api.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Source"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://api.covid19india.org/  \n",
    "https://api.covid19india.org/csv/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# to get web contents\n",
    "import requests\n",
    "# to parse json contents\n",
    "import json\n",
    "# to parse csv files\n",
    "import csv\n",
    "\n",
    "# for numerical operations\n",
    "import numpy as np\n",
    "# to store and analysis data in dataframes\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Raw data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Patient Number</th>\n",
       "      <th>State Patient Number</th>\n",
       "      <th>Date Announced</th>\n",
       "      <th>Estimated Onset Date</th>\n",
       "      <th>Age Bracket</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Detected City</th>\n",
       "      <th>Detected District</th>\n",
       "      <th>Detected State</th>\n",
       "      <th>State code</th>\n",
       "      <th>...</th>\n",
       "      <th>Contracted from which Patient (Suspected)</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Type of transmission</th>\n",
       "      <th>Status Change Date</th>\n",
       "      <th>Source_1</th>\n",
       "      <th>Source_2</th>\n",
       "      <th>Source_3</th>\n",
       "      <th>Backup Notes</th>\n",
       "      <th>Num Cases</th>\n",
       "      <th>Entry_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>KL-TS-P1</td>\n",
       "      <td>30/01/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "      <td>F</td>\n",
       "      <td>Thrissur</td>\n",
       "      <td>Thrissur</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>KL</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>Imported</td>\n",
       "      <td>14/02/2020</td>\n",
       "      <td>https://twitter.com/vijayanpinarayi/status/122...</td>\n",
       "      <td>https://weather.com/en-IN/india/news/news/2020...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Student from Wuhan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>KL-AL-P1</td>\n",
       "      <td>02/02/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alappuzha</td>\n",
       "      <td>Alappuzha</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>KL</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>Imported</td>\n",
       "      <td>14/02/2020</td>\n",
       "      <td>https://www.indiatoday.in/india/story/kerala-r...</td>\n",
       "      <td>https://weather.com/en-IN/india/news/news/2020...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Student from Wuhan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>KL-KS-P1</td>\n",
       "      <td>03/02/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kasaragod</td>\n",
       "      <td>Kasaragod</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>KL</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>Imported</td>\n",
       "      <td>14/02/2020</td>\n",
       "      <td>https://www.indiatoday.in/india/story/kerala-n...</td>\n",
       "      <td>https://twitter.com/ANI/status/122422148580539...</td>\n",
       "      <td>https://weather.com/en-IN/india/news/news/2020...</td>\n",
       "      <td>Student from Wuhan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>DL-P1</td>\n",
       "      <td>02/03/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45</td>\n",
       "      <td>M</td>\n",
       "      <td>East Delhi (Mayur Vihar)</td>\n",
       "      <td>East Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>DL</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>Imported</td>\n",
       "      <td>15/03/2020</td>\n",
       "      <td>https://www.indiatoday.in/india/story/not-a-ja...</td>\n",
       "      <td>https://economictimes.indiatimes.com/news/poli...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Travel history to Italy and Austria</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>TS-P1</td>\n",
       "      <td>02/03/2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>M</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>TG</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>Imported</td>\n",
       "      <td>02/03/2020</td>\n",
       "      <td>https://www.deccanherald.com/national/south/qu...</td>\n",
       "      <td>https://www.indiatoday.in/india/story/coronavi...</td>\n",
       "      <td>https://www.thehindu.com/news/national/coronav...</td>\n",
       "      <td>Travel history to Dubai, Singapore contact</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Patient Number State Patient Number Date Announced  Estimated Onset Date  \\\n",
       "0             1.0             KL-TS-P1     30/01/2020                   NaN   \n",
       "1             2.0             KL-AL-P1     02/02/2020                   NaN   \n",
       "2             3.0             KL-KS-P1     03/02/2020                   NaN   \n",
       "3             4.0                DL-P1     02/03/2020                   NaN   \n",
       "4             5.0                TS-P1     02/03/2020                   NaN   \n",
       "\n",
       "  Age Bracket Gender             Detected City Detected District  \\\n",
       "0          20      F                  Thrissur          Thrissur   \n",
       "1         NaN    NaN                 Alappuzha         Alappuzha   \n",
       "2         NaN    NaN                 Kasaragod         Kasaragod   \n",
       "3          45      M  East Delhi (Mayur Vihar)        East Delhi   \n",
       "4          24      M                 Hyderabad         Hyderabad   \n",
       "\n",
       "  Detected State State code  ... Contracted from which Patient (Suspected)  \\\n",
       "0         Kerala         KL  ...                                       NaN   \n",
       "1         Kerala         KL  ...                                       NaN   \n",
       "2         Kerala         KL  ...                                       NaN   \n",
       "3          Delhi         DL  ...                                       NaN   \n",
       "4      Telangana         TG  ...                                       NaN   \n",
       "\n",
       "  Nationality Type of transmission Status Change Date  \\\n",
       "0       India             Imported         14/02/2020   \n",
       "1       India             Imported         14/02/2020   \n",
       "2       India             Imported         14/02/2020   \n",
       "3       India             Imported         15/03/2020   \n",
       "4       India             Imported         02/03/2020   \n",
       "\n",
       "                                            Source_1  \\\n",
       "0  https://twitter.com/vijayanpinarayi/status/122...   \n",
       "1  https://www.indiatoday.in/india/story/kerala-r...   \n",
       "2  https://www.indiatoday.in/india/story/kerala-n...   \n",
       "3  https://www.indiatoday.in/india/story/not-a-ja...   \n",
       "4  https://www.deccanherald.com/national/south/qu...   \n",
       "\n",
       "                                            Source_2  \\\n",
       "0  https://weather.com/en-IN/india/news/news/2020...   \n",
       "1  https://weather.com/en-IN/india/news/news/2020...   \n",
       "2  https://twitter.com/ANI/status/122422148580539...   \n",
       "3  https://economictimes.indiatimes.com/news/poli...   \n",
       "4  https://www.indiatoday.in/india/story/coronavi...   \n",
       "\n",
       "                                            Source_3  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2  https://weather.com/en-IN/india/news/news/2020...   \n",
       "3                                                NaN   \n",
       "4  https://www.thehindu.com/news/national/coronav...   \n",
       "\n",
       "                                 Backup Notes Num Cases Entry_ID  \n",
       "0                          Student from Wuhan       1.0      NaN  \n",
       "1                          Student from Wuhan       1.0      NaN  \n",
       "2                          Student from Wuhan       1.0      NaN  \n",
       "3         Travel history to Italy and Austria       1.0      NaN  \n",
       "4  Travel history to Dubai, Singapore contact       1.0      NaN  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "raw_1 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data1.csv')\n",
    "raw_2 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data2.csv')\n",
    "raw_3 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data3.csv')\n",
    "raw_4 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data4.csv')\n",
    "raw_5 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data5.csv')\n",
    "raw_6 = pd.read_csv('https://api.covid19india.org/csv/latest/raw_data6.csv')\n",
    "\n",
    "# concatenate dfs\n",
    "full_data = pd.concat([raw_1, raw_2, raw_3, raw_4, raw_5, raw_6])\n",
    "\n",
    "# save to csv`\n",
    "full_data.to_csv('data/patients_data.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "full_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Daily cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Daily Confirmed</th>\n",
       "      <th>Total Confirmed</th>\n",
       "      <th>Daily Recovered</th>\n",
       "      <th>Total Recovered</th>\n",
       "      <th>Daily Deceased</th>\n",
       "      <th>Total Deceased</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30 January</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31 January</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01 February</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02 February</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03 February</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  Daily Confirmed  Total Confirmed  Daily Recovered  \\\n",
       "0   30 January                 1                1                0   \n",
       "1   31 January                 0                1                0   \n",
       "2  01 February                 0                1                0   \n",
       "3  02 February                 1                2                0   \n",
       "4  03 February                 1                3                0   \n",
       "\n",
       "   Total Recovered  Daily Deceased  Total Deceased  \n",
       "0                0               0               0  \n",
       "1                0               0               0  \n",
       "2                0               0               0  \n",
       "3                0               0               0  \n",
       "4                0               0               0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "day_wise = pd.read_csv('https://api.covid19india.org/csv/latest/case_time_series.csv')\n",
    "\n",
    "# save as a .csv file\n",
    "day_wise.to_csv('data/nation_level_daily.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "day_wise.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latest - State wise "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Active</th>\n",
       "      <th>Last_Updated_Time</th>\n",
       "      <th>Migrated_Other</th>\n",
       "      <th>State_code</th>\n",
       "      <th>Delta_Confirmed</th>\n",
       "      <th>Delta_Recovered</th>\n",
       "      <th>Delta_Deaths</th>\n",
       "      <th>State_Notes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total</td>\n",
       "      <td>970743</td>\n",
       "      <td>613878</td>\n",
       "      <td>24936</td>\n",
       "      <td>331540</td>\n",
       "      <td>16/07/2020 11:39:58</td>\n",
       "      <td>389</td>\n",
       "      <td>TT</td>\n",
       "      <td>574</td>\n",
       "      <td>143</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>275640</td>\n",
       "      <td>152613</td>\n",
       "      <td>10928</td>\n",
       "      <td>111801</td>\n",
       "      <td>15/07/2020 19:43:06</td>\n",
       "      <td>298</td>\n",
       "      <td>MH</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>298 cases were marked as non-covid deaths in M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>151820</td>\n",
       "      <td>102310</td>\n",
       "      <td>2167</td>\n",
       "      <td>47343</td>\n",
       "      <td>15/07/2020 19:18:00</td>\n",
       "      <td>0</td>\n",
       "      <td>TN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2 deaths cross notified to other states from C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>116993</td>\n",
       "      <td>95699</td>\n",
       "      <td>3487</td>\n",
       "      <td>17807</td>\n",
       "      <td>15/07/2020 20:54:01</td>\n",
       "      <td>0</td>\n",
       "      <td>DL</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>[July 14]: Value for the total tests conducted...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gujarat</td>\n",
       "      <td>44648</td>\n",
       "      <td>31346</td>\n",
       "      <td>2080</td>\n",
       "      <td>11222</td>\n",
       "      <td>15/07/2020 20:17:01</td>\n",
       "      <td>0</td>\n",
       "      <td>GJ</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         State  Confirmed  Recovered  Deaths  Active    Last_Updated_Time  \\\n",
       "0        Total     970743     613878   24936  331540  16/07/2020 11:39:58   \n",
       "1  Maharashtra     275640     152613   10928  111801  15/07/2020 19:43:06   \n",
       "2   Tamil Nadu     151820     102310    2167   47343  15/07/2020 19:18:00   \n",
       "3        Delhi     116993      95699    3487   17807  15/07/2020 20:54:01   \n",
       "4      Gujarat      44648      31346    2080   11222  15/07/2020 20:17:01   \n",
       "\n",
       "   Migrated_Other State_code  Delta_Confirmed  Delta_Recovered  Delta_Deaths  \\\n",
       "0             389         TT              574              143             7   \n",
       "1             298         MH                0                0             0   \n",
       "2               0         TN                0                0             0   \n",
       "3               0         DL                0                0             0   \n",
       "4               0         GJ                0                0             0   \n",
       "\n",
       "                                         State_Notes  \n",
       "0                                                NaN  \n",
       "1  298 cases were marked as non-covid deaths in M...  \n",
       "2  2 deaths cross notified to other states from C...  \n",
       "3  [July 14]: Value for the total tests conducted...  \n",
       "4                                                NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## https://api.covid19india.org/csv/latest/state_wise.csv\n",
    "    \n",
    "# read data\n",
    "latest = pd.read_csv('https://api.covid19india.org/csv/latest/state_wise.csv')\n",
    "\n",
    "# save as a .csv file`\n",
    "latest.to_csv('data/state_level_latest.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "latest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## State wise daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\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>Status</th>\n",
       "      <th>Date</th>\n",
       "      <th>State</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deceased</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>State_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01-Apr-20</td>\n",
       "      <td>AN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01-Apr-20</td>\n",
       "      <td>AP</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01-Apr-20</td>\n",
       "      <td>AR</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01-Apr-20</td>\n",
       "      <td>AS</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Assam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01-Apr-20</td>\n",
       "      <td>BR</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Bihar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4831</th>\n",
       "      <td>31-May-20</td>\n",
       "      <td>TT</td>\n",
       "      <td>8789</td>\n",
       "      <td>222</td>\n",
       "      <td>4928</td>\n",
       "      <td>Total</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4832</th>\n",
       "      <td>31-May-20</td>\n",
       "      <td>UN</td>\n",
       "      <td>448</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>State Unassigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4833</th>\n",
       "      <td>31-May-20</td>\n",
       "      <td>UP</td>\n",
       "      <td>374</td>\n",
       "      <td>4</td>\n",
       "      <td>192</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4834</th>\n",
       "      <td>31-May-20</td>\n",
       "      <td>UT</td>\n",
       "      <td>158</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Uttarakhand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4835</th>\n",
       "      <td>31-May-20</td>\n",
       "      <td>WB</td>\n",
       "      <td>371</td>\n",
       "      <td>8</td>\n",
       "      <td>187</td>\n",
       "      <td>West Bengal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4836 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Status       Date State  Confirmed  Deceased  Recovered  \\\n",
       "0       01-Apr-20    AN          0         0          0   \n",
       "1       01-Apr-20    AP         67         0          1   \n",
       "2       01-Apr-20    AR          0         0          0   \n",
       "3       01-Apr-20    AS         15         0          0   \n",
       "4       01-Apr-20    BR          3         0          0   \n",
       "...           ...   ...        ...       ...        ...   \n",
       "4831    31-May-20    TT       8789       222       4928   \n",
       "4832    31-May-20    UN        448         0          0   \n",
       "4833    31-May-20    UP        374         4        192   \n",
       "4834    31-May-20    UT        158         0          0   \n",
       "4835    31-May-20    WB        371         8        187   \n",
       "\n",
       "Status                   State_Name  \n",
       "0       Andaman and Nicobar Islands  \n",
       "1                    Andhra Pradesh  \n",
       "2                 Arunachal Pradesh  \n",
       "3                             Assam  \n",
       "4                             Bihar  \n",
       "...                             ...  \n",
       "4831                          Total  \n",
       "4832               State Unassigned  \n",
       "4833                  Uttar Pradesh  \n",
       "4834                    Uttarakhand  \n",
       "4835                    West Bengal  \n",
       "\n",
       "[4836 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "state_wise_daily = pd.read_csv('https://api.covid19india.org/csv/latest/state_wise_daily.csv')\n",
    "\n",
    "# melt dataframe\n",
    "state_wise_daily = state_wise_daily.melt(id_vars=['Date', 'Status'], \n",
    "                                         value_vars=state_wise_daily.columns[2:], \n",
    "                                         var_name='State', value_name='Count')\n",
    "\n",
    "# pivot table\n",
    "state_wise_daily = state_wise_daily.pivot_table(index=['Date', 'State'], \n",
    "                                                columns=['Status'], \n",
    "                                                values='Count').reset_index()\n",
    "\n",
    "# map state names to state codes\n",
    "state_codes = {code:state for code, state in zip(latest['State_code'], latest['State'])}\n",
    "state_codes['DD'] = 'Daman and Diu'\n",
    "state_wise_daily['State_Name'] = state_wise_daily['State'].map(state_codes)\n",
    "\n",
    "# save as a .csv file\n",
    "state_wise_daily.to_csv('data/state_level_daily.csv')\n",
    "\n",
    "# first few rows\n",
    "state_wise_daily"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## District wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "        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>SlNo</th>\n",
       "      <th>State_Code</th>\n",
       "      <th>State</th>\n",
       "      <th>District_Key</th>\n",
       "      <th>District</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Active</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Deceased</th>\n",
       "      <th>Migrated_Other</th>\n",
       "      <th>Delta_Confirmed</th>\n",
       "      <th>Delta_Active</th>\n",
       "      <th>Delta_Recovered</th>\n",
       "      <th>Delta_Deceased</th>\n",
       "      <th>District_Notes</th>\n",
       "      <th>Last_Updated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>UN</td>\n",
       "      <td>State Unassigned</td>\n",
       "      <td>UN_Unassigned</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>1435</td>\n",
       "      <td>1435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-239</td>\n",
       "      <td>-239</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>AN</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>AN_Nicobars</td>\n",
       "      <td>Nicobars</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>AN</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>AN_North and Middle Andaman</td>\n",
       "      <td>North and Middle Andaman</td>\n",
       "      <td>1</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>AN</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>AN_South Andaman</td>\n",
       "      <td>South Andaman</td>\n",
       "      <td>51</td>\n",
       "      <td>19</td>\n",
       "      <td>32</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>AP</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>AP_Foreign Evacuees</td>\n",
       "      <td>Foreign Evacuees</td>\n",
       "      <td>432</td>\n",
       "      <td>103</td>\n",
       "      <td>329</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SlNo State_Code                        State                 District_Key  \\\n",
       "0     0         UN             State Unassigned                UN_Unassigned   \n",
       "1     1         AN  Andaman and Nicobar Islands                  AN_Nicobars   \n",
       "2     2         AN  Andaman and Nicobar Islands  AN_North and Middle Andaman   \n",
       "3     3         AN  Andaman and Nicobar Islands             AN_South Andaman   \n",
       "4     0         AP               Andhra Pradesh          AP_Foreign Evacuees   \n",
       "\n",
       "                   District  Confirmed  Active  Recovered  Deceased  \\\n",
       "0                Unassigned       1435    1435          0         0   \n",
       "1                  Nicobars          0       0          0         0   \n",
       "2  North and Middle Andaman          1       0          1         0   \n",
       "3             South Andaman         51      19         32         0   \n",
       "4          Foreign Evacuees        432     103        329         0   \n",
       "\n",
       "   Migrated_Other  Delta_Confirmed  Delta_Active  Delta_Recovered  \\\n",
       "0               0             -239          -239                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",
       "   Delta_Deceased District_Notes Last_Updated  \n",
       "0               0            NaN          NaN  \n",
       "1               0            NaN          NaN  \n",
       "2               0            NaN          NaN  \n",
       "3               0            NaN          NaN  \n",
       "4               0            NaN          NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "district_wise = pd.read_csv('https://api.covid19india.org/csv/latest/district_wise.csv')\n",
    "\n",
    "# save as .csv file\n",
    "district_wise.to_csv('data/district_level_latest.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "district_wise.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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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>Update Time Stamp</th>\n",
       "      <th>Tested As Of</th>\n",
       "      <th>Total Samples Tested</th>\n",
       "      <th>Total Individuals Tested</th>\n",
       "      <th>Total Positive Cases</th>\n",
       "      <th>Tests conducted by Private Labs</th>\n",
       "      <th>Sample Reported today</th>\n",
       "      <th>Positive cases from samples reported</th>\n",
       "      <th>Source</th>\n",
       "      <th>Source 1</th>\n",
       "      <th>Test positivity rate</th>\n",
       "      <th>Individuals Tested Per Confirmed Case</th>\n",
       "      <th>Tests Per Confirmed Case</th>\n",
       "      <th>Tests per million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13/03/2020 00:00:00</td>\n",
       "      <td>13/03/2020</td>\n",
       "      <td>6500.0</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Press_Release_ICMR_13March2020.pdf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.20%</td>\n",
       "      <td>75.64</td>\n",
       "      <td>83.33</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18/03/2020 18:00:00</td>\n",
       "      <td>18/03/2020</td>\n",
       "      <td>13125.0</td>\n",
       "      <td>12235.0</td>\n",
       "      <td>150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICMR_website_update_18March_6PM_IST.pdf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.14%</td>\n",
       "      <td>81.57</td>\n",
       "      <td>87.50</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19/03/2020 10:00:00</td>\n",
       "      <td>19/03/2020</td>\n",
       "      <td>13316.0</td>\n",
       "      <td>12426.0</td>\n",
       "      <td>168</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICMR_website_update_19March_10AM_IST_V2.pdf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.26%</td>\n",
       "      <td>73.96</td>\n",
       "      <td>79.26</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19/03/2020 18:00:00</td>\n",
       "      <td>19/03/2020</td>\n",
       "      <td>14175.0</td>\n",
       "      <td>13285.0</td>\n",
       "      <td>182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICMR_website_update_19March_6PM_IST.pdf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.28%</td>\n",
       "      <td>72.99</td>\n",
       "      <td>77.88</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20/03/2020 10:00:00</td>\n",
       "      <td>20/03/2020</td>\n",
       "      <td>14376.0</td>\n",
       "      <td>13486.0</td>\n",
       "      <td>206</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICMR_website_update_20March_10AM_IST.pdf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.43%</td>\n",
       "      <td>65.47</td>\n",
       "      <td>69.79</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Update Time Stamp Tested As Of  Total Samples Tested  \\\n",
       "0  13/03/2020 00:00:00   13/03/2020                6500.0   \n",
       "1  18/03/2020 18:00:00   18/03/2020               13125.0   \n",
       "2  19/03/2020 10:00:00   19/03/2020               13316.0   \n",
       "3  19/03/2020 18:00:00   19/03/2020               14175.0   \n",
       "4  20/03/2020 10:00:00   20/03/2020               14376.0   \n",
       "\n",
       "   Total Individuals Tested Total Positive Cases  \\\n",
       "0                    5900.0                   78   \n",
       "1                   12235.0                  150   \n",
       "2                   12426.0                  168   \n",
       "3                   13285.0                  182   \n",
       "4                   13486.0                  206   \n",
       "\n",
       "   Tests conducted by Private Labs Sample Reported today  \\\n",
       "0                              NaN                   NaN   \n",
       "1                              NaN                   NaN   \n",
       "2                              NaN                   NaN   \n",
       "3                              NaN                   NaN   \n",
       "4                              NaN                   NaN   \n",
       "\n",
       "   Positive cases from samples reported  \\\n",
       "0                                   NaN   \n",
       "1                                   NaN   \n",
       "2                                   NaN   \n",
       "3                                   NaN   \n",
       "4                                   NaN   \n",
       "\n",
       "                                        Source Source 1 Test positivity rate  \\\n",
       "0           Press_Release_ICMR_13March2020.pdf      NaN                1.20%   \n",
       "1      ICMR_website_update_18March_6PM_IST.pdf      NaN                1.14%   \n",
       "2  ICMR_website_update_19March_10AM_IST_V2.pdf      NaN                1.26%   \n",
       "3      ICMR_website_update_19March_6PM_IST.pdf      NaN                1.28%   \n",
       "4     ICMR_website_update_20March_10AM_IST.pdf      NaN                1.43%   \n",
       "\n",
       "   Individuals Tested Per Confirmed Case  Tests Per Confirmed Case  \\\n",
       "0                                  75.64                     83.33   \n",
       "1                                  81.57                     87.50   \n",
       "2                                  73.96                     79.26   \n",
       "3                                  72.99                     77.88   \n",
       "4                                  65.47                     69.79   \n",
       "\n",
       "   Tests per million  \n",
       "0                5.0  \n",
       "1               10.0  \n",
       "2               10.0  \n",
       "3               11.0  \n",
       "4               11.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "tests_day_wise = pd.read_csv('https://api.covid19india.org/csv/latest/tested_numbers_icmr_data.csv')\n",
    "\n",
    "# save as .csv file\n",
    "tests_day_wise.to_csv('data/tests_day_wise.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "tests_day_wise.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## State wise tests no."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Updated On</th>\n",
       "      <th>State</th>\n",
       "      <th>Total Tested</th>\n",
       "      <th>Tag (Total Tested)</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Negative</th>\n",
       "      <th>Unconfirmed</th>\n",
       "      <th>Cumulative People In Quarantine</th>\n",
       "      <th>Total People Currently in Quarantine</th>\n",
       "      <th>Tag (People in Quarantine)</th>\n",
       "      <th>...</th>\n",
       "      <th>Corona Enquiry Calls</th>\n",
       "      <th>Num Calls State Helpline</th>\n",
       "      <th>Source1</th>\n",
       "      <th>Source2</th>\n",
       "      <th>Source3</th>\n",
       "      <th>Test positivity rate</th>\n",
       "      <th>Tests per thousand</th>\n",
       "      <th>Tests per million</th>\n",
       "      <th>Tests per positive case</th>\n",
       "      <th>Population NCP 2019 Projection</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17/04/2020</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>1403.0</td>\n",
       "      <td>Samples Sent</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1210</td>\n",
       "      <td>181.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://t.me/indiacovid/2550</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.86%</td>\n",
       "      <td>3.53</td>\n",
       "      <td>3534.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>397000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24/04/2020</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>2679.0</td>\n",
       "      <td>Samples Sent</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>246.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>614.0</td>\n",
       "      <td>Institutional</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>280.0</td>\n",
       "      <td>https://t.me/indiacovid/3147?single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.01%</td>\n",
       "      <td>6.75</td>\n",
       "      <td>6748.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>397000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>27/04/2020</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>2848.0</td>\n",
       "      <td>Samples Sent</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>724.0</td>\n",
       "      <td>Institutional</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>298.0</td>\n",
       "      <td>https://t.me/indiacovid/3365?single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.16%</td>\n",
       "      <td>7.17</td>\n",
       "      <td>7174.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>397000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Updated On                        State  Total Tested Tag (Total Tested)  \\\n",
       "0  17/04/2020  Andaman and Nicobar Islands        1403.0       Samples Sent   \n",
       "1  24/04/2020  Andaman and Nicobar Islands        2679.0       Samples Sent   \n",
       "2  27/04/2020  Andaman and Nicobar Islands        2848.0       Samples Sent   \n",
       "\n",
       "   Positive Negative  Unconfirmed  Cumulative People In Quarantine  \\\n",
       "0      12.0     1210        181.0                              NaN   \n",
       "1      27.0      NaN        246.0                              NaN   \n",
       "2      33.0      NaN        106.0                              NaN   \n",
       "\n",
       "   Total People Currently in Quarantine Tag (People in Quarantine)  ...  \\\n",
       "0                                   NaN                        NaN  ...   \n",
       "1                                 614.0              Institutional  ...   \n",
       "2                                 724.0              Institutional  ...   \n",
       "\n",
       "   Corona Enquiry Calls  Num Calls State Helpline  \\\n",
       "0                   NaN                       NaN   \n",
       "1                   NaN                     280.0   \n",
       "2                   NaN                     298.0   \n",
       "\n",
       "                               Source1  Source2  Source3  \\\n",
       "0         https://t.me/indiacovid/2550      NaN      NaN   \n",
       "1  https://t.me/indiacovid/3147?single      NaN      NaN   \n",
       "2  https://t.me/indiacovid/3365?single      NaN      NaN   \n",
       "\n",
       "   Test positivity rate  Tests per thousand  Tests per million  \\\n",
       "0                 0.86%                3.53             3534.0   \n",
       "1                 1.01%                6.75             6748.0   \n",
       "2                 1.16%                7.17             7174.0   \n",
       "\n",
       "   Tests per positive case  Population NCP 2019 Projection  \n",
       "0                    117.0                        397000.0  \n",
       "1                     99.0                        397000.0  \n",
       "2                     86.0                        397000.0  \n",
       "\n",
       "[3 rows x 28 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "tests_state_wise = pd.read_csv('https://api.covid19india.org/csv/latest/statewise_tested_numbers_data.csv')\n",
    "\n",
    "# save as .csv file\n",
    "tests_state_wise.to_csv('data/tests_state_wise.csv', index=False)\n",
    "\n",
    "# first few rows\n",
    "tests_state_wise.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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