EDA & Feature Engineering.ipynb

{
 "cells": [
  {
   "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",
    "from pylab import rcParams\n",
    "rcParams[\"figure.figsize\"] = (10, 6)\n",
    "sns.set()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "main_data = pd.read_csv(\"IPL Ball-by-Ball 2008-2020.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>non_boundary</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>fielder</th>\n",
       "      <th>extras_type</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>AA Noffke</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <th>1</th>\n",
       "      <td>335982</td>\n",
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       "      <td>6</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>AA Noffke</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>Z Khan</td>\n",
       "      <td>0</td>\n",
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       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>Z Khan</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>Z Khan</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "    <tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193463</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>NM Coulter-Nile</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193464</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>NM Coulter-Nile</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193465</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wides</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193466</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193467</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>193468 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball      batsman  non_striker  \\\n",
       "0        335982       1     6     5   RT Ponting  BB McCullum   \n",
       "1        335982       1     6     6  BB McCullum   RT Ponting   \n",
       "2        335982       1     7     1  BB McCullum   RT Ponting   \n",
       "3        335982       1     7     2  BB McCullum   RT Ponting   \n",
       "4        335982       1     7     3   RT Ponting  BB McCullum   \n",
       "...         ...     ...   ...   ...          ...          ...   \n",
       "193463  1237181       1    12     5      RR Pant      SS Iyer   \n",
       "193464  1237181       1    12     6      RR Pant      SS Iyer   \n",
       "193465  1237181       1    13     1      RR Pant      SS Iyer   \n",
       "193466  1237181       1    13     2      RR Pant      SS Iyer   \n",
       "193467  1237181       1    13     3      SS Iyer      RR Pant   \n",
       "\n",
       "                 bowler  batsman_runs  extra_runs  total_runs  non_boundary  \\\n",
       "0             AA Noffke             1           0           1             0   \n",
       "1             AA Noffke             1           0           1             0   \n",
       "2                Z Khan             0           0           0             0   \n",
       "3                Z Khan             1           0           1             0   \n",
       "4                Z Khan             1           0           1             0   \n",
       "...                 ...           ...         ...         ...           ...   \n",
       "193463  NM Coulter-Nile             0           0           0             0   \n",
       "193464  NM Coulter-Nile             1           0           1             0   \n",
       "193465        KH Pandya             0           1           1             0   \n",
       "193466        KH Pandya             1           0           1             0   \n",
       "193467        KH Pandya             1           0           1             0   \n",
       "\n",
       "        is_wicket dismissal_kind player_dismissed fielder extras_type  \\\n",
       "0               0            NaN              NaN     NaN         NaN   \n",
       "1               0            NaN              NaN     NaN         NaN   \n",
       "2               0            NaN              NaN     NaN         NaN   \n",
       "3               0            NaN              NaN     NaN         NaN   \n",
       "4               0            NaN              NaN     NaN         NaN   \n",
       "...           ...            ...              ...     ...         ...   \n",
       "193463          0            NaN              NaN     NaN         NaN   \n",
       "193464          0            NaN              NaN     NaN         NaN   \n",
       "193465          0            NaN              NaN     NaN       wides   \n",
       "193466          0            NaN              NaN     NaN         NaN   \n",
       "193467          0            NaN              NaN     NaN         NaN   \n",
       "\n",
       "                 batting_team                 bowling_team  \n",
       "0       Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "1       Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "2       Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "3       Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "4       Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "...                       ...                          ...  \n",
       "193463         Delhi Capitals               Mumbai Indians  \n",
       "193464         Delhi Capitals               Mumbai Indians  \n",
       "193465         Delhi Capitals               Mumbai Indians  \n",
       "193466         Delhi Capitals               Mumbai Indians  \n",
       "193467         Delhi Capitals               Mumbai Indians  \n",
       "\n",
       "[193468 rows x 18 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
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       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
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       "    <tr>\n",
       "      <th>58201</th>\n",
       "      <td>501270</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>MA Agarwal</td>\n",
       "      <td>SL Malinga</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
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       "      <th>79485</th>\n",
       "      <td>598011</td>\n",
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       "      <td>4</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>KD Karthik</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Pune Warriors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20245</th>\n",
       "      <td>392211</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>G Gambhir</td>\n",
       "      <td>TM Dilshan</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28907</th>\n",
       "      <td>419113</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>M Vijay</td>\n",
       "      <td>SE Bond</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  inning  over  ball    batsman     non_striker        bowler  \\\n",
       "58201   501270       1     5     2   CH Gayle      MA Agarwal    SL Malinga   \n",
       "116424  829771       2     4     3    V Kohli  AB de Villiers     PP Chawla   \n",
       "79485   598011       1    11     4  RG Sharma      KD Karthik  Yuvraj Singh   \n",
       "20245   392211       2    18     4  G Gambhir      TM Dilshan      I Sharma   \n",
       "28907   419113       1     2     5  ML Hayden         M Vijay       SE Bond   \n",
       "\n",
       "        batsman_runs  extra_runs  total_runs  non_boundary  is_wicket  \\\n",
       "58201              0           0           0             0          0   \n",
       "116424             1           0           1             0          0   \n",
       "79485              1           0           1             0          0   \n",
       "20245              0           0           0             0          0   \n",
       "28907              0           0           0             0          0   \n",
       "\n",
       "       dismissal_kind player_dismissed fielder extras_type  \\\n",
       "58201             NaN              NaN     NaN         NaN   \n",
       "116424            NaN              NaN     NaN         NaN   \n",
       "79485             NaN              NaN     NaN         NaN   \n",
       "20245             NaN              NaN     NaN         NaN   \n",
       "28907             NaN              NaN     NaN         NaN   \n",
       "\n",
       "                       batting_team           bowling_team  \n",
       "58201   Royal Challengers Bangalore         Mumbai Indians  \n",
       "116424  Royal Challengers Bangalore  Kolkata Knight Riders  \n",
       "79485                Mumbai Indians          Pune Warriors  \n",
       "20245              Delhi Daredevils  Kolkata Knight Riders  \n",
       "28907           Chennai Super Kings  Kolkata Knight Riders  "
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                       0\n",
       "inning                   0\n",
       "over                     0\n",
       "ball                     0\n",
       "batsman                  0\n",
       "non_striker              0\n",
       "bowler                   0\n",
       "batsman_runs             0\n",
       "extra_runs               0\n",
       "total_runs               0\n",
       "non_boundary             0\n",
       "is_wicket                0\n",
       "dismissal_kind      183973\n",
       "player_dismissed    183973\n",
       "fielder             186684\n",
       "extras_type         183235\n",
       "batting_team             0\n",
       "bowling_team           191\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'inning', 'over', 'ball', 'batsman', 'non_striker', 'bowler',\n",
       "       'batsman_runs', 'extra_runs', 'total_runs', 'non_boundary', 'is_wicket',\n",
       "       'dismissal_kind', 'player_dismissed', 'fielder', 'extras_type',\n",
       "       'batting_team', 'bowling_team'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(193468, 18)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- here i have 193468 records and 18 columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring ID Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "816"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.id.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- 816 are unique id means 816 matches data\n",
    "- id are unique which help me to get to access team IPL Matches data set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Inning Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's findout unique data of inning feature\n",
    "\n",
    "main_data.inning.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# let's findout the total counts of inning\n",
    "\n",
    "sns.countplot(main_data.inning)\n",
    "plt.title(\"Values Count of inning\")\n",
    "plt.xlabel(\"Inning\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Here in IPL there are two innings\n",
    "- data of first inning is more than second inning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Over Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          9.177027\n",
       "std           5.676848\n",
       "min           0.000000\n",
       "25%           4.000000\n",
       "50%           9.000000\n",
       "75%          14.000000\n",
       "max          19.000000\n",
       "Name: over, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.over.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Counts')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# let's see the count of overs\n",
    "\n",
    "sns.countplot(main_data.over)\n",
    "plt.title(\"Value Counts of Overs\")\n",
    "plt.xlabel(\"Overs\")\n",
    "plt.ylabel(\"Counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Over start from 0 to 19 it here it has 20 overs matches\n",
    "- most of the time matches were finished 18 over"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Ball Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          3.615967\n",
       "std           1.807128\n",
       "min           1.000000\n",
       "25%           2.000000\n",
       "50%           4.000000\n",
       "75%           5.000000\n",
       "max           9.000000\n",
       "Name: ball, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.ball.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(main_data.ball)\n",
    "plt.title(\"Values Count of Balls\")\n",
    "plt.xlabel(\"Balls\")\n",
    "plt.ylabel(\"Count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- As we know that there are 6 balls in 1 over\n",
    "- there are rarely more than 8 balls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Batsman Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "537"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.batsman.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- here we have 537 unique players are batsman in different teams and matches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Non-Striker Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "530"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.non_striker.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(list(filter(lambda x: x not in main_data.non_striker.unique(), main_data.batsman.unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(list(filter(lambda x: x not in main_data.batsman.unique(), main_data.non_striker.unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Here 530 players were on non strikers\n",
    "- 11 batsman which were not on non strike\n",
    "- 4 non striker which were not on strike or batsman"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Bowler Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "420"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.bowler.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Here 420 unique players are bowlers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Batsman Runs Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          1.240231\n",
       "std           1.610867\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           1.000000\n",
       "75%           1.000000\n",
       "max           6.000000\n",
       "Name: batsman_runs, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.batsman_runs.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 2, 6, 4, 5, 3])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.batsman_runs.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Batsman run can be between 0 to 6 in one ball"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Extra Runs Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          0.066414\n",
       "std           0.339991\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           0.000000\n",
       "75%           0.000000\n",
       "max           7.000000\n",
       "Name: extra_runs, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.extra_runs.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 4, 1, 2, 5, 3, 7])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.extra_runs.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Extra runs can be between 0 to 7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Total Runs Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          1.306645\n",
       "std           1.598802\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           1.000000\n",
       "75%           1.000000\n",
       "max           7.000000\n",
       "Name: total_runs, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.total_runs.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_runs', ylabel='Density'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(main_data.total_runs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- total_runs is indicates that total runs scored by the player in one ball\n",
    "- total runs scored between 0 to 7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Non-Boundary Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.non_boundary.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    193452\n",
       "1        16\n",
       "Name: non_boundary, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.non_boundary.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>non_boundary</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>fielder</th>\n",
       "      <th>extras_type</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7505</th>\n",
       "      <td>336014</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>LR Shukla</td>\n",
       "      <td>DJ Hussey</td>\n",
       "      <td>RP Singh</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23749</th>\n",
       "      <td>392226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>SM Katich</td>\n",
       "      <td>S Sohal</td>\n",
       "      <td>PJ Sangwan</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47927</th>\n",
       "      <td>501225</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>R Vinay Kumar</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54183</th>\n",
       "      <td>501252</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>TM Dilshan</td>\n",
       "      <td>J Botha</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55334</th>\n",
       "      <td>501257</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>PC Valthaty</td>\n",
       "      <td>AC Gilchrist</td>\n",
       "      <td>IK Pathan</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59111</th>\n",
       "      <td>548308</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>JEC Franklin</td>\n",
       "      <td>SA Yadav</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Pune Warriors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74924</th>\n",
       "      <td>548376</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>A Mishra</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82699</th>\n",
       "      <td>598024</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>KD Karthik</td>\n",
       "      <td>IK Pathan</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91617</th>\n",
       "      <td>598061</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>RN ten Doeschate</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Pune Warriors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123397</th>\n",
       "      <td>980909</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Kuldeep Yadav</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132655</th>\n",
       "      <td>980987</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>DS Kulkarni</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137361</th>\n",
       "      <td>1082594</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>DA Miller</td>\n",
       "      <td>RD Chahar</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138887</th>\n",
       "      <td>1082601</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>MM Sharma</td>\n",
       "      <td>VR Aaron</td>\n",
       "      <td>TA Boult</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155041</th>\n",
       "      <td>1136580</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>KS Williamson</td>\n",
       "      <td>Shakib Al Hasan</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190310</th>\n",
       "      <td>1216539</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>SM Curran</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193054</th>\n",
       "      <td>1237180</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>MP Stoinis</td>\n",
       "      <td>Rashid Khan</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball        batsman       non_striker  \\\n",
       "7505     336014       1    19     6      LR Shukla         DJ Hussey   \n",
       "23749    392226       2     1     3      SM Katich           S Sohal   \n",
       "47927    501225       2     4     4       R Dravid         SR Watson   \n",
       "54183    501252       2     5     1       CH Gayle        TM Dilshan   \n",
       "55334    501257       1     2     3    PC Valthaty      AC Gilchrist   \n",
       "59111    548308       2    11     3   JEC Franklin          SA Yadav   \n",
       "74924    548376       2     7     1        V Kohli    AB de Villiers   \n",
       "82699    598024       1     4     2   SR Tendulkar        KD Karthik   \n",
       "91617    598061       2    10     3      YK Pathan  RN ten Doeschate   \n",
       "123397   980909       2     9     7      RG Sharma         HH Pandya   \n",
       "132655   980987       1     3     1        V Kohli          CH Gayle   \n",
       "137361  1082594       2    12     4     GJ Maxwell         DA Miller   \n",
       "138887  1082601       1    18     6      MM Sharma          VR Aaron   \n",
       "155041  1136580       2     9     2  KS Williamson   Shakib Al Hasan   \n",
       "190310  1216539       1    15     1        RR Pant           SS Iyer   \n",
       "193054  1237180       1     6     4       S Dhawan        MP Stoinis   \n",
       "\n",
       "               bowler  batsman_runs  extra_runs  total_runs  non_boundary  \\\n",
       "7505         RP Singh             6           0           6             1   \n",
       "23749      PJ Sangwan             4           0           4             1   \n",
       "47927   R Vinay Kumar             4           0           4             1   \n",
       "54183         J Botha             4           0           4             1   \n",
       "55334       IK Pathan             4           0           4             1   \n",
       "59111         B Kumar             6           0           6             1   \n",
       "74924        A Mishra             6           0           6             1   \n",
       "82699       IK Pathan             4           0           4             1   \n",
       "91617    Yuvraj Singh             6           0           6             1   \n",
       "123397  Kuldeep Yadav             6           0           6             1   \n",
       "132655    DS Kulkarni             4           0           4             1   \n",
       "137361      RD Chahar             4           0           4             1   \n",
       "138887       TA Boult             4           0           4             1   \n",
       "155041      SR Watson             4           0           4             1   \n",
       "190310      SM Curran             4           0           4             1   \n",
       "193054    Rashid Khan             6           0           6             1   \n",
       "\n",
       "        is_wicket dismissal_kind player_dismissed fielder extras_type  \\\n",
       "7505            0            NaN              NaN     NaN         NaN   \n",
       "23749           0            NaN              NaN     NaN         NaN   \n",
       "47927           0            NaN              NaN     NaN         NaN   \n",
       "54183           0            NaN              NaN     NaN         NaN   \n",
       "55334           0            NaN              NaN     NaN         NaN   \n",
       "59111           0            NaN              NaN     NaN         NaN   \n",
       "74924           0            NaN              NaN     NaN         NaN   \n",
       "82699           0            NaN              NaN     NaN         NaN   \n",
       "91617           0            NaN              NaN     NaN         NaN   \n",
       "123397          0            NaN              NaN     NaN         NaN   \n",
       "132655          0            NaN              NaN     NaN         NaN   \n",
       "137361          0            NaN              NaN     NaN         NaN   \n",
       "138887          0            NaN              NaN     NaN         NaN   \n",
       "155041          0            NaN              NaN     NaN         NaN   \n",
       "190310          0            NaN              NaN     NaN         NaN   \n",
       "193054          0            NaN              NaN     NaN         NaN   \n",
       "\n",
       "                       batting_team            bowling_team  \n",
       "7505          Kolkata Knight Riders         Deccan Chargers  \n",
       "23749               Kings XI Punjab        Delhi Daredevils  \n",
       "47927              Rajasthan Royals    Kochi Tuskers Kerala  \n",
       "54183   Royal Challengers Bangalore        Rajasthan Royals  \n",
       "55334               Kings XI Punjab        Delhi Daredevils  \n",
       "59111                Mumbai Indians           Pune Warriors  \n",
       "74924   Royal Challengers Bangalore         Deccan Chargers  \n",
       "82699                Mumbai Indians        Delhi Daredevils  \n",
       "91617         Kolkata Knight Riders           Pune Warriors  \n",
       "123397               Mumbai Indians   Kolkata Knight Riders  \n",
       "132655  Royal Challengers Bangalore           Gujarat Lions  \n",
       "137361              Kings XI Punjab  Rising Pune Supergiant  \n",
       "138887              Kings XI Punjab   Kolkata Knight Riders  \n",
       "155041          Sunrisers Hyderabad     Chennai Super Kings  \n",
       "190310               Delhi Capitals     Chennai Super Kings  \n",
       "193054               Delhi Capitals     Sunrisers Hyderabad  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.loc[main_data.non_boundary == 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- non_boundary indincates that how many runs score by the boundary\n",
    "- when the ball gone outside the boundary then score would be either 4 or 6\n",
    "- if non boundary value is 1 then it means that ball was gone out of boundary\n",
    "- here 16 boundary and 193452 are non boundary which might be wrong and outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Wicket Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    193468.000000\n",
       "mean          0.049078\n",
       "std           0.216031\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           0.000000\n",
       "75%           0.000000\n",
       "max           1.000000\n",
       "Name: is_wicket, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.is_wicket.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>is_wicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
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       "      <td>335983</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335983</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
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       "      <th>4</th>\n",
       "      <td>335984</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>1237178</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>1237180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>1237180</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>1237181</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1629</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1630 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  inning  is_wicket\n",
       "0      335982       1          3\n",
       "1      335982       2         10\n",
       "2      335983       1          5\n",
       "3      335983       2          4\n",
       "4      335984       1          8\n",
       "...       ...     ...        ...\n",
       "1625  1237178       2          4\n",
       "1626  1237180       1          3\n",
       "1627  1237180       2          8\n",
       "1628  1237181       1          7\n",
       "1629  1237181       2          5\n",
       "\n",
       "[1630 rows x 3 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.groupby([\"id\", \"inning\"]).is_wicket.sum().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- is_wicket indicates that wickets taken in particular ball\n",
    "- sum of wickets in match of inning will become total wickets of that match"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring dismissal_kind Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'caught', 'run out', 'bowled', 'lbw', 'retired hurt',\n",
       "       'stumped', 'caught and bowled', 'hit wicket',\n",
       "       'obstructing the field'], dtype=object)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.dismissal_kind.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.dismissal_kind.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183973"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.dismissal_kind.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(main_data.dismissal_kind)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Dismissal Kind Feature tells about reason of wicket\n",
    "- here 9 categorical values and maximum value is caught which have around 5800 counts\n",
    "- here 183973 values are NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring player_dismissed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "506"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.player_dismissed.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9495"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(~main_data.player_dismissed.isna()).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183973"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.player_dismissed.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- 506 unique players who got dissmissed 9495 times\n",
    "- here we have 183973 values are NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Fielder Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "879"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.fielder.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6784"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(~main_data.fielder.isna()).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "186684"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.fielder.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Fielder column indicats that the fielder who involved in the dismissal\n",
    "- 879 unique fielder who involved 6784 times in dismissal\n",
    "- here we have 186684 values are NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring extras_type Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'byes', 'wides', 'legbyes', 'noballs', 'penalty'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.extras_type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.extras_type.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(main_data.extras_type)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183235"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.extras_type.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- Here we have 5 types of extra runs\n",
    "- here we have 183235 values are NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Batting Team Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Kolkata Knight Riders', 'Royal Challengers Bangalore',\n",
       "       'Kings XI Punjab', 'Chennai Super Kings', 'Rajasthan Royals',\n",
       "       'Delhi Daredevils', 'Mumbai Indians', 'Deccan Chargers',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Sunrisers Hyderabad',\n",
       "       'Rising Pune Supergiants', 'Gujarat Lions',\n",
       "       'Rising Pune Supergiant', 'Delhi Capitals'], dtype=object)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.batting_team.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.batting_team.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- here we have 15 unique teams in batting team"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Bowling Team"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Royal Challengers Bangalore', 'Kolkata Knight Riders',\n",
       "       'Chennai Super Kings', 'Kings XI Punjab', 'Delhi Daredevils',\n",
       "       'Rajasthan Royals', 'Mumbai Indians', 'Deccan Chargers',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', nan,\n",
       "       'Sunrisers Hyderabad', 'Rising Pune Supergiants', 'Gujarat Lions',\n",
       "       'Rising Pune Supergiant', 'Delhi Capitals'], dtype=object)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.bowling_team.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.bowling_team.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "191"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.bowling_team.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- here we have 15 unique teams in bowling team\n",
    "- here 191 values are NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### some columns are not required to predict score base on our domain knowledge\n",
    "- batsman: there might be new batsman will come in team that's information i don't have in this dataframe and in future may be batsman position will change so it's better to drop batsman\n",
    "- non_striker: same reason as batsman, it's better to drop non_striker\n",
    "- bowler: there might be new bolwer will come in team that's information i don't have in this dataframe\n",
    "- batsman_runs: batsman_runs is not require because i have not taken batsman name\n",
    "- extra_runs: it might have extra run so i will drop it instead of extra run i will total_runs\n",
    "- non_boundary: it indicates that ball gone out of boundary or not, here it's not needed because we have total_runs feature so from their we know that which balls gone out of boundary like either 4 or 6\n",
    "- dismissal_kind: dismissal_kind feautre tells about reason of wicket on particular ball here i'll not take every balls input from user and here dismissal_kind have 183973 NaN values so it's better to drop that feature\n",
    "- player_dismissed: here i'm not taking player name and player_dismissed have 183973 NaN values so it's better to drop that feature\n",
    "- fielder: fielder have 186684 NaN values it's better to drop it\n",
    "- extras_type: it might have extra run and extra_type have 183235 NaN values so it's better to drop extra_type\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's drop unnecessary features\n",
    "\n",
    "main_data.drop(columns=[\"batsman\", \"non_striker\", \"bowler\", \"batsman_runs\", \"extra_runs\", \"non_boundary\", \"dismissal_kind\", \"player_dismissed\", \"fielder\", \"extras_type\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1     6     5           1          0  Kolkata Knight Riders   \n",
       "1  335982       1     6     6           1          0  Kolkata Knight Riders   \n",
       "2  335982       1     7     1           0          0  Kolkata Knight Riders   \n",
       "3  335982       1     7     2           1          0  Kolkata Knight Riders   \n",
       "4  335982       1     7     3           1          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  \n",
       "0  Royal Challengers Bangalore  \n",
       "1  Royal Challengers Bangalore  \n",
       "2  Royal Challengers Bangalore  \n",
       "3  Royal Challengers Bangalore  \n",
       "4  Royal Challengers Bangalore  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we can see over start from 6 and 5 balls it means data is not in order \n",
    "# let's sort the records in order to id, inning, over and ball\n",
    "\n",
    "main_data = main_data.sort_values([\"id\", \"inning\", \"over\", \"ball\"]).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>111329</th>\n",
       "      <td>829725</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42064</th>\n",
       "      <td>501200</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185191</th>\n",
       "      <td>1216517</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball  total_runs  is_wicket  \\\n",
       "111329   829725       1    13     4           1          0   \n",
       "42064    501200       1     1     5           0          0   \n",
       "185191  1216517       2    10     6           6          0   \n",
       "\n",
       "                batting_team                 bowling_team  \n",
       "111329       Kings XI Punjab             Delhi Daredevils  \n",
       "42064   Kochi Tuskers Kerala  Royal Challengers Bangalore  \n",
       "185191       Kings XI Punjab               Mumbai Indians  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                0\n",
       "inning            0\n",
       "over              0\n",
       "ball              0\n",
       "total_runs        0\n",
       "is_wicket         0\n",
       "batting_team      0\n",
       "bowling_team    191\n",
       "dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>57048</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57049</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57050</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57051</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57052</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  inning  over  ball  total_runs  is_wicket      batting_team  \\\n",
       "57048  501265       1     0     1           1          0  Delhi Daredevils   \n",
       "57049  501265       1     0     2           1          0  Delhi Daredevils   \n",
       "57050  501265       1     0     3           0          0  Delhi Daredevils   \n",
       "57051  501265       1     0     4           0          0  Delhi Daredevils   \n",
       "57052  501265       1     0     5           0          0  Delhi Daredevils   \n",
       "\n",
       "      bowling_team  \n",
       "57048          NaN  \n",
       "57049          NaN  \n",
       "57050          NaN  \n",
       "57051          NaN  \n",
       "57052          NaN  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# here we have 191 NaN values in bowling_team \n",
    "# let's see that records\n",
    "main_data[main_data.bowling_team.isna()].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>57106</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57107</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57108</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57109</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57110</th>\n",
       "      <td>501265</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  inning  over  ball  total_runs  is_wicket      batting_team  \\\n",
       "57106  501265       1     9     4           1          0  Delhi Daredevils   \n",
       "57107  501265       1     9     5           4          0  Delhi Daredevils   \n",
       "57108  501265       1     9     6           1          0  Delhi Daredevils   \n",
       "57109  501265       1     9     7           0          0  Delhi Daredevils   \n",
       "57110  501265       1    10     1           1          0  Delhi Daredevils   \n",
       "\n",
       "      bowling_team  \n",
       "57106          NaN  \n",
       "57107          NaN  \n",
       "57108          NaN  \n",
       "57109          NaN  \n",
       "57110          NaN  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's see any match record which have NaN values in bowling_team\n",
    "main_data.loc[(main_data.id==501265)].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's see how much inning it has\n",
    "\n",
    "main_data.loc[(main_data.id==501265)].inning.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here we have only 1st inning in 501265 match let's see match details and try to find reason\n",
    "\n",
    "# let's read data of matches\n",
    "matches_data = pd.read_csv(\"IPL Matches 2008-2020.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>neutral_venue</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>winner</th>\n",
       "      <th>result</th>\n",
       "      <th>result_margin</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>method</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>980951</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2016-04-30</td>\n",
       "      <td>CR Brathwaite</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>runs</td>\n",
       "      <td>27.0</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>M Erasmus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>980989</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2016-05-14</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>bat</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>wickets</td>\n",
       "      <td>8.0</td>\n",
       "      <td>N</td>\n",
       "      <td>D/L</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>598</th>\n",
       "      <td>1082612</td>\n",
       "      <td>Indore</td>\n",
       "      <td>2017-04-20</td>\n",
       "      <td>JC Buttler</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>wickets</td>\n",
       "      <td>8.0</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id     city        date player_of_match                   venue  \\\n",
       "542   980951    Delhi  2016-04-30   CR Brathwaite        Feroz Shah Kotla   \n",
       "561   980989  Kolkata  2016-05-14       YK Pathan            Eden Gardens   \n",
       "598  1082612   Indore  2017-04-20      JC Buttler  Holkar Cricket Stadium   \n",
       "\n",
       "     neutral_venue                  team1                    team2  \\\n",
       "542              0       Delhi Daredevils    Kolkata Knight Riders   \n",
       "561              0  Kolkata Knight Riders  Rising Pune Supergiants   \n",
       "598              0        Kings XI Punjab           Mumbai Indians   \n",
       "\n",
       "                 toss_winner toss_decision                 winner   result  \\\n",
       "542    Kolkata Knight Riders         field       Delhi Daredevils     runs   \n",
       "561  Rising Pune Supergiants           bat  Kolkata Knight Riders  wickets   \n",
       "598           Mumbai Indians         field         Mumbai Indians  wickets   \n",
       "\n",
       "     result_margin eliminator method                umpire1        umpire2  \n",
       "542           27.0          N    NaN  KN Ananthapadmanabhan      M Erasmus  \n",
       "561            8.0          N    D/L         A Nand Kishore   BNJ Oxenford  \n",
       "598            8.0          N    NaN              M Erasmus  C Shamshuddin  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_data.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>neutral_venue</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>winner</th>\n",
       "      <th>result</th>\n",
       "      <th>result_margin</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>method</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>501265</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2011-05-21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SS Hazare</td>\n",
       "      <td>RJ Tucker</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id   city        date player_of_match             venue  \\\n",
       "241  501265  Delhi  2011-05-21             NaN  Feroz Shah Kotla   \n",
       "\n",
       "     neutral_venue             team1          team2       toss_winner  \\\n",
       "241              0  Delhi Daredevils  Pune Warriors  Delhi Daredevils   \n",
       "\n",
       "    toss_decision winner result  result_margin eliminator method    umpire1  \\\n",
       "241           bat    NaN    NaN            NaN        NaN    NaN  SS Hazare   \n",
       "\n",
       "       umpire2  \n",
       "241  RJ Tucker  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's see the data of match which have 501265 id\n",
    "\n",
    "matches_data.loc[matches_data.id == 501265]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "- As we can see in match details there are winner, result and other columns values are **NaN**\n",
    "- there were some reason that match was abandoned\n",
    "- we don't have data of that match which was abandoned so it's better to drop that records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's drop records which has NaN values in bowling team\n",
    "\n",
    "main_data.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id              0\n",
       "inning          0\n",
       "over            0\n",
       "ball            0\n",
       "total_runs      0\n",
       "is_wicket       0\n",
       "batting_team    0\n",
       "bowling_team    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>168791</th>\n",
       "      <td>1175372</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75068</th>\n",
       "      <td>548376</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118742</th>\n",
       "      <td>829791</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball  total_runs  is_wicket  \\\n",
       "168791  1175372       2    15     4           0          1   \n",
       "75068    548376       2     9     6           0          0   \n",
       "118742   829791       1    10     2           0          0   \n",
       "\n",
       "                       batting_team                 bowling_team  \n",
       "168791        Kolkata Knight Riders  Royal Challengers Bangalore  \n",
       "75068   Royal Challengers Bangalore              Deccan Chargers  \n",
       "118742              Kings XI Punjab        Kolkata Knight Riders  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_data.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's copy main_data and make it as df1 for further engineering\n",
    "\n",
    "df1 = main_data.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### IPL is a 20 over match\n",
    "- 20 over match start from 0 to 19.6 means 20th over completed, each over has 6 balls,\n",
    "- 0.1 to 0.6 means 1 over completed\n",
    "- so here we have value of over column is 0 to 19 so let's convert it to 1 to 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's combine the over and ball to make it perfect over\n",
    "\n",
    "df1.over = (df1.over.map(str) + \".\" + df1.ball.map(str)).map(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>18.4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>18.5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>18.6</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>19.1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>19.2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0    335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1    335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2    335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3    335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4    335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "..      ...     ...   ...   ...         ...        ...                    ...   \n",
       "115  335982       1  18.4     4           4          0  Kolkata Knight Riders   \n",
       "116  335982       1  18.5     5           1          0  Kolkata Knight Riders   \n",
       "117  335982       1  18.6     6           4          0  Kolkata Knight Riders   \n",
       "118  335982       1  19.1     1           6          0  Kolkata Knight Riders   \n",
       "119  335982       1  19.2     2           6          0  Kolkata Knight Riders   \n",
       "\n",
       "                    bowling_team  \n",
       "0    Royal Challengers Bangalore  \n",
       "1    Royal Challengers Bangalore  \n",
       "2    Royal Challengers Bangalore  \n",
       "3    Royal Challengers Bangalore  \n",
       "4    Royal Challengers Bangalore  \n",
       "..                           ...  \n",
       "115  Royal Challengers Bangalore  \n",
       "116  Royal Challengers Bangalore  \n",
       "117  Royal Challengers Bangalore  \n",
       "118  Royal Challengers Bangalore  \n",
       "119  Royal Challengers Bangalore  \n",
       "\n",
       "[120 rows x 8 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head(120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's copy df1 and make df2 for further feature engineering\n",
    "\n",
    "df2 = df1.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here we don't have final total runs of match \n",
    "# let's find final runs of match in particular inning\n",
    "\n",
    "# let's make new columns called final_total_runs\n",
    "df2[\"final_total_runs\"] = 0\n",
    "final_total_runs = df2.groupby([\"id\", \"inning\"]).total_runs.sum().reset_index()\n",
    "\n",
    "for i in range(len(final_total_runs)):\n",
    "    temp = final_total_runs.loc[i]\n",
    "    df2.loc[(df2.id == temp.id) & (df2.inning == temp.inning), \"final_total_runs\"] = temp.total_runs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1  335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2  335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3  335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4  335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  final_total_runs  \n",
       "0  Royal Challengers Bangalore               222  \n",
       "1  Royal Challengers Bangalore               222  \n",
       "2  Royal Challengers Bangalore               222  \n",
       "3  Royal Challengers Bangalore               222  \n",
       "4  Royal Challengers Bangalore               222  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Finding total runs, wickets and balls till particular over"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here is_wicket indicates the wicket in particular over, here we don't have total wickets till particular over\n",
    "\n",
    "# same for runs, here total_runs column indicates the runs scored in particular over, \n",
    "# here we don't have total scored runs till particular over\n",
    "\n",
    "# same for balls, here ball column indicates the ball of particular over\n",
    "# here we don't have total ball of the match till particular over \n",
    "\n",
    "# let's find out total wickets, total runs and total_balls till particular over\n",
    "\n",
    "# here i'm going to do sum of wickets and runs of particular match and it's inning\n",
    "\n",
    "# let's create new column for wickets with value 0\n",
    "df2[\"wickets\"] = 0\n",
    "# let's create new column for runs with value 0\n",
    "df2[\"runs\"] = 0\n",
    "# let's assign ball value as 1 to count total number of ball in particular over\n",
    "df2[\"ball\"] = 1\n",
    "\n",
    "\n",
    "# let's get unique id\n",
    "id = df2.id.unique()\n",
    "\n",
    "for i in id:\n",
    "    for inning in range(1, 3):\n",
    "        index = df2.loc[(df2.id == i) & (df2.inning == inning)].index\n",
    "        for j in range(len(index)):\n",
    "            current_index_df = df2.loc[(df2.index == index[j])]\n",
    "            previous_index_df = df2.loc[(df2.index == index[j-1])]\n",
    "            if j == 0:\n",
    "                df2.loc[df2.index == index[j], \"wickets\"] = current_index_df.is_wicket.values[0]\n",
    "                df2.loc[df2.index == index[j], \"runs\"] = current_index_df.total_runs.values[0]\n",
    "                df2.loc[df2.index == index[j], \"ball\"] = current_index_df.ball.values[0]\n",
    "            else:\n",
    "                df2.loc[df2.index == index[j], \"wickets\"] = current_index_df.is_wicket.values[0] + previous_index_df.wickets.values[0]\n",
    "                df2.loc[df2.index == index[j], \"runs\"] = current_index_df.total_runs.values[0] + previous_index_df.runs.values[0]\n",
    "                df2.loc[df2.index == index[j], \"ball\"] = current_index_df.ball.values[0] + previous_index_df.ball.values[0]\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1  335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2  335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3  335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4  335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  final_total_runs  wickets  runs  \n",
       "0  Royal Challengers Bangalore               222        0     1  \n",
       "1  Royal Challengers Bangalore               222        0     1  \n",
       "2  Royal Challengers Bangalore               222        0     2  \n",
       "3  Royal Challengers Bangalore               222        0     2  \n",
       "4  Royal Challengers Bangalore               222        0     2  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Finding last 5 over's runs, wickets and balls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193429</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>12.2</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193430</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>12.3</td>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193431</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193432</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>12.5</td>\n",
       "      <td>77</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193433</th>\n",
       "      <td>1237181</td>\n",
       "      <td>2</td>\n",
       "      <td>12.6</td>\n",
       "      <td>78</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130194 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball  total_runs  is_wicket  \\\n",
       "0        335982       1   0.1     1           1          0   \n",
       "1        335982       1   0.2     2           0          0   \n",
       "2        335982       1   0.3     3           1          0   \n",
       "3        335982       1   0.4     4           0          0   \n",
       "4        335982       1   0.5     5           0          0   \n",
       "...         ...     ...   ...   ...         ...        ...   \n",
       "193429  1237181       2  12.2    74           1          0   \n",
       "193430  1237181       2  12.3    75           1          0   \n",
       "193431  1237181       2  12.4    76           4          0   \n",
       "193432  1237181       2  12.5    77           1          0   \n",
       "193433  1237181       2  12.6    78           2          0   \n",
       "\n",
       "                 batting_team                 bowling_team  final_total_runs  \\\n",
       "0       Kolkata Knight Riders  Royal Challengers Bangalore               222   \n",
       "1       Kolkata Knight Riders  Royal Challengers Bangalore               222   \n",
       "2       Kolkata Knight Riders  Royal Challengers Bangalore               222   \n",
       "3       Kolkata Knight Riders  Royal Challengers Bangalore               222   \n",
       "4       Kolkata Knight Riders  Royal Challengers Bangalore               222   \n",
       "...                       ...                          ...               ...   \n",
       "193429         Mumbai Indians               Delhi Capitals               157   \n",
       "193430         Mumbai Indians               Delhi Capitals               157   \n",
       "193431         Mumbai Indians               Delhi Capitals               157   \n",
       "193432         Mumbai Indians               Delhi Capitals               157   \n",
       "193433         Mumbai Indians               Delhi Capitals               157   \n",
       "\n",
       "        wickets  runs  \n",
       "0             0     1  \n",
       "1             0     1  \n",
       "2             0     2  \n",
       "3             0     2  \n",
       "4             0     2  \n",
       "...         ...   ...  \n",
       "193429        2   104  \n",
       "193430        2   105  \n",
       "193431        2   109  \n",
       "193432        2   110  \n",
       "193433        2   112  \n",
       "\n",
       "[130194 rows x 11 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.loc[df2.over < int(str(current_index_df.over.values[0]).split(\".\")[0]) - 5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's create new column for last_5_over_wickets\n",
    "df2[\"last_5_over_wickets\"] = 0\n",
    "# let's create new column for last_5_over_runs\n",
    "df2[\"last_5_over_runs\"] = 0\n",
    "# let's create new column for last_5_over_balls\n",
    "df2[\"last_5_over_balls\"] = 0\n",
    " # calculating last run, wickets and balls of last 5 over\n",
    "for i in id:\n",
    "    for inning in range(1, 3):\n",
    "        index = df2.loc[(df2.id == i) & (df2.inning == inning)].index\n",
    "        for j in range(len(index)):\n",
    "            current_index_df = df2.loc[(df2.index == index[j])]\n",
    "            previous_index_df = df2.loc[(df2.index == index[j-1])]            \n",
    "            if current_index_df.over.values[0] <= 5:\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_wickets\"] = current_index_df.wickets.values[0]\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_runs\"] = current_index_df.runs.values[0]\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_balls\"] = current_index_df.ball.values[0]\n",
    "            else:\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_wickets\"] = current_index_df.wickets.values[0] - df2.loc[(df2.id == i) & (df2.inning == inning) & (df2.over < int(str(current_index_df.over.values[0]).split(\".\")[0]) - 5+1), \"wickets\"].values[0]\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_runs\"] = current_index_df.runs.values[0] - df2.loc[(df2.id == i) & (df2.inning == inning) & (df2.over < int(str(current_index_df.over.values[0]).split(\".\")[0]) - 5+1), \"runs\"].values[0]\n",
    "                df2.loc[df2.index == index[j], \"last_5_over_balls\"] = current_index_df.ball.values[0] - df2.loc[(df2.id == i) & (df2.inning == inning) & (df2.over < int(str(current_index_df.over.values[0]).split(\".\")[0]) - 5+1), \"ball\"].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>runs</th>\n",
       "      <th>last_5_over_wickets</th>\n",
       "      <th>last_5_over_runs</th>\n",
       "      <th>last_5_over_balls</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1  335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2  335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3  335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4  335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  final_total_runs  wickets  runs  \\\n",
       "0  Royal Challengers Bangalore               222        0     1   \n",
       "1  Royal Challengers Bangalore               222        0     1   \n",
       "2  Royal Challengers Bangalore               222        0     2   \n",
       "3  Royal Challengers Bangalore               222        0     2   \n",
       "4  Royal Challengers Bangalore               222        0     2   \n",
       "\n",
       "   last_5_over_wickets  last_5_over_runs  last_5_over_balls  \n",
       "0                    0                 1                  1  \n",
       "1                    0                 1                  2  \n",
       "2                    0                 2                  3  \n",
       "3                    0                 2                  4  \n",
       "4                    0                 2                  5  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adding Venue and Winner Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's add winner and venue column from matches_data\n",
    "# let's create column for venue in df2\n",
    "df2[\"venue\"] = \"\"\n",
    "# let's create column for winner\n",
    "df2[\"winner\"] = \"\"\n",
    "for i in id:\n",
    "    temp = matches_data.loc[matches_data.id == i]\n",
    "    df2.loc[df2.id == i, \"venue\"] = temp.venue.values[0]\n",
    "    df2.loc[df2.id == i, \"winner\"] = temp.winner.values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>runs</th>\n",
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       "      <th>last_5_over_runs</th>\n",
       "      <th>last_5_over_balls</th>\n",
       "      <th>venue</th>\n",
       "      <th>winner</th>\n",
       "    </tr>\n",
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       "      <th>0</th>\n",
       "      <td>335982</td>\n",
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       "      <td>1</td>\n",
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       "      <td>Kolkata Knight Riders</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
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       "      <th>1</th>\n",
       "      <td>335982</td>\n",
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       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1  335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2  335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3  335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4  335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  final_total_runs  wickets  runs  \\\n",
       "0  Royal Challengers Bangalore               222        0     1   \n",
       "1  Royal Challengers Bangalore               222        0     1   \n",
       "2  Royal Challengers Bangalore               222        0     2   \n",
       "3  Royal Challengers Bangalore               222        0     2   \n",
       "4  Royal Challengers Bangalore               222        0     2   \n",
       "\n",
       "   last_5_over_wickets  last_5_over_runs  last_5_over_balls  \\\n",
       "0                    0                 1                  1   \n",
       "1                    0                 1                  2   \n",
       "2                    0                 2                  3   \n",
       "3                    0                 2                  4   \n",
       "4                    0                 2                  5   \n",
       "\n",
       "                   venue                 winner  \n",
       "0  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "1  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "2  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "3  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "4  M Chinnaswamy Stadium  Kolkata Knight Riders  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                       0\n",
       "inning                   0\n",
       "over                     0\n",
       "ball                     0\n",
       "total_runs               0\n",
       "is_wicket                0\n",
       "batting_team             0\n",
       "bowling_team             0\n",
       "final_total_runs         0\n",
       "wickets                  0\n",
       "runs                     0\n",
       "last_5_over_wickets      0\n",
       "last_5_over_runs         0\n",
       "last_5_over_balls        0\n",
       "venue                    0\n",
       "winner                 181\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's find there is any NaN values \n",
    "\n",
    "df2.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 829813, 1178424])"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[df2.winner.isna()].id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2</td>\n",
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       "      <td>M Chinnaswamy Stadium</td>\n",
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       "      <td>Rajasthan Royals</td>\n",
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       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>17</td>\n",
       "      <td>M.Chinnaswamy Stadium</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>176347</th>\n",
       "      <td>1178424</td>\n",
       "      <td>2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>18</td>\n",
       "      <td>M.Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176348</th>\n",
       "      <td>1178424</td>\n",
       "      <td>2</td>\n",
       "      <td>3.1</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>19</td>\n",
       "      <td>M.Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176349</th>\n",
       "      <td>1178424</td>\n",
       "      <td>2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>41</td>\n",
       "      <td>20</td>\n",
       "      <td>M.Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>181 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  inning  over  ball  total_runs  is_wicket      batting_team  \\\n",
       "121109   829813       1   0.1     1           1          0  Delhi Daredevils   \n",
       "121110   829813       1   0.2     2           0          0  Delhi Daredevils   \n",
       "121111   829813       1   0.3     3           1          0  Delhi Daredevils   \n",
       "121112   829813       1   0.4     4           0          0  Delhi Daredevils   \n",
       "121113   829813       1   0.5     5           0          0  Delhi Daredevils   \n",
       "...         ...     ...   ...   ...         ...        ...               ...   \n",
       "176345  1178424       2   2.4    16           0          0  Rajasthan Royals   \n",
       "176346  1178424       2   2.5    17           6          0  Rajasthan Royals   \n",
       "176347  1178424       2   2.6    18           4          0  Rajasthan Royals   \n",
       "176348  1178424       2   3.1    19           1          0  Rajasthan Royals   \n",
       "176349  1178424       2   3.2    20           0          1  Rajasthan Royals   \n",
       "\n",
       "                       bowling_team  final_total_runs  wickets  runs  \\\n",
       "121109  Royal Challengers Bangalore               187        0     1   \n",
       "121110  Royal Challengers Bangalore               187        0     1   \n",
       "121111  Royal Challengers Bangalore               187        0     2   \n",
       "121112  Royal Challengers Bangalore               187        0     2   \n",
       "121113  Royal Challengers Bangalore               187        0     2   \n",
       "...                             ...               ...      ...   ...   \n",
       "176345  Royal Challengers Bangalore                41        0    30   \n",
       "176346  Royal Challengers Bangalore                41        0    36   \n",
       "176347  Royal Challengers Bangalore                41        0    40   \n",
       "176348  Royal Challengers Bangalore                41        0    41   \n",
       "176349  Royal Challengers Bangalore                41        1    41   \n",
       "\n",
       "        last_5_over_wickets  last_5_over_runs  last_5_over_balls  \\\n",
       "121109                    0                 1                  1   \n",
       "121110                    0                 1                  2   \n",
       "121111                    0                 2                  3   \n",
       "121112                    0                 2                  4   \n",
       "121113                    0                 2                  5   \n",
       "...                     ...               ...                ...   \n",
       "176345                    0                30                 16   \n",
       "176346                    0                36                 17   \n",
       "176347                    0                40                 18   \n",
       "176348                    0                41                 19   \n",
       "176349                    1                41                 20   \n",
       "\n",
       "                        venue winner  \n",
       "121109  M Chinnaswamy Stadium    NaN  \n",
       "121110  M Chinnaswamy Stadium    NaN  \n",
       "121111  M Chinnaswamy Stadium    NaN  \n",
       "121112  M Chinnaswamy Stadium    NaN  \n",
       "121113  M Chinnaswamy Stadium    NaN  \n",
       "...                       ...    ...  \n",
       "176345  M.Chinnaswamy Stadium    NaN  \n",
       "176346  M.Chinnaswamy Stadium    NaN  \n",
       "176347  M.Chinnaswamy Stadium    NaN  \n",
       "176348  M.Chinnaswamy Stadium    NaN  \n",
       "176349  M.Chinnaswamy Stadium    NaN  \n",
       "\n",
       "[181 rows x 16 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[df2.winner.isna()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### There is no result found for two matches, matches was abandoned in 2nd inning\n",
    "- here i get 31 NaN values in winner column \n",
    "- NaN values found for two id means two match was abandoned for some reason\n",
    "- here we can see in above record in two matches and in 2nd inning there were only 4-5 over was played\n",
    "- because some reasone matche was abandoned\n",
    "- that's why there is no result found for winning team\n",
    "- so it's better to drop that records\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(193277, 16)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's drop that NaN recorded matches and make a new data frame named df3\n",
    "\n",
    "df3 = df2.dropna().reset_index(drop=True).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>final_total_runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>runs</th>\n",
       "      <th>last_5_over_wickets</th>\n",
       "      <th>last_5_over_runs</th>\n",
       "      <th>last_5_over_balls</th>\n",
       "      <th>venue</th>\n",
       "      <th>winner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  inning  over  ball  total_runs  is_wicket           batting_team  \\\n",
       "0  335982       1   0.1     1           1          0  Kolkata Knight Riders   \n",
       "1  335982       1   0.2     2           0          0  Kolkata Knight Riders   \n",
       "2  335982       1   0.3     3           1          0  Kolkata Knight Riders   \n",
       "3  335982       1   0.4     4           0          0  Kolkata Knight Riders   \n",
       "4  335982       1   0.5     5           0          0  Kolkata Knight Riders   \n",
       "\n",
       "                  bowling_team  final_total_runs  wickets  runs  \\\n",
       "0  Royal Challengers Bangalore               222        0     1   \n",
       "1  Royal Challengers Bangalore               222        0     1   \n",
       "2  Royal Challengers Bangalore               222        0     2   \n",
       "3  Royal Challengers Bangalore               222        0     2   \n",
       "4  Royal Challengers Bangalore               222        0     2   \n",
       "\n",
       "   last_5_over_wickets  last_5_over_runs  last_5_over_balls  \\\n",
       "0                    0                 1                  1   \n",
       "1                    0                 1                  2   \n",
       "2                    0                 2                  3   \n",
       "3                    0                 2                  4   \n",
       "4                    0                 2                  5   \n",
       "\n",
       "                   venue                 winner  \n",
       "0  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "1  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "2  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "3  M Chinnaswamy Stadium  Kolkata Knight Riders  \n",
       "4  M Chinnaswamy Stadium  Kolkata Knight Riders  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(193096, 16)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Barabati Stadium', 'Brabourne Stadium', 'Buffalo Park',\n",
       "       'De Beers Diamond Oval', 'Dr DY Patil Sports Academy',\n",
       "       'Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium',\n",
       "       'Dubai International Cricket Stadium', 'Eden Gardens',\n",
       "       'Feroz Shah Kotla', 'Green Park',\n",
       "       'Himachal Pradesh Cricket Association Stadium',\n",
       "       'Holkar Cricket Stadium', 'JSCA International Stadium Complex',\n",
       "       'Kingsmead', 'M Chinnaswamy Stadium', 'M.Chinnaswamy Stadium',\n",
       "       'MA Chidambaram Stadium, Chepauk',\n",
       "       'Maharashtra Cricket Association Stadium', 'Nehru Stadium',\n",
       "       'New Wanderers Stadium', 'Newlands', 'OUTsurance Oval',\n",
       "       'Punjab Cricket Association IS Bindra Stadium, Mohali',\n",
       "       'Punjab Cricket Association Stadium, Mohali',\n",
       "       'Rajiv Gandhi International Stadium, Uppal',\n",
       "       'Sardar Patel Stadium, Motera',\n",
       "       'Saurashtra Cricket Association Stadium', 'Sawai Mansingh Stadium',\n",
       "       'Shaheed Veer Narayan Singh International Stadium',\n",
       "       'Sharjah Cricket Stadium', 'Sheikh Zayed Stadium',\n",
       "       \"St George's Park\", 'Subrata Roy Sahara Stadium',\n",
       "       'SuperSport Park', 'Vidarbha Cricket Association Stadium, Jamtha',\n",
       "       'Wankhede Stadium'], dtype=object)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's look at venue feature\n",
    "\n",
    "np.sort(df3.venue.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here M Chinnaswamy Stadium and M.Chinnaswamy Stadium both are same\n",
    "# Punjab Cricket Association IS Bindra Stadium, Mohali and Punjab Cricket Association Stadium, Mohali both are same\n",
    "# so let's make it one\n",
    "\n",
    "df3.venue.replace({\"M.Chinnaswamy Stadium\": \"M Chinnaswamy Stadium\", \"Punjab Cricket Association IS Bindra Stadium, Mohali\": \"Punjab Cricket Association Stadium, Mohali\"}, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# EDA and feature engineer are done here let's save this data frame for feature selection and model building\n",
    "\n",
    "df3.to_csv(\"eda_feature_engineering.csv\", index=False)"
   ]
  }
 ],
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