Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ipl.csv  Notebook.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('ipl.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>mid</th>\n",
       "      <th>date</th>\n",
       "      <th>venue</th>\n",
       "      <th>bat_team</th>\n",
       "      <th>bowl_team</th>\n",
       "      <th>batsman</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>overs</th>\n",
       "      <th>runs_last_5</th>\n",
       "      <th>wickets_last_5</th>\n",
       "      <th>striker</th>\n",
       "      <th>non-striker</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mid        date                  venue               bat_team  \\\n",
       "0    1  2008-04-18  M Chinnaswamy Stadium  Kolkata Knight Riders   \n",
       "1    1  2008-04-18  M Chinnaswamy Stadium  Kolkata Knight Riders   \n",
       "2    1  2008-04-18  M Chinnaswamy Stadium  Kolkata Knight Riders   \n",
       "3    1  2008-04-18  M Chinnaswamy Stadium  Kolkata Knight Riders   \n",
       "4    1  2008-04-18  M Chinnaswamy Stadium  Kolkata Knight Riders   \n",
       "\n",
       "                     bowl_team      batsman   bowler  runs  wickets  overs  \\\n",
       "0  Royal Challengers Bangalore   SC Ganguly  P Kumar     1        0    0.1   \n",
       "1  Royal Challengers Bangalore  BB McCullum  P Kumar     1        0    0.2   \n",
       "2  Royal Challengers Bangalore  BB McCullum  P Kumar     2        0    0.2   \n",
       "3  Royal Challengers Bangalore  BB McCullum  P Kumar     2        0    0.3   \n",
       "4  Royal Challengers Bangalore  BB McCullum  P Kumar     2        0    0.4   \n",
       "\n",
       "   runs_last_5  wickets_last_5  striker  non-striker  total  \n",
       "0            1               0        0            0    222  \n",
       "1            1               0        0            0    222  \n",
       "2            2               0        0            0    222  \n",
       "3            2               0        0            0    222  \n",
       "4            2               0        0            0    222  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df['venue'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- Data Cleaning ---\n",
    "# Removing unwanted columns\n",
    "columns_to_remove = ['mid', 'venue', 'batsman', 'bowler', 'striker', 'non-striker']\n",
    "df = df.drop(labels=columns_to_remove, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>bat_team</th>\n",
       "      <th>bowl_team</th>\n",
       "      <th>runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>overs</th>\n",
       "      <th>runs_last_5</th>\n",
       "      <th>wickets_last_5</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date               bat_team                    bowl_team  runs  \\\n",
       "0  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "1  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "2  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "3  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "4  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "\n",
       "   wickets  overs  runs_last_5  wickets_last_5  total  \n",
       "0        0    0.1            1               0    222  \n",
       "1        0    0.2            1               0    222  \n",
       "2        0    0.2            2               0    222  \n",
       "3        0    0.3            2               0    222  \n",
       "4        0    0.4            2               0    222  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Kolkata Knight Riders', 'Chennai Super Kings', 'Rajasthan Royals',\n",
       "       'Mumbai Indians', 'Deccan Chargers', 'Kings XI Punjab',\n",
       "       'Royal Challengers Bangalore', 'Delhi Daredevils',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Sunrisers Hyderabad',\n",
       "       'Rising Pune Supergiants', 'Gujarat Lions',\n",
       "       'Rising Pune Supergiant'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.bat_team.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "consistent_teams = ['Kolkata Knight Riders', 'Chennai Super Kings', 'Rajasthan Royals',\n",
    "                    'Mumbai Indians', 'Kings XI Punjab', 'Royal Challengers Bangalore',\n",
    "                    'Delhi Daredevils', 'Sunrisers Hyderabad']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[(df['bat_team'].isin(consistent_teams)) & (df['bowl_team'].isin(consistent_teams))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>bat_team</th>\n",
       "      <th>bowl_team</th>\n",
       "      <th>runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>overs</th>\n",
       "      <th>runs_last_5</th>\n",
       "      <th>wickets_last_5</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date               bat_team                    bowl_team  runs  \\\n",
       "0  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "1  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "2  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "3  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "4  2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore     2   \n",
       "\n",
       "   wickets  overs  runs_last_5  wickets_last_5  total  \n",
       "0        0    0.1            1               0    222  \n",
       "1        0    0.2            1               0    222  \n",
       "2        0    0.2            2               0    222  \n",
       "3        0    0.3            2               0    222  \n",
       "4        0    0.4            2               0    222  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['overs'] >= 5.0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Kolkata Knight Riders' 'Chennai Super Kings' 'Rajasthan Royals'\n",
      " 'Mumbai Indians' 'Kings XI Punjab' 'Royal Challengers Bangalore'\n",
      " 'Delhi Daredevils' 'Sunrisers Hyderabad']\n",
      "8\n"
     ]
    }
   ],
   "source": [
    "print(df.bat_team.unique())\n",
    "print(len(df.bat_team.unique()))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#To convert date\n",
    "\n",
    "from datetime import datetime\n",
    "df['date'] = df['date'].apply(lambda x: datetime.strptime(x, '%Y-%m-%d'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>date</th>\n",
       "      <th>bat_team</th>\n",
       "      <th>bowl_team</th>\n",
       "      <th>runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>overs</th>\n",
       "      <th>runs_last_5</th>\n",
       "      <th>wickets_last_5</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.2</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.3</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.4</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.5</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date               bat_team                    bowl_team  runs  \\\n",
       "32 2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore    61   \n",
       "33 2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore    61   \n",
       "34 2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore    61   \n",
       "35 2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore    61   \n",
       "36 2008-04-18  Kolkata Knight Riders  Royal Challengers Bangalore    61   \n",
       "\n",
       "    wickets  overs  runs_last_5  wickets_last_5  total  \n",
       "32        0    5.1           59               0    222  \n",
       "33        1    5.2           59               1    222  \n",
       "34        1    5.3           59               1    222  \n",
       "35        1    5.4           59               1    222  \n",
       "36        1    5.5           58               1    222  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfNew = pd.get_dummies(data=df, columns=['bat_team', 'bowl_team'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>date</th>\n",
       "      <th>runs</th>\n",
       "      <th>wickets</th>\n",
       "      <th>overs</th>\n",
       "      <th>runs_last_5</th>\n",
       "      <th>wickets_last_5</th>\n",
       "      <th>total</th>\n",
       "      <th>bat_team_Chennai Super Kings</th>\n",
       "      <th>bat_team_Delhi Daredevils</th>\n",
       "      <th>bat_team_Kings XI Punjab</th>\n",
       "      <th>...</th>\n",
       "      <th>bat_team_Royal Challengers Bangalore</th>\n",
       "      <th>bat_team_Sunrisers Hyderabad</th>\n",
       "      <th>bowl_team_Chennai Super Kings</th>\n",
       "      <th>bowl_team_Delhi Daredevils</th>\n",
       "      <th>bowl_team_Kings XI Punjab</th>\n",
       "      <th>bowl_team_Kolkata Knight Riders</th>\n",
       "      <th>bowl_team_Mumbai Indians</th>\n",
       "      <th>bowl_team_Rajasthan Royals</th>\n",
       "      <th>bowl_team_Royal Challengers Bangalore</th>\n",
       "      <th>bowl_team_Sunrisers Hyderabad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.2</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.3</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.4</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>5.5</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  runs  wickets  overs  runs_last_5  wickets_last_5  total  \\\n",
       "32 2008-04-18    61        0    5.1           59               0    222   \n",
       "33 2008-04-18    61        1    5.2           59               1    222   \n",
       "34 2008-04-18    61        1    5.3           59               1    222   \n",
       "35 2008-04-18    61        1    5.4           59               1    222   \n",
       "36 2008-04-18    61        1    5.5           58               1    222   \n",
       "\n",
       "    bat_team_Chennai Super Kings  bat_team_Delhi Daredevils  \\\n",
       "32                             0                          0   \n",
       "33                             0                          0   \n",
       "34                             0                          0   \n",
       "35                             0                          0   \n",
       "36                             0                          0   \n",
       "\n",
       "    bat_team_Kings XI Punjab  ...  bat_team_Royal Challengers Bangalore  \\\n",
       "32                         0  ...                                     0   \n",
       "33                         0  ...                                     0   \n",
       "34                         0  ...                                     0   \n",
       "35                         0  ...                                     0   \n",
       "36                         0  ...                                     0   \n",
       "\n",
       "    bat_team_Sunrisers Hyderabad  bowl_team_Chennai Super Kings  \\\n",
       "32                             0                              0   \n",
       "33                             0                              0   \n",
       "34                             0                              0   \n",
       "35                             0                              0   \n",
       "36                             0                              0   \n",
       "\n",
       "    bowl_team_Delhi Daredevils  bowl_team_Kings XI Punjab  \\\n",
       "32                           0                          0   \n",
       "33                           0                          0   \n",
       "34                           0                          0   \n",
       "35                           0                          0   \n",
       "36                           0                          0   \n",
       "\n",
       "    bowl_team_Kolkata Knight Riders  bowl_team_Mumbai Indians  \\\n",
       "32                                0                         0   \n",
       "33                                0                         0   \n",
       "34                                0                         0   \n",
       "35                                0                         0   \n",
       "36                                0                         0   \n",
       "\n",
       "    bowl_team_Rajasthan Royals  bowl_team_Royal Challengers Bangalore  \\\n",
       "32                           0                                      1   \n",
       "33                           0                                      1   \n",
       "34                           0                                      1   \n",
       "35                           0                                      1   \n",
       "36                           0                                      1   \n",
       "\n",
       "    bowl_team_Sunrisers Hyderabad  \n",
       "32                              0  \n",
       "33                              0  \n",
       "34                              0  \n",
       "35                              0  \n",
       "36                              0  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfNew.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfNew = dfNew[['date', 'bat_team_Chennai Super Kings', 'bat_team_Delhi Daredevils', 'bat_team_Kings XI Punjab',\n",
    "              'bat_team_Kolkata Knight Riders', 'bat_team_Mumbai Indians', 'bat_team_Rajasthan Royals',\n",
    "              'bat_team_Royal Challengers Bangalore', 'bat_team_Sunrisers Hyderabad',\n",
    "              'bowl_team_Chennai Super Kings', 'bowl_team_Delhi Daredevils', 'bowl_team_Kings XI Punjab',\n",
    "              'bowl_team_Kolkata Knight Riders', 'bowl_team_Mumbai Indians', 'bowl_team_Rajasthan Royals',\n",
    "              'bowl_team_Royal Challengers Bangalore', 'bowl_team_Sunrisers Hyderabad',\n",
    "              'overs', 'runs', 'wickets', 'runs_last_5', 'wickets_last_5', 'total']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = dfNew.drop(labels='total', axis=1)[dfNew['date'].dt.year <= 2016]\n",
    "X_test = dfNew.drop(labels='total', axis=1)[dfNew['date'].dt.year >= 2017]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = dfNew[dfNew['date'].dt.year <= 2016]['total'].values\n",
    "y_test = dfNew[dfNew['date'].dt.year >= 2017]['total'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train.drop(labels='date', axis=True, inplace=True)\n",
    "X_test.drop(labels='date', axis=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "regressor = LinearRegression()\n",
    "regressor.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction=regressor.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 12.118617546193295\n",
      "MSE: 251.00792310417455\n",
      "RMSE: 15.843229566732111\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "import numpy as np\n",
    "print('MAE:', metrics.mean_absolute_error(y_test, prediction))\n",
    "print('MSE:', metrics.mean_squared_error(y_test, prediction))\n",
    "print('RMSE:', np.sqrt(metrics.mean_squared_error(y_test, prediction)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4540962.186675368, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4461556.968411786, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4567942.344821787, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4124925.3101019016, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4566898.169749207, tolerance: 2646.1437660192796\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 589199.3415436838, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 482834.70580263715, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 253595.10633033793, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 273554.33741877694, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 328224.7875914704, tolerance: 2646.1437660192796\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 589202.593751845, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 482835.82185958605, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 253599.47337836865, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 273552.7474546684, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 328228.2559108827, tolerance: 2646.1437660192796\n",
      "  positive)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'alpha': 1}\n",
      "-320.8263789858526\n"
     ]
    }
   ],
   "source": [
    "lasso=Lasso()\n",
    "parameters={'alpha':[1e-15,1e-10,1e-8,1e-3,1e-2,1,5,10,20,30,35,40]}\n",
    "lasso_regressor=GridSearchCV(lasso,parameters,scoring='neg_mean_squared_error',cv=5)\n",
    "\n",
    "lasso_regressor.fit(X_train,y_train)\n",
    "print(lasso_regressor.best_params_)\n",
    "print(lasso_regressor.best_score_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'Model.pkl'\n",
    "pickle.dump(regressor, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction=lasso_regressor.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 12.214053814850246\n",
      "MSE: 262.3797366400714\n",
      "RMSE: 16.19813991296752\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "import numpy as np\n",
    "print('MAE:', metrics.mean_absolute_error(y_test, prediction))\n",
    "print('MSE:', metrics.mean_squared_error(y_test, prediction))\n",
    "print('RMSE:', np.sqrt(metrics.mean_squared_error(y_test, prediction)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Ridge Regression\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4540962.186675368, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4461556.968411786, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4567942.344821787, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4124925.3101019016, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4566898.169749207, tolerance: 2646.1437660192796\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 589199.3415436838, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 482834.70580263715, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 253595.10633033793, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 273554.33741877694, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 328224.7875914704, tolerance: 2646.1437660192796\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 589202.593751845, tolerance: 2529.955696594561\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 482835.82185958605, tolerance: 2547.0380710286604\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 253599.47337836865, tolerance: 2667.8126904366463\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 273552.7474546684, tolerance: 2712.348891397666\n",
      "  positive)\n",
      "/home/rishi/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:531: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 328228.2559108827, tolerance: 2646.1437660192796\n",
      "  positive)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'alpha': 1}\n",
      "-320.8263789858526\n"
     ]
    }
   ],
   "source": [
    "lasso=Lasso()\n",
    "parameters={'alpha':[1e-15,1e-10,1e-8,1e-3,1e-2,1,5,10,20,30,35,40]}\n",
    "lasso_regressor=GridSearchCV(lasso,parameters,scoring='neg_mean_squared_error',cv=5)\n",
    "\n",
    "lasso_regressor.fit(X_train,y_train)\n",
    "print(lasso_regressor.best_params_)\n",
    "print(lasso_regressor.best_score_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'Model.pkl'\n",
    "pickle.dump(lasso_regressor, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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