4EyEZkCrAKOA74/0AeZNjaf4vHtlJUNH+hdG2OMSYKMD4Cq2i4iZwPP4C7p3KWqH6Q4W8YYY1Is4wMggKo+BTyV6nwYY4xJH3ZDkDHGmKxkAdAYY0xWsgBojDEmK4nGjtuVZWpqarK7AIwxJguMHDlyk/u9rAZojDEmK1kANMYYk5WyvgnUGGNMdrIaoDHGmKxkAXAAiMhMEVkiIstE5IJU52ewiMgkEXleRBaLyAcico5PHy0i80Sk3P8dleq8JpuI5IjIOyLyD/96ioi87svgIRHJ+KlCRKRURB4RkY/8ObFvlp4LP/P/D++LyAMiMiwbzgcRuUtE1ovI+4G0uJ+/ODf778xFIjI9FXm2ANhPgQl3jwJ2BI4XkR1Tm6tB0w6cp6o7APsAZ/n3fgHwrKqWAc/615nuHGBx4PV1wE2+DKqAU1OSq8H1B+BfqjoV2A1XHll1LojIBOCnwJ6qujNu+MXjyI7zYQ4wMyatq8//KKDMP04Hbh2kPEaxANh/X0y4q6qtQMeEuxlPVdeo6n/98zrcF94E3Puf61ebCxyTmhwODhGZCHwNuMO/FuBQ4BG/SjaUQQlwEHAngKq2qmo1WXYueLlAoYjkAkXAGrLgfFDVF4HKmOSuPv+jgbvVeQ0oFZHxg5PTThYA+y/ehLsTUpSXlBGRycDuwOvAOFVdAy5IApunLmeD4vfA+UDEvx4DVKtqu3+dDefE1sDnwF99U/AdIlJMlp0LqroK+B3wGS7w1QBvk33nQ4euPv+0+N60ANh/CU+4m6lEZDjwKHCuqg7NWYH7SES+DqxX1beDyXFWzfRzIheYDtyqqrsDDWR4c2c8/hrX0cAUYEugGNfcFyvTz4eepMX/iAXA/huUCXfTlYjk4YLffar6mE9e19Gc4f+uT1X+BsH+wP+IyApc8/ehuBphqW8Cg+w4JyqAClV93b9+BBcQs+lcAPgKsFxVP1fVNuAxYD+y73zo0NXnnxbfmxYA+++LCXd9z67jgCdTnKdB4a913QksVtUbA4ueBGb757OBJwY7b4NFVS9U1YmqOhn32T+nqj8AngeO9atldBkAqOpaYKWIbO+TDgM+JIvOBe8zYB8RKfL/Hx3lkFXnQ0BXn/+TwCzfG3QfoKajqXQw2Y3wA0BEvor71d8x4e41Kc7SoBCRA4CXgPfovP51Ee464MPAl3BfCN9R1diL4xlHRGYAv1DVr4vI1rga4WjgHeAEVW1JZf6STUSm4ToC5QOfACfjfmRn1bkgIr8GvofrJf0OcBru+lZGnw8i8gAwAxgLrAMuBx4nzufvfxz8CddrtBE4WVXfGvQ8WwA0xhiTjawJ1BhjTFayAGiMMSYrWQA0xhiTlSwAGmOMyUoWAI0xxmQlC4DGpICIHCgiS1KdD2OymQVAk3FEZIWINIlInYhUi8grInKmiAzq+S4iO4nIv0WkyufjbX/PKKr6kqpu39M+Bjg/J4nIgiTst0BE7hSRT32ZvyMiRwWW7+OnwqkUkc9F5P8SHfhYRDb3UwqtFpEaEXlZRPaOWef7/tgNIvK4iIxOJF9+ncPETd/UKG5qr60GokzM0GAB0GSqb6jqCGAr4FrgV/iZCgbR34F5wDjcIMA/BTJxrNRc3MDGBwMjgUuBh/0A6QCjgNuAybjPow74a4L7Ho4bbWkP3E3kc4F/+vFnEZGdgL8AJ+LKuRG4JZF8ichY3FBll/p9vwU81Js3boY4VbWHPTLqAawAvhKTthdutJqd/euv4UbkqMV9SV4RWPefwE9itl+Em8pFgJtwYxrW+PSd4+RhLG5w39Iu8jgDN3ZmMM+/8PurwX0RDwssPxpY6PP7MTDTp4/EBfY1wCrgaiCni2OeBCwIvL7A76sON1zXN2PXxc1sUAUsB47qxWewCPh2F8umA3X9+HxrgT38898A9weWbQO0AiN6yhduHrpXAsuKgSZgaqrPYXsMzsNqgCYrqOobuAF4D/RJDcAsoBQXDH8kIh1zlc0FTujYVkR2ww1l9RRwBG7eu+38tt8DNsY55EZgGXCviBwjIuMSyOZ3cUNDTQF2xQUhRGQv4G7gl/6YB+ECZkde24FtcdNRHYEbeisRH+PKYyTwa5/XYNPk3sASXDC/HrjTD2HVLf9etwM+6GKVg7pZ1tO+p+GGWlvmk3YC3u1Yrqof4wLgdgnkK3bbBlyZ7NSXvJmhxwKgySarcU1dqOoLqvqeqkZUdRHwAK6pDNyAvWUiUuZfnwg8pG7C4zZgBDAVN5TgYo0ziK+qKnAILlDdAKwRkRcD+4znZlVdrW6szL8D03z6qbgxZuf5/K5S1Y/8F/pRuGmoGlR1Pa52elwihaGq/+ePF1HVh4ByXE25w6eqeruqhnGBdjyumbFLfnaQ+4C5qvpRnOW7Apfhgnmv+El37wF+rao1Pnk4rsYcVIP7jHrKV0LbmsxlAdBkkwn4GatFZG/f6eFzEakBzsTVdFA3SPHDwAm+48zxuC9eVPU53CC+f8ZN9XKb/2LehKpWqOrZqroN7tpXA64m15W1geeNuC9ocNPGfBxn/a2APFxwrRaRatz1sIQmnRWRWSKyMLDtzvgyiM2Pqjb6p8Ppgi+re3A1sLPjLN8WeBo4R1VfSiSPgW0LcT8KXlPV/w0sqgdiy78E16zbU7563NZkNguAJiuIyJdxAbCjF+T9uClZJqnqSOD/ET1J51zgB7jpbBpV9dWOBap6s6rugWsq244EajOquhIXNHfuQ/ZX4q5txUtvAcaqaql/lKhqj014vrfj7biAMEZVS4H3iT9RaY8CU2ONw11ja4tzvP8AV6nqPb3cdwFuVoFVwBkxiz8AdgusuzVQACxNIF+x2xbjyrlPzbNm6LEAaDKaiJSIm7X9QeBeVX3PLxoBVKpqs7/G9v3gdj7gRXDNl/cE9vdlX3vMw9XomoFwnOOOEpFfi8i2IhLyPQ5PAV7rw9u4EzjZd9kPicgEEZnqm17/Ddzg32dIRLYRkYN72B+4Dh8KfO7zezJ9C84dbgV2wPW+bQouEJEJwHPAn1X1/8Vu6G/PWBFvp76cH8F1TpmlqpGYVe4DviHuvspi4ErgMVXtqMV1mS/gb8DOIvJtERmGa5pdFK/p1mQmC4AmU/1dROpwtaSLgRtx89N1+DFwpV/nMlyTZ6y7gV2AewNpJbiaUxXwKa6zy+/ibNuK6/b/H1yvxfdxtbWTevtGfAeek3HX92qA+bjmT3AdefJxvTircMGiu3vs1O/zQ1xwfxU3d9suwMu9zRt8Ubs7A3fNcq2I1PvHD/wqpwFbA5cHltUHdjGpm2PvB3wd17mnOrD9gf59fIBrvr4P1zN3BO6z7TFfqvo58G3gGlzZ7U2C109NZrD5AI3pgojMAk5X1QNSnZeBICI/BQ5V1WN6XHkQici/cdcFF6c6Lya75KY6A8akIxEpwtUkbulp3aHAN/EdDTyf6rzEUtUjUp0Hk52sCdSYGCJyJO7a2DpcZ5khTUR2wfXorMX1YDXGYE2gxhhjspTVAI0xxmQlC4DGGGOykgVAY4wxWckCoDHGmKxkAdAYY0xWsgBojDEmK/1/V/6WdlJOw5cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_stats(adjusted_dates, total_deaths,'Number of COVID-19 Deaths Over Time','Number of Deaths')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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": [
    "plot_stats(adjusted_dates, total_recovered, 'Number of COVID-19 Recoveries Over Time', 'Number of Recoveries')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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": [
    "plot_stats(adjusted_dates, total_active, 'Number of COVID-19 Active Cases Over Time','Number of  Active Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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": [
    "plot_stats(adjusted_dates, world_daily_increase, 'Day-wise plot of Confirmed Cases - Worldwide', 'Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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": [
    "plot_stats(adjusted_dates, world_daily_death, 'Day-wise plot of Deaths - Worldwide','Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bEfd3py//HN/5s4GtOdJnp0k3DMMwhpl0wShQuJGXoyJ0qrod2CwiB7mkM4BXgHuB3sjJS4B73Od7gYtd9OXxQLNzcT4AnCUitS4I5SzgAXesRUSOd9GWF/vKMgzDMIaRdAPGwfroAD4H3CEipcAbwEfxhPbXInIpsAl4n8t7H3AusB5od3lR1UYRuRZY5fJdo6qN7vOngFuBCuB+txmGYRjDTCaha48p1aNcl3wYNaFT1ReAY9IcOiNNXgU+k6GcW4Bb0qQ/Cxw2xGoahmEYOQiuXNDLfu26NAzDMIqHtpj10RmGYRhFTCaLrlD76EzoDMMwjAGRyXIzi84wDMMoCjIHo6R3aY41JnSGYRjGgGjNMI7OXJeGYRhGUWCuS8MwDKOoyTaOrhAxoTMMwzAGRHumqMu4CZ1hGIYxzkmomkVnGIZhFC8dMc24NIwJnWEYhjHuySZmJnSGYRjGuCeT2xJseIFhGIZRBLRmCEQBs+gMwzCMIiDb7Cc2M4phGIYx7sk0oTOY69IwDMMoArL10Znr0jAMwxj3mNAZhmEYRU0212V3AgpR60zoDMMwjLzJtLp4L13xUarIADChMwzDMPImm0UH0FGAgZcmdIZhGPsJrT0J/rixg1ebegZdRrY+OoDOhAy67JFi1IRORDaIyEsi8oKIPOvSJovIgyISdX9rXbqIyA0isl5EVovIUb5yLnH5oyJyiS/9aFf+endu4bW2YRjGGNEdV069dxcXPdzISX/YyUNbOgdVTq6Ak05zXXKaqi5V1WPc/pXAQ6paDzzk9gHOAerddhnwY/CEEbgaOA5YBlzdK44uz2W+85aP/NcxDMMYHzy5vYv1+2KAFzByZ7R9UOVkWl28l/3aosvAecBt7vNtwPm+9NvV42lgkojMBM4GHlTVRlXdCzwILHfHJqjqClVV4HZfWYZhGPs9OzuTBWpX5+A608ajRRcZxWsp8FcRUeAnqvpTYLqqbgNQ1W0iUufyzgI2+85tcGnZ0hvSpKclGo0O6YsM9fxiwdrBw9rB2qCXQm6HN7ZFgNK+/T0t7YOq767mMiDctx9GidNvxXUmRr8d6uvrsx4fTaF7q6pudWL2oIi8miVvOttXB5GellyNko1oNDqk84sFawcPawdrg14KvR0qO1uAfX378UgZ9fVzB1yOvrYL6O7bn1IRZqcv1LIjLgXXDqPmulTVre7vTuD3eH1sO5zbEfd3p8veAMzxnT4b2JojfXaadMMwDANoCQwLyLYKQTaCUZdTy5NlZJAe0RElL6ETkQ+IyBL3+SAReVxEHhaRg/M8v0pEano/A2cBLwP3Ar2Rk5cA97jP9wIXu+jL44Fm5+J8ADhLRGpdEMpZwAPuWIuIHO+iLS/2lWUYhrHf0xYIIskVVJJvOdPKw0n7hRiMkq/r8pvAie7zfwMrgVbgRuD0PM6fDvzeRfxHgDtV9S8isgr4tYhcCmwC3ufy3wecC6wH2oGPAqhqo4hcC6xy+a5R1Ub3+VPArUAFcL/bDMMwDFItuFzj4TIRDEaZVhGw6MZxMMo0Vd0hIuXAScB7gR5gdz4nq+obwJFp0vcAZ6RJV+AzGcq6BbglTfqzwGH51McwDGN/Iyh0PQlvbF1peGAWWHBmlPHgusxX6HaJyCLgcGCVqnaJSCXpg0AMwzCMAiOdq7ItNjChU9UUSzDouuyIF54s5Ct01wLPAXHg/S7tDODFkaiUYRiGMby0pnFVtvQkqC3LPyaxI65J4ezlYaguSRa2cWvRqeqtIvJr97l3OP0zwIUjVTHDMAxj+AhGXULuCZpz5a+MhKiIBISuAC26gQwvqAAuEJEr3H6E0R2HZxiGYQySTK7LgRDMX1UiVAWEbtyuXiAipwDrgA8B/+aS63FzUBqGYRiFTTrrLThUYKBlVEekqCy6HwDvV9XlQMylPYM36NswDMMocNINEE/nzsxGcNHVyohQGRS68WrRAfNV9SH3ubdlujHXpWEYRsETSygd8TQW3QBdl8ExdFUloaISuldE5OxA2tuBl4a5PoZhGMYwk2m6r4EGowTLqYoIFZHggPHCc13ma5F9GfiTiPwZqBCRnwDvxFtOxzAMwyhgMk33NeA+ujTBKJXhIrHo3JpwRwBr8GYleRNYpqqrsp5oGIZhjDnpxtBlS89EexqLrjIwjm48DxjvXX3guwAiUoE3eNwwDMMocDK5Lge6gkFrmmCUimKx6ETkv0Vkmfv8T0Aj0CQi7xzJyhmGYRhDZ9hcl0GLrsiCUT6Et6wOwDeADwPvAv5zJCplGIZhDB8Zg1GGGHVZHRFKw4Jf6+IqdKeJ8BxL8nVdVqpqu4hMARaq6m8BRGTeyFXNMAzDGA6Gy3UZFMZea64yIuzzldU+wMmiR5p8he41EfkQsAh4EEBEpgIdI1UxwzAMY3jI5Loc6OKrQVdnlQtEqQgIXUdcmTTAOo4k+Qrdp4Ef4g0Sv9SlnQ38dSQqZRiGYQwfw+W6TBle4MbQBfvpgtGZY02+qxeson+F8d60O4A7RqJShmEYxvAxXAPGU4NR+i06P+3jtI8OESkFDgKm4ltwVVUfHoF6GYZhGMNES6aoy6FOAebro/PTESus0Mu8hE5ETgL+H1AGTAD2ATXAZmDhiNXOMAzDGDIZB4wPsI8uWE5/MEpyAH9QEMeafIcXXA98V1UnAy3u77XAjSNWM8MwDGNYyByMoqjmL0rtgXKqM7kux6nQLcYLRvHzbeBLw1sdwzAMY7jJ1BcXU+jO06hTVXYGVlWdWOpJSHDx1aauBP/v9XZ++0Y78cTYi16+QteM57IE2CYihwC1QPVALiYiYRF5XkT+5PYXiMgzIhIVkbtdPyAiUub217vj831lXOXS1/lXVBCR5S5tvYhcOZB6GYZhFDPZxsvlOzvKnq5EkuuyKiJMLfckJGjRffqJJj7x+F4ufWwv//J00yBqPLzkK3S/A851n28GHgGew+u3GwhfANb69r8DXK+q9cBe+ocuXArsVdVFeG7T7wA4gb0QOBRYDtzoxDMM/Ag4BzgE+IDLaxiGsd+TKRgF8p/YeUNL8vTG82rCiLg+uiyDw++IthMbY6su39ULvqiqd7rP3wcuAD4BXJbvhURkNvBPwE1uX4DTgd+4LLcB57vP57l93PEzXP7zgLtUtUtV3wTW461yvgxYr6pvqGo3cBe2hJBhGAaQ3aLLd3aUDS2xpP35Nf2xjMGoSz/dCdjWPrZrAGQVOhGpEJHDgumq+gRexGXpAK71A+AKoPenxRSgSVV7W68BmOU+z3Ll4443u/x96YFzMqUbhmHs92R3XQ7OoptfE+77HHRdBtnYOrZCl2t4wRXAJNIHnXwUaMKLvsyKiLwD2Kmqz4nIqb3JabJqjmOZ0tMJdsa7F41GM1c2D4Z6frFg7eBh7WBt0EuhtkNLdwXpX5+wbuNmJjXn7qdbvaUUv2RUdewlGt0FQHtThGx2z6r1W5jeMnJiV19fn/V4LqF7P3BmhmPX4c17mVPogLcC7xKRc4FyvMCWHwCTRCTirLbZwFaXvwGYAzSISASYiLc0UG96L/5zMqWnkKtRshGNRod0frFg7eBh7WBt0EuhtkNPQul+IuPrkEl1B1A/ryJnOY3rd+HNAulxzMKZ1M8pB2BurBU2NGc8t7NqKvX1EzIeH2ly9dHNUtUt6Q649Lzcg6p6larOVtX5eMEkD6vqh/CCWt7rsl0C3OM+3+v2cccfVm+wx73AhS4qcwFQD6wEVgH1Loqz1F3j3nzqZhiGUczk6oPLd3aUoPvR77osz+G63FTgrss2EZmjqpuDB0RkLtA+xOt/FbhLRL4JPI8X0Yn7+wsRWY9nyV0IoKprROTXwCtADPiMqsZdfT4LPACEgVtUdc0Q62YYhjHuyTX7ST6zo3THlS1tyWI1t7pfPoKrjAfZGAhkGW1yCd19eIurXpTm2LXAnwd6QVV9FHjUfX4DL2IymKcTeF+G878FfCtN+n2uvoZhGIYjp0WXRzBKQ1sc/wiBmZWhpACUI6eUJOU/bHIJLzf29O0XukX3dWCFiLyIN5ZuGzATeDdeP9uJWc41DMMwxphcQpfPOLpsQwsAFk0s4RtHT+Anr7Qyv6yHW8+cwZK7t/cd39oepyehlISEn61t5U8bOzl5ZhlfPLyacGjkF2jNKnSqul1EjgK+jDdAewqwB/gjcJ2q7h3xGhqGYRiDJpdrMh+LLmWweHU4Jc/lR9Rw+RE1RKNRZlaGmV4RYoebMiyhsKUtzqbWOF952gtaeWxbF3u7Enxz2cR8v8qgybl6gROzr7vNMAzDGEe05LLo8uijy2XRpWNedYQdHf1Rmhtb4vxlc0dSnv9Z08pRU0t4z8LKnOUNhXynADMMwzCGideaejj3vl2c+Psd3L+pI/cJQyAoZEFPYT5Rl4MRurk1yVbfxtYYL+zpScn32SebeGVvavpwYkJnGIYxyly1spmndnTzSlOMT/5974DXhRsIwT66uvJQ1uPpyDYrSiaC7s0NLTFeTCN07THloof30NQ1cm1gQmcYhjHKPLur36XX3K08v3vkLJqgxTa9MlmA8lm9YGNrskU3Lx+Lrjo5z4MNXRnXqasuCQ14tfOBkFHoRORp3+erR6wGhmEY+xGdMaW5O/ml/sKe7gy5h07QWpxRkfzazyUwTV2JpPqWh2F6RW4baV7A6nupMVnMe4fefXBRJX85dxqzqnJbiYMlmywvFpFyN6bty8B/jFgtDMMw9hN2dKSOKUvn0hsugsEoQYsul+sy2D83rzpCSHIPCQhadEE+c2g1S6eU8O4FFX3L/YwU2WpyD/CaiGwAKkTk8XSZVPXkkaiYYRhGMZJO6F4YJtelqqaIRlDIplcEXZe5hG7g/XMAs6vCCJln1z9+einnzs09x+ZwkFHoVPWjInISMB84lv7puQzDMIxBsr09tU9s/b4Yzd0JJpYOLmzip6+0cu0/9lFXEeKWUydz5JT+lQSCrsuZQYsulr2PLsWiy6N/DqA0LBxQGWZLhrXolk4ZyCpvQyPXgPEngCdEpFRVb8uW1zAMw8hNOosOYPWeHt42s2zA5e3tSvCvq5rpSUBLT5yvrWzmz+dM6zueatEF+uh6NK0l2Mtghhb0MrcmvdBNrwgxs3L0YiHzXWH8FhE5TURuEZEH3N/TR7pyhmEYxUbvbCFBBhuQsr45ht9oe3pHNy2+hKDQTS4PUeJ788cUurJMRbkhy6oFuZibZgYVgKVTS0e8X85PXkInIh8H7ga20z/n5Z0i8okRrJthGEbRsSODK2+wASk7AxZiXGHVzn7RDLouqyJCVWBZnbYs7suhWHSZ3JxvCUwCPdLkW+MrgDNV9cXeBBG5G/gt8LORqJhhGEYxksl1OdiAlN2dqSL15PYuTp/lLYoanLS5piREdUmIpu7+erT2KFPKU8uOJZTNrbnnucxEJovuLVNHr38O8h8wPgVvDTg/64DJw1sdwzCM4iZdMAp4ASn7ugc+O8iuNEL31A6/RZcsdNUlQnVJ0KJLHxvZ0BYn7js0rTxEVUn+fWvzMgwxWDrKFl2+NX4CuE5EKgFEpAr4HvDUSFXMMAyjGMlk0QGsbhy4VbcrTXnP7eqmw4lX0HVZXRJKdV1mGGLwcqA+iybm77aE9BbdrMpwyli+kSZfofskcATQLCI7gCbgSOD/jFTFDMMwio14QtNaYL28sHvgASnpXJfdCW+ase644jcSw+LNbBK0yjLNtRnsNzxi8sAssVlVYYKLjy+dOrrWHOTZR6eq24BTRGQ2cACwVVUbRrRmhmEYRcbuzkTSSt1BBhOQkkk4n9zexaG1ya/46hJBJDUYJdPiq6sDkaDBlcRzEQkJs6rCSSuMj3b/HAxwUmdVbVDVlSZyhmEYA2d7wM0YDLDPNrnz5tYY59y3i0W/2sYPX2rpS9+dwRX65PaulOm/apwll9JHl8F1GRTeIwcxyHvRhGSxPWoMLDpbvcAwDGOU2BEIRDl6WkmS2GULSPneiy2s2NHN7s4EVz+7jzf3eWH/OzNYdKt2dbO3K3VoAaQRujTDC7a3x9nuG/NXHoaDJg2sjw7gYwdX9a2Bd/jkEk4ZxKD4oTLwWhuGYRiDImjRLayJ0NKtrGvuH6u2urGHk2akij5KxVoAACAASURBVIF/bBx4A8znVofZk0HoOuPw921dSWm9AlcVyb0m3eqANXdobQmR4KqtefCOeRX8/V11bGyNcfoB5YQHUcZQyWnRiUhIRE4XkUE7VkWkXERWisiLIrJGRP7DpS8QkWdEJCoid/deQ0TK3P56d3y+r6yrXPo6ETnbl77cpa0XkSsHW1fDMIyRYmdgVpTplWGODLjynt+VGpCSUOXNwMDthrY4jV2JjJMmAzzQ0Jm0X+1cl1Ul2Sd+BngxpX9u8H1rh04u4dy5FZRHRl/kIA+hU9UEcI+qDmXBpC7gdFU9ElgKLBeR44HvANeraj2wF7jU5b8U2Kuqi4DrXT5E5BDgQuBQYDlwo4iERSQM/Ag4BzgE+IDLaxiGUTAEZ0WZXhHi6EBwxqo0Qre1LU5noCtuS1s8awQnwBPbk8vqteiq85gZJbV/bvT71oaLfPvoHnfCNCjUo9XtlrhNgdOB37j024Dz3efz3D7u+BniTYx2HnCXqnap6pvAemCZ29ar6htOkO9yeQ3DMAqGoOtyRmWYZXWpQqeabGG9vi814GRLW5xdAQuxLseCqH1CV5I6sXOQFxuLR+jy7aPbCNwvIvcAm/EtMaSq38inAGd1PQcswrO+XgeaVLXXHm8AZrnPs9x1UNWYiDTjzc4yC3jaV6z/nM2B9OPy/G6GYRijQjAYZXpFmENrSygP02exbWtP0NAWZ45vVpGg2xI8odsdMPOOqyvlmZ3dKS7SXmoyuC6DM6M0dsaTpv6KCCypLX6hqwD+4D7PHsyFVDUOLBWRScDvgSXpsrm/6Ry5miU93c+YjK7raDSavbI5GOr5xYK1g4e1g7VBL7naoWFfOf7XVefOzWxsVQ6uKuOFff2zhfxx9SbOnNYvNM9u7HWE9bOxuZtXNu8A+i3C0q4W3len/Ghj+v607pYmotFd7NsTBvoDXrbvbSUa3dO3/0xTCOif/HJhZYJNb6zP+t38jPbzUF9fn/V4vgPGPzostfHKahKRR4HjgUkiEnFW3Wxgq8vWAMwBGkQkAkwEGn3pvfjPyZSeQq5GyUY0Gh3S+cWCtYOHtYO1QS+52kFVaVyR/FpatmQhE0tDvK2pmRdebu1L3xyeTH39pL79vZv2AMmBJY09QnflZKD/vPoZk7liaQ27Ht/Lr9/oSKnDnLrJ1NdPYGtVJ6ztFzbKKqivn9u3e99LLcC+/noeUE19vf8Vm5lCfB7yHkcnIktE5N9E5H/c/kEickSe505zlhwiUgG8HVgLPAK812W7BLjHfb7X7eOOP6ye0/pe4EIXlbkAqAdWAquAehfFWYoXsHJvvt/NMAwjyCt7ezjrT7s4+rfbuWdDqmgMlOZuTQooqQgLE5wL8dhpyRbYs4GAlN4xc36U1CEA0ypChET40dtqOXt26hCF6r4B48mv/pcbe/jk442c+aed3P5aW8pKCuO5fw7yX4/ufcDjeP1hF7vkGuC6PK8zE3hERFbjidKDqvon4KvA5SKyHq8P7maX/2Zgiku/HLgSQFXXAL/GW0nhL8BnVDXuLMLPAg/gCeivXV7DMIxB8dWnm1i5q5vX98X51N/3pvSHDZTgZM7TK0N9i48eGwhIeXFPD11u2YCEKm+k6aPz8iUL4tRyz/1ZEhJ+ftpkTpieXO4RTrCCfXRN3cpdr3ewalcPn3+yiXs2Jgv7QOe4LDTy7aO7Bm89uhdE5P0u7UW8iZ1zoqqrgbekSX8DL2IymN4JvC9DWd8CvpUm/T7gvnzqYxiGkY22ngRP+pa6aY8pf97YySUHVQ26zODyPDMq+vvkZlaGmV0VpqHNE8PuhCdiy+rK2NaeSBla0EtTd3IowrTyftulMhLirrdP4apnmlm5s5v3LKzoE77gXJdB/PNxCnDYfiJ0dXjCBv1BHkqWgA/DMIzxygt7elImX75nQ8eQhC5o0QWHAiyrK6XhzX5LatWuHpbVlfF6GrdlJqYFypxYGuLGt9Wm5Au6LrOxeGJkQGvQFSL51v454KJA2oV4/WOGYRhFxXNpBm0/tq2LxiG4L1Ndl8lrsh0T6KfrnfIrXf9cJqaV57fOW3WJUBbIWhURFtSknj/e++cgf6H7PPBNEXkMqBKRB4BrgS+NWM0MwzDGiGAwCEBc4c+bOtPkTo+qcs1zzRzz2x1c/lRT0lI1kOy6BFIGjvfWIV+LLiIwsTS/KbZKQsIHF1X27R9fV8oT59Xx2LvqOGdOeVLe8+ZX5FVmIZPv8IJXReRg4B3An/AGZ//JN9uJYRhG0fCPDMvl3LOhg4sW5+e+/NuWLq5b7b0i16cRq+mVyXbG4ZNLKA3Rt1BqQ1ucrW1x3shT6KZV9Ae35MP3T5jEu+ZVEBLhpBmlfZMt33HGZH4Zbecvmzs57YAyzp1bnqOkwifv1QtUtV1EngTexFt41UTOMIyiY3t7vC8oJMijW7vY25WgtixZpLrimhIw8kRg5YAgQYuuLCwsnVLKSp81uWpXd/5Cl6fbspeQCKfNShWxkAgXL67i4jwFfTyQ7/CCuSLyd2AD8Gdgg4g8ISLzRrJyhmEYo006t2UvMYX7NiWH3t/9ejsL79zG8pUV/O6N9r70dFacn3TzUh5Tl9wf9tT2Lt5sya9fMBiIYvSTb8vchheQMklV64BavPFwt2U9yzAMY5wRDEQJGkr+weMdMeVfVjTRFlPa4sJVK5tJuAmZc/WtzahMtcCWTUse5P2LaDsd8f7wz4mlwuyq9Jbb1HITukzk2zJHA19R1TYA57b8qks3DMMoGoIW3acOqU7af2RrF01u5e6ndnTR4pv5f0dHgs2tceIJzelyTCdMZ8wuSwooaQ9MtnzghAizMgjdQF2X+xP5Ct3TpA7sPgZYMbzVMQzDGDviCeX5QCDKxYurWDShP5yhJ9HvvvxbQ2oU5qtNMTa3xfuCStIxs9KbqitITUkoRVj9LJwQyWjRmesyMxlbRkSu6d3wltS5T0TuFJHviMideLOQ5D+dtWEYRoGzrjlGq8+KmlIWYn5NmPPmJwdt/MG5Lx/ekhpwsnZvT4rbcnpFiJBP14KLrfr55CHVfXNgBllQk9miM9dlZrK1zBzfVg78Dm+l8Dr39/f413EwDMMY5wTdlkdPK0FEePeCyqT0h7d08eKebtY1p7on1zb1sD6Qfsascm4+pZYDJ4Q5YXopVx8zIWMdJpWFuCyDVWeuy8GRcXjBcC7NYxiGMR4IBqIc7WYrObQ2wuKJEV5zAhZT+PKKprRlvNoUY0Jpsg2xaGKEdy+oTBHMTHz6kCr+d01rknUJsHBCmJ0d6a09c11mZiDL9FSKyBEicqJ/G8nKGYZhjCZBi653Wi7PqqsI5E0/qHxdUw+vNSVbdP4+vnyYXB7mE0tSx7EdmK2PzlyXGcl3HN3FwHbgYeBu33bXyFXNMAxj9GjrSbA2IFD+vrT3LMhvKqzOODy9M7nvbtHEgQkdwGcPq05aZWB+TZjJZaEsfXTmusxEvj8BvgtcoKpTVXWOb5ub80zDMIxxwKtNsaQVCw6cEGaSbwaUgyaVcGhtfoLV5RvjLXhBJANlSnmYW06dTF1FiJmVIb53/CREhKnloZQJmSeUCOU5lt7Zn8m39buBR0ewHoZhGGPKa4EAkoMnpc7a/54FlazZu29A5c6uDlMxSBE6e045r104k4Rq33AEEeGAynDSjCkWcZmdfFvn34DrRGTqSFbGMAxjrFjfnNzntjiNuzGT+/K4uszDBQbaP5eO4Ji7oPtyWoW5LbORr9C9BrwL2CEicbclRGRoa8sbhmEUCEGLLl2/2oIJEZamWZ/t04dmHuQ9HEIXJCh0ZtFlJ9878AvgdrwAlI4ceQ3DMMYdwbFviyemX3D0ggUVvLCn3/o7YnIJJ88sS5sX4MBBBKLkIhh5aRGX2cn3DkwBvqGqmjOnYRjGOCOe0JTZTOozCNSFiyq54eVWdnV6c3x9YkkVtWUhppYm2N2dKjgjYdEFVyNfmmWmFSN/ofs5cBGeVWcYhlFUbGpNnptyWnkoKeLSz7SKMH88Zyq/eaODQ2sjnO9W4D6wUtmdZoWfwQwtyMVZs8u5bEkV923q5K0zSvnnA8f/KuAjSb727jLgJhFZJyKP+7d8ThaROSLyiIisFZE1IvIFlz5ZRB4Ukaj7W+vSRURuEJH1IrJaRI7ylXWJyx8VkUt86UeLyEvunBtkIEvtGoZR9Khq3xI6QYL9c5msuV4OnlTC14+awLsXVPat6r2wMnUW55IQzMkw7m0ohEPCd4+fxMv/PIOfnDyZyoi5LrOR70+Nn7ltsMSAL6vqP0SkBnhORB4EPgI8pKrfFpErgSvxlv85B6h323HAj4HjRGQycDXeygnqyrlXVfe6PJfhrbRwH7AcuH8IdTYMo0j4y+YO/mVFMwA/OHESb5+dPE3va4GIy1xCl450QrewJkI4ZL+5x5q87qaqDmmBVVXdBmxzn1tEZC0wCzgPONVluw1vrN5XXfrtrk/waRGZJCIzXd4HVbURwInlchF5FJigqitc+u3A+ZjQGcZ+TyyhfP7JJnZ2eEJ0+YomXnzvdPxOn2AgymCE7sDKVGtxJAJRjIGT110QkY9lOqaqtwzkgiIyH3gL8Aww3YkgqrpNROpctlnAZt9pDS4tW3pDmnTDMPZzXm7s6RM58PrjtrYnkkL0U12X6SMus7EgjUU3EoEoxsDJ9y5cFNifARwIPAnkLXQiUg38Fviiqu7L0o2W7oAOIj0t0Wg0R02zM9TziwVrBw9rh8Jugz9vjQDJUYkPrdnACbX9wrSusQL/a6R0bwPRzoEFmVdHYEZZgu1d/f1lNZ17iEZ3Dqre45nRfh7q6+uzHs/XdXlaMM1ZeUvyrYiIlOCJ3B2q+juXvENEZjprbibQ+0Q04K2D18tsYKtLPzWQ/qhLn50mf1pyNUo2otHokM4vFqwdPKwdCr8NNmxtJDj8d19lHfX1NQDs7UrQ+MS2vmOlITj5sAMH3LcWjUZZNqOSezf2rzr+9iWzqd/PQv8L8XkYSqjOrcCl+WR0EZA3A2tV9TrfoXuB3sjJS4B7fOkXu+jL44Fm5+J8ADhLRGpdhOZZwAPuWIuIHO+udbGvLMMw9mOe2Zka8/+qb5WCaCAQ5cAJgw8gufyIGurcunD/fGBF2llUjNEn3z66oCBWAh8G0q88mMpb8dyfL4nICy7ta8C3gV+LyKXAJuB97th9wLnAeqAd+CiAqjaKyLXAKpfvmt7AFOBTeOJbgReEYoEohrGfs709zqbW1JkK1zX1i1s0j6m/8mXp1FJeeO90WrqV6ZU2/2ShkO8djZHa57UF+EQ+J6vqE6TvRwM4I01+BT6ToaxbSNMvqKrPAoflUx/DMPYPVqax5gDWNcVQVUQkRejSTeY8ECojISotBqWgyPd2LAjst6nq7uGujGEYxnCSSej29Shb2uLMro6kCN1gIi6NwibfYJSNI10RwzCModKTUJq6EkwpDxESYdWu9EIHXj9deqEzc6zYyHpHReQRsoTp43kZU1yPhmEYo01Da4wL/rqHdc0xTjugjJ+eXMvz6SafdLza1MMpB5TxZsvw9dEZhUmuO/rLDOmzgM/jBaUYhmGMOV9e0cQ6Z509srWLC/66J2mi5iCvNsXY2BKjx5dnekWIiaU2b2SxkVXoVPVm/76ITAGuwgtCuRu4ZuSqZhiGkR+Pbu3kgYaupLTVjcnDBqaVh/qW1gHPohvoZM7G+CSvny4iMsGF9a8HpgNHqeplqtqQ41TDMIwRJZ5Q/nVlc858H1yU7IBa1xTj4S3J4mhCV5xkFToRqRCRq4A38GZBOUlVL1LV10eldoZhGEBbT4JHt3aysyN1TNyd69tZszeW5qxkzl9QwYSS/lFOLT3K7a+1JeU5ZWZ58DSjCMj18+VNIAx8F3gWmC4i0/0ZVPXhEaqbYRgGTV0JTvzDDra2J5hcFuLP50xlSa03BKC1J8G3/rEvKf+syjBb2pMFsSIsHDa5hIMnlbDSF4np78Orqwhx7lwTumIkl9B14kVdfirDcQUWDmuNDMMwfPxqfTtb2z1FauxK8C9PN/Gn5VMREX74UivbfSsTlIXhvnOn8tkn9vL37f2C9papJZSEhINrI0lC5+fi+ipKw7Z2XDGSKxhl/ijVwzAMIy3P70kWpie3d/NgQxdza8L84KWWpGOfObSaeTURfvy2Ws740y52OBH8+MFVgLcyeDpCApccZEHkxYr1vBqGUdC8vKcnJe3fn2umKiJJQwOmlYf44uHeigSzqyM8+q467tvUweKJJbxtZhkAB09K/8o7e3Y5c6rtdVis2J01DKNg6YxpyhAAgFfSBJ989/iJTPCNgZtZGebSg6uT8mSy6C51Fp9RnNjISMMwCpZXm3qI5bH+6blzyzl/fkXOfDMrQ0woTe6Hm18T5vRZZYOtojEOMKEzDKNgeakx1W0ZZEKp8P0TJuEtRZkdEeGQgFX3sYOqCOVxrjF+MaEzDKNgCQpd0BoD+OaxE5k5gLXfPry4P+hkTnWYixab27LYsT46wzAKlqDQffPYiVz9bDN7uzx/5qkHlHFR/cCiJT+0qJJp5WFea+7hXfMqqC2z3/vFjgmdYRgFSUKVlwNCd8rMMv5w9lT+78utTC0P8bW3TMjLZelHRDh7Tjlnz7HB4fsLJnSGYRQkm1rjtPT0R6JMKBXmVoeZJxFuOmXyGNbMGG+YzW4YRkGyOjB+7vDJJQO23gwDTOgMwyhQgv1zh9WmHwNnGLkwoTMMoyAJ9s8dPsWEzhgcJnSGYRQkQYvu8MkmdMbgGBWhE5FbRGSniLzsS5ssIg+KSNT9rXXpIiI3iMh6EVktIkf5zrnE5Y+KyCW+9KNF5CV3zg1ijnzDGNfs7UrQ0Na/1E5EMk/fZRi5GC2L7lZgeSDtSuAhVa0HHnL7AOcA9W67DPgxeMIIXA0cBywDru4VR5fnMt95wWsZhjGOCFpzB02KUGZL6BiDZFSETlUfBxoDyecBt7nPtwHn+9JvV4+ngUkiMhM4G3hQVRtVdS/wILDcHZugqitUVYHbfWUZhjEGvNrUwxef3Mt/Pb+PVv8SA3libktjOBnLcXTTVXUbgKpuE5E6lz4L2OzL1+DSsqU3pEnPSDQaHVLFh3p+sWDt4GHtkNwGMYX3PVdOQ6f3Ozq6vZGrFuWes7KXzjjc+UoZ0D+t14xEM9HonmGr70hhz4LHaLdDfX191uOFOGA8nX9CB5GekVyNko1oNDqk84sFawcPa4fUNnhxTzcNnbv69u/fVcqNZ86jPJLb9diTUD780B7WtHYlpZ+95ADqpxf2CgP2LHgUYjuMpdDtEJGZzpqbCex06Q3AHF++2cBWl35qIP1Rlz47TX7DMMaAza3xpP2OuLJiRxenzeqfcqulJ8G9Gzq4a307z+7qoapEOGF6KR0x5W9bkkXupBmlHF9XOip1N4qTsRxecC/QGzl5CXCPL/1iF315PNDsXJwPAGeJSK0LQjkLeMAdaxGR41205cW+sgzDGGX80ZK99IpXT0L56tNNHHTXdj7zRBN/395NR1zZ3Zngjxs7U0TukNoIvzx9is2IYgyJ0Rpe8CtgBXCQiDSIyKXAt4EzRSQKnOn2Ae4D3gDWAz8DPg2gqo3AtcAqt13j0gA+BdzkznkduH80vpdhGKk0tKYK3UNbOgH43zWt/GRtG+15rKa6oCbM786ayiRbXcAYIqPiulTVD2Q4dEaavAp8JkM5twC3pEl/FjhsKHU0DGN42NwWS0l7tSnGhpYYP1nbllcZMypC/P7sqcwYwDpzhpGJQgxGMQxjHJPOogP4yoqmJLdmeRg+fWg171tYSVdceXJHN8/t6qYqInxlaQ1zq+31ZAwP9iQZhjGspOujA3gw0P/2/gMr+cbRE/v2l061gBNjZDDnt2EYw0ZXXNnRkd8A8Y8vqR7h2hiGhwmdYRiDpqE1xvPNIeIJL7hkSwZrLsgJ00ttthNj1DChMwxjUDy8pZOjf7eDy14q55/u301CNWUMXSYuW1I1wrUzjH5M6AzDGDDtsQSfe6KJLqdrT+/s5vFtXTQEIi6r0syGMqMixDvmVYxGNQ0DMKEzDGMQ3LimjS3tydbb87t7UgJR3r2gImWOvo8eXEVJyAaAG6OHCZ1hGANiR3uc61e3pKS/1NiT4rpcOqWEk2b0R1NWhIWPLDa3pTG6mNAZhjEgvvX8PtrSzGyyek+qRTe7Osz1J07ibTNKObQ2ws2n1jLdBoEbo4yNozMMI29eauzhF6+1pz32+r4YbbHkoQWzqyIsmljCH8+ZNhrVM4y0mNAZ45o9nXFuftWbVupjB1cxtdyshZFCVfn6yuaMa2ApsK09KHR2P4yxx4TOGNdc9vheHnIzbjy9o5vfnT11jGtUvNy7sZPHtiXPbjK7KpxxJpQJJWITMhsFgT2FxrjltaaePpEDeHhrF+ub81/JOkhDa4yvrGhiyd3bOP2PO/nB6hY2tKROUDye2NEe57LHGzntjzu5M5rfhMrpaOtJ8K8rm5PSTj2gjI8dnDmwxKw5o1Awi84Yt/xhQ0dK2n2bOvn84QObcWNTa4wfvtTKL15ro9t53ra1J/jH7h7+/bl9LJkUYeGECPNqwsyqilBTIlRGhOoSoaxTWKTat17a7s44f9/WRUdMObaulEUTImO2ltrm1hjn/WU3b7R4Ftenn2iiNCy8d2HlgMu6fnVrkuUWEfjOcROzDhCfXW1CZxQGJnTGuCWz0NWkpL/a1MNNa9sQ4JDaEg6bXMKm1hh3RNt5ZGtXxn4ngLVNMdY2ZbLsKpj5ynaOqyujoS3Gc7t6ksqaXxPmrNnlfGBRJW8JTFocSyidcaW6JD/HSkKVx7d10diZ4Ny5FZSnGYzdy+vNMc57YHeKW/FzTzSxeGKEwyaXcPtr7dz8ahvlYXjrjDJOnlnGcXWlVAXq83pzjBteTh5O8KlDqzloUgmTSjPXfXaVvV6MwsCeRGNcEm3u4ZW9qeLzzM5udnbEqavotybujLZx+YomOvObnWrAbGtPpBVdgA0tcX66to2frm3j7DnlXLW0ht2dCW5/rY37N3fSk4Cp5SEOnBBh8cQI711Ywckzy1KswNeaevjiU008taMbgKOmtnLv8qkpIhlPKH9t6OSLTzWlnVy5I6586OFG5lSF+8oCWLWrhx+81EpFWPjsYdV8dWkNkZDQGVP+5emmPksXvJlNrljq/ZiYXhlmSomypydVdOeYRWcUCCZ0RkGzsyPOY1u7eGxbFzs74rxzXgUfrq/kng2dafMr8JfNnVy8uIquuHLlM038fF36cPh0zK0Oc/kRNfQklD9s6OCp7d1Zrb2B8MDmTh7YnFrv3Z0Jdnd288zObn4RbWfZtFKuWFrD4kkRtrfHeWhLF9evbkkSm3/s7uHjj+3ljtMnEw4Jezrj/HxdO7eua8sYHNLL5tZ4RpdjR1z53ost/H1bF1e+pYavr9rHy43J/Z7XHjuRGp/ALq5OsGJvqqhZH51RKJjQGcNOa0+C//tyK394s4NZVWEuXFTJO+dVUOFcbarK5rY4K3d6L/eXG3vY152gLaa09ShxpyyKsrcrWWb+2tBFW0wzWlAAf97YwfnzK7jgr7tZtSu/4JSlU0q49OAqLlxU2Tc91SeWVNPYGWf9vhibWuNsbImzvSNOe0xp71F2dMR5blcXXYlka+bIKSXUloV4antXkjjly8pd3bz3wT058/1lcydfW9nMAVVhvv9iC/t60kvyBxdVUhGRvmEY+fD0zm7OfyC1DidOL+W9C5PnqTyoKoPQmUVnFAgmdMawkVDlV+vbufa5fWx3brN1zTEe3trFxNImjp1Wytb2OA2t8Ywv5Xz42spmEllOf3RbF5c+2pgicuVhb6zdlrY4r+yNEQJOn1XGh+qrOCzDkjGTy8MsKw+zrC79tV5ZF6W1di6r9/RQXRLilAPKmOlm/mjrSfDw1i5ueKklo+CGhKzfJRc/WZtdvD55SBX/uWwicYVX9vawwueuBDhzVhkXLKzk6R1d/HlTJ7s6Myvz3OowP35bbYpbdXFV+nPMojMKBRM6Y1h4YXc3X1rRxPO707/Qm7uVvwVWmB4sQWF424xSz+Jy7riueOpq1gtqwtx++pRhXwOtJATL6spYVleWcqyqJMQ751XwjrnlPNjQxX8+v48X9vRQGRHOn1/BxYsrOWZaKQ1tcdY1xbjl1VYeaMjcRtPKQ1z1lgl878V9KQOz/ZSH4YKFlXz84Kq+AJiQwG2nTebdD+xmzd4Y08pD/Oeyibx3YQUiwoWLKvn60XE++fjetPfpggUVXHfiJCamCT5ZXJ1al7DQJ/iGMdaY0O3H9CS89cN2dcRp7ErQ2JWgPab0JLxjHTGlqTvB3q4Ezd1ehGBX3PtbFS/jzM4Wjq8r5fcbOvjp2rYhWSaZCInnVjzcRQmmu8T5Cyp4fV+MG9ekt26OnFLCPWdPHbPByyLCWXPKOXN2GVvbE0wuC/W5cQHm10SYXxPh7DnlvLC7m++vbuHJ7d2UhGBGZZgZlWGOmlrCZUuqqS0LcdTUEs69fzftgfkmJ5YKXzq8ho8cVJX2u9ZVhHn0XXW8uS/G/JoIpeFky2xqeZhfnzmFG15q5dp/7COuUB0RvnfCJC48sCLjMIk55UpVRJLmv5xZGSZiKxQYBUJRCZ2ILAd+CISBm1T122NcpRFDVWnqVpq6EpSGhYowlISFlm6lscsTp7ZYgo6Y0h5TmruVPZ1xdnUm2N4eZ31zjI2t8b7+sIET5oln92U8WhaGTx1STU8CfrW+ncau5F/9FWFh6dQSjqsrZVldKbOqwlRHQlSVCP5AwspIvyjMqY7wzX8kX1OAd86rINqcXujqKkLcecaUgpihQ0SYlcOdt3RqKb84fUrOPDedUsulj+6lI65EBD6+pIorjqxhco4p0EpCwuJJma3akAhfPKKGfz6wkud2d3PSjDJqc7Rd3vlxVgAADX5JREFUSOCwySU8s7PfLWoRl0YhUTRCJyJh4EfAmUADsEpE7lXVV4bzOv+zoYTObY2UhYWSkKDqBU2o9tYDBEFREgpxpc8K6f192x1XOpx1BFAaEkrDQkS8TAKowr4eZV93glbXnxUJQUSE5u4EDW3xtDPIFwLnzS/nmmMmMq/Ge7y+cfQEVuzooqlLmVUVZm51mGkVIUIDHEj95SOqeamxOyni8sQZpdRVhJlcFmJKWYg9PkEtDcEvT5+cU1zGI+fOrWDle0p4blcPR08rYU718P4rH1AV5oCq/BdHPTwgdNY/ZxQSRSN0wDJgvaq+ASAidwHnAcMqdE80hnm9PXPE3/7MvOow3z9hEm+fXZ6UXhYWTj2gPMNZ+SMi/OikWnZ17OGpHd1URoRvHDUBgEhIeM/CCn7mC874wYmT0vadFQtzqiPDLnCD5cTppdzki+o8Ysrw9oUaxlAQ1cK0CgaKiLwXWK6qH3f7FwHHqepnAZqbm/u+aDQaHfR1LniunE0dY+8GGy6mlSaoK1UmlsDEiFIZVkpC3hRPpSGoCSsTSpSaMFSElbKQ56p6rS3EP5pDPN8cpkfhPTNiXDqnh9FYPCCusL5NmF6m+L1w+2Lw3ddLebM9xD/P7OG8GSM0QtxIIaZw9bpSHtoT5uiJCf7r4C4mFIYGG/sB9fX1fZ8nTpyY4ioqpkcxnR8srYr7G2WgxFZtHvS5w01FWJhaESLmAke6E1BTItSWhagtCzGhRKhwfVzVES/v1PIQU8vDLKgJs3BCJO/pp4JEo1G+dvLg23GoHJwh/e4lo1oNotHokJ6nYiAajbJkcT2/XjzWNRlb7FnwKMR2KCahawDm+PZnA1uH+yKXL+yhauoMuuNKd0IRvA58wVNV9WlrWIRQb5+br4zSkFAeFsrCXp9eV9yLcowlkvvzqkuECaUhakq8cmIuGrIiIsypClNbFhqzCYMNwzDGC8UkdKuAehFZAGwBLgQ+ONwXOWVKnPpFA5/93TAMwxgbikboVDUmIp8FHsAbXnCLqq4Z42oZhmEYY0zRCB2Aqt4H3DfW9TAMwzAKh+IJHzQMwzCMNJjQGYZhGEWNCZ1hGIZR1BTNgPFc+AeMG4ZhGMVJugHjZtEZhmEYRY0JnWEYhlHU7DeuS8MwDGP/xCw6wzAMo6gxoRsAIrJcRNaJyHoRuXKs6zMaiMgcEXlERNaKyBoR+YJLnywiD4pI1P2tHeu6jgYiEhaR50XkT25/gYg849rhbhEpHes6jjQiMklEfiMir7rn4oT97XkQkS+5/4eXReRXIlK+PzwLInKLiOwUkZd9aWnvvXjc4N6Xq0XkqLGqtwldnvgWdj0HOAT4gIgcMra1GhViwJdVdQlwPPAZ972vBB5S1XrgIbe/P/AFYK1v/zvA9a4d9gKXjkmtRpcfAn9R1YOBI/HaY795HkRkFvB54BhVPQxvysEL2T+ehVuB5YG0TPf+HKDebZcBPx6lOqZgQpc/fQu7qmo30Luwa1GjqttU9R/ucwveS20W3ne/zWW7DTh/bGo4eojIbOCfgJvcvgCnA79xWYq+HURkAnAycDOAqnarahP73/MQASpEJAJUAtvYD54FVX0caAwkZ7r35wG3q8fTwCQRmTk6NU3GhC5/ZgH+xegaXNp+g4jMB94CPANMV9Vt4IkhUDd2NRs1fgBcASTc/hSgSVVjbn9/eCYWAruAnzsX7k0iUsV+9Dyo6hbgv4FNeALXDDzH/vcs9JLp3hfMO9OELn/+f3tnHmtXVcXh74dAkY5gI9GKDIVS0zIIgRJkEkgVBcFUBaEUqkTQIPoHximARVFjBBMig5DGlFKQQcQ2aFJIURk1ELDMSqXI2DbQvpaWSfrzj7UvHq/39d5X6bu8c9eXnLx7zx7OOvuce9bba6+zVseJXeuIpBHAr4Gv217dbXkGG0lHActt31fd3aJq3e+JzYG9gUttfxhYS43NlK0oa1DHADsB7weGE2a6Zup+L7TjHfP7SEXXOYOS2PWdiKQtCCU3z/aNZfeyhhmi/F3eLfkGiY8An5K0lDBbH0bM8MYU8xX0xj3xDPCM7T+X7zcQiq+X7ocjgCdtr7D9BnAjcAC9dy806O/av2OemanoOuetxK7Fm+p4YH6XZdrklHWo2cCjti+sFM0HTi6fTwZ+O9iyDSa2v237A7Z3JK79ItsnArcBnynVemEcXgCelrRb2XU48Ai9dT/8E9hf0tbl99EYg566Fyr0d+3nAzOK9+X+QF/DxDnY5AvjA0DSJ4j/4huJXc/vskibHEkHArcDD/KftanvEOt01wEfJH74n7XdvEhdSyQdCpxl+yhJOxMzvG2B+4Hptl/rpnybGkl7EQ45WwL/AGYS/zT3zP0gaRZwHOGVfD9wKrH+VOt7QdI1wKHAWGAZcC5wEy2uffkn4OeEl+Y6YKbte7sidyq6JEmSpM6k6TJJkiSpNanokiRJklqTii5JkiSpNanokiRJklqTii5JkiSpNanokmQTIukgSY93W44k6WVS0SVDFklLJb0iaY2kVZLuknS6pEG9ryVNkrRQ0soix33lnUts3257t3Z9vM3ynCLpjk3Q7zBJsyU9Vcb8fklHVsr3L2laXpK0QtL1nQbxlfTeku7mOUl9ku6UNKWpzgnl2Gsl3SRp207kKnUOV6QVWqdIO7XD2zEmydAgFV0y1Dna9khgB+DHwDcpkfUHkQXALcB2REDbM4E6xgPdnAjSewgwGjgbuK4E+wbYBrgc2JG4HmuAX3bY9wgi+tA+xAvXc4CbS4xVJE0CfgGcRIzzOuCSTuSSNJYI03V26fte4NqBnHgyxLGdW25DcgOWAkc07duPiOAyuXz/JBGlYjXxMPxepe7NwFeb2i8m0owI+BkRt6+v7J/cQoaxRKDaMf3IeCgRG7Iq81mlvz7igbtVpfwY4IEi7xLg42X/aEKBPw88C/wAeFc/xzwFuKPy/VulrzVEqKpPN9clovGvBJ4EjhzANVgMTOunbG9gzf9xfVcD+5TPPwSurpSNB14HRraTi8iFdlelbDjwCjCx2/dwboOz5YwuqRW2/0IEkz2o7FoLzADGEErvy5Ia+bLmANMbbSXtSYRx+h0wlci7NqG0PQ54scUhXwSeAK6SdKyk7ToQ83NEWKSdgD0IZYOk/YArgW+UYx5MKMaGrP8CdiFSJU0lwk51whJiPEYDs4qsVZPiFOBxQmn/BJhdwjdtkHKuE4CH+6ly8AbK2vW9FxFi7ImyaxLw10a57SWEopvQgVzNbdcSYzJpY2RLhh6p6JI68hxhosL2H2w/aHu97cXANYSJCyL47K6Sdi3fTwKudSTWfQMYCUwkQuU96hYBaW0b+CihkC4Anpf0p0qfrbjI9nOOWJALgL3K/i8SMVRvKfI+a/ux8uA+kkiRtNb2cmK2eXwng2H7+nK89bavBf5OzHwbPGX7CttvEgr1fYR5sF9KRot5wBzbj7Uo3wM4h1DaA6Ikd50LzLLdV3aPIGbAVfqIa9ROro7aJvUlFV1SR8ZRsiBLmlKcD1ZI6gNOJ2YuOALuXgdMLw4snycesNheRASkvZhIQ3J5eQD/D7afsX2G7fHE2tRaYmbWHy9UPq8jHsQQKU2WtKi/A7AFoURXSVpFrFd1lNxU0gxJD1TaTqaMQbM8tteVjyPohzJWc4kZ1RktyncBfg98zfbtnchYaftuQvnfY/tHlaKXgebxH0WYY9vJ1bZtUm9S0SW1QtK+hKJreB1eTaQL2d72aOAy/jsh5BzgRCLVyjrbdzcKbF9kex/CxDWBDmYntp8mlOPkjRD/aWLtqdX+14CxtseUbZTttqa34l14BfHgf4/tMcBDtE6K2ZZK2qbtiDWwN1oc71bg+7bnDrDvYUQk/GeB05qKHwb2rNTdGRgG/K0DuZrbDifGeaPMqsnQIxVdUgskjVJkAf8VcJXtB0vRSOAl26+WNbATqu2KYltPmB3nVvrbt8wGtyBmaK8Cb7Y47jaSZknaRdJmxcPvC8A9G3Eas4GZxRV+M0njJE0sJtOFwAXlPDeTNF7SIW36g3C8MLCiyDuTjVPCDS4FPkR4u75SLZA0DlgEXGz7suaG5bWHpa06LeN8A+EkMsP2+qYq84CjFe8lDgfOA2603ZiV9SsX8BtgsqRpkrYiTKqLW5lck3qSii4Z6iyQtIaY9XwXuJDIj9bgK8B5pc45hKmymSuB3YGrKvtGETOhlcBThNPJT1u0fZ1wp7+V8BJ8iJh9nTLQEymONDOJ9bc+4I+E2RLCoWZLwmtyJaEUNvSOmkufjxBK/G4if9juwJ0DlQ3emq2dRqwpviDp5bKdWKqcCuwMnFspe7nSxfYbOPYBwFGEk82qSvuDynk8TJid5xGesCOJa9tWLtsrgGnA+cTYTaHD9c2kHmQ+uqTnkTQD+JLtA7sty9uBpDOBw2wf27byICJpIbFu92i3ZUl6i827LUCSdBNJWxMzg0va1R0KFNPcMcBt3ZalGdtTuy1D0puk6TLpWSR9jFi7WkY4rQxpJO1OeFCuJjxGkyQhTZdJkiRJzckZXZIkSVJrUtElSZIktSYVXZIkSVJrUtElSZIktSYVXZIkSVJrUtElSZIktebfMxtrpJroXdMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_stats(adjusted_dates, world_daily_recovery, 'Day-wise plot of Recoveries - Worldwide', 'Number of Cases')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**USA wide data trends**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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": [
    "plot_stats(adjusted_dates,us_cases,'Number of Confirmed cases - USA','Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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": [
    "plot_stats(adjusted_dates,us_daily_increase,'Day-wise plot of Cases - USA','Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": [
    "plot_stats(adjusted_dates,us_daily_death,'Day-wise plot of Deaths - USA','Number of Cases')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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": [
    "plot_stats(adjusted_dates,us_daily_recovery,'Day-wise plot of Recoveries - USA','Number of Cases')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**State wise COVID-19 cases analysis**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we obtained and visualized the data of world and the US, the following cells are for plotting the region wise data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "states =  list(latest_data.loc[latest_data['Country_Region'] == 'US','Province_State'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "states_confirmed_cases = []\n",
    "states_death_cases = [] \n",
    "states_recovery_cases = []\n",
    "states_mortality_rate = [] \n",
    "\n",
    "no_cases = [] \n",
    "for state in states:\n",
    "    cases = latest_data[latest_data['Province_State']==state]['Confirmed'].sum()\n",
    "    if cases > 0:\n",
    "        states_confirmed_cases.append(cases)\n",
    "    else:\n",
    "        no_cases.append(state)\n",
    " \n",
    "# removing the areas with zero cases\n",
    "if len(no_cases) != 0:\n",
    "    for area in no_cases:\n",
    "        states.remove(area)\n",
    "    \n",
    "states = [k for k, v in sorted(zip(states, states_confirmed_cases), key=operator.itemgetter(1), reverse=True)]\n",
    "for i in range(len(states)):\n",
    "    states_confirmed_cases[i] = latest_data[latest_data['Province_State']==states[i]]['Confirmed'].sum()\n",
    "    states_death_cases.append(latest_data[latest_data['Province_State']==states[i]]['Deaths'].sum())\n",
    "    states_recovery_cases.append(latest_data[latest_data['Province_State']==states[i]]['Recovered'].sum())\n",
    "    states_mortality_rate.append(states_death_cases[i]/states_confirmed_cases[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            background-color:  #fda863;\n",
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       "            background-color:  #fff5eb;\n",
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       "            background-color:  #fff5eb;\n",
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       "            background-color:  #fee9d4;\n",
       "            color:  #000000;\n",
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       "            background-color:  #fff5eb;\n",
       "            color:  #000000;\n",
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       "            background-color:  #fff5eb;\n",
       "            color:  #000000;\n",
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       "            background-color:  #7f2704;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_31f5aec0_9006_11ea_b582_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >State</th>        <th class=\"col_heading level0 col1\" >Number of Confirmed Cases</th>        <th class=\"col_heading level0 col2\" >Number of Deaths</th>        <th class=\"col_heading level0 col3\" >Mortality Rate</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row0_col0\" class=\"data row0 col0\" >New York</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row0_col1\" class=\"data row0 col1\" >304372</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row0_col2\" class=\"data row0 col2\" >23587</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row0_col3\" class=\"data row0 col3\" >0.077494</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row1_col0\" class=\"data row1 col0\" >New Jersey</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row1_col1\" class=\"data row1 col1\" >118652</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row1_col2\" class=\"data row1 col2\" >7228</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row1_col3\" class=\"data row1 col3\" >0.060918</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row2_col0\" class=\"data row2 col0\" >Massachusetts</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row2_col1\" class=\"data row2 col1\" >62205</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row2_col2\" class=\"data row2 col2\" >3562</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row2_col3\" class=\"data row2 col3\" >0.057262</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row3_col0\" class=\"data row3 col0\" >Illinois</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row3_col1\" class=\"data row3 col1\" >52918</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row3_col2\" class=\"data row3 col2\" >2355</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row3_col3\" class=\"data row3 col3\" >0.044503</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row4_col0\" class=\"data row4 col0\" >California</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row4_col1\" class=\"data row4 col1\" >50130</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row4_col2\" class=\"data row4 col2\" >2031</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row4_col3\" class=\"data row4 col3\" >0.040515</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row5_col0\" class=\"data row5 col0\" >Pennsylvania</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row5_col1\" class=\"data row5 col1\" >47971</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row5_col2\" class=\"data row5 col2\" >2475</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row5_col3\" class=\"data row5 col3\" >0.051594</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row6_col0\" class=\"data row6 col0\" >Michigan</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row6_col1\" class=\"data row6 col1\" >41379</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row6_col2\" class=\"data row6 col2\" >3789</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row6_col3\" class=\"data row6 col3\" >0.091568</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row7_col0\" class=\"data row7 col0\" >Florida</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row7_col1\" class=\"data row7 col1\" >33690</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row7_col2\" class=\"data row7 col2\" >1268</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row7_col3\" class=\"data row7 col3\" >0.037637</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row8_col0\" class=\"data row8 col0\" >Texas</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row8_col1\" class=\"data row8 col1\" >28727</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row8_col2\" class=\"data row8 col2\" >812</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row8_col3\" class=\"data row8 col3\" >0.028266</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row9_col0\" class=\"data row9 col0\" >Louisiana</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row9_col1\" class=\"data row9 col1\" >28001</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row9_col2\" class=\"data row9 col2\" >1905</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row9_col3\" class=\"data row9 col3\" >0.068033</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row10_col0\" class=\"data row10 col0\" >Connecticut</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row10_col1\" class=\"data row10 col1\" >27700</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row10_col2\" class=\"data row10 col2\" >2257</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row10_col3\" class=\"data row10 col3\" >0.081480</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row11_col0\" class=\"data row11 col0\" >Georgia</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row11_col1\" class=\"data row11 col1\" >26264</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row11_col2\" class=\"data row11 col2\" >1132</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row11_col3\" class=\"data row11 col3\" >0.043101</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row12_col0\" class=\"data row12 col0\" >Maryland</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row12_col1\" class=\"data row12 col1\" >21742</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row12_col2\" class=\"data row12 col2\" >1140</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row12_col3\" class=\"data row12 col3\" >0.052433</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row13_col0\" class=\"data row13 col0\" >Ohio</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row13_col1\" class=\"data row13 col1\" >18027</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row13_col2\" class=\"data row13 col2\" >976</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row13_col3\" class=\"data row13 col3\" >0.054141</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row14_col0\" class=\"data row14 col0\" >Indiana</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row14_col1\" class=\"data row14 col1\" >17835</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row14_col2\" class=\"data row14 col2\" >1114</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row14_col3\" class=\"data row14 col3\" >0.062461</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row15_col0\" class=\"data row15 col0\" >Virginia</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row15_col1\" class=\"data row15 col1\" >15847</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row15_col2\" class=\"data row15 col2\" >552</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row15_col3\" class=\"data row15 col3\" >0.034833</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row16_col0\" class=\"data row16 col0\" >Colorado</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row16_col1\" class=\"data row16 col1\" >15284</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row16_col2\" class=\"data row16 col2\" >777</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row16_col3\" class=\"data row16 col3\" >0.050837</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row17_col0\" class=\"data row17 col0\" >Washington</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row17_col1\" class=\"data row17 col1\" >14327</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row17_col2\" class=\"data row17 col2\" >814</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row17_col3\" class=\"data row17 col3\" >0.056816</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row18_col0\" class=\"data row18 col0\" >North Carolina</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row18_col1\" class=\"data row18 col1\" >10754</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row18_col2\" class=\"data row18 col2\" >406</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row18_col3\" class=\"data row18 col3\" >0.037753</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row19_col0\" class=\"data row19 col0\" >Tennessee</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row19_col1\" class=\"data row19 col1\" >10735</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row19_col2\" class=\"data row19 col2\" >199</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row19_col3\" class=\"data row19 col3\" >0.018537</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row20_col0\" class=\"data row20 col0\" >Rhode Island</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row20_col1\" class=\"data row20 col1\" >8621</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row20_col2\" class=\"data row20 col2\" >266</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row20_col3\" class=\"data row20 col3\" >0.030855</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row21_col0\" class=\"data row21 col0\" >Missouri</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row21_col1\" class=\"data row21 col1\" >7818</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row21_col2\" class=\"data row21 col2\" >350</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row21_col3\" class=\"data row21 col3\" >0.044768</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row22_col0\" class=\"data row22 col0\" >Arizona</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row22_col1\" class=\"data row22 col1\" >7655</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row22_col2\" class=\"data row22 col2\" >320</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row22_col3\" class=\"data row22 col3\" >0.041803</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row23_col0\" class=\"data row23 col0\" >Iowa</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row23_col1\" class=\"data row23 col1\" >7145</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row23_col2\" class=\"data row23 col2\" >162</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row23_col3\" class=\"data row23 col3\" >0.022673</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row24_col0\" class=\"data row24 col0\" >Alabama</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row24_col1\" class=\"data row24 col1\" >7088</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row24_col2\" class=\"data row24 col2\" >272</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row24_col3\" class=\"data row24 col3\" >0.038375</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row25_col0\" class=\"data row25 col0\" >Wisconsin</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row25_col1\" class=\"data row25 col1\" >6854</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row25_col2\" class=\"data row25 col2\" >316</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row25_col3\" class=\"data row25 col3\" >0.046104</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row26_col0\" class=\"data row26 col0\" >Mississippi</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row26_col1\" class=\"data row26 col1\" >6815</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row26_col2\" class=\"data row26 col2\" >261</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row26_col3\" class=\"data row26 col3\" >0.038298</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row27_col0\" class=\"data row27 col0\" >South Carolina</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row27_col1\" class=\"data row27 col1\" >6095</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row27_col2\" class=\"data row27 col2\" >244</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row27_col3\" class=\"data row27 col3\" >0.040033</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row28_col0\" class=\"data row28 col0\" >Minnesota</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row28_col1\" class=\"data row28 col1\" >5136</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row28_col2\" class=\"data row28 col2\" >343</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row28_col3\" class=\"data row28 col3\" >0.066783</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row29_col0\" class=\"data row29 col0\" >Nevada</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row29_col1\" class=\"data row29 col1\" >5053</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row29_col2\" class=\"data row29 col2\" >243</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row29_col3\" class=\"data row29 col3\" >0.048090</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row30_col0\" class=\"data row30 col0\" >Delaware</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row30_col1\" class=\"data row30 col1\" >4734</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row30_col2\" class=\"data row30 col2\" >152</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row30_col3\" class=\"data row30 col3\" >0.032108</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row31_col0\" class=\"data row31 col0\" >Kentucky</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row31_col1\" class=\"data row31 col1\" >4708</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row31_col2\" class=\"data row31 col2\" >240</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row31_col3\" class=\"data row31 col3\" >0.050977</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row32_col0\" class=\"data row32 col0\" >Utah</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row32_col1\" class=\"data row32 col1\" >4672</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row32_col2\" class=\"data row32 col2\" >46</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row32_col3\" class=\"data row32 col3\" >0.009846</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row33_col0\" class=\"data row33 col0\" >Kansas</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row33_col1\" class=\"data row33 col1\" >4413</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row33_col2\" class=\"data row33 col2\" >134</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row33_col3\" class=\"data row33 col3\" >0.030365</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row34_col0\" class=\"data row34 col0\" >District of Columbia</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row34_col1\" class=\"data row34 col1\" >4323</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row34_col2\" class=\"data row34 col2\" >224</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row34_col3\" class=\"data row34 col3\" >0.051816</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row35_col0\" class=\"data row35 col0\" >Nebraska</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row35_col1\" class=\"data row35 col1\" >4281</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row35_col2\" class=\"data row35 col2\" >70</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row35_col3\" class=\"data row35 col3\" >0.016351</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row36_col0\" class=\"data row36 col0\" >Oklahoma</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row36_col1\" class=\"data row36 col1\" >3618</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row36_col2\" class=\"data row36 col2\" >222</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row36_col3\" class=\"data row36 col3\" >0.061360</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row37_col0\" class=\"data row37 col0\" >New Mexico</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row37_col1\" class=\"data row37 col1\" >3411</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row37_col2\" class=\"data row37 col2\" >123</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row37_col3\" class=\"data row37 col3\" >0.036060</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row38_col0\" class=\"data row38 col0\" >Arkansas</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row38_col1\" class=\"data row38 col1\" >3281</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row38_col2\" class=\"data row38 col2\" >61</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row38_col3\" class=\"data row38 col3\" >0.018592</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row39_col0\" class=\"data row39 col0\" >Oregon</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row39_col1\" class=\"data row39 col1\" >2510</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row39_col2\" class=\"data row39 col2\" >103</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row39_col3\" class=\"data row39 col3\" >0.041036</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row40_col0\" class=\"data row40 col0\" >South Dakota</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row40_col1\" class=\"data row40 col1\" >2449</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row40_col2\" class=\"data row40 col2\" >17</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row40_col3\" class=\"data row40 col3\" >0.006942</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row41_col0\" class=\"data row41 col0\" >New Hampshire</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row41_col1\" class=\"data row41 col1\" >2146</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row41_col2\" class=\"data row41 col2\" >72</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row41_col3\" class=\"data row41 col3\" >0.033551</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row42_col0\" class=\"data row42 col0\" >Idaho</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row42_col1\" class=\"data row42 col1\" >1984</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row42_col2\" class=\"data row42 col2\" >60</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row42_col3\" class=\"data row42 col3\" >0.030242</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row43_col0\" class=\"data row43 col0\" >Puerto Rico</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row43_col1\" class=\"data row43 col1\" >1539</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row43_col2\" class=\"data row43 col2\" >92</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row43_col3\" class=\"data row43 col3\" >0.059779</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row44_col0\" class=\"data row44 col0\" >West Virginia</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row44_col1\" class=\"data row44 col1\" >1125</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row44_col2\" class=\"data row44 col2\" >41</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row44_col3\" class=\"data row44 col3\" >0.036444</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row45_col0\" class=\"data row45 col0\" >Maine</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row45_col1\" class=\"data row45 col1\" >1095</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row45_col2\" class=\"data row45 col2\" >53</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row45_col3\" class=\"data row45 col3\" >0.048402</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row46_col0\" class=\"data row46 col0\" >North Dakota</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row46_col1\" class=\"data row46 col1\" >1067</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row46_col2\" class=\"data row46 col2\" >19</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row46_col3\" class=\"data row46 col3\" >0.017807</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row47_col0\" class=\"data row47 col0\" >Vermont</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row47_col1\" class=\"data row47 col1\" >866</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row47_col2\" class=\"data row47 col2\" >49</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row47_col3\" class=\"data row47 col3\" >0.056582</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row48_col0\" class=\"data row48 col0\" >Hawaii</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row48_col1\" class=\"data row48 col1\" >618</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row48_col2\" class=\"data row48 col2\" >16</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row48_col3\" class=\"data row48 col3\" >0.025890</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row49_col0\" class=\"data row49 col0\" >Wyoming</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row49_col1\" class=\"data row49 col1\" >559</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row49_col2\" class=\"data row49 col2\" >7</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row49_col3\" class=\"data row49 col3\" >0.012522</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row50_col0\" class=\"data row50 col0\" >Montana</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row50_col1\" class=\"data row50 col1\" >453</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row50_col2\" class=\"data row50 col2\" >16</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row50_col3\" class=\"data row50 col3\" >0.035320</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row51_col0\" class=\"data row51 col0\" >Alaska</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row51_col1\" class=\"data row51 col1\" >355</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row51_col2\" class=\"data row51 col2\" >9</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row51_col3\" class=\"data row51 col3\" >0.025352</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row52_col0\" class=\"data row52 col0\" >Guam</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row52_col1\" class=\"data row52 col1\" >145</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row52_col2\" class=\"data row52 col2\" >5</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row52_col3\" class=\"data row52 col3\" >0.034483</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row53_col0\" class=\"data row53 col0\" >Grand Princess</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row53_col1\" class=\"data row53 col1\" >116</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row53_col2\" class=\"data row53 col2\" >3</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row53_col3\" class=\"data row53 col3\" >0.025862</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row54_col0\" class=\"data row54 col0\" >Virgin Islands</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row54_col1\" class=\"data row54 col1\" >66</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row54_col2\" class=\"data row54 col2\" >4</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row54_col3\" class=\"data row54 col3\" >0.060606</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row55_col0\" class=\"data row55 col0\" >Diamond Princess</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row55_col1\" class=\"data row55 col1\" >49</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row55_col2\" class=\"data row55 col2\" >1</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row55_col3\" class=\"data row55 col3\" >0.020408</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_31f5aec0_9006_11ea_b582_acde48001122level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row56_col0\" class=\"data row56 col0\" >Northern Mariana Islands</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row56_col1\" class=\"data row56 col1\" >14</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row56_col2\" class=\"data row56 col2\" >2</td>\n",
       "                        <td id=\"T_31f5aec0_9006_11ea_b582_acde48001122row56_col3\" class=\"data row56 col3\" >0.142857</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a1b26b210>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of cases per US state\n",
    "state_df = pd.DataFrame({'State': states, 'Number of Confirmed Cases': states_confirmed_cases,'Number of Deaths': states_death_cases, 'Mortality Rate': states_mortality_rate})\n",
    "\n",
    "# number of cases per country/region\n",
    "state_df.style.background_gradient(cmap='Oranges')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plotting the 10 states with the most confirmed cases. The remaining states are grouped into \"others\" category**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_bar_graphs(x_axis, y_axis, title):\n",
    "    '''\n",
    "    INPUT - variables to be plotted on X-axis and Y-axis, and title\n",
    "    \n",
    "    OUTPUT - function doesn't return anything but prints required plots\n",
    "    '''\n",
    "    plt.figure()\n",
    "    plt.barh(x_axis, y_axis)\n",
    "    plt.title(title)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "visual_unique_states = [] \n",
    "visual_confirmed_cases = []\n",
    "others = np.sum(states_confirmed_cases[10:])\n",
    "for i in range(len(states_confirmed_cases[:10])):\n",
    "    visual_unique_states.append(states[i])\n",
    "    visual_confirmed_cases.append(states_confirmed_cases[i])\n",
    "\n",
    "visual_unique_states.append('Others')\n",
    "visual_confirmed_cases.append(others)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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": [
    "plot_bar_graphs(visual_unique_states, visual_confirmed_cases, 'Number of COVID-19 Cases in States')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plotting the same in a pie chart**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_pie_charts(x_axis, y_axis, title):\n",
    "    '''\n",
    "    INPUT - variables to be plotted on X-axis and Y-axis, and title\n",
    "    \n",
    "    OUTPUT - function doesn't return anything but prints required plots\n",
    "    \n",
    "    '''\n",
    "    plt.figure(figsize=(15,15))\n",
    "    plt.title(title)\n",
    "    plt.pie(y_axis, colors= random.choices(list(mcolors.CSS4_COLORS.values()),k = len(states)))\n",
    "    plt.legend(x_axis, loc='best')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pie_charts(visual_unique_states, visual_confirmed_cases, 'Number of COVID-19 Cases in States of USA')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot Worldwide Mortality and Recovery Rates**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_rates(x_axis,y_axis,title,y_label,color):\n",
    "    '''\n",
    "    INPUT - data to be plotted on X-axis and Y-axis and a strings for title, legend, and y-axis label\n",
    "    \n",
    "    OUTPUT - function doesn't return anything but prints required plots\n",
    "    '''\n",
    "    mean_rate = np.mean(y_axis)\n",
    "    plt.plot(x_axis, y_axis, color = color)\n",
    "    plt.axhline(y = mean_rate,linestyle='--', color='black')\n",
    "    plt.title(title)\n",
    "    plt.legend([y_label, 'y='+str(mean_rate)])\n",
    "    plt.xlabel('Days Since Jan 22,2020')\n",
    "    plt.ylabel(y_label)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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": [
    "plot_rates(adjusted_dates, mortality_rate, 'Mortality Rate of COVID-19 patients Over Time', 'Mortality Rate','red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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": [
    "plot_rates(adjusted_dates, recovery_rate, 'Recovery Rate of COVID-19 patients Over Time', 'Recovery Rate','green')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Split Data**\n",
    "<br>\n",
    "Now I'm predicting the number of confirmed cases for the next 15 days. For this first, we have to split the data into train and test sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_confirmed_train, X_confirmed_test, y_confirmed_train, y_confirmed_test = train_test_split(days, world_cases, test_size=0.30, shuffle=False) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Models for predicting confirmed cases**<br> I used variants of LinearRegression to compare the performance\n",
    "<br>*Note that this is just a simple model and the results are not accurate*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define linear regression model\n",
    "linear_model = LinearRegression(normalize=True, fit_intercept=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to train the model and predict the number of probable cases\n",
    "def execute_linear_model(X_confirmed_train, y_confirmed_train, X_confirmed_test, forecast_future):\n",
    "    '''\n",
    "    INPUT - the split data\n",
    "    \n",
    "    OUTPUT - executes linear model and prints MAE & MSE, returns predicted values\n",
    "    '''\n",
    "    linear_model.fit(X_confirmed_train, y_confirmed_train)\n",
    "    test_linear_pred = linear_model.predict(X_confirmed_test)\n",
    "    linear_pred = linear_model.predict(forecast_future)\n",
    "    print('MAE:', mean_absolute_error(test_linear_pred, y_confirmed_test))\n",
    "    print('MSE:',mean_squared_error(test_linear_pred, y_confirmed_test))\n",
    "    return test_linear_pred, linear_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to plot the models predictions against the test data\n",
    "def plot_model_predictions(model,y_confirmed_test,test_linear_pred):\n",
    "    '''\n",
    "    INPUT - model name, predicted and actual lables\n",
    "    \n",
    "    OUTPUT - displays graphs\n",
    "    '''\n",
    "    plt.plot(y_confirmed_test)\n",
    "    plt.plot(test_linear_pred)\n",
    "    plt.legend(['Test Data',  model+' Regression Predictions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 1865856.471105928\n",
      "MSE: 3951696420263.8076\n"
     ]
    }
   ],
   "source": [
    "test_linear_pred, linear_pred = execute_linear_model(X_confirmed_train, y_confirmed_train,X_confirmed_test,forecast_future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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": [
    "plot_model_predictions('Linear',y_confirmed_test,test_linear_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be seen that normal LinearRegression did not work well with the data. Try using Polynomial Regression. <br> For that first transform the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform our data for polynomial variants of linear regression\n",
    "def transform_to_poly(degree=2):\n",
    "    '''\n",
    "    INPUT - degree \n",
    "    \n",
    "    OUTPUT - returns the transformed data\n",
    "    \n",
    "    Transorms data into required polymonial degree\n",
    "    '''\n",
    "    poly = PolynomialFeatures(degree)\n",
    "    poly_X_confirmed_train = poly.fit_transform(X_confirmed_train)\n",
    "    poly_X_confirmed_test = poly.fit_transform(X_confirmed_test)\n",
    "    poly_forecast_future = poly.fit_transform(forecast_future)\n",
    "    \n",
    "    return poly_X_confirmed_train, poly_X_confirmed_test, poly_forecast_future"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "poly_2_X_confirmed_train, poly_2_X_confirmed_test, poly_2_forecast_future = transform_to_poly(degree = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 951180.4682575748\n",
      "MSE: 1020244614297.7096\n"
     ]
    }
   ],
   "source": [
    "test_ploy_2_pred, poly_2_pred = execute_linear_model(poly_2_X_confirmed_train,y_confirmed_train,poly_2_X_confirmed_test,poly_2_forecast_future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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": [
    "plot_model_predictions('Polynomial Degree 2',y_confirmed_test,test_ploy_2_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "poly_3_X_confirmed_train, poly_3_X_confirmed_test, poly_3_forecast_future = transform_to_poly(degree = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 447195.89871139434\n",
      "MSE: 423940090719.03186\n"
     ]
    }
   ],
   "source": [
    "test_ploy_3_pred, poly_3_pred = execute_linear_model(poly_3_X_confirmed_train,y_confirmed_train,poly_3_X_confirmed_test,poly_3_forecast_future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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": [
    "plot_model_predictions('Polynomial Degree 3',y_confirmed_test,test_ploy_3_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Average of predictions of Polynomial Regression models**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_avg_pred = []\n",
    "for i in range(0,len(test_ploy_2_pred)):\n",
    "    temp = float(test_ploy_2_pred[i]+test_ploy_3_pred[i])/2\n",
    "    test_avg_pred.append(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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": [
    "plot_model_predictions('Average of Polynomial Degree 2 & 3',y_confirmed_test,test_avg_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 278120.8237398122\n",
      "MSE: 90715282111.98846\n"
     ]
    }
   ],
   "source": [
    "print('MAE:', mean_absolute_error(test_avg_pred, y_confirmed_test))\n",
    "print('MSE:',mean_squared_error(test_avg_pred, y_confirmed_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is clear that the average of predictions of Polynomial Regression models of Degree-2&3 has less MAE and MSE compared to those of the individual models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = []\n",
    "for i in range(0,len(poly_2_pred)):\n",
    "    temp = float(poly_2_pred[i]+poly_3_pred[i])/2\n",
    "    preds.append(temp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we shall plot predictions of the 3 variants against the confirmed cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_future_predictions(x_data, y_data, predictions, algorithms):\n",
    "    '''\n",
    "    INPUT - \n",
    "        x_data & y_data: data for x-axis and y-axis\n",
    "        predictions1,predictions2,predictions3: predictions by te above declared models\n",
    "        algo_1_name,algo_2_name,algo_3_name: names for algorithms to show in graph legend\n",
    "        \n",
    "    OUTPUT - \n",
    "        This function doesn't return anything but prints the predictions of models against current confirmed cases\n",
    "    '''\n",
    "    \n",
    "    plt.figure(figsize=(12, 9))\n",
    "    plt.plot(x_data, y_data)\n",
    "    for prediction in predictions:\n",
    "        plt.plot(forecast_future, prediction, linestyle='dashed')\n",
    "    plt.title('Number of COVID-19 Cases Over Time')\n",
    "    plt.xlabel('Days Since Jan 22, 2020')\n",
    "    plt.ylabel('Number of Cases')\n",
    "    legend = ['Confirmed Cases']\n",
    "    for algorithm in algorithms:\n",
    "        legend.append(algorithm)\n",
    "    plt.legend(legend)\n",
    "    plt.ticklabel_format(style = 'plain')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred = [linear_pred, poly_2_pred, poly_3_pred, preds]\n",
    "algos = ['Linear Regression','Degree 2 Polynomial Regression','Degree 3 Polynomial Regression','Average of Polynomial Models']\n",
    "plot_future_predictions(adjusted_dates, world_cases,pred,algos)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be seen that the Polynomial variant with degree three performed well compared to other two variants of the Linear Regression model.\n",
    "\n",
    "<br> \n",
    "\n",
    "The next cell is for displaying our predictions for the next 15 days that we obtained using the Polynomial model.\n",
    "<br>*Note that this is just a simple model and the results are not accurate*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>Date</th>\n",
       "      <th>Number of worldwide cases predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>05/06/2020</td>\n",
       "      <td>5443228.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>05/07/2020</td>\n",
       "      <td>5657852.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>05/08/2020</td>\n",
       "      <td>5878025.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>05/09/2020</td>\n",
       "      <td>6103819.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05/10/2020</td>\n",
       "      <td>6335302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>05/11/2020</td>\n",
       "      <td>6572546.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>05/12/2020</td>\n",
       "      <td>6815619.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>05/13/2020</td>\n",
       "      <td>7064592.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>05/14/2020</td>\n",
       "      <td>7319535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>05/15/2020</td>\n",
       "      <td>7580517.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>05/16/2020</td>\n",
       "      <td>7847609.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>05/17/2020</td>\n",
       "      <td>8120880.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>05/18/2020</td>\n",
       "      <td>8400401.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>05/19/2020</td>\n",
       "      <td>8686240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>05/20/2020</td>\n",
       "      <td>8978469.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Number of worldwide cases predicted\n",
       "0   05/06/2020                            5443228.0\n",
       "1   05/07/2020                            5657852.0\n",
       "2   05/08/2020                            5878025.0\n",
       "3   05/09/2020                            6103819.0\n",
       "4   05/10/2020                            6335302.0\n",
       "5   05/11/2020                            6572546.0\n",
       "6   05/12/2020                            6815619.0\n",
       "7   05/13/2020                            7064592.0\n",
       "8   05/14/2020                            7319535.0\n",
       "9   05/15/2020                            7580517.0\n",
       "10  05/16/2020                            7847609.0\n",
       "11  05/17/2020                            8120880.0\n",
       "12  05/18/2020                            8400401.0\n",
       "13  05/19/2020                            8686240.0\n",
       "14  05/20/2020                            8978469.0"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly_3_preds = poly_3_pred.reshape(1,-1)[0]\n",
    "poly_3_df = pd.DataFrame({'Date': dates_for_forecast_future[-15:], 'Number of worldwide cases predicted': np.round(poly_3_preds[-15:])})\n",
    "poly_3_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\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>Date</th>\n",
       "      <th>Number of worldwide cases predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>05/06/2020</td>\n",
       "      <td>3850312.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>05/07/2020</td>\n",
       "      <td>3985155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>05/08/2020</td>\n",
       "      <td>4123100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>05/09/2020</td>\n",
       "      <td>4264184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05/10/2020</td>\n",
       "      <td>4408441.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>05/11/2020</td>\n",
       "      <td>4555905.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>05/12/2020</td>\n",
       "      <td>4706612.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>05/13/2020</td>\n",
       "      <td>4860597.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>05/14/2020</td>\n",
       "      <td>5017894.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>05/15/2020</td>\n",
       "      <td>5178539.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>05/16/2020</td>\n",
       "      <td>5342566.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>05/17/2020</td>\n",
       "      <td>5510011.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>05/18/2020</td>\n",
       "      <td>5680909.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>05/19/2020</td>\n",
       "      <td>5855294.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>05/20/2020</td>\n",
       "      <td>6033201.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Number of worldwide cases predicted\n",
       "0   05/06/2020                            3850312.0\n",
       "1   05/07/2020                            3985155.0\n",
       "2   05/08/2020                            4123100.0\n",
       "3   05/09/2020                            4264184.0\n",
       "4   05/10/2020                            4408441.0\n",
       "5   05/11/2020                            4555905.0\n",
       "6   05/12/2020                            4706612.0\n",
       "7   05/13/2020                            4860597.0\n",
       "8   05/14/2020                            5017894.0\n",
       "9   05/15/2020                            5178539.0\n",
       "10  05/16/2020                            5342566.0\n",
       "11  05/17/2020                            5510011.0\n",
       "12  05/18/2020                            5680909.0\n",
       "13  05/19/2020                            5855294.0\n",
       "14  05/20/2020                            6033201.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds_m = np.array(preds).reshape(1,-1)[0]\n",
    "poly_df = pd.DataFrame({'Date': dates_for_forecast_future[-15:], 'Number of worldwide cases predicted': np.round(preds[-15:])})\n",
    "poly_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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