NPV-Day 3_IC Exercise-Question.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<table align=\"left\" width=100%>\n",
    "    <tr>\n",
    "        <td width=\"10%\">\n",
    "            <img src=\"in_class.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"center\">\n",
    "                <font color=\"#21618C\" size=8px>\n",
    "                    <b>Inclass - Lab<br> (Day 3)\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Table of Content\n",
    "1. **[Reshape](#Reshape)**\n",
    "2. **[Pivot Table](#Pivoting)**\n",
    "3. **[Duplicate](#Duplicating)**\n",
    "4. **[Replace](#Replacing)**\n",
    "5. **[Index](#Indexing)**\n",
    "6. **[Summary Statistics](#Summary_Statistics)**\n",
    "7. **[Merge, Join, Concatenate](#merge)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Let us import the required library**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's begin with some hands-on practice exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Reshape'></a>\n",
    "## 1. Reshape"
   ]
  },
  {
   "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. Write a program to reshape the given dataframe using the melt function, considering 'Day' as the identifier variable\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>Day</th>\n",
    "<th>ICICI</th>\n",
    "<th>HDFC</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>MON</td>\n",
    "<td>1129</td>\n",
    "<td>191</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>TUES</td>\n",
    "<td>1132</td>\n",
    "<td>192</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>WED</td>\n",
    "<td>1134</td>\n",
    "<td>190</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>THU</td>\n",
    "<td>1152</td>\n",
    "<td>190</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>FRI</td>\n",
    "<td>1152</td>\n",
    "<td>188</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>Day</th>\n",
       "      <th>ICICI</th>\n",
       "      <th>HDFC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>MON</td>\n",
       "      <td>1129</td>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>TUES</td>\n",
       "      <td>1132</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>WED</td>\n",
       "      <td>1134</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>THU</td>\n",
       "      <td>1152</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>FRI</td>\n",
       "      <td>1152</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Day  ICICI  HDFC\n",
       "0   MON   1129   191\n",
       "1  TUES   1132   192\n",
       "2   WED   1134   190\n",
       "3   THU   1152   190\n",
       "4   FRI   1152   188"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "import pandas as pd\n",
    "df=pd.read_html('''<table>\n",
    "<tr>\n",
    "<th>Day</th>\n",
    "<th>ICICI</th>\n",
    "<th>HDFC</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>MON</td>\n",
    "<td>1129</td>\n",
    "<td>191</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>TUES</td>\n",
    "<td>1132</td>\n",
    "<td>192</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>WED</td>\n",
    "<td>1134</td>\n",
    "<td>190</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>THU</td>\n",
    "<td>1152</td>\n",
    "<td>190</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>FRI</td>\n",
    "<td>1152</td>\n",
    "<td>188</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Day</th>\n",
       "      <th>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>MON</td>\n",
       "      <td>ICICI</td>\n",
       "      <td>1129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>TUES</td>\n",
       "      <td>ICICI</td>\n",
       "      <td>1132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>WED</td>\n",
       "      <td>ICICI</td>\n",
       "      <td>1134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>THU</td>\n",
       "      <td>ICICI</td>\n",
       "      <td>1152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>FRI</td>\n",
       "      <td>ICICI</td>\n",
       "      <td>1152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>MON</td>\n",
       "      <td>HDFC</td>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>TUES</td>\n",
       "      <td>HDFC</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>WED</td>\n",
       "      <td>HDFC</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>THU</td>\n",
       "      <td>HDFC</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>FRI</td>\n",
       "      <td>HDFC</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Day variable  value\n",
       "0   MON    ICICI   1129\n",
       "1  TUES    ICICI   1132\n",
       "2   WED    ICICI   1134\n",
       "3   THU    ICICI   1152\n",
       "4   FRI    ICICI   1152\n",
       "5   MON     HDFC    191\n",
       "6  TUES     HDFC    192\n",
       "7   WED     HDFC    190\n",
       "8   THU     HDFC    190\n",
       "9   FRI     HDFC    188"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.melt(id_vars='Day')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Pivoting'></a>\n",
    "## 2. Pivot Table"
   ]
  },
  {
   "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 the average sales for each store\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": 4,
   "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df1=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",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
       "    <tr>\n",
       "      <th>Store</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>A</td>\n",
       "      <td>63750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>B</td>\n",
       "      <td>57500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C</td>\n",
       "      <td>89500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>D</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sales\n",
       "Store       \n",
       "A      63750\n",
       "B      57500\n",
       "C      89500\n",
       "D      87000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.groupby('Store')[['Sales']].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Store</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",
       "      <td>Sales</td>\n",
       "      <td>63750</td>\n",
       "      <td>57500</td>\n",
       "      <td>89500</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Store      A      B      C      D\n",
       "Sales  63750  57500  89500  87000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df1,columns='Store',values='Sales',aggfunc='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> 3. Compute the average sales for each store in every city\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": 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>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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df2=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",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Location</th>\n",
       "      <th>Delhi</th>\n",
       "      <th>Hyderabad</th>\n",
       "      <th>Mumbai</th>\n",
       "      <th>Pune</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Store</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>A</td>\n",
       "      <td>87000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>78000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>B</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89500.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>D</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Location    Delhi  Hyderabad   Mumbai     Pune\n",
       "Store                                         \n",
       "A         87000.0    50000.0  40000.0  78000.0\n",
       "B             NaN        NaN      NaN  57500.0\n",
       "C             NaN        NaN  89500.0      NaN\n",
       "D             NaN    85000.0      NaN  89000.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df2,values='Sales',index='Store',columns='Location',aggfunc='mean')"
   ]
  },
  {
   "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>Location</th>\n",
       "      <th>Store</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>A</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>A</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>D</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>A</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>C</td>\n",
       "      <td>89500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Pune</td>\n",
       "      <td>A</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Pune</td>\n",
       "      <td>B</td>\n",
       "      <td>57500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Pune</td>\n",
       "      <td>D</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Location Store  Sales\n",
       "0      Delhi     A  87000\n",
       "1  Hyderabad     A  50000\n",
       "2  Hyderabad     D  85000\n",
       "3     Mumbai     A  40000\n",
       "4     Mumbai     C  89500\n",
       "5       Pune     A  78000\n",
       "6       Pune     B  57500\n",
       "7       Pune     D  89000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.groupby(['Location','Store'])[['Sales']].mean().reset_index()"
   ]
  },
  {
   "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. Compute the minimum sales for each store in every city\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": 11,
   "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>Location</th>\n",
       "      <th>Delhi</th>\n",
       "      <th>Hyderabad</th>\n",
       "      <th>Mumbai</th>\n",
       "      <th>Pune</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Store</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>A</td>\n",
       "      <td>87000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>78000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>B</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>D</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Location    Delhi  Hyderabad   Mumbai     Pune\n",
       "Store                                         \n",
       "A         87000.0    50000.0  40000.0  78000.0\n",
       "B             NaN        NaN      NaN  45000.0\n",
       "C             NaN        NaN  89000.0      NaN\n",
       "D             NaN    85000.0      NaN  89000.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "pd.pivot_table(df2,values='Sales',index='Store',columns='Location',aggfunc='min')"
   ]
  },
  {
   "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></th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Location</th>\n",
       "      <th>Store</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Delhi</td>\n",
       "      <td>A</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Hyderabad</td>\n",
       "      <td>A</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>D</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Mumbai</td>\n",
       "      <td>A</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"3\" valign=\"top\">Pune</td>\n",
       "      <td>A</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>B</td>\n",
       "      <td>45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>D</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Sales\n",
       "Location  Store       \n",
       "Delhi     A      87000\n",
       "Hyderabad A      50000\n",
       "          D      85000\n",
       "Mumbai    A      40000\n",
       "          C      89000\n",
       "Pune      A      78000\n",
       "          B      45000\n",
       "          D      89000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.groupby(['Location','Store'])[['Sales']].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Duplicating'></a>\n",
    "## 3. Duplicate"
   ]
  },
  {
   "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. Find duplicate rows in the data\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>Sachine</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</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>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>Sachine</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  Sachine    3000   Chicago"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df3=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>Sachine</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "df3"
   ]
  },
  {
   "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>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>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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Salary     City\n",
       "1  Robert    3000  Chicago\n",
       "3  Robert    3000  Chicago\n",
       "4  Robert    3000  Chicago"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3[df3.duplicated(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> 6. Select duplicate rows, except the last occurrence \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>Sachine</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>3</td>\n",
       "      <td>Robert</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Salary     City\n",
       "1  Robert    3000  Chicago\n",
       "3  Robert    3000  Chicago"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df3[df3.duplicated(subset=None, keep='last')]"
   ]
  },
  {
   "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.  Select the duplicated rows based on the column names 'Salary' and 'City'\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>Sachine</td>\n",
    "<td>3000</td>\n",
    "<td>Chicago</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "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>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>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>7</td>\n",
       "      <td>Sachine</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Salary     City\n",
       "1   Robert    3000  Chicago\n",
       "3   Robert    3000  Chicago\n",
       "4   Robert    3000  Chicago\n",
       "7  Sachine    3000  Chicago"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df3[df3.duplicated(subset=['Salary','City'],keep=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>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>7</td>\n",
       "      <td>Sachine</td>\n",
       "      <td>3000</td>\n",
       "      <td>Chicago</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Salary     City\n",
       "1   Robert    3000  Chicago\n",
       "3   Robert    3000  Chicago\n",
       "4   Robert    3000  Chicago\n",
       "7  Sachine    3000  Chicago"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3[df3.duplicated(['Salary','City'],keep=False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Replacing'></a>\n",
    "## 4. Replace"
   ]
  },
  {
   "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.  Replace 'football' with 'hockey' in the column tournament \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": 26,
   "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": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df4=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",
    "df4"
   ]
  },
  {
   "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>Hockey</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>Hockey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Thurs</td>\n",
       "      <td>Hockey</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     Hockey\n",
       "1   Tues    Cricket\n",
       "2    Wed     Hockey\n",
       "3  Thurs     Hockey\n",
       "4    Fri    Cricket"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['Tournament'].replace({'Football':'Hockey'},inplace=True)\n",
    "df4"
   ]
  },
  {
   "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.  Replace all 0's with male and all 1's with female in the gender column\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>Num_Children</th>\n",
    "<th>Gender</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>0</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>4</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Johny</td>\n",
    "<td>5</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>3</td>\n",
    "<td>1</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\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>Num_Children</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>John</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Johny</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mia</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Num_Children  Gender\n",
       "0    John             0       0\n",
       "1  Robert             4       0\n",
       "2   Johny             5       0\n",
       "3     Mia             3       1"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "dg=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Num_Children</th>\n",
    "<th>Gender</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>0</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>4</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Johny</td>\n",
    "<td>5</td>\n",
    "<td>0</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>3</td>\n",
    "<td>1</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "dg\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Num_Children</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>John</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Johny</td>\n",
       "      <td>5</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mia</td>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Num_Children  Gender\n",
       "0    John             0    Male\n",
       "1  Robert             4    Male\n",
       "2   Johny             5    Male\n",
       "3     Mia             3  Female"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dg['Gender'].replace({0:'Male',1:'Female'},inplace=True)\n",
    "dg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Indexing'></a>\n",
    "## 5. Index"
   ]
  },
  {
   "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.  Set 'Name column as index for 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>City</th>\n",
    "<th>Sales</th>\n",
    "<th>Expenses</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>New York</td>\n",
    "<td>60000</td>\n",
    "<td>12000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>Chicago</td>\n",
    "<td>42000</td>\n",
    "<td>33000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jony</td>\n",
    "<td>Texas</td>\n",
    "<td>50000</td>\n",
    "<td>40000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>California</td>\n",
    "<td>24000</td>\n",
    "<td>34000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Edward</td>\n",
    "<td>Sydney</td>\n",
    "<td>12000</td>\n",
    "<td>28000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Thomas</td>\n",
    "<td>New York</td>\n",
    "<td>82000</td>\n",
    "<td>19000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Ethan</td>\n",
    "<td>Chicago</td>\n",
    "<td>59000</td>\n",
    "<td>32000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Olivia</td>\n",
    "<td>Sydeney</td>\n",
    "<td>85000</td>\n",
    "<td>10000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Arun</td>\n",
    "<td>California</td>\n",
    "<td>97000</td>\n",
    "<td>49000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Ankita</td>\n",
    "<td>Texas</td>\n",
    "<td>35000</td>\n",
    "<td>34000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Paulo</td>\n",
    "<td>Chicago</td>\n",
    "<td>47000</td>\n",
    "<td>55000</td>\n",
    "</tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>City</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Expenses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>John</td>\n",
       "      <td>New York</td>\n",
       "      <td>60000</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>42000</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Jony</td>\n",
       "      <td>Texas</td>\n",
       "      <td>50000</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mia</td>\n",
       "      <td>California</td>\n",
       "      <td>24000</td>\n",
       "      <td>34000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Edward</td>\n",
       "      <td>Sydney</td>\n",
       "      <td>12000</td>\n",
       "      <td>28000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Thomas</td>\n",
       "      <td>New York</td>\n",
       "      <td>82000</td>\n",
       "      <td>19000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>59000</td>\n",
       "      <td>32000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Sydeney</td>\n",
       "      <td>85000</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Arun</td>\n",
       "      <td>California</td>\n",
       "      <td>97000</td>\n",
       "      <td>49000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Ankita</td>\n",
       "      <td>Texas</td>\n",
       "      <td>35000</td>\n",
       "      <td>34000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Paulo</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>47000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name        City  Sales  Expenses\n",
       "0     John    New York  60000     12000\n",
       "1   Robert     Chicago  42000     33000\n",
       "2     Jony       Texas  50000     40000\n",
       "3      Mia  California  24000     34000\n",
       "4   Edward      Sydney  12000     28000\n",
       "5   Thomas    New York  82000     19000\n",
       "6    Ethan     Chicago  59000     32000\n",
       "7   Olivia     Sydeney  85000     10000\n",
       "8     Arun  California  97000     49000\n",
       "9   Ankita       Texas  35000     34000\n",
       "10   Paulo     Chicago  47000     55000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "dn=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>City</th>\n",
    "<th>Sales</th>\n",
    "<th>Expenses</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>New York</td>\n",
    "<td>60000</td>\n",
    "<td>12000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>Chicago</td>\n",
    "<td>42000</td>\n",
    "<td>33000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jony</td>\n",
    "<td>Texas</td>\n",
    "<td>50000</td>\n",
    "<td>40000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>California</td>\n",
    "<td>24000</td>\n",
    "<td>34000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Edward</td>\n",
    "<td>Sydney</td>\n",
    "<td>12000</td>\n",
    "<td>28000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Thomas</td>\n",
    "<td>New York</td>\n",
    "<td>82000</td>\n",
    "<td>19000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Ethan</td>\n",
    "<td>Chicago</td>\n",
    "<td>59000</td>\n",
    "<td>32000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Olivia</td>\n",
    "<td>Sydeney</td>\n",
    "<td>85000</td>\n",
    "<td>10000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Arun</td>\n",
    "<td>California</td>\n",
    "<td>97000</td>\n",
    "<td>49000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Ankita</td>\n",
    "<td>Texas</td>\n",
    "<td>35000</td>\n",
    "<td>34000</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Paulo</td>\n",
    "<td>Chicago</td>\n",
    "<td>47000</td>\n",
    "<td>55000</td>\n",
    "</tr>\n",
    "\n",
    "</table>''')[0]\n",
    "dn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>City</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Expenses</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>John</td>\n",
       "      <td>New York</td>\n",
       "      <td>60000</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Robert</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>42000</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Jony</td>\n",
       "      <td>Texas</td>\n",
       "      <td>50000</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Mia</td>\n",
       "      <td>California</td>\n",
       "      <td>24000</td>\n",
       "      <td>34000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Edward</td>\n",
       "      <td>Sydney</td>\n",
       "      <td>12000</td>\n",
       "      <td>28000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Thomas</td>\n",
       "      <td>New York</td>\n",
       "      <td>82000</td>\n",
       "      <td>19000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Ethan</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>59000</td>\n",
       "      <td>32000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Olivia</td>\n",
       "      <td>Sydeney</td>\n",
       "      <td>85000</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Arun</td>\n",
       "      <td>California</td>\n",
       "      <td>97000</td>\n",
       "      <td>49000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Ankita</td>\n",
       "      <td>Texas</td>\n",
       "      <td>35000</td>\n",
       "      <td>34000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Paulo</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>47000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City  Sales  Expenses\n",
       "Name                               \n",
       "John      New York  60000     12000\n",
       "Robert     Chicago  42000     33000\n",
       "Jony         Texas  50000     40000\n",
       "Mia     California  24000     34000\n",
       "Edward      Sydney  12000     28000\n",
       "Thomas    New York  82000     19000\n",
       "Ethan      Chicago  59000     32000\n",
       "Olivia     Sydeney  85000     10000\n",
       "Arun    California  97000     49000\n",
       "Ankita       Texas  35000     34000\n",
       "Paulo      Chicago  47000     55000"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dn.set_index('Name')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='Summary_Statistics'></a>\n",
    "## 6. Summary Statistics"
   ]
  },
  {
   "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> 11.  Find the descriptive statistics for the sales column of the given 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>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": 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>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": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "dm=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",
    "dm"
   ]
  },
  {
   "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>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": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dm.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> 12.  Find the median of 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": 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>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seasons</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Fall</td>\n",
       "      <td>56000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Spring</td>\n",
       "      <td>29000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Summer</td>\n",
       "      <td>67000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Winter</td>\n",
       "      <td>27000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Sales\n",
       "Seasons       \n",
       "Fall     56000\n",
       "Spring   29000\n",
       "Summer   67000\n",
       "Winter   27000"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "dm.groupby('Seasons')[['Sales']].median()"
   ]
  },
  {
   "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>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seasons</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Fall</td>\n",
       "      <td>56000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Spring</td>\n",
       "      <td>29666.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Summer</td>\n",
       "      <td>70666.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Winter</td>\n",
       "      <td>36333.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Sales\n",
       "Seasons              \n",
       "Fall     56000.000000\n",
       "Spring   29666.666667\n",
       "Summer   70666.666667\n",
       "Winter   36333.333333"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(dm,values='Sales',\n",
    "    index='Seasons',\n",
    "    columns=None,\n",
    "    aggfunc='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> 13. Find the descriptive statistics for categorical data from the 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>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": 58,
   "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>Seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>June</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Month Seasons\n",
       "count     12      12\n",
       "unique    12       4\n",
       "top     June  Winter\n",
       "freq       1       3"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "dm[['Month','Seasons']].describe()"
   ]
  },
  {
   "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>Month</th>\n",
       "      <th>Seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>June</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Month Seasons\n",
       "count     12      12\n",
       "unique    12       4\n",
       "top     June  Winter\n",
       "freq       1       3"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dm.describe(include=object)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='merge'></a>\n",
    "## 7. Merge, Join, Concatenate"
   ]
  },
  {
   "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> 14. Merge the given dataframes on the column 'Brand'\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>ID</th>\n",
    "<th>Brand</th>\n",
    "<th>Product</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>101</td>\n",
    "<td>Apple</td>\n",
    "<td>iPhone</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>102</td>\n",
    "<td>Canon</td>\n",
    "<td>DSLR</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>103</td>\n",
    "<td>Samsung</td>\n",
    "<td>SmartPhone</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>104</td>\n",
    "<td>Nikon</td>\n",
    "<td>DSLR</td>\n",
    "</tr>\n",
    "<td>105</td>\n",
    "<td>Sony</td>\n",
    "<td>SmartTV</td>\n",
    "</tr>\n",
    "   \n",
    "</table><br>\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "    <th>ID</th>\n",
    "<th>Brand</th>\n",
    "<th>Quantity_sold</th>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>101</td>\n",
    "<td>Apple</td>\n",
    "<td>234</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>102</td>\n",
    "<td>Canon</td>\n",
    "<td>344</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>104</td>\n",
    "<td>Samsung</td>\n",
    "<td>345</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>103</td>\n",
    "<td>Nikon</td>\n",
    "<td>262</td>\n",
    "</tr>\n",
    "    <td>105</td>\n",
    "<td>Sony</td>\n",
    "<td>356</td>\n",
    "</tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_html('''<table>\n",
    "<tr>\n",
    "<th>ID</th>\n",
    "<th>Brand</th>\n",
    "<th>Product</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>101</td>\n",
    "<td>Apple</td>\n",
    "<td>iPhone</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>102</td>\n",
    "<td>Canon</td>\n",
    "<td>DSLR</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>103</td>\n",
    "<td>Samsung</td>\n",
    "<td>SmartPhone</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>104</td>\n",
    "<td>Nikon</td>\n",
    "<td>DSLR</td>\n",
    "</tr><tr>\n",
    "<td>105</td>\n",
    "<td>Sony</td>\n",
    "<td>SmartTV</td>\n",
    "</tr>\n",
    "   \n",
    "</table><br>\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "    <th>ID</th>\n",
    "<th>Brand</th>\n",
    "<th>Quantity_sold</th>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>101</td>\n",
    "<td>Apple</td>\n",
    "<td>234</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>102</td>\n",
    "<td>Canon</td>\n",
    "<td>344</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>104</td>\n",
    "<td>Samsung</td>\n",
    "<td>345</td>\n",
    "</tr>\n",
    "<tr>\n",
    "    <td>103</td>\n",
    "<td>Nikon</td>\n",
    "<td>262</td>\n",
    "</tr>\n",
    "   <tr> <td>105</td>\n",
    "<td>Sony</td>\n",
    "<td>356</td>\n",
    "</tr>\n",
    "</table>''')\n",
    "\n",
    "df = data[0]\n",
    "\n",
    "df1 = data[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand     Product\n",
       "0  101    Apple      iPhone\n",
       "1  102    Canon        DSLR\n",
       "2  103  Samsung  SmartPhone\n",
       "3  104    Nikon        DSLR\n",
       "4  105     Sony     SmartTV"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Quantity_sold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>104</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>103</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand  Quantity_sold\n",
       "0  101    Apple            234\n",
       "1  102    Canon            344\n",
       "2  104  Samsung            345\n",
       "3  103    Nikon            262\n",
       "4  105     Sony            356"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>ID_x</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "      <th>ID_y</th>\n",
       "      <th>Quantity_sold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>101</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>102</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "      <td>104</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>103</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "      <td>105</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_x    Brand     Product  ID_y  Quantity_sold\n",
       "0   101    Apple      iPhone   101            234\n",
       "1   102    Canon        DSLR   102            344\n",
       "2   103  Samsung  SmartPhone   104            345\n",
       "3   104    Nikon        DSLR   103            262\n",
       "4   105     Sony     SmartTV   105            356"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df,df1,on='Brand')"
   ]
  },
  {
   "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> 15. Using the dataframes created in question 14, merge the given dataframes by 'ID' and 'Brand'\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity_sold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID  Brand  Product  Quantity_sold\n",
       "0  101  Apple   iPhone            234\n",
       "1  102  Canon     DSLR            344\n",
       "2  105   Sony  SmartTV            356"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "pd.merge(df,df1,on=['ID','Brand'])"
   ]
  },
  {
   "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> 16. Using the dataframes created in question 14, perform left join to combine values in the columns 'Brand' and 'ID'\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity_sold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>234.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "      <td>356.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand     Product  Quantity_sold\n",
       "0  101    Apple      iPhone          234.0\n",
       "1  102    Canon        DSLR          344.0\n",
       "2  103  Samsung  SmartPhone            NaN\n",
       "3  104    Nikon        DSLR            NaN\n",
       "4  105     Sony     SmartTV          356.0"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "pd.merge(df,df1,on=['ID','Brand'],how='left')"
   ]
  },
  {
   "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> 17. Using the dataframes created in question 14, perform outer join to combine values in the columns 'Brand' and 'ID'\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity_sold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>234.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "      <td>356.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>104</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>NaN</td>\n",
       "      <td>345.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>103</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>262.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand     Product  Quantity_sold\n",
       "0  101    Apple      iPhone          234.0\n",
       "1  102    Canon        DSLR          344.0\n",
       "2  103  Samsung  SmartPhone            NaN\n",
       "3  104    Nikon        DSLR            NaN\n",
       "4  105     Sony     SmartTV          356.0\n",
       "5  104  Samsung         NaN          345.0\n",
       "6  103    Nikon         NaN          262.0"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "pd.merge(df,df1,on=['ID','Brand'],how='outer')"
   ]
  },
  {
   "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> 18. Concatenate rows of the given dataframes and assign the store as its key \n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "                           Products in Store_A:\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>ID</th>\n",
    "        <th>Brand</th>\n",
    "        <th>Product</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPhone</td>\n",
    "        </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Canon</td>\n",
    "        <td>DSLR</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Samsung</td>\n",
    "        <td>SmartPhone</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Nikon</td>\n",
    "        <td>DSLR</td>\n",
    "  </tr>\n",
    "      <td>105</td>\n",
    "      <td>Sony</td>\n",
    "      <td>SmartTV</td>\n",
    "  </tr> \n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "                          Products in Store_B:\n",
    "<table>\n",
    "    <tr>\n",
    "        <th>ID</th>\n",
    "        <th>Brand</th>\n",
    "        <th>Product</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPhone</td>\n",
    "        </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPod</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Samsung</td>\n",
    "        <td>SmartPhone</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>107</td>\n",
    "        <td>Canon</td>\n",
    "        <td>DSLR</td>\n",
    "  </tr>\n",
    "      <td>101</td>\n",
    "      <td>Sony</td>\n",
    "      <td>SmartTV</td>\n",
    "  </tr> \n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_html('''<table>\n",
    "    <tr>\n",
    "        <th>ID</th>\n",
    "        <th>Brand</th>\n",
    "        <th>Product</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>101</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPhone</td>\n",
    "        </tr>\n",
    "    <tr>\n",
    "        <td>102</td>\n",
    "        <td>Canon</td>\n",
    "        <td>DSLR</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Samsung</td>\n",
    "        <td>SmartPhone</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Nikon</td>\n",
    "        <td>DSLR</td>\n",
    "  </tr><tr>\n",
    "      <td>105</td>\n",
    "      <td>Sony</td>\n",
    "      <td>SmartTV</td>\n",
    "  </tr> \n",
    "</table>''')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.read_html('''<table>\n",
    "    <tr>\n",
    "        <th>ID</th>\n",
    "        <th>Brand</th>\n",
    "        <th>Product</th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>103</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPhone</td>\n",
    "        </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Apple</td>\n",
    "        <td>iPod</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>104</td>\n",
    "        <td>Samsung</td>\n",
    "        <td>SmartPhone</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>107</td>\n",
    "        <td>Canon</td>\n",
    "        <td>DSLR</td>\n",
    "  </tr><tr>\n",
    "      <td>101</td>\n",
    "      <td>Sony</td>\n",
    "      <td>SmartTV</td>\n",
    "  </tr> \n",
    "</table>''')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand     Product\n",
       "0  101    Apple      iPhone\n",
       "1  102    Canon        DSLR\n",
       "2  103  Samsung  SmartPhone\n",
       "3  104    Nikon        DSLR\n",
       "4  105     Sony     SmartTV"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>104</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>104</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>107</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>101</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Brand     Product\n",
       "0  103    Apple      iPhone\n",
       "1  104    Apple        iPod\n",
       "2  104  Samsung  SmartPhone\n",
       "3  107    Canon        DSLR\n",
       "4  101     Sony     SmartTV"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "cd=pd.concat([df1,df2],keys=['Store_A','Store_b'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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></th>\n",
       "      <th>ID</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Product</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td rowspan=\"5\" valign=\"top\">Store_A</td>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>103</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>104</td>\n",
       "      <td>Nikon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"5\" valign=\"top\">Store_b</td>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>104</td>\n",
       "      <td>Apple</td>\n",
       "      <td>iPod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>104</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>SmartPhone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>107</td>\n",
       "      <td>Canon</td>\n",
       "      <td>DSLR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>101</td>\n",
       "      <td>Sony</td>\n",
       "      <td>SmartTV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ID    Brand     Product\n",
       "Store_A 0  101    Apple      iPhone\n",
       "        1  102    Canon        DSLR\n",
       "        2  103  Samsung  SmartPhone\n",
       "        3  104    Nikon        DSLR\n",
       "        4  105     Sony     SmartTV\n",
       "Store_b 0  103    Apple      iPhone\n",
       "        1  104    Apple        iPod\n",
       "        2  104  Samsung  SmartPhone\n",
       "        3  107    Canon        DSLR\n",
       "        4  101     Sony     SmartTV"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', 'Brand', 'Product'], dtype='object')"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cd.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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