Exploratory Data Analysis - IPL(2008-2019).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis - IPL(2008-2019)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main objection of this is to find out the most successful teams, players and factors contributing win or loss of a team. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Importing Libraries**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- *Numpy*\n",
    "- *Pandas*\n",
    "- *Matplotlib*\n",
    "- *Seaborn* \n",
    "- *Plotly*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Importing Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches = pd.read_csv(\"matches.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Understanding Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <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",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05/05/19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>07/05/19</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>08/05/19</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>10/05/19</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>Sundaram Ravi</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>Chettithody Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12/05/19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city      date                  team1  \\\n",
       "751  11347    2019         Mumbai  05/05/19  Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai  07/05/19    Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam  08/05/19    Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam  10/05/19         Delhi Capitals   \n",
       "755  11415    2019      Hyderabad  12/05/19         Mumbai Indians   \n",
       "\n",
       "                   team2          toss_winner toss_decision  result  \\\n",
       "751       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "752       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "753       Delhi Capitals       Delhi Capitals         field  normal   \n",
       "754  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "755  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "\n",
       "     dl_applied               winner  win_by_runs  win_by_wickets  \\\n",
       "751           0       Mumbai Indians            0               9   \n",
       "752           0       Mumbai Indians            0               6   \n",
       "753           0       Delhi Capitals            0               2   \n",
       "754           0  Chennai Super Kings            0               6   \n",
       "755           0       Mumbai Indians            1               0   \n",
       "\n",
       "    player_of_match                               venue        umpire1  \\\n",
       "751       HH Pandya                    Wankhede Stadium  Nanda Kishore   \n",
       "752        AS Yadav           M. A. Chidambaram Stadium    Nigel Llong   \n",
       "753         RR Pant                    ACA-VDCA Stadium            NaN   \n",
       "754    F du Plessis                    ACA-VDCA Stadium  Sundaram Ravi   \n",
       "755       JJ Bumrah  Rajiv Gandhi Intl. Cricket Stadium    Nitin Menon   \n",
       "\n",
       "            umpire2                  umpire3  \n",
       "751        O Nandan                   S Ravi  \n",
       "752     Nitin Menon                Ian Gould  \n",
       "753             NaN                      NaN  \n",
       "754  Bruce Oxenford  Chettithody Shamshuddin  \n",
       "755       Ian Gould              Nigel Llong  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
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   ],
   "source": [
    "matches.tail()"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
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    {
     "data": {
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       "<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>dl_applied</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1792.178571</td>\n",
       "      <td>2013.444444</td>\n",
       "      <td>0.025132</td>\n",
       "      <td>13.283069</td>\n",
       "      <td>3.350529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3464.478148</td>\n",
       "      <td>3.366895</td>\n",
       "      <td>0.156630</td>\n",
       "      <td>23.471144</td>\n",
       "      <td>3.387963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>189.750000</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>378.500000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>567.250000</td>\n",
       "      <td>2016.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11415.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id       season  dl_applied  win_by_runs  win_by_wickets\n",
       "count    756.000000   756.000000  756.000000   756.000000      756.000000\n",
       "mean    1792.178571  2013.444444    0.025132    13.283069        3.350529\n",
       "std     3464.478148     3.366895    0.156630    23.471144        3.387963\n",
       "min        1.000000  2008.000000    0.000000     0.000000        0.000000\n",
       "25%      189.750000  2011.000000    0.000000     0.000000        0.000000\n",
       "50%      378.500000  2013.000000    0.000000     0.000000        4.000000\n",
       "75%      567.250000  2016.000000    0.000000    19.000000        6.000000\n",
       "max    11415.000000  2019.000000    1.000000   146.000000       10.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Cleaning Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                 756\n",
       "season             756\n",
       "city               756\n",
       "date               756\n",
       "team1              756\n",
       "team2              756\n",
       "toss_winner        756\n",
       "toss_decision      756\n",
       "result             756\n",
       "dl_applied         756\n",
       "winner             756\n",
       "win_by_runs        756\n",
       "win_by_wickets     756\n",
       "player_of_match    756\n",
       "venue              756\n",
       "umpire1            756\n",
       "umpire2            756\n",
       "umpire3            756\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.isna().count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches.drop(['umpire1','umpire2','umpire3'],axis=1,inplace=True) #dropping which is not relevant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05/05/19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>07/05/19</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>08/05/19</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>10/05/19</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12/05/19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 15 columns</p>\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",
       "751  11347    2019         Mumbai    05/05/19        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai    07/05/19          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam    08/05/19          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam    10/05/19               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad    12/05/19               Mumbai Indians   \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",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           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",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \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",
       "751               9       HH Pandya                           Wankhede Stadium  \n",
       "752               6        AS Yadav                  M. A. Chidambaram Stadium  \n",
       "753               2         RR Pant                           ACA-VDCA Stadium  \n",
       "754               6    F du Plessis                           ACA-VDCA Stadium  \n",
       "755               0       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium  \n",
       "\n",
       "[756 rows x 15 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**PLAYER OF MATCHES**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CH Gayle           21\n",
       "AB de Villiers     20\n",
       "DA Warner          17\n",
       "MS Dhoni           17\n",
       "RG Sharma          17\n",
       "                   ..\n",
       "MS Bisla            1\n",
       "MA Starc            1\n",
       "EJG Morgan          1\n",
       "KMDN Kulasekara     1\n",
       "J Theron            1\n",
       "Name: player_of_match, Length: 226, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['player_of_match'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CH Gayle          21\n",
       "AB de Villiers    20\n",
       "DA Warner         17\n",
       "MS Dhoni          17\n",
       "RG Sharma         17\n",
       "Name: player_of_match, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['player_of_match'].value_counts()[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_player_of_matches=(matches['player_of_match'].value_counts()[0:5]).to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_player_of_matches=top_player_of_matches['player_of_match']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='player_of_match'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(top_player_of_matches.keys(), top_player_of_matches)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Toss Effects**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_wins = matches['toss_winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 98\n",
       "Kolkata Knight Riders          92\n",
       "Chennai Super Kings            89\n",
       "Royal Challengers Bangalore    81\n",
       "Kings XI Punjab                81\n",
       "Name: toss_winner, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toss_wins.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='toss_winner'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(toss_wins, toss_wins.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_wins_matches = matches[matches['winner']==matches['toss_winner']]['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='winner'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(toss_wins_matches, toss_wins_matches.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results(Results, Tie or No Result)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "ipl_results=matches['result'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "normal       743\n",
       "tie            9\n",
       "no result      4\n",
       "Name: result, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Batting First and Bowling First**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "win_batting_first=matches[matches['win_by_runs']!=0].count()['win_by_runs']\n",
    "win_bowling_first=matches[matches['win_by_wickets']!=0].count()['win_by_wickets']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_matches=ipl_results.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "337"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batting_first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "756"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_bowling_first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "win={'Type':['Batting First','Batting Second','Tie','No Result'], 'Wins':[win_batting_first, win_bowling_first,\n",
    "                                                                          ipl_results[1], ipl_results[2]]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "win=pd.DataFrame(win)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>Type</th>\n",
       "      <th>Wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Batting First</td>\n",
       "      <td>337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Batting Second</td>\n",
       "      <td>406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tie</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>No Result</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Type  Wins\n",
       "0   Batting First   337\n",
       "1  Batting Second   406\n",
       "2             Tie     9\n",
       "3       No Result     4"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Type', ylabel='Wins'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot('Type', 'Wins', data = win)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Duckworth–Lewis–Stern method**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl=matches[matches['dl_applied']!=0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\frame.py:4163: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().drop(\n"
     ]
    }
   ],
   "source": [
    "dl.drop(['id', 'city', 'date','player_of_match','venue','result','season','dl_applied'],axis=1, inplace = True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>field</td>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>597</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>field</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>bat</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>field</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>625</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>641</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>667</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           team1                        team2  \\\n",
       "56           Sunrisers Hyderabad        Kolkata Knight Riders   \n",
       "99              Delhi Daredevils              Kings XI Punjab   \n",
       "102        Kolkata Knight Riders          Chennai Super Kings   \n",
       "119              Kings XI Punjab             Delhi Daredevils   \n",
       "122              Kings XI Punjab        Kolkata Knight Riders   \n",
       "148          Chennai Super Kings              Kings XI Punjab   \n",
       "251          Chennai Super Kings         Kochi Tuskers Kerala   \n",
       "280          Chennai Super Kings        Kolkata Knight Riders   \n",
       "290        Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "488             Delhi Daredevils          Sunrisers Hyderabad   \n",
       "536          Sunrisers Hyderabad        Kolkata Knight Riders   \n",
       "567          Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "597          Sunrisers Hyderabad      Rising Pune Supergiants   \n",
       "620      Rising Pune Supergiants        Kolkata Knight Riders   \n",
       "624             Delhi Daredevils      Rising Pune Supergiants   \n",
       "625  Royal Challengers Bangalore              Kings XI Punjab   \n",
       "641             Rajasthan Royals             Delhi Daredevils   \n",
       "653        Kolkata Knight Riders              Kings XI Punjab   \n",
       "667             Delhi Daredevils             Rajasthan Royals   \n",
       "\n",
       "                     toss_winner toss_decision                       winner  \\\n",
       "56         Kolkata Knight Riders         field        Kolkata Knight Riders   \n",
       "99              Delhi Daredevils           bat              Kings XI Punjab   \n",
       "102        Kolkata Knight Riders           bat          Chennai Super Kings   \n",
       "119             Delhi Daredevils         field             Delhi Daredevils   \n",
       "122        Kolkata Knight Riders         field        Kolkata Knight Riders   \n",
       "148          Chennai Super Kings           bat          Chennai Super Kings   \n",
       "251         Kochi Tuskers Kerala         field         Kochi Tuskers Kerala   \n",
       "280          Chennai Super Kings           bat        Kolkata Knight Riders   \n",
       "290  Royal Challengers Bangalore         field  Royal Challengers Bangalore   \n",
       "488          Sunrisers Hyderabad         field          Sunrisers Hyderabad   \n",
       "536        Kolkata Knight Riders         field          Sunrisers Hyderabad   \n",
       "567          Sunrisers Hyderabad           bat  Royal Challengers Bangalore   \n",
       "597      Rising Pune Supergiants         field      Rising Pune Supergiants   \n",
       "620      Rising Pune Supergiants           bat        Kolkata Knight Riders   \n",
       "624      Rising Pune Supergiants         field      Rising Pune Supergiants   \n",
       "625              Kings XI Punjab         field  Royal Challengers Bangalore   \n",
       "641             Delhi Daredevils         field             Rajasthan Royals   \n",
       "653              Kings XI Punjab         field              Kings XI Punjab   \n",
       "667             Rajasthan Royals         field             Delhi Daredevils   \n",
       "\n",
       "     win_by_runs  win_by_wickets  \n",
       "56             0               7  \n",
       "99             6               0  \n",
       "102            3               0  \n",
       "119            0              10  \n",
       "122           11               0  \n",
       "148           12               0  \n",
       "251            0               7  \n",
       "280           10               0  \n",
       "290            0               4  \n",
       "488            0               8  \n",
       "536           16               0  \n",
       "567            0               6  \n",
       "597           34               0  \n",
       "620            0               8  \n",
       "624           19               0  \n",
       "625           82               0  \n",
       "641           10               0  \n",
       "653            0               9  \n",
       "667            4               0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl_win_by_runs=dl[dl['win_by_runs']!=0].count()['win_by_runs']\n",
    "dl_win_by_wickets=dl[dl['win_by_wickets']!=0].count()['win_by_wickets']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl_win=pd.DataFrame({'Type':['Batting First','Batting Second'], 'Wins':[dl_win_by_runs, dl_win_by_wickets]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Type', ylabel='Wins'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot('Type','Wins', data = dl_win)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Total Matches Each**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_matches_each = matches['team1'].value_counts() + matches['team2'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(total_matches_each, total_matches_each.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Total Wins Each**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches_won_each = matches['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 109\n",
       "Chennai Super Kings            100\n",
       "Kolkata Knight Riders           92\n",
       "Royal Challengers Bangalore     84\n",
       "Kings XI Punjab                 82\n",
       "Rajasthan Royals                75\n",
       "Delhi Daredevils                67\n",
       "Sunrisers Hyderabad             58\n",
       "Deccan Chargers                 29\n",
       "Gujarat Lions                   13\n",
       "Pune Warriors                   12\n",
       "Rising Pune Supergiant          10\n",
       "Delhi Capitals                  10\n",
       "Kochi Tuskers Kerala             6\n",
       "Rising Pune Supergiants          5\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_won_each"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='winner'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(matches_won_each, matches_won_each.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Win Percent**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "win_percent = matches_won_each/total_matches_each*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Chennai Super Kings            60.975610\n",
       "Deccan Chargers                38.666667\n",
       "Delhi Capitals                 62.500000\n",
       "Delhi Daredevils               41.614907\n",
       "Gujarat Lions                  43.333333\n",
       "Kings XI Punjab                46.590909\n",
       "Kochi Tuskers Kerala           42.857143\n",
       "Kolkata Knight Riders          51.685393\n",
       "Mumbai Indians                 58.288770\n",
       "Pune Warriors                  26.086957\n",
       "Rajasthan Royals               51.020408\n",
       "Rising Pune Supergiant         62.500000\n",
       "Rising Pune Supergiants        35.714286\n",
       "Royal Challengers Bangalore    46.666667\n",
       "Sunrisers Hyderabad            53.703704\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iXpc0ENiFdHvgAOArbVyemZk1iO+Z10DdEGda4Zx9SD3hv+Ws8L7AtNyQb0fq5VdyC/CVvD+SVssP8N1Nuv++eP6QsCekoXzgGUn75/LKjXLpvv0Y4A/ADRHxYRv1dQSqmVmTuGdeXTPiTAHuysdcCLgOOCWvHwFcL2kKKcP88Uo7R8Stkj4B3J+HzWcCX4qI8ZKuACaRRhfGFHY7GDhHKRK1N/DXXA7SUPtVwNB26u0IVDOzJnEEqjVF/35949QTt2x2NczmC57OdcEhR6BaT7LsCuv5PyAzswbxPXMzM7MW58bczMysxXmY3Zpi2mtPccaIXZpdDbMFxtEH39J+IWtZ7pmbmZm1ODfmXUTSypIuk/R0nvP8fkn71LBfxUS1DtbhMEmrVtlWaX71VSVd3Yhzm5lZ93Fj3gXy98T/BtwdEetExGDSdKirt7dvROweEdPrONfCbWw+DKjYmFc59wsRsV/7Jc3MrCdxY941tgfei4hzSysi4tmI+CPMm3Uu6QZJQ/Py7EQ1SX/LvfpHckhJqfxMSb+RNAnYUtIJOSXtYUnD8yxu+wFDgBFKueyLt1dpzZ3Hvpiki3IC2oQ861yp7teqLA3OqWlmZs3jB+C6xoakVLLO+kpEvJYb4jGSromIV4ElgQcj4nuQQlwi4qd5+S/AHhFxtaT/AY6NiLEdOPdRQETExpIGALdK+njeNoiyNDhSmlybqWlmZtY13DPvBpLOkjRJ0pj2S8/l6Nz7fgBYg5R+Bim05ZpCue0kPZinet2e9GGis7YBLgWIiMeBZ4FSY35HRMyIiHeAUhrc7NQ0SbsCb5QfUNIwSWMljZ35xnsNqKKZmYEb867yCIWgkYg4CtiBlHoGaa734ns/T7h3HnbfEdgyIgaSIk1L5d4phZ5IWowUyLJfRGwMnF/peA02TxpcDoMZCIwipaZdUL5TRAyPiCERMaTP0ot0cRXNzBYcbsy7xp3AYpK+UVi3RGF5KjBI0kKS1gC2qHCMvsDrEfF2Hub+VJVzlRruV3JSWvEBtjdJOeYdcQ8pgIU8vL4m8ES1wk5NMzNrHt8z7wIREZI+B/xO0g9IqWpvAT/MRUYDz5CGqB9j3vvrAdwMHCnpMVIj+kCVc02XdD7wMPAic6ehXQycK2kWqYc/q2z38yT9Pi8/BxxU2HY2KUltCmkk4bCIeDcnsVXi1DQzsyZxaloPkr9mNg34WES83+z6dKU11+kbx55SbbDBzBrNM8DNH5ya1hoeAS6Y3xtygJWWW8//uZiZNYgb8x4kIgY0uw5mZtZ6/ACcmZlZi3PP3Jpi6vSnOPy6XZtdDTOrw0X73NzsKlgV7pmbmZm1ODfmZmZmLc6NeR0kzSws7y7pSUlrSTpS0iFdeN4zJJ1QeH2cpLPy8jxRpoX1z+SQlfGStuzE+e9rZ/vsgBYzM+t+vmfeAZJ2AM4AdomIZ4Fz29mls44HJkq6NL8+ghR00p7v58CVnYHzgE06cvKI2Koj+5mZWfdwz7xOkj5Nmv98j4j4d153kqRj8/IoSadKeij33LfN65eQdKWkRyVdl4NRhtQSHRoRbwDHAWfmPyfUk3kO3A2sm+tRjFgdImlU4RouzPV/WtLRhWuemX/2kXRH7ulPkbR34Ry9JI2Q9JikqyUVp681M7Mu5Ma8PosCfwM+l5PEqukVEVsAxwAn5nXfJM21vgHwv8DgvH4QOTo0B6VcVOmAEXE5sCywdET8pc567wlMqaHcAGAX0lzxJ0rqXbb9HWCfiNgM2A74jebM77o+cHZEfIKUmPbN8oMXU9PecWqamVnDuDGvz/vAfcBX2yl3bf45DuiXl7cB/goQEQ8Dk/P6dqNDASStDqwCrJoDVWpxuqSJwLAa6gxwY0S8GxGvkKaVXbm8GsAvJE0GbifNx14q81xEjM7Ll5Kudy7F1LTFnJpmZtYwbszr8xFwALCFpJ+0Ua4UEfoh7TyXUEt0aPYHUi//Sub09tvz/YgYFBE75Q8QMHf8anlU6jzRpmXbDybFuA6OiEHAS4VjlE/y70n/zcy6iRvzOkXE28BngYMl1dLbLRlN+iCApA2AjfNyu9GhknYDVgL+DJwCfD4foyOmMmeIf9869+0LTIuI9yVtB6xV2LZm4Yn5LwL3drB+ZmZWJzfmHRARrwG7AsdL2qvG3c4GVpT0KPAzUqjKDNJQ9ag8HH4pZdGhkhYDfg98M5K3gO+THoTriJOBP0gaS+p916LUyx4BDMmxqIcAxecGngCOypGtywLndLB+ZmZWJ0egdpMcb9o7It6R1J90z3n9iOjRT4JJWh4YHxFrtVu4Dius2zf2PL3DX303sybwdK7N5wjU5lsCuCs/IS5ST7unN+Srku7l/7rRx+63zHr+j8HMrEHcmHeTiHgTmOfTVE8WES8AH292PczMrG2+Z25mZtbi3DO3pnhq+n/Z/bqfNbsaZvO9m/Y5vtlVsG7gnrmZmVmLm68a82qpZnUeo1oK2aqSri5bt3FOJZso6bVCStntdZyvyxPHGvG+VDluxffKzMy613w5zF4h1azT8sNg+5Wtm0KaWx1JFwM3RMTV8+zcRST1iogP6ihf9/siaeGIqPX76GZm1gTzVc8cqqaafTenkj0s6ZhC2UMkTZY0SVIxvOTTku7L6WH75bI196Bz8tiQvLyCpKl5ecOcpjYxn3e9sv3WkTRB0uaS+ku6WdI4SfdIGpDLXCzpXEkPAqdJ+kxhdGCCpKXqeF++VKjPefm78EiaKek3kiYBW0o6QdKY/P4NL4SrFI/fbhkzM+sa81vPvJRqNrSUaiZpMHA48EnS97sflPRP4D3S9KlbRcQrkpYrHGcVUlDIAGAk0Kje9pHAHyJihKRFgIXJQSWS1icFsRwWEZMk3QEcGRFPSfokaQa57fNxVs/1/lDS9cBRETE6B7C8U+G8ld6XTwAHAlvn6VnPJs29/mdgSeDBiPheLvtoRPw0L/8F2AO4vuwcZ9ZQxszMusD81jOvlGq2DXBdRLwVETNJiWbbkhrGq3JCWGmK1pK/RcRHEfEo8yaHdcb9wE8k/RBYKyJm5fUrAn8HDs4NeR9gK+CqPM3reaQPGCVXFYa+RwO/VcofX6bKsHul92UH0hztY/I5dgDWyds+BK4plN1OKX99Cul927DCOdoto0IE6ntvvFXhEGZm1hHzW2Nea6pZe4rpYR0ZLq6YTBYRlwF7AbOAmySVetozgP9jTmzoQsD0nHhW+vOJwvHfKhzzV8ARwOLA6NJwfJlK74uASwrHXz8iTsrb3il9WFCaG/5sYL+ct34+ZWlrtZTJdZ0dgbrI0ktWqKaZmXXE/NaYV0o1uwf4nKQlJC0J7JPX3QnsrzT3OGXD7J01lTnJZLMfmpO0DvB0RJxB6olvkje9l+t1iKQvRsQbwDOS9s/7SdLASieS1D8ipkTEqcAY0q2BeVR4X+4A9pO0Uj7OclWecC81yq/kEYNKT6/XUsbMzLrI/HbPHEhD5pJ2Be4Gvg1cDDyUN18QERMAJP0c+KekD4EJwGENqsKvgSslDQNuLKw/APiypPeBF4FfAEvnOr8laQ/gNqWvkh0MnCPpeKA36X76pArnOkYpjvQjUhLbP6pVqsL7cjxwq6SFSEPxRwHPlu0zXdL5wMO5zmMqHLfdMmZm1nWcmmZN0Xfd1WLr07/R7GqYzfc8A9z8RU5Ns55kvWVW8X8yZmYNMt/dMzczM1vQuDE3MzNrcR5mt6Z46vVX+Ow1FzS7GmbWA9247xHNrkLLcc/czMysxbkxNzMza3Et2ZirzkjPUnlJQyXdUMd5hkraqs66zXUOST/LgSmLtrHPXpJ+VM9xy7YdI2mJKttGSXpCKUxmjKRBhW03SVqmwj4nSTq2rfqYmVnP0ZKNeYnmRHru1qio0zJDSXOkd0ie8GVrYJ+IeLdauYgYmadl7ahjgIqNeXZwRAwkTbl6euG8u0fE9E6cF0hRrJ09hpmZdVzLNuZVIj0rRp1W2X9zpcjQ/pL2zCEhEyTdLmllSf1IKWffUYoI3bZSuTaO/z1gN2DPUqCKpKmSTpY0XtIUzYk1PUzSmXm5v6QH8vafFUchgD6Srpb0uKQReZrXo4FVgbsk3dXO23Y/sFqhjlMlrZCXj8sjHPcC6xfKNDSK1czMGq9Ve1Q1R52Wpm4tykPnfwT2joj/k/Qa8KmICElHAD+IiO9JOheYGRG/zvstW14O+F6F+m1NahAH56S2olciYjNJ3wSOJYWkFP2BFJN6uaQjy7ZtSkoje4GUlrZ1RJwh6bvAdqUEuDbsmt+38vdjMPAFYBDpd2I8MC5vHk6Doljz9LbDABZboZFT4ZuZLdhatTEvRnp+O6+bHXUKIKkUdVremH+C1EDtHBEv5HWrA1dIWgVYBHimynlrLfcvYFlgJ+aOEoUUwQqpsfx8hX23BD6Xly8jzfNe8lBEPJ+vbyLQD7i3Sh2KSvnpfUgNdrltSe/d2/nYI/PPYhRrqWzx3n+lKNYRwLWlehZFxHDSe0/f/v08j7CZWYO06jB7Z6JO/0vqNW5aWPdH4Mwc3/l1KsR31lnuJWB34Pc5BKWodO/8Q+r/MFW8717P/geTssovIV1DrRodxWpmZl2gVRvzeqJOy03P+/1S0tC8ri/wn7x8aKHsm0Dx3m+1cpXq9ySp531p8QnyGjwA7JuXv1DjPuX1rFSfAP4X+FSFhvZu0nu3eL7XvWfep+FRrGZm1ngt25hDivQk3Qc+njQEfjEp6vRBClGnFfZ7CdgDOCvfBz6JNJQ8Dijed74e2Kf0AFwb5arVbwzpPv5ISf1rvKxjgO9KmgysC8yoYZ/hwM3tPQCXH8T7DfD9svXjgStIEav/YO4I04OBr0qaRIpY3btavfODh5NJt0GqRrGamVljOQK1h1H6vvis/JDdF4CDIqJaA9qy+vbvF9uc5tQ0M5uXp3OtTo5AbRmDgTOVnjibDnyludXpGustu4L/wZqZNYgb8x4mIu4BKt6XNjMzq6Sl75mbmZmZe+bWJP96fTp7Xn1t+wXNzJrg+v0qTQPSc7lnbmZm1uLcmNdAUki6tPC6l6SXVUcCWzvHrzulTNJ9VdaXTx/b3nFmp7GphvQ2MzPreTzMXpu3gI0kLZ6/q70TcyaPaYqI6HCaWxvHHAmMbPRxzcysa7lnXrubSDPHARwEXF7aUN6zzpOn9Mt/Hs8JY0/mpLMdJY2W9JSkLQrHHyjp/rz+a/k4fSTdoTkpa3sXztFmDzz3uEeVp6zlbbvmdeMpzA+vudPbKibE5Wu9MB/7aaXUNiQtKelGpdz0hyUd2KF32czM6ubGvHZ/Bb4gaTFgE9Isc7VYlzTr2oD854ukUJhjgeK88puQ0si2BE6QtCppDvl9ImIzYDvgN6UGuUabkmaU24A0N/vWuf7nk6ZsHQx8rMq+95IS4jYlXfsPCtsGALsAWwAnSupNmonvhYgYGBEbATfXUU8zM+sEN+Y1iojJpJSyg0i99Fo9k+cs/4g0HeodeZ70Kfl4JX+PiFk5xvQuUkMp4Bd5itTbSVnkVTPUK3goIp7P556Yzzcg1+mpXI9Lq+y7OnCLpCmk6V83LGy7MSLezXWdlus0BdhJ0qmSto2IeaahlTRM0lhJY997o5ZZas3MrBZuzOszkhRJennZ+g+Y+70spqkVk84+Krz+iLmfWSifVzdI86KvSMpFH0RKY6uW1FZJR1PWoO2EuHmOm4NlNiM16j+TdEL5ASNieEQMiYghiyzdt46qmJlZW9yY1+dC4OSImFK2fiqpIUPSZsDaHTj23pIWk7Q8MJQUdtIXmBYR7+co1bU6WvGCx4F+heCXg6qUqzkhDiDfFng7Ii4FTie/H2Zm1vX8NHsdIuJ54IwKm64BDpH0COle+pMdOPxk0vD6CsApEfGCpBHA9XmoeyypIe6UiHhH0jDgRklvk2JiK8WnnkRKiHsduJP2P6BsDJwu6SNSato3OltXMzOrjVPTrCmW6b9ubHvqac2uhplZRT11BjinplmPsu6yy/TYfyxmZq3G98zNzMxanBtzMzOzFudhdmuKf78+k32uubfZ1bAe5Lp9t2l2FcxalnvmZmZmLc6NuZmZWYtzY94gkj6UNDGHjFwlaYkuPNd1kj5XeP2EpOMLr6+R1OFHxSX9VNKOnaymmZl1EzfmjTMrIgblkJH3gCO78Fyjga0A8oxxb5ECWkq2BCrmnZeTtHD564g4ISJur7Uy5ccwM7Pu5ca8a9wDrJtjSG8orZR0pqTD8vJUSScX4k0H5PVL5ojRh3L86N4Vjn8fuTHPP68HVlSyNumDxYuSzsnBJo9IOrlQj6k5EGU8sH+F1xdL2i+X3SHXY0qu16JVjnG0pEclTZb01wa/n2Zm1gY/zd5gknoBu1FbBOgrEbGZpG+SIlGPAI4D7oyIr0haBnhI0u0R8VZhv3HARpIWITXm/yRFnH6CFHta6pUfFxGv5Z7zHZI2yelvAK/maFUk/ars9a7552LAxcAOEfGkpD+Tpmn9fYVjvACsHRHv5npXem+GAcMAFl+hnvA3MzNri3vmjbO4pImkOdT/D/hTDftcm3+OY04c6s7Aj/KxRpHSytYs7hQR75LiVDcDPkWaD/5+UsO+FWkYHuCA3HOeQIow3aBwmCvK6lL+GmB9Ulxqaa75S4BPV9lnMjBC0pdIKXLzKKamLbr0MpWKmJlZB7hn3jizckzpbJLaikaFOVGixXhSAftGxBPtnG80qWFdKiJel/QA8D+knvl5ebj9WGDzvP3isvO/VXa88te1KO7z2VyfPYHjJG0cERUbdTMzayz3zLvWs8AGkhbNQ8871LDPLcC3JAlA0qZVyt1HyhmflF9PJvXS1wQeBpYmNbYzJK1MGvqv1xOkuNR18+svk4b05yJpIWCNiLgL+CEpPrVPB85nZmYd4J55F4qI5yRdSWpcnyENd7fnFNI96cm5kXwG2KNCuftI98l/mc/1gaRpwHMR8REwSdIEUmzqc8wZeq+n/u9IOpwUhdqLlLF+boWiCwOXSupLGlk4IyKm13s+MzPrGEegWlMs239ADD3tgmZXw3oQT+dq1j5HoFqP0n/ZPv7P28ysQXzP3MzMrMW5MTczM2txHma3pnhu+nscfd1zza6GmfUAZ+yzRrOr0PLcMzczM2txbswLypLPrq82LWmh/BBJZ3TgPMvkKVxLr+eaw71RJPWTNCtf06OS/iypd4PPMUrSPE9WmplZ93FjPrdi8tlrwFFtFY6IsRFxdAfOswzwzfYKNci/88x0GwOrAwd003nNzKybuDGv7n5gNQBJW0i6P6eH3Sdp/bx+do+6jTIb5gS0iTlRbD3gV0D/vO70fL4+kq6W9LikEYUZ4E6QNCaPFgwvrB+VU8sekvSkpG3bupiI+BB4qHBN86ShSdpe0t9K+0jaSdJ1ebliAluh7MI5be3hfMzvdPidNzOzurgxryCnjO0AjMyrHge2jYhNgROAX1TYrVqZI4E/5N7xEOB54EfkHnNEfD+X2xQ4hhSGsg6wdV5/ZkRsnkcLFmfu2eB6RcQWeb8T27mmxYBPAjcX0tAOjIiNSQ9CfgO4CxggacW82+HAhXn5uDxRwSbAZyRtUnaKQcBqEbFRPuZFbdXHzMwax4353ErJZy8CKwO35fV9SVOaPgz8jpRAVq5amfuBn0j6IbBWRMyqcu6HIuL5PBXrROakqG0n6UFJU4Dty85dKXWtXP98TS8B/80RqBXT0CJNB/gX4Ev5eYEtgX/kMm0lsAE8Dawj6Y85QvWN8opIGpZ792NnvfFaleqamVm93JjPrZR8thZpjvHSPfNTgLty73hP5k0/q1omIi4D9gJmATdJ2r7Kud8tLH8I9Mo96LOB/XJv9/yyc1dKXStXumfeHxgsaa8q5UouAr4EHARcled8LyWw7RARmwA3ltWDiHgdGEiKbT0SmGeu1mIE6uJLL9dONczMrFZuzCuIiLeBo4Hv5YCRvsB/8ubDquxWsYykdYCnI+IM4O+kYeo3gaVqqEqpwXxFUh9gv9qvYm4R8QppeP/HtJGGFhEvAC8AxzNnqLzdBDZJKwALRcQ1ed/NOlpXMzOrjxvzKiJiAilW9CDgNOCXOYWsvAdcSqqpVuYA4OE81L0R8OeIeBUYnR8WO50qcvLY+aTUtVtIqWWd8TdgCWBz0v3wq/Lw/UfMnYY2gpS+9liuxyTS8PrjwGVUTmBbDRiVr/NS0ocGMzPrBk5N6wRJ+wJ7RcShza5LI0k6E5gQEX/qqnOsvO4mceDpN3bV4c2shXgGuNo5Na3B8r3nnwNfaXZdGknSONKQ+ve68jxrLLOI/wGbmTWIG/MOioiRzPnq2nwjIgY3uw5mZlYf3zM3MzNrce6ZW1NMf/0Drr36lWZXw8ysW31+vxW65LjumZuZmbU4N+ZmZmYtrsc15tViSCWtKunqdva9r0F1GCppRq7HY5LanPe8AedbWdINkiblqNKbuvJ8NdSnw++jpMMkrdrI+piZWdt6XGNOlRjSiHghItqcAS0itmpgPe4phKN8SVJXzmj2U+C2iBgYERuQZmrrMnlWu6o6+T4eBrgxNzPrRj2xMS8qxpD2yyEm1WJFkTQz/xyaI0IrRYrunteNk3SGcoRpNRHxFinIZF1JJ0k6trQtjx70y38ek3R+jgi9VdLiuUx/STfn890jaUCF06xCSlMrnXNy4Tpm10/SmZIOy8tTJZ2W40YfKk3NKmlFSdcoxaaOkbR1Xn+SpL9IGg38JZe7Ldf3AknP5ilZi+9jH0l3SBqfz7N34e9inuuVtB/pw8+I/HezeA1/x2Zm1kk9tjHXvDGkRZViRcvNEymag0vOA3bL36descJ+5fVYHvgU8Eg7RdcDzoqIDYHpwL55/XDgW/l8x5KCU8qdBfxJ0l2SjqtjmHpGDmA5E/h9XvcH4HcRsXmuQzHwZANgx4g4iBSZemeu79XAmhWO/w6wT0RsBmwH/Kb0oajS9UbE1cBY4OA8ujJXQpwKqWkz3ni1xks0M7P29MSvppViSFcDHmNODGnR/cBxklYHro2IpyqUeSgingfIx+sHzCSFnjyTy1wODKtSj23zPOsfAb+KiEck7d9GvZ+JiIl5eRwpyKQPsBVpDvRSuUXLd4yIW5QCWXYlhZhMkLRRG+cqubzw83d5eUdgg8L5ls71ABhZaGC3AfbJ579Z0usVji/gF5I+TXofViNFw1a83vYqGxHDSR9uWLf/IM8jbGbWID2xMZ8VEYMkLUEKFzkKOKNYICIuk/Qg8FlSrOjXI+LOsuPMEylaZz3uiYg9ytZ9wNyjGZXiSEvnWzyXnZ5HENoUEa+RQkwuy0PrnyZlkFc7H8wJeSkuLwR8KiLeKRbMjftb7dWjzMGk0YvBEfG+pKmFOlS6XjMza4IeO8xeIYZ0NlWOFa3FE8A6kvrl1wfWWa2p5GjP/EDc2m0Vjog3gGdKPXolA8vLSdo+f3hB0lKk7PH/A54l9bIXVXqqf4eyXQ8s/Lw/L98KfKtw7EFVqjealOiGpJ2BZSuU6QtMyw35dqSc9/bUGu9qZmYN0mMbc5gnhrRonljRGo83C/gmcLNSoMibwIw6qnQNsJykR4D/AZ6sYZ+Dga9KmkS67753hTKDgbGSJpMa5QsiYkxEPAdcSYpAvZIUQ1q0bN7n28B38rqjgSH5wcBHSc8XVHIysLPSQ4X7Ay+S3o+iEflYU4BDSBGo7bkYONcPwJmZdZ8FLgJVUp+ImJkf5DoLeCoiftfefj1NHvIeEhEdmhNV0qLAhxHxgaQtgXNquR3QKOv2HxSnnXp7d53OzKxH6Ox0rnIE6mxfk3QosAipp3tek+vTLGsCV0paCHgP+Fp3nnyZZXt12RzFZmYLmgWuMc+98JbriZeLiH6d3P8p0tf3zMysxfXoe+ZmZmbWvgWuZ249w9uvfMCEC6Y1uxpmDbXpESs1uwq2gHLP3MzMrMU1rTGX09GcjmZmZg3RzJ6509GcjmZmZg3QU4bZnY7W4ulokn6VRxsmS/p1DX/nZmbWIE1vzOV0tFr06HQ0YAlSaMuGEbEJ8LMar8vMzBqgmU+zOx1t/klHm0H6QPCnPMJQcRRE0jDy38PHllu92rWamVmdmn7PnBTeIfI986KIuAzYC5hFSkfbvsJxGpGOtmlEDI6Ic/O6etLRelFIRyv8+USlk0XEaxFxWUR8GRhDSkdr63zQdjpa6XyrRcTMvK0z6WiDSGlt1dLR5nl/I+IDYAtSz38P4OZKJ4mI4RExJCKGLLvU8nVW0czMqmn6MLvT0Vo/HS2PCPSNiJtIgS/zXLuZmXWdHjFpTERMUEr/Ogi4p7DpAODLkt4npXr9osbjzZJUSkd7i9QDrsc1wCFK6WgPUns62jmSjgd6A38FJpWVGQycKanUE78gIsYASCqloz1D9XS0d5mTIHc0cFZe3wu4m8oJaScDl0v6MumDQLV0tOuV0tHGUl862izSLYO/52cVBHy3hv3NzKxB5tvUNDkdrbR/U9PRqtmg36AYcfytza6GWUN5BjjraloAU9OcjpY0NR2tmiVW6OX/+MzMGmS+bcydjjZ7f6ejmZnN55r+AJyZmZl1znzbM7ee7f2X3uXFX/+r2dUwszp87Nh1m10Fq8I9czMzsxbnxtzMzKzFtduYq0pUaaNIujgHd1TadqxSWMrEHCZySF4/tRQWUuM5ZgeZKEV3ntmY2neNwns+KYefNDIlrr1zzw66MTOz1lBLz7xiVGlXk3QksBOwRf5e9A6kCUlaVvkMd20ovecDgR8Dv+zCanVKHddkZmZdpN5h9mJU6SBJD+TIy+skLasUAzq+VFjSeqXXkk7IveuHJQ0vpHJV8xPgG3mqVCLijYi4pLD9W5oT2Tkgn2MLSfdLmiDpPknrt3UCtR0jeqFSvOrTko4u7PO/kp6QdK+ky5WjUlUlAjWPPJwr6UHgNEmfyb3uibmeS7XzPiwNvJ6PVVdUad62ef47mijpdM2Jl+2X6zm+Wu9f0mKSLsrnmqA01WtpdGOkpDuBOyQtmd+vh3K5vdu5JjMza6CaG3PNG1X6Z+CHOfJyCnBiRPwbmKE584QfDlyUl8+MiM1zD39xUiBHtXMtDSwVEU+3UaVXcmTnOaTIUUjTkG4bEZsCJ9D+9K9txYgOAHYhBYicKKm3pFK5gaQpTIuz8LQVgbo6sFVEfDdvOyqPNmxLCpEpt3hufB/PdTolr68rqjSvvwj4ej7fh4VzTAN2ysc6EDijQj2OAiLHrx4EXKI0ZSukuev3i4jPAMeRYla3yPU6XdKS5QeTNEzSWEljX535WoXTmZlZR9QyRDpPVKmkvsAyEfHPXOYS4Kq8fAFwuKTvkhqJLfL67ST9gJR9vRwpN/z6TtT92vxzHPD5vNyX1OCsR0oX693OMdqKEb0xIt4F3pU0jRQJujXw94h4B3hH0vUwO2ikrQjUqyKi1JCOBn4raQQp1rVSRnspUQ6lKVj/rBSVWldUqdLzDUtFRCmc5TLmfIjqTZonfhCpkf94hXpsA/wRICIel/RsodxtEVFqkXcG9iqNUpAS19Yk/b7MFhHDSR96GLjGxvPnPMJmZk1QS2M+KyIGKaV93ULqrV3SRvlrgBOBO4FxEfFq7s2dTZpj/DlJJzFvzOdsEfGGpJmS1mmjd16K5izGcp4C3BUR+yglpo1q59pKMaLvFFfmBrmeaNXZEahVts+OJI2IX0m6EdgdGC1pl4ioGmwSEfcrPey3Yt6nFFX6vtK87dWiShdvo76Q0s1eIo0yLETq9dejGLMqYN+IeKLOY5iZWQPUPMxejCol/Uf+uqRt8+YvA//M5d4hNfrnMGeIvdTgvJJ7sRWfXi/zS1Iq2NIw+37xIe3s0xf4T14+rIZz1BojWjIa2DPfS+5D7uXWGoGat/WPiCkRcSopzW1AWyfM994XBl6lzqjSiJgOvCnpk3nVFwqb+wL/jYiPSH9/C1c4xD2kNDgkfZzU267UYN9CeoZBuaynjzUz60Z1PQAXEROAUlTpoaR7o5OBQcBPC0VHkIaBb837TQfOJ0V83kJtkaTnAHcBY/JDW/fkY7blNOCXkiZQ26jD0cCQ/IDYo1SOEJ0tx5WOJL0H/yA9KzAjbz4Y+KqkSaRbCNUeAjtG6SHAycD7+TjlSvfMJwJXAIfmYfoRub5TgEOoLar0q8D5+VhLFup7NnBoru8A5u5pUyizUD7fFcBh+dZDuVNIw/aTlWJjT6lQxszMukiXRKDme6d9I+J/G37wJtOcaNUlSBniwyJifHv7NUupvnn5R8AqEfHtJleLgWtsHLd8+7pmV8PM6uDpXJtP3RWBKuk6oD+wfaOP3UMMl7QB6dbBJT25Ic8+K+nHpL/rZ6nt9kOX673yov6PwcysQRremEfEPo0+Zk8SEV9sdh3qERFXkIbIzcxsPuW52c3MzFqcp+K0pnh/2pu8dMaoZlfDzFrYykcPbXYVegz3zM3MzFpcSzfmko7Lc5GX5h7/ZPt71Xzsm9TghLgq55knpUxpbvhjq+1T4RizU+G6oj7dub+ZmdWvZYfZ8zSnewCbRcS7eZa0RRpwXJG+srd7A47VKyI+6OxxGq2n1svMzDqmlXvmq5DCVt4FiIhXIuIFmDvvXNIQSaPycsU0tNybfELSn0kT26xROoZSItiNStniD0s6MO8zWNI/lVLSbpG0Sl4/StLvJY0Fvi1p/7zfJEl313OBajuFblelrPfxzJmbHlVJMNO8SWcVE9iyXpJGKCWxXZ2/U181+S6/F5PyBDTdEpFrZmZztHJjfiup0X1S0tmSPlPjfvOkoeX16wFnR8SGEfFsofyuwAsRMTAnvt2c9/kjKTVsMHAh8PPCPotExJCI+A0pvW2XnE2+V5U69decWNSJ5JnoqqXQKc11fz6wJzAY+FjhWG0lmBWTztpKYFs/vxefAN4AvpnXV0u+u4iUGFdxClszM+taLduY51nNBgPDgJeBKyQdVsOuN0bEuxHxCikGtJQ69mxEPFCh/BRgJ0mnSto2ImaQGruNSAlyE4HjSTGnJcXvdY8GLpb0NSrPfw7w74gYVPoDnFvYVkqhW5iUQncZ6QPJMxHxVKQp/C4tlN8Z+FGu1yjmJJjB3ElnpQS2ycDtzJ3A9lxEjM7Ll5LS0yAl3z2Yp3fdHtgwP1ewTESURh3+UuUa54pAfW3mjGrFzMysTi17zxwgz1c+ChiVG5hDgYuBD5jzQaU8na1aGlqlucmJiCclbUZKLPuZpDuA64BHImLLKlUrpqQdmR/M+ywwTtLgiHi1tisEKqfQrdFG+YoJZrkOxWs8mOoJbOVz/IbqTL6rZK4I1DXXdwSqmVmDtGzPXNL6SrnlJYNI05UCTCX12gH27eR5VgXejohLgdNJQ9VPACvmh/CQ1FvShlX27x8RD0bECaQRhLYa4nlUSaF7nJRX3j+/PqiwS60JZm0lsK1Zujbgi8C9VEm+yyE60yWVeu8H13N9ZmbWeS3bmAN9gEskPZqHijcATsrbTgb+kB9C+7CT59kYeCgPW58I/Cwi3iM1Zqfmh74mAltV2f/0/IDZw8B9wKQO1KE8he4d0u2FG/MDcNMKZWtNMGsrge0J4ChJjwHLAue0k3x3OCmudiJpZMDMzLpRl6SmWWNpPkyhG7jm+nHrsec1uxpm1sIWxBng1F2padZYmk9T6HqvtNQC+Q/RzKwruDHv4eb3FDozM+s8D7NbU0h6k3Rvfn6wAvBKsyvRIL6WnsnX0jM141rWiogVy1e6Z27N8kSl+z6tSNJYX0vP42vpmXwtXaOVn2Y3MzMz3JibmZm1PDfm1izDm12BBvK19Ey+lp7J19IF/ACcmZlZi3PP3MzMrMW5MTczM2txbsytW0naVdITkv4l6UfNrk+9JF0oaVqea7+0bjlJt0l6Kv9ctpl1rIWkNSTdlbMNHpH07by+Fa9lMUkPSZqUr+XkvH7tHNn7L0lXSFqk2XWtlaSFJU2QdEN+3crXMjXnU0zMeRmt+nu2jKSrJT0u6TFJW/ak63Bjbt0mZ7KfBexGCsY5SNIGza1V3S4Gdi1b9yPgjohYD7gjv+7pPgC+FxEbAJ8iBetsQGtey7vA9hExkJSeuKukTwGnAr+LiHWB14GvNq+Kdfs28FjhdStfC8B2ETGo8J3sVvw9+wNwc0QMAAaS/n56zHW4MbfutAXwr4h4OifP/RXYu8l1qktE3A28VrZ6b+CSvHwJ8LnurFNHRMR/I2J8Xn6T9B/TarTmtUREzMwve+c/QcozuDqvb4lrAZC0OvBZ4IL8WrTotbShpX7PJPUFPg38CSAi3stJkj3mOtyYW3daDXiu8Pr5vK7VrRwR/83LLwIrN7My9ZLUD9gUeJAWvZY8LD2RFAd8G/BvYHpEfJCLtNLv2u+BH5BijwGWp3WvBdIHq1sljZM0LK9rtd+ztYGXgYvy7Y8LJC1JD7oON+ZmDRTpu54t831PSX2Aa4BjIuKN4rZWupaI+DAiBgGrk0aABjS3Rh0jaQ9gWkSMa3ZdGmibiNiMdHvtKEmfLm5skd+zXsBmwDkRsSnwFmVD6s2+Djfm1p3+A6xReL16XtfqXpK0CkD+Oa3J9amJpN6khnxERFybV7fktZTkoc+7gC2BZSSV8ida5Xdta2AvSVNJt6G2J92rbcVrASAi/pN/TgOuI33YarXfs+eB5yPiwfz6alLj3mOuw425dacxwHr5ydxFgC8AI5tcp0YYCRyalw8F/t7EutQk34f9E/BYRPy2sKkVr2VFScvk5cWBnUjPANwF7JeLtcS1RMSPI2L1iOhH+vdxZ0QcTAteC4CkJSUtVVoGdgYepsV+zyLiReA5SevnVTsAj9KDrsMzwFm3krQ76Z7gwsCFEfHz5taoPpIuB4aSog9fAk4E/gZcCawJPAscEBHlD8n1KJK2Ae4BpjDn3uxPSPfNW+1aNiE9fLQwqYNyZUT8VNI6pN7tcsAE4EsR8W7zalofSUOBYyNij1a9llzv6/LLXsBlEfFzScvTer9ng0gPJS4CPA0cTv59owdchxtzMzOzFudhdjMzsxbnxtzMzKzFuTE3MzNrcW7MzczMWpwbczMzsxbnxtzMzKzFuTE3MzNrcf8PhvyojY7RgEAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(win_percent,win_percent.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Toss Decision**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_decision = matches['toss_decision'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,len(toss_decision)):\n",
    "    toss_decision[i]= toss_decision[i]/total_matches*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\kumar aditya\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='toss_decision'>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(toss_decision.keys(), toss_decision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches.drop(['date'], axis = 1, inplace = True) #Drop date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>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",
       "    </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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city                        team1  \\\n",
       "0        1    2017      Hyderabad          Sunrisers Hyderabad   \n",
       "1        2    2017           Pune               Mumbai Indians   \n",
       "2        3    2017         Rajkot                Gujarat Lions   \n",
       "3        4    2017         Indore       Rising Pune Supergiant   \n",
       "4        5    2017      Bangalore  Royal Challengers Bangalore   \n",
       "..     ...     ...            ...                          ...   \n",
       "751  11347    2019         Mumbai        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad               Mumbai Indians   \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",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           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",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \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",
       "751               9       HH Pandya                           Wankhede Stadium  \n",
       "752               6        AS Yadav                  M. A. Chidambaram Stadium  \n",
       "753               2         RR Pant                           ACA-VDCA Stadium  \n",
       "754               6    F du Plessis                           ACA-VDCA Stadium  \n",
       "755               0       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium  \n",
       "\n",
       "[756 rows x 14 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Effect of toss on match**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_winner_wins = matches[matches['toss_winner']==matches['winner']]['winner'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_looser_wins = matches[matches['toss_winner']!=matches['winner']]['winner'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame_toss_and_win = pd.DataFrame({'Toss':['Toss Looser Wins', 'Toss Winner Wins'], \n",
    "                                        'Win': [toss_looser_wins,toss_winner_wins]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Toss', ylabel='Win'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='Toss', y = 'Win', data = data_frame_toss_and_win)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Stats for each Venue**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</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",
       "    </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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city                        team1  \\\n",
       "0        1    2017      Hyderabad          Sunrisers Hyderabad   \n",
       "1        2    2017           Pune               Mumbai Indians   \n",
       "2        3    2017         Rajkot                Gujarat Lions   \n",
       "3        4    2017         Indore       Rising Pune Supergiant   \n",
       "4        5    2017      Bangalore  Royal Challengers Bangalore   \n",
       "..     ...     ...            ...                          ...   \n",
       "751  11347    2019         Mumbai        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad               Mumbai Indians   \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",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           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",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \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",
       "751               9       HH Pandya                           Wankhede Stadium  \n",
       "752               6        AS Yadav                  M. A. Chidambaram Stadium  \n",
       "753               2         RR Pant                           ACA-VDCA Stadium  \n",
       "754               6    F du Plessis                           ACA-VDCA Stadium  \n",
       "755               0       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium  \n",
       "\n",
       "[756 rows x 14 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches_city = matches['city'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches_city = dict(matches_city)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "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>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",
       "    </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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city                        team1  \\\n",
       "0        1    2017      Hyderabad          Sunrisers Hyderabad   \n",
       "1        2    2017           Pune               Mumbai Indians   \n",
       "2        3    2017         Rajkot                Gujarat Lions   \n",
       "3        4    2017         Indore       Rising Pune Supergiant   \n",
       "4        5    2017      Bangalore  Royal Challengers Bangalore   \n",
       "..     ...     ...            ...                          ...   \n",
       "751  11347    2019         Mumbai        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad               Mumbai Indians   \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",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           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",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \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",
       "751               9       HH Pandya                           Wankhede Stadium  \n",
       "752               6        AS Yadav                  M. A. Chidambaram Stadium  \n",
       "753               2         RR Pant                           ACA-VDCA Stadium  \n",
       "754               6    F du Plessis                           ACA-VDCA Stadium  \n",
       "755               0       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium  \n",
       "\n",
       "[756 rows x 14 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-57-1b17ebd03fdc>:10: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(i)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+geG+ajBmN3KADiwx1X189pwHATJumJ3bNKHl9U4Vn+E8alAvGvfpY5N3mdA61mfjXsJZVCi9gDFfnMBAu/DAhNhASmR/X4376jnHAjJ6UOItSGRSzpG+GvYVzolA3eA+DPbUvjEddYSvhn2Fc0xahJr+uXYKxYRe6vScRYWSA/SfNIJcmyfIJIAJlEgPHw376DkHAzpumN1UbRJCOjDZR8M+wjkUiIzIt/GmSRhedm19hPMAoG5wXwunSRipE860CDUD7GCQSRwFPhqN6wGZokLpCfSfsC916WlkxLNtY/aCl+u/491zDgF0RL7dWG0SSi4lEvfV7uIdzkFAZEAeveLcrjF7a1i8G4x3OPOBaP9cC6dJOEkfzoFAQ++ettyCSThJH84BQENetoXTJJykD2d/oCE7E6/TPxjTCckbzmAazD5AY3Y6Xq5VNGYvJG84gaygPc3MwPucoMbsoUHxbjCe4cwGYhFBMtMsnCbhxH39lHiGswegeT3IEJuYxCSeuN/eGO9w0thMNI5tGtNV4n65aTzDmQbQ0EQsjm0a01XiHs54dtVRgJiiMUVt1r2uU15P/R1lVJbUkb05za6+6lJKRCM0E2F7c5ybjns4AWIxohGbomSv1EWJ3ldO+b1bSfsgg0EaYb/4H7JIGVm4GeDjyk84lWic204aT1Wx4a4qGl4X9ommM4ws3xWljHh3nHENyCdjzSCcpoPeqWbbbeVseaaJ/B2ZDLQ7Yb2I+8+st93aOLabkMrrqb+zjMrHasnbkE0/hN622+rVtng3GO9wCkDUes6dqo8Su7+c8nu2Enm/ZRxpl2uERWW8G/TSc0at5/yMp904sv51YZ/mdIbaODKUNsS7QS/hrK2nuk9P+sex7dBZXM32W8vZ/M9GBuzIsnFkAkjqnrOZYLd26w62DO3HiDi2HQoVDdTfuZ7KR2vJ3ZBFf4Re1ksmjKTuOeuARiB9YzVb4tiuV/VRYg9UUP67LTaOTHDJ23POWqhaVCiVQE7FtuQP5z+qqLqzirr5No5MFkndcwKUA+PWbWZrnNuNiyU1bL+1zI0ja7PIt3FkUimLd4PxDud64NCVlWyOc7vdpqKB+rvK2PBoDTmVNo5MTkojwofxbjbe4dwAyLrN1DZFacpI0Fnf66PE/i8YR5a6ceS+No5MYsIKvUmT+vI9gC2AAlTXsaVfLgPj3P5eeWYjVXdsoO41G0emmqU+GvURTgC2JUg4l9Ww/ZYyNv/DxpGpLCXCuZXgBu/yLVSOzPezelN7NjTScNd6Kv5YQ26FjSMNLPHRaFznrZ21UJtwAc1ato6P49l2exqjxH63nvUHLaNsn4/IuLOZ/Sqy6W+3hBs89Zw+1uf8EOg1r5S1sZj/KUtmb6TquBV8nFNK8+U7GLoiiyEa8fLvYsJI2aI36XofTfu44XkRULhtB1Ubqykf2Juh8S7g3Rq231LO5lkNwTjSbvs2uyK85qtpHz+WawiO2K7eyJp4hbOqkYa7yqicWU3PiiwG2DjSdNC/fDXsI5zlQBOQvmwdqw8bxZTuaqgxSuzBCip+uwVWpDNI0+x8pNlj3sIZ97HVrIUaBVYAvee9x8cxdb1oV3p2I1XTVvBxbilN39nBkOVZDNE0NzWnMR2mVOhNutxX875GW4uACZtq2LS5hsoBeeyzt2/4bo27P3JWA/1rbBxpusYcn437+hFeTTDuXLOR1Z0NZ1UjDXcH48hyG0earib+dmnBXzjX42ZGSFu0hlWFIzmioxs2Rok9VEn5jM2IjSNNN/u3z8a9nM+btVCbgfeB3s8vYVVDE/XtbfPcJjYeH4wjL6tlqI0jTbdS3tGbtMJnCT5Ptr8J5NY3Ef2wkhU7e8HyGqrP+4DVecuoPmUzA+ams29Thu24mjgQHvFdgs/DJktxcwrJK6UsO3gYXwDY1EjjXWVUzKymZ5kbR+ZZHE1cKVGEP/kuw1s4Zy3UzUWF8gEw6PklfBQpYPWvt5K53MaRxrcY/9Gfa9ynJWnL9zWkL0aVPuWNFFy9nKx3bRxpwiCNB32XAJ4XE2pS3l1Sz+gaJdKwksWMZLDPeowhRi0RnvZdBnjuOZ99W7eVRfnz9hjvNG7gDWop91mPMcDf9CZt9+xBPPjerQV4EYIR5joWeq3EmAgP+C6hRRjC+R6wA8hiCYtpotZ3QSZFNfGO3qSv+i6jhfdwaqk24a78H0gTzazjdd81mRQl/Nx3Ca15D2fgJdy1tuks4k2iNPguyKSYJj4iPRwHglqEIpxaqluBucAg6migwsaeJu5u1Zu0y29f3BuhCGfg37hTOxEWMx9bw9PESzNVZPi/XK+t0IRTS7USeB0YyFZqqGKx75pMiojxS71Jm3yX0VZowhl4DndaRVjCK9Z7mm7XzGYymeG7jJ0JWzg/BpYBA6hiC2V25NZ0swZ+rDdpKE/fhSqcWqoKPAXkAMICXqaJGr9VmaRVz4fkcK/vMnYlVOEE0FL9EHgNGEw9jXzIC75rMklIgQYuDdsR2tZCF87AE7h7PTN5h0XUxn/hUpPkavmX/lL/47uM3QllOLVUN+F2b91dKot51mc9JslEaUK52HcZ7QllOAMv4BY9ymM169joZzEZk4RquUfv0jW+y2hPaMOppVoP/BEYAMB8nrODQ4EY8HvgsTbPzwZuaWfbrcFr2l7evbP3fAK4h8/OQfcS7HzGpwRRx1qUH/ouoyNCG87AItyPwiCq2cFSZnmuJxxep+VX1qfWQ/tzGALPA2M68J4VuOu1vgOUBe9dHbRz4B7WGxZRomygWH8ZvgsOdibU4dRSjQEP435MsnmPD6jgLb9VebYN+ACY1Oq5GO6+npPa2XYF0BfI78B7pgHNwXtHcYfn5gLHdbLuMNjA7/UhfcV3GR0V6nACaKlWADOBIYDwCnOoZ5Pnsvx5DhfC1ov6LgAKgLzdbNeA25U9toPvmQ/0BO4L3nsz7vTDkM4W7tl23uddfuC7jD0R+nAGXsXNczuYRpp4i7+j/hfejbtS3OUZrQOyHXgXOKydbV8EjoDPTTO6s/dscQpwGTAF12tOA14G/gIJdd9QE/VU8BWdpwl1OahoeM/BfoYUSB/gZtzop4YpHMMIpvmtKs7+DSzG/UptxvWG6bhd0Jap2rbhdl3b9hEPBd8D9y8ouLBV7+Q9DwS+2mrb93ALNx4CvAJ8GXeo7hwgs4s+W3dax/X6gP7Cdxl7KmHCCSAFMh64GlhDBGU659Jnp4c3kt9HuOuovt7m+VuAG9vZdi4uVEd14D2juCAW43Zt3wDOAB4BzgZ6dKL2eKpiLv/ihODS0ISSKLu1LZbi+o/hxFDm8gR1VPkuKrTeA/b2GpgFwARcmAfhlj2+B7cbHPZgbmMti/hKIgYTEqznBJACyQauxf14VDCAPkzjYjLo6bk0Eyb1VPM2x+vzmrBH9xOt52y5OOG3uJFTXzaylYU8bvd+mk8008gKvpPIwYQEDCeAlupm4Fe444w9WcXHvMc/PJdlwiBGjOXcyYrPXT+VcBIynABaqmtwo59BQAaLWMxaEuYEs+kmH/A4y/hZoo4zW0vYcAJoqb6NO+s2HBDm8QIVvOm5LOPL+zzHQr4VzIWc8BI6nIFncafG9wOE/zDbApqC3mMub3GeluoO36V0lYQPZ3D97SO4K4gsoKnoPV7ibc4L7gNOGgkfTvhkSYf7sYCmHhfMYi3VpJstIynCCRbQlJTEwYQEvAihPVIgGcClwGRgDaBM5XiGM9VvZabLxIixgrks5vxkDSYkYThhFwGdwHgOpIiILWuf0Jpo4C2e4SO+l8zBhCQNJ3wS0AuAY4C1QBMjGc5k/ssu9UtQO9jGK/yFjdykpZr0q6AnbTgBpEAiwHTczU2VwA4G0IepFNPjc/MBmDDbTBnzuJ9afqWlut13OfGQ1OFsIQUyCTcbTi2whR5kMY2z6MNoz6WZjlhLKa9xB1Ee1VJt9F1OvKREOAGkQEYAV+AWSqoggnAER7MvxxFJnqPWSSVKI8tYwLvcDMxJhkvy9kTKhBNACqQf8D1gBG4cGmNfhjCZr5BNf6/Fmc/aRhmv8RJbuF1LdYnvcnxIqXDCJ/eDfg04EagCasgkg6M5mX2Y7Lc6Q4woH7KIhTyLcp+W6jrfJfmScuFsIQVyCHAJbsqrckAZyxgO4QwyyPFbXYrawWZe5zUqmAk8nUrjy51J2XACSIH0Bs4HDqVl6uQ8ejKFU+jPOL/VpZAYMdbyLm/wIs3co6X6nu+SwiClwwmfnG45ChfSZtwpFxjNCA7hVDvl0s22sJIFLGUTs4E/aanakhuBlA9nCymQfYALgbHABqCWCBEmcygjOI50sv1WmGTq2MRiFrKKD3B3Fb2Vakdj22PhbCXoRScD5+GmQCkHmskhm0M5ln041C7/20vN1PMh77CIUmL8E3hOS8O57LtvFs6dkALJwc13fipuMsgKQMmnL+M5mnwmWEj3UJQG1rGEd1jFDuYDjwdLbZhdsHDuhhTIINzc54cDNcBGQOlDLuM5gsFMJu1zCxyY1pqoYQ0LWcw6GliLm6J6he3Cts/C2Q4pEAFGAWcCB+EWLNgAxOhBFhOZzDCOIINcn3WGTj2bWMU7LKWcKJuAJ4H5yTK/TzxYODsoCOm+uN3dw3ALFVQCzaSTxngmMIwvkMswn3V6pSjbWclKPqCUDShlwN+BxRbKPWfh7IRgd/dE3FJAEVxIGwAYSD8OYDyDGE8Wff1VGUc7qKCcpSynnGpiuNU+ZwHLgzmeTCdYOPdCsPLZsbig5uICWgXB7PMjGc7+TKA/ByfdqZhGqqliKaWsooIm3OqdC3FrZ6+yMeXes3B2ASmQdNxi7kfjdnnTcQeQ3JKz6aQxguEMZn/6MYqeDEY+s1Rt+MWIUsNaNrOKtaxnHU0oAqwGXgCWaKlW+y0yuVg4u5gUSE/gYNwu71jcSpg7gC24K5Agh2xGMpKB7E9fRoV297eODWxmJRWs4iO20PjJNcdbcIFcqKVa6bHCpGbh7EbBLWoFwCTc0rMZwbeqcWtSu/FYL3IYxCD6MZA8BpHDIHqQT+STJXG7V4xm6tnEDjawjXI2UUE526ilB25MLcAq4C3gfWC1jSW7n4UzToJd32HAaNxVSC2L/kZwY9UaXA/rfugFYSD9GEA+PckjixyyyCWDHDLJIZ0cMsghQtYud5AViFJPMzU0UUsTtTRQS2PwtZbtbKSKjdSg5MInp4MEd053IW5R+4/sKp74s3B6EtxXOhy3ENMoYCQuvK2j1gQ0Bn9aHnfmPywj+JMZfM3C/VKIBV/rgJW4o6wfA+uBTXZQxy8LZ4hIgaQBA4CBwGBccPsGf/oAvXDhVToWUsGFbwewNfizBdiEu0VuI+7ocrUFMXwsnAkkuBCiB+6i/B6w2yO+jbgJzWq1VG1h4QRk4TQ7JSJRYCnuF0AUuFxVX+vC939NVafs5vsvAteotr86tYiMAKaoaklX1RcGNuuc2ZU6VZ2oqhOAHwG3deWb7y6YnTACKO7C9wsFC6fpiF64sSoiMlNEvtzyDRF5TETOaP1iEfmdiBQFj58UkYeCxxeJyC3B45pWr79ORJaKyGIRub3Ne0VE5GERuVlE0kTkThF5U0SWiMilwctuB6aKyCIRuVJEDhaRBcHfl4jIGBJQfM6jmUTUQ0QW4eb5HQwcHzz/IHAl8JSI9Aam4Ja9aG0eMBV3fe3QYHuC5/7c+oUicgpwBnC4qu4QkX6tvp0OPAYsU9VbROQSYJuqHioiWcCrIjIHuB63C3x68J4zgF+r6mMikgmJee+t9ZxmV1p2a8filrSYKSKiqi8BY0QkHzgXeEJVm9tsOw/Xkx0ELAcqRWQwcCTQdtx6IvAHVbcitapubvW9+wiCGfz9ZOD84JfGG0B/Pj1f3Np84AYRuQ7YT1XrOvMP4JuF07RLVefjTvG0THY2EzeVy4XAQzt5/XrcqZ/pwMu4sJ4N1Kju0fW3rwHTRKTlpgEBvhf80pioqiNVdc5O2i8BinDnb2eLyPFtX5MILJymXSIyFrdr2LKs+8O4pS1Q1eW72Oz14DUt4bwm+NrWv4ALRaRn0Fbr3doHgdnAX0QkHXfHy2UikhG89gARycFdDpnXqt79gVWq+hvgaWD8Hn3gkLAxp9mVljEnuB7rAlV3vlRVK0VkBfDUbrafB5ysqh+KyBqgHzsJp6o+JyITgbdEpBEXxhtaff+Xwdj2j8DXcUdm3xYRwV1A8WVgCRAVkcW4XxxZwDdEpGX+p1s78fm9s/OcZo8FvdxSYJKqbvNdT7Ky3VqzR0TkRGAFMMOC2b2s5zQmpKznNCakLJzGhJSF05iQsnAaE1IWTmNCysJpTEhZOI0JKQunMSFl4TQmpCycxoSUhdOYkLJwGhNSFk5jQsrCaUxIWTiNCan/B1RcmMnI6tY3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hLXrXIw8sgbNnwcAy18eTlwd54vp6UqjTKSOyRZRbOm5pmX62kF5GUjingdrXZ1Pe3cC59Mcw91aIb4Mj/jfc/yw89oK7vewNOOcHcNb33HO37oGzb+98W+h4e3DB8uvF8KXg/NL/+Zjb53UPwjWn9fQb0K6caOlEdsCnxORLwGTO53zKGOW7HtNGgtZb8mn+1sSMncPYlwagjAWauiuAPIjy4dVYoJYSa+lkkvxmGv9zAHLxCAucdpTgLvN4w3chvRHJwyuJSTFQyUCKyM/4Cbojo6yeuhWjKLh4hP1MOpH183dHtaUzFEhQYafKM8WYGmpWTqO0f1E0/xF2Q9Z3BUT1B1wJCCWZc5FZlJ1aT+36WZRb4HRJ1ncHRPWHXAbkWeh4liTxlST1z8ykLD+qv4ndl/WXeET18Gog0EqxhY4veS00/boCPpO5q2xmqqxv6UQ5dFoostDxoaSB+sWjKTwmOxa9yzQWOllqANBMEWW+C4maEbXUrphC3yHZtehdJsn6w6uo/uD740LHWjohmltHzaYZlFng9ErWt3Si+sOvAFrIz+kpLjNHkuQXWqhbmp2rbGaaUqolqw9LIxc6wZQWZUALkjPLlGQsaaH53hKa751ircoUyurQiWKfTiHgBpzZkjNp1aeR+qdHUHDCIGtRplhW/91mdfE9lMcHoZPR0yVks8G11L40iZJRJdaaTIOs/p5GNXRMmu0upmT8JlqAZt+15AgBNJFPQ3kembMweQ9EO3SUaM7rEYJkAfnJLP+PnKFK9ifJ6qktov1fX7P7h2ciq9V3Ab0RxdBJwvt9ORY6JhslfBfQG1ENHSdBamewNSb9GrVKs/r3Noqhk+BAS6eZWr+lGNNtWb/uVRRDpxkXPHk0U+e7GGO6yUIn22hcFdgPFFromCy0w3cBvRW50AnsA4potNAxWcdaOlnqPaDQQsdkIQudLLUHKKLeOpJN1rHDqyzlWjo11PguxJhu2uq7gN6KaujsA/J4l70kafFdjDHdsNp3Ab0V5dBJoigN7PJdjDFdorQAcd9l9FYUB3xC2864OnZSyoiU7XkZ8HJweyhwAbAZ+CtuQo0i4EJg0CHbJYA/Attw10zPBOYHjz0PvBTcngPMDW4vwi0wOwz4RHDfK0B9m+eY3CGs0yrN+pZ5VFs6u3F/2nnUpLBjbj/wD+DzwJeCV3gN+C/gIuBaYDqwuJ1tV+OG8X0x2P5FXHf3DlzgXA1cA7weVN+IC6gv4sZy7wBagJXAcSl7RyazrPJdQCpEMnQ0rglgC1DKeyk+BZnE/fEngs/luEEXB0bLNAX3HUrabNeKC5I+wLvAEbgWUj4wFlgbPD+Baz214H6SS3GBYxNK5KqcCJ2oHl4BbADmsSOFLZ1+wDzgh7hJUY8EJgDnAw/jvtt9gH9uZ9spwDrgTlyInAX0xc39/wzukKkAdzg1ItjPROBeYDxQDLwDnJSyd2Myj4VOltsAnMJ+ttNCHYUpmDi8ARcc1+FC4BFcH8ta4NO4Fsvfgb/g+nra2oJrrVwf7OdXuDAZDJwAPIgLsmF8MDHHCcEHwBPAKbhDsfW4/iQLoFzzqu8CUiGSh1eBnRyYl6SGzSnZ4wbcMn6luEOcybhO5B24wAGYGtx3qFW4VtGBtSpG8cEVGXOALwCfxYXZoZ3Q24LPlcAa4BJcf9Du3r4hkzGUzVqlqfk99SzKobODA+//XTakZI8VuEOcZlxfy1u4lkojrm8GXDAN7mDbt4LbzcF+KoOvD1w3vRfXapp+yLb/jWvlJPhgtqADfUQmNwhP+y4hVaJ8eLUf2AWU8jbrOSoFezwC1zdzHy7OhgNH4/p6HsEFQTEfHFqtw7VmTgWOxR0i/QQXWLNxh1IE29bjWkHnACVtXnMtro+nX/D1MOCnuMOrYZjcsch3AakiqtGdm1xicjGuy3YLF3MdRVT4rsmYD1EUYZhWadYP9oRoH16Baye478HeFB1iGZN6q3IlcMBC50AvirCD9V4rMaYjwl99l5BKkQ4djWs9Lnj6sZG3bBUsk6FyphMZIh46gReAftRQTx3v+C7GmIModbQ/cCZrWei4a3yd7bzmsQ5j2vOEVmmD7yJSyUIH3sZdA9yH11ltSw2bjCJU+y4h1Q4bOiKSEJGVIvKKiLwsIvNSWYCILD3M48+KyDFd3NdYEVnQndfXuLYCS4BK9lJLDRu7s70xaZNkH+RWJzJ0raXToKqzVHUmcBPw3VQWoKqpDLGxQLdCJ/AiB8Zmv8MrKazHmN6ozoX5cw7V3cOrfrhRPYjIAyJy4YEHRORhETloGKOI/EREzg9uPyYivwxuf1ZEbgtu17Z5/o0isipoVX3vkH3licivReTbIpIvIj8QkRdE5FUR+ULwtO8B84OW2VdEZKqILA++flVEJnbwvt7CzSZYwhrWkKC5m98XY1Ivj1/4LiEduhI6JcEf7TrgF8C3gvvvB64EEJEK3KQOTx6y7RI+mP9uJG6QAMF9B/XIi8jHcAMEjg9aVbe3ebgANznEG6p6C/A5YJ+qHosbQHC1iIwDvg4sCVpmP8RNe/UjVZ0FHAPtn53SuCZxpyUraaaF3dk/D63JcgnWapW+fPgnZp/uHF5NAj4KPCAioqp/AyaKyGDgUuAPqtp6yLZLcC2PKbjxzztEZDhuMs1D+3JOB36lqvUAqvpem8fuA15T1duCr88ELheRlbi5+gbhZpc51DLgZhG5ERij2ulZgBdwo6OEN96fHNQYP/L4qe8S0qVbh1equgw39vnAOOkHgMuAq4BftvP8LUB/XFgtxoXQJUCtqnZn+ZelwCkiUhx8LcC/BGE4S1XHqeqHOtxUtRo3hVYD8JSInNrhe4vrTtxkoAPYxBZq2NSN+oxJnQR7Ee73XUa6dCt0RGQSrsP1wEwtv8ZNWYWqrulgs+eD5xwInRuCz4daBFwlIn2D1xrY5rH7gaeAR0SkADcN1rUiUhg89ygRKQVqaDMZqIiMBzao6t24MdwzDvMW//r+9q/z3GGea0x6JPhprl2b01ZXprYoCQ5jwLUwrlDVBICq7hCRtcDjnWy/BDhTVd8UkU3AQNoJHVX9s4jMAl4UkWZcyNzc5vF/D/qOHsTNwzcWeFlEBDdFxYW4mdUSIvIKLhD7AJ8RkRZgO/Cdw7zXV3EL8ZUR500ms4O+DD3MNsakTpImirjTdxnp1KupLYJWySpgjqruS1lVHklM5uPm6NvETKYz9f3FXYxJvyZ+rt/RLxz+idmrx1cki8jpuKkh7smVwAksB+qAYlbxGk3s9VyPiQolQZ/3zw7nrB6Hjqo+rapjVPWuFNbjnca1CfgTMIQkytss812TiYhmHtcqzflBxzb2qn1/x80wXMgrvEwz+30XZHKckqDwgz7MXGah0w6Nay3uTNYwmmnl9dyaz8RkoHoe0oX6uu8ywmCh07FncGtt9uFVVlGbomVqjDlUK3UU8mXfZYTFQqcDGte9wB84sKbCSv5sk16YtKjjNr0tp07GdMpCp3PP4las6sfbbGUXK/2WY3JOI5up4Pu+ywiThU4nNK7NwEMcWFPzBZ6xEegmpZq4Vqs0efgn5g4LncN7FXcB5FD2Ucum3Jqv1nhUx2L9dz10ZoacZ6FzGBpXBf4TtzZnPstZRh1bPJdlsl0L9TTxad9l+GCh0wUa13dwp9BHkiTJMh4lYSuFm17YxU36o9y/ELA9Fjpd9wRudH1/dvIeb/IX3wWZLLWbJTzLPb7L8MVCp4uChfnuw80PVMBLvMReInExl0mhRvaxjU8Gh+2RZKHTDRrXN3HTeBwBwHP8kRbqfdZksoiibOfz+jvd4bsUnyx0uu9J3ETug9lPHav5o++CTJbYxe/1V/qI7zJ8s9DpJo1rC/Bz3ARhfVhDnC02Et0cxn42spErfJeRCSx0ekDjug130eBIQFjCIvax3nNZJlM1UsM6ztMnc3cK0u6w0Om5xbgpMEaRRHmW39PIe4fbyERMglbW8SV9Ul/zXUqmsNDpoWCtrP8ANgNDqKORv1NNK/bfzDiK8jp3sYaHfJeSSSx0ekHj2gjcAySACnawm5f4LUkSnkszmWA9T7CCm6N8erw9Fjq9pHF9F7gLt+RyCevZxFqesGkwIm4LL7Ccy4MTD6YNC50U0LiuB34GDMdNcbqKN3jSgieitrKG5zhP491aUDIyLHRSROP6IvAbYBSQz4u8aMETQVuJs5jzdU20LwDsjIVOav0ZeAy3EKAFT9RsIc5iLtK1apdPdMJCJ4WCDsPHgUex4ImWLcRZwkW6Vlf7LiXTWeikmAVPBFngdEuvlhU2HZOYCG599U8AG4EEs5jJJM4jj3yftZkU2sRrLON/WeB0nYVOGrUJno8DbwOtjGc0x/ApCujrtTjTO0mSrGYpq7hG4xY43WGhk2ZB8JwNXAJsBxqopD/zWUAJg/1WZ3qkhUaW81c2caPGdZ3vcrKNhU5IJCZHA9cCdcAeSujDqVxMBRM8l2a6o569PMfveJdbNa5bfZeTjSx0QiQxGQtch5vkfTt5CCdxFsM53mthpmveYyuLuY96fmgX/vWchU7IJCYDgX8BxuAGiyozmM5kziGfPn6rM+1SkqxnFS9yF0ketqENvWOh44HEpBi4CvgI8A7QwkAqmMeF9GOs1+LMwRrZw/MsZSs/Ap62wZu9Z6HjicQkDzgD+BSun2c3gnA8cxnLqXZaPQNsYR3L+B+a+bHGdY3vcnKFhY5nEpMxwDXAMFyrJ8FIhnIcn6CEIX6ri6gW6lnBP3iT3wEPa1z3+y4pl1joZACJSR/ctTwfw62ttZ8C8pnHKYxgLnl25XhodrKe51lKLT8DnrfDqdSz0MkgEpMpuFZPX2ALoAyjkmM4m36M81tdjmvgXVawgo38D3C/xnWn75JylYVOhpGYlAMLgHnAXmAPANOYQowz6EN/b8XlolYaWc8KVrCWJL8HFmlcW32XlcssdDJQcBVzDLgCNzHYNqCJAvI5huMZzXwKKPZaZLZLkmQbr/ICcep5DvitxnWX77KiwEIng0lMCoETgU8ChcBWIEEZJcxmLsM51sKnm5Ik2MVqVvImu3kTeBBYbX034bHQyQISk3648VtnAq24MVxJiiliJkczirkUUe61yEyXoJltrGAlG9nPbuARYKld6Bc+C50sIjEZDpyD6+9JADuAVgrIZzozGMc8iqn0WmSmaaGOzbzMSjbTyH7gKeC/Na51vkuLKgudLCQxGQycFnzk48KnCYApTGIsc6jgSCTCp9pr2cJm1rKKbbSyB3gCdwq83ndpUWehk8UkJhXAfFzrpxh3jU8tAP0oZRLTGcEM+jLcX5UhamIvO3iVdbzNu++3BB8DXta4NnuuzgQsdHKAxKQEmAt8FBiM6/fZBbg/tOEMZiIzGMIMiujnrdB0aKWR3axhPa+zkQZAgDjuMGq1xtUWPswwFjo5JDjVPhY4DjgJKAEagXeBBIIwiuGMZDyDGE8Zo7NujJei1LONPWxgC5vZSAMJ8nAhuwhYESyAaDKUhU6OCk63TwJOAI7G9f004S42dP0/RRQwljEMZzwDOJIShiK+Ku5EE3vZy3p2sIEN7KSeYtyiAvXAYmA5sMlOe2cHC50IkJiU4S42nAHMBsqCh+pwVz27Q5C+FDOCYQxiGBUMpy9DKWYQeRSEUqiSpIk91LOT/WznPbaxjffYRyFQFDxrO/AisBZ40055Zx8LnYgJDsGGAROAOcBUXCtIcH1Atbgwcr8YglBJfwZRSSn9KKaUIsooopQiSimklAJKyaek01ZSgmZaqKWVOlqoo5k6moKPemp4j3fZxV5a6YsLxbygplpgBfAKsEHjujcd3xcTHgudiAsOw47ADbeYAEwERrR9Ci6MWg75nOzBy+XjWixF8H7rpSDYl+A6wDfhOoI34Qa9brfDptxioWM+RGJSAAzCnQkbgmsZDQT6AwOAfrgAUejSEoKCa7k0Avv4YCDre7ihHbtwnd17Na49CTOTRSx0TLcFh2h9gNLgo7MDq1bc4Vqd9b8YsNAxxoQsupfJG2O8sNAxxoTKQscYEyoLHWNMqCx0jDGhstAxxoTKQscYEyoLHWNMqCx0jDGhstAxxoTKQscYEyoLHWNMqCx0jDGhstAxxoTKQscYEyoLHWNMqCx0jDGhstAxxoTKQscYEyoLHWNMqCx0jDGhstAxxoTKQscYEyoLHWNMqCx0jDGh+v8RpUwRTc5L/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ApEe2rYNi4k7ChzMfaOqWZeE0cSfhw5kHNOVmWjhN3In5GVsv4cyxcJr4k/AtZw+gKTvDwmniTuKGM5ijtjvQlJ1uZ2tN3MmP9Q5j2XJmAGlANNNWrTbxJ+Z3UMUynDmAZqWTalcHmTiU+OHMz7FgmriU8OGkvolIDPdpTGeJeTjTYr2v3fU0xXCfSaOqiaZzV7F5YQreZotLSEqKptBMCrubY7zrWIazCSCqaCRKJDWF1BjuO6G9sJ2ay7aQUZ/l5+6JJJAJdIv1TmMeToDmCE0Wzs4x8z2qnkgljyzEdy0JLtYNp6dwRmnKBO/rH8az9XXUn7kC3dg99uNvSSrmh2OxPCHUhLv1huaIHXd2xC82UjV8DRkbu9t4cQztivUOvbWcMdxvwmiMED1/Gbv/mU0+mb6rSTo7Yr3DWIfTWs6jNL+a2ulrSa/KJc93LUkq5uH00q1titAYw/3GvW99QOUpm8ipyrX20qPtsd6hl25tY7OF80jsaqTpk8tpWN6NnjH9P2Xakrgt5+wyVVxAU6r2UB2r/carv2yjeuAKWN4t9uNrpk0JfcwJsAdI31YT+zNf8SIahZkrqHwqlXyybewyRDbHeoexDuc2oN/GSgtnW9bWUX9mObqpGz1912IOsCLWO4z1TAgbgex126iM8X5D7+cbqBqxhoxN3WzsMnSUOqAi1ruNdcu5EchYuYXtUUVTxLpteyNEZyxj9+s2dhleQrnOUo31bmPdcu4EdG8TkZo6dsZ436Hzr2pq+y+l6fUc8uxjKtTe97HTWIfzo2PNHbvZFuN9h8o3PqDy1E3kVNvYZTyI+fEmxD6c23EXIsimKrbGeN+hsKuRptELqf2h0lPTvKzyZtov8VvO2WXagAto9tptyRfOP2+jumAFvG9jl/FmoY+d+vjkXgPkLt3AFg/79iIahZLlVBVX0qMhO/bTXZgOUDbpLF3tY9c+wvkBkL1yC9W766nysP+YWlNH3aDF1P82g3xS7LRP3BHm+Nq1j3BuAhRg7XY+8LD/mHmwgsqRa8nc3I1s37WYo/aGrx37COe6ln0vXJeY4ayPEDlrMTU37aVnJMOmY4lzydNyzi7TemAlkPeP5ayNRBNrqsx3q6jtv5TmN3LoYZ3YOKdUAst87d7Xqfx5QPfqOhq3VLHBUw2d7r9WUfmJzeTU2Nhlopjj48qgFr7CubLlQfnm+O/a7myk8YSF1P4IG7tMKMJsn7v39Ye0CagFMt9cySpPNXSK57ZSPXAFssLGLhOLEgGe91mCl3AGN17/C+j1rzVs29PAbh91dEQ0Clcup+rSKhu7TEjKXJ2lMb/BujWfXbAlBOtPrIuzIZUP6qgfuJj639vYZeJK4Wn/JfjTctWFLFj38TFo2N2/nspRa8nYYmOXiUtR4E++y/AWztllWosLaI/ny1hZ38geX7UcifoIkcmLqbm5wcYuE57yrs7SmE9Lsj/fZxbfAfIam4kuWs8Cz7Uc1NtV1B6zlOa5NnaZHFJ43HcJ4D+c83GX8qU+8y7zo647ESq3rqLyjM3k7Laxy+QQpQ540ncZ4Dmcs8u0Gngb6PvBVmrWbw/Psef2RhoLF7LnXhu7TC5RSnWWhmL0IAx/dK/i1j/k78v4l+daAHh2C9WDypGV3cj1XYuJsTTu811CizCEcw3uooQef13I6uo6f9NmRqNw+XKqLqsmrzHLxi6TTjPzdJYu911GC+/hDC5I+CvQU4F5q5nvo45Ve6gvWEz9H9zYpUlGqdzru4TWwvJnuBBoBNJ//w4LmyOxXUX4vvVUjVpHxlYbu0xeEbYj/NF3Ga2FIpzBbWT/BPptq2Fv+WaWxmK/9REiZyyi5uuN5Edt7DK5Rfm+ztJQLU0ZinAG5uAmuZbfvsWb0SjRrtzZm5Xs7reUyFu59OjK/Zg40MwO0vmZ7zL2F5pwzi7TTbj5QXsv2cDOxRVdd+x580oqJ28htzaXjK7ah4kjTXxfZ2nolqUMTTgDzwHdAfn5K7ze0MzeznzzbQ00jFxI7f1iY5cm0MQ2snnQdxltCdsf6ErcVUP9N1dRN3dF583f8vRmqgavJHWV3XdpWovwP2E71mwRqnAGwyp/wN1KlvqLV3m3o9NnNkfRTy+j6t9qyG/MsvWhTStNfEgWD/su42BCFU6A2WW6GXgZKKhvJPKXhfzjaN+rvJa6gYvZ+6dMG7s0bdjLjTpLQzvBXFj/ZF/ALVGf9du3Wb6luv2TgN27nqrR68ncZmOXpi27eUPv0T/7LuNQQhnO2WVag+ve9gd46k1ePtLX7okQOW0RNbfa2KU5mAiNNDLTdxmHE+ZjsDeA84Hur7/Pxk+dzLKRAxhzyBfsYveFFWTWJvPYZRT4Be6c99VAJe5jrg4oAC6l7f/rc4AFuI/r84HhwfOrgJeC950ATA6efxbYCowEpgXPvQ70A07ozF+oC9TwY71f1/su43BC2XICzC7TRtx9dX0AHniZv+1tov5g299UTuXZ2+iW9GOX7xD8Fwv8HTgNuBnIou31srbhpk7+KnAN7krnaPD1Ai7kXw222QZswQX8K7hbFvYCu4EPCX8w69lAI3f6LuNIhDacgcW44ZV+63dQ++w8DjhG2LKXhuEL2fNgCj01NcnnKajGtXQTgu8VWAuMDr4/ibaXgS0HxuAC1xPohQvah8HjXsHPxgTbpgLNuPBGcCuuvgqc3bm/TqeLotRynT4U3pNArYU6nLPLNAo8hrvfM+P37/D++5tY0vLz322masgqUlfbfZfOS8B0+Ogjqg7XWrYcefcAatp4XU3wM/bb7mDP9wVygIeBQtx65YrrNofZLh7Tn+orvss4UqEOJ8DsMt0IlAKDAH44mxcq66i6ZBnVV9WQ32Rjl045kEvsAnI+cCNwOq7VPAd3luBpoCxGNbRHLRtYxZd9l9Ee8fKH/RquszZ8XQ06vpTtGyYzPPwfLTG0ARfQVbguZwOuJd2L63qmcmBL2GL/FrX1dgd7vsUKYADuhr9dwBXAE8BYCM3RfzONbOIyfUkbfJfSHnHx5z27TCPAr7c3k7+8kcnbP2Q+Fbzqu65QmQbcCnwduAw4DvhM8O97wTaLcN3Q/RXiTvY0487u7gQG4lrhncFzzcE2rV8fwZ2AOiP4eUt3uuVYNCw28l19Suf5LqO9RP0totRu/UbLtJ0RvhB1J4miXMg15HG877pCZy3wFu4s6y7cUEo9roX7NK6/tAJ3pnVK8Jo3cGdyU4AZwIjg+ZW4FliBk4FPttrP27hj2pODnz+LO5s7AnfsGwbbeI1/MFXLtUtvQewKcRVOKRTB/clNASrIJZvz+AJZ9PJcmgmjaipYyHh9Vat8l3I04qJb20LLVYFncEdYx7CHeubyFM0HH/80SaqOapZSHK/BhDgLJ4CWawPwU9xRTh7b2MV8fkeCrZBtOqCRvSzhBv27LvZdSkfEXTgBtFy3A/fhzh1ms4YK3ve70KkJiShR3uN/WeN/lbCOistwAmi5rgZ+hjvNkc5illDB657LMj4psJJHeY+7g0OguBa34QTQcp0P/A4YDKQwl9fYGsohcBMLa3iRBXxVy+Pj8rzDietwBl7ETas5BIBX+IsFNAmt5DXe5Wot106dd8qnuA9n0H15CnfR2FDAAppsypnDfK7Rcq30XUpnivtwAmi5NuEuw14AHAuIBTRJlDOHMq7Scv3QdymdLSHCCaDl2ogLaEsL6gK6xc/aKyYGEjiYEGdXCB0JKZQM4AagCFgPKGdyDkP2ufDMxLMoUZbzT5byuUQNJiRgOGGfgE7EBTTKeMZxAsWk2LxCca2ZvczjBdbxtUQOJiRoOAGkUNL5+DrcDUATwxjCRK4kzWbki0v11DCX37Odb2u5bvFdTldL2HDCRxfKnw9cCWwG6ulHL86khCx6+63OtEsVW5nDw+zmHi0Px7LwXS2hw9lCCmUi7r793UAVuWRzNp8m76M55kyYfcgq3uJHNPFYcOIvKSRFOAGkUIbhbkVOw03qCKfyCY5jqh2HhlQzDSzmHcq5B3ghHu/J7IikCSeAFEpf4Cbc1UQbgQiDGcAkLrN7QkOmhi3M5Z9U8ZPgMs2kk1ThhI/O5F4KXABsB2rJIoPJXEBfxvutzqAoa1nCPJ4jys+T4cTPwSRdOFtIoYwBvoybhmoTAOMYQyEzSLepNr2op5Iy5lHBI8DsZDq+bEvShhNACqUncD0wDjeFciM5ZHEaUzmGIiTJJ6mOlSjNrGUxZbxLMw9puS73XVIYJHU4AaRQUoGpuEkdI7jFBpShDORkLiLHLaZkukgl63iXheziNeBxLY/faUU6W9KHs4UUSj/gKtz8uDuA3aQgFDGJYUwhlUy/FSaYRnazlPmUswh4FFiaCDdIdyYLZyvBRQvjgM8B+biubjPdyWECZzCASaSQ7rHE+NdMHWtZzCJW0cTzwItarjZBWxssnG2QQsnGnc29CLeI7xYgSg9ymcCZ9GciKXEzW344NFPPehawkPU0shR4ItGvje0oC+chSKEUAJ/CLaLXgLt4QcmnOyczmWOYYBcwHEaEBipYwALW0kAFbjWVxcl2QcHRsHAeASmUwUAxMAk3d/o2WkI6hiL6M4EMunstMmz2spMKlrCMzexlIy6UixJlfp9YsHC2gxTKUOAS3AIEDbiQRkghhdGM4lgm0YNjPZbolxKlknJWsoI11OBOrD0DlGm5NnuuLu5YONspOGk0FLfo3Rm42SR2AnsA6E8fTmAifRlLGjneCo2lRqrZzBKWsoEaGnGrtbyA6742ea4ublk4O0AKpQeuq3sBbv3nOlxroaSQwnCOYwgn0otRCXcPaSM17OA91rCGChpwY8RvAK8DG2xYpOMsnJ0guJBhFG5trXG4xfBqgCpcUIVhDGUQhfRiZFxeZK9APVvZQTnrWMtGmnGrfm7HtZLztVxrvdaYYCycnUwKJR84ETgLGI4L6h7cYnzuDGU+3RjMUPowhDyGkk2/0F0qGCVKHZuoYj3bqWA9O6kjB/f7VONayIVAhbWSXcPC2YWCoI7CDcWMwf1hC+6m7xpalpjNIYshDKY3BeTShxz6kEXvmF3wEKGBenZQzw5q2c52PqSCShrJxbWOKbibA97ELaG70YZCup6FM0akULJwy0YMA07CtaopuLDWBV/1uA6k04d8etOHPPqQTXfSyfnoKy34SiXroG2uokSop5k6mqijmToag8d11FDFDnawnSoagRygGx9/gGzFrYVdDlQAldZCxpaF05NgArKBuEmwR+OC26/1JrjhmgagEXelUjOtw9si5SDxjH60bRqQHnxlwD4np1JwrfgG4ANgFa6r2q55ekQkAiwN6o4AN6nqW+15j8O8/1uqevohfv4acJvq4W/MFpFjgdNVtbSz6usKdgmaJ8EQw7rg6zUAKZQ03FnfPrigDg3+zcMtd5iL++Pft0t58A5mS8u8FxfAnUBlsM8tuDPLO7Rc6zrhV6pX1ZMAROQ84C7ccXenOFQwj8KxQAlg4TRHJhio3xZ8vbf/z6VQUoAsXBc0h0PP2F9P0FX2cAFAD9yHACLyOPBHVX0u+P4p4GlVfb5lYxF5EPibqs4WkT8Blap6vYhcDxyvqt8SkVpV7RZsfztwDe5j6UVV/Uar90oBfo2bhmYWcDdwNpAJPKiqDwfPnSAii4DHgJeB3+B6FSnAZ1R1VZf8l2kHC2ccCU7CtByfhk128MeehVszdUrw/K9wE6s9JyJ5wOnAtfu9dg4wGZiN6+oPCJ6fjFvi8SMicj5wMXCqqtaJSOthqTTcolbLVPX7IvIloFpVJ4lIJvCmiLwMfAPXBb4oeM8HgP9T1adEJAPCcb10wqyVYryrV9WTVHUUMAN4XEREVV8HRohIX9z9ss+qHtCSzwEmi8hoXI9hq4gMAD4B7H/cOg34jarriqvqrlY/e5ggmMH35wIzgw+Nd4HewIg2an8buCNokYeqhuMWNgun6XSq+jbuuLlv8NTjuG7odbgu5/7bf4i7f3YG7iqjObiZKWpV23Vi6i3gHBHJCr4X4N+DD42TVPU4VX25jf2X4m5sqAdeEJEp+2/jg4XTdDoRGYXrGu4MnnoU+A8AVT3gWDrwTrBNSzhvC/7d39+B60QkJ9hX627tr3BXKz0tImnA34AbRSQ92HakiOTixpk/uotIRIYBa1T1fuB53FVe3tkxp+ksLcec4Fqsa1Xd7WGqulVE3geeO8Tr5wDnquoHIrIed9b6gHCq6ksichIwX0QacWG8o9XP7w2ObZ/ArZVzLLBARAR3qeElwBIgIiKLcR8cmcBnRaTlxvofHMXv3+lsnNN0uaCVWwpMUNVq3/XEC+vWmi4lItOA94EHLJjtYy2nMSFlLacxIWXhNCakLJzGhJSF05iQsnAaE1IWTmNCysJpTEhZOI0JKQunMSFl4TQmpCycxoSUhdOYkLJwGhNSFk5jQsrCaUxIWTiNCSkLpzEhZeE0JqT+H3qGcGrf6SmXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i=0\n",
    "for key in matches_city:\n",
    "    venue=key\n",
    "    venue_matches = matches[matches['city']==venue]\n",
    "    venue_matches_batting_first_wins = venue_matches[venue_matches['win_by_runs']!=0].count()['win_by_runs']\n",
    "    venue_matches_bowling_first_wins = venue_matches[venue_matches['win_by_runs']==0].count()['win_by_wickets']\n",
    "    df_venue_matches = pd.DataFrame({'win':['By runs','By wickets'], 'Count': [venue_matches_batting_first_wins, \n",
    "                                                                               venue_matches_bowling_first_wins]})\n",
    "    df_venue_matches.set_index('win',inplace = True)\n",
    "    plt.figure(i)\n",
    "    i+=1\n",
    "    plt.pie(df_venue_matches['Count'], labels = df_venue_matches.index,autopct = \"%.2f%%\", shadow= True,\n",
    "            colors = ['orange', 'green'])\n",
    "    plt.title(venue)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function for a particular venue\n",
    "def venue_data(venue):\n",
    "    if venue in matches_city:\n",
    "        venue_matches = matches[matches['city']==venue]\n",
    "        venue_matches_batting_first_wins = venue_matches[venue_matches['win_by_runs']!=0].count()['win_by_runs']\n",
    "        venue_matches_bowling_first_wins = venue_matches[venue_matches['win_by_runs']==0].count()['win_by_wickets']\n",
    "        df_venue_matches = pd.DataFrame({'win':['By runs','By wickets'], 'Count': [venue_matches_batting_first_wins,\n",
    "                                                                                   venue_matches_bowling_first_wins]})\n",
    "        df_venue_matches.set_index('win',inplace = True)\n",
    "        plt.pie(df_venue_matches['Count'], labels = df_venue_matches.index,autopct = \"%.2f%%\", shadow= True, \n",
    "                                                                                colors = ['orange', 'green'])\n",
    "        plt.title(venue)\n",
    "        top_player_of_matches_venue=(venue_matches['player_of_match'].value_counts()[0:5]).to_frame()\n",
    "        print(top_player_of_matches_venue)\n",
    "    else:\n",
    "        print(\"Invalid Query\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter Venue Name:Mumbai\n",
      "              player_of_match\n",
      "RG Sharma                   7\n",
      "KA Pollard                  7\n",
      "HH Pandya                   4\n",
      "SR Watson                   4\n",
      "SR Tendulkar                3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "venue_data(input(\"Enter Venue Name:\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>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",
       "    </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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city                        team1  \\\n",
       "0        1    2017      Hyderabad          Sunrisers Hyderabad   \n",
       "1        2    2017           Pune               Mumbai Indians   \n",
       "2        3    2017         Rajkot                Gujarat Lions   \n",
       "3        4    2017         Indore       Rising Pune Supergiant   \n",
       "4        5    2017      Bangalore  Royal Challengers Bangalore   \n",
       "..     ...     ...            ...                          ...   \n",
       "751  11347    2019         Mumbai        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad               Mumbai Indians   \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",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           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",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \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",
       "751               9       HH Pandya                           Wankhede Stadium  \n",
       "752               6        AS Yadav                  M. A. Chidambaram Stadium  \n",
       "753               2         RR Pant                           ACA-VDCA Stadium  \n",
       "754               6    F du Plessis                           ACA-VDCA Stadium  \n",
       "755               0       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium  \n",
       "\n",
       "[756 rows x 14 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**A team at each venue**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "def team_at_venue(team):\n",
    "    team_at_venue_df = matches[(matches['team1']== team) | (matches['team2']==team)]\n",
    "    team_venue_matches= team_at_venue_df['city'].value_counts()\n",
    "    team_venue_matches = dict(team_venue_matches)\n",
    "    i=0\n",
    "    for key in team_venue_matches:\n",
    "        team_venue=key\n",
    "        team_venue_matches = team_at_venue_df[team_at_venue_df['city']==team_venue]\n",
    "        team_venue_matches_batting_first_wins =team_venue_matches[team_venue_matches['win_by_runs']!=0].count()['win_by_runs']\n",
    "        team_venue_matches_bowling_first_wins = team_venue_matches[team_venue_matches['win_by_runs']==0].count()['win_by_wickets']\n",
    "        team_df_venue_matches = pd.DataFrame({'win':['By runs','By wickets'], 'Count': [team_venue_matches_batting_first_wins,team_venue_matches_bowling_first_wins]})\n",
    "        team_df_venue_matches.set_index('win',inplace = True)\n",
    "        plt.figure(i)\n",
    "        i+=1\n",
    "        plt.pie(team_df_venue_matches['Count'], labels = team_df_venue_matches.index,autopct = \"%.2f%%\", shadow= True, colors = ['orange', 'green'])\n",
    "        plt.title(team_venue)\n",
    "    plt.show();\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter team name:Mumbai Indians\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-61-39d32b570735>:13: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(i)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3t9JmPEyzy0iI96x4L6Cd8UAJBzPedyFR8kQtLb5ryHIjgVN9FxG2sJ6E0Exxbs1Y2FNlNuNhJnjfFA5NWCUu+cA0xtGLfPvH1xXbChhc00Sz7zqy3CUkxOtVX6EJKzAWKGS0bQJ3mRCbV2UzHqZZCeD10rkwhfUoIEkpcd+FRNGjO6n3XUMO+PiBX5I+oQhrMBnadIYAvSnxXU8UvdRoF+ZnwHSfjYcirMBw3FHgtFybmQvW59kfuQw4goR4W3YzLGGdCECpXZvZXc159Hl5Jzt815HlYsCJPhsPg6OBWvpbWHtiblV6pyc1gMdNYe9hDUYtTWIQSiH9fdcTZc/aohqZkLthxe2vFjKSzE3nnKVWYH/sMuBEX0MPwxDWUYBQysgDvtJ8qJp8Bm1qsFM4adYfONJHw2EI60Sgib4M9V1I5Ak8ZIP6M8HLpnAYwnoYsIs+DPZdSDZ4rDp9cwmbPU7w0ajXsAZzLY2ggEYK7SLqVHi12cZVZ8BYH4367lkHATCEQbm83moqbcmnpLGFpO86spyX6YZ8h3UwoJTYJnCqJGMUPG2D+tNtFAnJeOcShrDGGGBhTaWHd2JnXNOrEDJ/QNR3WMcATfS284Op9HwDeb5ryAEZ3xT2HdZRQD2FNpF3Kr0do9h3DTkg58JaAjTarPup1ZhPv+U1Nk44zXIurAOwsKbFg5Xs9F1Dlht14JeklrewBnMuFQHN5FPkq45s9VStnb5Js5zqWYuAFmLEyLMT+an2RtK2VtIsp44G9wWUQvJtOETqVRVQWtlkQw/TKOPT6PjuWSHmfb85Owny6HYbHJFG+Zlu0GdQ8oIKrF9Nk3/sYrfvGrJYTvWsseC/1rOmyctNFPquIYtlPKwZ78rbcD2qhTVt1hcwomCVXYyeSqLEkjGaJEZtU4bb9hnW1p7VNoPTRZBmO9KeDr0g86cbfW8GC822ApqJpIz/u/UZVtejNthBEBNJDZlu0GdYmwClkWaSNtrGRE5lphv0Gda9PWrSelcTOTkV1r2bES0WVhM5GR9wEo6etSXz2//G9FBO9ay797TfRK3HOozpjpwLqzsiXG8TU5vIeT/TDXoLq5ZrE1ADFFBvSxWayHk70w36HupXAfSmxsJqImdNphv0Hdb3gd7ssrCaSNmsszTj0736DusmoDe2mJKJloz3quA/rNsAoZo6mm1iahMZORnWKgiGGtay2W8pxnTaCh+N+g5rxZ4aqi2sJjIW+2jUd1h3ArVAIZUWVhMBSgvwmo+mvYZVy1WBt4D+vM8mn7UY00nLdZZ6GXHnu2cFWAX0ZRs7aLYxwibkhJd9NR2GsG4AFIBq3vVbijEHlNNh3UzrGOFtmR/CZUwXLfDVcBjCugN3bWAR71pYTYgp63SWrvbVvPewBgeZXgEGsYXtNNrqZyakhHk+m/ce1sAKWmfor7Le1YSWhRVYizvIJGyxsJoQUhqAf/osIRRh1XKtwwV2AGtYQ5Jm3zUZ0858naVeVzcIRVgDi4GBNNDITj8DpY3ZL+EB3yWEKazLaT2Fs5Hlfksxpg1lN/B332WEKaybcRej92MV5bTYQsAmJJL8Q2ep97MUoQlrcArnOaCERpqoZKXvmowBII8/+S4BQhTWwBJaN4XXsdRvKcYASSqBx32XASELq5ZrBW7WuGLWsI4GtvmuyeS8e3SWhuLsRKjCGngGGAjAu34u8jUGAEWJ8UvfZbQKY1jLcBOAF/IGZbYOjvGmmWd1lr7lu4xWoQurlms98BQwjN00sYXXfddkclQeP/BdQluhC2vgeVxtMZazGA2udzUmU5pYqbP1Od9ltJXvu4COaLlulbi8BkxmK1uoYiUlHJ6xArbxwVPgVcDpwABgPrAV+Fdg5Id8RhL4HdAfuCJ47CHcTMkKlAIXAb1wlzO/ittTvwz3W1kPrATO7fmPY7ohxo98l9BeWHtWgCeB3gAsZX5Ge9fBwJeC23VAATAJGAp8Bji4E5+xKPicts4JPvPfcMFsPXy2LHh8NO5YuOK2LU7tyQ9huq2ZzeTxN99ltBfmsL4FvAOUsJmtbOdNL1WsBUqAYmAI+wawIztx1R/b7vHewVcFmmk9o+wkgSbcb2QZMB4o6m7Rpkda+E5YTte0FdqwBiOa/k7raZwy5qPBhOCZ9CZwRBff8zhwFh8MY6u5wH/jNrWnBY9NA/6AC/kY4PU2z5nM2s16eoVjxFJ7odxnbWMlbvbDkVSwjQrKGLZPf5U+zUA5MKML7ykH+gIHAes6eP4iXC86D3fpwjHA0cEN3D7xCbieeSnuT9XZhPjPapZp4Rs6SzPfKXRCqP8JBL3rA7jDNMLrPJfRa13XACOAfl14z3u4wN4K3I8LbPuLq2K43rr9Igy7gI24/eOFwKdxm84dhd6kXgPL9Kc6x3cZ+xP2nhVcH7MMOJRKKtjAi4zhoxlp+Q3gyC6+ZwZ7e+J1wEvAxbj91ErcUWDFBbr9/u8/cUedwe2/gtuUbsJkgvIV3yV8mFD3rLCnd52DO9wS42VeoIHKtDfciDu4NKnNYyuBn+NmOk4AdweP7wL+coDPU9z+6q+DWw184E9O6+IhBwVfjwR+A7yLO9hk0quWx/Qn4Tqv2p6oRmO8gcTlGuBkYANxxjN1z9lLY3qmmQbqGKc/1/d9l/JhQt+ztjEH19/1oZw1dr2rSZld/DjsQYUIhVXLdRdu43M4AC/zuM0mYXqsltVsDNcY4P2JTFgDC3HHaIdQxS7e4gnfBZkIa6GZnVyu90djXzBSYdVybQH+DPQB8lnCEqpY5bksE1XbuE3/V5f4LqOzIhVWAC3Xd3HHVUcDsICHaaLGZ00mgqp4g2e40XcZXRG5sAbm4c6/DqOGepbyoF1EZzptNzWs55NaHs6RSvsTybBquTYDv8etj9OH1axlEws9l2WiQFE2cL0+qJFbpiWSYQXQct0C3IkbECi8wNNUs95vVSb03mcOL/Nn32V0R2TDGlgY3EbRQpL53MdudniuyYRVJatYzBXBqLjIiXRYg//pdwFbgCFUU8ci/kaLjaY17dSwjaWcp0s0shPwRTqsAFqutcDtuJ+lPxvZwpt2wMm0sZs6lnGFzo/efmpbkQ8r7Nl//QXuOpZClrOS9X7X0jQh0UIzy7lRn9AnfZfSU1kRVgAt15W4AROjgBgv8TybWOS5LONTEqWc37CK//FdSipkTVgD/wSexk1pJsznCSps3uGcpCgruZcybojqAaX2siqswS8lgZtb0M1B+AyPsN3We80pCqxgHku5Tss1ay72yKqwwp4BE3fgluEYg6I8zRx2EJplEEwaKbCKJ1jK1cGVWlkj68IKEPw1/S1u8pTRtJDkSe6l0gb9Z71ynuV1Pqvlut13KakWmZkiukPiUgTcgJvgcwMxhDM4n6Ec47k0k2pJkqzgaZZxVXB2IOtkdVgBJC79gOuBCbgZjeBUZjCKk3zWZVKohSZeYx5r+JKW6+YDvyGasj6sABKX3riFMI7BrSKjnMh0DuEsv5WZHmuknkX8nQ38Z7b2qK1yIqwAEpcC4GrgFFxgkxzFERzOhcQiMSWraa+eal7gDrYyW8t1h+9y0i1nwgogcckDLgU+hpuOu4nRjOAELqOQAX6rM12ynY28xK+p5tZgTd+sl1NhBZC4CG5Bipm4xRtrGEBfTuUSBjDWa3HmwBTlbZaxmF8Ad2u55sxFGzkX1lYSlyNwB56agG3EEE5hBiOZ7rk0sz9NNPAaC1jLz4GnojbTQ0/lbFgBJC4jgC/jLmB/D1DijOdILqCQ/n6rMx9QTQUv8BhV/FjLtdx3OT4cMKwi0oJb9UWAFuDLqvpSygoQeUlV99ubich84AZVfbUTnzUWmK6qiU63H5c+wGdxs/1vAhroS29O5hOUdnmxR5NqSVpYQxlLmEOS32q5pn/plJDqTFhrVLVfcP8c4CZVzczCUHQ5rKcFrz2vS224/diTgKtwf5DcKYCjOILD+Dj59Ola1SYlatjCQhaxlQTwYC7tn3akq8MNBwBVACJyl4hc1PqEiNwjIhe2fbGI/I+IXBDcf1BE/hjc/7yI3BLcr2nz+htF5A0RWSoiP2n3WTERuVNEfigieSLyMxF5RUSWich1wct+ApwiImUi8nURmSwii4Pvl4nIhI5+KC1X1XJ9AbgZd1pnHFDIMt7kSX5jS3VkWJIWVvMqj5BgK9/Scr0v14MKnVvysY+IlOFWCh0BnBE8fgfwdWCuiAwEpuPOY7a1AHde82FgZPB+gsf+1vaFIvIx4ELgBFWtE5GSdnXeA7ypqreIyBeAnap6vIj0Al4UkSeBb9GmZxWRXwK3q+o9IlKImw1xv7RcKyQuPwPOBC4DGthBBY9zHxM4hCP4GH32WajRpFIl63iFpWznAWCOlmud75LCojNhrVfVKQAi8hHgLhE5QlWfE5Ffi8gQ3AqkD6hq+4WOFwBfE5HDcUsHDxKREcBHYJ+1MGcAf1J1vxzVD+yb/C9wn6reEnx/NnCUiFwSfD8QN5yw/eVQC4Fvi8goYI6qHvDKm2DW/yclLiuAzwOHAlt4i7W8zW84nmmM5TTy6HWgzzJdUM9WyljCOlYAvw8mEzBtdGkzWFUX4qZOGRI8dBdwJfA54I8dvH4jUAycCzyPC++lQI2qVneh6ZeA00Wkd/C9ANer6pTgNk5132k7ggNNFwD1wDwROaP9a/ZHy3UDcAvu6p0iYAxJhJdZxGP8ki0sIUlOnTpIi2bqWMELzOVR1vF74GYLase6NMxORA7DbUq2Xn50J7AYeF9VV+znbYuAr+E2n0uB+4Nbe08B3xWRe1o3g9v0rncApwL3icingCeAL4nIs6raJCITgY1ANew95SIihwBrVfUXIjIGOAp4trM/b9DLLpS4LAPOw/3RaWAXFTzDIwxmAUdzCkOYQiw7LzdMm2YaeJcyylhHAy8C92f72N6e6so+K7ge7WpVbQFQ1S0ishK39sz+LADOVtU1IrIeKAke+wBVfVxEpgCvikgjbomMm9o8//+DfeO7gSuAscASERHcSKSLgGVAi4gsxf0h6QV8VkSagPeBH3Xi591HMIPivRKXF3D7skcCdWxjK8/wCKU8zxROtdB2QhO1vMfrvM577GYt7ve5OlumXkmnHg2KEJEi3DnYY1V1Z8qqCrHgNM8hwKeAyUAd7o+FUspAjmAawzjGTve000Al71DGMjbRzPu4ratXg60X0wndDquIzMBtnt6qqrelsqgoaBPaT+J62nqgAkhSQD6TmcwYjqcfI33W6VWSFqpYxVusZi3VuK2bB4AlwfQ7pgtyerhhKrQJ7TnAcbhZgLbhwgujGcFEplLKJPIp8lZoJjWwnY2U8SabqKUFeAe3q/Sm9aTdZ2FNIYlLCe601Dm4A101QCWgxIgxnrGMZnIQ3OzaTK5nK9tYxVreYyONuAskWs8AvGv7pD1nYU2D4EL3w3HngyfhDsztAnawN7jjGEmcQYyjdwQHWihKHZuoYBVvs54KwJ0KfBd4HCjLletMM8XCmmYSl2LcgahTgIm44FbjguvO0xbTj4MZxxAOoZhxFDLQT7UfIkmSOjaxg/VUsJ532EEDfXA/z/vAC7ij8RusF00PC2sGSVwG4YI7nb3BBdfr7oJgOa1i+jGM4ZQwjAEMp4jh9KYU2fP69GphN/VspZYKqqmgki2sZwdN9GXvkM13gBeB5cAWC2j6WVg9kbj0wk2ROgGYCntmqRCgAbe/W09rgAvJZwilDKSYfhTThwH0oj+F9KeAImIUEqMg+Jq/T7CTJFGaUZpJ0kQjNTRRzW5q2E019VRTyy62spVKGnGjtvq2qWkzsBQ3F/P6XJjzKGwsrCERzHE8GhgOjA9uw3BhbQ3e7ja3RtzlfB0rJJ888mimhSbanybJww0YKQxureOcFbffuQPXc64D1uLCWYPxysIaYhKXQlxgh+JGfh0UfF8KDAIKcAHrzBhlYW8Ym3BHqbcHX7fi9jsrgAo7MBROFtaICs7vFra5FQS3Qtww0iTQHNxa2tyvBRptHzN6LKzGRIQNOjcmIiysxkSEhdWYiLCwGhMRFlZjIsLCakxEWFiNiQgLqzERYWE1JiIsrMZEhIXVmIiwsBoTERZWYyLCwmpMRFhYjYkIC6sxEWFhNSYiLKzGRISF1ZiIsLAaExEWVmMiwsJqTERYWI2JCAurMRFhYTUmIv4PrBln0hmwG/4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "team_at_venue(input(\"Enter team name:\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Two teams head to head**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def both_team_head2head(team_a, team_b):\n",
    "    temp_a=team_a + ' Wins'\n",
    "    temp_b = team_b + ' wins'\n",
    "    both_team_head2head_df = matches[((matches['team1']== team_a) & (matches['team2']==team_b)) | ((matches['team1']== team_b) & (matches['team2']==team_a))]\n",
    "    df_head2head_matches = pd.DataFrame({'Category':[temp_a, temp_b], 'Count': [both_team_head2head_df[both_team_head2head_df['winner']==team_a].count()['winner'],\n",
    "                                                 both_team_head2head_df[both_team_head2head_df['winner']==team_b].count()['winner']]})\n",
    "    df_head2head_matches.set_index('Category')\n",
    "    df_team_a_record = pd.DataFrame({'Category': [\"Batting first wins\", \"Bowling first wins\"],\n",
    "                                                 'Count': [both_team_head2head_df[(both_team_head2head_df['winner']==team_a) & (both_team_head2head_df['win_by_runs']==0)].count()['winner'],\n",
    "                                                           both_team_head2head_df[(both_team_head2head_df['winner']==team_a) & (both_team_head2head_df['win_by_wickets']==0)].count()['winner']]})\n",
    "    df_team_b_record = pd.DataFrame({'Category': [\"Batting first wins\", \"Bowling first wins\"],\n",
    "                                                 'Count': [both_team_head2head_df[(both_team_head2head_df['winner']==team_b) & (both_team_head2head_df['win_by_runs']==0)].count()['winner'],\n",
    "                                                           both_team_head2head_df[(both_team_head2head_df['winner']==team_b) & (both_team_head2head_df['win_by_wickets']==0)].count()['winner']]})\n",
    "    plt.figure(1)\n",
    "    plt.pie(df_head2head_matches['Count'],labels = df_head2head_matches['Category'], autopct= \"%.2f%%\", shadow =True, colors=['orange', 'green'])\n",
    "    plt.title(\"Head to Head\")\n",
    "    plt.figure(2)\n",
    "    plt.pie(df_team_a_record['Count'], labels = df_team_a_record['Category'], autopct = \"%.2f%%\", shadow= True, colors = ['orange','green'])\n",
    "    plt.title(team_a + \" Record\")\n",
    "    plt.figure(3)\n",
    "    plt.pie(df_team_b_record['Count'], labels = df_team_b_record['Category'], autopct = \"%.2f%%\", shadow= True, colors = ['orange','green'])\n",
    "    plt.title(team_b + \" Record\")\n",
    "    print(df_head2head_matches,\"\\n\\n\",team_a,\"\\n\", df_team_a_record,\"\\n\\n\", team_b,\"\\n\", df_team_b_record)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter team A name:Mumbai Indians\n",
      "Enter team B name:Delhi Capitals\n",
      "              Category  Count\n",
      "0  Mumbai Indians Wins      1\n",
      "1  Delhi Capitals wins      1 \n",
      "\n",
      " Mumbai Indians \n",
      "              Category  Count\n",
      "0  Batting first wins      0\n",
      "1  Bowling first wins      1 \n",
      "\n",
      " Delhi Capitals \n",
      "              Category  Count\n",
      "0  Batting first wins      0\n",
      "1  Bowling first wins      1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "team_a = input(\"Enter team A name:\")\n",
    "team_b = input(\"Enter team B name:\")\n",
    "both_team_head2head(team_a, team_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}