COVID-BI.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### input data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sno</th>\n",
       "      <th>Date</th>\n",
       "      <th>Province/State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Last Update</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>1715</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Madison, WI</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-05T21:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>1716</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Orange, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:53:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>1717</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>San Antonio, TX</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-13T18:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>1718</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-09T07:03:04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>1719</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Tempe, AZ</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:43:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1719 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sno                 Date   Province/State Country          Last Update  \\\n",
       "0        1  01/22/2020 12:00:00            Anhui   China  01/22/2020 12:00:00   \n",
       "1        2  01/22/2020 12:00:00          Beijing   China  01/22/2020 12:00:00   \n",
       "2        3  01/22/2020 12:00:00        Chongqing   China  01/22/2020 12:00:00   \n",
       "3        4  01/22/2020 12:00:00           Fujian   China  01/22/2020 12:00:00   \n",
       "4        5  01/22/2020 12:00:00            Gansu   China  01/22/2020 12:00:00   \n",
       "...    ...                  ...              ...     ...                  ...   \n",
       "1714  1715  02/17/2020 22:00:00      Madison, WI      US  2020-02-05T21:53:02   \n",
       "1715  1716  02/17/2020 22:00:00       Orange, CA      US  2020-02-01T19:53:03   \n",
       "1716  1717  02/17/2020 22:00:00  San Antonio, TX      US  2020-02-13T18:53:02   \n",
       "1717  1718  02/17/2020 22:00:00      Seattle, WA      US  2020-02-09T07:03:04   \n",
       "1718  1719  02/17/2020 22:00:00        Tempe, AZ      US  2020-02-01T19:43:03   \n",
       "\n",
       "      Confirmed  Deaths  Recovered  \n",
       "0             1       0          0  \n",
       "1            14       0          0  \n",
       "2             6       0          0  \n",
       "3             1       0          0  \n",
       "4             0       0          0  \n",
       "...         ...     ...        ...  \n",
       "1714          1       0          0  \n",
       "1715          1       0          0  \n",
       "1716          1       0          0  \n",
       "1717          1       0          1  \n",
       "1718          1       0          0  \n",
       "\n",
       "[1719 rows x 8 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('C:\\\\Users\\\\User\\\\Desktop\\\\final12652\\\\2019_nCoV_data.csv')\n",
    "data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sno               False\n",
       "Date              False\n",
       "Province/State     True\n",
       "Country           False\n",
       "Last Update       False\n",
       "Confirmed         False\n",
       "Deaths            False\n",
       "Recovered         False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
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       "      <td>Beijing</td>\n",
       "      <td>China</td>\n",
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       "      <td>14</td>\n",
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       "      <th>2</th>\n",
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       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>1714</th>\n",
       "      <td>1715</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Madison, WI</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-05T21:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>1716</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Orange, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:53:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>1717</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>San Antonio, TX</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-13T18:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>1718</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-09T07:03:04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>1719</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Tempe, AZ</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:43:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "<p>1719 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sno                 Date   Province/State Country          Last Update  \\\n",
       "0        1  01/22/2020 12:00:00            Anhui   China  01/22/2020 12:00:00   \n",
       "1        2  01/22/2020 12:00:00          Beijing   China  01/22/2020 12:00:00   \n",
       "2        3  01/22/2020 12:00:00        Chongqing   China  01/22/2020 12:00:00   \n",
       "3        4  01/22/2020 12:00:00           Fujian   China  01/22/2020 12:00:00   \n",
       "4        5  01/22/2020 12:00:00            Gansu   China  01/22/2020 12:00:00   \n",
       "...    ...                  ...              ...     ...                  ...   \n",
       "1714  1715  02/17/2020 22:00:00      Madison, WI      US  2020-02-05T21:53:02   \n",
       "1715  1716  02/17/2020 22:00:00       Orange, CA      US  2020-02-01T19:53:03   \n",
       "1716  1717  02/17/2020 22:00:00  San Antonio, TX      US  2020-02-13T18:53:02   \n",
       "1717  1718  02/17/2020 22:00:00      Seattle, WA      US  2020-02-09T07:03:04   \n",
       "1718  1719  02/17/2020 22:00:00        Tempe, AZ      US  2020-02-01T19:43:03   \n",
       "\n",
       "      Confirmed  Deaths  Recovered  \n",
       "0             1       0          0  \n",
       "1            14       0          0  \n",
       "2             6       0          0  \n",
       "3             1       0          0  \n",
       "4             0       0          0  \n",
       "...         ...     ...        ...  \n",
       "1714          1       0          0  \n",
       "1715          1       0          0  \n",
       "1716          1       0          0  \n",
       "1717          1       0          1  \n",
       "1718          1       0          0  \n",
       "\n",
       "[1719 rows x 8 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Province/State']=data['Province/State'].fillna('error')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sno               False\n",
       "Date              False\n",
       "Province/State    False\n",
       "Country           False\n",
       "Last Update       False\n",
       "Confirmed         False\n",
       "Deaths            False\n",
       "Recovered         False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "datai=data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### set country as group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "datai = data[data['Country']!='error']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
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       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>China</td>\n",
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       "      <td>Chongqing</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>6</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>China</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>1715</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Madison, WI</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-05T21:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>1716</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Orange, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:53:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>1717</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>San Antonio, TX</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-13T18:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>1718</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-09T07:03:04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>1719</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>Tempe, AZ</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-02-01T19:43:03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1719 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sno                 Date   Province/State Country          Last Update  \\\n",
       "0        1  01/22/2020 12:00:00            Anhui   China  01/22/2020 12:00:00   \n",
       "1        2  01/22/2020 12:00:00          Beijing   China  01/22/2020 12:00:00   \n",
       "2        3  01/22/2020 12:00:00        Chongqing   China  01/22/2020 12:00:00   \n",
       "3        4  01/22/2020 12:00:00           Fujian   China  01/22/2020 12:00:00   \n",
       "4        5  01/22/2020 12:00:00            Gansu   China  01/22/2020 12:00:00   \n",
       "...    ...                  ...              ...     ...                  ...   \n",
       "1714  1715  02/17/2020 22:00:00      Madison, WI      US  2020-02-05T21:53:02   \n",
       "1715  1716  02/17/2020 22:00:00       Orange, CA      US  2020-02-01T19:53:03   \n",
       "1716  1717  02/17/2020 22:00:00  San Antonio, TX      US  2020-02-13T18:53:02   \n",
       "1717  1718  02/17/2020 22:00:00      Seattle, WA      US  2020-02-09T07:03:04   \n",
       "1718  1719  02/17/2020 22:00:00        Tempe, AZ      US  2020-02-01T19:43:03   \n",
       "\n",
       "      Confirmed  Deaths  Recovered  \n",
       "0             1       0          0  \n",
       "1            14       0          0  \n",
       "2             6       0          0  \n",
       "3             1       0          0  \n",
       "4             0       0          0  \n",
       "...         ...     ...        ...  \n",
       "1714          1       0          0  \n",
       "1715          1       0          0  \n",
       "1716          1       0          0  \n",
       "1717          1       0          1  \n",
       "1718          1       0          0  \n",
       "\n",
       "[1719 rows x 8 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "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",
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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>Sno</th>\n",
       "      <th>Date</th>\n",
       "      <th>Province/State</th>\n",
       "      <th>Last Update</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Australia</td>\n",
       "      <td>1696</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>9/2/2020 19:33</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>1704</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>4/2/2020 15:43</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>83</td>\n",
       "      <td>01/23/2020 12:00:00</td>\n",
       "      <td>error</td>\n",
       "      <td>01/23/2020 12:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cambodia</td>\n",
       "      <td>1705</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>31/1/2020 8:15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>1706</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Toronto, ON</td>\n",
       "      <td>7/2/2020 5:43</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>China</td>\n",
       "      <td>35</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>01/22/2020 12:00:00</td>\n",
       "      <td>444</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Egypt</td>\n",
       "      <td>1707</td>\n",
       "      <td>02/17/2020 22:00:00</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-14T23:53:02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Finland</td>\n",
       "      <td>1708</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>31/1/2020 8:15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>France</td>\n",
       "      <td>1685</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>8/2/2020 9:53</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Germany</td>\n",
       "      <td>1683</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>9/2/2020 6:13</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>1677</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>2020-02-17T22:53:01</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>India</td>\n",
       "      <td>1693</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>3/2/2020 21:43</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Italy</td>\n",
       "      <td>1694</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>7/2/2020 17:53</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Ivory Coast</td>\n",
       "      <td>264</td>\n",
       "      <td>01/27/2020 20:30:00</td>\n",
       "      <td>error</td>\n",
       "      <td>01/27/2020 20:30:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Japan</td>\n",
       "      <td>1676</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>9/2/2020 6:13</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Macau</td>\n",
       "      <td>1686</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Macau</td>\n",
       "      <td>6/2/2020 14:23</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Mainland China</td>\n",
       "      <td>1709</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>9/2/2020 8:53</td>\n",
       "      <td>59989</td>\n",
       "      <td>1789</td>\n",
       "      <td>7862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>1680</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-15T23:43:02</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>82</td>\n",
       "      <td>01/23/2020 12:00:00</td>\n",
       "      <td>error</td>\n",
       "      <td>01/23/2020 12:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>1710</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>31/1/2020 8:15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Others</td>\n",
       "      <td>1657</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Diamond Princess cruise ship</td>\n",
       "      <td>9/2/2020 6:13</td>\n",
       "      <td>454</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>1695</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>7/2/2020 16:43</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Russia</td>\n",
       "      <td>1698</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>31/1/2020 16:13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>1672</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-17T14:33:04</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>1679</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-17T23:43:01</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Spain</td>\n",
       "      <td>1699</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>9/2/2020 20:33</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>1711</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>8/2/2020 3:43</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>1712</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-01T02:13:26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>1681</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Taiwan</td>\n",
       "      <td>9/2/2020 9:13</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>1678</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>8/2/2020 12:53</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>UK</td>\n",
       "      <td>1687</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>7/2/2020 18:33</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>US</td>\n",
       "      <td>1719</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>Washington</td>\n",
       "      <td>9/2/2020 7:03</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>1688</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>8/2/2020 7:03</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>1684</td>\n",
       "      <td>2/9/2020 23:20</td>\n",
       "      <td>error</td>\n",
       "      <td>2020-02-13T06:33:02</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Country   Sno                 Date  \\\n",
       "0              Australia  1696       2/9/2020 23:20   \n",
       "1                Belgium  1704       2/9/2020 23:20   \n",
       "2                 Brazil    83  01/23/2020 12:00:00   \n",
       "3               Cambodia  1705       2/9/2020 23:20   \n",
       "4                 Canada  1706       2/9/2020 23:20   \n",
       "5                  China    35  01/22/2020 12:00:00   \n",
       "6                  Egypt  1707  02/17/2020 22:00:00   \n",
       "7                Finland  1708       2/9/2020 23:20   \n",
       "8                 France  1685       2/9/2020 23:20   \n",
       "9                Germany  1683       2/9/2020 23:20   \n",
       "10             Hong Kong  1677       2/9/2020 23:20   \n",
       "11                 India  1693       2/9/2020 23:20   \n",
       "12                 Italy  1694       2/9/2020 23:20   \n",
       "13           Ivory Coast   264  01/27/2020 20:30:00   \n",
       "14                 Japan  1676       2/9/2020 23:20   \n",
       "15                 Macau  1686       2/9/2020 23:20   \n",
       "16        Mainland China  1709       2/9/2020 23:20   \n",
       "17              Malaysia  1680       2/9/2020 23:20   \n",
       "18                Mexico    82  01/23/2020 12:00:00   \n",
       "19                 Nepal  1710       2/9/2020 23:20   \n",
       "20                Others  1657       2/9/2020 23:20   \n",
       "21           Philippines  1695       2/9/2020 23:20   \n",
       "22                Russia  1698       2/9/2020 23:20   \n",
       "23             Singapore  1672       2/9/2020 23:20   \n",
       "24           South Korea  1679       2/9/2020 23:20   \n",
       "25                 Spain  1699       2/9/2020 23:20   \n",
       "26             Sri Lanka  1711       2/9/2020 23:20   \n",
       "27                Sweden  1712       2/9/2020 23:20   \n",
       "28                Taiwan  1681       2/9/2020 23:20   \n",
       "29              Thailand  1678       2/9/2020 23:20   \n",
       "30                    UK  1687       2/9/2020 23:20   \n",
       "31                    US  1719       2/9/2020 23:20   \n",
       "32  United Arab Emirates  1688       2/9/2020 23:20   \n",
       "33               Vietnam  1684       2/9/2020 23:20   \n",
       "\n",
       "                  Province/State          Last Update  Confirmed  Deaths  \\\n",
       "0                          error       9/2/2020 19:33          5       0   \n",
       "1                          error       4/2/2020 15:43          1       0   \n",
       "2                          error  01/23/2020 12:00:00          0       0   \n",
       "3                          error       31/1/2020 8:15          1       0   \n",
       "4                    Toronto, ON        7/2/2020 5:43          5       0   \n",
       "5                       Zhejiang  01/22/2020 12:00:00        444       0   \n",
       "6                          error  2020-02-14T23:53:02          1       0   \n",
       "7                          error       31/1/2020 8:15          1       0   \n",
       "8                          error        8/2/2020 9:53         12       1   \n",
       "9                          error        9/2/2020 6:13         16       0   \n",
       "10                     Hong Kong  2020-02-17T22:53:01         60       1   \n",
       "11                         error       3/2/2020 21:43          3       0   \n",
       "12                         error       7/2/2020 17:53          3       0   \n",
       "13                         error  01/27/2020 20:30:00          0       0   \n",
       "14                         error        9/2/2020 6:13         66       1   \n",
       "15                         Macau       6/2/2020 14:23         10       0   \n",
       "16                      Zhejiang        9/2/2020 8:53      59989    1789   \n",
       "17                         error  2020-02-15T23:43:02         22       0   \n",
       "18                         error  01/23/2020 12:00:00          0       0   \n",
       "19                         error       31/1/2020 8:15          1       0   \n",
       "20  Diamond Princess cruise ship        9/2/2020 6:13        454       0   \n",
       "21                         error       7/2/2020 16:43          3       1   \n",
       "22                         error      31/1/2020 16:13          2       0   \n",
       "23                         error  2020-02-17T14:33:04         77       0   \n",
       "24                         error  2020-02-17T23:43:01         30       0   \n",
       "25                         error       9/2/2020 20:33          2       0   \n",
       "26                         error        8/2/2020 3:43          1       0   \n",
       "27                         error  2020-02-01T02:13:26          1       0   \n",
       "28                        Taiwan        9/2/2020 9:13         22       1   \n",
       "29                         error       8/2/2020 12:53         35       0   \n",
       "30                         error       7/2/2020 18:33          9       0   \n",
       "31                    Washington        9/2/2020 7:03          3       0   \n",
       "32                         error        8/2/2020 7:03          9       0   \n",
       "33                         error  2020-02-13T06:33:02         16       0   \n",
       "\n",
       "    Recovered  \n",
       "0           4  \n",
       "1           1  \n",
       "2           0  \n",
       "3           1  \n",
       "4           1  \n",
       "5           0  \n",
       "6           0  \n",
       "7           1  \n",
       "8           4  \n",
       "9           1  \n",
       "10          2  \n",
       "11          3  \n",
       "12          0  \n",
       "13          0  \n",
       "14         12  \n",
       "15          5  \n",
       "16       7862  \n",
       "17          7  \n",
       "18          0  \n",
       "19          1  \n",
       "20          0  \n",
       "21          1  \n",
       "22          2  \n",
       "23         24  \n",
       "24         10  \n",
       "25          2  \n",
       "26          1  \n",
       "27          0  \n",
       "28          2  \n",
       "29         15  \n",
       "30          8  \n",
       "31          2  \n",
       "32          4  \n",
       "33          7  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datacovidx = datai.groupby('Country').max().reset_index()\n",
    "datacovidx "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'data2' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-44-49481b60d613>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdata2\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Last Update'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata2\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Last Update'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdatetime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrptime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%Y-%m-%d,%H:%M:%S'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mdata2\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Last Update'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata2\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Last Update'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"%m/%d/%y,%H:%M:%S\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'data2' is not defined"
     ]
    }
   ],
   "source": [
    "data2['Last Update'] = data2['Last Update'].datetime.strptime('%Y-%m-%d,%H:%M:%S')\n",
    "data2['Last Update'].date.strftime(data2['Last Update'], \"%m/%d/%y,%H:%M:%S\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ END ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
   ]
  }
 ],
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