explore.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'\n",
    "url_death = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv'\n",
    "url_recovered = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(url_confirmed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>...</th>\n",
       "      <th>10/3/20</th>\n",
       "      <th>10/4/20</th>\n",
       "      <th>10/5/20</th>\n",
       "      <th>10/6/20</th>\n",
       "      <th>10/7/20</th>\n",
       "      <th>10/8/20</th>\n",
       "      <th>10/9/20</th>\n",
       "      <th>10/10/20</th>\n",
       "      <th>10/11/20</th>\n",
       "      <th>10/12/20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>33.93911</td>\n",
       "      <td>67.709953</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>39297</td>\n",
       "      <td>39341</td>\n",
       "      <td>39422</td>\n",
       "      <td>39486</td>\n",
       "      <td>39548</td>\n",
       "      <td>39616</td>\n",
       "      <td>39693</td>\n",
       "      <td>39703</td>\n",
       "      <td>39799</td>\n",
       "      <td>39870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>41.15330</td>\n",
       "      <td>20.168300</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>14117</td>\n",
       "      <td>14266</td>\n",
       "      <td>14410</td>\n",
       "      <td>14568</td>\n",
       "      <td>14730</td>\n",
       "      <td>14899</td>\n",
       "      <td>15066</td>\n",
       "      <td>15231</td>\n",
       "      <td>15399</td>\n",
       "      <td>15570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>28.03390</td>\n",
       "      <td>1.659600</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>51995</td>\n",
       "      <td>52136</td>\n",
       "      <td>52270</td>\n",
       "      <td>52399</td>\n",
       "      <td>52520</td>\n",
       "      <td>52658</td>\n",
       "      <td>52804</td>\n",
       "      <td>52940</td>\n",
       "      <td>53072</td>\n",
       "      <td>53325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>42.50630</td>\n",
       "      <td>1.521800</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>2110</td>\n",
       "      <td>2110</td>\n",
       "      <td>2370</td>\n",
       "      <td>2370</td>\n",
       "      <td>2568</td>\n",
       "      <td>2568</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>-11.20270</td>\n",
       "      <td>17.873900</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>5370</td>\n",
       "      <td>5402</td>\n",
       "      <td>5530</td>\n",
       "      <td>5725</td>\n",
       "      <td>5725</td>\n",
       "      <td>5958</td>\n",
       "      <td>6031</td>\n",
       "      <td>6246</td>\n",
       "      <td>6366</td>\n",
       "      <td>6488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 269 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Province/State Country/Region       Lat       Long  1/22/20  1/23/20  \\\n",
       "0            NaN    Afghanistan  33.93911  67.709953        0        0   \n",
       "1            NaN        Albania  41.15330  20.168300        0        0   \n",
       "2            NaN        Algeria  28.03390   1.659600        0        0   \n",
       "3            NaN        Andorra  42.50630   1.521800        0        0   \n",
       "4            NaN         Angola -11.20270  17.873900        0        0   \n",
       "\n",
       "   1/24/20  1/25/20  1/26/20  1/27/20  ...  10/3/20  10/4/20  10/5/20  \\\n",
       "0        0        0        0        0  ...    39297    39341    39422   \n",
       "1        0        0        0        0  ...    14117    14266    14410   \n",
       "2        0        0        0        0  ...    51995    52136    52270   \n",
       "3        0        0        0        0  ...     2110     2110     2370   \n",
       "4        0        0        0        0  ...     5370     5402     5530   \n",
       "\n",
       "   10/6/20  10/7/20  10/8/20  10/9/20  10/10/20  10/11/20  10/12/20  \n",
       "0    39486    39548    39616    39693     39703     39799     39870  \n",
       "1    14568    14730    14899    15066     15231     15399     15570  \n",
       "2    52399    52520    52658    52804     52940     53072     53325  \n",
       "3     2370     2568     2568     2696      2696      2696      2995  \n",
       "4     5725     5725     5958     6031      6246      6366      6488  \n",
       "\n",
       "[5 rows x 269 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "case_columns=df.columns[4:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f42341877f0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "german_index = df.loc[df['Country/Region']=='Germany'].index[0]\n",
    "df.loc[german_index,case_columns].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4233ec7970>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "df.loc[german_index,case_columns].diff().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4233e746d0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "df.loc[german_index,case_columns].diff().rolling(window=7, axis=0).apply(np.mean).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Australia', 'Canada', 'China', 'Denmark', 'France', 'Netherlands',\n",
       "       'United Kingdom'], dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna()[\"Country/Region\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Australia', 'Canada', 'China', 'Denmark', 'France', 'Netherlands',\n",
       "       'United Kingdom'], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[~pd.isna(df['Province/State'])]['Country/Region'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'Australian Capital Territory', 'New South Wales',\n",
       "       'Northern Territory', 'Queensland', 'South Australia', 'Tasmania',\n",
       "       'Victoria', 'Western Australia', 'Alberta', 'British Columbia',\n",
       "       'Diamond Princess', 'Grand Princess', 'Manitoba', 'New Brunswick',\n",
       "       'Newfoundland and Labrador', 'Northwest Territories',\n",
       "       'Nova Scotia', 'Ontario', 'Prince Edward Island', 'Quebec',\n",
       "       'Saskatchewan', 'Yukon', 'Anhui', 'Beijing', 'Chongqing', 'Fujian',\n",
       "       'Gansu', 'Guangdong', 'Guangxi', 'Guizhou', 'Hainan', 'Hebei',\n",
       "       'Heilongjiang', 'Henan', 'Hong Kong', 'Hubei', 'Hunan',\n",
       "       'Inner Mongolia', 'Jiangsu', 'Jiangxi', 'Jilin', 'Liaoning',\n",
       "       'Macau', 'Ningxia', 'Qinghai', 'Shaanxi', 'Shandong', 'Shanghai',\n",
       "       'Shanxi', 'Sichuan', 'Tianjin', 'Tibet', 'Xinjiang', 'Yunnan',\n",
       "       'Zhejiang', 'Faroe Islands', 'Greenland', 'French Guiana',\n",
       "       'French Polynesia', 'Guadeloupe', 'Martinique', 'Mayotte',\n",
       "       'New Caledonia', 'Reunion', 'Saint Barthelemy',\n",
       "       'Saint Pierre and Miquelon', 'St Martin', 'Aruba',\n",
       "       'Bonaire, Sint Eustatius and Saba', 'Curacao', 'Sint Maarten',\n",
       "       'Anguilla', 'Bermuda', 'British Virgin Islands', 'Cayman Islands',\n",
       "       'Channel Islands', 'Falkland Islands (Malvinas)', 'Gibraltar',\n",
       "       'Isle of Man', 'Montserrat', 'Turks and Caicos Islands'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Province/State'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>...</th>\n",
       "      <th>10/3/20</th>\n",
       "      <th>10/4/20</th>\n",
       "      <th>10/5/20</th>\n",
       "      <th>10/6/20</th>\n",
       "      <th>10/7/20</th>\n",
       "      <th>10/8/20</th>\n",
       "      <th>10/9/20</th>\n",
       "      <th>10/10/20</th>\n",
       "      <th>10/11/20</th>\n",
       "      <th>10/12/20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Anhui</td>\n",
       "      <td>China</td>\n",
       "      <td>31.8257</td>\n",
       "      <td>117.2264</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "      <td>60</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "      <td>991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Beijing</td>\n",
       "      <td>China</td>\n",
       "      <td>40.1824</td>\n",
       "      <td>116.4142</td>\n",
       "      <td>14</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>41</td>\n",
       "      <td>68</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>936</td>\n",
       "      <td>937</td>\n",
       "      <td>937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Chongqing</td>\n",
       "      <td>China</td>\n",
       "      <td>30.0572</td>\n",
       "      <td>107.8740</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>57</td>\n",
       "      <td>75</td>\n",
       "      <td>110</td>\n",
       "      <td>...</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "      <td>585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Fujian</td>\n",
       "      <td>China</td>\n",
       "      <td>26.0789</td>\n",
       "      <td>117.9874</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>59</td>\n",
       "      <td>...</td>\n",
       "      <td>411</td>\n",
       "      <td>413</td>\n",
       "      <td>413</td>\n",
       "      <td>413</td>\n",
       "      <td>413</td>\n",
       "      <td>414</td>\n",
       "      <td>414</td>\n",
       "      <td>415</td>\n",
       "      <td>416</td>\n",
       "      <td>416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Gansu</td>\n",
       "      <td>China</td>\n",
       "      <td>35.7518</td>\n",
       "      <td>104.2861</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Guangdong</td>\n",
       "      <td>China</td>\n",
       "      <td>23.3417</td>\n",
       "      <td>113.4244</td>\n",
       "      <td>26</td>\n",
       "      <td>32</td>\n",
       "      <td>53</td>\n",
       "      <td>78</td>\n",
       "      <td>111</td>\n",
       "      <td>151</td>\n",
       "      <td>...</td>\n",
       "      <td>1840</td>\n",
       "      <td>1841</td>\n",
       "      <td>1846</td>\n",
       "      <td>1848</td>\n",
       "      <td>1848</td>\n",
       "      <td>1851</td>\n",
       "      <td>1852</td>\n",
       "      <td>1858</td>\n",
       "      <td>1861</td>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Guangxi</td>\n",
       "      <td>China</td>\n",
       "      <td>23.8298</td>\n",
       "      <td>108.7881</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>36</td>\n",
       "      <td>46</td>\n",
       "      <td>...</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Guizhou</td>\n",
       "      <td>China</td>\n",
       "      <td>26.8154</td>\n",
       "      <td>106.8748</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Hainan</td>\n",
       "      <td>China</td>\n",
       "      <td>19.1959</td>\n",
       "      <td>109.7453</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>22</td>\n",
       "      <td>33</td>\n",
       "      <td>...</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Hebei</td>\n",
       "      <td>China</td>\n",
       "      <td>39.5490</td>\n",
       "      <td>116.1306</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>367</td>\n",
       "      <td>367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>China</td>\n",
       "      <td>47.8620</td>\n",
       "      <td>127.7615</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "      <td>...</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "      <td>948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Henan</td>\n",
       "      <td>China</td>\n",
       "      <td>37.8957</td>\n",
       "      <td>114.9042</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>32</td>\n",
       "      <td>83</td>\n",
       "      <td>128</td>\n",
       "      <td>...</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "      <td>1281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>China</td>\n",
       "      <td>22.3000</td>\n",
       "      <td>114.2000</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>5108</td>\n",
       "      <td>5113</td>\n",
       "      <td>5124</td>\n",
       "      <td>5132</td>\n",
       "      <td>5143</td>\n",
       "      <td>5161</td>\n",
       "      <td>5169</td>\n",
       "      <td>5175</td>\n",
       "      <td>5182</td>\n",
       "      <td>5193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Hubei</td>\n",
       "      <td>China</td>\n",
       "      <td>30.9756</td>\n",
       "      <td>112.2707</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>549</td>\n",
       "      <td>761</td>\n",
       "      <td>1058</td>\n",
       "      <td>1423</td>\n",
       "      <td>...</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "      <td>68139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Hunan</td>\n",
       "      <td>China</td>\n",
       "      <td>27.6104</td>\n",
       "      <td>111.7088</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>24</td>\n",
       "      <td>43</td>\n",
       "      <td>69</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "      <td>1019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Inner Mongolia</td>\n",
       "      <td>China</td>\n",
       "      <td>44.0935</td>\n",
       "      <td>113.9448</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>266</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>268</td>\n",
       "      <td>269</td>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>China</td>\n",
       "      <td>32.9711</td>\n",
       "      <td>119.4550</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>47</td>\n",
       "      <td>...</td>\n",
       "      <td>666</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "      <td>667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>China</td>\n",
       "      <td>27.6140</td>\n",
       "      <td>115.7221</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>36</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "      <td>935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Jilin</td>\n",
       "      <td>China</td>\n",
       "      <td>43.6661</td>\n",
       "      <td>126.1923</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Liaoning</td>\n",
       "      <td>China</td>\n",
       "      <td>41.2956</td>\n",
       "      <td>122.6085</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>...</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "      <td>273</td>\n",
       "      <td>275</td>\n",
       "      <td>276</td>\n",
       "      <td>280</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Macau</td>\n",
       "      <td>China</td>\n",
       "      <td>22.1667</td>\n",
       "      <td>113.5500</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Ningxia</td>\n",
       "      <td>China</td>\n",
       "      <td>37.2692</td>\n",
       "      <td>106.1655</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Qinghai</td>\n",
       "      <td>China</td>\n",
       "      <td>35.7452</td>\n",
       "      <td>95.9956</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Shaanxi</td>\n",
       "      <td>China</td>\n",
       "      <td>35.1917</td>\n",
       "      <td>108.8701</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>22</td>\n",
       "      <td>35</td>\n",
       "      <td>...</td>\n",
       "      <td>413</td>\n",
       "      <td>413</td>\n",
       "      <td>414</td>\n",
       "      <td>414</td>\n",
       "      <td>414</td>\n",
       "      <td>425</td>\n",
       "      <td>428</td>\n",
       "      <td>428</td>\n",
       "      <td>428</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Shandong</td>\n",
       "      <td>China</td>\n",
       "      <td>36.3427</td>\n",
       "      <td>118.1498</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>...</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>832</td>\n",
       "      <td>838</td>\n",
       "      <td>838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Shanghai</td>\n",
       "      <td>China</td>\n",
       "      <td>31.2020</td>\n",
       "      <td>121.4491</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "      <td>33</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "      <td>...</td>\n",
       "      <td>1012</td>\n",
       "      <td>1022</td>\n",
       "      <td>1024</td>\n",
       "      <td>1025</td>\n",
       "      <td>1030</td>\n",
       "      <td>1036</td>\n",
       "      <td>1038</td>\n",
       "      <td>1048</td>\n",
       "      <td>1053</td>\n",
       "      <td>1056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Shanxi</td>\n",
       "      <td>China</td>\n",
       "      <td>37.5777</td>\n",
       "      <td>112.2922</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>204</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>206</td>\n",
       "      <td>206</td>\n",
       "      <td>206</td>\n",
       "      <td>206</td>\n",
       "      <td>206</td>\n",
       "      <td>208</td>\n",
       "      <td>208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Sichuan</td>\n",
       "      <td>China</td>\n",
       "      <td>30.6171</td>\n",
       "      <td>102.7103</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "      <td>44</td>\n",
       "      <td>69</td>\n",
       "      <td>...</td>\n",
       "      <td>701</td>\n",
       "      <td>704</td>\n",
       "      <td>707</td>\n",
       "      <td>710</td>\n",
       "      <td>713</td>\n",
       "      <td>713</td>\n",
       "      <td>718</td>\n",
       "      <td>721</td>\n",
       "      <td>722</td>\n",
       "      <td>723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>Tianjin</td>\n",
       "      <td>China</td>\n",
       "      <td>39.3054</td>\n",
       "      <td>117.3230</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>23</td>\n",
       "      <td>...</td>\n",
       "      <td>241</td>\n",
       "      <td>241</td>\n",
       "      <td>242</td>\n",
       "      <td>242</td>\n",
       "      <td>242</td>\n",
       "      <td>242</td>\n",
       "      <td>244</td>\n",
       "      <td>244</td>\n",
       "      <td>245</td>\n",
       "      <td>245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Tibet</td>\n",
       "      <td>China</td>\n",
       "      <td>31.6927</td>\n",
       "      <td>88.0924</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>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>China</td>\n",
       "      <td>41.1129</td>\n",
       "      <td>85.2401</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "      <td>902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Yunnan</td>\n",
       "      <td>China</td>\n",
       "      <td>24.9740</td>\n",
       "      <td>101.4870</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>26</td>\n",
       "      <td>...</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>China</td>\n",
       "      <td>29.1832</td>\n",
       "      <td>120.0934</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>43</td>\n",
       "      <td>62</td>\n",
       "      <td>104</td>\n",
       "      <td>128</td>\n",
       "      <td>...</td>\n",
       "      <td>1282</td>\n",
       "      <td>1282</td>\n",
       "      <td>1282</td>\n",
       "      <td>1282</td>\n",
       "      <td>1283</td>\n",
       "      <td>1283</td>\n",
       "      <td>1283</td>\n",
       "      <td>1283</td>\n",
       "      <td>1283</td>\n",
       "      <td>1283</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>33 rows × 269 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Province/State Country/Region      Lat      Long  1/22/20  1/23/20  \\\n",
       "56           Anhui          China  31.8257  117.2264        1        9   \n",
       "57         Beijing          China  40.1824  116.4142       14       22   \n",
       "58       Chongqing          China  30.0572  107.8740        6        9   \n",
       "59          Fujian          China  26.0789  117.9874        1        5   \n",
       "60           Gansu          China  35.7518  104.2861        0        2   \n",
       "61       Guangdong          China  23.3417  113.4244       26       32   \n",
       "62         Guangxi          China  23.8298  108.7881        2        5   \n",
       "63         Guizhou          China  26.8154  106.8748        1        3   \n",
       "64          Hainan          China  19.1959  109.7453        4        5   \n",
       "65           Hebei          China  39.5490  116.1306        1        1   \n",
       "66    Heilongjiang          China  47.8620  127.7615        0        2   \n",
       "67           Henan          China  37.8957  114.9042        5        5   \n",
       "68       Hong Kong          China  22.3000  114.2000        0        2   \n",
       "69           Hubei          China  30.9756  112.2707      444      444   \n",
       "70           Hunan          China  27.6104  111.7088        4        9   \n",
       "71  Inner Mongolia          China  44.0935  113.9448        0        0   \n",
       "72         Jiangsu          China  32.9711  119.4550        1        5   \n",
       "73         Jiangxi          China  27.6140  115.7221        2        7   \n",
       "74           Jilin          China  43.6661  126.1923        0        1   \n",
       "75        Liaoning          China  41.2956  122.6085        2        3   \n",
       "76           Macau          China  22.1667  113.5500        1        2   \n",
       "77         Ningxia          China  37.2692  106.1655        1        1   \n",
       "78         Qinghai          China  35.7452   95.9956        0        0   \n",
       "79         Shaanxi          China  35.1917  108.8701        0        3   \n",
       "80        Shandong          China  36.3427  118.1498        2        6   \n",
       "81        Shanghai          China  31.2020  121.4491        9       16   \n",
       "82          Shanxi          China  37.5777  112.2922        1        1   \n",
       "83         Sichuan          China  30.6171  102.7103        5        8   \n",
       "84         Tianjin          China  39.3054  117.3230        4        4   \n",
       "85           Tibet          China  31.6927   88.0924        0        0   \n",
       "86        Xinjiang          China  41.1129   85.2401        0        2   \n",
       "87          Yunnan          China  24.9740  101.4870        1        2   \n",
       "88        Zhejiang          China  29.1832  120.0934       10       27   \n",
       "\n",
       "    1/24/20  1/25/20  1/26/20  1/27/20  ...  10/3/20  10/4/20  10/5/20  \\\n",
       "56       15       39       60       70  ...      991      991      991   \n",
       "57       36       41       68       80  ...      936      936      936   \n",
       "58       27       57       75      110  ...      585      585      585   \n",
       "59       10       18       35       59  ...      411      413      413   \n",
       "60        2        4        7       14  ...      170      170      170   \n",
       "61       53       78      111      151  ...     1840     1841     1846   \n",
       "62       23       23       36       46  ...      260      260      260   \n",
       "63        3        4        5        7  ...      147      147      147   \n",
       "64        8       19       22       33  ...      171      171      171   \n",
       "65        2        8       13       18  ...      365      365      365   \n",
       "66        4        9       15       21  ...      948      948      948   \n",
       "67        9       32       83      128  ...     1281     1281     1281   \n",
       "68        2        5        8        8  ...     5108     5113     5124   \n",
       "69      549      761     1058     1423  ...    68139    68139    68139   \n",
       "70       24       43       69      100  ...     1019     1019     1019   \n",
       "71        1        7        7       11  ...      266      268      268   \n",
       "72        9       18       33       47  ...      666      667      667   \n",
       "73       18       18       36       72  ...      935      935      935   \n",
       "74        3        4        4        6  ...      157      157      157   \n",
       "75        4       17       21       27  ...      271      271      271   \n",
       "76        2        2        5        6  ...       46       46       46   \n",
       "77        2        3        4        7  ...       75       75       75   \n",
       "78        0        1        1        6  ...       18       18       18   \n",
       "79        5       15       22       35  ...      413      413      414   \n",
       "80       15       27       46       75  ...      832      832      832   \n",
       "81       20       33       40       53  ...     1012     1022     1024   \n",
       "82        1        6        9       13  ...      204      205      205   \n",
       "83       15       28       44       69  ...      701      704      707   \n",
       "84        8       10       14       23  ...      241      241      242   \n",
       "85        0        0        0        0  ...        1        1        1   \n",
       "86        2        3        4        5  ...      902      902      902   \n",
       "87        5       11       16       26  ...      211      211      211   \n",
       "88       43       62      104      128  ...     1282     1282     1282   \n",
       "\n",
       "    10/6/20  10/7/20  10/8/20  10/9/20  10/10/20  10/11/20  10/12/20  \n",
       "56      991      991      991      991       991       991       991  \n",
       "57      936      936      936      936       936       937       937  \n",
       "58      585      585      585      585       585       585       585  \n",
       "59      413      413      414      414       415       416       416  \n",
       "60      170      170      170      170       170       170       170  \n",
       "61     1848     1848     1851     1852      1858      1861      1863  \n",
       "62      260      260      260      260       260       260       260  \n",
       "63      147      147      147      147       147       147       147  \n",
       "64      171      171      171      171       171       171       171  \n",
       "65      365      365      365      365       365       367       367  \n",
       "66      948      948      948      948       948       948       948  \n",
       "67     1281     1281     1281     1281      1281      1281      1281  \n",
       "68     5132     5143     5161     5169      5175      5182      5193  \n",
       "69    68139    68139    68139    68139     68139     68139     68139  \n",
       "70     1019     1019     1019     1019      1019      1019      1019  \n",
       "71      268      268      268      268       268       269       270  \n",
       "72      667      667      667      667       667       667       667  \n",
       "73      935      935      935      935       935       935       935  \n",
       "74      157      157      157      157       157       157       157  \n",
       "75      271      271      273      275       276       280       280  \n",
       "76       46       46       46       46        46        46        46  \n",
       "77       75       75       75       75        75        75        75  \n",
       "78       18       18       18       18        18        18        18  \n",
       "79      414      414      425      428       428       428       428  \n",
       "80      832      832      832      832       832       838       838  \n",
       "81     1025     1030     1036     1038      1048      1053      1056  \n",
       "82      206      206      206      206       206       208       208  \n",
       "83      710      713      713      718       721       722       723  \n",
       "84      242      242      242      244       244       245       245  \n",
       "85        1        1        1        1         1         1         1  \n",
       "86      902      902      902      902       902       902       902  \n",
       "87      211      211      211      211       211       211       211  \n",
       "88     1282     1283     1283     1283      1283      1283      1283  \n",
       "\n",
       "[33 rows x 269 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Country/Region']=='China']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "idx = df.groupby('Country/Region')[case_columns[-1]].transform(max) == df[case_columns[-1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "coord_df = df.loc[idx,df.columns[0:4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Hubei</td>\n",
       "      <td>China</td>\n",
       "      <td>30.9756</td>\n",
       "      <td>112.2707</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "   Province/State Country/Region      Lat      Long\n",
       "69          Hubei          China  30.9756  112.2707"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coord_df[coord_df['Country/Region']=='China']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.groupby('Country/Region')[case_columns].agg(sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>1/28/20</th>\n",
       "      <th>1/29/20</th>\n",
       "      <th>1/30/20</th>\n",
       "      <th>1/31/20</th>\n",
       "      <th>...</th>\n",
       "      <th>10/3/20</th>\n",
       "      <th>10/4/20</th>\n",
       "      <th>10/5/20</th>\n",
       "      <th>10/6/20</th>\n",
       "      <th>10/7/20</th>\n",
       "      <th>10/8/20</th>\n",
       "      <th>10/9/20</th>\n",
       "      <th>10/10/20</th>\n",
       "      <th>10/11/20</th>\n",
       "      <th>10/12/20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country/Region</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>39297</td>\n",
       "      <td>39341</td>\n",
       "      <td>39422</td>\n",
       "      <td>39486</td>\n",
       "      <td>39548</td>\n",
       "      <td>39616</td>\n",
       "      <td>39693</td>\n",
       "      <td>39703</td>\n",
       "      <td>39799</td>\n",
       "      <td>39870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14117</td>\n",
       "      <td>14266</td>\n",
       "      <td>14410</td>\n",
       "      <td>14568</td>\n",
       "      <td>14730</td>\n",
       "      <td>14899</td>\n",
       "      <td>15066</td>\n",
       "      <td>15231</td>\n",
       "      <td>15399</td>\n",
       "      <td>15570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>51995</td>\n",
       "      <td>52136</td>\n",
       "      <td>52270</td>\n",
       "      <td>52399</td>\n",
       "      <td>52520</td>\n",
       "      <td>52658</td>\n",
       "      <td>52804</td>\n",
       "      <td>52940</td>\n",
       "      <td>53072</td>\n",
       "      <td>53325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2110</td>\n",
       "      <td>2110</td>\n",
       "      <td>2370</td>\n",
       "      <td>2370</td>\n",
       "      <td>2568</td>\n",
       "      <td>2568</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5370</td>\n",
       "      <td>5402</td>\n",
       "      <td>5530</td>\n",
       "      <td>5725</td>\n",
       "      <td>5725</td>\n",
       "      <td>5958</td>\n",
       "      <td>6031</td>\n",
       "      <td>6246</td>\n",
       "      <td>6366</td>\n",
       "      <td>6488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>41078</td>\n",
       "      <td>41498</td>\n",
       "      <td>41957</td>\n",
       "      <td>42432</td>\n",
       "      <td>42840</td>\n",
       "      <td>43256</td>\n",
       "      <td>43664</td>\n",
       "      <td>43945</td>\n",
       "      <td>44299</td>\n",
       "      <td>44684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Sahara</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2041</td>\n",
       "      <td>2041</td>\n",
       "      <td>2041</td>\n",
       "      <td>2047</td>\n",
       "      <td>2049</td>\n",
       "      <td>2050</td>\n",
       "      <td>2051</td>\n",
       "      <td>2051</td>\n",
       "      <td>2052</td>\n",
       "      <td>2052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14974</td>\n",
       "      <td>15052</td>\n",
       "      <td>15089</td>\n",
       "      <td>15170</td>\n",
       "      <td>15224</td>\n",
       "      <td>15301</td>\n",
       "      <td>15339</td>\n",
       "      <td>15415</td>\n",
       "      <td>15458</td>\n",
       "      <td>15549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7885</td>\n",
       "      <td>7888</td>\n",
       "      <td>7898</td>\n",
       "      <td>7915</td>\n",
       "      <td>7919</td>\n",
       "      <td>7951</td>\n",
       "      <td>7994</td>\n",
       "      <td>8010</td>\n",
       "      <td>8011</td>\n",
       "      <td>8021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>189 rows × 265 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    1/22/20  1/23/20  1/24/20  1/25/20  1/26/20  1/27/20  \\\n",
       "Country/Region                                                             \n",
       "Afghanistan               0        0        0        0        0        0   \n",
       "Albania                   0        0        0        0        0        0   \n",
       "Algeria                   0        0        0        0        0        0   \n",
       "Andorra                   0        0        0        0        0        0   \n",
       "Angola                    0        0        0        0        0        0   \n",
       "...                     ...      ...      ...      ...      ...      ...   \n",
       "West Bank and Gaza        0        0        0        0        0        0   \n",
       "Western Sahara            0        0        0        0        0        0   \n",
       "Yemen                     0        0        0        0        0        0   \n",
       "Zambia                    0        0        0        0        0        0   \n",
       "Zimbabwe                  0        0        0        0        0        0   \n",
       "\n",
       "                    1/28/20  1/29/20  1/30/20  1/31/20  ...  10/3/20  10/4/20  \\\n",
       "Country/Region                                          ...                     \n",
       "Afghanistan               0        0        0        0  ...    39297    39341   \n",
       "Albania                   0        0        0        0  ...    14117    14266   \n",
       "Algeria                   0        0        0        0  ...    51995    52136   \n",
       "Andorra                   0        0        0        0  ...     2110     2110   \n",
       "Angola                    0        0        0        0  ...     5370     5402   \n",
       "...                     ...      ...      ...      ...  ...      ...      ...   \n",
       "West Bank and Gaza        0        0        0        0  ...    41078    41498   \n",
       "Western Sahara            0        0        0        0  ...       10       10   \n",
       "Yemen                     0        0        0        0  ...     2041     2041   \n",
       "Zambia                    0        0        0        0  ...    14974    15052   \n",
       "Zimbabwe                  0        0        0        0  ...     7885     7888   \n",
       "\n",
       "                    10/5/20  10/6/20  10/7/20  10/8/20  10/9/20  10/10/20  \\\n",
       "Country/Region                                                              \n",
       "Afghanistan           39422    39486    39548    39616    39693     39703   \n",
       "Albania               14410    14568    14730    14899    15066     15231   \n",
       "Algeria               52270    52399    52520    52658    52804     52940   \n",
       "Andorra                2370     2370     2568     2568     2696      2696   \n",
       "Angola                 5530     5725     5725     5958     6031      6246   \n",
       "...                     ...      ...      ...      ...      ...       ...   \n",
       "West Bank and Gaza    41957    42432    42840    43256    43664     43945   \n",
       "Western Sahara           10       10       10       10       10        10   \n",
       "Yemen                  2041     2047     2049     2050     2051      2051   \n",
       "Zambia                15089    15170    15224    15301    15339     15415   \n",
       "Zimbabwe               7898     7915     7919     7951     7994      8010   \n",
       "\n",
       "                    10/11/20  10/12/20  \n",
       "Country/Region                          \n",
       "Afghanistan            39799     39870  \n",
       "Albania                15399     15570  \n",
       "Algeria                53072     53325  \n",
       "Andorra                 2696      2995  \n",
       "Angola                  6366      6488  \n",
       "...                      ...       ...  \n",
       "West Bank and Gaza     44299     44684  \n",
       "Western Sahara            10        10  \n",
       "Yemen                   2052      2052  \n",
       "Zambia                 15458     15549  \n",
       "Zimbabwe                8011      8021  \n",
       "\n",
       "[189 rows x 265 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_population = pd.read_csv('data/population.csv',index_col=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Country/Region</th>\n",
       "      <th>Population</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>Italy</td>\n",
       "      <td>60421760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>10283822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World</th>\n",
       "      <td>World</td>\n",
       "      <td>7594270356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rwanda</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>12301939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bulgaria</th>\n",
       "      <td>Bulgaria</td>\n",
       "      <td>7025037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>Diamond Princess</th>\n",
       "      <td>Diamond Princess</td>\n",
       "      <td>3600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holy See</th>\n",
       "      <td>Holy See</td>\n",
       "      <td>825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan*</th>\n",
       "      <td>Taiwan*</td>\n",
       "      <td>23780000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Sahara</th>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>595060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS Zaandam</th>\n",
       "      <td>MS Zaandam</td>\n",
       "      <td>1829</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Country/Region  Population\n",
       "Italy                        Italy    60421760\n",
       "Portugal                  Portugal    10283822\n",
       "World                        World  7594270356\n",
       "Rwanda                      Rwanda    12301939\n",
       "Bulgaria                  Bulgaria     7025037\n",
       "...                            ...         ...\n",
       "Diamond Princess  Diamond Princess        3600\n",
       "Holy See                  Holy See         825\n",
       "Taiwan*                    Taiwan*    23780000\n",
       "Western Sahara      Western Sahara      595060\n",
       "MS Zaandam              MS Zaandam        1829\n",
       "\n",
       "[268 rows x 2 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_w_pop = df.merge(df_population, left_index=True,right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
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       "      <th>10/6/20</th>\n",
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       "      <th>10/8/20</th>\n",
       "      <th>10/9/20</th>\n",
       "      <th>10/10/20</th>\n",
       "      <th>10/11/20</th>\n",
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       "      <th>Country/Region</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>0</td>\n",
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       "      <td>39548</td>\n",
       "      <td>39616</td>\n",
       "      <td>39693</td>\n",
       "      <td>39703</td>\n",
       "      <td>39799</td>\n",
       "      <td>39870</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>37172386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>0</td>\n",
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       "      <td>14568</td>\n",
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       "      <td>14899</td>\n",
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       "      <td>15399</td>\n",
       "      <td>15570</td>\n",
       "      <td>Albania</td>\n",
       "      <td>2866376</td>\n",
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       "      <td>52270</td>\n",
       "      <td>52399</td>\n",
       "      <td>52520</td>\n",
       "      <td>52658</td>\n",
       "      <td>52804</td>\n",
       "      <td>52940</td>\n",
       "      <td>53072</td>\n",
       "      <td>53325</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>42228429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2370</td>\n",
       "      <td>2370</td>\n",
       "      <td>2568</td>\n",
       "      <td>2568</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2696</td>\n",
       "      <td>2995</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>77006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5530</td>\n",
       "      <td>5725</td>\n",
       "      <td>5725</td>\n",
       "      <td>5958</td>\n",
       "      <td>6031</td>\n",
       "      <td>6246</td>\n",
       "      <td>6366</td>\n",
       "      <td>6488</td>\n",
       "      <td>Angola</td>\n",
       "      <td>30809762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>41957</td>\n",
       "      <td>42432</td>\n",
       "      <td>42840</td>\n",
       "      <td>43256</td>\n",
       "      <td>43664</td>\n",
       "      <td>43945</td>\n",
       "      <td>44299</td>\n",
       "      <td>44684</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>4569087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Sahara</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>595060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2041</td>\n",
       "      <td>2047</td>\n",
       "      <td>2049</td>\n",
       "      <td>2050</td>\n",
       "      <td>2051</td>\n",
       "      <td>2051</td>\n",
       "      <td>2052</td>\n",
       "      <td>2052</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>28498687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15089</td>\n",
       "      <td>15170</td>\n",
       "      <td>15224</td>\n",
       "      <td>15301</td>\n",
       "      <td>15339</td>\n",
       "      <td>15415</td>\n",
       "      <td>15458</td>\n",
       "      <td>15549</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>17351822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7898</td>\n",
       "      <td>7915</td>\n",
       "      <td>7919</td>\n",
       "      <td>7951</td>\n",
       "      <td>7994</td>\n",
       "      <td>8010</td>\n",
       "      <td>8011</td>\n",
       "      <td>8021</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>14439018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>189 rows × 267 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    1/22/20  1/23/20  1/24/20  1/25/20  1/26/20  1/27/20  \\\n",
       "Afghanistan               0        0        0        0        0        0   \n",
       "Albania                   0        0        0        0        0        0   \n",
       "Algeria                   0        0        0        0        0        0   \n",
       "Andorra                   0        0        0        0        0        0   \n",
       "Angola                    0        0        0        0        0        0   \n",
       "...                     ...      ...      ...      ...      ...      ...   \n",
       "West Bank and Gaza        0        0        0        0        0        0   \n",
       "Western Sahara            0        0        0        0        0        0   \n",
       "Yemen                     0        0        0        0        0        0   \n",
       "Zambia                    0        0        0        0        0        0   \n",
       "Zimbabwe                  0        0        0        0        0        0   \n",
       "\n",
       "                    1/28/20  1/29/20  1/30/20  1/31/20  ...  10/5/20  10/6/20  \\\n",
       "Afghanistan               0        0        0        0  ...    39422    39486   \n",
       "Albania                   0        0        0        0  ...    14410    14568   \n",
       "Algeria                   0        0        0        0  ...    52270    52399   \n",
       "Andorra                   0        0        0        0  ...     2370     2370   \n",
       "Angola                    0        0        0        0  ...     5530     5725   \n",
       "...                     ...      ...      ...      ...  ...      ...      ...   \n",
       "West Bank and Gaza        0        0        0        0  ...    41957    42432   \n",
       "Western Sahara            0        0        0        0  ...       10       10   \n",
       "Yemen                     0        0        0        0  ...     2041     2047   \n",
       "Zambia                    0        0        0        0  ...    15089    15170   \n",
       "Zimbabwe                  0        0        0        0  ...     7898     7915   \n",
       "\n",
       "                    10/7/20  10/8/20  10/9/20  10/10/20  10/11/20  10/12/20  \\\n",
       "Afghanistan           39548    39616    39693     39703     39799     39870   \n",
       "Albania               14730    14899    15066     15231     15399     15570   \n",
       "Algeria               52520    52658    52804     52940     53072     53325   \n",
       "Andorra                2568     2568     2696      2696      2696      2995   \n",
       "Angola                 5725     5958     6031      6246      6366      6488   \n",
       "...                     ...      ...      ...       ...       ...       ...   \n",
       "West Bank and Gaza    42840    43256    43664     43945     44299     44684   \n",
       "Western Sahara           10       10       10        10        10        10   \n",
       "Yemen                  2049     2050     2051      2051      2052      2052   \n",
       "Zambia                15224    15301    15339     15415     15458     15549   \n",
       "Zimbabwe               7919     7951     7994      8010      8011      8021   \n",
       "\n",
       "                        Country/Region  Population  \n",
       "Afghanistan                Afghanistan    37172386  \n",
       "Albania                        Albania     2866376  \n",
       "Algeria                        Algeria    42228429  \n",
       "Andorra                        Andorra       77006  \n",
       "Angola                          Angola    30809762  \n",
       "...                                ...         ...  \n",
       "West Bank and Gaza  West Bank and Gaza     4569087  \n",
       "Western Sahara          Western Sahara      595060  \n",
       "Yemen                            Yemen    28498687  \n",
       "Zambia                          Zambia    17351822  \n",
       "Zimbabwe                      Zimbabwe    14439018  \n",
       "\n",
       "[189 rows x 267 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_w_pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Population    82905782\n",
       "Name: Germany, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pop_germany = df_w_pop.loc['Germany',['Population']]\n",
    "pop_germany"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f4233dbb9d0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "ax = df_w_pop.loc['Germany',case_columns].apply(lambda x: x/pop_germany).plot()\n",
    "ax.legend([\"Confirmed cases Germany per capita\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f4233d2ab50>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "ax = df_w_pop.loc['Germany',case_columns].apply(lambda x: x/(pop_germany/1e6)).plot()\n",
    "ax.legend([\"Confirmed cases Germany per million\"])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}