NPV-Day 2_IC Exercise-Questions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kic6oK53broE"
   },
   "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 2)\n",
    "                    </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "oe1s0Kh3broG"
   },
   "source": [
    "## Table of Content\n",
    "1. **[Data Structures with Examples](#Data_Structures)**\n",
    "2. **[Create and Manipulate the DataFrames](#create_manipulate)**\n",
    "3. **[Sort](#sorting)**\n",
    "4. **[Rank](#ranking)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JlJ7Wtw-broG"
   },
   "source": [
    "### Let's begin with some hands-on practice exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "26XpOEYEbroH"
   },
   "source": [
    "<a id='Data_Structures'></a>\n",
    "## 1. Data Structures with Examples:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Rj8q582cbroI"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>1. Write a program to create a dataframe from list of lists\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "PzHrJnNRbroJ"
   },
   "source": [
    "**Use the below nested list:**<br>\n",
    "\n",
    "        data = [['Joy', 21], ['Mia', 15], ['Sam', 14]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Joy', 21], ['Mia', 15], ['Sam', 14]]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "import pandas as pd\n",
    "data = [['Joy', 21], ['Mia', 15], ['Sam', 14]]\n",
    "data"
   ]
  },
  {
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Joy</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sam</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Name  Age\n",
       "0  Joy   21\n",
       "1  Mia   15\n",
       "2  Sam   14"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.DataFrame(data,columns=['Name','Age'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "GTblkct8broO"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>2. Extract the second word from the given string\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wqAJ6qeKbroO"
   },
   "source": [
    "**Use the below string:**<br>\n",
    "    \n",
    "    sentence = 'Be confident and be yourself'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'confident'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "sentence = 'Be confident and be yourself'\n",
    "sentence.split()[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Es6zyYS5broR"
   },
   "source": [
    "<a id='create_manipulate'></a>\n",
    "## 2. Create and Manipulate the DataFrames:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "N45T_7y0broS"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>3. Split the 'Name' column into two separate columns as First_Name and Last_Name </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cqJ5X7DrbroS"
   },
   "source": [
    "**Use the dataframe given below:**\n",
    "\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Salary</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma Larter</td>\n",
    "<td>3200</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia Junior</td>\n",
    "<td>4500</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia Depp</td>\n",
    "<td>3600</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James Smith</td>\n",
    "<td>5596</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></th>\n",
       "      <th>Name</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma Larter</td>\n",
       "      <td>3200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia Junior</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia Depp</td>\n",
       "      <td>3600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James Smith</td>\n",
       "      <td>5596</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Salary\n",
       "0  Emma Larter    3200\n",
       "1   Mia Junior    4500\n",
       "2  Sophia Depp    3600\n",
       "3  James Smith    5596"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_html('''<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Salary</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma Larter</td>\n",
    "<td>3200</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia Junior</td>\n",
    "<td>4500</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia Depp</td>\n",
    "<td>3600</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James Smith</td>\n",
    "<td>5596</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Salary</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Last Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma Larter</td>\n",
       "      <td>3200</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Larter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia Junior</td>\n",
       "      <td>4500</td>\n",
       "      <td>Mia</td>\n",
       "      <td>Junior</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia Depp</td>\n",
       "      <td>3600</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Depp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James Smith</td>\n",
       "      <td>5596</td>\n",
       "      <td>James</td>\n",
       "      <td>Smith</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Salary First Name Last Name\n",
       "0  Emma Larter    3200       Emma    Larter\n",
       "1   Mia Junior    4500        Mia    Junior\n",
       "2  Sophia Depp    3600     Sophia      Depp\n",
       "3  James Smith    5596      James     Smith"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "data['First Name']=data['Name'].apply(lambda x:x.split()[0])\n",
    "\n",
    "data['Last Name']=data['Name'].apply(lambda x:x.split()[1])\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HR_gxOnCbroV"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>4. Select the rows from below dataframe where marks are less than 60 </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "psRI2T3TbroW"
   },
   "source": [
    "**Use the dataframe given below:**\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Marks</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>90</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>50</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jonny</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>55</td>\n",
    "</tr>\n",
    "   \n",
    "</table>"
   ]
  },
  {
   "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>Marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>John</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Jonny</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mia</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Marks\n",
       "0    John     90\n",
       "1  Robert     50\n",
       "2   Jonny     89\n",
       "3     Mia     55"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_html('''<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Marks</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>John</td>\n",
    "<td>90</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Robert</td>\n",
    "<td>50</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Jonny</td>\n",
    "<td>89</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia</td>\n",
    "<td>55</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "data"
   ]
  },
  {
   "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>Marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Robert</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Mia</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Marks\n",
       "1  Robert     50\n",
       "3     Mia     55"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['Marks']<60]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "z35FqMrYbroZ"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>5. Write a program to select the rows where the sales are higher than 60000 for Mumbai </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pEwm6Uj4brob"
   },
   "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": {
    "colab": {},
    "colab_type": "code",
    "id": "Z_-bcP7ibrob"
   },
   "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",
    "data=pd.read_html('''<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",
    "data"
   ]
  },
  {
   "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></th>\n",
       "      <th>Store</th>\n",
       "      <th>Location</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store Location  Sales\n",
       "3     C   Mumbai  90000\n",
       "8     C   Mumbai  89000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['Sales']>60000) & (data['Location']=='Mumbai')]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_UZzFsqcbroe"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>6. Write a program to select stores located in Hyderabad</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xpPd6-yxbroe"
   },
   "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": 22,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "S3J4OGa_brof"
   },
   "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": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "data=pd.read_html('''<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",
    "data"
   ]
  },
  {
   "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>Store</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store\n",
       "2     A\n",
       "6     D"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['Location']=='Hyderabad'][['Store']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "MkRQWQJMbroh"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>7. Write a program to replace the 'Store' column with the values A, B, C, and D with Store_A,  Store_B, Store_C and Store_D respectively </b>  \n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "NjNY0QDobroh"
   },
   "source": [
    "**Use the dataframe given below:**\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>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "FcqGrhbobroi"
   },
   "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": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "data=pd.read_html('''<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",
    "data"
   ]
  },
  {
   "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>Store</th>\n",
       "      <th>Location</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Store_A</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Store_B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Store_A</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Store_C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Store_D</td>\n",
       "      <td>Pune</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Store_A</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Store_D</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Store_A</td>\n",
       "      <td>Pune</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Store_C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Store_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  Store_A     Mumbai  40000\n",
       "1  Store_B       Pune  45000\n",
       "2  Store_A  Hyderabad  50000\n",
       "3  Store_C     Mumbai  90000\n",
       "4  Store_D       Pune  89000\n",
       "5  Store_A      Delhi  87000\n",
       "6  Store_D  Hyderabad  85000\n",
       "7  Store_A       Pune  78000\n",
       "8  Store_C     Mumbai  89000\n",
       "9  Store_B       Pune  70000"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Store']=data['Store'].map({'A':'Store_A',\n",
    "                                 'B':'Store_B',\n",
    "                                 'C':'Store_C',\n",
    "                                 'D':'Store_D'\n",
    "    \n",
    "})\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "A_FO5JqKbrok"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>8. Create a dataframe in pandas using the given list.\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "492OEIcHbrol"
   },
   "source": [
    "**Use the below list**\n",
    "\n",
    "        city = ['Delhi', 'Mumbai', 'Chennai', 'Kolkata']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ujlQ0ABIbrom"
   },
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Chennai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Kolkata</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City\n",
       "0    Delhi\n",
       "1   Mumbai\n",
       "2  Chennai\n",
       "3  Kolkata"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "city = ['Delhi', 'Mumbai', 'Chennai', 'Kolkata']\n",
    "city_df=pd.DataFrame(data=city,columns=['City'])\n",
    "city_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "YaZVCuk0brop"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>9. Save a given dataframe to a csv file\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "zdG3-8djbroq"
   },
   "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": 33,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "LRIV0DMCbroq"
   },
   "outputs": [],
   "source": [
    "# type your code here\n",
    "data.to_csv('Stores.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kzBS49kCbrot"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>10. Find the maximum sales for each store\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6pTfSncBbrot"
   },
   "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": 68,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-ru3CyhDbrou"
   },
   "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": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df=pd.read_html('''\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>''')[0]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>D</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store  Sales\n",
       "0     A  87000\n",
       "1     B  70000\n",
       "2     C  90000\n",
       "3     D  89000"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Store')[['Sales']].max().reset_index()#reset_index()-DATA FRAME RESET"
   ]
  },
  {
   "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>Store</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>D</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store  Sales\n",
       "0     A  87000\n",
       "1     B  70000\n",
       "2     C  90000\n",
       "3     D  89000"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g=df.groupby('Store')\n",
    "g[['Sales']].max().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-AeYRdcBbrow"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>11. Write a program to select all columns, except the 'Location' from the given dataframe\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "FhMe-BOlbrow"
   },
   "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": 45,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "VZwFNyNmbrow"
   },
   "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>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
       "      <td>87000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>D</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>A</td>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>C</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>B</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store  Sales\n",
       "0     A  40000\n",
       "1     B  45000\n",
       "2     A  50000\n",
       "3     C  90000\n",
       "4     D  89000\n",
       "5     A  87000\n",
       "6     D  85000\n",
       "7     A  78000\n",
       "8     C  89000\n",
       "9     B  70000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df[['Store','Sales']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "jdPQGGNbbroy"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>12. Write a program to insert a given column at the second position in a dataframe\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "eTt8takEbroz"
   },
   "source": [
    "**Use the dataframe given below:**\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Age</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma Larter</td>\n",
    "<td>34</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia Junior</td>\n",
    "<td>59</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia Depp</td>\n",
    "<td>32</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James Smith</td>\n",
    "<td>40</td>\n",
    "</tr>\n",
    "   \n",
    "</table>\n",
    "\n",
    "**Add the variable 'Salary' as second column**<br>\n",
    "            \n",
    "            Salary = [35000, 24000, 55000, 40000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "SkFzhAaRbroz"
   },
   "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>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma Larter</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia Junior</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia Depp</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James Smith</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Age\n",
       "0  Emma Larter   34\n",
       "1   Mia Junior   59\n",
       "2  Sophia Depp   32\n",
       "3  James Smith   40"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df1=pd.read_html('''\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Age</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma Larter</td>\n",
    "<td>34</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia Junior</td>\n",
    "<td>59</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia Depp</td>\n",
    "<td>32</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James Smith</td>\n",
    "<td>40</td>\n",
    "</tr>\n",
    "   \n",
    "</table>''')[0]\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Emma Larter</td>\n",
       "      <td>35000</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Mia Junior</td>\n",
       "      <td>24000</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sophia Depp</td>\n",
       "      <td>55000</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James Smith</td>\n",
       "      <td>40000</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Salary  Age\n",
       "0  Emma Larter   35000   34\n",
       "1   Mia Junior   24000   59\n",
       "2  Sophia Depp   55000   32\n",
       "3  James Smith   40000   40"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.insert(loc=1,column='Salary',value=[35000, 24000, 55000, 40000])\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "u57xUd5cbro1"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>13. Write a program to get the third observation of the given dataframe\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "q-SX6ARYbro2"
   },
   "source": [
    "**Use the dataframe given below:**\n",
    "\n",
    "<table>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Age</th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Emma Larter</td>\n",
    "<td>34</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Mia Junior</td>\n",
    "<td>59</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Sophia Depp</td>\n",
    "<td>32</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>James Smith</td>\n",
    "<td>40</td>\n",
    "</tr>\n",
    "</table>    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "mbhm0alkbro2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name      Sophia Depp\n",
       "Salary          55000\n",
       "Age                32\n",
       "Name: 2, dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df2=df1.loc[2] #oriloc[2]\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "3BSI3I2Bbro4"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>14. Write a program to create a dataframe from the provided lists</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6sJVU9BKbro5"
   },
   "source": [
    "**Use the following lists to create your arrays:**\n",
    "        \n",
    "            columns = [\"Science\", \"Maths\", \"English\"]\n",
    "            \n",
    "            marks = [[55, 78, 88], [93, 63, 83],[94, 74, 64]]\n",
    "            \n",
    "**Hint:** Convert the list marks into an array           "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "i43LDErebro5"
   },
   "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>Science</th>\n",
       "      <th>Maths</th>\n",
       "      <th>English</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>78</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>93</td>\n",
       "      <td>63</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>94</td>\n",
       "      <td>74</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Science  Maths  English\n",
       "0       55     78       88\n",
       "1       93     63       83\n",
       "2       94     74       64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "c = [\"Science\", \"Maths\", \"English\"]\n",
    "marks = [[55, 78, 88], [93, 63, 83],[94, 74, 64]]\n",
    "df=pd.DataFrame(data=marks,columns=c)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "lT3ns2Anbro8"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>15. Write a program to count total sales per store </b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JLRKaQRMbro8"
   },
   "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": 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>Store</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>255000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>115000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>179000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>D</td>\n",
       "      <td>174000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store   Sales\n",
       "0     A  255000\n",
       "1     B  115000\n",
       "2     C  179000\n",
       "3     D  174000"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df3=df.groupby(['Store'])[['Sales']].sum().reset_index()\n",
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "MczOZRuhbrpB"
   },
   "source": [
    "<a id='sorting'></a>\n",
    "## 3. Sort"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5t-wNWrlbrpC"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>16. Write a program to sort the dataframe by 'Sales' in ascending order\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "PKqI6PuFbrpC"
   },
   "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": 80,
   "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>9</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>70000</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>6</td>\n",
       "      <td>D</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>85000</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>4</td>\n",
       "      <td>D</td>\n",
       "      <td>Pune</td>\n",
       "      <td>89000</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>3</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</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",
       "9     B       Pune  70000\n",
       "7     A       Pune  78000\n",
       "6     D  Hyderabad  85000\n",
       "5     A      Delhi  87000\n",
       "4     D       Pune  89000\n",
       "8     C     Mumbai  89000\n",
       "3     C     Mumbai  90000"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df.sort_values(by='Sales',ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7ti1ghjLbrpG"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>17. Write a program to sort the dataframe by 'Store' in ascending order and by 'Sales' in descending order with respect to store simultaneously\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cGyakcEdbrpG"
   },
   "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": 83,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tdCkIYaXbrpG"
   },
   "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>5</td>\n",
       "      <td>A</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>87000</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>2</td>\n",
       "      <td>A</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>70000</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>3</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</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>4</td>\n",
       "      <td>D</td>\n",
       "      <td>Pune</td>\n",
       "      <td>89000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>D</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store   Location  Sales\n",
       "5     A      Delhi  87000\n",
       "7     A       Pune  78000\n",
       "2     A  Hyderabad  50000\n",
       "0     A     Mumbai  40000\n",
       "9     B       Pune  70000\n",
       "1     B       Pune  45000\n",
       "3     C     Mumbai  90000\n",
       "8     C     Mumbai  89000\n",
       "4     D       Pune  89000\n",
       "6     D  Hyderabad  85000"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df.sort_values(by=['Store','Sales'],ascending=[True,False])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6ISK8C4nbrpI"
   },
   "source": [
    "<a id='ranking'></a>\n",
    "## 4. Rank"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Vk0X5xxqbrpJ"
   },
   "source": [
    "<table align=\"left\">\n",
    "    <tr>\n",
    "        <td width=\"6%\">\n",
    "            <img src=\"question_icon.png\">\n",
    "        </td>\n",
    "        <td>\n",
    "            <div align=\"left\", style=\"font-size:120%\">\n",
    "                <font color=\"#21618C\">\n",
    "                    <b>18. Create a column 'Rank_sales' which contains the rank of each store based on sales of the product in ascending order\n",
    "</b>\n",
    "                </font>\n",
    "            </div>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7O5czmbmbrpJ"
   },
   "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": 84,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "8Crt7wH6brpJ"
   },
   "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",
       "      <th>Rank_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",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>45000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>50000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>90000</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>Pune</td>\n",
       "      <td>89000</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>87000</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>D</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>85000</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>A</td>\n",
       "      <td>Pune</td>\n",
       "      <td>78000</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>C</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>89000</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>B</td>\n",
       "      <td>Pune</td>\n",
       "      <td>70000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Store   Location  Sales  Rank_Sales\n",
       "0     A     Mumbai  40000         1.0\n",
       "1     B       Pune  45000         2.0\n",
       "2     A  Hyderabad  50000         3.0\n",
       "3     C     Mumbai  90000        10.0\n",
       "4     D       Pune  89000         8.5\n",
       "5     A      Delhi  87000         7.0\n",
       "6     D  Hyderabad  85000         6.0\n",
       "7     A       Pune  78000         5.0\n",
       "8     C     Mumbai  89000         8.5\n",
       "9     B       Pune  70000         4.0"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type your code here\n",
    "df['Rank_Sales']=df['Sales'].rank()#default \n",
    "df"
   ]
  }
 ],
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   "name": "NPV - In-Class - Lab Exercise (DAY 2)  -  Questions [v2.0 - 200320].ipynb",
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