Final_Data_Shaping.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## COVID - 19 Data From Jhon Hopkins University  \n",
    "\n",
    "Data Link -> [GitHub](https://github.com/CSSEGISandData/COVID-19)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_case_link = \"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_link = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv\"\n",
    "recovered_link = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv\"\n",
    "consise_link = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/web-data/data/cases_country.csv\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Defining Some Utility Function to Sort and Clean Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dropoff(dfs, data_left):\n",
    "    for i in range(0, len(data_left)):\n",
    "        ele = data_left[i]\n",
    "        idx = dfs[dfs.country == ele].index\n",
    "        dfs.drop(idx, axis = 0, inplace = True)\n",
    "    \n",
    "    return dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def order_data(dframes):\n",
    "    dframe = pd.DataFrame(dframes)\n",
    "    dframe.drop(['Lat', 'Long'], axis = 1, inplace = True)\n",
    "    dframe.rename(columns={'Province/State':'province','Country/Region':'country'}, inplace = True)\n",
    "    \n",
    "    #----------------------------------------------------------\n",
    "    country_list = np.sort(np.array(dframe.country.unique()))\n",
    "    repeated = {}\n",
    "    rep_country = []\n",
    "    rep_first_dict = {}\n",
    "    \n",
    "    for i in range(0, len(country_list)):\n",
    "        idx = np.array(dframe[dframe.country == country_list[i]].index)\n",
    "        \n",
    "        if len(idx) > 1:\n",
    "            repeated[country_list[i]] = idx\n",
    "            rep_country.append(country_list[i])\n",
    "            rep_first_dict[idx[0]] = country_list[i]\n",
    "        \n",
    "        else:\n",
    "            continue\n",
    "    \n",
    "    #---------------------------------------------------------\n",
    "    to_drop = []\n",
    "    to_change = []\n",
    "    \n",
    "    for i in range(0, len(rep_country)):\n",
    "        nation = rep_country[i]\n",
    "        index = repeated[nation]\n",
    "        first_index = index[0]\n",
    "        to_change.append(first_index)\n",
    "        \n",
    "        last_index = index[1:]\n",
    "        for j in last_index:\n",
    "            to_drop.append(j)\n",
    "        \n",
    "        dframe.iloc[first_index] = np.sum(dframe.iloc[index], axis = 0)\n",
    "    \n",
    "    \n",
    "    #----------------------------------------------------------\n",
    "    for i in to_change:\n",
    "        dframe.loc[i, 'country'] = rep_first_dict[i]\n",
    "    \n",
    "    \n",
    "    #----------------------------------------------------------\n",
    "    dframe.drop(to_drop, inplace = True)\n",
    "    \n",
    "    \n",
    "    #----------------------------------------------------------\n",
    "    to_drop = ['Diamond Princess', 'Kosovo', 'MS Zaandam']\n",
    "\n",
    "    new_frame = dropoff(dframe, to_drop)\n",
    "    new_frame = dframe.drop(columns=['province'])\n",
    "    new_frame.set_index('country', inplace = True)\n",
    "    \n",
    "    #--------------------\n",
    "    return new_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_data(dframe, dframe1, dframe2):\n",
    "    cno = dframe.shape[0]\n",
    "    dno = dframe.shape[1]\n",
    "    entrys = cno*dno\n",
    "    date = np.array(dframe.columns)\n",
    "    country_list = np.array(dframe.index)\n",
    "    \n",
    "    nations = []\n",
    "    dates = []\n",
    "    values = []\n",
    "    deaths = []\n",
    "    recovery = []\n",
    "    \n",
    "    for i in range(0, cno):\n",
    "        for j in range(0, dno):\n",
    "            nations.append(country_list[i])\n",
    "            dates.append(date[j])\n",
    "            val = dframe.get_value(country_list[i], date[j])\n",
    "            values.append(val)\n",
    "    \n",
    "    for i in range(0, cno):\n",
    "        for j in range(0, dno):\n",
    "            val1 = dframe1.get_value(country_list[i], date[j])\n",
    "            recovery.append(val1)\n",
    "    \n",
    "    for i in range(0, cno):\n",
    "        for j in range(0, dno):\n",
    "            val2 = dframe2.get_value(country_list[i], date[j])\n",
    "            deaths.append(val2)\n",
    "    \n",
    "    values = np.array(values).astype(np.int32)\n",
    "    recovery = np.array(recovery).astype(np.int32)\n",
    "    deaths = np.array(deaths).astype(np.int32)\n",
    "    res = {'country':nations, 'date':dates, 'total_cases':values, 'recovered_cases':recovery, 'total_deaths':deaths}\n",
    "    rec = pd.DataFrame(res)\n",
    "    rec['date'] = pd.to_datetime(rec['date'])\n",
    "    rec.fillna(0)\n",
    "    \n",
    "    return rec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_timeSeries_data(total_case_link, recovered_link, deaths_link):\n",
    "    \n",
    "    total = pd.read_csv(total_case_link)\n",
    "    recovered = pd.read_csv(recovered_link)\n",
    "    deaths = pd.read_csv(deaths_link)\n",
    "\n",
    "    dframe = order_data(total)\n",
    "    dframe1 = order_data(recovered)\n",
    "    dframe2 = order_data(deaths)\n",
    "\n",
    "    df = clean_data(dframe, dframe1, dframe2)\n",
    "\n",
    "    to_drop = ['Diamond Princess', 'Kosovo', 'MS Zaandam']\n",
    "\n",
    "    df_final = dropoff(df, to_drop)\n",
    "\n",
    "    return df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_cumulativeCountry_data(consise_link):\n",
    "\n",
    "    datac = pd.read_csv(consise_link)\n",
    "    data = pd.DataFrame(datac)\n",
    "\n",
    "    data = data.drop(['People_Tested', 'People_Hospitalized'], axis =1)\n",
    "    data['Last_Update'] = pd.to_datetime(data['Last_Update']) \n",
    "    data = data.rename(columns = {'Country_Region':'country'})\n",
    "\n",
    "    to_drop_from_data = ['Diamond Princess', 'Kosovo', 'MS Zaandam']\n",
    "\n",
    "    cumulative = dropoff(data, to_drop_from_data)\n",
    "    \n",
    "    cumulative.set_index('country', inplace = True)\n",
    "\n",
    "    return cumulative"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading time series data into a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:18: FutureWarning: get_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:23: FutureWarning: get_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:28: FutureWarning: get_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n"
     ]
    }
   ],
   "source": [
    "df = get_timeSeries_data(total_case_link, recovered_link, deaths_link)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31815</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>91</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31816</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>91</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31817</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>134</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31818</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>184</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31819</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>184</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31820 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           country       date  total_cases  recovered_cases  total_deaths\n",
       "0      Afghanistan 2020-01-22            0                0             0\n",
       "1      Afghanistan 2020-01-23            0                0             0\n",
       "2      Afghanistan 2020-01-24            0                0             0\n",
       "3      Afghanistan 2020-01-25            0                0             0\n",
       "4      Afghanistan 2020-01-26            0                0             0\n",
       "...            ...        ...          ...              ...           ...\n",
       "31815      Lesotho 2020-07-07           91               11             0\n",
       "31816      Lesotho 2020-07-08           91               11             0\n",
       "31817      Lesotho 2020-07-09          134               20             1\n",
       "31818      Lesotho 2020-07-10          184               26             1\n",
       "31819      Lesotho 2020-07-11          184               26             1\n",
       "\n",
       "[31820 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading Cumulative COVID 19 country data into a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumulative = get_cumulativeCountry_data(consise_link)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Mortality_Rate</th>\n",
       "      <th>UID</th>\n",
       "      <th>ISO3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Australia</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>-25.000000</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>9797.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>7727.0</td>\n",
       "      <td>1962.0</td>\n",
       "      <td>38.480422</td>\n",
       "      <td>1.102378</td>\n",
       "      <td>36</td>\n",
       "      <td>AUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Austria</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>47.516200</td>\n",
       "      <td>14.550100</td>\n",
       "      <td>18783.0</td>\n",
       "      <td>706.0</td>\n",
       "      <td>16864.0</td>\n",
       "      <td>1213.0</td>\n",
       "      <td>208.551697</td>\n",
       "      <td>3.758718</td>\n",
       "      <td>40</td>\n",
       "      <td>AUT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Canada</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>60.001000</td>\n",
       "      <td>-95.001000</td>\n",
       "      <td>109150.0</td>\n",
       "      <td>8818.0</td>\n",
       "      <td>72784.0</td>\n",
       "      <td>27549.0</td>\n",
       "      <td>288.331729</td>\n",
       "      <td>8.078791</td>\n",
       "      <td>124</td>\n",
       "      <td>CAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>30.592800</td>\n",
       "      <td>114.305500</td>\n",
       "      <td>85071.0</td>\n",
       "      <td>4641.0</td>\n",
       "      <td>79876.0</td>\n",
       "      <td>554.0</td>\n",
       "      <td>6.056271</td>\n",
       "      <td>5.455443</td>\n",
       "      <td>156</td>\n",
       "      <td>CHN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Denmark</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>56.263900</td>\n",
       "      <td>9.501800</td>\n",
       "      <td>13147.0</td>\n",
       "      <td>609.0</td>\n",
       "      <td>12278.0</td>\n",
       "      <td>260.0</td>\n",
       "      <td>226.977542</td>\n",
       "      <td>4.632235</td>\n",
       "      <td>208</td>\n",
       "      <td>DNK</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>31.952200</td>\n",
       "      <td>35.233200</td>\n",
       "      <td>5931.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>5362.0</td>\n",
       "      <td>116.261838</td>\n",
       "      <td>0.556399</td>\n",
       "      <td>275</td>\n",
       "      <td>PSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>24.215500</td>\n",
       "      <td>-12.885800</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.674116</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>732</td>\n",
       "      <td>ESH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Yemen</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>15.552727</td>\n",
       "      <td>48.516388</td>\n",
       "      <td>1389.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>382.0</td>\n",
       "      <td>4.657016</td>\n",
       "      <td>26.277898</td>\n",
       "      <td>887</td>\n",
       "      <td>YEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Zambia</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>-13.133897</td>\n",
       "      <td>27.849332</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1348.0</td>\n",
       "      <td>505.0</td>\n",
       "      <td>10.307901</td>\n",
       "      <td>2.216359</td>\n",
       "      <td>894</td>\n",
       "      <td>ZMB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020-07-12 05:34:33</td>\n",
       "      <td>-19.015438</td>\n",
       "      <td>29.154857</td>\n",
       "      <td>982.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>644.0</td>\n",
       "      <td>6.607043</td>\n",
       "      <td>1.832994</td>\n",
       "      <td>716</td>\n",
       "      <td>ZWE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>185 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Last_Update        Lat       Long_  Confirmed  \\\n",
       "country                                                                    \n",
       "Australia          2020-07-12 05:34:33 -25.000000  133.000000     9797.0   \n",
       "Austria            2020-07-12 05:34:33  47.516200   14.550100    18783.0   \n",
       "Canada             2020-07-12 05:34:33  60.001000  -95.001000   109150.0   \n",
       "China              2020-07-12 05:34:33  30.592800  114.305500    85071.0   \n",
       "Denmark            2020-07-12 05:34:33  56.263900    9.501800    13147.0   \n",
       "...                                ...        ...         ...        ...   \n",
       "West Bank and Gaza 2020-07-12 05:34:33  31.952200   35.233200     5931.0   \n",
       "Western Sahara     2020-07-12 05:34:33  24.215500  -12.885800       10.0   \n",
       "Yemen              2020-07-12 05:34:33  15.552727   48.516388     1389.0   \n",
       "Zambia             2020-07-12 05:34:33 -13.133897   27.849332     1895.0   \n",
       "Zimbabwe           2020-07-12 05:34:33 -19.015438   29.154857      982.0   \n",
       "\n",
       "                    Deaths  Recovered   Active  Incident_Rate  Mortality_Rate  \\\n",
       "country                                                                         \n",
       "Australia            108.0     7727.0   1962.0      38.480422        1.102378   \n",
       "Austria              706.0    16864.0   1213.0     208.551697        3.758718   \n",
       "Canada              8818.0    72784.0  27549.0     288.331729        8.078791   \n",
       "China               4641.0    79876.0    554.0       6.056271        5.455443   \n",
       "Denmark              609.0    12278.0    260.0     226.977542        4.632235   \n",
       "...                    ...        ...      ...            ...             ...   \n",
       "West Bank and Gaza    33.0      536.0   5362.0     116.261838        0.556399   \n",
       "Western Sahara         1.0        8.0      1.0       1.674116       10.000000   \n",
       "Yemen                365.0      642.0    382.0       4.657016       26.277898   \n",
       "Zambia                42.0     1348.0    505.0      10.307901        2.216359   \n",
       "Zimbabwe              18.0      320.0    644.0       6.607043        1.832994   \n",
       "\n",
       "                    UID ISO3  \n",
       "country                       \n",
       "Australia            36  AUS  \n",
       "Austria              40  AUT  \n",
       "Canada              124  CAN  \n",
       "China               156  CHN  \n",
       "Denmark             208  DNK  \n",
       "...                 ...  ...  \n",
       "West Bank and Gaza  275  PSE  \n",
       "Western Sahara      732  ESH  \n",
       "Yemen               887  YEM  \n",
       "Zambia              894  ZMB  \n",
       "Zimbabwe            716  ZWE  \n",
       "\n",
       "[185 rows x 11 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cumulative"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing Population Data"
   ]
  },
  {
   "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>population</th>\n",
       "      <th>median_age</th>\n",
       "      <th>urban_percentage_share</th>\n",
       "      <th>world_share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>China</td>\n",
       "      <td>1438207241</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>India</td>\n",
       "      <td>1377233523</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>US</td>\n",
       "      <td>330610570</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Indonesia</td>\n",
       "      <td>272931713</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Pakistan</td>\n",
       "      <td>219992900</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>53123</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>33 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Monaco</td>\n",
       "      <td>39186</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Liechtenstein</td>\n",
       "      <td>38106</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>15 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>San Marino</td>\n",
       "      <td>33917</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>97 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Holy See</td>\n",
       "      <td>801</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>185 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       population median_age urban_percentage_share  \\\n",
       "country                                                               \n",
       "China                  1438207241         38                   61 %   \n",
       "India                  1377233523         28                   35 %   \n",
       "US                      330610570         38                   83 %   \n",
       "Indonesia               272931713         30                   56 %   \n",
       "Pakistan                219992900         23                   35 %   \n",
       "...                           ...        ...                    ...   \n",
       "Saint Kitts and Nevis       53123       N.A.                   33 %   \n",
       "Monaco                      39186       N.A.                   N.A.   \n",
       "Liechtenstein               38106       N.A.                   15 %   \n",
       "San Marino                  33917       N.A.                   97 %   \n",
       "Holy See                      801       N.A.                   N.A.   \n",
       "\n",
       "                      world_share  \n",
       "country                            \n",
       "China                     18.47 %  \n",
       "India                     17.70 %  \n",
       "US                         4.25 %  \n",
       "Indonesia                  3.51 %  \n",
       "Pakistan                   2.83 %  \n",
       "...                           ...  \n",
       "Saint Kitts and Nevis      0.00 %  \n",
       "Monaco                     0.00 %  \n",
       "Liechtenstein              0.00 %  \n",
       "San Marino                 0.00 %  \n",
       "Holy See                   0.00 %  \n",
       "\n",
       "[185 rows x 4 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population = pd.read_csv('population_data.csv')\n",
    "population.drop(['Unnamed: 0'], axis = 1, inplace = True)\n",
    "population.set_index('country', inplace = True)\n",
    "population"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Studying Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "61 %\n",
      "35 %\n",
      "83 %\n",
      "56 %\n",
      "35 %\n",
      "88 %\n",
      "52 %\n",
      "39 %\n",
      "74 %\n",
      "84 %\n",
      "92 %\n",
      "21 %\n",
      "47 %\n",
      "43 %\n",
      "38 %\n",
      "46 %\n",
      "76 %\n",
      "76 %\n",
      "76 %\n",
      "51 %\n",
      "83 %\n",
      "82 %\n",
      "69 %\n",
      "37 %\n",
      "67 %\n",
      "31 %\n",
      "28 %\n",
      "82 %\n",
      "80 %\n",
      "80 %\n",
      "26 %\n",
      "93 %\n",
      "73 %\n",
      "35 %\n",
      "69 %\n",
      "73 %\n",
      "25 %\n",
      "60 %\n",
      "81 %\n",
      "64 %\n",
      "84 %\n",
      "50 %\n",
      "79 %\n",
      "67 %\n",
      "78 %\n",
      "38 %\n",
      "57 %\n",
      "38 %\n",
      "21 %\n",
      "N.A.\n",
      "39 %\n",
      "56 %\n",
      "51 %\n",
      "86 %\n",
      "17 %\n",
      "79 %\n",
      "18 %\n",
      "31 %\n",
      "44 %\n",
      "55 %\n",
      "18 %\n",
      "85 %\n",
      "58 %\n",
      "45 %\n",
      "52 %\n",
      "63 %\n",
      "60 %\n",
      "92 %\n",
      "49 %\n",
      "24 %\n",
      "23 %\n",
      "47 %\n",
      "38 %\n",
      "39 %\n",
      "18 %\n",
      "48 %\n",
      "14 %\n",
      "70 %\n",
      "69 %\n",
      "98 %\n",
      "57 %\n",
      "78 %\n",
      "25 %\n",
      "85 %\n",
      "74 %\n",
      "85 %\n",
      "91 %\n",
      "66 %\n",
      "56 %\n",
      "88 %\n",
      "57 %\n",
      "86 %\n",
      "72 %\n",
      "27 %\n",
      "79 %\n",
      "57 %\n",
      "13 %\n",
      "56 %\n",
      "93 %\n",
      "74 %\n",
      "43 %\n",
      "43 %\n",
      "36 %\n",
      "62 %\n",
      "76 %\n",
      "78 %\n",
      "78 %\n",
      "57 %\n",
      "36 %\n",
      "73 %\n",
      "N.A.\n",
      "88 %\n",
      "86 %\n",
      "70 %\n",
      "54 %\n",
      "83 %\n",
      "87 %\n",
      "80 %\n",
      "80 %\n",
      "53 %\n",
      "63 %\n",
      "43 %\n",
      "87 %\n",
      "57 %\n",
      "68 %\n",
      "N.A.\n",
      "58 %\n",
      "43 %\n",
      "58 %\n",
      "63 %\n",
      "96 %\n",
      "52 %\n",
      "67 %\n",
      "63 %\n",
      "55 %\n",
      "96 %\n",
      "63 %\n",
      "71 %\n",
      "55 %\n",
      "59 %\n",
      "73 %\n",
      "87 %\n",
      "31 %\n",
      "59 %\n",
      "55 %\n",
      "45 %\n",
      "69 %\n",
      "89 %\n",
      "73 %\n",
      "52 %\n",
      "68 %\n",
      "33 %\n",
      "41 %\n",
      "67 %\n",
      "30 %\n",
      "79 %\n",
      "59 %\n",
      "29 %\n",
      "27 %\n",
      "46 %\n",
      "68 %\n",
      "88 %\n",
      "87 %\n",
      "65 %\n",
      "68 %\n",
      "35 %\n",
      "93 %\n",
      "80 %\n",
      "46 %\n",
      "86 %\n",
      "94 %\n",
      "31 %\n",
      "74 %\n",
      "19 %\n",
      "35 %\n",
      "53 %\n",
      "56 %\n",
      "26 %\n",
      "88 %\n",
      "74 %\n",
      "33 %\n",
      "N.A.\n",
      "15 %\n",
      "97 %\n",
      "N.A.\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 185):\n",
    "    print(population['urban_percentage_share'][i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "38  years\n",
      "28  years\n",
      "38  years\n",
      "30  years\n",
      "23  years\n",
      "33  years\n",
      "18  years\n",
      "28  years\n",
      "40  years\n",
      "29  years\n",
      "48  years\n",
      "19  years\n",
      "26  years\n",
      "25  years\n",
      "32  years\n",
      "17  years\n",
      "32  years\n",
      "32  years\n",
      "46  years\n",
      "40  years\n",
      "40  years\n",
      "42  years\n",
      "47  years\n",
      "18  years\n",
      "28  years\n",
      "29  years\n",
      "20  years\n",
      "44  years\n",
      "31  years\n",
      "45  years\n",
      "17  years\n",
      "32  years\n",
      "29  years\n",
      "20  years\n",
      "41  years\n",
      "21  years\n",
      "18  years\n",
      "42  years\n",
      "41  years\n",
      "30  years\n",
      "32  years\n",
      "28  years\n",
      "31  years\n",
      "17  years\n",
      "30  years\n",
      "18  years\n",
      "22  years\n",
      "20  years\n",
      "25  years\n",
      "30  years\n",
      "20  years\n",
      "19  years\n",
      "19  years\n",
      "38  years\n",
      "15  years\n",
      "42  years\n",
      "34  years\n",
      "18  years\n",
      "16  years\n",
      "43  years\n",
      "18  years\n",
      "35  years\n",
      "31  years\n",
      "18  years\n",
      "23  years\n",
      "28  years\n",
      "26  years\n",
      "43  years\n",
      "19  years\n",
      "26  years\n",
      "17  years\n",
      "17  years\n",
      "19  years\n",
      "18  years\n",
      "20  years\n",
      "19  years\n",
      "17  years\n",
      "33  years\n",
      "26  years\n",
      "42  years\n",
      "24  years\n",
      "42  years\n",
      "19  years\n",
      "28  years\n",
      "43  years\n",
      "46  years\n",
      "24  years\n",
      "46  years\n",
      "32  years\n",
      "41  years\n",
      "24  years\n",
      "33  years\n",
      "43  years\n",
      "22  years\n",
      "40  years\n",
      "43  years\n",
      "22  years\n",
      "42  years\n",
      "30  years\n",
      "43  years\n",
      "19  years\n",
      "19  years\n",
      "24  years\n",
      "26  years\n",
      "45  years\n",
      "29  years\n",
      "30  years\n",
      "26  years\n",
      "26  years\n",
      "28  years\n",
      "42  years\n",
      "42  years\n",
      "43  years\n",
      "19  years\n",
      "41  years\n",
      "40  years\n",
      "31  years\n",
      "21  years\n",
      "33  years\n",
      "19  years\n",
      "38  years\n",
      "18  years\n",
      "38  years\n",
      "20  years\n",
      "30  years\n",
      "37  years\n",
      "44  years\n",
      "38  years\n",
      "38  years\n",
      "19  years\n",
      "36  years\n",
      "43  years\n",
      "28  years\n",
      "35  years\n",
      "31  years\n",
      "32  years\n",
      "36  years\n",
      "45  years\n",
      "22  years\n",
      "18  years\n",
      "24  years\n",
      "23  years\n",
      "24  years\n",
      "39  years\n",
      "45  years\n",
      "19  years\n",
      "44  years\n",
      "32  years\n",
      "22  years\n",
      "36  years\n",
      "42  years\n",
      "21  years\n",
      "37  years\n",
      "37  years\n",
      "21  years\n",
      "27  years\n",
      "28  years\n",
      "20  years\n",
      "27  years\n",
      "28  years\n",
      "39  years\n",
      "40  years\n",
      "28  years\n",
      "29  years\n",
      "28  years\n",
      "30  years\n",
      "43  years\n",
      "32  years\n",
      "25  years\n",
      "32  years\n",
      "37  years\n",
      "40  years\n",
      "19  years\n",
      "34  years\n",
      "32  years\n",
      "33  years\n",
      "34  years\n",
      "34  years\n",
      "N.A.  years\n",
      "N.A.  years\n",
      "N.A.  years\n",
      "N.A.  years\n",
      "N.A.  years\n",
      "N.A.  years\n",
      "N.A.  years\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 185):\n",
    "    print(population['median_age'][i], \" years\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       country       date  total_cases  recovered_cases  total_deaths\n",
       "0  Afghanistan 2020-01-22            0                0             0\n",
       "1  Afghanistan 2020-01-23            0                0             0\n",
       "2  Afghanistan 2020-01-24            0                0             0\n",
       "3  Afghanistan 2020-01-25            0                0             0\n",
       "4  Afghanistan 2020-01-26            0                0             0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if __name__ == '__main__':\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # Remove the CWD from sys.path while we load stuff.\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # This is added back by InteractiveShellApp.init_path()\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in longlong_scalars\n",
      "  if sys.path[0] == '':\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if sys.path[0] == '':\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\pandas\\core\\indexing.py:205: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in longlong_scalars\n",
      "  if sys.path[0] == '':\n"
     ]
    }
   ],
   "source": [
    "df['new_reported_cases'] = [0]*df.shape[0]\n",
    "df['daily_recovered_cases'] = [0]*df.shape[0]\n",
    "df['daily_deaths'] = [0]*df.shape[0]\n",
    "df['active_cases'] = [0]*df.shape[0]\n",
    "df['cases_growth_rate_in_percent'] = [0]*df.shape[0]\n",
    "\n",
    "for i in range(1, df.shape[0]):\n",
    "    df['new_reported_cases'][i] = df['total_cases'][i] -df['total_cases'][i-1] \n",
    "    df['daily_recovered_cases'][i] = df['recovered_cases'][i] -df['recovered_cases'][i-1]\n",
    "    df['daily_deaths'][i] = df['total_deaths'][i] -df['total_deaths'][i-1]\n",
    "    df['active_cases'][i] = df['total_cases'][i] -df['recovered_cases'][i] - df['total_deaths'][i]\n",
    "    df['cases_growth_rate_in_percent'][i] = (df['new_reported_cases'][i]/df['total_cases'][i-1])*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "       country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "0  Afghanistan 2020-01-22            0                0             0   \n",
       "1  Afghanistan 2020-01-23            0                0             0   \n",
       "2  Afghanistan 2020-01-24            0                0             0   \n",
       "3  Afghanistan 2020-01-25            0                0             0   \n",
       "4  Afghanistan 2020-01-26            0                0             0   \n",
       "\n",
       "   new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "0                   0                      0             0             0   \n",
       "1                   0                      0             0             0   \n",
       "2                   0                      0             0             0   \n",
       "3                   0                      0             0             0   \n",
       "4                   0                      0             0             0   \n",
       "\n",
       "   cases_growth_rate_in_percent  \n",
       "0                           0.0  \n",
       "1                           NaN  \n",
       "2                           NaN  \n",
       "3                           NaN  \n",
       "4                           NaN  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days = int(df.shape[0]/185)\n",
    "indexs1 = []\n",
    "for i in range(0,185):\n",
    "    indexs1.append(i*days)\n",
    "\n",
    "\n",
    "df.loc[indexs1 , 'new_reported_cases'] = 0\n",
    "df.loc[indexs1 , 'daily_recovered_cases'] = 0\n",
    "df.loc[indexs1 , 'daily_deaths'] = 0\n",
    "df.loc[indexs1 , 'cases_growth_rate_in_percent'] = 0\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['mortality_rate'] = df['total_deaths']/df['total_cases']*100\n",
    "df['recovery_rate'] = df['recovered_cases']/df['total_cases']*100\n",
    "df = df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "      <td>12207</td>\n",
       "      <td>India</td>\n",
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       "      <td>742417</td>\n",
       "      <td>456831</td>\n",
       "      <td>20642</td>\n",
       "      <td>22753</td>\n",
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       "      <td>264944</td>\n",
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       "      <td>12208</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>767296</td>\n",
       "      <td>476378</td>\n",
       "      <td>21129</td>\n",
       "      <td>24879</td>\n",
       "      <td>19547</td>\n",
       "      <td>487</td>\n",
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       "      <td>62.085297</td>\n",
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       "      <td>12209</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>793802</td>\n",
       "      <td>495513</td>\n",
       "      <td>21604</td>\n",
       "      <td>26506</td>\n",
       "      <td>19135</td>\n",
       "      <td>475</td>\n",
       "      <td>276685</td>\n",
       "      <td>3.454469</td>\n",
       "      <td>2.721585</td>\n",
       "      <td>62.422745</td>\n",
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       "    <tr>\n",
       "      <td>12210</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>820916</td>\n",
       "      <td>515386</td>\n",
       "      <td>22123</td>\n",
       "      <td>27114</td>\n",
       "      <td>19873</td>\n",
       "      <td>519</td>\n",
       "      <td>283407</td>\n",
       "      <td>3.415713</td>\n",
       "      <td>2.694916</td>\n",
       "      <td>62.781819</td>\n",
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       "      <td>12211</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>849522</td>\n",
       "      <td>534618</td>\n",
       "      <td>22673</td>\n",
       "      <td>28606</td>\n",
       "      <td>19232</td>\n",
       "      <td>550</td>\n",
       "      <td>292231</td>\n",
       "      <td>3.484644</td>\n",
       "      <td>2.668913</td>\n",
       "      <td>62.931625</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "12040   India 2020-01-22            0                0             0   \n",
       "12041   India 2020-01-23            0                0             0   \n",
       "12042   India 2020-01-24            0                0             0   \n",
       "12043   India 2020-01-25            0                0             0   \n",
       "12044   India 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "12207   India 2020-07-07       742417           456831         20642   \n",
       "12208   India 2020-07-08       767296           476378         21129   \n",
       "12209   India 2020-07-09       793802           495513         21604   \n",
       "12210   India 2020-07-10       820916           515386         22123   \n",
       "12211   India 2020-07-11       849522           534618         22673   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "12040                   0                      0             0             0   \n",
       "12041                   0                      0             0             0   \n",
       "12042                   0                      0             0             0   \n",
       "12043                   0                      0             0             0   \n",
       "12044                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "12207               22753                  16897           483        264944   \n",
       "12208               24879                  19547           487        269789   \n",
       "12209               26506                  19135           475        276685   \n",
       "12210               27114                  19873           519        283407   \n",
       "12211               28606                  19232           550        292231   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \n",
       "12040                      0.000000        0.000000       0.000000  \n",
       "12041                      0.000000        0.000000       0.000000  \n",
       "12042                      0.000000        0.000000       0.000000  \n",
       "12043                      0.000000        0.000000       0.000000  \n",
       "12044                      0.000000        0.000000       0.000000  \n",
       "...                             ...             ...            ...  \n",
       "12207                      3.161614        2.780378      61.532939  \n",
       "12208                      3.351082        2.753696      62.085297  \n",
       "12209                      3.454469        2.721585      62.422745  \n",
       "12210                      3.415713        2.694916      62.781819  \n",
       "12211                      3.484644        2.668913      62.931625  \n",
       "\n",
       "[172 rows x 12 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'India']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Calulating doubling time\n",
    "to_remove = []\n",
    "for i in range(0,185):\n",
    "    for j in range(0,6):\n",
    "        to_remove.append((i*days) + j)\n",
    "\n",
    "\n",
    "r_avg = df['cases_growth_rate_in_percent'].rolling(7).mean()\n",
    "dbl = np.log(2)/np.log(1 + (r_avg/100))\n",
    "df['doubling_time_in_days'] = dbl\n",
    "df.loc[to_remove, 'doubling_time_in_days'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
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       "      <td>12208</td>\n",
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       "      <td>767296</td>\n",
       "      <td>476378</td>\n",
       "      <td>21129</td>\n",
       "      <td>24879</td>\n",
       "      <td>19547</td>\n",
       "      <td>487</td>\n",
       "      <td>269789</td>\n",
       "      <td>3.351082</td>\n",
       "      <td>2.753696</td>\n",
       "      <td>62.085297</td>\n",
       "      <td>20.364878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12209</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>793802</td>\n",
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       "      <td>21604</td>\n",
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       "    <tr>\n",
       "      <td>12210</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>820916</td>\n",
       "      <td>515386</td>\n",
       "      <td>22123</td>\n",
       "      <td>27114</td>\n",
       "      <td>19873</td>\n",
       "      <td>519</td>\n",
       "      <td>283407</td>\n",
       "      <td>3.415713</td>\n",
       "      <td>2.694916</td>\n",
       "      <td>62.781819</td>\n",
       "      <td>20.554273</td>\n",
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       "    <tr>\n",
       "      <td>12211</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>849522</td>\n",
       "      <td>534618</td>\n",
       "      <td>22673</td>\n",
       "      <td>28606</td>\n",
       "      <td>19232</td>\n",
       "      <td>550</td>\n",
       "      <td>292231</td>\n",
       "      <td>3.484644</td>\n",
       "      <td>2.668913</td>\n",
       "      <td>62.931625</td>\n",
       "      <td>20.851866</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "12040   India 2020-01-22            0                0             0   \n",
       "12041   India 2020-01-23            0                0             0   \n",
       "12042   India 2020-01-24            0                0             0   \n",
       "12043   India 2020-01-25            0                0             0   \n",
       "12044   India 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "12207   India 2020-07-07       742417           456831         20642   \n",
       "12208   India 2020-07-08       767296           476378         21129   \n",
       "12209   India 2020-07-09       793802           495513         21604   \n",
       "12210   India 2020-07-10       820916           515386         22123   \n",
       "12211   India 2020-07-11       849522           534618         22673   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "12040                   0                      0             0             0   \n",
       "12041                   0                      0             0             0   \n",
       "12042                   0                      0             0             0   \n",
       "12043                   0                      0             0             0   \n",
       "12044                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "12207               22753                  16897           483        264944   \n",
       "12208               24879                  19547           487        269789   \n",
       "12209               26506                  19135           475        276685   \n",
       "12210               27114                  19873           519        283407   \n",
       "12211               28606                  19232           550        292231   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "12040                      0.000000        0.000000       0.000000   \n",
       "12041                      0.000000        0.000000       0.000000   \n",
       "12042                      0.000000        0.000000       0.000000   \n",
       "12043                      0.000000        0.000000       0.000000   \n",
       "12044                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "12207                      3.161614        2.780378      61.532939   \n",
       "12208                      3.351082        2.753696      62.085297   \n",
       "12209                      3.454469        2.721585      62.422745   \n",
       "12210                      3.415713        2.694916      62.781819   \n",
       "12211                      3.484644        2.668913      62.931625   \n",
       "\n",
       "       doubling_time_in_days  \n",
       "12040               0.000000  \n",
       "12041               0.000000  \n",
       "12042               0.000000  \n",
       "12043               0.000000  \n",
       "12044               0.000000  \n",
       "...                      ...  \n",
       "12207              20.429991  \n",
       "12208              20.364878  \n",
       "12209              20.367046  \n",
       "12210              20.554273  \n",
       "12211              20.851866  \n",
       "\n",
       "[172 rows x 13 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'India']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#adding active cases per million and total cases per million\n",
    "cases_per_million = []\n",
    "active_cases_per_million = []\n",
    "population_share = []\n",
    "\n",
    "for i in range(0, df.shape[0]):\n",
    "    cntry = df['country'][i]\n",
    "    cases = df['total_cases'][i]\n",
    "    active = df['active_cases'][i]\n",
    "    population_size = population['population'][cntry]\n",
    "    share = population['world_share'][cntry]\n",
    "    \n",
    "    entry_cases = cases/population_size*1000000\n",
    "    cases_per_million.append(entry_cases)\n",
    "    \n",
    "    entry_active = active/population_size*1000000\n",
    "    active_cases_per_million.append(entry_active)\n",
    "    \n",
    "    population_share.append(share)\n",
    "\n",
    "df['total_cases_per_million'] = cases_per_million\n",
    "df['active_cases_per_million'] = active_cases_per_million\n",
    "df['world_population_share'] = population_share"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "      <td>12208</td>\n",
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       "      <td>557.128466</td>\n",
       "      <td>195.891979</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>12210</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>820916</td>\n",
       "      <td>515386</td>\n",
       "      <td>22123</td>\n",
       "      <td>27114</td>\n",
       "      <td>19873</td>\n",
       "      <td>519</td>\n",
       "      <td>283407</td>\n",
       "      <td>3.415713</td>\n",
       "      <td>2.694916</td>\n",
       "      <td>62.781819</td>\n",
       "      <td>20.554273</td>\n",
       "      <td>596.061587</td>\n",
       "      <td>205.779917</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12211</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>849522</td>\n",
       "      <td>534618</td>\n",
       "      <td>22673</td>\n",
       "      <td>28606</td>\n",
       "      <td>19232</td>\n",
       "      <td>550</td>\n",
       "      <td>292231</td>\n",
       "      <td>3.484644</td>\n",
       "      <td>2.668913</td>\n",
       "      <td>62.931625</td>\n",
       "      <td>20.851866</td>\n",
       "      <td>616.832212</td>\n",
       "      <td>212.186964</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "12040   India 2020-01-22            0                0             0   \n",
       "12041   India 2020-01-23            0                0             0   \n",
       "12042   India 2020-01-24            0                0             0   \n",
       "12043   India 2020-01-25            0                0             0   \n",
       "12044   India 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "12207   India 2020-07-07       742417           456831         20642   \n",
       "12208   India 2020-07-08       767296           476378         21129   \n",
       "12209   India 2020-07-09       793802           495513         21604   \n",
       "12210   India 2020-07-10       820916           515386         22123   \n",
       "12211   India 2020-07-11       849522           534618         22673   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "12040                   0                      0             0             0   \n",
       "12041                   0                      0             0             0   \n",
       "12042                   0                      0             0             0   \n",
       "12043                   0                      0             0             0   \n",
       "12044                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "12207               22753                  16897           483        264944   \n",
       "12208               24879                  19547           487        269789   \n",
       "12209               26506                  19135           475        276685   \n",
       "12210               27114                  19873           519        283407   \n",
       "12211               28606                  19232           550        292231   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "12040                      0.000000        0.000000       0.000000   \n",
       "12041                      0.000000        0.000000       0.000000   \n",
       "12042                      0.000000        0.000000       0.000000   \n",
       "12043                      0.000000        0.000000       0.000000   \n",
       "12044                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "12207                      3.161614        2.780378      61.532939   \n",
       "12208                      3.351082        2.753696      62.085297   \n",
       "12209                      3.454469        2.721585      62.422745   \n",
       "12210                      3.415713        2.694916      62.781819   \n",
       "12211                      3.484644        2.668913      62.931625   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "12040               0.000000                 0.000000   \n",
       "12041               0.000000                 0.000000   \n",
       "12042               0.000000                 0.000000   \n",
       "12043               0.000000                 0.000000   \n",
       "12044               0.000000                 0.000000   \n",
       "...                      ...                      ...   \n",
       "12207              20.429991               539.063991   \n",
       "12208              20.364878               557.128466   \n",
       "12209              20.367046               576.374294   \n",
       "12210              20.554273               596.061587   \n",
       "12211              20.851866               616.832212   \n",
       "\n",
       "       active_cases_per_million world_population_share  \n",
       "12040                  0.000000                17.70 %  \n",
       "12041                  0.000000                17.70 %  \n",
       "12042                  0.000000                17.70 %  \n",
       "12043                  0.000000                17.70 %  \n",
       "12044                  0.000000                17.70 %  \n",
       "...                         ...                    ...  \n",
       "12207                192.374057                17.70 %  \n",
       "12208                195.891979                17.70 %  \n",
       "12209                200.899118                17.70 %  \n",
       "12210                205.779917                17.70 %  \n",
       "12211                212.186964                17.70 %  \n",
       "\n",
       "[172 rows x 16 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'India']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_reported_cases</th>\n",
       "      <th>daily_recovered_cases</th>\n",
       "      <th>daily_deaths</th>\n",
       "      <th>active_cases</th>\n",
       "      <th>cases_growth_rate_in_percent</th>\n",
       "      <th>mortality_rate</th>\n",
       "      <th>recovery_rate</th>\n",
       "      <th>doubling_time_in_days</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>active_cases_per_million</th>\n",
       "      <th>world_population_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>26660</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003025</td>\n",
       "      <td>0.003025</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26661</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003025</td>\n",
       "      <td>0.003025</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26662</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26663</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26664</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015124</td>\n",
       "      <td>0.015124</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>26827</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>2996098</td>\n",
       "      <td>936476</td>\n",
       "      <td>131480</td>\n",
       "      <td>60021</td>\n",
       "      <td>12328</td>\n",
       "      <td>1195</td>\n",
       "      <td>1928142</td>\n",
       "      <td>2.044258</td>\n",
       "      <td>4.388374</td>\n",
       "      <td>31.256521</td>\n",
       "      <td>37.935536</td>\n",
       "      <td>9062.317639</td>\n",
       "      <td>5832.063990</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26828</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>3054699</td>\n",
       "      <td>953462</td>\n",
       "      <td>132300</td>\n",
       "      <td>58601</td>\n",
       "      <td>16986</td>\n",
       "      <td>820</td>\n",
       "      <td>1968937</td>\n",
       "      <td>1.955911</td>\n",
       "      <td>4.331032</td>\n",
       "      <td>31.212961</td>\n",
       "      <td>37.892295</td>\n",
       "      <td>9239.568475</td>\n",
       "      <td>5955.456899</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26829</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>3117946</td>\n",
       "      <td>969111</td>\n",
       "      <td>133290</td>\n",
       "      <td>63247</td>\n",
       "      <td>15649</td>\n",
       "      <td>990</td>\n",
       "      <td>2015545</td>\n",
       "      <td>2.070482</td>\n",
       "      <td>4.274930</td>\n",
       "      <td>31.081712</td>\n",
       "      <td>37.764615</td>\n",
       "      <td>9430.872098</td>\n",
       "      <td>6096.432428</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26830</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>3184573</td>\n",
       "      <td>983185</td>\n",
       "      <td>134092</td>\n",
       "      <td>66627</td>\n",
       "      <td>14074</td>\n",
       "      <td>802</td>\n",
       "      <td>2067296</td>\n",
       "      <td>2.136888</td>\n",
       "      <td>4.210674</td>\n",
       "      <td>30.873370</td>\n",
       "      <td>37.216798</td>\n",
       "      <td>9632.399230</td>\n",
       "      <td>6252.964024</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26831</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>3245925</td>\n",
       "      <td>995576</td>\n",
       "      <td>134777</td>\n",
       "      <td>61352</td>\n",
       "      <td>12391</td>\n",
       "      <td>685</td>\n",
       "      <td>2115572</td>\n",
       "      <td>1.926538</td>\n",
       "      <td>4.152191</td>\n",
       "      <td>30.671565</td>\n",
       "      <td>36.434497</td>\n",
       "      <td>9817.971035</td>\n",
       "      <td>6398.984763</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "26660      US 2020-01-22            1                0             0   \n",
       "26661      US 2020-01-23            1                0             0   \n",
       "26662      US 2020-01-24            2                0             0   \n",
       "26663      US 2020-01-25            2                0             0   \n",
       "26664      US 2020-01-26            5                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "26827      US 2020-07-07      2996098           936476        131480   \n",
       "26828      US 2020-07-08      3054699           953462        132300   \n",
       "26829      US 2020-07-09      3117946           969111        133290   \n",
       "26830      US 2020-07-10      3184573           983185        134092   \n",
       "26831      US 2020-07-11      3245925           995576        134777   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "26660                   0                      0             0             1   \n",
       "26661                   0                      0             0             1   \n",
       "26662                   1                      0             0             2   \n",
       "26663                   0                      0             0             2   \n",
       "26664                   3                      0             0             5   \n",
       "...                   ...                    ...           ...           ...   \n",
       "26827               60021                  12328          1195       1928142   \n",
       "26828               58601                  16986           820       1968937   \n",
       "26829               63247                  15649           990       2015545   \n",
       "26830               66627                  14074           802       2067296   \n",
       "26831               61352                  12391           685       2115572   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "26660                      0.000000        0.000000       0.000000   \n",
       "26661                      0.000000        0.000000       0.000000   \n",
       "26662                    100.000000        0.000000       0.000000   \n",
       "26663                      0.000000        0.000000       0.000000   \n",
       "26664                    150.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "26827                      2.044258        4.388374      31.256521   \n",
       "26828                      1.955911        4.331032      31.212961   \n",
       "26829                      2.070482        4.274930      31.081712   \n",
       "26830                      2.136888        4.210674      30.873370   \n",
       "26831                      1.926538        4.152191      30.671565   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "26660               0.000000                 0.003025   \n",
       "26661               0.000000                 0.003025   \n",
       "26662               0.000000                 0.006049   \n",
       "26663               0.000000                 0.006049   \n",
       "26664               0.000000                 0.015124   \n",
       "...                      ...                      ...   \n",
       "26827              37.935536              9062.317639   \n",
       "26828              37.892295              9239.568475   \n",
       "26829              37.764615              9430.872098   \n",
       "26830              37.216798              9632.399230   \n",
       "26831              36.434497              9817.971035   \n",
       "\n",
       "       active_cases_per_million world_population_share  \n",
       "26660                  0.003025                 4.25 %  \n",
       "26661                  0.003025                 4.25 %  \n",
       "26662                  0.006049                 4.25 %  \n",
       "26663                  0.006049                 4.25 %  \n",
       "26664                  0.015124                 4.25 %  \n",
       "...                         ...                    ...  \n",
       "26827               5832.063990                 4.25 %  \n",
       "26828               5955.456899                 4.25 %  \n",
       "26829               6096.432428                 4.25 %  \n",
       "26830               6252.964024                 4.25 %  \n",
       "26831               6398.984763                 4.25 %  \n",
       "\n",
       "[172 rows x 16 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'US']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_country = len(df.country.unique())\n",
    "num_dates = len(df.date.unique())\n",
    "\n",
    "country_list = np.array(df.country.unique())\n",
    "date_list = df.date.unique()\n",
    "\n",
    "total_case_share = []\n",
    "active_case_share = []\n",
    "death_share = []\n",
    "recovered_case_share = []\n",
    "\n",
    "\n",
    "total_case_share_by_date = []\n",
    "active_case_share_by_date = []\n",
    "death_share_by_date = []\n",
    "recovered_case_share_by_date = []\n",
    "\n",
    "for i  in date_list:\n",
    "    \n",
    "    total_day_case = df[df.date == i].sum()['total_cases']\n",
    "    active_day_case = df[df.date == i].sum()['active_cases']\n",
    "    death_day_case = df[df.date == i].sum()['total_deaths']\n",
    "    recovered_day_case = df[df.date == i].sum()['recovered_cases']\n",
    "    \n",
    "    total_case_share_by_date.append(total_day_case)\n",
    "    active_case_share_by_date.append(active_day_case)\n",
    "    death_share_by_date.append(death_day_case)\n",
    "    recovered_case_share_by_date.append(recovered_day_case)\n",
    "    \n",
    "for j in country_list:\n",
    "    idx = df[df.country == j].index\n",
    "    \n",
    "    tot = np.array(df['total_cases'][idx])/total_case_share_by_date*100\n",
    "    act = np.array(df['active_cases'][idx])/active_case_share_by_date*100\n",
    "    dea = np.array(df['total_deaths'][idx])/death_share_by_date*100\n",
    "    reco = np.array(df['recovered_cases'][idx])/recovered_case_share_by_date*100\n",
    "    \n",
    "    total_case_share = np.concatenate([total_case_share,tot])\n",
    "    active_case_share = np.concatenate([active_case_share, act])\n",
    "    death_share = np.concatenate([death_share, dea])\n",
    "    recovered_case_share = np.concatenate([recovered_case_share,reco])\n",
    "\n",
    "df['world_total_cases_share'] = total_case_share\n",
    "df['world_active_cases_share'] = active_case_share\n",
    "df['world_deaths_share'] = death_share\n",
    "df['world_recovered_cases_share'] = recovered_case_share\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>12043</td>\n",
       "      <td>India</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>India</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>12207</td>\n",
       "      <td>India</td>\n",
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       "      <td>742417</td>\n",
       "      <td>456831</td>\n",
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       "      <td>22753</td>\n",
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       "      <td>20.429991</td>\n",
       "      <td>539.063991</td>\n",
       "      <td>192.374057</td>\n",
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       "      <td>6.278273</td>\n",
       "      <td>5.478521</td>\n",
       "      <td>3.794004</td>\n",
       "      <td>7.088081</td>\n",
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       "    <tr>\n",
       "      <td>12208</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>767296</td>\n",
       "      <td>476378</td>\n",
       "      <td>21129</td>\n",
       "      <td>24879</td>\n",
       "      <td>19547</td>\n",
       "      <td>487</td>\n",
       "      <td>269789</td>\n",
       "      <td>3.351082</td>\n",
       "      <td>2.753696</td>\n",
       "      <td>62.085297</td>\n",
       "      <td>20.364878</td>\n",
       "      <td>557.128466</td>\n",
       "      <td>195.891979</td>\n",
       "      <td>17.70 %</td>\n",
       "      <td>6.374546</td>\n",
       "      <td>5.523314</td>\n",
       "      <td>3.846035</td>\n",
       "      <td>7.214620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12209</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>793802</td>\n",
       "      <td>495513</td>\n",
       "      <td>21604</td>\n",
       "      <td>26506</td>\n",
       "      <td>19135</td>\n",
       "      <td>475</td>\n",
       "      <td>276685</td>\n",
       "      <td>3.454469</td>\n",
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       "      <td>576.374294</td>\n",
       "      <td>200.899118</td>\n",
       "      <td>17.70 %</td>\n",
       "      <td>6.472779</td>\n",
       "      <td>5.565463</td>\n",
       "      <td>3.893854</td>\n",
       "      <td>7.354651</td>\n",
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       "    <tr>\n",
       "      <td>12210</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>820916</td>\n",
       "      <td>515386</td>\n",
       "      <td>22123</td>\n",
       "      <td>27114</td>\n",
       "      <td>19873</td>\n",
       "      <td>519</td>\n",
       "      <td>283407</td>\n",
       "      <td>3.415713</td>\n",
       "      <td>2.694916</td>\n",
       "      <td>62.781819</td>\n",
       "      <td>20.554273</td>\n",
       "      <td>596.061587</td>\n",
       "      <td>205.779917</td>\n",
       "      <td>17.70 %</td>\n",
       "      <td>6.570777</td>\n",
       "      <td>5.604735</td>\n",
       "      <td>3.949830</td>\n",
       "      <td>7.494589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12211</td>\n",
       "      <td>India</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>849522</td>\n",
       "      <td>534618</td>\n",
       "      <td>22673</td>\n",
       "      <td>28606</td>\n",
       "      <td>19232</td>\n",
       "      <td>550</td>\n",
       "      <td>292231</td>\n",
       "      <td>3.484644</td>\n",
       "      <td>2.668913</td>\n",
       "      <td>62.931625</td>\n",
       "      <td>20.851866</td>\n",
       "      <td>616.832212</td>\n",
       "      <td>212.186964</td>\n",
       "      <td>17.70 %</td>\n",
       "      <td>6.682587</td>\n",
       "      <td>5.679871</td>\n",
       "      <td>4.012764</td>\n",
       "      <td>7.634759</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "12040   India 2020-01-22            0                0             0   \n",
       "12041   India 2020-01-23            0                0             0   \n",
       "12042   India 2020-01-24            0                0             0   \n",
       "12043   India 2020-01-25            0                0             0   \n",
       "12044   India 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "12207   India 2020-07-07       742417           456831         20642   \n",
       "12208   India 2020-07-08       767296           476378         21129   \n",
       "12209   India 2020-07-09       793802           495513         21604   \n",
       "12210   India 2020-07-10       820916           515386         22123   \n",
       "12211   India 2020-07-11       849522           534618         22673   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "12040                   0                      0             0             0   \n",
       "12041                   0                      0             0             0   \n",
       "12042                   0                      0             0             0   \n",
       "12043                   0                      0             0             0   \n",
       "12044                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "12207               22753                  16897           483        264944   \n",
       "12208               24879                  19547           487        269789   \n",
       "12209               26506                  19135           475        276685   \n",
       "12210               27114                  19873           519        283407   \n",
       "12211               28606                  19232           550        292231   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "12040                      0.000000        0.000000       0.000000   \n",
       "12041                      0.000000        0.000000       0.000000   \n",
       "12042                      0.000000        0.000000       0.000000   \n",
       "12043                      0.000000        0.000000       0.000000   \n",
       "12044                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "12207                      3.161614        2.780378      61.532939   \n",
       "12208                      3.351082        2.753696      62.085297   \n",
       "12209                      3.454469        2.721585      62.422745   \n",
       "12210                      3.415713        2.694916      62.781819   \n",
       "12211                      3.484644        2.668913      62.931625   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "12040               0.000000                 0.000000   \n",
       "12041               0.000000                 0.000000   \n",
       "12042               0.000000                 0.000000   \n",
       "12043               0.000000                 0.000000   \n",
       "12044               0.000000                 0.000000   \n",
       "...                      ...                      ...   \n",
       "12207              20.429991               539.063991   \n",
       "12208              20.364878               557.128466   \n",
       "12209              20.367046               576.374294   \n",
       "12210              20.554273               596.061587   \n",
       "12211              20.851866               616.832212   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "12040                  0.000000                17.70 %   \n",
       "12041                  0.000000                17.70 %   \n",
       "12042                  0.000000                17.70 %   \n",
       "12043                  0.000000                17.70 %   \n",
       "12044                  0.000000                17.70 %   \n",
       "...                         ...                    ...   \n",
       "12207                192.374057                17.70 %   \n",
       "12208                195.891979                17.70 %   \n",
       "12209                200.899118                17.70 %   \n",
       "12210                205.779917                17.70 %   \n",
       "12211                212.186964                17.70 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "12040                 0.000000                  0.000000            0.000000   \n",
       "12041                 0.000000                  0.000000            0.000000   \n",
       "12042                 0.000000                  0.000000            0.000000   \n",
       "12043                 0.000000                  0.000000            0.000000   \n",
       "12044                 0.000000                  0.000000            0.000000   \n",
       "...                        ...                       ...                 ...   \n",
       "12207                 6.278273                  5.478521            3.794004   \n",
       "12208                 6.374546                  5.523314            3.846035   \n",
       "12209                 6.472779                  5.565463            3.893854   \n",
       "12210                 6.570777                  5.604735            3.949830   \n",
       "12211                 6.682587                  5.679871            4.012764   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "12040                     0.000000  \n",
       "12041                     0.000000  \n",
       "12042                     0.000000  \n",
       "12043                     0.000000  \n",
       "12044                     0.000000  \n",
       "...                            ...  \n",
       "12207                     7.088081  \n",
       "12208                     7.214620  \n",
       "12209                     7.354651  \n",
       "12210                     7.494589  \n",
       "12211                     7.634759  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'India']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
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       "      <td>0.006049</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>0.212540</td>\n",
       "      <td>0.227531</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26663</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>0.139470</td>\n",
       "      <td>0.147820</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26664</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015124</td>\n",
       "      <td>0.015124</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>0.236072</td>\n",
       "      <td>0.248756</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>26827</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>2996098</td>\n",
       "      <td>936476</td>\n",
       "      <td>131480</td>\n",
       "      <td>60021</td>\n",
       "      <td>12328</td>\n",
       "      <td>1195</td>\n",
       "      <td>1928142</td>\n",
       "      <td>2.044258</td>\n",
       "      <td>4.388374</td>\n",
       "      <td>31.256521</td>\n",
       "      <td>37.935536</td>\n",
       "      <td>9062.317639</td>\n",
       "      <td>5832.063990</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>25.336600</td>\n",
       "      <td>39.870183</td>\n",
       "      <td>24.166052</td>\n",
       "      <td>14.530139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26828</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>3054699</td>\n",
       "      <td>953462</td>\n",
       "      <td>132300</td>\n",
       "      <td>58601</td>\n",
       "      <td>16986</td>\n",
       "      <td>820</td>\n",
       "      <td>1968937</td>\n",
       "      <td>1.955911</td>\n",
       "      <td>4.331032</td>\n",
       "      <td>31.212961</td>\n",
       "      <td>37.892295</td>\n",
       "      <td>9239.568475</td>\n",
       "      <td>5955.456899</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>25.377845</td>\n",
       "      <td>40.309494</td>\n",
       "      <td>24.082087</td>\n",
       "      <td>14.439933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26829</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>3117946</td>\n",
       "      <td>969111</td>\n",
       "      <td>133290</td>\n",
       "      <td>63247</td>\n",
       "      <td>15649</td>\n",
       "      <td>990</td>\n",
       "      <td>2015545</td>\n",
       "      <td>2.070482</td>\n",
       "      <td>4.274930</td>\n",
       "      <td>31.081712</td>\n",
       "      <td>37.764615</td>\n",
       "      <td>9430.872098</td>\n",
       "      <td>6096.432428</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>25.424193</td>\n",
       "      <td>40.542283</td>\n",
       "      <td>24.023878</td>\n",
       "      <td>14.384029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26830</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>3184573</td>\n",
       "      <td>983185</td>\n",
       "      <td>134092</td>\n",
       "      <td>66627</td>\n",
       "      <td>14074</td>\n",
       "      <td>802</td>\n",
       "      <td>2067296</td>\n",
       "      <td>2.136888</td>\n",
       "      <td>4.210674</td>\n",
       "      <td>30.873370</td>\n",
       "      <td>37.216798</td>\n",
       "      <td>9632.399230</td>\n",
       "      <td>6252.964024</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>25.489963</td>\n",
       "      <td>40.883414</td>\n",
       "      <td>23.940725</td>\n",
       "      <td>14.297181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26831</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>3245925</td>\n",
       "      <td>995576</td>\n",
       "      <td>134777</td>\n",
       "      <td>61352</td>\n",
       "      <td>12391</td>\n",
       "      <td>685</td>\n",
       "      <td>2115572</td>\n",
       "      <td>1.926538</td>\n",
       "      <td>4.152191</td>\n",
       "      <td>30.671565</td>\n",
       "      <td>36.434497</td>\n",
       "      <td>9817.971035</td>\n",
       "      <td>6398.984763</td>\n",
       "      <td>4.25 %</td>\n",
       "      <td>25.533390</td>\n",
       "      <td>41.118758</td>\n",
       "      <td>23.853407</td>\n",
       "      <td>14.217597</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "26660      US 2020-01-22            1                0             0   \n",
       "26661      US 2020-01-23            1                0             0   \n",
       "26662      US 2020-01-24            2                0             0   \n",
       "26663      US 2020-01-25            2                0             0   \n",
       "26664      US 2020-01-26            5                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "26827      US 2020-07-07      2996098           936476        131480   \n",
       "26828      US 2020-07-08      3054699           953462        132300   \n",
       "26829      US 2020-07-09      3117946           969111        133290   \n",
       "26830      US 2020-07-10      3184573           983185        134092   \n",
       "26831      US 2020-07-11      3245925           995576        134777   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "26660                   0                      0             0             1   \n",
       "26661                   0                      0             0             1   \n",
       "26662                   1                      0             0             2   \n",
       "26663                   0                      0             0             2   \n",
       "26664                   3                      0             0             5   \n",
       "...                   ...                    ...           ...           ...   \n",
       "26827               60021                  12328          1195       1928142   \n",
       "26828               58601                  16986           820       1968937   \n",
       "26829               63247                  15649           990       2015545   \n",
       "26830               66627                  14074           802       2067296   \n",
       "26831               61352                  12391           685       2115572   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "26660                      0.000000        0.000000       0.000000   \n",
       "26661                      0.000000        0.000000       0.000000   \n",
       "26662                    100.000000        0.000000       0.000000   \n",
       "26663                      0.000000        0.000000       0.000000   \n",
       "26664                    150.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "26827                      2.044258        4.388374      31.256521   \n",
       "26828                      1.955911        4.331032      31.212961   \n",
       "26829                      2.070482        4.274930      31.081712   \n",
       "26830                      2.136888        4.210674      30.873370   \n",
       "26831                      1.926538        4.152191      30.671565   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "26660               0.000000                 0.003025   \n",
       "26661               0.000000                 0.003025   \n",
       "26662               0.000000                 0.006049   \n",
       "26663               0.000000                 0.006049   \n",
       "26664               0.000000                 0.015124   \n",
       "...                      ...                      ...   \n",
       "26827              37.935536              9062.317639   \n",
       "26828              37.892295              9239.568475   \n",
       "26829              37.764615              9430.872098   \n",
       "26830              37.216798              9632.399230   \n",
       "26831              36.434497              9817.971035   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "26660                  0.003025                 4.25 %   \n",
       "26661                  0.003025                 4.25 %   \n",
       "26662                  0.006049                 4.25 %   \n",
       "26663                  0.006049                 4.25 %   \n",
       "26664                  0.015124                 4.25 %   \n",
       "...                         ...                    ...   \n",
       "26827               5832.063990                 4.25 %   \n",
       "26828               5955.456899                 4.25 %   \n",
       "26829               6096.432428                 4.25 %   \n",
       "26830               6252.964024                 4.25 %   \n",
       "26831               6398.984763                 4.25 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "26660                 0.180180                  0.196078            0.000000   \n",
       "26661                 0.152905                  0.165017            0.000000   \n",
       "26662                 0.212540                  0.227531            0.000000   \n",
       "26663                 0.139470                  0.147820            0.000000   \n",
       "26664                 0.236072                  0.248756            0.000000   \n",
       "...                        ...                       ...                 ...   \n",
       "26827                25.336600                 39.870183           24.166052   \n",
       "26828                25.377845                 40.309494           24.082087   \n",
       "26829                25.424193                 40.542283           24.023878   \n",
       "26830                25.489963                 40.883414           23.940725   \n",
       "26831                25.533390                 41.118758           23.853407   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "26660                     0.000000  \n",
       "26661                     0.000000  \n",
       "26662                     0.000000  \n",
       "26663                     0.000000  \n",
       "26664                     0.000000  \n",
       "...                            ...  \n",
       "26827                    14.530139  \n",
       "26828                    14.439933  \n",
       "26829                    14.384029  \n",
       "26830                    14.297181  \n",
       "26831                    14.217597  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'US']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
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       "      <td>21156</td>\n",
       "      <td>Russia</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>21157</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.87 %</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>21158</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21159</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>21160</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <td>21323</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>693215</td>\n",
       "      <td>463103</td>\n",
       "      <td>10478</td>\n",
       "      <td>6363</td>\n",
       "      <td>9533</td>\n",
       "      <td>198</td>\n",
       "      <td>219634</td>\n",
       "      <td>0.926400</td>\n",
       "      <td>1.511508</td>\n",
       "      <td>66.805104</td>\n",
       "      <td>70.213425</td>\n",
       "      <td>4750.585604</td>\n",
       "      <td>1505.146482</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>5.862195</td>\n",
       "      <td>4.541599</td>\n",
       "      <td>1.925859</td>\n",
       "      <td>7.185396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21324</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>699749</td>\n",
       "      <td>471718</td>\n",
       "      <td>10650</td>\n",
       "      <td>6534</td>\n",
       "      <td>8615</td>\n",
       "      <td>172</td>\n",
       "      <td>217381</td>\n",
       "      <td>0.942565</td>\n",
       "      <td>1.521974</td>\n",
       "      <td>67.412458</td>\n",
       "      <td>70.923935</td>\n",
       "      <td>4795.362948</td>\n",
       "      <td>1489.706728</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>5.813379</td>\n",
       "      <td>4.450380</td>\n",
       "      <td>1.938581</td>\n",
       "      <td>7.144046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21325</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>706240</td>\n",
       "      <td>480494</td>\n",
       "      <td>10826</td>\n",
       "      <td>6491</td>\n",
       "      <td>8776</td>\n",
       "      <td>176</td>\n",
       "      <td>214920</td>\n",
       "      <td>0.927618</td>\n",
       "      <td>1.532907</td>\n",
       "      <td>68.035512</td>\n",
       "      <td>72.025197</td>\n",
       "      <td>4839.845613</td>\n",
       "      <td>1472.841554</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>5.758785</td>\n",
       "      <td>4.323073</td>\n",
       "      <td>1.951253</td>\n",
       "      <td>7.131732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21326</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>712863</td>\n",
       "      <td>488234</td>\n",
       "      <td>11000</td>\n",
       "      <td>6623</td>\n",
       "      <td>7740</td>\n",
       "      <td>174</td>\n",
       "      <td>213629</td>\n",
       "      <td>0.937783</td>\n",
       "      <td>1.543073</td>\n",
       "      <td>68.489177</td>\n",
       "      <td>72.866509</td>\n",
       "      <td>4885.232872</td>\n",
       "      <td>1463.994362</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>5.705899</td>\n",
       "      <td>4.224786</td>\n",
       "      <td>1.963935</td>\n",
       "      <td>7.099752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21327</td>\n",
       "      <td>Russia</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>719449</td>\n",
       "      <td>496594</td>\n",
       "      <td>11188</td>\n",
       "      <td>6586</td>\n",
       "      <td>8360</td>\n",
       "      <td>188</td>\n",
       "      <td>211667</td>\n",
       "      <td>0.923880</td>\n",
       "      <td>1.555079</td>\n",
       "      <td>69.024212</td>\n",
       "      <td>73.623998</td>\n",
       "      <td>4930.366570</td>\n",
       "      <td>1450.548824</td>\n",
       "      <td>1.87 %</td>\n",
       "      <td>5.659395</td>\n",
       "      <td>4.114010</td>\n",
       "      <td>1.980100</td>\n",
       "      <td>7.091747</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "21156  Russia 2020-01-22            0                0             0   \n",
       "21157  Russia 2020-01-23            0                0             0   \n",
       "21158  Russia 2020-01-24            0                0             0   \n",
       "21159  Russia 2020-01-25            0                0             0   \n",
       "21160  Russia 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "21323  Russia 2020-07-07       693215           463103         10478   \n",
       "21324  Russia 2020-07-08       699749           471718         10650   \n",
       "21325  Russia 2020-07-09       706240           480494         10826   \n",
       "21326  Russia 2020-07-10       712863           488234         11000   \n",
       "21327  Russia 2020-07-11       719449           496594         11188   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "21156                   0                      0             0             0   \n",
       "21157                   0                      0             0             0   \n",
       "21158                   0                      0             0             0   \n",
       "21159                   0                      0             0             0   \n",
       "21160                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "21323                6363                   9533           198        219634   \n",
       "21324                6534                   8615           172        217381   \n",
       "21325                6491                   8776           176        214920   \n",
       "21326                6623                   7740           174        213629   \n",
       "21327                6586                   8360           188        211667   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "21156                      0.000000        0.000000       0.000000   \n",
       "21157                      0.000000        0.000000       0.000000   \n",
       "21158                      0.000000        0.000000       0.000000   \n",
       "21159                      0.000000        0.000000       0.000000   \n",
       "21160                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "21323                      0.926400        1.511508      66.805104   \n",
       "21324                      0.942565        1.521974      67.412458   \n",
       "21325                      0.927618        1.532907      68.035512   \n",
       "21326                      0.937783        1.543073      68.489177   \n",
       "21327                      0.923880        1.555079      69.024212   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "21156               0.000000                 0.000000   \n",
       "21157               0.000000                 0.000000   \n",
       "21158               0.000000                 0.000000   \n",
       "21159               0.000000                 0.000000   \n",
       "21160               0.000000                 0.000000   \n",
       "...                      ...                      ...   \n",
       "21323              70.213425              4750.585604   \n",
       "21324              70.923935              4795.362948   \n",
       "21325              72.025197              4839.845613   \n",
       "21326              72.866509              4885.232872   \n",
       "21327              73.623998              4930.366570   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "21156                  0.000000                 1.87 %   \n",
       "21157                  0.000000                 1.87 %   \n",
       "21158                  0.000000                 1.87 %   \n",
       "21159                  0.000000                 1.87 %   \n",
       "21160                  0.000000                 1.87 %   \n",
       "...                         ...                    ...   \n",
       "21323               1505.146482                 1.87 %   \n",
       "21324               1489.706728                 1.87 %   \n",
       "21325               1472.841554                 1.87 %   \n",
       "21326               1463.994362                 1.87 %   \n",
       "21327               1450.548824                 1.87 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "21156                 0.000000                  0.000000            0.000000   \n",
       "21157                 0.000000                  0.000000            0.000000   \n",
       "21158                 0.000000                  0.000000            0.000000   \n",
       "21159                 0.000000                  0.000000            0.000000   \n",
       "21160                 0.000000                  0.000000            0.000000   \n",
       "...                        ...                       ...                 ...   \n",
       "21323                 5.862195                  4.541599            1.925859   \n",
       "21324                 5.813379                  4.450380            1.938581   \n",
       "21325                 5.758785                  4.323073            1.951253   \n",
       "21326                 5.705899                  4.224786            1.963935   \n",
       "21327                 5.659395                  4.114010            1.980100   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "21156                     0.000000  \n",
       "21157                     0.000000  \n",
       "21158                     0.000000  \n",
       "21159                     0.000000  \n",
       "21160                     0.000000  \n",
       "...                            ...  \n",
       "21323                     7.185396  \n",
       "21324                     7.144046  \n",
       "21325                     7.131732  \n",
       "21326                     7.099752  \n",
       "21327                     7.091747  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'Russia']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_reported_cases</th>\n",
       "      <th>daily_recovered_cases</th>\n",
       "      <th>daily_deaths</th>\n",
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       "      <th>mortality_rate</th>\n",
       "      <th>recovery_rate</th>\n",
       "      <th>doubling_time_in_days</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>active_cases_per_million</th>\n",
       "      <th>world_population_share</th>\n",
       "      <th>world_total_cases_share</th>\n",
       "      <th>world_active_cases_share</th>\n",
       "      <th>world_deaths_share</th>\n",
       "      <th>world_recovered_cases_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3612</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3613</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-01-23</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3614</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3615</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-01-25</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",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3616</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-01-26</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\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",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3779</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>1668589</td>\n",
       "      <td>1107012</td>\n",
       "      <td>66741</td>\n",
       "      <td>45305</td>\n",
       "      <td>44470</td>\n",
       "      <td>1254</td>\n",
       "      <td>494836</td>\n",
       "      <td>2.790947</td>\n",
       "      <td>3.999847</td>\n",
       "      <td>66.344199</td>\n",
       "      <td>27.848304</td>\n",
       "      <td>7861.315604</td>\n",
       "      <td>2331.348204</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>14.110477</td>\n",
       "      <td>10.232235</td>\n",
       "      <td>12.267010</td>\n",
       "      <td>17.176134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3780</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>1713160</td>\n",
       "      <td>1139844</td>\n",
       "      <td>67964</td>\n",
       "      <td>44571</td>\n",
       "      <td>32832</td>\n",
       "      <td>1223</td>\n",
       "      <td>505352</td>\n",
       "      <td>2.671179</td>\n",
       "      <td>3.967172</td>\n",
       "      <td>66.534591</td>\n",
       "      <td>28.918177</td>\n",
       "      <td>8071.305420</td>\n",
       "      <td>2380.892816</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>14.232600</td>\n",
       "      <td>10.345930</td>\n",
       "      <td>12.371239</td>\n",
       "      <td>17.262640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3781</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>1755779</td>\n",
       "      <td>1171447</td>\n",
       "      <td>69184</td>\n",
       "      <td>42619</td>\n",
       "      <td>31603</td>\n",
       "      <td>1220</td>\n",
       "      <td>515148</td>\n",
       "      <td>2.487742</td>\n",
       "      <td>3.940359</td>\n",
       "      <td>66.719502</td>\n",
       "      <td>30.391616</td>\n",
       "      <td>8272.098671</td>\n",
       "      <td>2427.045252</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>14.316882</td>\n",
       "      <td>10.362099</td>\n",
       "      <td>12.469562</td>\n",
       "      <td>17.387201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3782</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>1800827</td>\n",
       "      <td>1217361</td>\n",
       "      <td>70398</td>\n",
       "      <td>45048</td>\n",
       "      <td>45914</td>\n",
       "      <td>1214</td>\n",
       "      <td>513068</td>\n",
       "      <td>2.565699</td>\n",
       "      <td>3.909204</td>\n",
       "      <td>67.600108</td>\n",
       "      <td>30.873857</td>\n",
       "      <td>8484.335804</td>\n",
       "      <td>2417.245633</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>14.414182</td>\n",
       "      <td>10.146574</td>\n",
       "      <td>12.568827</td>\n",
       "      <td>17.702499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3783</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>1839850</td>\n",
       "      <td>1244088</td>\n",
       "      <td>71469</td>\n",
       "      <td>39023</td>\n",
       "      <td>26727</td>\n",
       "      <td>1071</td>\n",
       "      <td>524293</td>\n",
       "      <td>2.166949</td>\n",
       "      <td>3.884501</td>\n",
       "      <td>67.618991</td>\n",
       "      <td>31.455340</td>\n",
       "      <td>8668.187021</td>\n",
       "      <td>2470.130596</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>14.472795</td>\n",
       "      <td>10.190283</td>\n",
       "      <td>12.648888</td>\n",
       "      <td>17.766541</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "3612  Brazil 2020-01-22            0                0             0   \n",
       "3613  Brazil 2020-01-23            0                0             0   \n",
       "3614  Brazil 2020-01-24            0                0             0   \n",
       "3615  Brazil 2020-01-25            0                0             0   \n",
       "3616  Brazil 2020-01-26            0                0             0   \n",
       "...      ...        ...          ...              ...           ...   \n",
       "3779  Brazil 2020-07-07      1668589          1107012         66741   \n",
       "3780  Brazil 2020-07-08      1713160          1139844         67964   \n",
       "3781  Brazil 2020-07-09      1755779          1171447         69184   \n",
       "3782  Brazil 2020-07-10      1800827          1217361         70398   \n",
       "3783  Brazil 2020-07-11      1839850          1244088         71469   \n",
       "\n",
       "      new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "3612                   0                      0             0             0   \n",
       "3613                   0                      0             0             0   \n",
       "3614                   0                      0             0             0   \n",
       "3615                   0                      0             0             0   \n",
       "3616                   0                      0             0             0   \n",
       "...                  ...                    ...           ...           ...   \n",
       "3779               45305                  44470          1254        494836   \n",
       "3780               44571                  32832          1223        505352   \n",
       "3781               42619                  31603          1220        515148   \n",
       "3782               45048                  45914          1214        513068   \n",
       "3783               39023                  26727          1071        524293   \n",
       "\n",
       "      cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "3612                      0.000000        0.000000       0.000000   \n",
       "3613                      0.000000        0.000000       0.000000   \n",
       "3614                      0.000000        0.000000       0.000000   \n",
       "3615                      0.000000        0.000000       0.000000   \n",
       "3616                      0.000000        0.000000       0.000000   \n",
       "...                            ...             ...            ...   \n",
       "3779                      2.790947        3.999847      66.344199   \n",
       "3780                      2.671179        3.967172      66.534591   \n",
       "3781                      2.487742        3.940359      66.719502   \n",
       "3782                      2.565699        3.909204      67.600108   \n",
       "3783                      2.166949        3.884501      67.618991   \n",
       "\n",
       "      doubling_time_in_days  total_cases_per_million  \\\n",
       "3612               0.000000                 0.000000   \n",
       "3613               0.000000                 0.000000   \n",
       "3614               0.000000                 0.000000   \n",
       "3615               0.000000                 0.000000   \n",
       "3616               0.000000                 0.000000   \n",
       "...                     ...                      ...   \n",
       "3779              27.848304              7861.315604   \n",
       "3780              28.918177              8071.305420   \n",
       "3781              30.391616              8272.098671   \n",
       "3782              30.873857              8484.335804   \n",
       "3783              31.455340              8668.187021   \n",
       "\n",
       "      active_cases_per_million world_population_share  \\\n",
       "3612                  0.000000                 2.73 %   \n",
       "3613                  0.000000                 2.73 %   \n",
       "3614                  0.000000                 2.73 %   \n",
       "3615                  0.000000                 2.73 %   \n",
       "3616                  0.000000                 2.73 %   \n",
       "...                        ...                    ...   \n",
       "3779               2331.348204                 2.73 %   \n",
       "3780               2380.892816                 2.73 %   \n",
       "3781               2427.045252                 2.73 %   \n",
       "3782               2417.245633                 2.73 %   \n",
       "3783               2470.130596                 2.73 %   \n",
       "\n",
       "      world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "3612                 0.000000                  0.000000            0.000000   \n",
       "3613                 0.000000                  0.000000            0.000000   \n",
       "3614                 0.000000                  0.000000            0.000000   \n",
       "3615                 0.000000                  0.000000            0.000000   \n",
       "3616                 0.000000                  0.000000            0.000000   \n",
       "...                       ...                       ...                 ...   \n",
       "3779                14.110477                 10.232235           12.267010   \n",
       "3780                14.232600                 10.345930           12.371239   \n",
       "3781                14.316882                 10.362099           12.469562   \n",
       "3782                14.414182                 10.146574           12.568827   \n",
       "3783                14.472795                 10.190283           12.648888   \n",
       "\n",
       "      world_recovered_cases_share  \n",
       "3612                     0.000000  \n",
       "3613                     0.000000  \n",
       "3614                     0.000000  \n",
       "3615                     0.000000  \n",
       "3616                     0.000000  \n",
       "...                           ...  \n",
       "3779                    17.176134  \n",
       "3780                    17.262640  \n",
       "3781                    17.387201  \n",
       "3782                    17.702499  \n",
       "3783                    17.766541  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'Brazil']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_reported_cases</th>\n",
       "      <th>daily_recovered_cases</th>\n",
       "      <th>daily_deaths</th>\n",
       "      <th>active_cases</th>\n",
       "      <th>cases_growth_rate_in_percent</th>\n",
       "      <th>mortality_rate</th>\n",
       "      <th>recovery_rate</th>\n",
       "      <th>doubling_time_in_days</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>active_cases_per_million</th>\n",
       "      <th>world_population_share</th>\n",
       "      <th>world_total_cases_share</th>\n",
       "      <th>world_active_cases_share</th>\n",
       "      <th>world_deaths_share</th>\n",
       "      <th>world_recovered_cases_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5504</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>548</td>\n",
       "      <td>28</td>\n",
       "      <td>17</td>\n",
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       "      <td>503</td>\n",
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       "      <td>5.109489</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.381030</td>\n",
       "      <td>0.349741</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>98.738739</td>\n",
       "      <td>98.627451</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5505</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>643</td>\n",
       "      <td>30</td>\n",
       "      <td>18</td>\n",
       "      <td>95</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>595</td>\n",
       "      <td>17.335766</td>\n",
       "      <td>2.799378</td>\n",
       "      <td>4.665630</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.447084</td>\n",
       "      <td>0.413710</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>98.318043</td>\n",
       "      <td>98.184818</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5506</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>920</td>\n",
       "      <td>36</td>\n",
       "      <td>26</td>\n",
       "      <td>277</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>858</td>\n",
       "      <td>43.079316</td>\n",
       "      <td>2.826087</td>\n",
       "      <td>3.913043</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.639685</td>\n",
       "      <td>0.596576</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>97.768332</td>\n",
       "      <td>97.610922</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5507</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>1406</td>\n",
       "      <td>39</td>\n",
       "      <td>42</td>\n",
       "      <td>486</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>1325</td>\n",
       "      <td>52.826087</td>\n",
       "      <td>2.987198</td>\n",
       "      <td>2.773826</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.977606</td>\n",
       "      <td>0.921286</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>98.047420</td>\n",
       "      <td>97.930525</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5508</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>2075</td>\n",
       "      <td>49</td>\n",
       "      <td>56</td>\n",
       "      <td>669</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>1970</td>\n",
       "      <td>47.581792</td>\n",
       "      <td>2.698795</td>\n",
       "      <td>2.361446</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.442768</td>\n",
       "      <td>1.369761</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>97.969783</td>\n",
       "      <td>98.009950</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>94.230769</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>5671</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>84917</td>\n",
       "      <td>79754</td>\n",
       "      <td>4641</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>522</td>\n",
       "      <td>0.032984</td>\n",
       "      <td>5.465337</td>\n",
       "      <td>93.919945</td>\n",
       "      <td>3118.880618</td>\n",
       "      <td>59.043647</td>\n",
       "      <td>0.362952</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>0.718103</td>\n",
       "      <td>0.010794</td>\n",
       "      <td>0.853017</td>\n",
       "      <td>1.237444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5672</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>84950</td>\n",
       "      <td>79802</td>\n",
       "      <td>4641</td>\n",
       "      <td>33</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>507</td>\n",
       "      <td>0.038861</td>\n",
       "      <td>5.463214</td>\n",
       "      <td>93.939965</td>\n",
       "      <td>3073.482756</td>\n",
       "      <td>59.066592</td>\n",
       "      <td>0.352522</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>0.705748</td>\n",
       "      <td>0.010380</td>\n",
       "      <td>0.844784</td>\n",
       "      <td>1.208580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5673</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>84992</td>\n",
       "      <td>79802</td>\n",
       "      <td>4641</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>549</td>\n",
       "      <td>0.049441</td>\n",
       "      <td>5.460514</td>\n",
       "      <td>93.893543</td>\n",
       "      <td>2543.075134</td>\n",
       "      <td>59.095795</td>\n",
       "      <td>0.381725</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>0.693037</td>\n",
       "      <td>0.011043</td>\n",
       "      <td>0.836483</td>\n",
       "      <td>1.184461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5674</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>84992</td>\n",
       "      <td>79802</td>\n",
       "      <td>4641</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>549</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.460514</td>\n",
       "      <td>93.893543</td>\n",
       "      <td>2675.274417</td>\n",
       "      <td>59.095795</td>\n",
       "      <td>0.381725</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>0.680293</td>\n",
       "      <td>0.010857</td>\n",
       "      <td>0.828602</td>\n",
       "      <td>1.160457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5675</td>\n",
       "      <td>China</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>85071</td>\n",
       "      <td>79876</td>\n",
       "      <td>4641</td>\n",
       "      <td>79</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>554</td>\n",
       "      <td>0.092950</td>\n",
       "      <td>5.455443</td>\n",
       "      <td>93.893336</td>\n",
       "      <td>1926.187167</td>\n",
       "      <td>59.150724</td>\n",
       "      <td>0.385202</td>\n",
       "      <td>18.47 %</td>\n",
       "      <td>0.669193</td>\n",
       "      <td>0.010768</td>\n",
       "      <td>0.821384</td>\n",
       "      <td>1.140691</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "5504   China 2020-01-22          548               28            17   \n",
       "5505   China 2020-01-23          643               30            18   \n",
       "5506   China 2020-01-24          920               36            26   \n",
       "5507   China 2020-01-25         1406               39            42   \n",
       "5508   China 2020-01-26         2075               49            56   \n",
       "...      ...        ...          ...              ...           ...   \n",
       "5671   China 2020-07-07        84917            79754          4641   \n",
       "5672   China 2020-07-08        84950            79802          4641   \n",
       "5673   China 2020-07-09        84992            79802          4641   \n",
       "5674   China 2020-07-10        84992            79802          4641   \n",
       "5675   China 2020-07-11        85071            79876          4641   \n",
       "\n",
       "      new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "5504                   0                      0             0           503   \n",
       "5505                  95                      2             1           595   \n",
       "5506                 277                      6             8           858   \n",
       "5507                 486                      3            16          1325   \n",
       "5508                 669                     10            14          1970   \n",
       "...                  ...                    ...           ...           ...   \n",
       "5671                  28                     29             0           522   \n",
       "5672                  33                     48             0           507   \n",
       "5673                  42                      0             0           549   \n",
       "5674                   0                      0             0           549   \n",
       "5675                  79                     74             0           554   \n",
       "\n",
       "      cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "5504                      0.000000        3.102190       5.109489   \n",
       "5505                     17.335766        2.799378       4.665630   \n",
       "5506                     43.079316        2.826087       3.913043   \n",
       "5507                     52.826087        2.987198       2.773826   \n",
       "5508                     47.581792        2.698795       2.361446   \n",
       "...                            ...             ...            ...   \n",
       "5671                      0.032984        5.465337      93.919945   \n",
       "5672                      0.038861        5.463214      93.939965   \n",
       "5673                      0.049441        5.460514      93.893543   \n",
       "5674                      0.000000        5.460514      93.893543   \n",
       "5675                      0.092950        5.455443      93.893336   \n",
       "\n",
       "      doubling_time_in_days  total_cases_per_million  \\\n",
       "5504               0.000000                 0.381030   \n",
       "5505               0.000000                 0.447084   \n",
       "5506               0.000000                 0.639685   \n",
       "5507               0.000000                 0.977606   \n",
       "5508               0.000000                 1.442768   \n",
       "...                     ...                      ...   \n",
       "5671            3118.880618                59.043647   \n",
       "5672            3073.482756                59.066592   \n",
       "5673            2543.075134                59.095795   \n",
       "5674            2675.274417                59.095795   \n",
       "5675            1926.187167                59.150724   \n",
       "\n",
       "      active_cases_per_million world_population_share  \\\n",
       "5504                  0.349741                18.47 %   \n",
       "5505                  0.413710                18.47 %   \n",
       "5506                  0.596576                18.47 %   \n",
       "5507                  0.921286                18.47 %   \n",
       "5508                  1.369761                18.47 %   \n",
       "...                        ...                    ...   \n",
       "5671                  0.362952                18.47 %   \n",
       "5672                  0.352522                18.47 %   \n",
       "5673                  0.381725                18.47 %   \n",
       "5674                  0.381725                18.47 %   \n",
       "5675                  0.385202                18.47 %   \n",
       "\n",
       "      world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "5504                98.738739                 98.627451          100.000000   \n",
       "5505                98.318043                 98.184818          100.000000   \n",
       "5506                97.768332                 97.610922          100.000000   \n",
       "5507                98.047420                 97.930525          100.000000   \n",
       "5508                97.969783                 98.009950          100.000000   \n",
       "...                       ...                       ...                 ...   \n",
       "5671                 0.718103                  0.010794            0.853017   \n",
       "5672                 0.705748                  0.010380            0.844784   \n",
       "5673                 0.693037                  0.011043            0.836483   \n",
       "5674                 0.680293                  0.010857            0.828602   \n",
       "5675                 0.669193                  0.010768            0.821384   \n",
       "\n",
       "      world_recovered_cases_share  \n",
       "5504                   100.000000  \n",
       "5505                   100.000000  \n",
       "5506                   100.000000  \n",
       "5507                   100.000000  \n",
       "5508                    94.230769  \n",
       "...                           ...  \n",
       "5671                     1.237444  \n",
       "5672                     1.208580  \n",
       "5673                     1.184461  \n",
       "5674                     1.160457  \n",
       "5675                     1.140691  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'China']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26316         0\n",
       "26317         0\n",
       "26318         0\n",
       "26319         0\n",
       "26320         0\n",
       "          ...  \n",
       "26483     98149\n",
       "26484     99527\n",
       "26485    100905\n",
       "26486    102283\n",
       "26487    103661\n",
       "Name: recovered_cases, Length: 172, dtype: int32"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Just Some Testing\n",
    "arn = pd.DataFrame(df[df.country == 'United Kingdom'])\n",
    "arn_sm = arn['recovered_cases'].cumsum()\n",
    "arn_sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>23567</td>\n",
       "      <td>Spain</td>\n",
       "      <td>2020-01-25</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>Spain</td>\n",
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       "      <td>2.333198</td>\n",
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       "    <tr>\n",
       "      <td>23732</td>\n",
       "      <td>Spain</td>\n",
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       "      <td>426.552389</td>\n",
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       "      <td>1.509679</td>\n",
       "      <td>5.168820</td>\n",
       "      <td>2.277405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23733</td>\n",
       "      <td>Spain</td>\n",
       "      <td>2020-07-09</td>\n",
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       "      <td>150376</td>\n",
       "      <td>28401</td>\n",
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       "      <td>2.063456</td>\n",
       "      <td>1.494107</td>\n",
       "      <td>5.118930</td>\n",
       "      <td>2.231956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23734</td>\n",
       "      <td>Spain</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>253908</td>\n",
       "      <td>150376</td>\n",
       "      <td>28403</td>\n",
       "      <td>852</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>75129</td>\n",
       "      <td>0.336684</td>\n",
       "      <td>11.186335</td>\n",
       "      <td>59.224601</td>\n",
       "      <td>363.637401</td>\n",
       "      <td>5431.050663</td>\n",
       "      <td>1606.997043</td>\n",
       "      <td>0.60 %</td>\n",
       "      <td>2.032331</td>\n",
       "      <td>1.485772</td>\n",
       "      <td>5.071059</td>\n",
       "      <td>2.186723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23735</td>\n",
       "      <td>Spain</td>\n",
       "      <td>2020-07-11</td>\n",
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       "      <td>1606.997043</td>\n",
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       "      <td>1.997314</td>\n",
       "      <td>1.460225</td>\n",
       "      <td>5.026884</td>\n",
       "      <td>2.147486</td>\n",
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       "<p>172 rows × 20 columns</p>\n",
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      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "23564   Spain 2020-01-22            0                0             0   \n",
       "23565   Spain 2020-01-23            0                0             0   \n",
       "23566   Spain 2020-01-24            0                0             0   \n",
       "23567   Spain 2020-01-25            0                0             0   \n",
       "23568   Spain 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "23731   Spain 2020-07-07       252130           150376         28392   \n",
       "23732   Spain 2020-07-08       252513           150376         28396   \n",
       "23733   Spain 2020-07-09       253056           150376         28401   \n",
       "23734   Spain 2020-07-10       253908           150376         28403   \n",
       "23735   Spain 2020-07-11       253908           150376         28403   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "23564                   0                      0             0             0   \n",
       "23565                   0                      0             0             0   \n",
       "23566                   0                      0             0             0   \n",
       "23567                   0                      0             0             0   \n",
       "23568                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "23731                 341                      0             4         73362   \n",
       "23732                 383                      0             4         73741   \n",
       "23733                 543                      0             5         74279   \n",
       "23734                 852                      0             2         75129   \n",
       "23735                   0                      0             0         75129   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "23564                      0.000000        0.000000       0.000000   \n",
       "23565                      0.000000        0.000000       0.000000   \n",
       "23566                      0.000000        0.000000       0.000000   \n",
       "23567                      0.000000        0.000000       0.000000   \n",
       "23568                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "23731                      0.135431       11.260857      59.642248   \n",
       "23732                      0.151906       11.245362      59.551785   \n",
       "23733                      0.215038       11.223208      59.424001   \n",
       "23734                      0.336684       11.186335      59.224601   \n",
       "23735                      0.000000       11.186335      59.224601   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "23564               0.000000                 0.000000   \n",
       "23565               0.000000                 0.000000   \n",
       "23566               0.000000                 0.000000   \n",
       "23567               0.000000                 0.000000   \n",
       "23568               0.000000                 0.000000   \n",
       "...                      ...                      ...   \n",
       "23731             425.153762              5393.019534   \n",
       "23732             426.552389              5401.211841   \n",
       "23733             413.067505              5412.826523   \n",
       "23734             363.637401              5431.050663   \n",
       "23735             363.637401              5431.050663   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "23564                  0.000000                 0.60 %   \n",
       "23565                  0.000000                 0.60 %   \n",
       "23566                  0.000000                 0.60 %   \n",
       "23567                  0.000000                 0.60 %   \n",
       "23568                  0.000000                 0.60 %   \n",
       "...                         ...                    ...   \n",
       "23731               1569.201202                 0.60 %   \n",
       "23732               1577.307950                 0.60 %   \n",
       "23733               1588.815682                 0.60 %   \n",
       "23734               1606.997043                 0.60 %   \n",
       "23735               1606.997043                 0.60 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "23564                 0.000000                  0.000000            0.000000   \n",
       "23565                 0.000000                  0.000000            0.000000   \n",
       "23566                 0.000000                  0.000000            0.000000   \n",
       "23567                 0.000000                  0.000000            0.000000   \n",
       "23568                 0.000000                  0.000000            0.000000   \n",
       "...                        ...                       ...                 ...   \n",
       "23731                 2.132145                  1.516982            5.218456   \n",
       "23732                 2.097829                  1.509679            5.168820   \n",
       "23733                 2.063456                  1.494107            5.118930   \n",
       "23734                 2.032331                  1.485772            5.071059   \n",
       "23735                 1.997314                  1.460225            5.026884   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "23564                     0.000000  \n",
       "23565                     0.000000  \n",
       "23566                     0.000000  \n",
       "23567                     0.000000  \n",
       "23568                     0.000000  \n",
       "...                            ...  \n",
       "23731                     2.333198  \n",
       "23732                     2.277405  \n",
       "23733                     2.231956  \n",
       "23734                     2.186723  \n",
       "23735                     2.147486  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
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   ],
   "source": [
    "df[df.country == 'Spain']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
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       "      <td>Italy</td>\n",
       "      <td>2020-01-24</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13075</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-01-25</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13076</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-01-26</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>13239</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-07-07</td>\n",
       "      <td>241956</td>\n",
       "      <td>192815</td>\n",
       "      <td>34899</td>\n",
       "      <td>137</td>\n",
       "      <td>574</td>\n",
       "      <td>30</td>\n",
       "      <td>14242</td>\n",
       "      <td>0.056654</td>\n",
       "      <td>14.423697</td>\n",
       "      <td>79.690109</td>\n",
       "      <td>849.507109</td>\n",
       "      <td>4000.633339</td>\n",
       "      <td>235.485047</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>2.046109</td>\n",
       "      <td>0.294497</td>\n",
       "      <td>6.414444</td>\n",
       "      <td>2.991672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13240</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>242149</td>\n",
       "      <td>193640</td>\n",
       "      <td>34914</td>\n",
       "      <td>193</td>\n",
       "      <td>825</td>\n",
       "      <td>15</td>\n",
       "      <td>13595</td>\n",
       "      <td>0.079767</td>\n",
       "      <td>14.418395</td>\n",
       "      <td>79.967293</td>\n",
       "      <td>843.434791</td>\n",
       "      <td>4003.824507</td>\n",
       "      <td>224.787194</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>2.011727</td>\n",
       "      <td>0.278327</td>\n",
       "      <td>6.355268</td>\n",
       "      <td>2.932627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13241</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>242363</td>\n",
       "      <td>193978</td>\n",
       "      <td>34926</td>\n",
       "      <td>214</td>\n",
       "      <td>338</td>\n",
       "      <td>12</td>\n",
       "      <td>13459</td>\n",
       "      <td>0.088375</td>\n",
       "      <td>14.410615</td>\n",
       "      <td>80.036144</td>\n",
       "      <td>836.331961</td>\n",
       "      <td>4007.362901</td>\n",
       "      <td>222.538495</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>1.976264</td>\n",
       "      <td>0.270725</td>\n",
       "      <td>6.294981</td>\n",
       "      <td>2.879118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13242</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-07-10</td>\n",
       "      <td>242639</td>\n",
       "      <td>194273</td>\n",
       "      <td>34938</td>\n",
       "      <td>276</td>\n",
       "      <td>295</td>\n",
       "      <td>12</td>\n",
       "      <td>13428</td>\n",
       "      <td>0.113879</td>\n",
       "      <td>14.399169</td>\n",
       "      <td>80.066683</td>\n",
       "      <td>806.694369</td>\n",
       "      <td>4011.926436</td>\n",
       "      <td>222.025924</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>1.942131</td>\n",
       "      <td>0.265556</td>\n",
       "      <td>6.237815</td>\n",
       "      <td>2.825060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13243</td>\n",
       "      <td>Italy</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>242827</td>\n",
       "      <td>194579</td>\n",
       "      <td>34945</td>\n",
       "      <td>188</td>\n",
       "      <td>306</td>\n",
       "      <td>7</td>\n",
       "      <td>13303</td>\n",
       "      <td>0.077481</td>\n",
       "      <td>14.390904</td>\n",
       "      <td>80.130710</td>\n",
       "      <td>834.351760</td>\n",
       "      <td>4015.034932</td>\n",
       "      <td>219.959105</td>\n",
       "      <td>0.78 %</td>\n",
       "      <td>1.910148</td>\n",
       "      <td>0.258560</td>\n",
       "      <td>6.184715</td>\n",
       "      <td>2.778739</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>172 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country       date  total_cases  recovered_cases  total_deaths  \\\n",
       "13072   Italy 2020-01-22            0                0             0   \n",
       "13073   Italy 2020-01-23            0                0             0   \n",
       "13074   Italy 2020-01-24            0                0             0   \n",
       "13075   Italy 2020-01-25            0                0             0   \n",
       "13076   Italy 2020-01-26            0                0             0   \n",
       "...       ...        ...          ...              ...           ...   \n",
       "13239   Italy 2020-07-07       241956           192815         34899   \n",
       "13240   Italy 2020-07-08       242149           193640         34914   \n",
       "13241   Italy 2020-07-09       242363           193978         34926   \n",
       "13242   Italy 2020-07-10       242639           194273         34938   \n",
       "13243   Italy 2020-07-11       242827           194579         34945   \n",
       "\n",
       "       new_reported_cases  daily_recovered_cases  daily_deaths  active_cases  \\\n",
       "13072                   0                      0             0             0   \n",
       "13073                   0                      0             0             0   \n",
       "13074                   0                      0             0             0   \n",
       "13075                   0                      0             0             0   \n",
       "13076                   0                      0             0             0   \n",
       "...                   ...                    ...           ...           ...   \n",
       "13239                 137                    574            30         14242   \n",
       "13240                 193                    825            15         13595   \n",
       "13241                 214                    338            12         13459   \n",
       "13242                 276                    295            12         13428   \n",
       "13243                 188                    306             7         13303   \n",
       "\n",
       "       cases_growth_rate_in_percent  mortality_rate  recovery_rate  \\\n",
       "13072                      0.000000        0.000000       0.000000   \n",
       "13073                      0.000000        0.000000       0.000000   \n",
       "13074                      0.000000        0.000000       0.000000   \n",
       "13075                      0.000000        0.000000       0.000000   \n",
       "13076                      0.000000        0.000000       0.000000   \n",
       "...                             ...             ...            ...   \n",
       "13239                      0.056654       14.423697      79.690109   \n",
       "13240                      0.079767       14.418395      79.967293   \n",
       "13241                      0.088375       14.410615      80.036144   \n",
       "13242                      0.113879       14.399169      80.066683   \n",
       "13243                      0.077481       14.390904      80.130710   \n",
       "\n",
       "       doubling_time_in_days  total_cases_per_million  \\\n",
       "13072               0.000000                 0.000000   \n",
       "13073               0.000000                 0.000000   \n",
       "13074               0.000000                 0.000000   \n",
       "13075               0.000000                 0.000000   \n",
       "13076               0.000000                 0.000000   \n",
       "...                      ...                      ...   \n",
       "13239             849.507109              4000.633339   \n",
       "13240             843.434791              4003.824507   \n",
       "13241             836.331961              4007.362901   \n",
       "13242             806.694369              4011.926436   \n",
       "13243             834.351760              4015.034932   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "13072                  0.000000                 0.78 %   \n",
       "13073                  0.000000                 0.78 %   \n",
       "13074                  0.000000                 0.78 %   \n",
       "13075                  0.000000                 0.78 %   \n",
       "13076                  0.000000                 0.78 %   \n",
       "...                         ...                    ...   \n",
       "13239                235.485047                 0.78 %   \n",
       "13240                224.787194                 0.78 %   \n",
       "13241                222.538495                 0.78 %   \n",
       "13242                222.025924                 0.78 %   \n",
       "13243                219.959105                 0.78 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "13072                 0.000000                  0.000000            0.000000   \n",
       "13073                 0.000000                  0.000000            0.000000   \n",
       "13074                 0.000000                  0.000000            0.000000   \n",
       "13075                 0.000000                  0.000000            0.000000   \n",
       "13076                 0.000000                  0.000000            0.000000   \n",
       "...                        ...                       ...                 ...   \n",
       "13239                 2.046109                  0.294497            6.414444   \n",
       "13240                 2.011727                  0.278327            6.355268   \n",
       "13241                 1.976264                  0.270725            6.294981   \n",
       "13242                 1.942131                  0.265556            6.237815   \n",
       "13243                 1.910148                  0.258560            6.184715   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "13072                     0.000000  \n",
       "13073                     0.000000  \n",
       "13074                     0.000000  \n",
       "13075                     0.000000  \n",
       "13076                     0.000000  \n",
       "...                            ...  \n",
       "13239                     2.991672  \n",
       "13240                     2.932627  \n",
       "13241                     2.879118  \n",
       "13242                     2.825060  \n",
       "13243                     2.778739  \n",
       "\n",
       "[172 rows x 20 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.country == 'Italy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Latest Day Data\n",
    "ts = df['date'][df.shape[0]-1]\n",
    "last_day_df = pd.DataFrame(df[df.date == ts])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>recovered_cases</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_reported_cases</th>\n",
       "      <th>daily_recovered_cases</th>\n",
       "      <th>daily_deaths</th>\n",
       "      <th>active_cases</th>\n",
       "      <th>cases_growth_rate_in_percent</th>\n",
       "      <th>mortality_rate</th>\n",
       "      <th>recovery_rate</th>\n",
       "      <th>doubling_time_in_days</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>active_cases_per_million</th>\n",
       "      <th>world_population_share</th>\n",
       "      <th>world_total_cases_share</th>\n",
       "      <th>world_active_cases_share</th>\n",
       "      <th>world_deaths_share</th>\n",
       "      <th>world_recovered_cases_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>171</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>34366</td>\n",
       "      <td>21135</td>\n",
       "      <td>994</td>\n",
       "      <td>172</td>\n",
       "      <td>253</td>\n",
       "      <td>23</td>\n",
       "      <td>12237</td>\n",
       "      <td>0.503012</td>\n",
       "      <td>2.892394</td>\n",
       "      <td>61.499738</td>\n",
       "      <td>95.971872</td>\n",
       "      <td>887.026791</td>\n",
       "      <td>315.851331</td>\n",
       "      <td>0.50 %</td>\n",
       "      <td>0.270333</td>\n",
       "      <td>0.237841</td>\n",
       "      <td>0.175922</td>\n",
       "      <td>0.301824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>343</td>\n",
       "      <td>Albania</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>3371</td>\n",
       "      <td>1881</td>\n",
       "      <td>89</td>\n",
       "      <td>93</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>1401</td>\n",
       "      <td>2.837096</td>\n",
       "      <td>2.640166</td>\n",
       "      <td>55.799466</td>\n",
       "      <td>27.130557</td>\n",
       "      <td>1171.128605</td>\n",
       "      <td>486.725356</td>\n",
       "      <td>0.04 %</td>\n",
       "      <td>0.026517</td>\n",
       "      <td>0.027230</td>\n",
       "      <td>0.015752</td>\n",
       "      <td>0.026862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>515</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>18712</td>\n",
       "      <td>13124</td>\n",
       "      <td>1004</td>\n",
       "      <td>470</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>4584</td>\n",
       "      <td>2.576472</td>\n",
       "      <td>5.365541</td>\n",
       "      <td>70.136811</td>\n",
       "      <td>25.762907</td>\n",
       "      <td>428.333187</td>\n",
       "      <td>104.931559</td>\n",
       "      <td>0.56 %</td>\n",
       "      <td>0.147194</td>\n",
       "      <td>0.089096</td>\n",
       "      <td>0.177692</td>\n",
       "      <td>0.187421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>687</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>855</td>\n",
       "      <td>803</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.081871</td>\n",
       "      <td>93.918129</td>\n",
       "      <td>inf</td>\n",
       "      <td>11069.394096</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00 %</td>\n",
       "      <td>0.006726</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009203</td>\n",
       "      <td>0.011467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>859</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>462</td>\n",
       "      <td>118</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>321</td>\n",
       "      <td>0.873362</td>\n",
       "      <td>4.978355</td>\n",
       "      <td>25.541126</td>\n",
       "      <td>16.158390</td>\n",
       "      <td>14.152338</td>\n",
       "      <td>9.833118</td>\n",
       "      <td>0.42 %</td>\n",
       "      <td>0.003634</td>\n",
       "      <td>0.006239</td>\n",
       "      <td>0.004071</td>\n",
       "      <td>0.001685</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>31131</td>\n",
       "      <td>Sao Tome and Principe</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>727</td>\n",
       "      <td>284</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.925722</td>\n",
       "      <td>39.064649</td>\n",
       "      <td>438.238019</td>\n",
       "      <td>3330.157392</td>\n",
       "      <td>1965.113509</td>\n",
       "      <td>0.00 %</td>\n",
       "      <td>0.005719</td>\n",
       "      <td>0.008338</td>\n",
       "      <td>0.002478</td>\n",
       "      <td>0.004056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31303</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>1389</td>\n",
       "      <td>642</td>\n",
       "      <td>365</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>382</td>\n",
       "      <td>0.652174</td>\n",
       "      <td>26.277898</td>\n",
       "      <td>46.220302</td>\n",
       "      <td>45.267821</td>\n",
       "      <td>46.787819</td>\n",
       "      <td>12.867492</td>\n",
       "      <td>0.38 %</td>\n",
       "      <td>0.010926</td>\n",
       "      <td>0.007425</td>\n",
       "      <td>0.064599</td>\n",
       "      <td>0.009168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31475</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>317</td>\n",
       "      <td>296</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>0.955414</td>\n",
       "      <td>2.208202</td>\n",
       "      <td>93.375394</td>\n",
       "      <td>189.491723</td>\n",
       "      <td>366.179352</td>\n",
       "      <td>16.171959</td>\n",
       "      <td>0.01 %</td>\n",
       "      <td>0.002494</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.001239</td>\n",
       "      <td>0.004227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31647</td>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>6506</td>\n",
       "      <td>5176</td>\n",
       "      <td>55</td>\n",
       "      <td>49</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>1275</td>\n",
       "      <td>0.758866</td>\n",
       "      <td>0.845374</td>\n",
       "      <td>79.557332</td>\n",
       "      <td>88.522346</td>\n",
       "      <td>685.394605</td>\n",
       "      <td>134.318801</td>\n",
       "      <td>0.12 %</td>\n",
       "      <td>0.051178</td>\n",
       "      <td>0.024781</td>\n",
       "      <td>0.009734</td>\n",
       "      <td>0.073917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31819</td>\n",
       "      <td>Lesotho</td>\n",
       "      <td>2020-07-11</td>\n",
       "      <td>184</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>157</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.543478</td>\n",
       "      <td>14.130435</td>\n",
       "      <td>2.482425</td>\n",
       "      <td>86.029590</td>\n",
       "      <td>73.405682</td>\n",
       "      <td>0.03 %</td>\n",
       "      <td>0.001447</td>\n",
       "      <td>0.003051</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000371</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>185 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     country       date  total_cases  recovered_cases  \\\n",
       "171              Afghanistan 2020-07-11        34366            21135   \n",
       "343                  Albania 2020-07-11         3371             1881   \n",
       "515                  Algeria 2020-07-11        18712            13124   \n",
       "687                  Andorra 2020-07-11          855              803   \n",
       "859                   Angola 2020-07-11          462              118   \n",
       "...                      ...        ...          ...              ...   \n",
       "31131  Sao Tome and Principe 2020-07-11          727              284   \n",
       "31303                  Yemen 2020-07-11         1389              642   \n",
       "31475                Comoros 2020-07-11          317              296   \n",
       "31647             Tajikistan 2020-07-11         6506             5176   \n",
       "31819                Lesotho 2020-07-11          184               26   \n",
       "\n",
       "       total_deaths  new_reported_cases  daily_recovered_cases  daily_deaths  \\\n",
       "171             994                 172                    253            23   \n",
       "343              89                  93                      6             4   \n",
       "515            1004                 470                      0             8   \n",
       "687              52                   0                      0             0   \n",
       "859              23                   4                      1             0   \n",
       "...             ...                 ...                    ...           ...   \n",
       "31131            14                   0                      0             0   \n",
       "31303           365                   9                     12             1   \n",
       "31475             7                   3                     24             0   \n",
       "31647            55                  49                     61             0   \n",
       "31819             1                   0                      0             0   \n",
       "\n",
       "       active_cases  cases_growth_rate_in_percent  mortality_rate  \\\n",
       "171           12237                      0.503012        2.892394   \n",
       "343            1401                      2.837096        2.640166   \n",
       "515            4584                      2.576472        5.365541   \n",
       "687               0                      0.000000        6.081871   \n",
       "859             321                      0.873362        4.978355   \n",
       "...             ...                           ...             ...   \n",
       "31131           429                      0.000000        1.925722   \n",
       "31303           382                      0.652174       26.277898   \n",
       "31475            14                      0.955414        2.208202   \n",
       "31647          1275                      0.758866        0.845374   \n",
       "31819           157                      0.000000        0.543478   \n",
       "\n",
       "       recovery_rate  doubling_time_in_days  total_cases_per_million  \\\n",
       "171        61.499738              95.971872               887.026791   \n",
       "343        55.799466              27.130557              1171.128605   \n",
       "515        70.136811              25.762907               428.333187   \n",
       "687        93.918129                    inf             11069.394096   \n",
       "859        25.541126              16.158390                14.152338   \n",
       "...              ...                    ...                      ...   \n",
       "31131      39.064649             438.238019              3330.157392   \n",
       "31303      46.220302              45.267821                46.787819   \n",
       "31475      93.375394             189.491723               366.179352   \n",
       "31647      79.557332              88.522346               685.394605   \n",
       "31819      14.130435               2.482425                86.029590   \n",
       "\n",
       "       active_cases_per_million world_population_share  \\\n",
       "171                  315.851331                 0.50 %   \n",
       "343                  486.725356                 0.04 %   \n",
       "515                  104.931559                 0.56 %   \n",
       "687                    0.000000                 0.00 %   \n",
       "859                    9.833118                 0.42 %   \n",
       "...                         ...                    ...   \n",
       "31131               1965.113509                 0.00 %   \n",
       "31303                 12.867492                 0.38 %   \n",
       "31475                 16.171959                 0.01 %   \n",
       "31647                134.318801                 0.12 %   \n",
       "31819                 73.405682                 0.03 %   \n",
       "\n",
       "       world_total_cases_share  world_active_cases_share  world_deaths_share  \\\n",
       "171                   0.270333                  0.237841            0.175922   \n",
       "343                   0.026517                  0.027230            0.015752   \n",
       "515                   0.147194                  0.089096            0.177692   \n",
       "687                   0.006726                  0.000000            0.009203   \n",
       "859                   0.003634                  0.006239            0.004071   \n",
       "...                        ...                       ...                 ...   \n",
       "31131                 0.005719                  0.008338            0.002478   \n",
       "31303                 0.010926                  0.007425            0.064599   \n",
       "31475                 0.002494                  0.000272            0.001239   \n",
       "31647                 0.051178                  0.024781            0.009734   \n",
       "31819                 0.001447                  0.003051            0.000177   \n",
       "\n",
       "       world_recovered_cases_share  \n",
       "171                       0.301824  \n",
       "343                       0.026862  \n",
       "515                       0.187421  \n",
       "687                       0.011467  \n",
       "859                       0.001685  \n",
       "...                            ...  \n",
       "31131                     0.004056  \n",
       "31303                     0.009168  \n",
       "31475                     0.004227  \n",
       "31647                     0.073917  \n",
       "31819                     0.000371  \n",
       "\n",
       "[185 rows x 20 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_day_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(r'final_data/covid_time_series.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumulative.to_csv(r'final_data/covid_cumulative.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "population.to_csv(r'final_data/population_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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