Exploratory Data Analysis - Sports.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Author - AKSHAYSRIVATS VIJAYARAGHAVAN\n",
    "\n",
    "# Exploratory Data Analysis - Sports\n",
    "- Problem Statement: Perform Exploratory Data Analysis on 'Indian Premiere League' <br>\n",
    "\n",
    "- As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team.<br>\n",
    "\n",
    "- Suggest teams or players a company should endorse for its products.<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing LIBRARIES:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading 1st Dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches = pd.read_csv(\"matches.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "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>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": [
    {
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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>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",
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       "      <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": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 756 entries, 0 to 755\n",
      "Data columns (total 18 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               756 non-null    int64 \n",
      " 1   season           756 non-null    int64 \n",
      " 2   city             749 non-null    object\n",
      " 3   date             756 non-null    object\n",
      " 4   team1            756 non-null    object\n",
      " 5   team2            756 non-null    object\n",
      " 6   toss_winner      756 non-null    object\n",
      " 7   toss_decision    756 non-null    object\n",
      " 8   result           756 non-null    object\n",
      " 9   dl_applied       756 non-null    int64 \n",
      " 10  winner           752 non-null    object\n",
      " 11  win_by_runs      756 non-null    int64 \n",
      " 12  win_by_wickets   756 non-null    int64 \n",
      " 13  player_of_match  752 non-null    object\n",
      " 14  venue            756 non-null    object\n",
      " 15  umpire1          754 non-null    object\n",
      " 16  umpire2          754 non-null    object\n",
      " 17  umpire3          119 non-null    object\n",
      "dtypes: int64(5), object(13)\n",
      "memory usage: 106.4+ KB\n"
     ]
    }
   ],
   "source": [
    "matches.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(756, 18)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading 2nd Dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "deliveries = pd.read_csv(\"deliveries.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
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       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning         batting_team                 bowling_team  over  \\\n",
       "0         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "1         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "2         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "3         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "4         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "\n",
       "   ball    batsman non_striker    bowler  is_super_over  ...  bye_runs  \\\n",
       "0     1  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "1     2  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "2     3  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "3     4  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "4     5  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",
       "\n",
       "   legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",
       "0            0            0             0             0           0   \n",
       "1            0            0             0             0           0   \n",
       "2            0            0             0             4           0   \n",
       "3            0            0             0             0           0   \n",
       "4            0            0             0             0           2   \n",
       "\n",
       "   total_runs  player_dismissed dismissal_kind fielder  \n",
       "0           0               NaN            NaN     NaN  \n",
       "1           0               NaN            NaN     NaN  \n",
       "2           4               NaN            NaN     NaN  \n",
       "3           0               NaN            NaN     NaN  \n",
       "4           2               NaN            NaN     NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>179073</th>\n",
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       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>RA Jadeja</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <th>179074</th>\n",
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       "      <td>SR Watson</td>\n",
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       "      <td>SL Malinga</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>179075</th>\n",
       "      <td>11415</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>SR Watson</td>\n",
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       "      <td>SL Malinga</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>run out</td>\n",
       "      <td>KH Pandya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179076</th>\n",
       "      <td>11415</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>RA Jadeja</td>\n",
       "      <td>SL Malinga</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>179077</th>\n",
       "      <td>11415</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>RA Jadeja</td>\n",
       "      <td>SL Malinga</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>lbw</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id  inning         batting_team    bowling_team  over  ball  \\\n",
       "179073     11415       2  Chennai Super Kings  Mumbai Indians    20     2   \n",
       "179074     11415       2  Chennai Super Kings  Mumbai Indians    20     3   \n",
       "179075     11415       2  Chennai Super Kings  Mumbai Indians    20     4   \n",
       "179076     11415       2  Chennai Super Kings  Mumbai Indians    20     5   \n",
       "179077     11415       2  Chennai Super Kings  Mumbai Indians    20     6   \n",
       "\n",
       "          batsman non_striker      bowler  is_super_over  ...  bye_runs  \\\n",
       "179073  RA Jadeja   SR Watson  SL Malinga              0  ...         0   \n",
       "179074  SR Watson   RA Jadeja  SL Malinga              0  ...         0   \n",
       "179075  SR Watson   RA Jadeja  SL Malinga              0  ...         0   \n",
       "179076  SN Thakur   RA Jadeja  SL Malinga              0  ...         0   \n",
       "179077  SN Thakur   RA Jadeja  SL Malinga              0  ...         0   \n",
       "\n",
       "        legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",
       "179073            0            0             0             1           0   \n",
       "179074            0            0             0             2           0   \n",
       "179075            0            0             0             1           0   \n",
       "179076            0            0             0             2           0   \n",
       "179077            0            0             0             0           0   \n",
       "\n",
       "        total_runs  player_dismissed dismissal_kind    fielder  \n",
       "179073           1               NaN            NaN        NaN  \n",
       "179074           2               NaN            NaN        NaN  \n",
       "179075           1         SR Watson        run out  KH Pandya  \n",
       "179076           2               NaN            NaN        NaN  \n",
       "179077           0         SN Thakur            lbw        NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 179078 entries, 0 to 179077\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count   Dtype \n",
      "---  ------            --------------   ----- \n",
      " 0   match_id          179078 non-null  int64 \n",
      " 1   inning            179078 non-null  int64 \n",
      " 2   batting_team      179078 non-null  object\n",
      " 3   bowling_team      179078 non-null  object\n",
      " 4   over              179078 non-null  int64 \n",
      " 5   ball              179078 non-null  int64 \n",
      " 6   batsman           179078 non-null  object\n",
      " 7   non_striker       179078 non-null  object\n",
      " 8   bowler            179078 non-null  object\n",
      " 9   is_super_over     179078 non-null  int64 \n",
      " 10  wide_runs         179078 non-null  int64 \n",
      " 11  bye_runs          179078 non-null  int64 \n",
      " 12  legbye_runs       179078 non-null  int64 \n",
      " 13  noball_runs       179078 non-null  int64 \n",
      " 14  penalty_runs      179078 non-null  int64 \n",
      " 15  batsman_runs      179078 non-null  int64 \n",
      " 16  extra_runs        179078 non-null  int64 \n",
      " 17  total_runs        179078 non-null  int64 \n",
      " 18  player_dismissed  8834 non-null    object\n",
      " 19  dismissal_kind    8834 non-null    object\n",
      " 20  fielder           6448 non-null    object\n",
      "dtypes: int64(13), object(8)\n",
      "memory usage: 28.7+ MB\n"
     ]
    }
   ],
   "source": [
    "deliveries.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(179078, 21)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>wide_runs</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1802.252957</td>\n",
       "      <td>1.482952</td>\n",
       "      <td>10.162488</td>\n",
       "      <td>3.615587</td>\n",
       "      <td>0.000452</td>\n",
       "      <td>0.036721</td>\n",
       "      <td>0.004936</td>\n",
       "      <td>0.021136</td>\n",
       "      <td>0.004183</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>1.246864</td>\n",
       "      <td>0.067032</td>\n",
       "      <td>1.313897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3472.322805</td>\n",
       "      <td>0.502074</td>\n",
       "      <td>5.677684</td>\n",
       "      <td>1.806966</td>\n",
       "      <td>0.021263</td>\n",
       "      <td>0.251161</td>\n",
       "      <td>0.116480</td>\n",
       "      <td>0.194908</td>\n",
       "      <td>0.070492</td>\n",
       "      <td>0.016709</td>\n",
       "      <td>1.608270</td>\n",
       "      <td>0.342553</td>\n",
       "      <td>1.605422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>190.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>379.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>567.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11415.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            match_id         inning           over           ball  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean     1802.252957       1.482952      10.162488       3.615587   \n",
       "std      3472.322805       0.502074       5.677684       1.806966   \n",
       "min         1.000000       1.000000       1.000000       1.000000   \n",
       "25%       190.000000       1.000000       5.000000       2.000000   \n",
       "50%       379.000000       1.000000      10.000000       4.000000   \n",
       "75%       567.000000       2.000000      15.000000       5.000000   \n",
       "max     11415.000000       5.000000      20.000000       9.000000   \n",
       "\n",
       "       is_super_over      wide_runs       bye_runs    legbye_runs  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean        0.000452       0.036721       0.004936       0.021136   \n",
       "std         0.021263       0.251161       0.116480       0.194908   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         0.000000       0.000000       0.000000       0.000000   \n",
       "50%         0.000000       0.000000       0.000000       0.000000   \n",
       "75%         0.000000       0.000000       0.000000       0.000000   \n",
       "max         1.000000       5.000000       4.000000       5.000000   \n",
       "\n",
       "         noball_runs   penalty_runs   batsman_runs     extra_runs  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean        0.004183       0.000056       1.246864       0.067032   \n",
       "std         0.070492       0.016709       1.608270       0.342553   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         0.000000       0.000000       0.000000       0.000000   \n",
       "50%         0.000000       0.000000       1.000000       0.000000   \n",
       "75%         0.000000       0.000000       1.000000       0.000000   \n",
       "max         5.000000       5.000000       7.000000       7.000000   \n",
       "\n",
       "          total_runs  \n",
       "count  179078.000000  \n",
       "mean        1.313897  \n",
       "std         1.605422  \n",
       "min         0.000000  \n",
       "25%         0.000000  \n",
       "50%         1.000000  \n",
       "75%         1.000000  \n",
       "max        10.000000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now, We will merge the 2 datasets for better insights from the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>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>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>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>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>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",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning         batting_team                 bowling_team  over  \\\n",
       "0         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "1         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "\n",
       "   ball    batsman non_striker    bowler  is_super_over  ...  result  \\\n",
       "0     1  DA Warner    S Dhawan  TS Mills              0  ...  normal   \n",
       "1     2  DA Warner    S Dhawan  TS Mills              0  ...  normal   \n",
       "\n",
       "   dl_applied               winner  win_by_runs  win_by_wickets  \\\n",
       "0           0  Sunrisers Hyderabad           35               0   \n",
       "1           0  Sunrisers Hyderabad           35               0   \n",
       "\n",
       "   player_of_match                                      venue      umpire1  \\\n",
       "0     Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal  AY Dandekar   \n",
       "1     Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal  AY Dandekar   \n",
       "\n",
       "    umpire2 umpire3  \n",
       "0  NJ Llong     NaN  \n",
       "1  NJ Llong     NaN  \n",
       "\n",
       "[2 rows x 39 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merging the 2 datasets\n",
    "merge = pd.merge(deliveries,matches, left_on='match_id', right_on ='id')\n",
    "merge.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 179078 entries, 0 to 179077\n",
      "Data columns (total 39 columns):\n",
      " #   Column            Non-Null Count   Dtype \n",
      "---  ------            --------------   ----- \n",
      " 0   match_id          179078 non-null  int64 \n",
      " 1   inning            179078 non-null  int64 \n",
      " 2   batting_team      179078 non-null  object\n",
      " 3   bowling_team      179078 non-null  object\n",
      " 4   over              179078 non-null  int64 \n",
      " 5   ball              179078 non-null  int64 \n",
      " 6   batsman           179078 non-null  object\n",
      " 7   non_striker       179078 non-null  object\n",
      " 8   bowler            179078 non-null  object\n",
      " 9   is_super_over     179078 non-null  int64 \n",
      " 10  wide_runs         179078 non-null  int64 \n",
      " 11  bye_runs          179078 non-null  int64 \n",
      " 12  legbye_runs       179078 non-null  int64 \n",
      " 13  noball_runs       179078 non-null  int64 \n",
      " 14  penalty_runs      179078 non-null  int64 \n",
      " 15  batsman_runs      179078 non-null  int64 \n",
      " 16  extra_runs        179078 non-null  int64 \n",
      " 17  total_runs        179078 non-null  int64 \n",
      " 18  player_dismissed  8834 non-null    object\n",
      " 19  dismissal_kind    8834 non-null    object\n",
      " 20  fielder           6448 non-null    object\n",
      " 21  id                179078 non-null  int64 \n",
      " 22  season            179078 non-null  int64 \n",
      " 23  city              177378 non-null  object\n",
      " 24  date              179078 non-null  object\n",
      " 25  team1             179078 non-null  object\n",
      " 26  team2             179078 non-null  object\n",
      " 27  toss_winner       179078 non-null  object\n",
      " 28  toss_decision     179078 non-null  object\n",
      " 29  result            179078 non-null  object\n",
      " 30  dl_applied        179078 non-null  int64 \n",
      " 31  winner            178706 non-null  object\n",
      " 32  win_by_runs       179078 non-null  int64 \n",
      " 33  win_by_wickets    179078 non-null  int64 \n",
      " 34  player_of_match   178706 non-null  object\n",
      " 35  venue             179078 non-null  object\n",
      " 36  umpire1           178578 non-null  object\n",
      " 37  umpire2           178578 non-null  object\n",
      " 38  umpire3           28366 non-null   object\n",
      "dtypes: int64(18), object(21)\n",
      "memory usage: 54.7+ MB\n"
     ]
    }
   ],
   "source": [
    "merge.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>wide_runs</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>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>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "      <td>179078.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1802.252957</td>\n",
       "      <td>1.482952</td>\n",
       "      <td>10.162488</td>\n",
       "      <td>3.615587</td>\n",
       "      <td>0.000452</td>\n",
       "      <td>0.036721</td>\n",
       "      <td>0.004936</td>\n",
       "      <td>0.021136</td>\n",
       "      <td>0.004183</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>1.246864</td>\n",
       "      <td>0.067032</td>\n",
       "      <td>1.313897</td>\n",
       "      <td>1802.252957</td>\n",
       "      <td>2013.444510</td>\n",
       "      <td>0.017914</td>\n",
       "      <td>13.404036</td>\n",
       "      <td>3.261579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3472.322805</td>\n",
       "      <td>0.502074</td>\n",
       "      <td>5.677684</td>\n",
       "      <td>1.806966</td>\n",
       "      <td>0.021263</td>\n",
       "      <td>0.251161</td>\n",
       "      <td>0.116480</td>\n",
       "      <td>0.194908</td>\n",
       "      <td>0.070492</td>\n",
       "      <td>0.016709</td>\n",
       "      <td>1.608270</td>\n",
       "      <td>0.342553</td>\n",
       "      <td>1.605422</td>\n",
       "      <td>3472.322805</td>\n",
       "      <td>3.363947</td>\n",
       "      <td>0.132639</td>\n",
       "      <td>23.261007</td>\n",
       "      <td>3.347033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\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>190.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>190.000000</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>379.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>379.000000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>567.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>567.000000</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>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>10.000000</td>\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": [
       "            match_id         inning           over           ball  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean     1802.252957       1.482952      10.162488       3.615587   \n",
       "std      3472.322805       0.502074       5.677684       1.806966   \n",
       "min         1.000000       1.000000       1.000000       1.000000   \n",
       "25%       190.000000       1.000000       5.000000       2.000000   \n",
       "50%       379.000000       1.000000      10.000000       4.000000   \n",
       "75%       567.000000       2.000000      15.000000       5.000000   \n",
       "max     11415.000000       5.000000      20.000000       9.000000   \n",
       "\n",
       "       is_super_over      wide_runs       bye_runs    legbye_runs  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean        0.000452       0.036721       0.004936       0.021136   \n",
       "std         0.021263       0.251161       0.116480       0.194908   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         0.000000       0.000000       0.000000       0.000000   \n",
       "50%         0.000000       0.000000       0.000000       0.000000   \n",
       "75%         0.000000       0.000000       0.000000       0.000000   \n",
       "max         1.000000       5.000000       4.000000       5.000000   \n",
       "\n",
       "         noball_runs   penalty_runs   batsman_runs     extra_runs  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean        0.004183       0.000056       1.246864       0.067032   \n",
       "std         0.070492       0.016709       1.608270       0.342553   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         0.000000       0.000000       0.000000       0.000000   \n",
       "50%         0.000000       0.000000       1.000000       0.000000   \n",
       "75%         0.000000       0.000000       1.000000       0.000000   \n",
       "max         5.000000       5.000000       7.000000       7.000000   \n",
       "\n",
       "          total_runs             id         season     dl_applied  \\\n",
       "count  179078.000000  179078.000000  179078.000000  179078.000000   \n",
       "mean        1.313897    1802.252957    2013.444510       0.017914   \n",
       "std         1.605422    3472.322805       3.363947       0.132639   \n",
       "min         0.000000       1.000000    2008.000000       0.000000   \n",
       "25%         0.000000     190.000000    2011.000000       0.000000   \n",
       "50%         1.000000     379.000000    2013.000000       0.000000   \n",
       "75%         1.000000     567.000000    2016.000000       0.000000   \n",
       "max        10.000000   11415.000000    2019.000000       1.000000   \n",
       "\n",
       "         win_by_runs  win_by_wickets  \n",
       "count  179078.000000   179078.000000  \n",
       "mean       13.404036        3.261579  \n",
       "std        23.261007        3.347033  \n",
       "min         0.000000        0.000000  \n",
       "25%         0.000000        0.000000  \n",
       "50%         0.000000        3.000000  \n",
       "75%        19.000000        6.000000  \n",
       "max       146.000000       10.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.id.is_unique"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Note:<br>\n",
    "- since id is unique we can set this as our index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches.set_index('id', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>count</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>749</td>\n",
       "      <td>756</td>\n",
       "      <td>756</td>\n",
       "      <td>756</td>\n",
       "      <td>756</td>\n",
       "      <td>756</td>\n",
       "      <td>756</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>752</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>752</td>\n",
       "      <td>756</td>\n",
       "      <td>754</td>\n",
       "      <td>754</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>546</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>226</td>\n",
       "      <td>41</td>\n",
       "      <td>61</td>\n",
       "      <td>65</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2015-05-02</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>O Nandan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "      <td>2</td>\n",
       "      <td>101</td>\n",
       "      <td>95</td>\n",
       "      <td>98</td>\n",
       "      <td>463</td>\n",
       "      <td>743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21</td>\n",
       "      <td>77</td>\n",
       "      <td>73</td>\n",
       "      <td>57</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2013.444444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.025132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.283069</td>\n",
       "      <td>3.350529</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.366895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.156630</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.471144</td>\n",
       "      <td>3.387963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2008.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2011.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2013.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2019.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             season    city        date           team1  \\\n",
       "count    756.000000     749         756             756   \n",
       "unique          NaN      32         546              15   \n",
       "top             NaN  Mumbai  2015-05-02  Mumbai Indians   \n",
       "freq            NaN     101           2             101   \n",
       "mean    2013.444444     NaN         NaN             NaN   \n",
       "std        3.366895     NaN         NaN             NaN   \n",
       "min     2008.000000     NaN         NaN             NaN   \n",
       "25%     2011.000000     NaN         NaN             NaN   \n",
       "50%     2013.000000     NaN         NaN             NaN   \n",
       "75%     2016.000000     NaN         NaN             NaN   \n",
       "max     2019.000000     NaN         NaN             NaN   \n",
       "\n",
       "                              team2     toss_winner toss_decision  result  \\\n",
       "count                           756             756           756     756   \n",
       "unique                           15              15             2       3   \n",
       "top     Royal Challengers Bangalore  Mumbai Indians         field  normal   \n",
       "freq                             95              98           463     743   \n",
       "mean                            NaN             NaN           NaN     NaN   \n",
       "std                             NaN             NaN           NaN     NaN   \n",
       "min                             NaN             NaN           NaN     NaN   \n",
       "25%                             NaN             NaN           NaN     NaN   \n",
       "50%                             NaN             NaN           NaN     NaN   \n",
       "75%                             NaN             NaN           NaN     NaN   \n",
       "max                             NaN             NaN           NaN     NaN   \n",
       "\n",
       "        dl_applied          winner  win_by_runs  win_by_wickets  \\\n",
       "count   756.000000             752   756.000000      756.000000   \n",
       "unique         NaN              15          NaN             NaN   \n",
       "top            NaN  Mumbai Indians          NaN             NaN   \n",
       "freq           NaN             109          NaN             NaN   \n",
       "mean      0.025132             NaN    13.283069        3.350529   \n",
       "std       0.156630             NaN    23.471144        3.387963   \n",
       "min       0.000000             NaN     0.000000        0.000000   \n",
       "25%       0.000000             NaN     0.000000        0.000000   \n",
       "50%       0.000000             NaN     0.000000        4.000000   \n",
       "75%       0.000000             NaN    19.000000        6.000000   \n",
       "max       1.000000             NaN   146.000000       10.000000   \n",
       "\n",
       "       player_of_match         venue          umpire1        umpire2   umpire3  \n",
       "count              752           756              754            754       119  \n",
       "unique             226            41               61             65        25  \n",
       "top           CH Gayle  Eden Gardens  HDPK Dharmasena  C Shamshuddin  O Nandan  \n",
       "freq                21            77               73             57        10  \n",
       "mean               NaN           NaN              NaN            NaN       NaN  \n",
       "std                NaN           NaN              NaN            NaN       NaN  \n",
       "min                NaN           NaN              NaN            NaN       NaN  \n",
       "25%                NaN           NaN              NaN            NaN       NaN  \n",
       "50%                NaN           NaN              NaN            NaN       NaN  \n",
       "75%                NaN           NaN              NaN            NaN       NaN  \n",
       "max                NaN           NaN              NaN            NaN       NaN  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Summary statistics of matches data\n",
    "matches.describe(include = 'all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preprocessing <br>\n",
    "- Here we will perform Data Preprocessing on our matches dataset first, to make the data usable for EDA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\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>2</th>\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>3</th>\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>4</th>\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>5</th>\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": [
       "    season       city        date                        team1  \\\n",
       "id                                                               \n",
       "1     2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "2     2017       Pune  2017-04-06               Mumbai Indians   \n",
       "3     2017     Rajkot  2017-04-07                Gujarat Lions   \n",
       "4     2017     Indore  2017-04-08       Rising Pune Supergiant   \n",
       "5     2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "\n",
       "                          team2                  toss_winner toss_decision  \\\n",
       "id                                                                           \n",
       "1   Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "2        Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "3         Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "4               Kings XI Punjab              Kings XI Punjab         field   \n",
       "5              Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "    result  dl_applied                       winner  win_by_runs  \\\n",
       "id                                                                 \n",
       "1   normal           0          Sunrisers Hyderabad           35   \n",
       "2   normal           0       Rising Pune Supergiant            0   \n",
       "3   normal           0        Kolkata Knight Riders            0   \n",
       "4   normal           0              Kings XI Punjab            0   \n",
       "5   normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "    win_by_wickets player_of_match                                      venue  \\\n",
       "id                                                                              \n",
       "1                0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "2                7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "3               10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "4                6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "5                0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "           umpire1        umpire2 umpire3  \n",
       "id                                         \n",
       "1      AY Dandekar       NJ Llong     NaN  \n",
       "2   A Nand Kishore         S Ravi     NaN  \n",
       "3      Nitin Menon      CK Nandan     NaN  \n",
       "4     AK Chaudhary  C Shamshuddin     NaN  \n",
       "5              NaN            NaN     NaN  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From Pre profiling, we found that:\n",
    "\n",
    "- city has missing values\n",
    "\n",
    "- team1 and team2 columns have 14 distinct values but winner has 15 distinct values\n",
    "\n",
    "- umpire1 and umpire2 have 1 missing value each\n",
    "\n",
    "- umpire3 has 94% missing values\n",
    "\n",
    "- city has 33 distinct values while venue has 35 distinct values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filling in the missing values of city column\n",
    "### First let's find the venues corresponding to which the values of city are empty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>venue</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>463</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    city                                venue\n",
       "id                                           \n",
       "462  NaN  Dubai International Cricket Stadium\n",
       "463  NaN  Dubai International Cricket Stadium\n",
       "467  NaN  Dubai International Cricket Stadium\n",
       "469  NaN  Dubai International Cricket Stadium\n",
       "470  NaN  Dubai International Cricket Stadium\n",
       "475  NaN  Dubai International Cricket Stadium\n",
       "477  NaN  Dubai International Cricket Stadium"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches[matches.city.isnull()][['city','venue']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- So, missing values can be filled with Dubai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches.city = matches.city.fillna('Dubai')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- umpire1 and umpire2 columns have one missing value each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\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",
       "    <tr>\n",
       "      <th>11413</th>\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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       season           city        date                        team1  \\\n",
       "id                                                                      \n",
       "5        2017      Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "11413    2019  Visakhapatnam    08/05/19          Sunrisers Hyderabad   \n",
       "\n",
       "                  team2                  toss_winner toss_decision  result  \\\n",
       "id                                                                           \n",
       "5      Delhi Daredevils  Royal Challengers Bangalore           bat  normal   \n",
       "11413    Delhi Capitals               Delhi Capitals         field  normal   \n",
       "\n",
       "       dl_applied                       winner  win_by_runs  win_by_wickets  \\\n",
       "id                                                                            \n",
       "5               0  Royal Challengers Bangalore           15               0   \n",
       "11413           0               Delhi Capitals            0               2   \n",
       "\n",
       "      player_of_match                  venue umpire1 umpire2 umpire3  \n",
       "id                                                                    \n",
       "5           KM Jadhav  M Chinnaswamy Stadium     NaN     NaN     NaN  \n",
       "11413         RR Pant       ACA-VDCA Stadium     NaN     NaN     NaN  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches[(matches.umpire1.isnull()) | (matches.umpire2.isnull())]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Umpire3 column has close to 92% missing values. hence dropping that column\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "matches = matches.drop('umpire3', axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <th>venue</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Abu Dhabi</th>\n",
       "      <th>Sheikh Zayed Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ahmedabad</th>\n",
       "      <th>Sardar Patel Stadium, Motera</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bangalore</th>\n",
       "      <th>M Chinnaswamy Stadium</th>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Bengaluru</th>\n",
       "      <th>M Chinnaswamy Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M. Chinnaswamy Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bloemfontein</th>\n",
       "      <th>OUTsurance Oval</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cape Town</th>\n",
       "      <th>Newlands</th>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>Centurion</th>\n",
       "      <th>SuperSport Park</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Chandigarh</th>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association Stadium, Mohali</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Chennai</th>\n",
       "      <th>M. A. Chidambaram Stadium</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium, Chepauk</th>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cuttack</th>\n",
       "      <th>Barabati Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Delhi</th>\n",
       "      <th>Feroz Shah Kotla</th>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Feroz Shah Kotla Ground</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dharamsala</th>\n",
       "      <th>Himachal Pradesh Cricket Association Stadium</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dubai</th>\n",
       "      <th>Dubai International Cricket Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Durban</th>\n",
       "      <th>Kingsmead</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East London</th>\n",
       "      <th>Buffalo Park</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Hyderabad</th>\n",
       "      <th>Rajiv Gandhi International Stadium, Uppal</th>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi Intl. Cricket Stadium</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indore</th>\n",
       "      <th>Holkar Cricket Stadium</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jaipur</th>\n",
       "      <th>Sawai Mansingh Stadium</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johannesburg</th>\n",
       "      <th>New Wanderers Stadium</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kanpur</th>\n",
       "      <th>Green Park</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kimberley</th>\n",
       "      <th>De Beers Diamond Oval</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kochi</th>\n",
       "      <th>Nehru Stadium</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kolkata</th>\n",
       "      <th>Eden Gardens</th>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Mohali</th>\n",
       "      <th>IS Bindra Stadium</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Mumbai</th>\n",
       "      <th>Brabourne Stadium</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr DY Patil Sports Academy</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wankhede Stadium</th>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nagpur</th>\n",
       "      <th>Vidarbha Cricket Association Stadium, Jamtha</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Port Elizabeth</th>\n",
       "      <th>St George's Park</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Pune</th>\n",
       "      <th>Maharashtra Cricket Association Stadium</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Subrata Roy Sahara Stadium</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Raipur</th>\n",
       "      <th>Shaheed Veer Narayan Singh International Stadium</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajkot</th>\n",
       "      <th>Saurashtra Cricket Association Stadium</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ranchi</th>\n",
       "      <th>JSCA International Stadium Complex</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharjah</th>\n",
       "      <th>Sharjah Cricket Stadium</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Visakhapatnam</th>\n",
       "      <th>ACA-VDCA Stadium</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                   season\n",
       "city           venue                                                     \n",
       "Abu Dhabi      Sheikh Zayed Stadium                                     7\n",
       "Ahmedabad      Sardar Patel Stadium, Motera                            12\n",
       "Bangalore      M Chinnaswamy Stadium                                   66\n",
       "Bengaluru      M Chinnaswamy Stadium                                    7\n",
       "               M. Chinnaswamy Stadium                                   7\n",
       "Bloemfontein   OUTsurance Oval                                          2\n",
       "Cape Town      Newlands                                                 7\n",
       "Centurion      SuperSport Park                                         12\n",
       "Chandigarh     Punjab Cricket Association IS Bindra Stadium, M...      11\n",
       "               Punjab Cricket Association Stadium, Mohali              35\n",
       "Chennai        M. A. Chidambaram Stadium                                8\n",
       "               MA Chidambaram Stadium, Chepauk                         49\n",
       "Cuttack        Barabati Stadium                                         7\n",
       "Delhi          Feroz Shah Kotla                                        67\n",
       "               Feroz Shah Kotla Ground                                  7\n",
       "Dharamsala     Himachal Pradesh Cricket Association Stadium             9\n",
       "Dubai          Dubai International Cricket Stadium                      7\n",
       "Durban         Kingsmead                                               15\n",
       "East London    Buffalo Park                                             3\n",
       "Hyderabad      Rajiv Gandhi International Stadium, Uppal               56\n",
       "               Rajiv Gandhi Intl. Cricket Stadium                       8\n",
       "Indore         Holkar Cricket Stadium                                   9\n",
       "Jaipur         Sawai Mansingh Stadium                                  47\n",
       "Johannesburg   New Wanderers Stadium                                    8\n",
       "Kanpur         Green Park                                               4\n",
       "Kimberley      De Beers Diamond Oval                                    3\n",
       "Kochi          Nehru Stadium                                            5\n",
       "Kolkata        Eden Gardens                                            77\n",
       "Mohali         IS Bindra Stadium                                        7\n",
       "               Punjab Cricket Association IS Bindra Stadium, M...       3\n",
       "Mumbai         Brabourne Stadium                                       11\n",
       "               Dr DY Patil Sports Academy                              17\n",
       "               Wankhede Stadium                                        73\n",
       "Nagpur         Vidarbha Cricket Association Stadium, Jamtha             3\n",
       "Port Elizabeth St George's Park                                         7\n",
       "Pune           Maharashtra Cricket Association Stadium                 21\n",
       "               Subrata Roy Sahara Stadium                              17\n",
       "Raipur         Shaheed Veer Narayan Singh International Stadium         6\n",
       "Rajkot         Saurashtra Cricket Association Stadium                  10\n",
       "Ranchi         JSCA International Stadium Complex                       7\n",
       "Sharjah        Sharjah Cricket Stadium                                  6\n",
       "Visakhapatnam  ACA-VDCA Stadium                                         2\n",
       "               Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...      11"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#city has 33 distinct values while we have 35 venues.\n",
    "#Let's find out venues grouped by cities to see which cities have multiple venues\n",
    "\n",
    "city_venue = matches.groupby(['city','venue']).count()['season']\n",
    "city_venue_df = pd.DataFrame(city_venue)\n",
    "city_venue_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "- Bengaluru and Bangalore both are in the data when they are same. So we need to keep one of them\n",
    "- Chandigarh and Mohali are same and there is just one stadium Punjab Cricket Association IS Bindra Stadium, Mohali whose value has not been entered correctly. We need to have either Chandigarh or Mohali as well as correct name of the stadium there\n",
    "- Mumbai has 3 stadiums/venues used for IPL\n",
    "- Pune has 2 venues for IPL<br>\n",
    "### Visual representation of number of venues in each city ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  0.,  20.,  40.,  60.,  80., 100., 120.]),\n",
       " <a list of 7 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting venues along with cities \n",
    "v = pd.crosstab(matches['city'],matches['venue'])\n",
    "v.replace(v[v!=0],1, inplace = True)\n",
    "\n",
    "#Adding a column by summing each columns\n",
    "v['count'] = v.sum(axis = 'columns')\n",
    "#We will just keep last column = 'count'\n",
    "b = v['count']\n",
    "\n",
    "#Plotting\n",
    "plt.figure(figsize = (20,7))\n",
    "b.plot(kind = 'bar')\n",
    "plt.title(\"Number of stadiums in different cities\", fontsize = 25, fontweight = 'bold')\n",
    "plt.xlabel(\"City\", size = 30)\n",
    "plt.ylabel(\"Frequency\", size = 30)\n",
    "plt.xticks(size = 20)\n",
    "plt.yticks(size = 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploratory Data Analysis:<br>\n",
    "### Number of matches played in each season "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0., 10., 20., 30., 40., 50., 60., 70., 80.]),\n",
       " <a list of 9 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "sns.countplot('season', data = matches)\n",
    "plt.title(\"Number of matches played each season\",fontsize=18,fontweight=\"bold\")\n",
    "plt.ylabel(\"Count\", size = 25)\n",
    "plt.xlabel(\"Season\", size = 25)\n",
    "plt.xticks(size = 20)\n",
    "plt.yticks(size = 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 2011-2013 have more matches being played than other seasons\n",
    "\n",
    "- All other seasons have approximately 58-60 matches while 2011-2013 have more than 70 matches."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How many teams played in each season?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0.,  2.,  4.,  6.,  8., 10., 12.]),\n",
       " <a list of 7 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "matches.groupby('season')['team1'].nunique().plot(kind = 'bar', figsize=(15,5))\n",
    "plt.title(\"Number of teams participated each season \",fontsize=18,fontweight=\"bold\")\n",
    "plt.ylabel(\"Count of teams\", size = 25)\n",
    "plt.xlabel(\"Season\", size = 25)\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 10 teams played in 2011 and 9 teams each in 2012 and 2013\n",
    "\n",
    "- This explains why 2011-2013 have seen more matches being played than other seasons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Venue which has hosted most number of IPL matches ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Frequency')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "matches.venue.value_counts().sort_values(ascending = True).tail(10).plot(kind = 'barh',figsize=(12,8), fontsize=15, color='green')\n",
    "plt.title(\"Venue which has hosted most number of IPL matches\",fontsize=18,fontweight=\"bold\")\n",
    "plt.ylabel(\"Venue\", size = 25)\n",
    "plt.xlabel(\"Frequency\", size = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- M Chinnaswamy Stadium in Bengaluru has hosted the highest number of matches so far in IPL followed by Eden Gardens in Kolkata\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which team has maximum wins in IPL so far?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating a dataframe with season and winner columns\n",
    "winning_teams = matches[['season','winner']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dictionaries to get winners to each season\n",
    "winners_team = {}\n",
    "for i in sorted(winning_teams.season.unique()):\n",
    "    winners_team[i] = winning_teams[winning_teams.season == i]['winner'].tail(1).values[0]\n",
    "    \n",
    "winners_of_IPL = pd.Series(winners_team)\n",
    "winners_of_IPL = pd.DataFrame(winners_of_IPL, columns=['team'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1, 2, 3, 4, 5]), <a list of 6 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fvn3yQyXdEeS2G8YoSZIkSZJuj+y5IEmSJEmSxmJyQZIkSZIkjcXkgiRJkiRJGovJBUmSJEmSNBaTC5IkSZIkaSzLzXYA0tJirbXWqg022GC2w5AkSZKkWTF37tyLq+puE+0zuSDN0AYbbMCcOXNmOwxJkiRJmhVJzp5sn8MiJEmSJEnSWEwuSJIkSZKksZhckCRJkiRJYzG5IEmSJEmSxmJyQZIkSZIkjcXkgiRJkiRJGovJBUmSJEmSNBaTC5IkSZIkaSwmFyRJkiRJ0liWm+0ApKXF3LkXknx8tsOQlkhVO852CJIkSZpF9lyQJEmSJEljMbkgSZIkSZLGYnJBkiRJkiSNxeSCJEmSJEkai8kFSZIkSZI0liU+uZBkmyRzk1yV5LIkv03yv7MQxzFJvntbn3emuvtUSVadYN8uSS5eROe5OMkui6KuEc5ZSd68GOv/bpJjFlf9kiRJknR7t0QnF5LsBHwJ+DGwObA18EPgBbMQzvbATrNwXkmSJEmSlmjLzXYA03gzsG9Vvbe37ZAku95WASRZuarmVdWfb6PzrVRV190W55otSQKseHu/TkmSJEm6o1iiey4AdwEuGN5YVTV4nWTjrtv8w/plhocxJNkvyZwkz0ryhyTXJDk+yUOHjqsk70iyd5J/AadMUt+9knwnyUVJ5iX5e5IPD9X1pCTHJrk2ySVJvphktd7+wVCGjbr65wHv6vbtlORvSa5LcmGSI5OsvZD3sR/TcknOT7LzBPuOTfL93vunJPl9F8PcJE+YpM7Nunt7XZILkuyZZPne/l264RRPSnIycB2wRZI7JflsklO7e3Rmkn2S3HmC06yQ5FNJLk1yeZLPJFmhd457JvlKkjO6z+O0JLv1y3Tl1ktyeFfmrCSvW4jbKEmSJEnqWdJ7LvwGeEuSfwCHVtUlY9a3PrAXsDswD/g48J0kD+snLGgN/OOAVzJ5AuYAYGVgO+By4L7Agwc7kzwR+BnwA+AlwJrAR4E1uvd93wQ+B+wKXJ5ka+C9wP8Af+qOfTpwpxlc47JJhj/XW66hqm5Ksj+wTZIPDa47yX2BJwObde/XAY4ATuriXQf4BrBKv+IkW3bx79vFfD9gj+6cO/aKrgLsD+wJnAac321bFngf8C9gve71QcCzh67hncCvga2Ah9I+w+vokjHAWsClwDuAy4AHArsAdwNe38Ua2rCatYDXdsfvCtwVOH2CeylJkiRJmoElPbnwJlrjfD+gkvwF+B7w8aq6ciHquyvwxKo6HSDJMsDBwIOAv/bKXVBVL52mro2Al1XVId37Y4b2fxT4Zb+eJOcBP+uSGX/slf10VX2qV+61wE+q6v96Zb7PzFw+yfZ+YuYrwHuAjYGfd9u2AS6iJRQAdqA1vjetqmu7uK4Bvt6LM7RkzQFVtX1v+/XAPkn26CWEVgbeUVU/HIrrjb3jlgPOBI5Psn5V/aNX7ipgi6q6GTgiyYrA+7pzXFpVp9BLZiQ5AbgG+EqSt1TVDcB/Af8JPK6qTuzKzQX+jskFSZIkSVpoS/SwiKr6A/AftAkc/w8I8AFgTiZYFWEGzhokFjqDeRTuNVTusBnU9Ttgj25ow/r9HUlWAR5P6xWx3OABHA/cCGw4zfl+Bzw3ya7dkIllZxDPwFOAxww9vtgv0N2D42gJhUGSYGvga1V1U1dsI+CoQWKhM5zgeCCtN8jwdR4NrAT0h6oU8xMXt0jyyrQVQK6m3Zvje3X3/bBLLPRjWXlwjjQ7JPlzN7zkRlpPixW7GAfXdOEgsdDdi7OBucNx9eLbrhvyMQeunqyYJEmSJN2hLdHJBYCqur6qDqmqN1fVQ4DXAQ+gdWsf1fCv+jd0zysNbb9wBnW9FJgDfBI4O8nvkjyj27cGrbv//9EauYPH9cDytO7/U53vK7QhBlsCJwIXJvnwDJMMv62qOf0HbQjCsC8DL+nmgHg6cG/gq739a9N6MtyiquaxYAt7re758KHrPLPb3r/Oy7reA7dI8iLa8JJfAVsAjwNe1O0e/kwumuT9PbvnHYBP0HqibEZLJLxpqK5bXdMkdd+iqr5QVY+uqkfDwuSzJEmSJOn2b0kfFnErVfXlJHsyf36DwYoDKwwVvStw8cKeZgZxnEebt2AZWkN2F+BHXS+Gy7s6dqE1vIcNN/YXOF/3C/0ngU8mWY82z8DuwHnA50e5kCkcBHya1qh/GnDi0IoYFwB37x+QZGUWbGFf2j1vB/x2gnOc2Xs90T3dojtvf0jFUyeJ9+6TvP9nr66Dqup9vboeMnTMra6pV9e8Sc4rSZIkSZrGEt1zIcmtGoJJ7gaszvxf+8/tnv+jV2Y92jwKi11V3VxVv6ZNDLgKcO+quoY2+eCDhnsRdI+JehJMVv85VfVR4G/AcGN5nLjn0SZifBOwOQv2WgA4GXhWN8RjYPOhMqfSEh4bTHKd003AuTKtN0ffVpOU3axL5PRjmQcM5q6YSV0nA/dI8tjBhi4Z9Khp4pQkSZIkTWFJ77lwSpIfAj+hdV2/N23SvmtpKw9QVed2yxt+OMm1tITJe5n/q/oil2R14Me0Lv2n0cb1v5P2y/hfumLvpk3eeDPwXdqEhOsDmwLvq6rTpqh/3y7+XwNX0HoWPIC2esSi9GXgDbRG+reG9u1NSzwcmuR/aatF7ETvF/6qujnJO4GvdctHHkEbanJf4IXAS4bmbBh2FG3ix/fRhn88F3jGJGVXAw5K8kXaahEfBD5bVYPP+SjgrUlOpE3QuBVw/6E6Dgd+39XzP7ReLx9iimERkiRJkqTpLenJhQ/Rxs9/mjbM4QLgl8BLq6rf5f7lwJdoKxmcS2vYv30xxnUdcArwNtq8AtfSEgGbdD0CqKrjkzyF1qPha7Q5GM4GjmT6OR1+BWxLW0JxJVqvhW2r6geL8iKqak63gsUxVXXF0L7zkjyXdu+/R0uavIK2lGO/3LeTXElL6LwG+DdwBnAo8+e0mMy+tETE22jXeRTts/z1BGU/0ZX9Ji2B9KXunAMfoi07uVv3/vvAW4HBah5UVSV5AfAF2rwWFwEfAZ7F/PkjJEmSJEkjStW00wvodqqbk+BPwDOr6mezHc+SLlmvWh5E0rCqHacvJEmSpKVakrltsvtbW9J7LmgxSLImbU6KD9PmLDh6diOSJEmSJC3NlugJHbXYPB84nraM4zZl9xVJkiRJ0hjsuXAHVFX7AfvNchiSJEmSpNsJey5IkiRJkqSx2HNBmqENN7wHc+Y4aZ0kSZIkDbPngiRJkiRJGovJBUmSJEmSNBaTC5IkSZIkaSwmFyRJkiRJ0lhMLkiSJEmSpLGYXJAkSZIkSWMxuSBJkiRJksZickGSJEmSJI3F5IIkSZIkSRqLyQVJkiRJkjQWkwuSJEmSJGksJhckSZIkSdJYTC5IkiRJkqSxmFyQJEmSJEljMbkgSZIkSZLGYnJBkiRJkiSNxeSCJEmSJEkai8kFSZIkSZI0FpMLkiRJkiRpLCYXJEmSJEnSWEwuSJIkSZKksZhckCRJkiRJY1lutgOQlhZz515I8vHZDkNaIlXtONshSJIkaRbZc0GSJEmSJI3F5IIkSZIkSRqLyQVJkiRJkjQWkwuSJEmSJGksJheGJNklSXWPm5NcluTkJLsnWXu241tckiyT5HVJfpnkyiTXJfljknclWbUrs3F3Xx422/FKkiRJkpYcrhYxsSuA53SvVwceBbwR2C7Jc6pq7qxFthgkWQb4NvB8YB/gQ8ANwH8CbwbWAd4+awFKkiRJkpZoJhcmdlNV/br3/sdJPgccB3w7yYOq6t+zFNvi8CbgxcAmVfXT3vajk+wDPPG2CCLJSlV13WKsP8CKi/MckiRJknRH5LCIGaqqy4F3A/cDnjXYnmSlJHsmOSfJ9Ul+n+S5w8cn2TbJKd1wgwuTfDfJ6r39T0ny8yRXJ7kiyTFJ/rPbd88kX0lyRpJ5SU5LsluSFXrHb9ANWdgyyb5dHecm2bXrmTCVtwMHDyUWBtd9XVX9bGjzWkkO6mI9I8n2Q9f6+CQ/SnJ+kmuS/C7JVkNltuni3ai71nnAu7p9Gyf5Q3evTu7KXJxkl6E6Nksypyt3Qfc5LN/bv0t33JOSnAxcB2yRZPkkH0/yj+4zOz/Jwf37KUmSJEmaOZMLo/k5cBPwuN627wLbAB+hDSs4GfhRkkcOCiR5P7AvcCzwQtoQiyuAW+YyAH4G3Ai8Cngp8Atg3a6KtYBLgXfQhmvsBbwa+MwEMe4JXA28BPg68MHu9YSSrAfcBzhyBtc/8EXg98CLgGOAfZJs1Nt/b+AE4HW0e/I94KtJXjZBXd8EDgWeCxyaZF3gcOCiLu59gW8AKw/FvSXwfeAk4AXArsB2wB5D9a8C7A98iXbvTgJ2ArYCPkBLFO1A+zyWHeEeSJIkSZI6DosYQVVdn+Ri4B4ASZ4BbApsXFXHdsV+kuSBwPtov5LfBXgvsHdVvaNX3fd7r/egNdafXVXVbbulsV9VpwA7Dt4nOQG4BvhKkrdU1Q29uo6rqnd2r49K8hxgc+A7k1zWIIHxj+nvwC2+WVW7dbEcQ0sgbE5ruFNV3+rFGtpwknsB29KSCX2frqpP9crvBVwLPL+q5nXbrqTNCdGvcy/ggKravrf9elqiY4+quqTbvDLwjqr6Ya/cRsCBVbV/L47J7o8kSZIkaRr2XBhdeq+fCVwAnJBkucGD1gvh0V2Zx9MauF+dsLLkTsBjgf17iYXhMkmyQ5I/d8MHbqT9mr8isP5Q8Z8Mvf8zrWE/nQnPPYlbzlFVNwKn98+RZI0kn05ydhfrjbReBQ+coK7Dht4/BjhqkFjo/GiozANp1/2doft+NLAS0F/NooAjho7/HbBNkncneUSXrJhQku26oRdzWocQSZIkSdIwey6MIMlKwJrAhd2mtYC1aY3nYYMJH9fsnv85SbVr0BIWk+2H1m3/48BHaUMrLqM1wvehNab7Lh96f8MEZfrO656HkxRTme4c+9GGjnyYlty4kjYUZLMJ6rpw6P3awB/6G6rquiT9lv1a3fPhk8S3Xu/1ZUM9OwB2A24Gtgc+BpyXZK9+D4reub8AfAEgWW+UBIwkSZIk3WGYXBjN02j37Ffd+0tpjfMXTnHMoHv+PYGLJ9h/Ga2he88p6tgCOKiq3jfYkOQhM4x5SlV1TpIzgGfT5iUYS5eA2RR4c1V9vrd9sl4yww32C4C7TVDnqr1Nl3bP2wG/naDOM6eon261iA8CH0zyAOANwN5JTq2qUeaekCRJkiThsIgZ6+ZO+BjwN2CwqsLPaL+0X11Vc4YfXZlfAfNoEzXeSlVdA5wIbD1F9/yVgeuHtm01UcGFtDeweZKnDe9IWw3j6SPUtSJtYsRb4k2yGm3SxZk4GXhWkv4EjsPHnkpL6mww0X3vzbcwrao6nTafxfXAIknYSJIkSdIdjT0XJrZcksGKEKsBG9K69a8CPKeqBkMejgJ+TJs48WPAn4A7A48EVqqqnarq8iQfBnbvljo8nNYA3xTYtarOA95DS1gckeQLtMkaHw/MqapDu/O8NcmJwN9piYX7L8Lr3Qd4CnB4kn26890A/D/gzcAhtPkMplVVV3TLPn6wm4jx5u76rqDdm+nsDbwJOCTJJ2nJm/fQJnm8uTvHzUneCXwtyZ1pcyrcANyX1ovkJVV17WQnSHIwMJfW62EebVWK5WgTT0qSJEmSRmRyYWKr03ocFG2+gL/RlnX8TFVdMChUVZVkc9pqEDvQ5i24lDZh4Gd65fZIcinwNuD1tKEQxwFXdfuPS/Is2hwFX6c1lH8L/KCr4kO0oQK7de+/D7yV1ugfW9dYfynwGtrykW+gfTdOB75Ga/CP4uW0eQoOoA0L+SwtMfPmGcRyXpJNgU/RrvMvXVxH0T6LQblvd8mL93b7/w2cQVvWcniOhWG/pC33+S5a750/Ay/u9TaRJEmSJI0gkyxQIC0xkjwJ+AXw9Kr6+ezFsV61/JCkYVU7Tl9IkiRJS7Ukc6vq0RPts+eCljjdEJPf0iZ3fBDwAdoKEsfOZlySJEmSpImZXNCSaEVgL+AetKEjPwHeUVU3z2pUkiRJkqQJmVzQEqeqdqDNYSFJkiRJWgq4FKUkSZIkSRqLPRekGdpww3swZ46T1kmSJFQWU7EAACAASURBVEnSMHsuSJIkSZKksZhckCRJkiRJYzG5IEmSJEmSxmJyQZIkSZIkjcXkgiRJkiRJGovJBUmSJEmSNBaTC5IkSZIkaSwmFyRJkiRJ0lhMLkiSJEmSpLGYXJAkSZIkSWMxuSBJkiRJksZickGSJEmSJI3F5IIkSZIkSRqLyQVJkiRJkjQWkwuSJEmSJGksJhckSZIkSdJYTC5IkiRJkqSxmFyQJEmSJEljWeTJhSRrJLnzoq5XkiRJkiQtmUZKLiRZJ8nWSZ4zwb6HJpkDXAxcluQXSR64qAKVJEmSJElLplF7LrwG+CqwcX9jkpWBw4H/BNI9ngj81F4MkiRJkiTdvo2aXHhm9/ztoe2vAtYDLgW2BV4BnAusC7xpnAAlSZIkSdKSbbkRy2/QPf91aPvmQAHvraovAyS5BDgCeAGwxxgxSkuEuXMvJPn4bIchLZGqdpztECRJkjSLRu25sBZwZVXNG2xIsgzwBFpy4bu9skcBNwMPGjdISZIkSZK05Bo1ubAssOLQtocDqwB/qqrLBhur6mbgMuBOY0UoSZIkSZKWaKMmF/4JrJjkPr1tz+6efzlB+VVp8zBIkiRJkqTbqVGTC7/qnndOskySuwFvpA2J+HG/YJeAWJGWkJAkSZIkSbdToyYXPtU9vxK4HDgHuDdwJnDoUNlndc+/WejoZkGSXZJU73FBkkOTPGIh6tqmq2PVRRjfCl2MjxzavkF3ructqnMtjCTH9O7dTUnOSrJvl4iazZi+O31JSZIkSdLCGCm5UFUnAa8BrqYNeViBtnLE5lV101Dxrbvnn48b5Cy4Anh899gBeCBwVJK7jljPYV0d1y7C2FYAdgYeOV3BWfRz2nVvDPwv8DLgm7MZkCRJkiRp8Rl1KUqqav8k3wEeRuu98Pdu8sZbJFkB+ALwRVoDe2lzU1X9unv96yRn0YaEPAc4cKaVVNW/gH8t+vCWeJf27t/xSVYB9kiyTlWdP5uBSZIkSZIWvVGHRQBQVfOq6uSqOn04sdDtv6GqDqiq/avq8vHDnHW/757XG2xI8vgkP0pyfpJrkvwuyVb9gyYaFpHko0lOSXJ1knOTfCPJ2kPHvSDJ3K7ey5KcmOSp3e6ruuev9oYfbNA7fJVuGMIVXf27dsuFDup+cJJvJTknybVJ/pRkh6EyG3f1bpzkoC7WM5Jsvwjv31pJ9k9ySRfHMUke3du/V3fODN2bVye5Icla3ft3Jjm5u94LkxyS5P5TBZPkXkm+k+SiJPOS/D3Jhxfy2iRJkiTpDm+hkgt3QOt3z2f2tt0bOAF4HfB84Hu0Bv/Lpqnr7sBHgE1pQy7uCxydZFmAJPcDvgsc3dW7FW0+i8GQjKd3z7sxf+hGf9LMPWnDVl4CfB34YPd6YF3gVGB74Lm03iW7Av8zQaxfpCUGXgQcA+yTZKNprm8i6wM3A2f3tv2AttLIjsBLad/Fn/cSA18C7gM8lQVtAxxSVRd37+8FfBbYDNiWtlzqCUlWnyKeA2iJju2A/wJ259ZLrEqSJEmSZmjkYRF9SVYG7gIsP1W5qvrHOOeZDUkG9+betMbr74AfDvZX1bd6ZQMcR2vobssU8wtU1Wt6xy1LG25xLvDEro7/BK6qqnf1Dju89/rk7vnvvaEH9H7gP66q3tm9PirJc4DNge905/8Z8LNe3McDq3Rx7zEU7jerareu7DG0ZMfmwEmTXd/8cLIcraG/IbAT8IWquqDb+ZzuejeuqmO7bUcDZwHvAl5fVacmOQF4NS2xQZL7Ak8GXjA4UVW9vXfSZYGjgItoyYYDJolvI+BlVXVI9/6Yaa5HkiRJkjSFkZMLXRf/dwP/DdxvBofUwpxnlq0J3Nh7fwnwmKq6frAhyRq0X/w3o/UGWLbbdd5UFSf5L+ADwEOBO/d2PZCWXDgFWD3J/sA3gBOq6poRYv/J0Ps/M7/nBUlWojX2t+q2L9/bt9zQxJy31FVVNyY5nZZAmc7mLHj/TgLe2nu/EfCvQWKhq/+aJIcCT+qV+zLwmSRvqqqrab0WLgSO7MX8OODDwKOY37sD2v2czO9oc0CsCRw9VfIryXa0Hg60PJokSZIkadhIwyKS3B2YA7wPuD+QGTyWxqEXVwCPAR4HvJ62QsOB/XkJgP1o3fn3Ajbpyn8FWGmySpM8BvgRrafCK2lDGh7X7V4JoKpOpSUs7kvrsXBxkgNHWMpxeI6LG4Zi+hhtKMIXaMMiHkMbYgG3jn26uiZzdFfvk7rzbdQ7B8A9aUmCYReyYILgO7ThFFt2vSy2Bg4YJECSrE9LgIT2OT2xO+9F08T5Utr3+JPA2d18Gc+YqGBVfaGqHl1Vj24LpEiSJEmSho3ao2B32i/C1wKfAH5MaxAOL0O5tLupquZ0r09MMo/WxX4L4Nvdr/+bAm+uqs8PDhpKPkzkRbTVI15aVdUdc+/hQlV1GHBYN2/ApsDewGdovUXGtQXwmarasxf3poug3r7LevfvhC4xskOSz1bVObQ5Iu4+wXH3AC4dvOl6M3yL1mPhbNoQlf165Z9DG9Kx2aB3RzccY8olQ6vqPGCb7vPaCNgF+FGS9avqkhGvVZIkSZLu8EbtVfA82jCHbapq56r6ZVX9varOnuqxGOK+rX0d+BPzJz1ckTYMoj9MYjV6cwFMYmXgxkFiobPVZIWr6oqqOhA4GHhIt/mG7nkmPQgmi6Ef97IsmqTFVHbungfzI5wI3D3JU3pxrEJLpBw/dOyXafMs7AL8uqr+0tu3Mq1nQz+5tSUzTJpV1c3dvBW70pIUt0r0SJIkSZKmN2rPhdVpjduDF0MsS6yqqiQfAb6R5BlV9bMkJwMfTHIlrYH7HtpwijtPUdVRtF/w9wYOAZ4AvKJfIMnracMljgTOBx5A621wQBfLDUnOpA0V+CNwHfCHES7nKOBNSf5G6yXwJhbzSglVdW43h8S2ST5UVT/uJmv8dpL30Oa02JGWLNhr6NgTk/yJNsTi9UNVH01L8nw1yZdp81jsyK2Hc9yi6w3yY9r9PI127e8ELgD+MtlxkiRJkqTJjdpz4RzakIF/L45glnDfBk6nTWYJ8HLa0pQHAJ+iLUU52eoEBVBVh9N6P7yYNvfCU2m9Qfr+ANwN+F/afALvpy0J2V8q8g3AWsBPaatHrDPCdbwF+AWwD22OiD9y61UiFoeP0npbvLF7/yJaomNv4CDavAlPr6q/TXDsD4B5wLf6G6vqFNpqEo+lLdf5cloi5oop4riONmnm22ifwf60YT6bVNW8hbkwSZIkSbqjy4I99KcpnAwmA3xcVZ08Xfk7uiRvAfaqqoUdwiAgyUnAqVX1ytmNY71qOQlJw6p2nO0QJEmStJglmdsmu7+1UXsu7EmbWO/zSVyXbxJJlk3yNNqKEHNnO56lVZJHJ3k3bQWIT892PJIkSZKkiY0050JVXZLkmcCBwJ+T7Etb0u+qaY47buFDXCqtRhvXfwq3nidAM3cybf6EnewpI0mSJElLrlEndIQ2M/9ZtCX8PjiD8rWQ51lqVdXlwAqzHcfSrqoy2zFIkiRJkqY3UqM/yQa0pQLvOdg0k8NGC0mSJEmSJC1NRp1z4UO0lQkuAV4L3AtYvqqWmeqxqIOWJEmSJElLjlGHKzyDNszhZVX1s8UQj7TE2nDDezBnjjPiS5IkSdKwUXsV3AWYBxy9GGKRJEmSJElLoVGTC2cDqapaHMFIkiRJkqSlz6jJhe8AKyV5+uIIRpIkSZIkLX1GTS58DPgj8MUk91kM8UiSJEmSpKXMqBM6bgF8GdgFOCXJ94CTgKumOqiqDlio6CRJkiRJ0hJv1OTCfrTVIgACvKJ7TKUAkwuSJEmSJN1OjZpc+AfzkwuSJEmSJEmjJReqaoPFFIckSZIkSVpKjTqhoyRJkiRJ0gJMLkiSJEmSpLGYXJAkSZIkSWMZdULHWyR5AvAk4F7AnWirR0ykquq1C3seSZIkSZK0ZBs5uZDkAcCBwKOGd3HrlSQG20wuSJIkSZJ0OzVSciHJmsDRwLrAhcCxwJbAPOB7wNrAY4HVgIuBwxZlsJIkSZIkackz6pwLO9ASCycC96uq/+62X1FVW1fVJsA6wF7AWsC8qnr1IotWkiRJkiQtcUYdFrEpbZjDe6vq2okKVNU1wP8kWQF4a5KfV9VBY8YpSZIkSZKWUKP2XLgfLbnwi6HtK0xQ9qPd83ajBiVJkiRJkpYeoyYXlqcNgbipt+1a2hwLC6iqC4ErgEcsfHiSJEmSJGlJN2py4Xxg9ST94RQXAssluW+/YJLlgTsDq48XoiRJkiRJWpKNmlw4k7a85Hq9bSd3z68YKrtNV/95CxWZJEmSJElaKoyaXPhJ9/yc3rav0RIO70+yT5Jtk3wW+CxtfoYfjB+mJEmSJElaUqWqZl44eSAtwfDLqnp5b/uBwH/Tkgm3bAb+Ajyhqq5YNOFKsydZr+Btsx2GJGkpUrXjbIcgSdIik2RuVT16on0jLUVZVacBG0ywayvg58BLaUMmrgCOBD5hYkGSJEmSpNu3kZILk6nW/eGL3UOSJEmSJN2BjDrngiRJkiRJ0gLG6rmQ5G7AvYFVquq4RROSJEmSJElamixUz4UkL0jyG+AC4ETg6KH9ayQ5snvcaRHEKUmSJEmSllAjJxeSvAc4GHgkbUWIweMWVXUZcC3wLOC5I9a/S5KLh7Ytk+QbSa5LsskM69kmSSVZtXu/Qff+eaPEM0G9GyXZZZw6hupbIM7e9j2S3Jzk1SPUtVDXmGTj7riHTVNuyyTbzLDOs7o6K8kNSU5P8rHhZFOS/ZLMmUF9Fy/K+y5JkiRJWnRGSi4keSywO3AT8HZgLeDCSYp/nZZ0eME4ASYJbaLILYAtquon49S3CGwE7Lw4T5BkZ+A9wPZV9dURDv0n8Hjg+MUSGGwJbDNC+QNp8TwTOID2nfnUUJkPj1inJEmSJGkJM+qcC2/rnveoqk8BtLb/hI7tnh+zEHH1fRZ4FfDSqjpkzLqWeEneDewC7FBVnx/l2Kq6Hvj14ohrIf2zqgbxHJdkXWCbJNtV1c0AVfX32yqYLlG1YlVdd1udU5IkSZLuCEYdFvGk7vmz0xWsqkuAq4F1Rw1qIMkngDcAW1fV94b2bZnklCTXJzknye5JRkqWdMMBrkryke7945P8KMn5Sa5J8rskW/XKbwN8pns96PJ/TPf+wUm+1cVybZI/JdkhyYzvcZK3Ah8D3jNI3vT2HZPku0lenuRvSa5MckSSe/XK3GpYRJIVk3wuyeVJLkmyVxdXTRDCWkkOSnJ1kjOSbN+rZz/gxcBTe9e+y0yvrfN7YEXgbv16h4dFJHlKkt93w2DmJnnCRJUl2SzJnK7cBUn2TLJ8b/8u3XCKJyU5GbgO2CLJ8kk+nuQf3ffn/CQHJ1lhxOuRJEmSJDF6z4W7A1dV1cXTlmxuBFadttQEkuxO60b/2qo6cGjfJsC3aV3t3wU8gta9fk1aMmIm9T+bNnfER6vqQ93mewMnAJ+nNUSfCHw1yc1V9U3gMOATwDtp3f0Bruye1wVOBb4BXEWbk2JXYGVgjxmEtG1X9y5V9bFJyjwWWKc7/8q0IQZfYOp5LfakDTt4L/AX4NXAf09S9ovA/l2dLwP2STKnqk6i3d/1gbsAg6TDuTO4rr71afdm0u9PknWAI4CTgJfQrvcbwCpD5bYEvgns213b/Wj3eRlgx17RVbpr2hM4DTgf2AnYijb05Exgbdo9XHbE65EkSZIkMXpy4Vpg1STLDLq1TybJnWkN0X8tRFxr0hqMn5xkzoEPAcdU1au690d2wzP2SLJbVU3Z6E3yAuA7wPur6uOD7VX1rV6ZAMcB96I1/L9ZVf9KclZXdoHhB1X1M+BnvWOPpzVst2VmyYX/BQ6uql2nKHNnYNNuwkySrA18MsnKVTVvgutcE9gO+GBVfbLb9mPgj5PU/82q2q0rdwzwfGBz4KSq+nuSS4Flhq99Cul6k6wAPIWW+Nm9qv49xTE70BI7m1bVtV0l19Dm8LilUmAv4ICq6veuuJ6WENmj6zkDLQnzjqr6Ya/cRsCBVbV/77zfmeE1SZIkSZKGjDos4jTar7uPmEHZF9MmdPz9qEHRegOcCLw2ySP7O5IsCzwKOGjomG/TrufxTO3F3bHv7CcWurrXSPLpJGfTel3cSGucP3C6gJOslGTXJH8Dru+O3R24zwyHa/wEeF7Xo2IyJw8SC50/d8+TDT15OLAS8KPBhqoqYLK5K37SK3cjcDotubKw3kG7D9fQeiP8fIpeGQMbAUcNEgud7w+VeSCtF8R3kiw3eNCWRF0J6K96Ud25+35Hm/vh3Uke0SUrJpRku27oxZw2ykeSJEmSNGzU5MIhtITBe6YqlOT+wEdpDbsfLERcNwKb0rqwH5Hkvr19awHLc+tVKgbv7zpN3S8ALqUNiRi2H/BS2q/im9Amo/wKrcE6nY/RuuMPhik8Btit2zeT47cCfgV8r/tlfSKXD72/YZr61+6eh3uPTNabZKL6ZxL7ZL5Ouw8bA18FXpTkjdMcszZwUX9D1yuj37Jfq3s+nPlJoBtpQxwA1uuVvayqbmBBuwH70IZ3/B44J8nbmEBVfaGqHl1Vj17IET6SJEmSdLs3ZXIhydZJtuht+gyt4bdFkq8mefBQ+fsmeS9wMm3SvrNojfORdd3aN6Ete/njJHfvdl1Ma0jefeiQe3TPl05T9VuA84CjumEDg9hXoiU0dq6qz1bV0VU1h5knYLYAPlNVe1bVT7tjb5rhsdCGArwAOAM4LMmDRjh2Mhd0z3cb2j78fnG5sKrmVNWxVfUaWs+CDyW50xTHXMDQZ5tkZRZs2Q8+4+1oyYvhR7+nwq0mrqyq66rqg1W1Aa0XxLeBvZM8Z5SLkyRJkiQ10zWc9wP2HrypqiuBzWjDFrYG/kTXEExyNa0b/YeB1YFLgM275REXSlWdAzyHNgfDEUlW68brz6U15vu2BG6m/fo/lSuBZ9ManT/u5oaAtorBsrQhDXTXtBqtwd93Q7dv+Bf9lYeOXZbJJ06cUFVd0cV2dRfbOqMcP4FTaEmLzXpxhTaXwsIYtyfDTrReB6+doszJwLOS9Cdw3HyozKm0BNEGXfJi+HEJM1RVp9N6nFwPPGSmx0mSJEmS5pvJr/ILjEevqhNpKyF8n9ZAT/dYpVf2B8BGVbUw8y0soKr+BDwP+A9gsFzgzsDTut4Tz06yIy2p8cXpJnPs6rwEeBZtwslDk6zSNexPBj6Y5MVJXgT8FLhi6PC/ds9vS/KYXg+Do4A3JXllkk1pQ0hWXIjr/SctwbAKbaLKu4xaR6+uS2grQOya5O3dL/Pfok0MOdFSlNP5K/DwJC9M8uhRkx/dqhNHAW/vki8T2ZuWqDk0yfOSbEcbxnDLhJXdZKLvBN6V5DNJnpvkmd38CIcPJSZupVt28v1JNk3ydNoQieVoE3hKkiRJkkY06pwLAFTV2VW1Ba17/fNo3dPfCLwIWLuqNq+qM6eqY8Tz/ZLWM+GpwNdojf7/Bh5Na8TvQFvG8c0j1PlP4BnABsD3u6TFy2nj9g+gLfP4ve513y9oczK8jTbp5L7d9rd0+/ahDQX5IzNbJWKi2E6jDdG4D/CjCXpJjOLdtB4ou9CWbrwQ+DLzl9Acxf/RJn38Ci0Rs91C1LEb7Z5vOdHOqjqPNmfFWrT7vz3wCtpKJf1y36b1yHgkbYLO73dlf8P8uSgm80vghcCBwA+BDYEXd0NZJEmSJEkjSls8YJKdyc3ABVU1bvd8LUGS/BRYvqqeOtuxLE2S9arllCRJmpmqHWc7BEmSFpkkc9tk97c2kyUStRRL8jTgsbRf9JenrYbxDG49Z4UkSZIkSQvF5MLt39W0IQA70SZjPB3Ypqq+O6tRSZIkSZJuN2aSXLhHkn+PcY6qKpMYs6SqTgYeN9txSJIkSZJuv2ba6M/0RSRJkiRJ0h3RTJIL19BWYpDu0Dbc8B7MmePEXJIkSZI0bCbJhauratfFHokkSZIkSVoqLTPbAUiSJEmSpKWbyQVJkiRJkjQWkwuSJEmSJGksJhckSZIkSdJYTC5IkiRJkqSxTLlaRFWZfJAkSZIkSVMyeSBJkiRJksZickGSJEmSJI3F5IIkSZIkSRqLyQVJkiRJkjQWkwuSJEmSJGksJhckSZIkSdJYTC5IkiRJkqSxmFyQJEmSJEljMbkgSZIkSZLGYnJBkiRJkiSNxeSCJEmSJEkai8kFSZIkSZI0FpMLkiRJkiRpLCYXJEmSJEnSWEwuSJIkSZKksSw32wFIS4u5cy8k+fhshyFJkrTUq9pxtkOQtIjZc0GSJEmSJI3F5IIkSZIkSRqLyQVJkiRJkjQWkwuSJEmSJGksS1VyIcnmSY5OcnmS65OclmS3JGt1+zdIUkmeN9uxLowkxyT57jRllk/yjiR/THJtkouTnJjkPbdVnOOa6DqTrJnklCRnJVl/af8sJUmSJOmOZKlZLSLJJ4AdgK8CnwSuBB4CvAF4KPCi2YtukdkeuHGaMp8FtgJ2B04E7gI8Dng+8NHFGt1ikuQuwFHAGsBTq+ofSVYEHg/8dVaDkyRJkiRNa6lILiR5PvAO4LVV9ZXermOTfAHYZHYiW7Sq6s9T7U+yCvBq4H1VtVdv1/eTZLEGN6IkK1fVvBmUWw04EliHllj4O0BVXQ/8evFGKUmSJElaFJaWYRFvB34zlFgAoKr+XVVHDG1eJcm+Sa5Icm6SXZMscK1JHpbksCRXdY+Dkqzd279x1y1/427f1UnOSLL9UD37JZmT5FlJ/pDkmiTHJ3noULl3Jjm5i+nCJIckuf9QmemGRdwJWB64YIL7UL16tuliX3Wo/rOSfHz4fEm26/bN6+7JukPHrZRkzyTndMNRfp/kuRPU/YkkH0hyLq1nyZS6ZMlhwP2AZ1TVqb19txoWMYg/ydu7z/Wy/9/enUdfUtR3H39/BBGGfRsxYkCMitH4qIxEIUQ8KiqYoIiKhqiJSoxPfDQRNSjo4PaIKBqXoJgIalSSqAiCggQYVIySYTEGBTWCBmSR3QHZv/mj+jKXO/e33t86836dc0//uruqbnUXxZn+3qrqJMd3Ix/6y31sku8kuS3JRUn27trouL40j05yapLruzb7UZL/O1GdJUmSJElrWvDBhST3B3aj/bo9We8DVgH7A/8EvK37u1fm7wDnABsCfwq8nDa14qtDRgB8Evg+bdrFCuBjSXYdSPPbwJG0qQovBpYC/zJQ1va0KQ37Aq8C1gPOSbL5ZC+qqn4F/A+wvFt/YtPJ5h3Hk4HX0o0MAR4LfGUgzRdp9+g9tOkX/wGclORxA+leAjyFNr3jRRN874bAScBjgGdU1UWTrO8LgacBBwFvBp7T1Qu4N2BxGrARrS3eRZtG89sD5ZwE3A0cCPwx8BFgJu6nJEmSJK1zFsO0iK2BBwC/mEKeb1bVG7q/T0/yLGA/4F+6Y2+n/fr/7Kq6AyDJf9Lm9+9N+zW95wtV9a4uzQraw/V+wLl9abYCdq+qn3Tp7gecADyyK5Oq+ute4iTr0dYYuIYWbPjMFK7t5cDxwJeAe5Jc0O1/uHctU7QU2K2qft7V7efAt5M8q6pOTfI0YB9gz6o6u8vzjSSPAN4KvGCgvOdU1W2T+N59uu2+VXXhFOp7J/Dcqrqrq+/vAgfQAhrQpo1sDSyrqiu6NP9NW5+Cbn8bYKeunB90h8+YQh0kSZIkSX0W/MiFPjVxknt9Y2D/h7SRAz1Ppz3835Nk/STrA5cClwHLxiqrqu4EfjJQFsBlvcBC3/fRny7Jk5KcnuQ64C7gVmAT4BFTuC6q6kzaNIIXA5+iPUgfCZw5OPVjks7vBRa68s+hBT16ozOeTgvEnNO7V939OoM179UZkwwsAJwPXAu8ayqjN4CzeoGFzg+BpUk26PafCJzXCyx013QucHVfnutpI0A+nuRFSZaO9WXdlJGVSVa2wTCSJEmSpEGLIbhwHXA7aw5rH8+NA/t30Ibh92xDG1J/58BnJ+AhUyxrrDT00iX5bVqQIsBfALvTHoKvGVLWhKrq11V1fFW9qqvzO7sy/2iqZXV1GHbsQd3f2wDbsea9Ws6a9+pqJu9S2uiFnWhTLCZ7H4bd6wC94MJ2wK+G5Lv3WFXdQ1sE9CpagOaqJN9K8vjBTFV1TFUtq6plLRYkSZIkSRq04KdFVNWdSc4BngkcOkPFXk8bufAPQ85dO0Pf0e9ZwBLaFIBbALpf/7cateCqqiRHAocBOwMnAr3RAxsMJN9ySBHDfrVfClzZ/X09cAXw3MlUZxJpVieuOjfJ84GvAl9Isn9V3T2VMoa4ijYdZdC2A999MfD8bk2PPYAjgFOSbN8FHyRJkiRJk7QYRi4AfAhYluRlgyeS3K9bU2EqzqAtJHheVa0c+Fw2A/UdtBFwD206RM8LmWJwJ8n9B9+M0Hl4t+2NHLi82z6qL+/vA5sNyfuEbmRFL93utOBCb02JM2ijAVYNuVcrp1L/YarqNNo6CfsCR49aHm2xyWX9b7zoFuB84Bjff2c31eQo2miNYfdXkiRJkjSOBT9yAaCqvprkKOAfu4ffE2kT4HcGXk1bK2Eqb5NYTnt4PiXJp2ijFR4MPAM4rqpWzFjlmzNpb4c4Nsk/0t5McTBrDvGfyObAj5N8GjgLuIn2K/0htNEFJ3Tpzu32P5zkMNoIiTcx/PWQ1wAnJ1lOm6JxBG0dht79PJ329oXTkxwBXEQLUjwO2LCqDpniNayhqj7XrXtwVJKrq+qwEYo7ljbC5eQkh9MCO4fTpkXcA+1VlcD7gX8GfkYb0fFm4PtVdf0I3y1JkiRJ66RFEVwAqKo3JPkO8FfA52kPjZfRXin4/imW9eMkT6K9pvCYrqwraL/S/3QGq937vh8k+TPaWyqeR3u15QtoD7dTcTPtNZt70177uBmt3qcB76qqm7rvuyPJ84C/p71G8hLgL4HPDSnzwaCr4QAAFmtJREFU34F/o40O2Zb2us2D+upeSfYD3gK8nrb2xfXAhbTXN86IqvpgkgcChya5ivu+sWMq5dzajWQ5mnZ/L6MFVt7H6uDKVbRRHm8FfosW5DmLFmCQJEmSJE1RqqY0TV5rke7VmtdW1f7zXZfZlOShwI+Bg6rq2OmX85CC181cxSRJktZRVQfPdxUkTUOS89pi92taNCMXpMlKcgjwS+DntJEWh9CmRXxpPuslSZIkSWsrgwtaGxVtCspv0V5j+i3g4KoatuaEJEmSJGlEBhfWYVW153zXYTZU1XuB9853PSRJkiRpXbFYXkUpSZIkSZIWKEcuSJO0yy4PZOVKFx+SJEmSpEGOXJAkSZIkSSMxuCBJkiRJkkZicEGSJEmSJI3E4IIkSZIkSRqJwQVJkiRJkjQSgwuSJEmSJGkkBhckSZIkSdJIDC5IkiRJkqSRGFyQJEmSJEkjMbggSZIkSZJGYnBBkiRJkiSNxOCCJEmSJEkaicEFSZIkSZI0EoMLkiRJkiRpJAYXJEmSJEnSSAwuSJIkSZKkkRhckCRJkiRJIzG4IEmSJEmSRmJwQZIkSZIkjcTggiRJkiRJGonBBUmSJEmSNBKDC5IkSZIkaSTrz3cFpMXivPOuJnn/fFdDkiRJ0lqs6uD5rsK0OHJBkiRJkiSNxOCCJEmSJEkaicEFSZIkSZI0EoMLkiRJkiRpJAYXpinJ8iSV5CdjnP9pd375HNfp2hkq67gkK+fw+x7T3a89+45Vkr+aifIlSZIkSbPHt0WM5jbgoUmWVdW9D+JJngjs0J1frN4JbDTPdXgycOk810GSJEmSNAFHLozmFuBM4ICB4wd0x2+Z8xrNkKr676r6r3muw3er6ur5rIMkSZIkaWIGF0Z3PPDCJAHoti/sjt9HkhVJvjhwbM9u+P9juv0du/0Dkhyb5OYklyc5sDv/piS/TPKrJEckWaMNk+ye5PwktyW5MMkfDJx/aZJvJ7k+yQ1JzkqybCDNhNMihnxv71r2TPKvSVYl+VmS1wxJ+5ok/5PkliRfBR40JM19pkUk2SfJ6Umu6e7Ld5PsNZBneZJrkzy+O39rkguS7DGQ7o+TnNd9/w1JvpfkKVO5XkmSJElSY3BhdF8GHgj0HuD3ALYFThix3COAK4HnA98CPp3kA8CuwJ8DHwLeRAtk9FsC/BPwceAFwI3A15Ns15dmR+Az3fmXAJcD30yy04h17vkk8H3gecAK4GNJdu2dTLIv8DHgZGA/4AfApyZR7kOBrwJ/Srsv36Fd2+4D6ZYAnwY+0aW7HTghyZLu+x8GfJE2uuSPgD/p6rLV1C9VkiRJkuSaCyOqqhuTnEqbCvGtbntqd3yUos+sqrcAJPkesD/wx8DOVXU3cGr3kP487jtKYiPgrVX1+S7vWcAvgNcDf9vV+R29xN3Ih9OBJwIHAu9gdF+oqnd15a+gPcDvB5zbnX8r7R79Zbd/WpJtgVeOV2hVfXSg3mcBjwZeAZzTl3Qj4PVVdWaX9krgAuAPgVOBxwO/rqo39uX52tQvU5IkSZIEjlyYKccD+yd5AC0IsMaUiGk4o/dHVd0M/Ao4uwss9PwUePCQvPeOmqiqVbTgQf/IgUclOSHJ1cDdwJ3AI4FHzEC9Ab7R9/13Aj8Btu++ez3aw/2JA3m+PFGhSbZP8ukkVwB3dfXea0i976SNmOj5Ybfdvtv+ANi8K2uvJBuP850HJVnZpoismqiKkiRJkrROMrgwM04CNgHeDWxMG7o/qhsH9u8Y49iGA8dWVdVvBo5dQ7emQZJNaQ//DwH+hjaN44m0aQyDZU3XePXcljZi5pohdRxTN1LhJGA34G3AU2n1/jpr1vvmqrqnt1NVd3R/btjtXwLsC+xEG7FwbZLPd6Mn7qOqjqmqZVW1rDWxJEmSJGmQ0yJmQFXdkuRk4K+Bf62qsd4ScRuwwcCxmZ7nv0mSjQYCDEtp6zdAe73j9sAzquriXoIkm89wPcbyK9qog6UDxwf3B/0ObcTDs6vq1N7BJNN6XWZVnQKc0l33PrQ1LD7Cmm/+kCRJkiRNwJELM+do2oiFj4+T5nJg54Fjz5iFujyv90eSTbrv6K130HsYv70vzW60RR5nXTet40LayIF++02QdVi9dwAGF3Ocan1u6tanOAH43VHKkiRJkqR1lSMXZkhVreC+8/yHOQF4RZIPAqfQhvY/c4ar8hvg3V1Q4ZfAwbTREn/Xnf8ubfGATyZ5H20Uw3Lgihmux3jeA3w5ydG0e/IU4FkT5LmYFpz5QJLDgE2Bw5lGvZP8BW0Ex6m0e/Rw2pszPjPVsiRJkiRJjlyYU91Q/LfQFn08AdiB9haHmXQr8FLgNcCXgC2Bvavqyq4OV9MepLejLar4euDVtMUh50RVnQC8lvYWia/Qpju8YoI8t9NGN9xFe43kO4H/D5w9jSr8J23th6No608cSnt95punUZYkSZIkrfNSVfNdB2lRSB5S8Lr5roYkSZKktVjVwfNdhTElOa8tdr8mRy5IkiRJkqSRGFyQJEmSJEkjMbggSZIkSZJGYnBBkiRJkiSNxFdRSpO0yy4PZOXKhbu4iiRJkiTNF0cuSJIkSZKkkRhckCRJkiRJIzG4IEmSJEmSRmJwQZIkSZIkjcTggiRJkiRJGonBBUmSJEmSNBKDC5IkSZIkaSQGFyRJkiRJ0kgMLkiSJEmSpJEYXJAkSZIkSSMxuCBJkiRJkkaSqprvOkiLQpJfA5fMdz10r22Aa+e7ErqX7bFw2BYLi+2xsNgeC4dtsbDYHgvLQm6PHapq22En1p/rmkiL2CVVtWy+K6EmyUrbY+GwPRYO22JhsT0WFttj4bAtFhbbY2FZrO3htAhJkiRJkjQSgwuSJEmSJGkkBhekyTtmviug+7A9FhbbY+GwLRYW22NhsT0WDttiYbE9FpZF2R4u6ChJkiRJkkbiyAVJkiRJkjQSgwsSkOR3k5yR5NYkv0zyjiTrTSLf5kmOTXJDkpuSfC7J1nNR57XVdNoiyY5Jasjn+Lmq99oqye8k+USS7ye5O8mKSeazb8yw6bSFfWN2JHlBkpOSXJFkVZLzkrx4EvnsF7NgOu1h35g9SfZP8p0k1yW5LcklSQ5NssEE+ewfM2w6bWHfmBtJHtz9/6qSbDJB2kXTN3wVpdZ5SbYE/g34IbAv8DDgA7Tg26ETZP9n4JHAK4F7gCOArwB7zFZ912YjtgXAwcA5ffsL9f3Ai8mjgb2B7wLj/sNwgH1j5k23LcC+MdP+BrgU+Gvavdwb+HySbarqI+Pks1/Mjum2B9g3ZsPWwFnAkcCNwK7AcmA74K/GyWf/mHnTbQuwb8y2I4FVwMaTSLt4+kZV+fGzTn+AQ4AbgM36jr0JuLX/2JB8TwYK+MO+Y7t2x54+39e1GD8jtMWO3X1/znxfw9r2Ae7X9/cXgRWTyGPfWDhtYd+YnbbYZsixzwOXjpPHfrGw2sO+Mbdt9G7aw23GOG//WDhtYd+Y/TbYA7ieFsApYJNx0i6qvuG0CAmeDZxWVTf3HTse2Ah4ygT5rq6qb/YOVNW5tF9Pnj0bFV0HTLctNEuq6p5pZLNvzIJptoVmQVUN+wXvAmDpONnsF7Nkmu2huXUd44+4sn/MnYnaQrOom+r7EeAdTG40yKLqGwYXJNgZuLj/QFX9gvZr+c5Tydf50QT5NLbptkXPsd1c9CuTHJVko9mopCZk31h47BuzbzfalK6x2C/m1kTt0WPfmCVJ1kuyJMkfAP8POLq6n12HsH/Moim2RY99Y3a8GtgQ+Ngk0y+qvuGaCxJsSRseNuiG7tx08u00A/VaF023LW6n/U/6G8DNwJ7Am2lrNuw7s1XUJNg3Fg77xhxI8jTa/fzzcZLZL+bIJNvDvjH7bgEe0P39GeCN46S1f8yuqbSFfWOWdIswvhM4sKruTDKZbIuqbxhckJph0duMcXwm8mlsU76nVXUl912YaEWSq4G/T/K4qrpwhuuoidk3FgD7xuxLsiNtfv+JVXXcBMntF7Nssu1h35gTuwFLaPPD3wZ8FHjNOOntH7Nn0m1h35hV7wa+V1Vfm2K+RdM3nBYhtcjfFkOOb87wSOFE+baYIJ/GNt22GOaL3fYJI9VI02HfWNjsGzMkyVbA14FfAAdOkNx+Mcum2B7D2DdmUFWdX1XfrqqjaEPx/zLJw8ZIbv+YRVNsi2HsGyNK8mjaaKrDk2yRZAtawAdg83GmnSyqvmFwQWrzmO4zZynJQ2ivhhk2x2nMfJ2x5kZpYtNti2FqYKu5Y99Y2OwbMyDJEuBk2sJo+1TVLRNksV/Momm0xzD2jdlzfrd96Bjn7R9zZ6K2GMa+MbqHA/cH/p0WMLiB1esuXE5b5HGYRdU3DC5I7VeOZybZtO/Yi4DfAGdPkG+7bnEcAJIso81/+vpsVHQdMN22GGb/bnveTFRMU2LfWNjsGyNKsj7wr7R/LD67qq6ZRDb7xSyZZnsMY9+YPbt320vHOG//mDsTtcUw9o3RfRt46sDniO7c3sCRY+RbVH0jEy8UKq3dkmxJW1H6v2idfCfgKOBDVXVoX7qfAmdX1Sv6jp0KPIL2ntp7uvzXVNUec3cFa4/ptkWS5cCmwDm0xYf+kLZY0deq6vlzeQ1rm+7XwL273TcAmwFv7/a/VlW32jfmxnTawr4xO5IcA7wKeB1w7sDpC6rqdvvF3JlOe9g3Zk/33/m/ARcBd9MeZt8AnFxVB3Rp7B9zYDptYd+YO0leDhwLbFpVq7pji7pvuKCj1nlVdUO3svRHga/S5i99EFg+kHR9YL2BYwd0aT9FGwl0Mm0um6ZhhLa4mPY/3FcCG9Hm2x5JWzhHo1lK+0WwX2//ocBl2DfmynTawr4xO/bqtn835Jz9Yu5Npz3sG7PnP4CXAzsCdwE/Aw4BPt6Xxv4xN6bTFvaN+bWo+4YjFyRJkiRJ0khcc0GSJEmSJI3E4IIkSZIkSRqJwQVJkiRJkjQSgwuSJEmSJGkkBhckSZIkSdJIDC5IkiRJkqSRGFyQJEmSJEkjMbggSZIWnSTLk9RkPvNdV0mS1gXrz3cFJEmSRnT1fFdAkqR1ncEFSZK0qFXVdvNdB0mS1nVOi5AkSZIkSSMxuCBJktZqSXbsW4NhxyQPS3JMkkuT3J7ksiF5npvkK0l+meSOJDck+WaSVye5/wTf9ydJzkny6yQ3JflekoPSHNfV47gh+Xp13HOcsld0aZaPk+bxST6V5L+T3JpkVZLvJ3lXkm3GyNNbw2JFt/+0JKck+VWS25L8KMnbk2w4wbVvneRt3TVf3+W9LMlp3b3bvEv3qL7r3XWCMj/bXzdJ0sLktAhJkrQu2Q34BLAJcCtwZ//JJJsAXwCe03f4ZmBzYI/u89Ik+1TVDQN5A/wj8GfdoQJuBJYBuwJPBW6f4eu5jySHA4cB6Q7dCtwfeGz3+fOu7heMU8YbgSO63ZuADYCdgeXAU5I8o6ruHpJvL+B4YMvu0F3AKmCH7rMXcBXwlar6UZKzgacABwHnjlGXLYH9u91jJrp+SdL8ceSCJElal3wCuAh4YlVtXFWb0B56ez5LCyz8FHgJsFlVbQ4sAfYFfgY8GfjUkLJfy+rAwkeBpVW1FbAV7cH8RV0ZsyLJ64G30R7oDwEeVFUbd3VfBpwJPAg4qQuiDPN/gPd2n6VVtSWwBfCO7vxTgZcN+e7HAyfSAgsXAXsDS7r8GwNPBD4A/Lov29Hd9oAkm45RnwOBDYHrgC+Nd/2SpPnlyAVJkrSoJblqnNNPA27p278OeHpVreodqKofd+XsAzyX9uv6nlV1RV+a22gP5ecDFwPPTfK4qrqwy7sh8PYu+Wer6rV9eW8CDu/S/O30r3Rs3XSHd9NGSzyvqs7o+/67gfOSPBP4LrAL8ErgQ0OK2gI4vKqW9+W/GXh7kscA+wEvZs3gyodpQYCfALt319zLfyuwsvv0+zJwDbCUFsj5xJD6vKrbfrqqZnXUhyRpNI5ckCRJi90Dx/kMro/w0f7AwoBXdtvP9gcW+lXV5cBZ3e4z+07tRRuhAKt/5R/0XuC2Mc6N6k9oIxRW9gcW+lXVXbQpH3Dfuve7HXj/GOdO7LaP7T+Y5OHAH3S7b+kPLIynqu6kTSOBNjXiPpI8Cfi9btcpEZK0wDlyQZIkLWpVlfHOJ9mxb/eccZL2HpAPSvLScdJt3m136Du2rNv+T1X9dFimqropyXnA7uOUPV29uj9mgpEcG3XbHcY4f9E4wZdfdtutBo7v1m3vBr4+bi3XdAzwZuAJSZ5QVef3neuNWji7qi6ZYrmSpDlmcEGSJK1Lrhl2sHsDRO9NCpuzOoAwniV9fy/ttkNHPPS5fBLlTsdvdduNWB1AGM+SMY7/eozj0BZohDX//bhdt722qm5hCqrqsiSnAc+mjV54NUCSzWhrVMDw6RKSpAXGaRGSJGldssZbDjrr9f19QFVlEp+XDymnZr7Kk9Kr/8cnWfcdZ6EO07323sKOL0myce9v2kKQ19HWZpAkLXAGFyRJ0jqvW7Cxt1bA742Xdgy9ERHbT5DuweOc6wU+NhwnzVgjKnpTIaZT91Fd2W237QsOTMUpwC+ATYEDumO9KRHHuZCjJC0OBhckSZKa3noML0gy1X8j9d6E8JAkDxuWoBvqv8s4ZdzQK2OM/JsCjxojb6/uT0oy1noKs+U73XY92vSGKamqe4BPdrsHJXkC8IRu/5PDc0mSFhqDC5IkSU3vjQSPAN44XsIkGyfZoO/Q6awODhw2RrY3Mf56CN/vts8f4/zBwAPGOPdZ4De0B/yPJVlvjHQkuV+SLcapx5R0C1h+s9t9TxdEmap/oK3psCurX5G5woUcJWnxMLggSZIEVNWJwAnd7nuTHJ3kEb3zSTZI8vtJjgB+zupFHKmq3wDv7HZfluRDSbbu8m2W5DDgLcCN41Th3tdEJjm895CeZJsk7wEOHSt/VV0F/G23uw9wepLde0GGNDsn+Rvgv4DnTOqmTN7raK/ZfDhwTpJndYtkkmRJd98+nuTp49S/96rLPbqtr5+UpEXE4IIkSdJqBwLHd3+/Grgkyaok19NGBnyXNgJha9ZcwPDvaCMIoD1sX9Plux54B/DPrH6AHuY44Kzu77cBN3b5r6EFDt7M6tENa6iqD3d1uxt4KvBt4NYk1wK3Az8CPkCbWjGjC09W1YXAvrR1Kx5DeyXlLV39b6Hdt78ANhmnmKP7/nYhR0laZAwuSJIkdarq1qp6Me3h/LPAz2j/XtqE9pB/Ju0B/uFVdcVA3nuq6qXAS2kP07+hvbbxfFqg4iUTfPfdtFEHbwcuBu6gBQG+ATyjqt4/ifofCewMfBD4T9pogi2AVcB/AO8DdgM+P1FZU1VV36CNXHg3cAHt+jcCLgNOowUXzhyniDNpgRhwIUdJWnRSNV9vTJIkSVq3JDkOeBnw6TFeZbnOSrILqxfG3Nn1FiRpcXHkgiRJkhaC13bbMw0sSNLiY3BBkiRJ8yrJ3rT1LgAmnP4hSVp41p/vCkiSJGndk2R72qKTS4Btu8MnV9XX569WkqTpMrggSZKk+bA+sANt0crLgS8Ch81rjSRJ0+aCjpIkSZIkaSSuuSBJkiRJkkZicEGSJEmSJI3E4IIkSZIkSRqJwQVJkiRJkjQSgwuSJEmSJGkkBhckSZIkSdJI/hes1w15Ze2wQgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "winners_of_IPL['team'].value_counts().plot(kind = 'barh', figsize = (15,5), color = 'darkblue')\n",
    "plt.title(\"Winners of IPL across 11 seasons\",fontsize=18,fontweight=\"bold\")\n",
    "plt.ylabel(\"Teams\", size = 25)\n",
    "plt.xlabel(\"Frequency\", size = 25)\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- MI and CSK have both won 3 times each followed by KKR who has won 2 times.\n",
    "- Hyderabad team has also won 2 matches under 2 franchise name - Deccan Chargers and Sunrisers Hyderabad"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Does teams choosed to bat or field first, after winning toss?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Decision taken by captains after winning tosses')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matches['toss_decision'].value_counts().plot(kind='pie', fontsize=14, autopct='%3.1f%%', \n",
    "                                               figsize=(10,7), shadow=True, startangle=135, legend=True, cmap='Oranges')\n",
    "\n",
    "plt.ylabel('Toss Decision')\n",
    "plt.title('Decision taken by captains after winning tosses')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Close to 60% times teams who have won tosses have decided to chase down"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How toss decision affects match results?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Frequency')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "matches['toss_win_game_win'] = np.where((matches.toss_winner == matches.winner),'Yes','No')\n",
    "plt.figure(figsize = (15,5))\n",
    "sns.countplot('toss_win_game_win', data=matches, hue = 'toss_decision')\n",
    "plt.title(\"How Toss Decision affects match result\", fontsize=18,fontweight=\"bold\")\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)\n",
    "plt.xlabel(\"Winning Toss and winning match\", fontsize = 25)\n",
    "plt.ylabel(\"Frequency\", fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Teams winning tosses and electng to field first have won most number of times."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Individual teams decision to choose bat or field after winning toss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (25,10))\n",
    "sns.countplot('toss_winner', data = matches, hue = 'toss_decision')\n",
    "plt.title(\"Teams decision to bat first or second after winning toss\", size = 30, fontweight = 'bold')\n",
    "plt.xticks(size = 10)\n",
    "plt.yticks(size = 15)\n",
    "plt.xlabel(\"Toss Winner\", size = 35)\n",
    "plt.ylabel(\"Count\", size = 35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Most teams field first after winning toss except for Chennai Super Kings who has mostly opted to bat first. Deccan Chargers and Pune Warriors also show the same trend."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which player's performance has mostly led team's win?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Players')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "MoM= matches['player_of_match'].value_counts()\n",
    "MoM.head(10).plot(kind = 'bar',figsize=(12,8), fontsize=15, color='black')\n",
    "plt.title(\"Top 10 players with most MoM awards\",fontsize=18,fontweight=\"bold\")\n",
    "plt.ylabel(\"Frequency\", size = 25)\n",
    "plt.xlabel(\"Players\", size = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Chris Gayle has so far won the most number of MoM awards followed by AB de Villiers.\n",
    "- Also, all top 10 are batsmen which kind of hints that in IPL batsmen have mostly dictated the matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How winning matches by fielding first varies across venues?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-47-e4ab3f734c32>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  new_matches['win_batting_first'] = np.where((new_matches.win_by_runs > 0), 'Yes', 'No')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Venue')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_matches = matches[matches['result'] == 'normal']   #taking all those matches where result is normal and creating a new dataframe\n",
    "new_matches['win_batting_first'] = np.where((new_matches.win_by_runs > 0), 'Yes', 'No')\n",
    "new_matches.groupby('venue')['win_batting_first'].value_counts().unstack().plot(kind = 'barh', stacked = True,\n",
    "                                                                               figsize=(15,15))\n",
    "plt.title(\"How winning matches by fielding first varies across venues?\", fontsize=18,fontweight=\"bold\")\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)\n",
    "plt.xlabel(\"Frequency\", fontsize = 25)\n",
    "plt.ylabel(\"Venue\", fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Batting second has been more rewarding in almost all the venues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Is batting second advantageous across all years?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,5))\n",
    "sns.countplot('season', data = new_matches, hue = 'win_batting_first')\n",
    "plt.title(\"Is batting second advantageous across all years\", fontsize=20,fontweight=\"bold\")\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)\n",
    "plt.xlabel(\"Season\", fontsize = 25)\n",
    "plt.ylabel(\"Count\", fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Exceptt for 2010 and 2015, in all other years it can be seen that teams batting second have won more matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Teams total scoring runs, over the years?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([15000., 16000., 17000., 18000., 19000., 20000., 21000., 22000.]),\n",
       " <a list of 8 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merge.groupby('season')['batsman_runs'].sum().plot(kind = 'line', linewidth = 3, figsize =(15,5),\n",
    "                                                                                             color = 'blue')\n",
    "plt.title(\"Runs over the years\",fontsize= 25, fontweight = 'bold')\n",
    "plt.xlabel(\"Season\", size = 25)\n",
    "plt.ylabel(\"Total Runs Scored\", size = 25)\n",
    "plt.xticks(size = 12)\n",
    "plt.yticks(size = 12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Run scoring has gone up from the start of the IPL in 2008."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top Run Getters of IPL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([   0., 1000., 2000., 3000., 4000., 5000., 6000.]),\n",
       " <a list of 7 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#let's plot the top 10 run getter so far in IPL\n",
    "merge.groupby('batsman')['batsman_runs'].sum().sort_values(ascending = False).head(10).plot(kind = 'bar', color = 'red',\n",
    "                                                                                            figsize = (15,5))\n",
    "plt.title(\"Top Run Getters of IPL\", fontsize = 20, fontweight = 'bold')\n",
    "plt.xlabel(\"Batsmen\", size = 25)\n",
    "plt.ylabel(\"Total Runs Scored\", size = 25)\n",
    "plt.xticks(size = 12)\n",
    "plt.yticks(size = 12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Except for MS Dhoni, all other top run getters are either openers or come in 3rd or 4th positions to bat\n",
    "- Suresh Raina is the highest run getter in IPL."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which batsman has been most consistent among top 10 run getters?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-200.,    0.,  200.,  400.,  600.,  800., 1000., 1200.]),\n",
       " <a list of 8 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "consistent_batsman = merge[merge.batsman.isin(['SK Raina', 'V Kohli','RG Sharma','G Gambhir',\n",
    "                                            'RV Uthappa', 'S Dhawan','CH Gayle', 'MS Dhoni',\n",
    "                                            'DA Warner', 'AB de Villiers'])][['batsman','season','total_runs']]\n",
    "\n",
    "consistent_batsman.groupby(['season','batsman'])['total_runs'].sum().unstack().plot(kind = 'box', figsize = (15,8))\n",
    "plt.title(\"Most Consistent batsmen of IPL\", fontsize = 20, fontweight = 'bold')\n",
    "plt.xlabel(\"Batsmen\", size = 25)\n",
    "plt.ylabel(\"Total Runs Scored each season\", size = 25)\n",
    "plt.xticks(size = 15)\n",
    "plt.yticks(size = 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Median score for Raina is above all the top 10 run getters. He has the highest lowest run among all the batsmen across 11 seasons. Considering the highest and lowest season totals and spread of runs, it seems Raina has been most consistent among all."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which bowlers have performed the best?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  0.,  25.,  50.,  75., 100., 125., 150., 175., 200.]),\n",
       " <a list of 9 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merge.groupby('bowler')['player_dismissed'].count().sort_values(ascending = False).head(10).plot(kind = 'bar', \n",
    "                                                color = 'purple', figsize = (15,5))\n",
    "plt.title(\"Top Wicket Takers of IPL\", fontsize = 20, fontweight = 'bold')\n",
    "plt.xlabel(\"Bowler\", size = 25)\n",
    "plt.ylabel(\"Total Wickets Taken\", size = 25)\n",
    "plt.xticks(size = 12)\n",
    "plt.yticks(size = 12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Malinga has taken the most number of wickets in IPL followed by Bravo and Amit Mishra\n",
    "- In top 10 bowlers, 5 are fast and medium pacers while the other 5 are spinners\n",
    "- All 5 spinners are right arm spinners and 2 are leg spinners while 3 are off spinners\n",
    "- All 5 pacers are right arm pacers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Batsmen with the best strike rates over the years ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>batsman</th>\n",
       "      <th>strike_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>11</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>145.640370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>10</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>141.751527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>10</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>139.523249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>11</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>136.945813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>11</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>127.332746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>10</td>\n",
       "      <td>STR Binny</td>\n",
       "      <td>126.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>11</td>\n",
       "      <td>DJ Bravo</td>\n",
       "      <td>125.565801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>11</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>125.283190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>10</td>\n",
       "      <td>AT Rayudu</td>\n",
       "      <td>124.058187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>11</td>\n",
       "      <td>G Gambhir</td>\n",
       "      <td>119.835414</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     season       batsman  strike_rate\n",
       "92       11      CH Gayle   145.640370\n",
       "213      10    KA Pollard   141.751527\n",
       "112      10     DA Warner   139.523249\n",
       "444      11     SR Watson   136.945813\n",
       "72       11   BB McCullum   127.332746\n",
       "449      10     STR Binny   126.000000\n",
       "118      11      DJ Bravo   125.565801\n",
       "514      11  Yuvraj Singh   125.283190\n",
       "53       10     AT Rayudu   124.058187\n",
       "147      11     G Gambhir   119.835414"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We will consider players who have played 10 or more seasons\n",
    "no_of_balls = pd.DataFrame(merge.groupby('batsman')['ball'].count()) #total number of matches played by each batsman\n",
    "runs = pd.DataFrame(merge.groupby('batsman')['batsman_runs'].sum()) #total runs of each batsman\n",
    "seasons = pd.DataFrame(merge.groupby('batsman')['season'].nunique()) #season = 1 implies played only 1 season\n",
    "\n",
    "batsman_strike_rate = pd.DataFrame({'balls':no_of_balls['ball'],'run':runs['batsman_runs'],'season':seasons['season']})\n",
    "batsman_strike_rate.reset_index(inplace = True)\n",
    "\n",
    "batsman_strike_rate['strike_rate'] = batsman_strike_rate['run']/batsman_strike_rate['balls']*100\n",
    "highest_strike_rate = batsman_strike_rate[batsman_strike_rate.season.isin([10,11])][['season','batsman','strike_rate']].sort_values(by = 'strike_rate',\n",
    "                                                                                                            ascending = False)\n",
    "\n",
    "highest_strike_rate.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  0.,  20.,  40.,  60.,  80., 100., 120., 140., 160.]),\n",
       " <a list of 9 Text major ticklabel objects>)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,6))\n",
    "sns.barplot(x='batsman', y='strike_rate', data = highest_strike_rate.head(10), hue = 'season')\n",
    "plt.title(\"Highest strike rates in IPL\",fontsize= 30, fontweight = 'bold')\n",
    "plt.xlabel(\"Player\", size = 25)\n",
    "plt.ylabel(\"Strike Rate\", size = 25)\n",
    "plt.xticks(size = 14)\n",
    "plt.yticks(size = 14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- AB de Villiers, Gayle have the highest strike rates in IPL. They are the big hitters and can win any match on their day\n",
    "- One surprise here is that Harbhajan Singh who is a bowler has a strike rate of 130+ and comes before Rohit Sharma in ranking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bowlers with maximum number of extras."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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>SL Malinga</th>\n",
       "      <th>P Kumar</th>\n",
       "      <th>UT Yadav</th>\n",
       "      <th>DJ Bravo</th>\n",
       "      <th>B Kumar</th>\n",
       "      <th>SR Watson</th>\n",
       "      <th>I Sharma</th>\n",
       "      <th>RP Singh</th>\n",
       "      <th>DW Steyn</th>\n",
       "      <th>R Ashwin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bowler</th>\n",
       "      <td>221</td>\n",
       "      <td>185</td>\n",
       "      <td>180</td>\n",
       "      <td>176</td>\n",
       "      <td>162</td>\n",
       "      <td>155</td>\n",
       "      <td>151</td>\n",
       "      <td>145</td>\n",
       "      <td>139</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SL Malinga  P Kumar  UT Yadav  DJ Bravo  B Kumar  SR Watson  I Sharma  \\\n",
       "bowler         221      185       180       176      162        155       151   \n",
       "\n",
       "        RP Singh  DW Steyn  R Ashwin  \n",
       "bowler       145       139       133  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extra = deliveries[deliveries['extra_runs']!=0]['bowler'].value_counts()[:10]\n",
    "extra.plot(kind='bar', figsize=(11,6), title='Bowlers who have bowled maximum number of Extra balls')\n",
    "\n",
    "plt.xlabel('BOWLER')\n",
    "plt.ylabel('BALLS')\n",
    "plt.show()\n",
    "\n",
    "extra = pd.DataFrame(extra)\n",
    "extra.T\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which bowlers have picked up wickets more frequently?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "#strike_rate = balls bowled by wickets taken\n",
    "balls_bowled = pd.DataFrame(merge.groupby('bowler')['ball'].count())\n",
    "wickets_taken = pd.DataFrame(merge[merge['dismissal_kind'] != 'no dismissal'].groupby('bowler')['dismissal_kind'].count())\n",
    "seasons_played = pd.DataFrame(merge.groupby('bowler')['season'].nunique())\n",
    "bowler_strike_rate = pd.DataFrame({'balls':balls_bowled['ball'],'wickets':wickets_taken['dismissal_kind'],\n",
    "                          'season':seasons_played['season']})\n",
    "bowler_strike_rate.reset_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col4 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col0 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col2 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col4 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col0 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col2 {\n",
       "            background-color:  skyblue;\n",
       "        }    #T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col4 {\n",
       "            background-color:  skyblue;\n",
       "        }</style><table id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >bowler</th>        <th class=\"col_heading level0 col1\" >balls</th>        <th class=\"col_heading level0 col2\" >wickets</th>        <th class=\"col_heading level0 col3\" >season</th>        <th class=\"col_heading level0 col4\" >strike_rate</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5level0_row0\" class=\"row_heading level0 row0\" >134</th>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row0_col0\" class=\"data row0 col0\" >Imran Tahir</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row0_col1\" class=\"data row0 col1\" >1249</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row0_col2\" class=\"data row0 col2\" >82</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row0_col3\" class=\"data row0 col3\" >6</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row0_col4\" class=\"data row0 col4\" >15.231707</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5level0_row1\" class=\"row_heading level0 row1\" >340</th>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row1_col0\" class=\"data row1 col0\" >SL Malinga</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row1_col1\" class=\"data row1 col1\" >2974</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row1_col2\" class=\"data row1 col2\" >188</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row1_col3\" class=\"data row1 col3\" >9</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row1_col4\" class=\"data row1 col4\" >15.819149</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5level0_row2\" class=\"row_heading level0 row2\" >93</th>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col0\" class=\"data row2 col0\" >DJ Bravo</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col1\" class=\"data row2 col1\" >2711</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col2\" class=\"data row2 col2\" >168</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col3\" class=\"data row2 col3\" >10</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row2_col4\" class=\"data row2 col4\" >16.136905</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5level0_row3\" class=\"row_heading level0 row3\" >9</th>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col0\" class=\"data row3 col0\" >A Nehra</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col1\" class=\"data row3 col1\" >1974</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col2\" class=\"data row3 col2\" >121</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col3\" class=\"data row3 col3\" >9</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row3_col4\" class=\"data row3 col4\" >16.314050</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5level0_row4\" class=\"row_heading level0 row4\" >225</th>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col0\" class=\"data row4 col0\" >MM Patel</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col1\" class=\"data row4 col1\" >1382</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col2\" class=\"data row4 col2\" >82</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col3\" class=\"data row4 col3\" >7</td>\n",
       "                        <td id=\"T_1106714a_4054_11eb_a6cb_97acce4251f5row4_col4\" class=\"data row4 col4\" >16.853659</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x24cb6afb190>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bowler_strike_rate['strike_rate'] = bowler_strike_rate['balls']/bowler_strike_rate['wickets']\n",
    "def highlight_cols(s):\n",
    "    color = 'skyblue'\n",
    "    return 'background-color: %s' % color\n",
    "#Strike rate for bowlers who have taken more than 50 wickets\n",
    "best_bowling_strike_rate = bowler_strike_rate[bowler_strike_rate['wickets'] > 50].sort_values(by = 'strike_rate', ascending = True)\n",
    "best_bowling_strike_rate.head().style.applymap(highlight_cols, subset=pd.IndexSlice[:, ['bowler', 'wickets','strike_rate']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q1. As a sports analysts, The most successful teams, players & factors contributing win or loss of a team:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Mumbai Indians is the most successful team in IPL and has won the most number of toss.\n",
    "- There were more matches won by chasing the total(419 matches) than defending(350 matches).\n",
    "- When defending a total, the biggest victory was by 146 runs(Mumbai Indians defeated Delhi Daredevils by 146 runs on 06 May 2017 at Feroz Shah Kotla stadium, Delhi).\n",
    "- When chasing a target, the biggest victory was by 10 wickets(without losing any wickets) and there were 11 such instances.\n",
    "- The Mumbai city has hosted the most number of IPL matches.\n",
    "- Chris Gayle has won the maximum number of player of the match title.\n",
    "- S. Ravi(Sundaram Ravi) has officiated the most number of IPL matches on-field.\n",
    "- Eden Gardens has hosted the maximum number of IPL matches.\n",
    "- If a team wins a toss choose to field first as it has highest probablity of winning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q2. Teams or Players a company should endorse for its products."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- If the franchise is looking for a consistant batsman who needs to score good amount of runs then go for V Kohli, S Raina, Rohit Sharma , David Warner...\n",
    "- If the franchise is looking for a game changing batsman then go for Chris Gayle, AB deVillers, R Sharma , MS Dhoni...\n",
    "- If the franchise is looking for a batsman who could score good amount of runs every match the go for DA Warner, CH Gayle, V Kohli,AB de Villiers,S Dhawan\n",
    "- If the franchise needs the best finisher in lower order having good strike rate then go for CH Gayle,KA Pollard, DA Warner,SR Watson,BB McCullum\n",
    "- If the franchise need a experienced bowler then go for Harbhajan Singh ,A Mishra,PP Chawla ,R Ashwin,SL Malinga,DJ Bravo\n",
    "- If the franchise need a wicket taking bowler then go for SL Malinga,DJ Bravo,A Mishra ,Harbhajan Singh, PP Chawla\n",
    "- If the franchise need a bowler bowling most number of dot balls then go for Harbhajan Singh,SL Malinga,B Kumar,A Mishra,PP Chawla\n",
    "- If the franchise need a bowler with good economy then go for DW Steyn ,M Muralitharan ,R Ashwin,SP Narine ,Harbhajan Singh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Thank You !"
   ]
  }
 ],
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