Task_05.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> HASHWANTH S</h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Data Science and Business Analytics Intern @ TSF </h2>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>TASK 5: EDA ON INDIAN PREMIER LEAGUE (IPL)</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.2.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.2.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from plotly.offline import init_notebook_mode,iplot\n",
    "import cufflinks as cf\n",
    "import chart_studio.plotly as py\n",
    "init_notebook_mode(connected=True)\n",
    "cf.go_offline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('matches.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city        date                        team1  \\\n",
       "0   1    2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "1   2    2017       Pune  2017-04-06               Mumbai Indians   \n",
       "2   3    2017     Rajkot  2017-04-07                Gujarat Lions   \n",
       "3   4    2017     Indore  2017-04-08       Rising Pune Supergiant   \n",
       "4   5    2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3              Kings XI Punjab              Kings XI Punjab         field   \n",
       "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0          Sunrisers Hyderabad           35   \n",
       "1  normal           0       Rising Pune Supergiant            0   \n",
       "2  normal           0        Kolkata Knight Riders            0   \n",
       "3  normal           0              Kings XI Punjab            0   \n",
       "4  normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "   win_by_wickets player_of_match                                      venue  \\\n",
       "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "          umpire1        umpire2 umpire3  \n",
       "0     AY Dandekar       NJ Llong     NaN  \n",
       "1  A Nand Kishore         S Ravi     NaN  \n",
       "2     Nitin Menon      CK Nandan     NaN  \n",
       "3    AK Chaudhary  C Shamshuddin     NaN  \n",
       "4             NaN            NaN     NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df.drop('umpire3',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city        date                        team1  \\\n",
       "0   1    2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "1   2    2017       Pune  2017-04-06               Mumbai Indians   \n",
       "2   3    2017     Rajkot  2017-04-07                Gujarat Lions   \n",
       "3   4    2017     Indore  2017-04-08       Rising Pune Supergiant   \n",
       "4   5    2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3              Kings XI Punjab              Kings XI Punjab         field   \n",
       "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0          Sunrisers Hyderabad           35   \n",
       "1  normal           0       Rising Pune Supergiant            0   \n",
       "2  normal           0        Kolkata Knight Riders            0   \n",
       "3  normal           0              Kings XI Punjab            0   \n",
       "4  normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "   win_by_wickets player_of_match                                      venue  \\\n",
       "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "          umpire1        umpire2  \n",
       "0     AY Dandekar       NJ Llong  \n",
       "1  A Nand Kishore         S Ravi  \n",
       "2     Nitin Menon      CK Nandan  \n",
       "3    AK Chaudhary  C Shamshuddin  \n",
       "4             NaN            NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.title('Matches per Season',fontsize=16)\n",
    "sns.countplot(x='season',data=df1,palette='viridis')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>winner</th>\n",
       "      <th>venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>New Wanderers Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Eden Gardens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Eden Gardens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    season                 winner                                      venue\n",
       "1     2008       Rajasthan Royals                 Dr DY Patil Sports Academy\n",
       "2     2009        Deccan Chargers                      New Wanderers Stadium\n",
       "3     2010    Chennai Super Kings                 Dr DY Patil Sports Academy\n",
       "4     2011    Chennai Super Kings            MA Chidambaram Stadium, Chepauk\n",
       "5     2012  Kolkata Knight Riders            MA Chidambaram Stadium, Chepauk\n",
       "6     2013         Mumbai Indians                               Eden Gardens\n",
       "7     2014  Kolkata Knight Riders                      M Chinnaswamy Stadium\n",
       "8     2015         Mumbai Indians                               Eden Gardens\n",
       "9     2016    Sunrisers Hyderabad                      M Chinnaswamy Stadium\n",
       "0     2017         Mumbai Indians  Rajiv Gandhi International Stadium, Uppal\n",
       "10    2018    Chennai Super Kings                           Wankhede Stadium\n",
       "11    2019         Mumbai Indians         Rajiv Gandhi Intl. Cricket Stadium"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "season_finals = df1.drop_duplicates(subset=['season'],keep='last')\n",
    "season_finals[['season','winner','venue']].reset_index(drop=True).sort_values('season')"
   ]
  },
  {
   "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>season</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>winner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    season                  toss_winner toss_decision                 winner\n",
       "1     2008             Rajasthan Royals         field       Rajasthan Royals\n",
       "2     2009  Royal Challengers Bangalore         field        Deccan Chargers\n",
       "3     2010          Chennai Super Kings           bat    Chennai Super Kings\n",
       "4     2011          Chennai Super Kings           bat    Chennai Super Kings\n",
       "5     2012          Chennai Super Kings           bat  Kolkata Knight Riders\n",
       "6     2013               Mumbai Indians           bat         Mumbai Indians\n",
       "7     2014        Kolkata Knight Riders         field  Kolkata Knight Riders\n",
       "8     2015          Chennai Super Kings         field         Mumbai Indians\n",
       "9     2016          Sunrisers Hyderabad           bat    Sunrisers Hyderabad\n",
       "0     2017               Mumbai Indians           bat         Mumbai Indians\n",
       "10    2018          Chennai Super Kings         field    Chennai Super Kings\n",
       "11    2019               Mumbai Indians           bat         Mumbai Indians"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "season_finals[['season','toss_winner','toss_decision','winner']].reset_index(drop=True).sort_values('season')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize =(5, 5))\n",
    "winning = 0;\n",
    "losing = 0;\n",
    "for i in range(1,len(season_finals)):\n",
    "    if(season_finals['toss_winner'].reset_index(drop=True)[i] == season_finals['winner'].reset_index(drop=True)[i]):\n",
    "        winning+=1;\n",
    "    else:\n",
    "        losing+=1;\n",
    "data = [winning,losing]\n",
    "label = ['Yes','No']\n",
    "explode=(0.05,0.0)\n",
    "plt.title('Toss winners winning season finals',fontsize=16)\n",
    "plt.pie(data,labels=label,explode=explode,autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "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>season</th>\n",
       "      <th>winner</th>\n",
       "      <th>player_of_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>YK Pathan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>A Kumble</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>SK Raina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>M Vijay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>MS Bisla</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>KA Pollard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>MK Pandey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>RG Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>KH Pandya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>SR Watson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    season                 winner player_of_match\n",
       "1     2008       Rajasthan Royals       YK Pathan\n",
       "2     2009        Deccan Chargers        A Kumble\n",
       "3     2010    Chennai Super Kings        SK Raina\n",
       "4     2011    Chennai Super Kings         M Vijay\n",
       "5     2012  Kolkata Knight Riders        MS Bisla\n",
       "6     2013         Mumbai Indians      KA Pollard\n",
       "7     2014  Kolkata Knight Riders       MK Pandey\n",
       "8     2015         Mumbai Indians       RG Sharma\n",
       "9     2016    Sunrisers Hyderabad     BCJ Cutting\n",
       "0     2017         Mumbai Indians       KH Pandya\n",
       "10    2018    Chennai Super Kings       SR Watson\n",
       "11    2019         Mumbai Indians       JJ Bumrah"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "season_finals[['season','winner','player_of_match']].reset_index(drop=True).sort_values('season')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians           4\n",
       "Chennai Super Kings      3\n",
       "Kolkata Knight Riders    2\n",
       "Rajasthan Royals         1\n",
       "Sunrisers Hyderabad      1\n",
       "Deccan Chargers          1\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "season_finals['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.title('Leading Players of IPL',fontsize=16)\n",
    "leading_players = df1['player_of_match'].value_counts()[:10]\n",
    "sns.barplot(x=leading_players.index,y=leading_players,palette=\"viridis\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HDPK Dharmasena</th>\n",
       "      <td>73.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asad Rauf</th>\n",
       "      <td>51.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Ravi</th>\n",
       "      <td>49.0</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK Chaudhary</th>\n",
       "      <td>43.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aleem Dar</th>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 umpire1  umpire2\n",
       "HDPK Dharmasena     73.0     14.0\n",
       "Asad Rauf           51.0      NaN\n",
       "S Ravi              49.0     57.0\n",
       "AK Chaudhary        43.0     15.0\n",
       "Aleem Dar           38.0      NaN"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "up1 = df1['umpire1'].value_counts()\n",
    "up2 = df1['umpire2'].value_counts()\n",
    "dup = pd.concat([up1,up2],axis=1)\n",
    "dup.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fcab649048>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,6))\n",
    "plt.title('Total number of matches won by team',fontsize=16)\n",
    "plt.xticks(rotation=40)\n",
    "sns.countplot(x='winner',data=df1,palette='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,6))\n",
    "plt.title('Winning Team choices',fontsize=16)\n",
    "sns.countplot(x='season',hue='toss_decision',data=df1,palette='viridis')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BB4DngEa384ntk+LxrjBwZl0ye4Pfp+7zzKyVyhPTV4QWrm9yO5fnRIM+jtmjB+MP7N900KBKfzZnvVwWDvwdZ15IHuAeJMXjPfslMuZVPlW5cE51vfXIR8vKJs1bRzZXvPM1hVQVD3LmqL7WJYcMSnaNBRMBn3J/yO/7OzIf5ClSPN4Qt2z7wsa0eUPOsvs/Nm158OmZK/2r6lJu5ypq+/TtwkUHD0iftn9f27LsR2Mh/x3ASrdzCSket5VnTev6nGXfOG1JjfKfD5fGPli0sdPO23SU7mUhvnfEkOwFYwZYOct+riwc+DXOjovCJVI87uiaMXI/tGxuePfL9cqfJi2ILt4gczcdrUskwOWHDTYvP2ywmbPtt8rDgVsAOYWPC6R4CqssY+RutOCGN79Yq/757QWRZTVJtzN1OrGgj4sOHpi76qhhWQWmlkcCPwemu52rM5HiKYyQmbO+b+Ts2979cr3/rolfRlfUSuG4LeRXGf+N/vb144angj71i/JI4ErgE7dzdQZSPB1LBS5IZMy7Z1fXxX7z6rzY/DWyi4nX+FWFc77Rz/75SXumVUV5NBby34RzckPRQaR4Os6IxrTx5Kq61IhfvTQ3Pn1prdt5xA5URAPccvLI1En79EpHg/6rgaeQ/YA6hBRP+/NnjNyNOdu+5Q9v6qFHPlqmyipVcTlgQFfuHr9foioe/LwsHLgU5wSIoh1J8bSv/ZvSxlPz1jT2++F/P4tVb5L9cIqVT1X4zqGDcj88bkRWUZS/RAK+23AObCbagRRP+winsrnbcrZ9za0vzw0/+3G14nYg0T56loe4/Yy9k4cOrWqMhfyXAa+7nakUSPHsvkObMuZT05fUdPvp859HNzRm3M4jOsARw6v4/dn7JWIh39tl4cAlOId0FbtIimfXxRMZ827Tsi++6bk5kYlfrHU7j+hgIb/KbafvnT5l3941sZD/JGCO25mKlRTPrtESGXPSO/PXVf3ipbkRrx7VT3SMM0b1te88c+9UyO+7zqcqD7qdpxhJ8ey8U5JZ88nbXpkXfWrmSjk9UCc1rEec/1x6YLJrNPhyPOy/HOesGqKNpHjaTk0ZuV+mjdxPLn94ZvSTFXVu5xEuiwZ9/P7sfVNjtR5r4iH/icACtzMVCymetilrSptPr9iUPOLSh2bE1ssEsmjhgoMGWLecsmcq7PddpqrKf93OUwykeHZsaCJjTnpz7treP33u87AckEu0Zq8+5Tx06YHJWMj/eDzkvxaQV6ftkOLZvuOTWfOZ377+ZWzCtOUynyO2qzzs597zR6VGD+w6rywcGAfI9vg2SPG0TkkbuZsypvXL7z46KzJD3mcl2khR4LbT9s6ceUDf6njIfwSw2u1MXiTFszUlkTH/vrY+fclFD06Prqkv3VPGiI5z9VHDzKuPGlobDfoPRyadtyLF83VKImP+c+Wm5IXj758aLcRpfUXpGv+Nftatp+3VGA36jwVmup3HS6R4vqImMuYDy2uS5537z6nRxoyUjth9x+zZg/vOH5WIBv0nAB+4nccrpHgcaiJjPrhsY+Kcc/81LdYkpSPa0eHDq/jnxaOT0aD/VOBdt/N4gRSPUzoPL9mQOOu8f02NJbI5t/OIEnTwkEoe/PaByVjIfxbwptt53NbZi0dtypgTFq9vOv2CB6ZJ6YgOdcCArky4/KBkLOQfD7zmdh43debi8TVlzMcWrms87cJ/T48mpXREAezfv4InvjsmGQ36jwJmuJ3HLZ11pzhfU8Z8Ql/beOoFD0jpiML5bGUd1z75aTSZNd8EBrudxy2dsniSWfNPi9Y3nXzhv6fFUoaUjiisd+av566JelkiY04GKt3O44ZOVzxmzvpefdL4v28/NCOWNuR9V8Idj3y0zPf0rJU9GtPGm0DI7TyF1tmKZ1zKyN1z/gPTonLwLuG237w6LzRjae3IprT5ONCpjtPdmYpnZCqbe+HyR2bJaYOFJ9g2XPX4J9EVtckTUtncb93OU0idZVWrMpExv/jlS3N7PfeJnAECIPDu3RAIA2BHK8n1H41/3hug+rBDcczRF4A/uNXt1NVzUFfNxjzwYufzZdPwLZuGXdEPc/+zAfDPnIC5/zmb719sX7dYkNeuOzzZLR68LuBTO8WhVDvDiMfXmDZeeObj6kopnbycs5lpHH41xuFXY44+H//s5zAOvgzjiGuw41X4lk/b6ma+OS/gm/u681LdfNmKWRhHXgepesgmUdfOw+o2REpnJ9Qkspz/wLRo2sjdBxzrdp5CKPniSWbNOxeubxp9+6vzOt0E3rYo9ashlyXw4f0EpvwdpXYZxuFXQ7jMuYJlYauBrW5nVw7C3P9bX7/QH4ScCXYOFAV1+XSsQQcX4KcoLUs3Jrjs4ZmRVDb3PDDQ7TwdrdSL58xUNnfNdx+ZFTPlPMJf8QXIDRuLcej3MPc/m8CsxyEYA/KbUhsXYQ34xlY3s/qNYss5UHPEOPwzJ2D12Rd15SdYA8fgW/g//J89i9K4vhA/TcmYuWwT9767MNyYNp4FfG7n6UilXDzDkllzwncenhmtSWTdzuIpdrwH1oDRoCjYZT2wg1FIN+BbNBnfwvcwDr0CfFuPeFq9r6ohmIdcjtV3f9SaJdixKpR0PeaeJ+D78q0O/klKzz8nL/Yv3pDYM2PkbnQ7S0cq1eJRG9PG0396a0F4TnW921k8R10+Hf/nLzufpOrByOBbPgNl4xKMw74PofhO36dvwdvkhh8NuSy2ogIKmHLY4Z1l2XD145/EDMv+BTDK7TwdpSSLx8hZ1y6rSWoPfbi0pIeru8oaNAaMFIHJ9xGY+SjmqLPx6W+jpOsJfPQAgSl/Q13yIQCBD+8HaweHCUnUohhp7Iq+2F36oCQ3EZj6ALmhhxXgpyk9q+pS3PzC5+FExnwBiLqdpyOU4nL60FTWnHPSvR9El25MuJ1FiF32jwsPSB0xovtjsZD/CreztLdSG/E4m1iTFoSkdESxu+n5OZG0kbsQONHtLO2tpIrHyFnXrKhN7vHgB7KJJYpfQ8rkmic+jSaz5uNAd7fztKdSKp4hZs7+7bVPfBqTlXNRKqYuqeGJ6StijWnjMUro/VylUjxqY9p46s9vLwgtkU0sUWJ+P1EPbmzKfhM4z+0s7aUkisfIWVetrE2NfGDKEtnEEiUnm7O48dnZsWTWvBeIuJ2nPZRC8Qw0c/Zd1z4pm1iidM1ctolpS2ojGSP3I7eztIeiL57GtHH3A1OWBBdvaHI7ihAd6tevzI1ZNj8DerqdZXcVe/HsbcNJ/5y82O92ECE62vKaJE/NXOFryph3uZ1ldxV18TSkjHv+8vbCkJyWRnQWf357YQib8cDebmfZHcVcPAebln3oY9OWF/PPIMROqU8Z/GmSHmpIG393O8vuKNonbUPK+MtdE7+MZEw5YLvoXCZMW64mMuYBwPFuZ9lVxVo845oy5l7PfixHFBSdj5Gz+dVLc2NNafN+oCjnN4uxeJTGtHHvHa/Nj+Vk/Vx0Um/NW8eiDU3dc5Z9udtZdkUxFs8ZGxoz/V//Yo3bOYRw1a9e+iKWMXN3AG07apuHFFvx+JrS5j23vTIvXnpH8xBi58yurmfB2sYQcI7bWXZWsRXP+Us2NnV7b8EGt3MI4Ql/eWdRvCFl3EqRvYG0qIqnIWXcfM+khTt/XE4hStR7C9bTkDZ6A0e7nWVnFFPxjDJyVv/JC+TMBUI0s224952FsXpn1FM0iqZ4mtLmdY9OXR6ShSwhvu7FT1crCowG9nA7S1sVS/HE/T7l3CdnrCjKfRaE6EjZnMVj05f7ExnzereztFWxFM/505bU5NY3yulShGjN49NWBHyqcgkQcztLWxRF8TSkjB//58NlMqksxDasqksxY2mtRZEcpbAYimd0Nmf1e3+hLKELsT3/nrIk3pAyfkoRLK17vnia0ub1j3y0LCQ7DAqxfVMWbSRjWr2B/dzOsiNeL54yv085+6mZK+VYykLsgG3DS5+tCmbMnOf3ZPZ08Vi2fcFHi2usDTKpLESbvP752kDGsC50O8eOeLp4GlLG9x+fvrwoZumF8IJPV24C6AEMcznKdnm5eLqFA76RHyzc6HYOIYqGbcMbX6xVTMs6y+0s2+Pl4jlp2pKarBxhUIid89qc1eGmtHmJ2zm2x7PFU5fMXvjqnDWy744QO2nqkhqCfnUY0NvtLNvi1eIJR4K+I9/9Ut4QKsTOMnI2k/UNJnC621m2xavFc8TiDYlsbSLrdg4hitLLs1fH6pJZz25uebJ4UtncyW9+sVZWs4TYRZMXbCAS9I0GKtzO0hpPFk82Z506ZeEG2WlQiF2UzOaYuXRTBjjZ7Syt8WLx9Az61D6zq+vdziFEUXtr3tqyxrRxgts5WuPF4jlm5rLarJy6RojdM6e6HsvmULdztMZzxdOQMk6dNG9dmds5hCh289c0EA36BgARt7NsyXPFY8Mh+d2+hRC7IWNarKxNJoFRbmfZkteKJxgL+vouXNfkdg4hSsKMZbVB4EC3c2zJa8WjrW/MpORtEkK0j4+XbwrXp4yxbufYkteKZ9+5qxvcziBEyZizsh5V4SC3c2zJU8WTMXIHzF5ZJ+/PEqKdLNrQRNCvdsdjOxJ6qngS2dwh89c2eP54sUIUi5xls2h9UxLnvFue4aniCQfUPb9c0+h2DCFKyoyltRHLsj21ueWl4qlSFSW6qi7ldg4hSsqnK+qCDWnjKLdztOSl4tln8YYmaR0h2tmSjU0oKEPdztGSl4pn39kr60NuhxCi1KyrzzRPMHuGZ4qnIWUcNHd1fdjtHEKUmppEhqBfjQEBt7M080zxmJY9aE192u0YQpQcy4bGtJHGQ4dC9UzxKArdNskRB4XoEBubMgbQx+0czTxTPAFV7bopKcUjREdYXZdWkOLZWsCvlG1KGm7HEKIkrdqUCiLFs5VAQFXDDWkpHiE6QnVdKmzkrP5u52jmleKpTBq5jC0HHRSiQ6xvSJPImJ7Zl8crxdOtMW3IcEeIDrK2IY1lM8DtHM08UzybkoYchEeIDrKuIY1fVWQ5fQtVtU2yoiVER2lKm/hUJep2jmZeKZ5uG5syfrdDCFGqTMtGUfDMueq8VDxBt0MIUaqc4lGkeLagmJYtBwATooOYloWKd0Y8Xtm8yYb9PplcLiKqAj5VXiuKhaooKIrilYGGZ4onEw6oObdDiK+rigcZUBmlX9coAyqj9pDusdSQqpjRrzLq7xoNRgDZ86qIpI3cyqDfG93jmeIJBWTEU2jxkJ/+lRH6d43SvzLK4KpYZmj3eHpAZVTpXhaKWLadTRu5VTYsjgZ9c0N+3yJgKbAEWAHIUmQRiYW88nT3UPGE/aq8erazoE+lT0WYAZVOsQyojJrDesRTA7vFrD5dwuGAX1VS2dw607KXhvzq/FjI/yVOsTR/NIYDnpkWECXEM8UT9Ksy4tlJigI9y8LOqKUySv+uUXtYj3hycFXM7Ns14i8L+8PprFWbzVnL/aqil4X98xRFaS6VJcCGQEQKXxSeZ4onFPDJE6AVXSIB+ldGnFFL1yiDu8dSQ7vHs/27RtWqeDCazVlNGdNapcCiWMg/N+BTF+OUylKgOh5WTZd/BCG24p3i8cikV6GFAyr9ukbz8ywRBnWLGc7mUJSe5eGwqihWysitsSx7aTjgmxsJ+hbw1abQMr9PTUYLswdUEBgIDAYGY2aHYaZ6YctuEEVDUbOEy38KrHc7ileKJ1uqxeNTFXp3CW+ewB1QGbWG9oglB1fFcn26RILRoC+QNHIbzJy9POBTviwLB+bz1abQUmBTsDDzXyrOoTGdYrGsIWQa9sa2huML9icQ7kKyNkXdihw1iwJsXBghWaPIwlYROeTqNOHyl4CX3I7ileLJBHzFO9dQFQ9uLpb+lRF7SFU8NaR7zOjXNerrGgtEMoZVnzWtalVhYTwc+MKnKs2lshRYXe4r2PxWV5xiGQIMJtO4J7nsHqj+gQSiPTCSBvWrstQuVtmgR9m0zEfdcti0HBqqwcrJ6aWL2T7nZKga4YlNb88UT8jv3b3RYkFfvlSiDKiMMqhbNDu0Rzw1oDKq9CgLRy3bzqSN3GobFseC/rlBv/q1ZWd/SM3ECnPinggwiOZRi7K+oTIAABPgSURBVJEejpEciaIMJRDtjW37aFyTpnYJbFwYpnZxcHOx1K0AI+nP34coRaofQIqnhdoukYBrWQI+hb4Vm1eGGNAtmhvWPZ4cVBWzencJh4J+1ZfK5taalr0s5Fe/zC87txy1NBRo2dkH9GPz5pA5lEzj3tj2MPyhfvhCcRIbktQtt9i4MEjNoohTLMucj9QmcOZqRGckxbOVVV2igbCqOKfiaG+KAj3KQi02h6L2sO7x5ODuMbNvRcRfHvGH04ZVa5jWSp+z7Dy3xbLzUmBdgZadFaCKlptD6fqRWKaGGhhAMFpFpjFD3UqD2sU+NugxNi1TNo9aGteAbZUVIKcoRlI8W8kYpp2oiofK1zdmdukOyiN+Z7RSuXkv3PTQ7vFM/8qI2j0eiho5O5E2c9tadl4ZD6kmhdkcitM8YoHBZJMaZmokim8wwWgvcoZNw5o0tYtVNi6IULvUT90yZ8RStxJyWc8cU0UUmVCZAjS5HQO8UzxkzNy6PhWRbRZPyJ9fds7v4j+wW9Qc3iOeHNgtRs8u4bBPUeztLzuTiAQLsjkUAAbw1bLzcLJNe4EylEC4D6ovQtP6FJuWWWxcEKJmcdgplfyoJdMAFKgCRecSqwoAa9yOAR4qHstmxT59uwwPB9Svlp27x51l54pIIB7yh5JZc4Ox7WXn2gItOytAL5o3hZxl55HYuRH4QgMIhCtI1aWpW2FSs8jPxgXRr20ONa0DkM0hUViKCsF4CA/swwMeKp6QX5340xP3OCBrWtWKwsKyVpady8KBQr2DvYKWm0OZpj3IZUZuXnY20yb11fll5wUtlp2XQX01WGasQDmFaJtYFeQyCdSoJ+Z4FLtznlMmzNf2ws2MIJsYiaIMIRDpA0qAxjUpapfml50XBZ0l5/yyczbhcnwhdlKvfeDbry4jUjHY7SjgoRFPO/PhnDUxvzmUG0KmYS9sezj+UH/8oTISNSnqlufYuCBAzaKoUyzLnM2hZA04czVClIZ4T7Bz69yO0axYi0cButFycyjdsBeW0XLZOUt9tUHNYl9+nkXdPInbsBpsS/bCFZ1HvCcoarXbMZp5uXhifLUX7hCM5AiM/LJzINob28RZdl6iOMvOSwKbi6VuJZhpL/9sQhRWvCcEYkvdjtHMS0/OKKm6/2Bb+xAI90MNREisT1G7zKJmYYiaReHN8yyblkO6DmTZWYi26dI3gz+4yu0YzbxUPL3xBc5gwpnO+4ea1oFty7KzEO2hvF8Wj+zDA94qnuX4QyprZoOZdjuLEKWlcrAFrHQ7RjMvHQTHJJtYT6UnVvuEKB2qDyoHR4HP3Y7SzEvFA1ZuEZVD3U4hRGnpNhyM9Eag0e0ozbxVPIHIZ3Qb5nYKIUpL7/3AMj91O0ZLXiueT+h/kCfePStEyegzyiBSMcXtGC15q3jgIwYc7NkjEQpRlPqPSaKoMuLZjkUEohblfd3OIUTp6L5HGJDi2Q4bIzWT/mPcziFEaagYCNgpPHI4jGZeKx6IVLzJwEPlnNxCtIfe+4KZ9swyejPvFY+ifsTgI2QPQiHaQ+/9LEJlnppYBi8WD8yicnCEgBxaWIjdNviIJnzB6W7H2JIXiydNNrGQvge4nUOI4haMQe/9w8D/3I6yJS8WD/jD79B/TKHOrilEaRoyFrKJ2Xhoj+Vm3iyeQOQ9hhwlOxIKsTu0k1NEKp50O0ZrvFk8MJl+B4YIyNl0hdhl2ok2ivq62zFa49XiqcFMzWbYsW7nEKI49dwbfIFGYIHbUVrj1eKBSNeH2He8nM5BiF0x4ngLRX0R8ORpZLxbPPACw8b58YfdziFE8Rl5RhPB2Atux9gWLxfPesz0Fww7xu0cQhSXSFforoWAyW5H2RYvF4+zubWPbG4JsVOGHg1Gcirg2XcAeLt44HlGHOfHLyeTEKLNRl3cRKTro27H2B6vF89azMx8hhzldg4hikNZbxhwiA/4r9tRtsfrxQPhLg+xzzlJt2MIURRGXZzDMp4GPD1F4f3iUdTn0U7yyeqWEDugKDDmigyhsvvcjrIj3i8eWEUuO5V9x3tyfwQhPGPI0eALrgI+cTvKjhRD8UCk4g4O/5Gnh45CuG7MFQlCZX9yO0ZbFEfxwDtEKmsYMtbtHEJ4U6w7DB6roqhPuB2lLYqleGxC8ds57AZ5x7oQrRl1kUUu+yLQ4HaUtiiW4gFFfZz+Y6ByiNtJhPCeg76XIlx+r9sx2qp4igdSwN845JqM20GE8JShR0Mwth7w3CFOt6WYigcCkXvZ/3ybcBe3kwjhHcfe1kS4/GY8+k701hRX8cBqcsZEDrhEDosqBMCwcdB1UA0e31N5S8VWPBDu8lsOvT6N6nM7iRDuO+72JkJlPwFybkfZGcVXPDADf/ALRl1cNMNKITrEiBOgvO964Dm3o+ysYiweCHe5inG/ThOMu51ECPccd3sT4fIfAUU39VCcxQMfo6ivc9gNhttBhHDFHqdAvOca4CW3o+wKxbaLdotlINnkfO47IELjGrezCFE4igLXftJE5ZDzgVfdjrMrinXEA7Ac+Afjbk25HUSIgtrzdIhWrQReczvKrirm4oFg9DZGnmbScy+3kwhRGL4AHHd7Ij+3U7SbK8VdPFCPGryZE38v71wXncNhN5iEu8wAJrodZXcUe/GAz38/vfevZ6icjUKUuG7D4LAbsoTLv0MRj3agFIoHDELxazj5j02yU6EoaWfen0Dx/wJnfrOolULxALxItOozDv+xLK+L0rT/hTbdtRX4g39xO0p7KObl9C31I5ucz0PHx1k7x+0sQrSfWBVc92mKUPk3gU/djtMeSmXEA1BNIHwl4x9J4Au6nUWI9nPS3SkU378okdKB0ioe52Bh0aoPOOaXWbejCNEuhh0Dw8c1EIzd7HaU9lRKm1rNupNNLmTCGV1YWTTHRfKkmrTKWW9246Gjavnr53E2pp3J+1UJH/t1y3LPN+s3X7cuo/CTqRU0GQoVIYvbD2qgW9jir5/HmLImxFF9M3x/rwSmBT/8qIJ7Dq3DV1ove+0vEIXrP0sS73kW8KbbcdpTKf7pNxCMXso5jyQJxtzOUrQMC345s5ywz3lhuueb9Uw4ppa/Hr6JsoDFzw5o/Nr1/zkvzujuWZ48tpaLRyT502znDbwfrQvx9HG1TFnjnIb66UVRvjUkKaXTFiffncYfeZ0SKx0ozeIBeJFQ/FWOv1MOk7qL7vq0jPOGJekR+fobn+/7PM5FI7a+fFG9nyN6O7/uA6qyfLzBmWfzKzbZHKiKTWNW4ZONAY7sI1vCOzTqEos9T1uX32en5JRq8UCo7Hvsc04TQ492O0nReX5JhMqQxeG9v14QNWmVqWuDnDV467fH7dnV4N1Vzqjm3VVh0jkFgItHJLnuwwou1ZL8a16My/dI8IfP4tw2q4yNqdJ9+O2WXvvCiXelCcVPAEryzCql/JevIxg7l7MfSlLe1+0sReW5JRE+Whvi4ncqmb/Jz01Tu7AhpTJxZYhTBqVb3Uy6YmSCVQkfl77blTVJlV5R54B4x/bPcP8RdYyoMGkyFWoyKpUhizMHp5iwIFrgn6wIhCvgwmeSBMLfAb50O05HKeXiAXiHQOR2Ln4hQUAe5G31+LhaHhtXy4Rjatmzq8ldh9TTPWIxdW1o8+bUlmatD3L64DQPH72JfvEcB1R9fbT0j7kxrtwrQdpU8CnOkR0SplKIH6d4KAqc858kwfgjKGpRHUN5Z5V68YA//DvK+7zG2Q+lUOSBvjuWNvjoH//6oX0v+19XsjkYXG7y5zlxzptUyWvLI1y191fv2/10Y4A+sRw9IhaH9sry7qoQv5lVztlD5IgmX3P4j036HbiQUPx6t6N0tFJcTm9NmEzjNKbfP5J3bw+4HUaIrQwZC+c9WU8wuhewyuU0Ha70RzyONKGy4zn4qjr2OqtTNK0oIuV9YPyjKYLRs+gEpQOdp3gA1hGMHcfpf0vRZ5TbWYRwhMrg4hcS+IJ3AO+6HadQOlPxAHxGMHoRFz2XpKyX21lEZ+cLOitY5f2eIRC50+04hdTZigfgBQKx33PRCwn8YbeziM5KUeHs/6ToufdkQvH/o8gP7LWzOmPxQCB8GxX9X+fi55NSPsIVJ/0xw5AjvyBUdhZFdhbQ9tA5iwdsQmUX0GvfiVI+ouDG/TrLvuOXEyo7Fki7HccNnbV4AExCZec65fNCkkDE7TyiMzjypwYH/t8qQmWHAfU7vH6J6szFA075jKfXPm9I+YgO980fmHzz2nWE4ocCG9yO46bOXjwAOUJl59Jz79e5+EUpH9ExDr4qx5E3biQYPwRY63Yct3WWPZfbwkem8UnWzT2ZCWdEMWR3ftEOFAWO/U2Wb3xnPcH44cAytyN5gRTP1/nIND7B+nmn8OgZUYyk23lEMfMF4Vv/TjH0aJ1Q2Tigxu1IXiHFszUfmcbHqV1yKhPOjJKUx4rYBeEucOGzSXrs+X5+yVyG0C3IHM/WcoTKLqDbsL9y5UdJumtu5xHFprwvXDE5Sc+RjxIqOwUpna3IiGd7LPNSjNTfefqiCEveczuNKAY994Jvv5IkELuVQPiPdLI9kttKimfHjsRIvsJbt8SY+aCMEMW2DRkL5z6eJBi9DEV92u04XibF0zbDyDRNYv7LvXj1B2FMOYa82MKBl1sce3uCYPQU4H2343idFE/blZFpfIq65Ufy+DkxGla7nUd4QaQrnPnPJAMPXUWo7FRAdztSMZDi2TkKRupmzMzPefqiCMumuJ1HuGngoTB+QhJ/+BFC8RsAGQq3kRTPrjmObOIpPns8yqRfhmRnw05G9TnvuTrkmiTB6AXA625HKjZSPLuuG+mGB8g0Hs+zl0ZZOcPtPKIQuvSD8RMSdBs2h3D5t4A1bkcqRlI8u+9bZJMPMuuhCO/eFpSJ5xK252lwxt9T+AK34w//DrB2eBvRKime9tGDdMPDpGqP4JlLY6z+1O08oj1FK+H4O9PseVodwdjpgAxvd5MUT/tRsK1zMdL/Yvo/wrz32wA5w+1MYneoPhh9mcW4X2VQlEcIxm8CGtyOVQqkeNpfb9INE0hsOJhXroux7AO384hdMeBgOP1vCWI95hEuvwz4wu1IpUSKp2MowHiyTX+helaciT+NsX6+25lEW5T1ghN+l2T4cWmCsSuBZ5C3PbQ7KZ6OFSJnXI1l3Mq8l/28fWuERlkE8SRfIH+wrpuyoPyNYPTXQJPbsUqVFE9hVJBN3oLCVUz/p58pfwqQkakCT1AU0E6CE+5KEO4yi3D5d4GFbscqdVI8hdWfdMPvgdP53x0hZj2oygS0S1Q/7HM2jP15E5GuqwiX/xh4DdmsKggpHnfsS7r+Psz0aN6/O8rsJxQyjW5n6hwCERh1icWRN6bxBb4g3OVm4B2kcApKisdd3yRd/3PUwNF89rjCtL+HqF3idqbSFK6Ag75rcuh1BtgfEO7yC2C627E6Kykeb+iPkbwOlO9RPVPhgz/HWfIuyN9m95X1gkOuzfKN71jYuVcIld8KzHM7VmcnxeMtEeA80g03k2nsxYd/jvLZEwpZWVzZKcEY7HEyjP5OI30P8JMzJxCK3wksdzuacEjxeJMCHEa6/meogaOY95LNF89GWDoZmYzeBkV1jgA46pIk2gk+zMx0IhX/AF4G5HQhHiPF4339sXLjyTRcij80nAVv5fj8mSiL30EOxwH02gf2vzDLfufnUJQVBOP/QPU9BaxzO5rYNime4tIHOIPUpkvxR/Zl6WSDOU/HWfgWnWZVLBCB/gfD0KMMRp6eJlaVQfE/SCD8MPCl2/FE20jxFK8q4DRSm75NIHowK2ekWfhWGdUzFVZ/Cmba7XztwxeAvqNh8Ngc2olN9BgZJdv0JaH4S/iCE4GpyOEpio4UT2noAhxPNnEUuexRBGNDqF2aYtmUEMs/ClE9E+pWuJ2xbXxB6DESBh9uo53YSN/RYYz0CvyhVwlE3gQ+QN7KUPSkeEpTBBiNbR1Cqu44/OEDsYwg1TMNlk4po3axQt0Kp4xSm9xJGCqDqhHQXYPue5r03jdJ9z1Uot3CGMnVKL63CMXfAN4Dat0JKTqKFE/noAADgEMwUodiJPdC8Q0mEOmNbas0rU2zaRnULApRuyTklNJKyDRALutstpkZ598drar5QxCMO6fwjXaDWBVEq5z/V/TP0mvfFFXDAwTjAbJNy4G5hMpnofrmAfOBRYAs3ZU4KR5RAQza/JFNjMBM74GiDkTxxVDUIKovgOoLoPj8KKoPyzCxzBw5I0cua6H4FAJhP75QAGybnJnBMprIGbXY1gZU31r8kWoC4ZU4E8DzgRXI3EynJcUjdpYPCAHh/L8RwMSZd2kCsu5FE8VCikcIUXByLnAhRMFJ8QghCk6KRwhRcFI8QoiCk+IRHUrTtLGaptVpmta/xWW/0zTtUhdjCZdJ8YhCyAL/0TRNcTuI8Aa/2wFEp/Auzovc1cBfmy/UNO1HwHk4+wG9r+v6Te7EE4UmIx5RKFcCN2iaNjz/eRkwHjg0/zFc07RT3AonCkuKRxSErus1wA+Ah3Eed2Fgmq7rhq7rNjAF2Mu9hKKQpHhEwei6/gqgA5cCaWCMpmn+/NzPEcACF+OJApLiEYX2AyAFNAL/BT4EZgDLgBfdiyUKSd6rJYQoOBnxCCEKTopHCFFwUjxCiIKT4hFCFJwUjxCi4KR4hBAFJ8UjhCg4KR4hRMFJ8QghCk6KRwhRcFI8QoiCk+IRQhScFI8QouCkeIQQBSfFI4QoOCkeIUTBSfEIIQpOikcIUXBSPEKIgpPiEUIU3P8DSPz216k6BpMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize =(5, 5))\n",
    "winning = 0;\n",
    "losing = 0;\n",
    "for i in range(1,len(df1)):\n",
    "    if(df1['toss_winner'][i] == df1['winner'][i]):\n",
    "        winning+=1;\n",
    "    else:\n",
    "        losing+=1;\n",
    "data = [winning,losing]\n",
    "label = ['Yes','No']\n",
    "explode=(0.05,0.0)\n",
    "plt.title('Toss winners winning matches',fontsize=16)\n",
    "plt.pie(data,labels=label,explode=explode,autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Eden Gardens                                 77\n",
       "Wankhede Stadium                             73\n",
       "M Chinnaswamy Stadium                        73\n",
       "Feroz Shah Kotla                             67\n",
       "Rajiv Gandhi International Stadium, Uppal    56\n",
       "Name: venue, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venue = df1['venue'].value_counts()\n",
    "venue.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning         batting_team                 bowling_team  over  \\\n",
       "0         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "1         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "2         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "3         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "4         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "\n",
       "   ball    batsman non_striker    bowler  is_super_over  ...  bye_runs  \\\n",
       "0     1  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "1     2  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "2     3  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "3     4  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "4     5  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "\n",
       "   legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",
       "0            0            0             0             0           0   \n",
       "1            0            0             0             0           0   \n",
       "2            0            0             0             4           0   \n",
       "3            0            0             0             0           0   \n",
       "4            0            0             0             0           2   \n",
       "\n",
       "   total_runs  player_dismissed dismissal_kind fielder  \n",
       "0           0               NaN            NaN     NaN  \n",
       "1           0               NaN            NaN     NaN  \n",
       "2           4               NaN            NaN     NaN  \n",
       "3           0               NaN            NaN     NaN  \n",
       "4           2               NaN            NaN     NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df2 = pd.read_csv('deliveries.csv')\n",
    "df2.head()"
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  {
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   "execution_count": 21,
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       "                  batting_team  fours\n",
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    "four = df2[df2['batsman_runs']==4]\n",
    "fteam = four.groupby('batting_team')['batsman_runs'].agg([('fours','count')]).sort_values('fours',ascending=False).head().reset_index()\n",
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       "                  batting_team   six\n",
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       "1               Mumbai Indians  1096\n",
       "2              Kings XI Punjab   976\n",
       "3          Chennai Super Kings   973\n",
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       "    season  fours\n",
       "0     2008   1703\n",
       "1     2009   1321\n",
       "2     2010   1709\n",
       "3     2011   1916\n",
       "4     2012   1911\n",
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    "four = final_data[final_data['batsman_runs']==4]\n",
    "fseason = four.groupby('season')['batsman_runs'].agg([('fours','count')]).sort_values('season',ascending=True).reset_index()\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>six</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015</td>\n",
       "      <td>692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2016</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2017</td>\n",
       "      <td>706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018</td>\n",
       "      <td>869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019</td>\n",
       "      <td>778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    season  six\n",
       "0     2008  623\n",
       "1     2009  508\n",
       "2     2010  587\n",
       "3     2011  639\n",
       "4     2012  733\n",
       "5     2013  681\n",
       "6     2014  715\n",
       "7     2015  692\n",
       "8     2016  639\n",
       "9     2017  706\n",
       "10    2018  869\n",
       "11    2019  778"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "six = final_data[final_data['batsman_runs']==6]\n",
    "sseason = six.groupby('season')['batsman_runs'].agg([('six','count')]).sort_values('season',ascending=True).reset_index()\n",
    "sseason"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.title('Most number of fours per season',fontsize=16)\n",
    "sns.barplot(x='season',y='fours',data=fseason,palette='mako')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.title('Most number of six per season',fontsize=16)\n",
    "sns.barplot(x='season',y='six',data=sseason,palette='rocket')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "hovertemplate": "variable=fours<br>season=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "fours",
         "marker": {
          "color": "#636efa",
          "pattern": {
           "shape": ""
          }
         },
         "name": "fours",
         "offsetgroup": "fours",
         "orientation": "v",
         "showlegend": true,
         "textposition": "auto",
         "type": "bar",
         "x": [
          2008,
          2009,
          2010,
          2011,
          2012,
          2013,
          2014,
          2015,
          2016,
          2017,
          2018,
          2019
         ],
         "xaxis": "x",
         "y": [
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          1911,
          2054,
          1563,
          1611,
          1633,
          1612,
          1674,
          1685
         ],
         "yaxis": "y"
        },
        {
         "alignmentgroup": "True",
         "hovertemplate": "variable=six<br>season=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "six",
         "marker": {
          "color": "#EF553B",
          "pattern": {
           "shape": ""
          }
         },
         "name": "six",
         "offsetgroup": "six",
         "orientation": "v",
         "showlegend": true,
         "textposition": "auto",
         "type": "bar",
         "x": [
          2008,
          2009,
          2010,
          2011,
          2012,
          2013,
          2014,
          2015,
          2016,
          2017,
          2018,
          2019
         ],
         "xaxis": "x",
         "y": [
          623,
          508,
          587,
          639,
          733,
          681,
          715,
          692,
          639,
          706,
          869,
          778
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "title": {
          "text": "variable"
         },
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
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              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
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             "ticks": ""
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            "colorscale": [
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             ],
             [
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              "#fdca26"
             ],
             [
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             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
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             [
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            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
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             ],
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             ],
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            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
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            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
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  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "batsman_score = df2.groupby('batsman')['batsman_runs'].agg(['sum']).reset_index().sort_values('sum',ascending=False).head(10).reset_index(drop=True)\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.title('Leading run scorers',fontsize=16)\n",
    "sns.barplot(x='batsman',y='sum',data=batsman_score,palette='icefire')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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poWdXIpQkTX0DM2fxt584bLKbMeF+8p4PTnYTJE1j9kBLkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJwNDDD012E3piuq6XNJlmTnYDJEmaCgZmzuIlJx082c2YcBftdeRkN0GaduyBliRJkhowQEuSJEkNGKAlSZKkBgzQkiRJUgMGaEmS9BgPPTI9z9wxXddL/dezs3BExObAxzJzQUT8HfAp4BFgCNgzM2+JiH2BfwEeBj6UmWf0qj2SJGl8Zq05i70XHzDZzZhwX1x01GQ3QdNET3qgI+JA4ARgTp30X8DbM3MBcBpwUERsCLwD2ArYEfhIRAz0oj2SJEnSROnVEI7rgd3abr8mM6+qf88EHgA2Ay7OzKHMvBu4DnhBj9ojSZIkTYieDOHIzG9ExEZtt/8AEBFbAm8DtqH0Ot/d9rB7gXXHWvbQ0BBLlizpet+8efNWvNFT2EjrOxpr0WItWqxFMV3rANainbVosRYtK7LvlDr17UqEEbE7cDCwS2beGhH3AHPbZpkL3DXWcgYGBqb1ht3N6ra+o7EWLdaixVq0WIsWa9FiLVqa1uLhpQ8yc43ZPWrN5Jmu6zXRBgcHu07vS4COiD0oPxZckJl31MlXAEdGxBxgAJgHXN2P9kiSJI3HzDVm87GL9pjsZky4g17y5cluwiqt5wE6ItYEjgF+A5wWEQDnZ+ZhEXEMcCFlLPbBmflAr9sjSZIkrYyeBejMvAHYot580gjzHA8c36s2SJIkSRPNC6lIkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhowQEuSJGlMjywdmuwm9MSKrNfMHrRDkiRJ08yaawxw+uUvmexmTLiXb35R48fYAy1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhro2aW8I2Jz4GOZuSAi/ho4CVgGXA3sl5lLI+IwYBfgYWD/zLyiV+2RJEmSJkJPeqAj4kDgBGBOnXQUcEhmbg3MAHaNiBcB2wKbA68BPt2LtkiSJEkTqVdDOK4Hdmu7PR84v/69GFgIvAQ4OzOXZeZvgJkR8eQetUeSJEmaED0ZwpGZ34iIjdomzcjMZfXve4F1gXWA29vmGZ5+62jLHhoaYsmSJV3vmzdv3oo2eUobaX1HYy1arEWLtSimax3AWrSzFi3WosVatFiLlqa16NkY6A5L2/6eC9wF3FP/7pw+qoGBgWn9Anazuq3vaKxFi7VosRYt1qLFWrRYixZr0WItWkaqxeDgYNfp/ToLx48jYkH9exFwIXAxsGNErBERTwfWyMzb+tQeSZIkaYX0qwf63cDxETEbWAKcmpmPRMSFwKWUIL9fn9oiSZIkrbCeBejMvAHYov79C8oZNzrnORw4vFdtkCRJkiaaF1KRJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqYFxBeiI2Kfj9jt60xxJkiRpahv1NHYR8VrgFcB2EbF9nbwm8DfAMT1umyRJkjTljHUe6LOAPwDrAZ+r05YC1/eyUZIkSdJUNWqAzsw7gfOA8yJiA2DOeB4nSZIkTVfjCsIR8WlgF+D3wAxgGbBlD9slSZIkTUnj7UneHHhmZi7tZWMkSZKkqW68p7G7jtbwDUmSJGm1Nd4e6KcDN0bEdfX2ssx0CIckSZJWO+MN0K/taSskSZKkVcR4A/Qbukw7YiIbIkmSJK0Kxhugb6n/zwBehJcAlyRJ0mpqXAE6Mz/XfjsiFvemOZIkSdLUNt7zQD+n7eZTKD8qlCRJklY74x3C0d4D/QDwnh60RZIkSZryxjuEY7uIWA94FvCrzLytt82SJEmSpqZx/RgwIl4FXAK8H7gsIvboaaskSZKkKWq8Z9M4AJifma8EXgi8s3dNkiRJkqau8QbopZl5H0Bm3ksZBy1JkiStdsb7I8LrI+KTwAXA1sD1vWuSJEmSNHWNtwf688AdwA7A3sCxPWuRJEmSNIWNN0AfBXwzM98GbFpvS5IkSaud8QbohzPzGoDM/BWwtHdNkiRJkqau8Y6BvjEiPgxcCmwG/K53TZIkSZKmrvH2QO8N/BHYGbgVeGPPWiRJkiRNYeO9EuEDwNEr80QRMQv4b2Aj4BFgX+Bh4CRgGXA1sF9mOjxEkiRJU9Z4e6Anws7AzMzcEjgCOJLyY8RDMnNrYAawax/bI0mSJDXWzwD9C2BmRKwBrAM8BMwHzq/3LwYW9rE9kiRJUmPj/RHhRLiPMnzjWmB94GXANpm5rN5/L7DuWAsZGhpiyZIlXe+bN2/ehDR0qhlpfUdjLVqsRYu1KKZrHcBatLMWLdaixVq0WIuWprXoZ4B+F/C9zHxfRDwNOBeY3Xb/XOCusRYyMDAwrV/Abla39R2NtWixFi3WosVatFiLFmvRYi1arEXLSLUYHBzsOr2fQzjuBO6uf98BzAJ+HBEL6rRFwIV9bI8kSZLUWD97oP8T+EJEXEjpeX4/cCVwfETMBpYAp/axPZIkSVJjfQvQmXkf8Ooud23brzZIkiRJK6ufQzgkSZKkVZ4BWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhowQEuSJEkNGKAlSZKkBgzQkiRJUgMGaEmSJKkBA7QkSZLUgAFakiRJasAALUmSJDVggJYkSZIaMEBLkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGpjZzyeLiPcBrwBmA58BzgdOApYBVwP7ZebSfrZJkiRJaqJvPdARsQDYEtgK2BZ4GnAUcEhmbg3MAHbtV3skSZKkFdHPIRw7Aj8DvgmcDpwBzKf0QgMsBhb2sT2SJElSY/0cwrE+8AzgZcDGwHeANTJzWb3/XmDdsRYyNDTEkiVLut43b968iWnpFDPS+o7GWrRYixZrUUzXOoC1aGctWqxFi7VosRYtTWvRzwB9O3BtZj4IZEQ8QBnGMWwucNdYCxkYGJjWL2A3q9v6jsZatFiLFmvRYi1arEWLtWixFi3WomWkWgwODnad3s8hHBcBO0XEjIh4KvB44Jw6NhpgEXBhH9sjSZIkNda3HujMPCMitgGuoAT3/YBfA8dHxGxgCXBqv9ojSZIkrYi+nsYuMw/sMnnbfrZBkiRJWhleSEWSJElqwAAtSZIkNWCAliRJkhowQEuSJEkNGKAlSZKkBgzQkiRJUgMGaEmSJKkBA7QkSZLUgAFakiRJasAALUmSJDVggJYkSZIaMEBLkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhowQEuSJEkNGKAlSZKkBmb2+wkjYgNgENgBeBg4CVgGXA3sl5lL+90mSZIkabz62gMdEbOAzwF/rpOOAg7JzK2BGcCu/WyPJEmS1FS/h3B8Avgs8Pt6ez5wfv17MbCwz+2RJEmSGunbEI6I2Au4NTO/FxHvq5NnZOay+ve9wLpjLWdoaIglS5Z0vW/evHkT0dQpZ6T1HY21aLEWLdaimK51AGvRzlq0WIsWa9FiLVqa1qKfY6DfCCyLiIXA3wFfAjZou38ucNdYCxkYGJjWL2A3q9v6jsZatFiLFmvRYi1arEWLtWixFi3WomWkWgwODnad3rchHJm5TWZum5kLgKuAPYHFEbGgzrIIuLBf7ZEkSZJWRN/PwtHh3cDxETEbWAKcOsntkSRJkkY1KQG69kIP23Yy2iBJkiStCC+kIkmSJDVggJYkSZIaMEBLkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhowQEuSJEkNGKAlSZKkBgzQkiRJUgMGaEmSJKkBA7QkSZLUgAFakiRJasAALUmSJDVggJYkSZIaMEBLkiRJDRigJUmSpAZm9uuJImIW8AVgI2AA+BBwDXASsAy4GtgvM5f2q02SJElSU/3sgd4DuD0ztwYWAccCRwGH1GkzgF372B5JkiSpsX4G6FOAQ9tuPwzMB86vtxcDC/vYHkmSJKmxvg3hyMz7ACJiLnAqcAjwicxcVme5F1h3rOUMDQ2xZMmSrvfNmzdvYho7xYy0vqOxFi3WosVaFNO1DmAt2lmLFmvRYi1arEVL01r0LUADRMTTgG8Cn8nMr0bEx9vungvcNdYyBgYGpvUL2M3qtr6jsRYt1qLFWrRYixZr0WItWqxFi7VoGakWg4ODXaf3bQhHRPwFcDZwUGZ+oU7+cUQsqH8vAi7sV3skSZKkFdHPHuj3A08EDo2I4bHQ7wSOiYjZwBLK0A5JkiRpyurnGOh3UgJzp2371QZJkiRpZXkhFUmSJKkBA7QkSZLUgAFakiRJasAALUmSJDVggJYkSZIaMEBLkiRJDRigJUmSpAYM0JIkSVIDBmhJkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSAwZoSZIkqQEDtCRJktSAAVqSJElqwAAtSZIkNWCAliRJkhowQEuSJEkNGKAlSZKkBgzQkiRJUgMGaEmSJKkBA7QkSZLUgAFakiRJasAALUmSJDVggJYkSZIamDnZDYiINYDPAH8LDAH7ZOZ1k9sqSZIkqbup0AP9SmBOZr4YeC/wyUlujyRJkjSiqRCgXwKcBZCZlwF/P7nNkSRJkkY2Y9myZZPagIg4AfhGZi6ut38DPDMzH+42/+Dg4K3AjX1soiRJklZPz5g/f/6TOydO+hho4B5gbtvtNUYKzwDdVkKSJEnql6kwhONiYGeAiNgC+NnkNkeSJEka2VTogf4msENEXALMAPae5PZIkiRJI5r0MdCSJEnSqmQqDOGQJEmSVhkGaEmSJKmBqTAGesJFxHuBhcBSYBnw/swcjIiTgJMz86wRHrcX8EVgi8y8vE6bBfwBODYzDx/hcYcDNwOXAa/IzCMmcn16KSIOAvYHNs7MBzruuwFYkpmL2qYdAHwyM2fUOp+bmVd0We4C4C2Z+ZoetXu55UfER4FrM/OkFXl8nX5enX7tOJYx4vqP1yjv1aOBozLzNw2WtYBx1rzO+3Xgmvq8jwO+kpmfqtvJi4A76n0z63J/3rGMTYCPA2sBawNnAocD2463HeNo5w3Aczvfm73UUZsZwCzg6Mz8esd8J9GxP6n7gn8Gfk+p2x+BN2Tmvf1oey+MUI83dm4j7a9VRGwInA18PDO/3NcG90CX7WUd4FfA6zLzwS7zH0c5jrxwjOWexzj3N22POS0zdxt/6yfOGMfWUfcZtYbfAp6fmb+t05rsszcEPpCZ/zqR67SiRjsGAU8GdgGeADyV8r4B+IfMfKTOeypwZWZ+tN5eGxgEXp2ZPxnH818GvCYzb5iodVoR49k2ImJ34AvAszPz92Msa7zHsDmU985GI9z/d/Q4j027AB0RzwNeAWyVmctqEf+bcqnw8bgWeC1web29E3D3eB6YmVcBVzVr8aR7HXAy8BrgpC73/1VErJ+Zt9XbOwN3Agxv+KurlV3/0d6rmbn/RLRxDOcO76giYgDIiPifet+Bw8EwIhYB/w48etCOiCdQ3je7ZeYvI2JN4BTgXyjb0KquvTZrA+dHxC/qNj6WozLzs/WxH6bU5BO9a2pftNfjpZT1eVm3GSPiLykfpj6Qmd/qXxN77tyOsPRVyvZ7avtMEbEWsDun0agAAA3jSURBVBVwdUQsyMzzJrIRkxiexzq2jrrPqB4EvhgRO2Rmox9gZebNwJQIz2PJzP8A/mOMQPgWYDAivpOZ11C2qc+PJzxPQWNtG/sAnwLeTOlk6bl+5LFpF6ApPT5PB94YEWdl5lURsVmDxy8GdoyINTJzKSVMf234zoj4COVqiXMpvbN7t923gLqxRMQvKafoC+AW4P8Bs4EvUT6R/hbYJjOfGhHbAofVxawF7JmZv1iBdW+ktvd64LPAl+keoE8BXgUcFxHPrfP/TX38SZQQ9av62IeAh4E962OfHRGLgQ2A0zPz8NrjcivwREpNjqd8Sl8fOD4zj5uA9VoT+BzwNGA9YHFmHlrbu1799x+1fd+rt4/LzBPrIg6LiL8AHk95/W8cZXknA5cAJ3SuR13Xq2q91gFelZntFwEa8b063DNF+WCzca3hM4B3Zeb3IuJlwBGUD3d3Aj8FzqNLzcdZtrnAI5TXr9OTgPs6pu1K2Wn+EiAzH4mIPSkHyC27taPb+5xyQLwoM0+tr8VZmfmf9QJLXxh+soj4G+AoyrCzJwDvyMxLxrluKyUz74uIzwH/RPMd8hOBHwFExI2UDxdLKO+Xx6wP5b3zj8P7lIj4MbAjsAPlW6Ih4JfAmzPzoZVcrZXxROCGEe57OqWX8R2Z+X149Ju952bme9t7jep7/CeU7eM+4ELK+j4BeCnl/TjSdjW8D9lxuEevnyJiNvAUamdCh1cD51COJW+jbJdExJHA9pTX/GuZeXSdv3N/cxTwocy8MiISeG9mfjMizqacpWowMzccx/5lojU5tnbbZwCcS1n//YBj2+/odmyt3+hsSfmG603AFzNzi4j4KXA+8AJKr+eumXl3XcY29TmOysxTVmqNeygzb4uItwEnRMT7gGcBbwUYKRPU99BOlPywfp33r4DjgDmU49MRlGPy0Zm5fZ3nDODQzPxxr9erc9uIiI0p74ePAD+KiCPHs/+qtdmN8o3X3fXv2cBXKNv+dW3zPh84hvIN2e3AG4EX0spjyy2r2zdHTU27MdC1p/QVlB6ASyPiWkboKRnBg8ClwLYRMZeyY7oJICLWAe7MzB0oG/UWtbelm2dS3rAvpnydsynl09evM3Mryqewv6jzbgLsUd/s36EE1n7YBzghMxMYiojNu8zzNcoBAWAPypu30w6Ur54WAkdS3txQNuhXAltTDiTDvpqZCyk7jJMz86WU1+iAhu3fPiLOG/5H+eocStC9LDN3pFwq/q1tjzk3M7ekbNyzgJfX9h0UEcMX6flufS0WU0LTaMsD+OtR1uOKuq7/Rzk4PqrBe3UoyzCadwLvqh8QjgEWZeZ2wJ/b5h2p5t0M1+9cyuv69swcPuh9vN53DmWHfVDHY59K2Um3r899bTulbu3o9j4/DVgUEY+jBKWFETGD8nXwpW2L3wR4d63lUfT/dJe3UA9Y43BArd1PKYFweD2eBvxz/Xah2/p8F3hxRDw+IjalfFh9BPggsH1mvgS4i9Kj3W/D75VLKR9sTh1hvlMp78cNxrncKzLzH4AB4P66b72GMgxotO3qq5m5sM/hebgG11A+FH0zM8/pMt8+lOD/feCFbceIPSn7qG147Dbbub8Z3iY2Bh6gnOZ1XWBOZv6u47lG3L9MtHHsr8baZwx7K2U/9uzhCWMcW5fUfXZ7zdahfAjZFvgdpV6LKEMRtwK2Aw6u35T127h71jPzdMqH6pOAvdp65ZfbV9ZOhG0oWWJPWhegey5lWOUOlH3tfpn5U+BxEfGMiHgKsH6Pw/No28abgC9k5t2UfeGY36BExBqUDwMLM3NryrF6U2Av4OrM3IbSqTXseMp6L6B8+3XgOJa10qZdD3RE/DVwT2a+sd7+e+DMiPhBg8V8lbIzejplZza7Tv8zsEFEfI3y6XptyovRzW1Zx3lRPi3OAeYBZwFk5rURcWu9/3fAMRFxH/CXlJ7rnoqIJ1KGY2wQEW8H1qVsfJd3zPpbYEZEPI2y4zy0y+JOpOwsz6J8unt/nX51Zg7V52vv2cz6/83A/hGxG+WKlCPVciSdXxsND6m4A9g0Iraryx3o8txQQvHwGK1rgI3q9MG29m04xvLGWo/hndZv67Ie1eC92r6MOZQPZPdk5i11+oVtyx6p5t08pn4dHv06dgQ3UkJu+/psTAmJI7Wj2/v8IuC/KAe8b1ACxNbApfVrYtoee2hE/Jly4LhnjHWbaM8AbqpBf1m2xmR3O1i2D+F4E+Vr7oWUfcLtdZ7l1qf24p9KOcC8mHJQeCbw82yNob6A0jvbb+1DOIISoP4yM//cMd8bKR82Lo6IH+XyY3tndNz+Uf3/LlrjRO+kvM9H267at+N+Obf2Zq1HCay/7pwhIuZReoQ/WScto3yTdCjl26SPULbVxW0P69zfnA58G7gN+Bjlg8OiOr3TiPuXiTaO/dVY+wwAMvP2iNifEhqHj3WjHVtHeq0794tPB+bXzhTq459BeW/1wp9Z/liwNo8N+uPxJWCtjg9H3faVm1DGTC8F7omI4YvO/QE4pO5rltGq24mUoD1E+W1XL3XdNmpnzx7AryPi5ZSe6LcB/zv8wBpw59aADWX/ujQiHgS+VmvwV3W9NqGVoS6PiOGe7HnAZ+rxYhbw6Df4oyxrpU27HmjKVzrHRfmqEEoh76b05IzXecAWlB6y9p6WRcDTMvO1lJD4OJY/IAzrdmC9mnJgJCKeRatH6wRg78zci/Ljo5GWOZH2AE7MzJdm5k7A5sBL23ph251MOSBcmt3Hre0KXFh7kk6h1fMw0ifxpfX/99Rl7lEfN1HrvRdwV2a+rrZ7rdqr2f7cUHqHZkbE4ykb4PUjtHu05Y21HqP1Roz3vdq5jD8Cc9teqy3G+XwT6Qxgp/o+Hv6x7VHU4T0jtGO593k9GFxJ6TE4mxKoP0754NruGOCwzHwD5Wql/dhGAKjfRO1LeW0/RKun76mU12I0v6H1Abz9vTfS+pwIvJ7ymg4fiJ5X36NQemZ7PrxrDLeMct/VtePgAOCU+oHjAcpXutDxoYvR36+jbVdLuz+k9+qHoD0oX70/pePufYCDM3Onul/dnjLkYYByPHltnbZXRDyjPuYxNcjMO4H7gd0pYeE3lCE8ndvEco/tsYk4tgKP9rwmZd8Kox9bR3qtO9f9WuAHtRdye8oP237V+aAJtIRyDHkKPPqjtm1ofShcGd0yQQKbRcQadX/wvDrvvwNfyszXAz+gVbeTKd8Q7EbbMNRe6rJt7Az8MDO3q9vEZsBfRMQL2h62CaWXHeo+td7/yszcHXg7JavOoLzGwxnqhTz2Q9ae9bU/kPJtHnW+kZa10qZdgM7M0ygB+PKIuBj4HvBvbZ9ujomIK+u/bsMRqAf1/6N8pdje03UF8Mwov349lbJxPrVB804ENoqICyhDOIZ7sf6nrb1zGy5zRe1TnxeAzLyf0gO4b5d5T6F8HT/Sr+mvBI6MiAspvS2fGmcbTgfeGREXUQ4QD9cDzco6B9g5ytUtj6OMG+1W0wcoPUHnAYdn5h0ruLwVWo9xvFdHetxSyqf4MyPi+5Sel76Oia3bxRuA42uPz2WU8ayjjWEf6X1+GuUDzE8oNXg2ZXxjuy8D367vsefQ+21k+CvJcygfFg6rQ50+B7y5bsPX0H1M9PAQju9Thl+8u8s8XdcnM4d7Nb+VmUvr1+aHAT+o+531Gb3GvdJej7OBA7r0Pj8qM0+lfJv1GUoI3KhuH69m/N8e9Gr/sNKy/OjrmPoPeHTs52to613Lchadn1B+73EH5f1yLqWGo51h59uUXsk7KNvE4zLz+lHm77kV3V+NYn9avbUre2yF8n65r25Tg5SezJ6d/abuAw8AvlvfoxcAn8rM60Z/5Lgst6/M8qO4U4AfUsLx8If3Uyi55kLKcMr1a/vuo7z3runIMT3VsW3sS1vOqE6gbXhhZv6M0kN9MWW4xyco45v/FBFXUrLYHyjvh08Df1nrvR+ldx3KsKAv1Rp8lPKboGEjLWuleSXCPoqILYG1M/PsKOO/zsrMZ012u7Ri6gewEzPz3El47vdRhgoMRcSXgbMz80v9bockSVNNROwAvD4z9xxz5hU07cZAT3G/oozDOYzy1cN+k9weraAaYJ9Haxxev90LXBYR91POiPC/o88uSdL0FxHzKT3ZR/byeeyBliRJkhqYdmOgJUmSpF4yQEuSJEkNGKAlSZKkBgzQkrQKiYi9onXRoJVZzs0T0R5JWh0ZoCVJkqQGPI2dJK16XlwvarIO5aJMD1KukvgAcDvlktonAR/KzCsjIoH3ZuY3I+JsYO/hBUXE8ykXPZjR9tgXUi4j/SDw+czsvBiCJK3W7IGWpFXPn4CFwC7AscDngd0yc1vKVRwPoVzhcVFEbEwJ1jtExLrAnMz8Xduyjgf2q5fBPZNyKVzqfFsbniVpefZAS9Kq56LMXAb8sV5Mh7ZQfAHwYcpFBL4N3EbpTT4AWES55HG7ecBnIgLKBZ5+UadnL1dAklZl9kBL0qpnU4CI2BCYA6wVEU+p920L/CIz7wTuB3YHzgJ+A+xP6Zlul8CetQf6QOC7dfrSXq6AJK3K7IGWpFXP4yLiXGBt4M2U8cunRcRS4E5grzrft4G9M/OOiPge8K+ZeX3Hst4KfCki1qy33wQ8tdcrIEmrMi/lLUmSJDXgEA5JkiSpAQO0JEmS1IABWpIkSWrAAC1JkiQ1YICWJEmSGjBAS5IkSQ0YoCVJkqQGDNCSJElSA/8fq42aIsCzILMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wickets = df2.dropna(subset=['dismissal_kind'])\n",
    "wickets = wickets[~wickets['dismissal_kind'].isin(['run out','retired hurt','obstructing the field'])]\n",
    "wicket_final = wickets.groupby('bowler')['dismissal_kind'].agg(['count']).reset_index().sort_values('count',ascending=False).head(10).reset_index(drop=True)\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.title('Leading wicket takers',fontsize=16)\n",
    "sns.barplot(x='bowler',y='count',data=wicket_final,palette='viridis')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "catch = wickets[~wickets['dismissal_kind'].isin(['run out','retired hurt','obstructing the field','bowled','lbw','stumped'])]\n",
    "catchers = catch.groupby('fielder')['dismissal_kind'].agg(['count']).reset_index().sort_values('count',ascending=False).head(10).reset_index(drop=True)\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.title('Most number of catches by player',fontsize=16)\n",
    "sns.barplot(x='fielder',y='count',data=catchers,palette='icefire')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stumping = wickets[~wickets['dismissal_kind'].isin(['run out','retired hurt','obstructing the field','bowled','lbw','caught','caught and bowled'])]\n",
    "most_stumpings = stumping.groupby('fielder')['dismissal_kind'].agg(['count']).reset_index().sort_values('count',ascending=False).head(5).reset_index(drop=True)\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.title('Most number of stumpings by player',fontsize=16)\n",
    "sns.barplot(x='fielder',y='count',data=most_stumpings,palette='mako')\n",
    "plt.xlabel('Wicket_keepers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 187\n",
       "Royal Challengers Bangalore    180\n",
       "Kolkata Knight Riders          178\n",
       "Kings XI Punjab                176\n",
       "Chennai Super Kings            164\n",
       "Delhi Daredevils               161\n",
       "Rajasthan Royals               147\n",
       "Sunrisers Hyderabad            108\n",
       "Deccan Chargers                 75\n",
       "Pune Warriors                   46\n",
       "Gujarat Lions                   30\n",
       "Rising Pune Supergiant          16\n",
       "Delhi Capitals                  16\n",
       "Rising Pune Supergiants         14\n",
       "Kochi Tuskers Kerala            14\n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = df1['team1'].value_counts()\n",
    "b = df1['team2'].value_counts()\n",
    "c = a.add(b).sort_values(ascending=False)\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "won = df1['winner'].value_counts()\n",
    "df3 = pd.concat([c,won],axis=1).reset_index()\n",
    "df3.columns=['Team','Matches_played','Matches_won']\n",
    "for i in range(0,len(df3)):\n",
    "    df3['win_percentage'] = (df3['Matches_won']/df3['Matches_played'])*100\n",
    "win_percent = df3.sort_values(by='win_percentage',ascending=False)"
   ]
  },
  {
   "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>Team</th>\n",
       "      <th>Matches_played</th>\n",
       "      <th>Matches_won</th>\n",
       "      <th>win_percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>164</td>\n",
       "      <td>100</td>\n",
       "      <td>60.975610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>187</td>\n",
       "      <td>109</td>\n",
       "      <td>58.288770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>108</td>\n",
       "      <td>58</td>\n",
       "      <td>53.703704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>178</td>\n",
       "      <td>92</td>\n",
       "      <td>51.685393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>147</td>\n",
       "      <td>75</td>\n",
       "      <td>51.020408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>180</td>\n",
       "      <td>84</td>\n",
       "      <td>46.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>176</td>\n",
       "      <td>82</td>\n",
       "      <td>46.590909</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Team  Matches_played  Matches_won  win_percentage\n",
       "0          Chennai Super Kings             164          100       60.975610\n",
       "1               Mumbai Indians             187          109       58.288770\n",
       "2          Sunrisers Hyderabad             108           58       53.703704\n",
       "3        Kolkata Knight Riders             178           92       51.685393\n",
       "4             Rajasthan Royals             147           75       51.020408\n",
       "5  Royal Challengers Bangalore             180           84       46.666667\n",
       "6              Kings XI Punjab             176           82       46.590909"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_win_percent = win_percent[2:9].reset_index(drop=True)\n",
    "team_win_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.title('Win percentage of current teams',fontsize=16)\n",
    "plt.xticks(rotation=50)\n",
    "sns.barplot(x='Team',y='win_percentage',data=team_win_percent,palette='viridis',hue='win_percentage')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,6))\n",
    "plt.title('Team victory per seasons',fontsize=16)\n",
    "plt.xticks(rotation=50)\n",
    "sns.violinplot(x=\"winner\",y=\"season\",data=df1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>winner</th>\n",
       "      <th>matches_won</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   season               winner  matches_won\n",
       "0    2008       Mumbai Indians            7\n",
       "1    2008  Chennai Super Kings            9\n",
       "2    2009       Mumbai Indians            5\n",
       "3    2009  Chennai Super Kings            8\n",
       "4    2010       Mumbai Indians           11"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = df1[(df1['winner']=='Chennai Super Kings') | (df1['winner']=='Mumbai Indians')]\n",
    "team_results = result.groupby('season')['winner'].value_counts().sort_values()\n",
    "dff = pd.DataFrame(team_results)\n",
    "dff.columns=['matches_won']\n",
    "csk_mi_result = dff.reset_index().sort_values(by='season').reset_index(drop=True)\n",
    "csk_mi_result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.title('CSK vs MI Comparison over the seasons',fontsize=16)\n",
    "sns.lineplot(x='season',y='matches_won',data=csk_mi_result,hue='winner')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.title('CSK vs MI Comparison over the seasons',fontsize=16)\n",
    "sns.boxplot(x='winner',y='season',data=csk_mi_result)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "hovertemplate": "season=2008<br>winner=%{x}<br>matches_won=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#636efa",
          "pattern": {
           "shape": ""
          }
         },
         "name": "",
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "textposition": "auto",
         "type": "bar",
         "x": [
          "Mumbai Indians",
          "Chennai Super Kings"
         ],
         "xaxis": "x",
         "y": [
          7,
          9
         ],
         "yaxis": "y"
        }
       ],
       "frames": [
        {
         "data": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.bar(csk_mi_result, x=\"winner\", y=\"matches_won\",\n",
    "  animation_frame=\"season\", range_y=[0,15])\n",
    "fig.update_layout(title_text='Comparison between matches won by MI and CSK per season')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "batting_records = pd.read_csv('most_runs_average_strikerate.csv')\n",
    "average = batting_records.sort_values(by='average',ascending=False)\n",
    "strikerate = batting_records.sort_values(by='strikerate',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>batsman</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>out</th>\n",
       "      <th>numberofballs</th>\n",
       "      <th>average</th>\n",
       "      <th>strikerate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>V Kohli</td>\n",
       "      <td>5426</td>\n",
       "      <td>152</td>\n",
       "      <td>4111</td>\n",
       "      <td>35.697368</td>\n",
       "      <td>131.987351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SK Raina</td>\n",
       "      <td>5386</td>\n",
       "      <td>160</td>\n",
       "      <td>3916</td>\n",
       "      <td>33.662500</td>\n",
       "      <td>137.538304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>4902</td>\n",
       "      <td>161</td>\n",
       "      <td>3742</td>\n",
       "      <td>30.447205</td>\n",
       "      <td>130.999466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>4601</td>\n",
       "      <td>137</td>\n",
       "      <td>3665</td>\n",
       "      <td>33.583942</td>\n",
       "      <td>125.538881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>G Gambhir</td>\n",
       "      <td>4219</td>\n",
       "      <td>134</td>\n",
       "      <td>3400</td>\n",
       "      <td>31.485075</td>\n",
       "      <td>124.088235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RV Uthappa</td>\n",
       "      <td>4420</td>\n",
       "      <td>156</td>\n",
       "      <td>3381</td>\n",
       "      <td>28.333333</td>\n",
       "      <td>130.730553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DA Warner</td>\n",
       "      <td>4717</td>\n",
       "      <td>114</td>\n",
       "      <td>3292</td>\n",
       "      <td>41.377193</td>\n",
       "      <td>143.286756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>4450</td>\n",
       "      <td>118</td>\n",
       "      <td>3206</td>\n",
       "      <td>37.711864</td>\n",
       "      <td>138.802246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>3834</td>\n",
       "      <td>117</td>\n",
       "      <td>3133</td>\n",
       "      <td>32.769231</td>\n",
       "      <td>122.374721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>4525</td>\n",
       "      <td>110</td>\n",
       "      <td>2972</td>\n",
       "      <td>41.136364</td>\n",
       "      <td>152.254374</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      batsman  total_runs  out  numberofballs    average  strikerate\n",
       "0     V Kohli        5426  152           4111  35.697368  131.987351\n",
       "1    SK Raina        5386  160           3916  33.662500  137.538304\n",
       "2   RG Sharma        4902  161           3742  30.447205  130.999466\n",
       "3    S Dhawan        4601  137           3665  33.583942  125.538881\n",
       "4   G Gambhir        4219  134           3400  31.485075  124.088235\n",
       "5  RV Uthappa        4420  156           3381  28.333333  130.730553\n",
       "6   DA Warner        4717  114           3292  41.377193  143.286756\n",
       "7    MS Dhoni        4450  118           3206  37.711864  138.802246\n",
       "8   AM Rahane        3834  117           3133  32.769231  122.374721\n",
       "9    CH Gayle        4525  110           2972  41.136364  152.254374"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Top_players = strikerate.reset_index(drop=True).sort_values(by='numberofballs',ascending=False).head(10).reset_index(drop=True)\n",
    "Top_players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.title('Top Batsman as per strikerate',fontsize=16)\n",
    "sns.barplot(x='batsman',y='strikerate',data=Top_players,palette='viridis')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.title('Top Batsman as per average',fontsize=16)\n",
    "sns.barplot(x='batsman',y='average',data=Top_players,palette='rocket')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Conclusions **"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Find out the most successful teams, players and factors \n",
    "contributing win or loss of a team </h4>\n",
    "<h6>Most Successful Teams</h6>\n",
    "\n",
    "<ul><li>Most successful team wrt number of cups : Mumbai Indians<br>\n",
    "<li>Most successful team wrt win percentage : Chennai Super kings<br>\n",
    "<li>Most successful team wrt most number of wins : Royal challengers Bangalore<br></ul>\n",
    "\n",
    "<h6>Most Successful Players</h6>\n",
    "\n",
    "*Batsman*<br>\n",
    "<ul><li>Most successful player wrt most man of the matches : Chris Gayle<br>\n",
    "<li>Most successful player wrt most runs : Virat Kohli<br>\n",
    "<li>Most successful player wrt average : David Warner<br></ul>\n",
    "\n",
    "\n",
    "*Fielding*<br>\n",
    "<ul><li>Most wicket Taker : SL Malinga<br>\n",
    "<li>Most number of catches : Dinesh Kartik<br>\n",
    "<li>Most stumpings : MS Dhoni<br></ul>\n",
    "\n",
    "<h6>Factors Contributing win or loss</h6>\n",
    "<ul><li>There is a high probability of toss winners winning the match\n",
    "<li>The Teams Fielding first have won most number of matches\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Suggest teams or players a company should endorse for its products</h4>\n",
    "\n",
    "I would suggest the following, <br>\n",
    "<ul><li><h6>Team:</h6> Chennai Super Kings (Based on the comparison of CSK vs MI) \n",
    "<li><h6>Player:</h6> \n",
    "    <ul><li>Batsman: Chris Gayle/ Virat Kohli (c)\n",
    "        <li>Bowler: SL Malinga\n",
    "        <li>Wicket Keeper: MS Dhoni (c)\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " *** Thank You! ***"
   ]
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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