Day 9 Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Joining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2\n",
       "0     1     2\n",
       "1     4     5\n",
       "2     7     8"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1= pd.DataFrame({'col1':[1,4,7],'col2':[2,5,8]})\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>col3</th>\n",
       "      <th>col4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col3  col4\n",
       "0     1     2\n",
       "1     4     5\n",
       "3     7     9"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2= pd.DataFrame({'col3':[1,4,7],'col4':[2,5,9]}, index=[0,1,3])\n",
    "df2"
   ]
  },
  {
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3  col4\n",
       "0     1     2   1.0   2.0\n",
       "1     4     5   4.0   5.0\n",
       "2     7     8   NaN   NaN"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2, how='left')"
   ]
  },
  {
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3  col4\n",
       "0   1.0   2.0     1     2\n",
       "1   4.0   5.0     4     5\n",
       "3   NaN   NaN     7     9"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=df1.join(df2, how='right')\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df3.col1.values[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3  col4\n",
       "0   1.0   2.0   1.0   2.0\n",
       "1   4.0   5.0   4.0   5.0\n",
       "2   7.0   8.0   NaN   NaN\n",
       "3   NaN   NaN   7.0   9.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2, how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3  col4\n",
       "0     1     2     1     2\n",
       "1     4     5     4     5"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2, how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Input and Output using Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# csv files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    a   b   c   d\n",
       "0   0   1   2   3\n",
       "1   4   5   6   7\n",
       "2   8   9  10  11\n",
       "3  12  13  14  15"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pd.read_csv('example')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('H:\\\\example.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Name</th>\n",
       "      <th>roll</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Subham</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sarthak</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Khsitiz</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  roll  class\n",
       "0   Subham     1     10\n",
       "1  Sarthak     2      9\n",
       "2  Khsitiz     3     10"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('example2.tsv', sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Excel"
   ]
  },
  {
   "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>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    a   b   c   d\n",
       "0   0   1   2   3\n",
       "1   4   5   6   7\n",
       "2   8   9  10  11\n",
       "3  12  13  14  15"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('Excel_Sample.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_excel('......',sheet_name='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2= pd.read_html('https://en.wikipedia.org/wiki/Coronavirus_disease_2019', header=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Coronavirus disease 2019(COVID-19)</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Other names</td>\n",
       "      <td>Coronavirus Corona COVID 2019-nCoV acute respi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False-color transmission electron microscope i...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Pronunciation</td>\n",
       "      <td>/kəˈroʊnəˌvaɪrəs dɪˈziːz//ˌkoʊvɪdnaɪnˈtiːn, ˌk...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Specialty</td>\n",
       "      <td>Infectious disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Symptoms</td>\n",
       "      <td>Fever, cough, fatigue, shortness of breath, lo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Complications</td>\n",
       "      <td>Pneumonia, viral sepsis, acute respiratory dis...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Usual onset</td>\n",
       "      <td>2–14 days (typically 5) from infection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Causes</td>\n",
       "      <td>Severe acute respiratory syndrome coronavirus ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Diagnostic method</td>\n",
       "      <td>rRT-PCR testing, CT scan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Prevention</td>\n",
       "      <td>Hand washing, face coverings, quarantine, soci...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Treatment</td>\n",
       "      <td>Symptomatic and supportive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Frequency</td>\n",
       "      <td>26,065,382[8] confirmed cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Deaths</td>\n",
       "      <td>863,826 ([8]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Coronavirus disease 2019(COVID-19)  \\\n",
       "0                                         Other names   \n",
       "1                                                 NaN   \n",
       "2   False-color transmission electron microscope i...   \n",
       "3                                       Pronunciation   \n",
       "4                                           Specialty   \n",
       "5                                            Symptoms   \n",
       "6                                       Complications   \n",
       "7                                         Usual onset   \n",
       "8                                              Causes   \n",
       "9                                   Diagnostic method   \n",
       "10                                         Prevention   \n",
       "11                                          Treatment   \n",
       "12                                          Frequency   \n",
       "13                                             Deaths   \n",
       "\n",
       "                                           Unnamed: 1  \n",
       "0   Coronavirus Corona COVID 2019-nCoV acute respi...  \n",
       "1                                                 NaN  \n",
       "2                                                 NaN  \n",
       "3   /kəˈroʊnəˌvaɪrəs dɪˈziːz//ˌkoʊvɪdnaɪnˈtiːn, ˌk...  \n",
       "4                                  Infectious disease  \n",
       "5   Fever, cough, fatigue, shortness of breath, lo...  \n",
       "6   Pneumonia, viral sepsis, acute respiratory dis...  \n",
       "7              2–14 days (typically 5) from infection  \n",
       "8   Severe acute respiratory syndrome coronavirus ...  \n",
       "9                            rRT-PCR testing, CT scan  \n",
       "10  Hand washing, face coverings, quarantine, soci...  \n",
       "11                         Symptomatic and supportive  \n",
       "12                      26,065,382[8] confirmed cases  \n",
       "13                                       863,826 ([8]  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
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   ],
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    "df2[0]"
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       "                             Part of a series on the\n",
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       "6  Impact Socio-economic Crime Death rates by cou...\n",
       "7                                    COVID-19 Portal\n",
       "8                                                vte"
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       "      <th>2</th>\n",
       "      <td>Loss of appetite</td>\n",
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       "      <th>3</th>\n",
       "      <td>Fatigue</td>\n",
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       "      <th>4</th>\n",
       "      <td>Shortness of breath</td>\n",
       "      <td>31–40%</td>\n",
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       "      <th>5</th>\n",
       "      <td>Coughing up sputum</td>\n",
       "      <td>28–33%</td>\n",
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       "      <th>6</th>\n",
       "      <td>Muscle aches and pains</td>\n",
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       "                  Symptom   Range\n",
       "0                   Fever  83–99%\n",
       "1                   Cough  59–82%\n",
       "2        Loss of appetite  40–84%\n",
       "3                 Fatigue  44–70%\n",
       "4     Shortness of breath  31–40%\n",
       "5      Coughing up sputum  28–33%\n",
       "6  Muscle aches and pains  11–35%"
      ]
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       "      <td>Argentina as of 7 May[164]</td>\n",
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       "      <th>3</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.8</td>\n",
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       "      <th>6</th>\n",
       "      <td>Ontario as of 3 June[169]</td>\n",
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       "      <td>15.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>10</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.6</td>\n",
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       "      <td>9.4</td>\n",
       "      <td>18.1</td>\n",
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       "      <th>11</th>\n",
       "      <td>Denmark as of 4 June[175]</td>\n",
       "      <td>0.2</td>\n",
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       "      <td>16.5</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Finland as of 4 June[176]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;0.4</td>\n",
       "      <td>&lt;0.4</td>\n",
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       "      <td>0.8</td>\n",
       "      <td>3.8</td>\n",
       "      <td>18.1</td>\n",
       "      <td>42.3</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Germany as of 5 June[177]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>19.7</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>14</th>\n",
       "      <td>Bavaria as of 5 June[178]</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Israel as of 3 May[179]</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.9</td>\n",
       "      <td>3.1</td>\n",
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       "      <td>22.9</td>\n",
       "      <td>30.8</td>\n",
       "      <td>31.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Italy as of 3 June[180]</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>10.6</td>\n",
       "      <td>25.9</td>\n",
       "      <td>32.4</td>\n",
       "      <td>29.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Japan as of 7 May[181]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>6.8</td>\n",
       "      <td>14.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mexico as of 3 June[182]</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>7.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>25.3</td>\n",
       "      <td>33.7</td>\n",
       "      <td>40.3</td>\n",
       "      <td>40.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Netherlands as of 3 June[183]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>8.1</td>\n",
       "      <td>25.6</td>\n",
       "      <td>33.3</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Norway as of 4 June[184]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22.7</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Philippines as of 4 June[185]</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2.4</td>\n",
       "      <td>5.5</td>\n",
       "      <td>13.2</td>\n",
       "      <td>20.9</td>\n",
       "      <td>31.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Portugal as of 3 June[186]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.3</td>\n",
       "      <td>3.6</td>\n",
       "      <td>10.5</td>\n",
       "      <td>21.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>South Africa as of 28 May[187]</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>9.2</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>South Korea as of 17 July[188]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.3</td>\n",
       "      <td>9.5</td>\n",
       "      <td>25.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Spain as of 29 May[189]</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sweden as of 5 June[190]</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>6.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>35.6</td>\n",
       "      <td>40.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Switzerland as of 4 June[191]</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>11.6</td>\n",
       "      <td>28.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>United States</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Colorado as of 3 June[192]</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1.9</td>\n",
       "      <td>6.2</td>\n",
       "      <td>18.5</td>\n",
       "      <td>39.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Connecticut as of 3 June[193]</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>31.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Georgia as of 3 June[194]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>13.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Idaho as of 3 June[195]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>3.1</td>\n",
       "      <td>8.9</td>\n",
       "      <td>31.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Indiana as of 3 June[196]</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7.3</td>\n",
       "      <td>17.1</td>\n",
       "      <td>30.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Kentucky as of 20 May[197]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.9</td>\n",
       "      <td>5.9</td>\n",
       "      <td>14.2</td>\n",
       "      <td>29.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Maryland as of 20 May[198]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>6.1</td>\n",
       "      <td>14.6</td>\n",
       "      <td>28.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Massachusetts as of 20 May[199]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>5.2</td>\n",
       "      <td>16.8</td>\n",
       "      <td>28.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Minnesota as of 13 May[200]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>5.4</td>\n",
       "      <td>26.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Mississippi as of 19 May[201]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>2.1</td>\n",
       "      <td>8.1</td>\n",
       "      <td>16.1</td>\n",
       "      <td>19.4</td>\n",
       "      <td>27.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Missouri as of 19 May[202]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>6.3</td>\n",
       "      <td>14.3</td>\n",
       "      <td>22.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Nevada as of 20 May[203]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>7.7</td>\n",
       "      <td>22.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>N. Hampshire as of 12 May[204]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>12.0</td>\n",
       "      <td>21.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Oregon as of 12 May[205]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>12.1</td>\n",
       "      <td>28.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Texas as of 20 May[206]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2.1</td>\n",
       "      <td>5.5</td>\n",
       "      <td>10.1</td>\n",
       "      <td>30.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Virginia as of 19 May[207]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>12.9</td>\n",
       "      <td>24.9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Washington as of 10 May[208]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>9.8</td>\n",
       "      <td>31.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Wisconsin as of 20 May[209]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>19.9</td>\n",
       "      <td>30.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Unnamed: 0  Age Unnamed: 2 Unnamed: 3 Unnamed: 4  \\\n",
       "0                           Country  0–9      10–19      20–29      30–39   \n",
       "1        Argentina as of 7 May[164]  0.0        0.0        0.1        0.4   \n",
       "2       Australia as of 4 June[165]  0.0        0.0        0.0        0.0   \n",
       "3          Canada as of 3 June[166]  0.0        0.1        0.7       11.2   \n",
       "4         Alberta as of 3 June[167]  0.0        0.0        0.1        0.1   \n",
       "5    Br. Columbia as of 2 June[168]  0.0        0.0        0.0        0.0   \n",
       "6         Ontario as of 3 June[169]  0.0        0.0        0.1        0.2   \n",
       "7          Quebec as of 2 June[170]  0.0        0.1        0.1        0.2   \n",
       "8      Chile as of 31 May[171][172]  0.1        0.3        0.7        2.3   \n",
       "9      China as of 11 February[173]  0.0        0.2        0.2        0.2   \n",
       "10       Colombia as of 3 June[174]  0.3        0.0        0.2        0.5   \n",
       "11        Denmark as of 4 June[175]  0.2        4.1       16.5       28.1   \n",
       "12        Finland as of 4 June[176]  0.0        0.0       <0.4       <0.4   \n",
       "13        Germany as of 5 June[177]  0.0        0.0        0.1        1.9   \n",
       "14        Bavaria as of 5 June[178]  0.0        0.0        0.1        0.1   \n",
       "15          Israel as of 3 May[179]  0.0        0.0        0.0        0.9   \n",
       "16          Italy as of 3 June[180]  0.3        0.0        0.1        0.3   \n",
       "17           Japan as of 7 May[181]  0.0        0.0        0.0        0.1   \n",
       "18         Mexico as of 3 June[182]  3.3        0.6        1.2        2.9   \n",
       "19    Netherlands as of 3 June[183]  0.0        0.2        0.1        0.3   \n",
       "20         Norway as of 4 June[184]  0.0        0.0        0.0        0.0   \n",
       "21    Philippines as of 4 June[185]  1.6        0.9        0.5        0.8   \n",
       "22       Portugal as of 3 June[186]  0.0        0.0        0.0        0.0   \n",
       "23   South Africa as of 28 May[187]  0.3        0.1        0.1        0.4   \n",
       "24   South Korea as of 17 July[188]  0.0        0.0        0.0        0.1   \n",
       "25          Spain as of 29 May[189]  0.3        0.2        0.2        0.3   \n",
       "26         Sweden as of 5 June[190]  0.5        0.0        0.2        0.2   \n",
       "27    Switzerland as of 4 June[191]  0.6        0.0        0.0        0.1   \n",
       "28                    United States  NaN        NaN        NaN        NaN   \n",
       "29       Colorado as of 3 June[192]  0.2        0.2        0.2        0.2   \n",
       "30    Connecticut as of 3 June[193]  0.2        0.1        0.1        0.3   \n",
       "31        Georgia as of 3 June[194]  0.0        0.1        0.5        0.9   \n",
       "32          Idaho as of 3 June[195]  0.0        0.0        0.0        0.0   \n",
       "33        Indiana as of 3 June[196]  0.1        0.1        0.2        0.6   \n",
       "34       Kentucky as of 20 May[197]  0.0        0.0        0.0        0.2   \n",
       "35       Maryland as of 20 May[198]  0.0        0.1        0.2        0.3   \n",
       "36  Massachusetts as of 20 May[199]  0.0        0.0        0.1        0.1   \n",
       "37      Minnesota as of 13 May[200]  0.0        0.0        0.0        0.1   \n",
       "38    Mississippi as of 19 May[201]  0.0        0.1        0.5        0.9   \n",
       "39       Missouri as of 19 May[202]  0.0        0.0        0.1        0.2   \n",
       "40         Nevada as of 20 May[203]  0.0        0.3        0.3        0.4   \n",
       "41   N. Hampshire as of 12 May[204]  0.0        0.0        0.4        0.0   \n",
       "42         Oregon as of 12 May[205]  0.0        0.0        0.0        0.0   \n",
       "43          Texas as of 20 May[206]  0.0        0.5        0.4        0.3   \n",
       "44       Virginia as of 19 May[207]  0.0        0.0        0.0        0.1   \n",
       "45     Washington as of 10 May[208]  0.0        0.2        1.3        9.8   \n",
       "46      Wisconsin as of 20 May[209]  0.0        0.0        0.2        0.2   \n",
       "\n",
       "   Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10  \n",
       "0       40–49      50–59      60–69      70–79      80–89         90+  \n",
       "1         1.3        3.6       12.9       18.8       28.4         NaN  \n",
       "2         0.1        0.2        1.1        4.1       18.1        40.8  \n",
       "3        30.7        NaN        NaN        NaN        NaN         NaN  \n",
       "4         0.1        0.2        1.9       11.9       30.8         NaN  \n",
       "5         0.5        0.8        4.6       12.3       33.8        33.6  \n",
       "6         0.5        1.5        5.6       17.7       26.0        33.3  \n",
       "7         1.1        6.1       21.4       30.4       36.1         NaN  \n",
       "8         7.7       15.6        NaN        NaN        NaN         NaN  \n",
       "9         0.4        1.3        3.6        8.0       14.8         NaN  \n",
       "10        1.6        3.4        9.4       18.1       25.6        35.1  \n",
       "11       48.2        NaN        NaN        NaN        NaN         NaN  \n",
       "12       <0.5        0.8        3.8       18.1       42.3         NaN  \n",
       "13       19.7       31.0        NaN        NaN        NaN         NaN  \n",
       "14        0.2        0.9        5.4       15.8       28.0        35.8  \n",
       "15        0.9        3.1        9.7       22.9       30.8        31.3  \n",
       "16        0.9        2.7       10.6       25.9       32.4        29.9  \n",
       "17        0.3        0.6        2.5        6.8       14.8         NaN  \n",
       "18        7.5       15.0       25.3       33.7       40.3        40.6  \n",
       "19        0.5        1.7        8.1       25.6       33.3        34.5  \n",
       "20        0.3        0.4        2.2        9.0       22.7        57.0  \n",
       "21        2.4        5.5       13.2       20.9       31.5         NaN  \n",
       "22        0.3        1.3        3.6       10.5       21.2         NaN  \n",
       "23        1.1        3.8        9.2       15.0       12.3         NaN  \n",
       "24        0.2        0.6        2.3        9.5       25.2         NaN  \n",
       "25        0.6        1.4        5.0       14.3       20.8        21.7  \n",
       "26        0.6        1.7        6.6       23.4       35.6        40.3  \n",
       "27        0.1        0.6        3.4       11.6       28.2         NaN  \n",
       "28        NaN        NaN        NaN        NaN        NaN         NaN  \n",
       "29        0.8        1.9        6.2       18.5       39.0         NaN  \n",
       "30        0.7        1.8        7.0       18.0       31.2         NaN  \n",
       "31        2.0        6.1       13.2       22.0        NaN         NaN  \n",
       "32        0.0        0.4        3.1        8.9       31.4         NaN  \n",
       "33        1.8        7.3       17.1       30.2        NaN         NaN  \n",
       "34        0.5        1.9        5.9       14.2       29.1         NaN  \n",
       "35        0.7        1.9        6.1       14.6       28.8         NaN  \n",
       "36        0.4        1.5        5.2       16.8       28.9         NaN  \n",
       "37        0.3        1.6        5.4       26.9        NaN         NaN  \n",
       "38        2.1        8.1       16.1       19.4       27.2         NaN  \n",
       "39        0.8        2.2        6.3       14.3       22.5         NaN  \n",
       "40        1.7        2.6        7.7       22.3        NaN         NaN  \n",
       "41        1.2        0.0        2.2       12.0       21.2         NaN  \n",
       "42        0.5        0.8        5.6       12.1       28.9         NaN  \n",
       "43        0.8        2.1        5.5       10.1       30.6         NaN  \n",
       "44        0.4        1.0        4.4       12.9       24.9         NaN  \n",
       "45       31.2        NaN        NaN        NaN        NaN         NaN  \n",
       "46        0.6        2.0        5.0       14.7       19.9        30.4  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     Coronavirus Corona COVID 2019-nCoV acute respi...\n",
       "1                                                   NaN\n",
       "2                                                   NaN\n",
       "3     /kəˈroʊnəˌvaɪrəs dɪˈziːz//ˌkoʊvɪdnaɪnˈtiːn, ˌk...\n",
       "4                                    Infectious disease\n",
       "5     Fever, cough, fatigue, shortness of breath, lo...\n",
       "6     Pneumonia, viral sepsis, acute respiratory dis...\n",
       "7                2–14 days (typically 5) from infection\n",
       "8     Severe acute respiratory syndrome coronavirus ...\n",
       "9                              rRT-PCR testing, CT scan\n",
       "10    Hand washing, face coverings, quarantine, soci...\n",
       "11                           Symptomatic and supportive\n",
       "12                        26,065,382[8] confirmed cases\n",
       "13                                         863,826 ([8]\n",
       "Name: Unnamed: 1, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[0]['Unnamed: 1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     Coronavirus Corona COVID 2019-nCoV acute respi...\n",
       "1                                                   nan\n",
       "2                                                   nan\n",
       "3     /kəˈroʊnəˌvaɪrəs dɪˈziːz//ˌkoʊvɪdnaɪnˈtiːn, ˌk...\n",
       "4                                    Infectious disease\n",
       "5     Fever, cough, fatigue, shortness of breath, lo...\n",
       "6     Pneumonia, viral sepsis, acute respiratory dis...\n",
       "7                2–14 days (typically 5) from infection\n",
       "8     Severe acute respiratory syndrome coronavirus ...\n",
       "9                              rRT-PCR testing, CT scan\n",
       "10    Hand washing, face coverings, quarantine, soci...\n",
       "11                           Symptomatic and supportive\n",
       "12                           26,065,382 confirmed cases\n",
       "13                                            863,826 (\n",
       "Name: Unnamed: 1, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[0]['Unnamed: 1'].apply(lambda x: re.sub('\\[\\d\\]', '', str(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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