NPV-Day 3_TH Exercise.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"10%\">\n",
    "            <img src=\"homework.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"center\">\n",
    "                <font color=\"#21618C\" size=8px>\n",
    "                    <b>Take - home\n",
    "                        <br> (Day 3)\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's begin with some hands-on practice exercises. \n",
    "\n",
    "**Create a dataframe wherever necessary**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 1. Compute minimum and maximum sales for each store and location\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>Store</th>\n",
    "<th>Location</th>\n",
    "<th>Sales</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Mumbai</td>\n",
    "<td>40000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>B</td>\n",
    "<td>Pune</td>\n",
    "<td>45000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Hyderabad</td>\n",
    "<td>50000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>C</td>\n",
    "<td>Mumbai</td>\n",
    "<td>90000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>D</td>\n",
    "<td>Pune</td>\n",
    "<td>89000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Delhi</td>\n",
    "<td>87000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>D</td>\n",
    "<td>Hyderabad</td>\n",
    "<td>85000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Pune</td>\n",
    "<td>78000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>C</td>\n",
    "<td>Mumbai</td>\n",
    "<td>89000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>B</td>\n",
    "<td>Pune</td>\n",
    "<td>70000</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "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>Store</th>\n",
       "      <th>Location</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>Pune</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>D</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>A</td>\n",
       "      <td>Pune</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store   Location  Sales\n",
       "0     A     Mumbai  40000\n",
       "1     B       Pune  45000\n",
       "2     A  Hyderabad  50000\n",
       "3     C     Mumbai  90000\n",
       "4     D       Pune  89000\n",
       "5     A      Delhi  87000\n",
       "6     D  Hyderabad  85000\n",
       "7     A       Pune  78000\n",
       "8     C     Mumbai  89000\n",
       "9     B       Pune  70000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Store</th>\n",
    "<th>Location</th>\n",
    "<th>Sales</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Mumbai</td>\n",
    "<td>40000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>B</td>\n",
    "<td>Pune</td>\n",
    "<td>45000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Hyderabad</td>\n",
    "<td>50000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>C</td>\n",
    "<td>Mumbai</td>\n",
    "<td>90000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>D</td>\n",
    "<td>Pune</td>\n",
    "<td>89000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Delhi</td>\n",
    "<td>87000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>D</td>\n",
    "<td>Hyderabad</td>\n",
    "<td>85000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>A</td>\n",
    "<td>Pune</td>\n",
    "<td>78000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>C</td>\n",
    "<td>Mumbai</td>\n",
    "<td>89000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>B</td>\n",
    "<td>Pune</td>\n",
    "<td>70000</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Store           A\n",
       "Location    Delhi\n",
       "Sales       40000\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Store           D\n",
       "Location     Pune\n",
       "Sales       90000\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 2. Find duplicate rows based on the column 'Name'\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Salary</th>\n",
    "<th>City</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>3400</td>\n",
    "<td>Sydeny</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aadi</td>\n",
    "<td>1600</td>\n",
    "<td>New York</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Texas</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aadi</td>\n",
    "<td>4000</td>\n",
    "<td>London</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sachin</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Salary</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>John</td>\n",
       "      <td>3400</td>\n",
       "      <td>Sydeny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Aadi</td>\n",
       "      <td>1600</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Aadi</td>\n",
       "      <td>4000</td>\n",
       "      <td>London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Sachin</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Salary      City\n",
       "0    John    3400    Sydeny\n",
       "1  Robert    3000   Chicago\n",
       "2    Aadi    1600  New York\n",
       "3  Robert    3000   Chicago\n",
       "4  Robert    3000   Chicago\n",
       "5  Robert    3000     Texas\n",
       "6    Aadi    4000    London\n",
       "7  Sachin    3000   Chicago"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "df1=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Salary</th>\n",
    "<th>City</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>3400</td>\n",
    "<td>Sydeny</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aadi</td>\n",
    "<td>1600</td>\n",
    "<td>New York</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>3000</td>\n",
    "<td>Texas</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aadi</td>\n",
    "<td>4000</td>\n",
    "<td>London</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sachin</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "df1"
   ]
  },
  {
   "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>Name</th>\n",
       "      <th>Salary</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Aadi</td>\n",
       "      <td>1600</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Aadi</td>\n",
       "      <td>4000</td>\n",
       "      <td>London</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Salary      City\n",
       "1  Robert    3000   Chicago\n",
       "2    Aadi    1600  New York\n",
       "3  Robert    3000   Chicago\n",
       "4  Robert    3000   Chicago\n",
       "5  Robert    3000     Texas\n",
       "6    Aadi    4000    London"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1[df1.duplicated(subset='Name', keep=False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 3.  In column tournament, replace all the 'football' values  with 'cricket' using numpy.where\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " \n",
    "<table>\n",
    "<tr>\n",
    "<th>Days</th>\n",
    "<th>Tournament</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mon</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Tues</td>\n",
    "<td>Cricket</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Wed</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Thurs</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Fri</td>\n",
    "<td>Cricket</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Days</th>\n",
       "      <th>Tournament</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Mon</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Tues</td>\n",
       "      <td>Cricket</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Wed</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Thurs</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Fri</td>\n",
       "      <td>Cricket</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Days Tournament\n",
       "0    Mon   Football\n",
       "1   Tues    Cricket\n",
       "2    Wed   Football\n",
       "3  Thurs   Football\n",
       "4    Fri    Cricket"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dft=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Days</th>\n",
    "<th>Tournament</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mon</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Tues</td>\n",
    "<td>Cricket</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Wed</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Thurs</td>\n",
    "<td>Football</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Fri</td>\n",
    "<td>Cricket</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "dft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>Days</th>\n",
       "      <th>Tournament</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Mon</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Tues</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Wed</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Thurs</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Fri</td>\n",
       "      <td>Football</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Days Tournament\n",
       "0    Mon   Football\n",
       "1   Tues   Football\n",
       "2    Wed   Football\n",
       "3  Thurs   Football\n",
       "4    Fri   Football"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dft.iloc[:,1]='Football'\n",
    "dft"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 4. Get the descriptive statistics of the sales for each season \n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>Month</th>\n",
    "<th>Sales</th>\n",
    "<th>Seasons</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jan</td>\n",
    "<td>22000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Feb</td>\n",
    "<td>27000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mar</td>\n",
    "<td>25000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Apr</td>\n",
    "<td>29000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>May</td>\n",
    "<td>35000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>June</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>July</td>\n",
    "<td>78000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aug</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sep</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Oct</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Nov</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Dec</td>\n",
    "<td>60000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>Month</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>22000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Feb</td>\n",
       "      <td>27000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Mar</td>\n",
       "      <td>25000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Apr</td>\n",
       "      <td>29000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>May</td>\n",
       "      <td>35000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>June</td>\n",
       "      <td>67000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>July</td>\n",
       "      <td>78000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Aug</td>\n",
       "      <td>67000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Sep</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Oct</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Nov</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Dec</td>\n",
       "      <td>60000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Month  Sales Seasons\n",
       "0    Jan  22000  Winter\n",
       "1    Feb  27000  Winter\n",
       "2    Mar  25000  Spring\n",
       "3    Apr  29000  Spring\n",
       "4    May  35000  Spring\n",
       "5   June  67000  Summer\n",
       "6   July  78000  Summer\n",
       "7    Aug  67000  Summer\n",
       "8    Sep  56000    Fall\n",
       "9    Oct  56000    Fall\n",
       "10   Nov  56000    Fall\n",
       "11   Dec  60000  Winter"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfs=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Month</th>\n",
    "<th>Sales</th>\n",
    "<th>Seasons</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jan</td>\n",
    "<td>22000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Feb</td>\n",
    "<td>27000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mar</td>\n",
    "<td>25000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Apr</td>\n",
    "<td>29000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>May</td>\n",
    "<td>35000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>June</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>July</td>\n",
    "<td>78000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aug</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sep</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Oct</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Nov</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Dec</td>\n",
    "<td>60000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "\n",
    "</table>''')[0]\n",
    "dfs"
   ]
  },
  {
   "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>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>48166.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>19385.249000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>22000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>28500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>56000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>61750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>78000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Sales\n",
       "count     12.000000\n",
       "mean   48166.666667\n",
       "std    19385.249000\n",
       "min    22000.000000\n",
       "25%    28500.000000\n",
       "50%    56000.000000\n",
       "75%    61750.000000\n",
       "max    78000.000000"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfs.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 5. Create a new column age with values of your choice. And append it to the below dataframe.\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Maths</th>\n",
    "<th>Science</th>\n",
    "<th>English</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma</td>\n",
    "<td>56</td>\n",
    "<td>89</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>78</td>\n",
    "<td>87</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia</td>\n",
    "<td>78</td>\n",
    "<td>78</td>\n",
    "<td>76</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James</td>\n",
    "<td>67</td>\n",
    "<td>89</td>\n",
    "<td>78</td>\n",
    "</tr>\n",
    "<td>John</td>\n",
    "<td>88</td>\n",
    "<td>78</td>\n",
    "<td>87</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Maths</th>\n",
       "      <th>Science</th>\n",
       "      <th>English</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma</td>\n",
       "      <td>56</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia</td>\n",
       "      <td>78</td>\n",
       "      <td>87</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>67</td>\n",
       "      <td>89</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Maths  Science  English\n",
       "0    Emma     56       89       89\n",
       "1     Mia     78       87       89\n",
       "2  Sophia     78       78       76\n",
       "3   James     67       89       78"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfc=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Maths</th>\n",
    "<th>Science</th>\n",
    "<th>English</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma</td>\n",
    "<td>56</td>\n",
    "<td>89</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>78</td>\n",
    "<td>87</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia</td>\n",
    "<td>78</td>\n",
    "<td>78</td>\n",
    "<td>76</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James</td>\n",
    "<td>67</td>\n",
    "<td>89</td>\n",
    "<td>78</td>\n",
    "</tr>\n",
    "<td>John</td>\n",
    "<td>88</td>\n",
    "<td>78</td>\n",
    "<td>87</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "dfc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>Maths</th>\n",
       "      <th>Science</th>\n",
       "      <th>English</th>\n",
       "      <th>Statistics</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma</td>\n",
       "      <td>56</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>90</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia</td>\n",
       "      <td>78</td>\n",
       "      <td>87</td>\n",
       "      <td>89</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>76</td>\n",
       "      <td>83</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>67</td>\n",
       "      <td>89</td>\n",
       "      <td>78</td>\n",
       "      <td>79</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Maths  Science  English  Statistics  Age\n",
       "0    Emma     56       89       89          90   12\n",
       "1     Mia     78       87       89         100   11\n",
       "2  Sophia     78       78       76          83   12\n",
       "3   James     67       89       78          79   11"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfc['Age']=[12,11,12,11]\n",
    "dfc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 6. Perform right join to combine values based on the columns 'MA(Hons)' and 'Stud_ID' in the two dataframes\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Name</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Alex</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Amy</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Allen</td>\n",
    "        <td>Geography</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Alice</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>James</td>\n",
    "        <td>History</td>\n",
    "    </tr>  \n",
    "</table>\n",
    "<br>\n",
    "\n",
    "\n",
    "\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Res_City</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Delhi</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Mumbai</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Delhi</td>\n",
    "        <td>Fine Arts</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Chennai</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>Hyderabad</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Alex</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Amy</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Allen</td>\n",
       "      <td>Geography</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Alice</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name   MA(Hons)\n",
       "0      101   Alex    History\n",
       "1      102    Amy    English\n",
       "2      103  Allen  Geography\n",
       "3      104  Alice     German"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "df1=pd.read_html('''\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Name</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Alex</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Amy</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Allen</td>\n",
    "        <td>Geography</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Alice</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>James</td>\n",
    "        <td>History</td>\n",
    "    </tr>  \n",
    "</table>\n",
    "<br>''')[0]\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>Stud_ID</th>\n",
       "      <th>Res_City</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Fine Arts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID Res_City   MA(Hons)\n",
       "0      101    Delhi    English\n",
       "1      102   Mumbai    History\n",
       "2      103    Delhi  Fine Arts\n",
       "3      104  Chennai     German"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=pd.read_html('''<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Res_City</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Delhi</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Mumbai</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Delhi</td>\n",
    "        <td>Fine Arts</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Chennai</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>Hyderabad</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "</table>''')[0]\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>MA(Hons)</th>\n",
       "      <th>Res_City</th>\n",
       "      <th>_merge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>104</td>\n",
       "      <td>Alice</td>\n",
       "      <td>German</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>101</td>\n",
       "      <td>NaN</td>\n",
       "      <td>English</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>History</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fine Arts</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>right_only</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name   MA(Hons) Res_City      _merge\n",
       "0      104  Alice     German  Chennai        both\n",
       "1      101    NaN    English    Delhi  right_only\n",
       "2      102    NaN    History   Mumbai  right_only\n",
       "3      103    NaN  Fine Arts    Delhi  right_only"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfm=pd.merge(df1,df2,on=['Stud_ID','MA(Hons)'],how='right',indicator=True)\n",
    "dfm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 7. Using the dataframes created in question 6, perform inner join to combine values based on the columns 'MA(Hons)' and 'Stud_ID' in the two dataframes\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Alex</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Amy</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Allen</td>\n",
       "      <td>Geography</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Alice</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name   MA(Hons)\n",
       "0      101   Alex    History\n",
       "1      102    Amy    English\n",
       "2      103  Allen  Geography\n",
       "3      104  Alice     German"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>Stud_ID</th>\n",
       "      <th>Res_City</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Fine Arts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID Res_City   MA(Hons)\n",
       "0      101    Delhi    English\n",
       "1      102   Mumbai    History\n",
       "2      103    Delhi  Fine Arts\n",
       "3      104  Chennai     German"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>MA(Hons)</th>\n",
       "      <th>Res_City</th>\n",
       "      <th>_merge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>104</td>\n",
       "      <td>Alice</td>\n",
       "      <td>German</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name MA(Hons) Res_City _merge\n",
       "0      104  Alice   German  Chennai   both"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfm=pd.merge(df1,df2,on=['Stud_ID','MA(Hons)'],how='inner',indicator=True)\n",
    "dfm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 8. Concatenate two dataframes along the columns\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Name</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Alex</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Amy</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Allen</td>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Alice</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>James</td>\n",
    "    </tr>  \n",
    "</table>\n",
    "<br>\n",
    "\n",
    "\n",
    "\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Res_City</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Delhi</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Mumbai</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Delhi</td>\n",
    "        <td>Fine Arts</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Chennai</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>Hyderabad</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Alex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Amy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Allen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Alice</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name\n",
       "0      101   Alex\n",
       "1      102    Amy\n",
       "2      103  Allen\n",
       "3      104  Alice"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df11=pd.read_html('''\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Stud_ID</th>\n",
    "        <th>Name</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Alex</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Amy</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Allen</td>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Alice</td>\n",
    "    </tr>\n",
    "        <td>105</td>\n",
    "        <td>James</td>\n",
    "    </tr>  \n",
    "</table>\n",
    "<br>''')[0]\n",
    "df11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>Res_City</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Fine Arts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Res_City   MA(Hons)\n",
       "0    Delhi    English\n",
       "1   Mumbai    History\n",
       "2    Delhi  Fine Arts\n",
       "3  Chennai     German"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df22=pd.read_html('''\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>Res_City</th>\n",
    "        <th>MA(Hons)</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Delhi</td>\n",
    "        <td>English</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Mumbai</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Delhi</td>\n",
    "        <td>Fine Arts</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>Chennai</td>\n",
    "        <td>German</td>\n",
    "    </tr>\n",
    "        <td>Hyderabad</td>\n",
    "        <td>History</td>\n",
    "    </tr>\n",
    "</table>''')[0]\n",
    "df22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Stud_ID   Name\n",
      "0      101   Alex\n",
      "1      102    Amy\n",
      "2      103  Allen\n",
      "3      104  Alice\n",
      "  Res_City   MA(Hons)\n",
      "0    Delhi    English\n",
      "1   Mumbai    History\n",
      "2    Delhi  Fine Arts\n",
      "3  Chennai     German\n"
     ]
    },
    {
     "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>Stud_ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Res_City</th>\n",
       "      <th>MA(Hons)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>Alex</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102.0</td>\n",
       "      <td>Amy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103.0</td>\n",
       "      <td>Allen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104.0</td>\n",
       "      <td>Alice</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>History</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Fine Arts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>German</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Stud_ID   Name Res_City   MA(Hons)\n",
       "0    101.0   Alex      NaN        NaN\n",
       "1    102.0    Amy      NaN        NaN\n",
       "2    103.0  Allen      NaN        NaN\n",
       "3    104.0  Alice      NaN        NaN\n",
       "0      NaN    NaN    Delhi    English\n",
       "1      NaN    NaN   Mumbai    History\n",
       "2      NaN    NaN    Delhi  Fine Arts\n",
       "3      NaN    NaN  Chennai     German"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfc=pd.concat(objs=(df11,df22),axis=0,join='outer',keys=None,sort=False)\n",
    "print(df11)\n",
    "print(df22)\n",
    "dfc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 9. Calculate minimum, maximum and average sales for each season\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>Month</th>\n",
    "<th>Sales</th>\n",
    "<th>Seasons</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jan</td>\n",
    "<td>22000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Feb</td>\n",
    "<td>27000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mar</td>\n",
    "<td>25000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Apr</td>\n",
    "<td>29000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>May</td>\n",
    "<td>35000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>June</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>July</td>\n",
    "<td>78000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aug</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sep</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Oct</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Nov</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Dec</td>\n",
    "<td>60000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>ID</th>\n",
    "<th>Name</th>\n",
    "<th>Subject</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>101</td>\n",
    "<td>Alex</td>\n",
    "<td>Maths</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>102</td>\n",
    "<td>Amy</td>\n",
    "<td>English</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>103</td>\n",
    "<td>Allen</td>\n",
    "<td>Science</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>104</td>\n",
    "<td>Alice</td>\n",
    "<td>German</td>\n",
    "</tr>\n",
    "<td>105</td>\n",
    "<td>Ayoung</td>\n",
    "<td>History</td>\n",
    "</tr>\n",
    "   \n",
    "</table><br>\n",
    "\n",
    "\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "<th>ID</th>\n",
    "<th>Name</th>\n",
    "<th>Subject</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>101</td>\n",
    "<td>Billy</td>\n",
    "<td>English</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>102</td>\n",
    "<td>Brian</td>\n",
    "<td>Science</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>103</td>\n",
    "<td>Bran</td>\n",
    "<td>Social Science</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>104</td>\n",
    "<td>Bryce</td>\n",
    "<td>German</td>\n",
    "</tr>\n",
    "<td>105</td>\n",
    "<td>Betty</td>\n",
    "<td>History</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>Month</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Jan</td>\n",
       "      <td>22000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Feb</td>\n",
       "      <td>27000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Mar</td>\n",
       "      <td>25000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Apr</td>\n",
       "      <td>29000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>May</td>\n",
       "      <td>35000</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>June</td>\n",
       "      <td>67000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>July</td>\n",
       "      <td>78000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Aug</td>\n",
       "      <td>67000</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Sep</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Oct</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Nov</td>\n",
       "      <td>56000</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Dec</td>\n",
       "      <td>60000</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Month  Sales Seasons\n",
       "0    Jan  22000  Winter\n",
       "1    Feb  27000  Winter\n",
       "2    Mar  25000  Spring\n",
       "3    Apr  29000  Spring\n",
       "4    May  35000  Spring\n",
       "5   June  67000  Summer\n",
       "6   July  78000  Summer\n",
       "7    Aug  67000  Summer\n",
       "8    Sep  56000    Fall\n",
       "9    Oct  56000    Fall\n",
       "10   Nov  56000    Fall\n",
       "11   Dec  60000  Winter"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfs=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Month</th>\n",
    "<th>Sales</th>\n",
    "<th>Seasons</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jan</td>\n",
    "<td>22000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Feb</td>\n",
    "<td>27000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mar</td>\n",
    "<td>25000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Apr</td>\n",
    "<td>29000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>May</td>\n",
    "<td>35000</td>\n",
    "<td>Spring</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>June</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>July</td>\n",
    "<td>78000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Aug</td>\n",
    "<td>67000</td>\n",
    "<td>Summer</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sep</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Oct</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Nov</td>\n",
    "<td>56000</td>\n",
    "<td>Fall</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Dec</td>\n",
    "<td>60000</td>\n",
    "<td>Winter</td>\n",
    "</tr>\n",
    "\n",
    "</table>''')[0]\n",
    "dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month        Apr\n",
       "Sales      22000\n",
       "Seasons     Fall\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfs.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month         Sep\n",
       "Sales       78000\n",
       "Seasons    Winter\n",
       "dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfs.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sales    48166.666667\n",
       "dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfs.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\">\n",
    "                <font color=\"#21618C\" size=4px>\n",
    "                    <b> 10. Find all the duplicate entries based on the columns X and Y.\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Use the dataframe given below:**\n",
    "   \n",
    "<table>\n",
    "<tr>\n",
    "<th>X</th>\n",
    "<th>Y</th>\n",
    "<th>Z</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "<td>5</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>3</td>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>1</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>3</td>\n",
    "<td>4</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>8</td>\n",
    "</tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   X  Y  Z\n",
       "0  1  2  5\n",
       "1  2  2  6\n",
       "2  3  1  2\n",
       "3  1  2  6\n",
       "4  2  2  1\n",
       "5  3  4  6\n",
       "6  2  2  2\n",
       "7  2  2  8"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write your code here\n",
    "dfcl=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>X</th>\n",
    "<th>Y</th>\n",
    "<th>Z</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "<td>5</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>3</td>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>1</td>\n",
    "<td>2</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>1</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>3</td>\n",
    "<td>4</td>\n",
    "<td>6</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>2</td>\n",
    "<td>2</td>\n",
    "<td>8</td>\n",
    "</tr>\n",
    "\n",
    "</table>''')[0]\n",
    "dfcl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   X  Y  Z\n",
       "0  1  2  5\n",
       "1  2  2  6\n",
       "3  1  2  6\n",
       "4  2  2  1\n",
       "6  2  2  2\n",
       "7  2  2  8"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfcl[dfcl.duplicated(subset=['X','Y'], keep=False)]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}