Exploratory Data Analysis on IPL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "efba3c63",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis on Indian Premier League (IPL)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b06842a",
   "metadata": {},
   "source": [
    "## Interesting insights into Indian Premier League matches (2008–2019)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6cbccd9",
   "metadata": {},
   "source": [
    "The dataset consist of data about IPL matches played from the year 2008 to 2019. IPL is a professional Twenty20 cricket league founded by the Board of Control for Cricket in India (BCCI) in 2008. The league has 8 teams representing 8 different Indian cities or states. It enjoys tremendous popularity and the brand value of the IPL in 2019 was estimated to be ₹475 billion (US$6.7 billion). So let’s analyze IPL through stats."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db2b9b6e",
   "metadata": {},
   "source": [
    "### Objectives:\n",
    "\n",
    "* To find the team that won the most number of matches in a season.\n",
    "* To find the team that lost the most number of matches in a season.\n",
    "* Does winning toss increases the chances of victory.\n",
    "* To find the player with the most player of the match awards.\n",
    "* To find the city that hosted the maximum number of IPL matches.\n",
    "* To find the most winning team for each season.\n",
    "* To find the on-field umpire with the maximum number of IPL matches.\n",
    "* To find the biggest victories in IPL while defending a total and while chasing a total."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aea93ffb",
   "metadata": {},
   "source": [
    "To have a detailed understanding of Exploratory Data Analysis(EDA), I recommend you to visit my blog:\n",
    "\n",
    "### Data Preparation and Cleaning\n",
    "\n",
    "Let’s start by reading the csv file to Pandas DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2902f8a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "ipl_matches_df = pd.read_csv('matches.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7c8ac2d3",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05/05/19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>07/05/19</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>08/05/19</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>10/05/19</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>Sundaram Ravi</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>Chettithody Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12/05/19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season           city        date                        team1  \\\n",
       "0        1    2017      Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "1        2    2017           Pune  2017-04-06               Mumbai Indians   \n",
       "2        3    2017         Rajkot  2017-04-07                Gujarat Lions   \n",
       "3        4    2017         Indore  2017-04-08       Rising Pune Supergiant   \n",
       "4        5    2017      Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "..     ...     ...            ...         ...                          ...   \n",
       "751  11347    2019         Mumbai    05/05/19        Kolkata Knight Riders   \n",
       "752  11412    2019        Chennai    07/05/19          Chennai Super Kings   \n",
       "753  11413    2019  Visakhapatnam    08/05/19          Sunrisers Hyderabad   \n",
       "754  11414    2019  Visakhapatnam    10/05/19               Delhi Capitals   \n",
       "755  11415    2019      Hyderabad    12/05/19               Mumbai Indians   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "0    Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1         Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2          Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3                Kings XI Punjab              Kings XI Punjab         field   \n",
       "4               Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "..                           ...                          ...           ...   \n",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           bat   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "0    normal           0          Sunrisers Hyderabad           35   \n",
       "1    normal           0       Rising Pune Supergiant            0   \n",
       "2    normal           0        Kolkata Knight Riders            0   \n",
       "3    normal           0              Kings XI Punjab            0   \n",
       "4    normal           0  Royal Challengers Bangalore           15   \n",
       "..      ...         ...                          ...          ...   \n",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "0                 0    Yuvraj Singh   \n",
       "1                 7       SPD Smith   \n",
       "2                10         CA Lynn   \n",
       "3                 6      GJ Maxwell   \n",
       "4                 0       KM Jadhav   \n",
       "..              ...             ...   \n",
       "751               9       HH Pandya   \n",
       "752               6        AS Yadav   \n",
       "753               2         RR Pant   \n",
       "754               6    F du Plessis   \n",
       "755               0       JJ Bumrah   \n",
       "\n",
       "                                         venue         umpire1  \\\n",
       "0    Rajiv Gandhi International Stadium, Uppal     AY Dandekar   \n",
       "1      Maharashtra Cricket Association Stadium  A Nand Kishore   \n",
       "2       Saurashtra Cricket Association Stadium     Nitin Menon   \n",
       "3                       Holkar Cricket Stadium    AK Chaudhary   \n",
       "4                        M Chinnaswamy Stadium             NaN   \n",
       "..                                         ...             ...   \n",
       "751                           Wankhede Stadium   Nanda Kishore   \n",
       "752                  M. A. Chidambaram Stadium     Nigel Llong   \n",
       "753                           ACA-VDCA Stadium             NaN   \n",
       "754                           ACA-VDCA Stadium   Sundaram Ravi   \n",
       "755         Rajiv Gandhi Intl. Cricket Stadium     Nitin Menon   \n",
       "\n",
       "            umpire2                  umpire3  \n",
       "0          NJ Llong                      NaN  \n",
       "1            S Ravi                      NaN  \n",
       "2         CK Nandan                      NaN  \n",
       "3     C Shamshuddin                      NaN  \n",
       "4               NaN                      NaN  \n",
       "..              ...                      ...  \n",
       "751        O Nandan                   S Ravi  \n",
       "752     Nitin Menon                Ian Gould  \n",
       "753             NaN                      NaN  \n",
       "754  Bruce Oxenford  Chettithody Shamshuddin  \n",
       "755       Ian Gould              Nigel Llong  \n",
       "\n",
       "[756 rows x 18 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_matches_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a73e774",
   "metadata": {},
   "source": [
    "So there are 756 rows and 18 columns. 756 rows imply that there were 756 IPL matches held between 2008 and 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e5159054",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 756 entries, 0 to 755\n",
      "Data columns (total 18 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               756 non-null    int64 \n",
      " 1   season           756 non-null    int64 \n",
      " 2   city             749 non-null    object\n",
      " 3   date             756 non-null    object\n",
      " 4   team1            756 non-null    object\n",
      " 5   team2            756 non-null    object\n",
      " 6   toss_winner      756 non-null    object\n",
      " 7   toss_decision    756 non-null    object\n",
      " 8   result           756 non-null    object\n",
      " 9   dl_applied       756 non-null    int64 \n",
      " 10  winner           752 non-null    object\n",
      " 11  win_by_runs      756 non-null    int64 \n",
      " 12  win_by_wickets   756 non-null    int64 \n",
      " 13  player_of_match  752 non-null    object\n",
      " 14  venue            756 non-null    object\n",
      " 15  umpire1          754 non-null    object\n",
      " 16  umpire2          754 non-null    object\n",
      " 17  umpire3          119 non-null    object\n",
      "dtypes: int64(5), object(13)\n",
      "memory usage: 106.4+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl_matches_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d03b6ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1792.178571</td>\n",
       "      <td>2013.444444</td>\n",
       "      <td>0.025132</td>\n",
       "      <td>13.283069</td>\n",
       "      <td>3.350529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3464.478148</td>\n",
       "      <td>3.366895</td>\n",
       "      <td>0.156630</td>\n",
       "      <td>23.471144</td>\n",
       "      <td>3.387963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>189.750000</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>378.500000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>567.250000</td>\n",
       "      <td>2016.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11415.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id       season  dl_applied  win_by_runs  win_by_wickets\n",
       "count    756.000000   756.000000  756.000000   756.000000      756.000000\n",
       "mean    1792.178571  2013.444444    0.025132    13.283069        3.350529\n",
       "std     3464.478148     3.366895    0.156630    23.471144        3.387963\n",
       "min        1.000000  2008.000000    0.000000     0.000000        0.000000\n",
       "25%      189.750000  2011.000000    0.000000     0.000000        0.000000\n",
       "50%      378.500000  2013.000000    0.000000     0.000000        4.000000\n",
       "75%      567.250000  2016.000000    0.000000    19.000000        6.000000\n",
       "max    11415.000000  2019.000000    1.000000   146.000000       10.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_matches_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59697505",
   "metadata": {},
   "source": [
    "### Observations:\n",
    "\n",
    "The following inferences can be made from the describe() method:\n",
    "\n",
    "* The .csv file has data of IPL matches starting from the season 2008 to 2019.\n",
    "* The biggest margin of victory for the team batting first(win_by_runs) is 146 runs.\n",
    "* The biggest victory of the team batting second(win_by_wickets) is by 10 wickets.\n",
    "* 75% of the victorious teams that bat first won by a margin of 19 runs.\n",
    "* 75% of the victorious teams that bat second won by a margin of 6 wickets.\n",
    "* There were 756 IPL matches hosted from 2008 to 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "06605048",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',\n",
       "       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',\n",
       "       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',\n",
       "       'umpire3'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_matches_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19d144a0",
   "metadata": {},
   "source": [
    "Let’s view the unique values of each column to help us understand the dataset better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c78ea543",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[    1     2     3     4     5     6     7     8     9    10    11    12\n",
      "    13    14    15    16    17    18    19    20    21    22    23    24\n",
      "    25    26    27    28    29    30    31    32    33    34    35    36\n",
      "    37    38    39    40    41    42    43    44    45    46    47    48\n",
      "    49    50    51    52    53    54    55    56    57    58    59    60\n",
      "    61    62    63    64    65    66    67    68    69    70    71    72\n",
      "    73    74    75    76    77    78    79    80    81    82    83    84\n",
      "    85    86    87    88    89    90    91    92    93    94    95    96\n",
      "    97    98    99   100   101   102   103   104   105   106   107   108\n",
      "   109   110   111   112   113   114   115   116   117   118   119   120\n",
      "   121   122   123   124   125   126   127   128   129   130   131   132\n",
      "   133   134   135   136   137   138   139   140   141   142   143   144\n",
      "   145   146   147   148   149   150   151   152   153   154   155   156\n",
      "   157   158   159   160   161   162   163   164   165   166   167   168\n",
      "   169   170   171   172   173   174   175   176   177   178   179   180\n",
      "   181   182   183   184   185   186   187   188   189   190   191   192\n",
      "   193   194   195   196   197   198   199   200   201   202   203   204\n",
      "   205   206   207   208   209   210   211   212   213   214   215   216\n",
      "   217   218   219   220   221   222   223   224   225   226   227   228\n",
      "   229   230   231   232   233   234   235   236   237   238   239   240\n",
      "   241   242   243   244   245   246   247   248   249   250   251   252\n",
      "   253   254   255   256   257   258   259   260   261   262   263   264\n",
      "   265   266   267   268   269   270   271   272   273   274   275   276\n",
      "   277   278   279   280   281   282   283   284   285   286   287   288\n",
      "   289   290   291   292   293   294   295   296   297   298   299   300\n",
      "   301   302   303   304   305   306   307   308   309   310   311   312\n",
      "   313   314   315   316   317   318   319   320   321   322   323   324\n",
      "   325   326   327   328   329   330   331   332   333   334   335   336\n",
      "   337   338   339   340   341   342   343   344   345   346   347   348\n",
      "   349   350   351   352   353   354   355   356   357   358   359   360\n",
      "   361   362   363   364   365   366   367   368   369   370   371   372\n",
      "   373   374   375   376   377   378   379   380   381   382   383   384\n",
      "   385   386   387   388   389   390   391   392   393   394   395   396\n",
      "   397   398   399   400   401   402   403   404   405   406   407   408\n",
      "   409   410   411   412   413   414   415   416   417   418   419   420\n",
      "   421   422   423   424   425   426   427   428   429   430   431   432\n",
      "   433   434   435   436   437   438   439   440   441   442   443   444\n",
      "   445   446   447   448   449   450   451   452   453   454   455   456\n",
      "   457   458   459   460   461   462   463   464   465   466   467   468\n",
      "   469   470   471   472   473   474   475   476   477   478   479   480\n",
      "   481   482   483   484   485   486   487   488   489   490   491   492\n",
      "   493   494   495   496   497   498   499   500   501   502   503   504\n",
      "   505   506   507   508   509   510   511   512   513   514   515   516\n",
      "   517   518   519   520   521   522   523   524   525   526   527   528\n",
      "   529   530   531   532   533   534   535   536   537   538   539   540\n",
      "   541   542   543   544   545   546   547   548   549   550   551   552\n",
      "   553   554   555   556   557   558   559   560   561   562   563   564\n",
      "   565   566   567   568   569   570   571   572   573   574   575   576\n",
      "   577   578   579   580   581   582   583   584   585   586   587   588\n",
      "   589   590   591   592   593   594   595   596   597   598   599   600\n",
      "   601   602   603   604   605   606   607   608   609   610   611   612\n",
      "   613   614   615   616   617   618   619   620   621   622   623   624\n",
      "   625   626   627   628   629   630   631   632   633   634   635   636\n",
      "  7894  7895  7896  7897  7898  7899  7900  7901  7902  7903  7904  7905\n",
      "  7906  7907  7908  7909  7910  7911  7912  7913  7914  7915  7916  7917\n",
      "  7918  7919  7920  7921  7922  7923  7924  7925  7926  7927  7928  7929\n",
      "  7930  7931  7932  7933  7934  7935  7936  7937  7938  7939  7940  7941\n",
      "  7942  7943  7944  7945  7946  7947  7948  7949  7950  7951  7952  7953\n",
      " 11137 11138 11139 11140 11141 11142 11143 11144 11145 11146 11147 11148\n",
      " 11149 11150 11151 11152 11153 11309 11310 11311 11312 11313 11314 11315\n",
      " 11316 11317 11318 11319 11320 11321 11322 11323 11324 11325 11326 11327\n",
      " 11328 11329 11330 11331 11332 11333 11334 11335 11336 11337 11338 11339\n",
      " 11340 11341 11342 11343 11344 11345 11346 11347 11412 11413 11414 11415]\n",
      "[2017 2008 2009 2010 2011 2012 2013 2014 2015 2016 2018 2019]\n",
      "['Hyderabad' 'Pune' 'Rajkot' 'Indore' 'Bangalore' 'Mumbai' 'Kolkata'\n",
      " 'Delhi' 'Chandigarh' 'Kanpur' 'Jaipur' 'Chennai' 'Cape Town'\n",
      " 'Port Elizabeth' 'Durban' 'Centurion' 'East London' 'Johannesburg'\n",
      " 'Kimberley' 'Bloemfontein' 'Ahmedabad' 'Cuttack' 'Nagpur' 'Dharamsala'\n",
      " 'Kochi' 'Visakhapatnam' 'Raipur' 'Ranchi' 'Abu Dhabi' 'Sharjah' nan\n",
      " 'Mohali' 'Bengaluru']\n",
      "['2017-04-05' '2017-04-06' '2017-04-07' '2017-04-08' '2017-04-09'\n",
      " '2017-04-10' '2017-04-11' '2017-04-12' '2017-04-13' '2017-04-14'\n",
      " '2017-04-15' '2017-04-16' '2017-04-17' '2017-04-18' '2017-04-19'\n",
      " '2017-04-20' '2017-04-21' '2017-04-22' '2017-04-23' '2017-04-24'\n",
      " '2017-04-26' '2017-04-27' '2017-04-28' '2017-04-29' '2017-04-30'\n",
      " '2017-05-01' '2017-05-02' '2017-05-03' '2017-05-04' '2017-05-05'\n",
      " '2017-05-06' '2017-05-07' '2017-05-08' '2017-05-09' '2017-05-10'\n",
      " '2017-05-11' '2017-05-12' '2017-05-13' '2017-05-14' '2017-05-16'\n",
      " '2017-05-17' '2017-05-19' '2017-05-21' '2008-04-18' '2008-04-19'\n",
      " '2008-04-20' '2008-04-21' '2008-04-22' '2008-04-23' '2008-04-24'\n",
      " '2008-04-25' '2008-04-26' '2008-04-27' '2008-04-28' '2008-04-29'\n",
      " '2008-04-30' '2008-05-01' '2008-05-02' '2008-05-25' '2008-05-03'\n",
      " '2008-05-04' '2008-05-05' '2008-05-06' '2008-05-07' '2008-05-08'\n",
      " '2008-05-09' '2008-05-28' '2008-05-10' '2008-05-11' '2008-05-12'\n",
      " '2008-05-13' '2008-05-14' '2008-05-15' '2008-05-16' '2008-05-17'\n",
      " '2008-05-18' '2008-05-19' '2008-05-20' '2008-05-21' '2008-05-23'\n",
      " '2008-05-24' '2008-05-26' '2008-05-27' '2008-05-30' '2008-05-31'\n",
      " '2008-06-01' '2009-04-18' '2009-04-19' '2009-04-20' '2009-04-21'\n",
      " '2009-04-22' '2009-04-23' '2009-04-24' '2009-04-25' '2009-04-26'\n",
      " '2009-04-27' '2009-04-28' '2009-04-29' '2009-04-30' '2009-05-01'\n",
      " '2009-05-02' '2009-05-03' '2009-05-04' '2009-05-05' '2009-05-06'\n",
      " '2009-05-07' '2009-05-08' '2009-05-09' '2009-05-10' '2009-05-11'\n",
      " '2009-05-12' '2009-05-13' '2009-05-14' '2009-05-15' '2009-05-16'\n",
      " '2009-05-17' '2009-05-18' '2009-05-19' '2009-05-20' '2009-05-21'\n",
      " '2009-05-22' '2009-05-23' '2009-05-24' '2010-03-12' '2010-03-13'\n",
      " '2010-03-14' '2010-03-15' '2010-03-16' '2010-03-17' '2010-03-18'\n",
      " '2010-03-19' '2010-03-20' '2010-03-21' '2010-03-22' '2010-03-23'\n",
      " '2010-03-24' '2010-03-25' '2010-03-26' '2010-03-27' '2010-03-28'\n",
      " '2010-03-29' '2010-03-30' '2010-03-31' '2010-04-01' '2010-04-02'\n",
      " '2010-04-03' '2010-04-04' '2010-04-05' '2010-04-06' '2010-04-07'\n",
      " '2010-04-08' '2010-04-09' '2010-04-10' '2010-04-11' '2010-04-12'\n",
      " '2010-04-13' '2010-04-14' '2010-04-15' '2010-04-16' '2010-04-17'\n",
      " '2010-04-18' '2010-04-19' '2010-04-21' '2010-04-22' '2010-04-24'\n",
      " '2010-04-25' '2011-04-08' '2011-04-09' '2011-04-10' '2011-04-11'\n",
      " '2011-04-12' '2011-04-13' '2011-04-14' '2011-04-15' '2011-04-16'\n",
      " '2011-04-17' '2011-04-18' '2011-04-19' '2011-04-20' '2011-04-21'\n",
      " '2011-04-22' '2011-04-23' '2011-04-24' '2011-04-25' '2011-04-26'\n",
      " '2011-04-27' '2011-04-28' '2011-04-29' '2011-04-30' '2011-05-01'\n",
      " '2011-05-02' '2011-05-03' '2011-05-04' '2011-05-05' '2011-05-06'\n",
      " '2011-05-07' '2011-05-08' '2011-05-09' '2011-05-10' '2011-05-11'\n",
      " '2011-05-12' '2011-05-13' '2011-05-14' '2011-05-15' '2011-05-16'\n",
      " '2011-05-17' '2011-05-18' '2011-05-19' '2011-05-20' '2011-05-21'\n",
      " '2011-05-22' '2011-05-24' '2011-05-25' '2011-05-27' '2011-05-28'\n",
      " '2012-04-04' '2012-04-05' '2012-04-06' '2012-04-07' '2012-04-08'\n",
      " '2012-04-09' '2012-04-10' '2012-04-11' '2012-04-12' '2012-04-13'\n",
      " '2012-04-19' '2012-04-14' '2012-04-15' '2012-04-16' '2012-04-17'\n",
      " '2012-04-18' '2012-05-10' '2012-04-20' '2012-04-21' '2012-04-22'\n",
      " '2012-04-23' '2012-04-24' '2012-04-25' '2012-04-26' '2012-04-27'\n",
      " '2012-04-28' '2012-04-29' '2012-04-30' '2012-05-01' '2012-05-02'\n",
      " '2012-05-03' '2012-05-04' '2012-05-05' '2012-05-06' '2012-05-07'\n",
      " '2012-05-08' '2012-05-09' '2012-05-11' '2012-05-12' '2012-05-13'\n",
      " '2012-05-14' '2012-05-15' '2012-05-16' '2012-05-17' '2012-05-18'\n",
      " '2012-05-19' '2012-05-20' '2012-05-22' '2012-05-23' '2012-05-25'\n",
      " '2012-05-27' '2013-04-03' '2013-04-04' '2013-04-05' '2013-04-06'\n",
      " '2013-04-07' '2013-04-08' '2013-04-09' '2013-04-10' '2013-04-11'\n",
      " '2013-04-12' '2013-04-13' '2013-04-14' '2013-04-15' '2013-04-16'\n",
      " '2013-04-17' '2013-04-18' '2013-04-19' '2013-04-20' '2013-04-21'\n",
      " '2013-04-22' '2013-04-23' '2013-05-16' '2013-04-24' '2013-04-25'\n",
      " '2013-04-26' '2013-04-27' '2013-04-28' '2013-04-29' '2013-04-30'\n",
      " '2013-05-01' '2013-05-02' '2013-05-03' '2013-05-04' '2013-05-14'\n",
      " '2013-05-05' '2013-05-07' '2013-05-08' '2013-05-09' '2013-05-10'\n",
      " '2013-05-11' '2013-05-12' '2013-05-13' '2013-05-15' '2013-05-06'\n",
      " '2013-05-17' '2013-05-18' '2013-05-19' '2013-05-21' '2013-05-22'\n",
      " '2013-05-24' '2013-05-26' '2014-04-16' '2014-04-17' '2014-04-18'\n",
      " '2014-04-19' '2014-04-20' '2014-04-21' '2014-04-22' '2014-04-23'\n",
      " '2014-04-24' '2014-04-25' '2014-04-26' '2014-04-27' '2014-04-28'\n",
      " '2014-04-29' '2014-04-30' '2014-05-02' '2014-05-03' '2014-05-04'\n",
      " '2014-05-05' '2014-05-06' '2014-05-07' '2014-05-08' '2014-05-09'\n",
      " '2014-05-10' '2014-05-11' '2014-05-12' '2014-05-13' '2014-05-14'\n",
      " '2014-05-15' '2014-05-18' '2014-05-19' '2014-05-20' '2014-05-21'\n",
      " '2014-05-22' '2014-05-23' '2014-05-24' '2014-05-25' '2014-05-27'\n",
      " '2014-05-28' '2014-05-30' '2014-06-01' '2015-04-08' '2015-04-09'\n",
      " '2015-04-10' '2015-04-11' '2015-04-12' '2015-04-13' '2015-04-14'\n",
      " '2015-04-30' '2015-04-15' '2015-04-16' '2015-04-17' '2015-04-18'\n",
      " '2015-04-19' '2015-04-20' '2015-04-21' '2015-04-22' '2015-04-23'\n",
      " '2015-04-24' '2015-04-25' '2015-04-26' '2015-04-27' '2015-05-07'\n",
      " '2015-04-29' '2015-04-28' '2015-05-01' '2015-05-02' '2015-05-03'\n",
      " '2015-05-04' '2015-05-05' '2015-05-06' '2015-05-08' '2015-05-09'\n",
      " '2015-05-10' '2015-05-11' '2015-05-12' '2015-05-13' '2015-05-14'\n",
      " '2015-05-15' '2015-05-16' '2015-05-17' '2015-05-19' '2015-05-20'\n",
      " '2015-05-22' '2015-05-24' '2016-04-09' '2016-04-10' '2016-04-11'\n",
      " '2016-04-12' '2016-04-13' '2016-04-14' '2016-04-15' '2016-04-16'\n",
      " '2016-04-17' '2016-04-18' '2016-04-19' '2016-04-20' '2016-04-21'\n",
      " '2016-04-22' '2016-04-23' '2016-04-24' '2016-04-25' '2016-04-26'\n",
      " '2016-04-27' '2016-04-28' '2016-04-29' '2016-04-30' '2016-05-01'\n",
      " '2016-05-02' '2016-05-03' '2016-05-04' '2016-05-05' '2016-05-06'\n",
      " '2016-05-07' '2016-05-08' '2016-05-09' '2016-05-10' '2016-05-11'\n",
      " '2016-05-12' '2016-05-13' '2016-05-14' '2016-05-15' '2016-05-16'\n",
      " '2016-05-17' '2016-05-18' '2016-05-19' '2016-05-20' '2016-05-21'\n",
      " '2016-05-22' '2016-05-24' '2016-05-25' '2016-05-27' '2016-05-29'\n",
      " '07/04/18' '08/04/18' '09/04/18' '10/04/18' '11/04/18' '12/04/18'\n",
      " '13/04/18' '14/04/18' '15/04/18' '16/04/18' '17/04/18' '18/04/18'\n",
      " '19/04/18' '20/04/18' '21/04/18' '22/04/18' '23/04/18' '24/04/18'\n",
      " '25/04/18' '26/04/18' '27/04/18' '28/04/18' '29/04/18' '30/04/18'\n",
      " '01/05/18' '02/05/18' '03/05/18' '04/05/18' '05/05/18' '06/05/18'\n",
      " '07/05/18' '08/05/18' '09/05/18' '10/05/18' '11/05/18' '12/05/18'\n",
      " '13/05/18' '14/05/18' '15/05/18' '16/05/18' '17/05/18' '18/05/18'\n",
      " '19/05/18' '20/05/18' '22/05/18' '23/05/18' '25/05/18' '27/05/18'\n",
      " '23/03/19' '24/03/19' '25/03/19' '26/03/19' '27/03/19' '28/03/19'\n",
      " '29/03/19' '30/03/19' '31/03/19' '01/04/19' '02/04/19' '03/04/19'\n",
      " '04/04/19' '05/04/19' '06/04/19' '07/04/19' '08/04/19' '09/04/19'\n",
      " '10/04/19' '11/04/19' '12/04/19' '13/04/19' '14/04/19' '15/04/19'\n",
      " '16/04/19' '17/04/19' '18/04/19' '19/04/19' '20/04/19' '21/04/19'\n",
      " '22/04/19' '23/04/19' '24/04/19' '25/04/19' '26/04/19' '27/04/19'\n",
      " '28/04/19' '29/04/19' '30/04/19' '01/05/19' '02/05/19' '03/05/19'\n",
      " '04/05/19' '05/05/19' '07/05/19' '08/05/19' '10/05/19' '12/05/19']\n",
      "['Sunrisers Hyderabad' 'Mumbai Indians' 'Gujarat Lions'\n",
      " 'Rising Pune Supergiant' 'Royal Challengers Bangalore'\n",
      " 'Kolkata Knight Riders' 'Delhi Daredevils' 'Kings XI Punjab'\n",
      " 'Chennai Super Kings' 'Rajasthan Royals' 'Deccan Chargers'\n",
      " 'Kochi Tuskers Kerala' 'Pune Warriors' 'Rising Pune Supergiants'\n",
      " 'Delhi Capitals']\n",
      "['Royal Challengers Bangalore' 'Rising Pune Supergiant'\n",
      " 'Kolkata Knight Riders' 'Kings XI Punjab' 'Delhi Daredevils'\n",
      " 'Sunrisers Hyderabad' 'Mumbai Indians' 'Gujarat Lions' 'Rajasthan Royals'\n",
      " 'Chennai Super Kings' 'Deccan Chargers' 'Pune Warriors'\n",
      " 'Kochi Tuskers Kerala' 'Rising Pune Supergiants' 'Delhi Capitals']\n",
      "['Royal Challengers Bangalore' 'Rising Pune Supergiant'\n",
      " 'Kolkata Knight Riders' 'Kings XI Punjab' 'Sunrisers Hyderabad'\n",
      " 'Mumbai Indians' 'Gujarat Lions' 'Delhi Daredevils' 'Chennai Super Kings'\n",
      " 'Rajasthan Royals' 'Deccan Chargers' 'Kochi Tuskers Kerala'\n",
      " 'Pune Warriors' 'Rising Pune Supergiants' 'Delhi Capitals']\n",
      "['field' 'bat']\n",
      "['normal' 'tie' 'no result']\n",
      "[0 1]\n",
      "['Sunrisers Hyderabad' 'Rising Pune Supergiant' 'Kolkata Knight Riders'\n",
      " 'Kings XI Punjab' 'Royal Challengers Bangalore' 'Mumbai Indians'\n",
      " 'Delhi Daredevils' 'Gujarat Lions' 'Chennai Super Kings'\n",
      " 'Rajasthan Royals' 'Deccan Chargers' 'Pune Warriors'\n",
      " 'Kochi Tuskers Kerala' nan 'Rising Pune Supergiants' 'Delhi Capitals']\n",
      "[ 35   0  15  97  17  51  27   5  21  14  26  82   3  61  48  19  12 146\n",
      "   7   9  10  20   1 140  33   6  66  13  45  29  18  23  41  65  25 105\n",
      "  75  92  11  24  38   8  78  16  53   2   4  31  55  98  34  36  39  40\n",
      "  67  63  37  57  22  85  32  76 111  43  58  28  74  42  59  46  47  86\n",
      "  44  87 130  60  77  30  50  93  72  62 138  71 144  80  64 102 118]\n",
      "[ 0  7 10  6  9  4  8  5  2  3  1]\n",
      "['Yuvraj Singh' 'SPD Smith' 'CA Lynn' 'GJ Maxwell' 'KM Jadhav'\n",
      " 'Rashid Khan' 'N Rana' 'AR Patel' 'SV Samson' 'JJ Bumrah' 'SP Narine'\n",
      " 'KA Pollard' 'AJ Tye' 'RV Uthappa' 'CJ Anderson' 'BA Stokes'\n",
      " 'NM Coulter-Nile' 'B Kumar' 'CH Gayle' 'KS Williamson' 'JC Buttler'\n",
      " 'SK Raina' 'MJ McClenaghan' 'MS Dhoni' 'HM Amla' 'G Gambhir'\n",
      " 'LH Ferguson' 'KH Pandya' 'Sandeep Sharma' 'DA Warner' 'RG Sharma'\n",
      " 'Mohammed Shami' 'RA Tripathi' 'RR Pant' 'JD Unadkat' 'LMP Simmons'\n",
      " 'DR Smith' 'S Dhawan' 'MM Sharma' 'SS Iyer' 'WP Saha' 'KK Nair'\n",
      " 'Mohammed Siraj' 'AT Rayudu' 'HV Patel' 'Washington Sundar' 'KV Sharma'\n",
      " 'BB McCullum' 'MEK Hussey' 'MF Maharoof' 'MV Boucher' 'DJ Hussey'\n",
      " 'SR Watson' 'V Sehwag' 'ML Hayden' 'YK Pathan' 'KC Sangakkara' 'JDP Oram'\n",
      " 'AC Gilchrist' 'SM Katich' 'ST Jayasuriya' 'GD McGrath' 'SE Marsh'\n",
      " 'SA Asnodkar' 'R Vinay Kumar' 'IK Pathan' 'SM Pollock' 'Sohail Tanvir'\n",
      " 'S Sreesanth' 'A Nehra' 'SC Ganguly' 'CRD Fernando' 'L Balaji'\n",
      " 'Shoaib Akhtar' 'A Mishra' 'DPMD Jayawardene' 'GC Smith' 'DJ Bravo'\n",
      " 'M Ntini' 'SP Goswami' 'A Kumble' 'KD Karthik' 'JA Morkel' 'P Kumar'\n",
      " 'Umar Gul' 'SR Tendulkar' 'R Dravid' 'DL Vettori' 'RP Singh'\n",
      " 'M Muralitharan' 'AB de Villiers' 'RS Bopara' 'PP Ojha' 'TM Dilshan'\n",
      " 'HH Gibbs' 'DP Nannes' 'JP Duminy' 'SB Jakati' 'JH Kallis' 'A Singh'\n",
      " 'S Badrinath' 'LRPL Taylor' 'Harbhajan Singh' 'R Bhatia' 'SK Warne'\n",
      " 'B Lee' 'BJ Hodge' 'LR Shukla' 'MK Pandey' 'AD Mathews' 'MK Tiwary'\n",
      " 'WPUJC Vaas' 'A Symonds' 'AA Jhunjhunwala' 'J Theron' 'AC Voges'\n",
      " 'NV Ojha' 'SL Malinga' 'M Vijay' 'KP Pietersen' 'PD Collingwood'\n",
      " 'MJ Lumb' 'TL Suman' 'RJ Harris' 'PP Chawla' 'Harmeet Singh' 'R Ashwin'\n",
      " 'R McLaren' 'M Kartik' 'DE Bollinger' 'S Anirudha' 'SK Trivedi' 'SB Wagh'\n",
      " 'PC Valthaty' 'MD Mishra' 'DW Steyn' 'S Sohal' 'MM Patel' 'V Kohli'\n",
      " 'I Sharma' 'J Botha' 'Iqbal Abdulla' 'P Parameswaran' 'R Sharma'\n",
      " 'MR Marsh' 'BA Bhatt' 'S Aravind' nan 'JEC Franklin' 'RE Levi'\n",
      " 'AM Rahane' 'RA Jadeja' 'MN Samuels' 'M Morkel' 'F du Plessis'\n",
      " 'AD Mascarenhas' 'Shakib Al Hasan' 'JD Ryder' 'S Nadeem'\n",
      " 'KMDN Kulasekara' 'CL White' 'Mandeep Singh' 'P Negi' 'Azhar Mahmood'\n",
      " 'BW Hilfenhaus' 'A Chandila' 'UT Yadav' 'MS Bisla' 'M Vohra' 'GH Vihari'\n",
      " 'AJ Finch' 'JP Faulkner' 'MS Gony' 'DA Miller' 'DJG Sammy' 'MG Johnson'\n",
      " 'KK Cooper' 'PA Patel' 'AP Tare' 'LJ Wright' 'YS Chahal' 'PV Tambe'\n",
      " 'DJ Hooda' 'GJ Bailey' 'AD Russell' 'MA Agarwal' 'MA Starc' 'VR Aaron'\n",
      " 'TA Boult' 'EJG Morgan' 'HH Pandya' 'MC Henriques' 'Z Khan' 'Q de Kock'\n",
      " 'Mustafizur Rahman' 'SA Yadav' 'AB Dinda' 'CH Morris' 'CR Brathwaite'\n",
      " 'MP Stoinis' 'A Zampa' 'BCJ Cutting' 'KL Rahul' 'SW Billings' 'JJ Roy'\n",
      " 'B Stanlake' 'J Archer' 'AS Rajpoot' 'TG Southee' 'AS Yadav'\n",
      " 'M Ur Rahman' 'Ishan Kishan' 'Kuldeep Yadav' 'S Gopal' 'L Ngidi' 'P Shaw'\n",
      " 'J Bairstow' 'S Curran' 'A Joseph' 'K Rabada' 'H Gurney' 'DL Chahar'\n",
      " 'Imran Tahir' 'K Paul' 'K Ahmed' 'S Gill' 'S Hetmyer']\n",
      "['Rajiv Gandhi International Stadium, Uppal'\n",
      " 'Maharashtra Cricket Association Stadium'\n",
      " 'Saurashtra Cricket Association Stadium' 'Holkar Cricket Stadium'\n",
      " 'M Chinnaswamy Stadium' 'Wankhede Stadium' 'Eden Gardens'\n",
      " 'Feroz Shah Kotla' 'Punjab Cricket Association IS Bindra Stadium, Mohali'\n",
      " 'Green Park' 'Punjab Cricket Association Stadium, Mohali'\n",
      " 'Sawai Mansingh Stadium' 'MA Chidambaram Stadium, Chepauk'\n",
      " 'Dr DY Patil Sports Academy' 'Newlands' \"St George's Park\" 'Kingsmead'\n",
      " 'SuperSport Park' 'Buffalo Park' 'New Wanderers Stadium'\n",
      " 'De Beers Diamond Oval' 'OUTsurance Oval' 'Brabourne Stadium'\n",
      " 'Sardar Patel Stadium, Motera' 'Barabati Stadium'\n",
      " 'Vidarbha Cricket Association Stadium, Jamtha'\n",
      " 'Himachal Pradesh Cricket Association Stadium' 'Nehru Stadium'\n",
      " 'Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium'\n",
      " 'Subrata Roy Sahara Stadium'\n",
      " 'Shaheed Veer Narayan Singh International Stadium'\n",
      " 'JSCA International Stadium Complex' 'Sheikh Zayed Stadium'\n",
      " 'Sharjah Cricket Stadium' 'Dubai International Cricket Stadium'\n",
      " 'M. A. Chidambaram Stadium' 'Feroz Shah Kotla Ground'\n",
      " 'M. Chinnaswamy Stadium' 'Rajiv Gandhi Intl. Cricket Stadium'\n",
      " 'IS Bindra Stadium' 'ACA-VDCA Stadium']\n",
      "['AY Dandekar' 'A Nand Kishore' 'Nitin Menon' 'AK Chaudhary' nan\n",
      " 'A Deshmukh' 'KN Ananthapadmanabhan' 'YC Barde' 'S Ravi' 'CB Gaffaney'\n",
      " 'M Erasmus' 'NJ Llong' 'CK Nandan' 'Asad Rauf' 'MR Benson' 'Aleem Dar'\n",
      " 'SJ Davis' 'BF Bowden' 'IL Howell' 'DJ Harper' 'RE Koertzen'\n",
      " 'BR Doctrove' 'AV Jayaprakash' 'BG Jerling' 'HDPK Dharmasena' 'S Asnani'\n",
      " 'GAV Baxter' 'SS Hazare' 'K Hariharan' 'SL Shastri' 'SK Tarapore'\n",
      " 'SJA Taufel' 'S Das' 'AM Saheba' 'PR Reiffel' 'JD Cloete' 'VA Kulkarni'\n",
      " 'BNJ Oxenford' 'C Shamshuddin' 'RK Illingworth' 'RM Deshpande'\n",
      " 'K Srinath' 'SD Fry' 'PG Pathak' 'K Bharatan' 'Chris Gaffaney'\n",
      " 'Rod Tucker' 'Nigel Llong' 'Anil Chaudhary' 'K Ananthapadmanabhan'\n",
      " 'O Nandan' 'A Nanda Kishore' 'Vineet Kulkarni' 'Bruce Oxenford'\n",
      " 'Marais Erasmus' 'Kumar Dharmasena' 'Anil Dandekar' 'Yeshwant Barde'\n",
      " 'Ian Gould' 'Ulhas Gandhe' 'Nanda Kishore' 'Sundaram Ravi']\n",
      "['NJ Llong' 'S Ravi' 'CK Nandan' 'C Shamshuddin' nan 'AK Chaudhary'\n",
      " 'Nitin Menon' 'A Deshmukh' 'VK Sharma' 'M Erasmus' 'CB Gaffaney'\n",
      " 'A Nand Kishore' 'RE Koertzen' 'SL Shastri' 'GA Pratapkumar' 'DJ Harper'\n",
      " 'K Hariharan' 'RB Tiffin' 'AM Saheba' 'MR Benson' 'IL Howell'\n",
      " 'AV Jayaprakash' 'I Shivram' 'BR Doctrove' 'BG Jerling' 'SJ Davis'\n",
      " 'SD Ranade' 'SJA Taufel' 'TH Wijewardene' 'SK Tarapore' 'HDPK Dharmasena'\n",
      " 'SS Hazare' 'PR Reiffel' 'AL Hill' 'RJ Tucker' 'VA Kulkarni' 'JD Cloete'\n",
      " 'BNJ Oxenford' 'S Asnani' 'S Das' 'K Srinath' 'Subroto Das'\n",
      " 'RK Illingworth' 'PG Pathak' 'K Srinivasan' 'SD Fry' 'A Nanda Kishore'\n",
      " 'K Ananthapadmanabhan' 'A.D Deshmukh' 'Vineet Kulkarni' 'Chris Gaffaney'\n",
      " 'Rod Tucker' 'Nigel Llong' 'Anil Chaudhary' 'O Nandan'\n",
      " 'Virender Kumar Sharma' 'Yeshwant Barde' 'Anil Dandekar'\n",
      " 'Kumar Dharmasena' 'KN Anantapadmanabhan' 'Ulhas Gandhe' 'Nanda Kishore'\n",
      " 'Bruce Oxenford' 'Nand Kishore' 'KN Ananthapadmanabhan' 'Ian Gould']\n",
      "[nan 'Anil Chaudhary' 'Nitin Menon' 'S Ravi' 'O Nandan' 'A Nanda Kishore'\n",
      " 'Vineet Kulkarni' 'C Shamshuddin' 'Rod Tucker' 'Chris Gaffaney'\n",
      " 'A.D Deshmukh' 'Nigel Llong' 'K Ananthapadmanabhan' 'Anil Dandekar'\n",
      " 'Virender Kumar Sharma' 'Yeshwant Barde' 'Bruce Oxenford'\n",
      " 'Marais Erasmus' 'Kumar Dharmasena' 'KN Anantapadmanabhan' 'Ulhas Gandhe'\n",
      " 'Nanda Kishore' 'Ian Gould' 'Sundaram Ravi' 'KN Ananthapadmanabhan'\n",
      " 'Chettithody Shamshuddin']\n"
     ]
    }
   ],
   "source": [
    "for col in ipl_matches_df:\n",
    "    print(ipl_matches_df[col].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3812af0",
   "metadata": {},
   "source": [
    "The dataset has 18 columns. Let’s get acquainted with the columns.\n",
    "\n",
    "* id: The IPL match id.\n",
    "* season: The IPL season\n",
    "* city: The city where the IPL match was held.\n",
    "* date: The date on which the match was held.\n",
    "* team1: One of the teams of the IPL match\n",
    "* team2: The other team of the IPL match\n",
    "* toss_winner: The team that won the toss\n",
    "* toss_decision: The decision taken by the team that won the toss to ‘bat’ or ‘field’\n",
    "* result: The result(‘normal’, ‘tie’, ‘no result’) of the match.\n",
    "* dl_applied: (1 or 0)indicates whether the Duckworth-Lewis rule was applied or not.\n",
    "* winner: The winner of the match.\n",
    "* win_by_runs: Provides the runs by which the team batting first won\n",
    "* win_by_runs: Provides the number of wickets by which the team batting second won.\n",
    "* player_of_match: The outstanding player of the match.\n",
    "* venue: The venue where the match was hosted.\n",
    "* umpire1: One of the two on-field umpires who officiate the match.\n",
    "* umpire2: One of the two on-field umpires who officiate the match.\n",
    "* umpire3: The off-field umpire who officiates the match"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb85184b",
   "metadata": {},
   "source": [
    "A mere glance of the DataFrame through its columns indicates the presence of NaN values in the ‘umpire3’ column. Let’s see the count of NaN values in the column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2bbad768",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "636"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the first index that doesn't contain a NaN value \n",
    "ipl_matches_df.umpire3.first_valid_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a6ea3bc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>634</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2016-05-25</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>MC Henriques</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>635</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2016-05-27</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>636</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>636</th>\n",
       "      <td>7894</td>\n",
       "      <td>2018</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>07/04/18</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>DJ Bravo</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chris Gaffaney</td>\n",
       "      <td>A Nanda Kishore</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>637</th>\n",
       "      <td>7895</td>\n",
       "      <td>2018</td>\n",
       "      <td>Mohali</td>\n",
       "      <td>08/04/18</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>KL Rahul</td>\n",
       "      <td>Punjab Cricket Association IS Bindra Stadium, ...</td>\n",
       "      <td>Rod Tucker</td>\n",
       "      <td>K Ananthapadmanabhan</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>638</th>\n",
       "      <td>7896</td>\n",
       "      <td>2018</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>08/04/18</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>SP Narine</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>A.D Deshmukh</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>639</th>\n",
       "      <td>7897</td>\n",
       "      <td>2018</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>09/04/18</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Vineet Kulkarni</td>\n",
       "      <td>O Nandan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>640</th>\n",
       "      <td>7898</td>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>10/04/18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>SW Billings</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "      <td>Chris Gaffaney</td>\n",
       "      <td>A Nanda Kishore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  season       city        date                        team1  \\\n",
       "633   634    2016      Delhi  2016-05-25          Sunrisers Hyderabad   \n",
       "634   635    2016      Delhi  2016-05-27                Gujarat Lions   \n",
       "635   636    2016  Bangalore  2016-05-29          Sunrisers Hyderabad   \n",
       "636  7894    2018     Mumbai    07/04/18               Mumbai Indians   \n",
       "637  7895    2018     Mohali    08/04/18             Delhi Daredevils   \n",
       "638  7896    2018    Kolkata    08/04/18  Royal Challengers Bangalore   \n",
       "639  7897    2018  Hyderabad    09/04/18             Rajasthan Royals   \n",
       "640  7898    2018    Chennai    10/04/18        Kolkata Knight Riders   \n",
       "\n",
       "                           team2            toss_winner toss_decision  result  \\\n",
       "633        Kolkata Knight Riders  Kolkata Knight Riders         field  normal   \n",
       "634          Sunrisers Hyderabad    Sunrisers Hyderabad         field  normal   \n",
       "635  Royal Challengers Bangalore    Sunrisers Hyderabad           bat  normal   \n",
       "636          Chennai Super Kings    Chennai Super Kings         field  normal   \n",
       "637              Kings XI Punjab        Kings XI Punjab         field  normal   \n",
       "638        Kolkata Knight Riders  Kolkata Knight Riders         field  normal   \n",
       "639          Sunrisers Hyderabad    Sunrisers Hyderabad         field  normal   \n",
       "640          Chennai Super Kings    Chennai Super Kings         field  normal   \n",
       "\n",
       "     dl_applied                 winner  win_by_runs  win_by_wickets  \\\n",
       "633           0    Sunrisers Hyderabad           22               0   \n",
       "634           0    Sunrisers Hyderabad            0               4   \n",
       "635           0    Sunrisers Hyderabad            8               0   \n",
       "636           0    Chennai Super Kings            0               1   \n",
       "637           0        Kings XI Punjab            0               6   \n",
       "638           0  Kolkata Knight Riders            0               4   \n",
       "639           0    Sunrisers Hyderabad            0               9   \n",
       "640           0    Chennai Super Kings            0               5   \n",
       "\n",
       "    player_of_match                                              venue  \\\n",
       "633    MC Henriques                                   Feroz Shah Kotla   \n",
       "634       DA Warner                                   Feroz Shah Kotla   \n",
       "635     BCJ Cutting                              M Chinnaswamy Stadium   \n",
       "636        DJ Bravo                                   Wankhede Stadium   \n",
       "637        KL Rahul  Punjab Cricket Association IS Bindra Stadium, ...   \n",
       "638       SP Narine                                       Eden Gardens   \n",
       "639        S Dhawan          Rajiv Gandhi International Stadium, Uppal   \n",
       "640     SW Billings                    MA Chidambaram Stadium, Chepauk   \n",
       "\n",
       "             umpire1               umpire2          umpire3  \n",
       "633        M Erasmus         C Shamshuddin              NaN  \n",
       "634        M Erasmus             CK Nandan              NaN  \n",
       "635  HDPK Dharmasena          BNJ Oxenford              NaN  \n",
       "636   Chris Gaffaney       A Nanda Kishore   Anil Chaudhary  \n",
       "637       Rod Tucker  K Ananthapadmanabhan      Nitin Menon  \n",
       "638    C Shamshuddin          A.D Deshmukh           S Ravi  \n",
       "639      Nigel Llong       Vineet Kulkarni         O Nandan  \n",
       "640   Anil Chaudhary        Chris Gaffaney  A Nanda Kishore  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Confirming the first valid index\n",
    "ipl_matches_df.loc[633:640]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c01d26c6",
   "metadata": {},
   "source": [
    "It’s imperative to know the count of NaN values for each column before we proceed further."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "18cbe17a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                   0\n",
       "season               0\n",
       "city                 7\n",
       "date                 0\n",
       "team1                0\n",
       "team2                0\n",
       "toss_winner          0\n",
       "toss_decision        0\n",
       "result               0\n",
       "dl_applied           0\n",
       "winner               4\n",
       "win_by_runs          0\n",
       "win_by_wickets       0\n",
       "player_of_match      4\n",
       "venue                0\n",
       "umpire1              2\n",
       "umpire2              2\n",
       "umpire3            637\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_matches_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c71e6d7b",
   "metadata": {},
   "source": [
    "The column ‘umpire3’ has a significant number of NaN values. As the off-field umpire parameter is insignificant, we can drop this column. The other columns that have Nan values are of type object(Pandas equivalent of Python String data type) and are very few in number(<=7)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3db81fc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ipl_matches_df = ipl_matches_df.drop(columns=['umpire3'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "027f0789",
   "metadata": {},
   "source": [
    "## Exploratory Analysis and Visualization\n",
    "\n",
    "Now that our data set has been cleaned up, it’s time to do the in-depth analysis and visualization.\n",
    "\n",
    "Let’s begin by importingmatplotlib.pyplot and seaborn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fb5355f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "sns.color_palette(\"Paired\")\n",
    "matplotlib.rcParams['font.size'] = 14\n",
    "matplotlib.rcParams['figure.figsize'] = (12, 8)\n",
    "matplotlib.rcParams['figure.facecolor'] = '#00000000'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0c7e611",
   "metadata": {},
   "source": [
    "### The team with the most number of wins per season.\n",
    "\n",
    "Each IPL season has a fair share of excitement and adulation. No team other than Chennai Super Kings(in 2010 and 2011) was able to win the IPL trophy in succession. That is a testimony to the unpredictability of IPL.\n",
    "\n",
    "Let’s analyze the team with the most wins in each season."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9a70fbd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "season  winner                     \n",
       "2008    Rajasthan Royals               13\n",
       "        Kings XI Punjab                10\n",
       "        Chennai Super Kings             9\n",
       "        Delhi Daredevils                7\n",
       "        Mumbai Indians                  7\n",
       "                                       ..\n",
       "2019    Kings XI Punjab                 6\n",
       "        Kolkata Knight Riders           6\n",
       "        Sunrisers Hyderabad             6\n",
       "        Rajasthan Royals                5\n",
       "        Royal Challengers Bangalore     5\n",
       "Name: winner, Length: 100, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teams_per_season = ipl_matches_df.groupby('season')['winner'].value_counts()\n",
    "teams_per_season"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "79673076",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "((2008, 'Rajasthan Royals'), 13)\n",
      "((2009, 'Delhi Daredevils'), 10)\n",
      "((2010, 'Mumbai Indians'), 11)\n",
      "((2011, 'Chennai Super Kings'), 11)\n",
      "((2012, 'Kolkata Knight Riders'), 12)\n",
      "((2013, 'Mumbai Indians'), 13)\n",
      "((2014, 'Kings XI Punjab'), 12)\n",
      "((2015, 'Chennai Super Kings'), 10)\n",
      "((2016, 'Sunrisers Hyderabad'), 11)\n",
      "((2017, 'Mumbai Indians'), 12)\n",
      "((2018, 'Chennai Super Kings'), 11)\n",
      "((2019, 'Mumbai Indians'), 11)\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "for i, v in win_per_season.iteritems():\n",
    "    print(i, v)\n",
    "    \n",
    "for items in win_per_season.iteritems():\n",
    "    print(items)    \n",
    "\"\"\"\n",
    "year = 2008\n",
    "win_per_season_df = pd.DataFrame(columns=['year', 'team', 'wins'])\n",
    "for items in teams_per_season.iteritems():    \n",
    "    if items[0][0]==year:\n",
    "        print(items)\n",
    "        win_series = pd.DataFrame({\n",
    "            'year': [items[0][0]],\n",
    "            'team': [items[0][1]],\n",
    "            'wins': [items[1]]\n",
    "        })\n",
    "        win_per_season_df = win_per_season_df.append(win_series)\n",
    "        year += 1   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "79a289f5",
   "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>year</th>\n",
       "      <th>team</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year                   team wins\n",
       "0  2008       Rajasthan Royals   13\n",
       "0  2009       Delhi Daredevils   10\n",
       "0  2010         Mumbai Indians   11\n",
       "0  2011    Chennai Super Kings   11\n",
       "0  2012  Kolkata Knight Riders   12\n",
       "0  2013         Mumbai Indians   13\n",
       "0  2014        Kings XI Punjab   12\n",
       "0  2015    Chennai Super Kings   10\n",
       "0  2016    Sunrisers Hyderabad   11\n",
       "0  2017         Mumbai Indians   12\n",
       "0  2018    Chennai Super Kings   11\n",
       "0  2019         Mumbai Indians   11"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_per_season_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea72d6f6",
   "metadata": {},
   "source": [
    "The number of wins is a discrete value. Hence, we will plot a bar chart(barplot in Seaborn)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aabb55a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot('wins', 'team', hue='year', data=win_per_season_df, palette='Paired');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8525437a",
   "metadata": {},
   "source": [
    "From the barplot, we can easily make inferences regarding the year in which a particular team has scored the maximum wins(and also the number of wins).\n",
    "\n",
    "### Observations:\n",
    "\n",
    "* Mumbai Indians has secured the most wins in four seasons(2010, 2013, 2017, and 2019).\n",
    "\n",
    "### The venue that hosted the maximum number of matches\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6724f3f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "venue_ser = ipl_matches_df['venue'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8d6dc737",
   "metadata": {},
   "outputs": [],
   "source": [
    "venue_df = pd.DataFrame(columns=['venue', 'matches'])\n",
    "for items in venue_ser.iteritems():\n",
    "    temp_df = pd.DataFrame({\n",
    "        'venue':[items[0]],\n",
    "        'matches':[items[1]]\n",
    "    })\n",
    "    venue_df = venue_df.append(temp_df, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c6726439",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"IPL Venues\")\n",
    "sns.barplot(x='matches', y='venue', data=venue_df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7b2a222e",
   "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>venue</th>\n",
       "      <th>matches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Sawai Mansingh Stadium</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Subrata Roy Sahara Stadium</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Kingsmead</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Punjab Cricket Association IS Bindra Stadium, ...</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SuperSport Park</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Brabourne Stadium</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Himachal Pradesh Cricket Association Stadium</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>New Wanderers Stadium</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Feroz Shah Kotla Ground</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Barabati Stadium</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>M. Chinnaswamy Stadium</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>St George's Park</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Newlands</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>JSCA International Stadium Complex</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>IS Bindra Stadium</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Shaheed Veer Narayan Singh International Stadium</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Sharjah Cricket Stadium</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Nehru Stadium</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Green Park</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>De Beers Diamond Oval</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Vidarbha Cricket Association Stadium, Jamtha</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Buffalo Park</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>OUTsurance Oval</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                venue matches\n",
       "0                                        Eden Gardens      77\n",
       "1                               M Chinnaswamy Stadium      73\n",
       "2                                    Wankhede Stadium      73\n",
       "3                                    Feroz Shah Kotla      67\n",
       "4           Rajiv Gandhi International Stadium, Uppal      56\n",
       "5                     MA Chidambaram Stadium, Chepauk      49\n",
       "6                              Sawai Mansingh Stadium      47\n",
       "7          Punjab Cricket Association Stadium, Mohali      35\n",
       "8             Maharashtra Cricket Association Stadium      21\n",
       "9                          Subrata Roy Sahara Stadium      17\n",
       "10                         Dr DY Patil Sports Academy      17\n",
       "11                                          Kingsmead      15\n",
       "12  Punjab Cricket Association IS Bindra Stadium, ...      14\n",
       "13                                    SuperSport Park      12\n",
       "14                       Sardar Patel Stadium, Motera      12\n",
       "15  Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...      11\n",
       "16                                  Brabourne Stadium      11\n",
       "17             Saurashtra Cricket Association Stadium      10\n",
       "18                             Holkar Cricket Stadium       9\n",
       "19       Himachal Pradesh Cricket Association Stadium       9\n",
       "20                 Rajiv Gandhi Intl. Cricket Stadium       8\n",
       "21                          M. A. Chidambaram Stadium       8\n",
       "22                              New Wanderers Stadium       8\n",
       "23                            Feroz Shah Kotla Ground       7\n",
       "24                                   Barabati Stadium       7\n",
       "25                             M. Chinnaswamy Stadium       7\n",
       "26                                   St George's Park       7\n",
       "27                                           Newlands       7\n",
       "28                 JSCA International Stadium Complex       7\n",
       "29                               Sheikh Zayed Stadium       7\n",
       "30                Dubai International Cricket Stadium       7\n",
       "31                                  IS Bindra Stadium       7\n",
       "32   Shaheed Veer Narayan Singh International Stadium       6\n",
       "33                            Sharjah Cricket Stadium       6\n",
       "34                                      Nehru Stadium       5\n",
       "35                                         Green Park       4\n",
       "36                              De Beers Diamond Oval       3\n",
       "37       Vidarbha Cricket Association Stadium, Jamtha       3\n",
       "38                                       Buffalo Park       3\n",
       "39                                    OUTsurance Oval       2\n",
       "40                                   ACA-VDCA Stadium       2"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venue_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f0f7b4",
   "metadata": {},
   "source": [
    "### Observations:\n",
    "\n",
    "* Eden Gardens has hosted the maximum number of IPL matches followed by Wankhede Stadium and M Chinnaswamy Stadium.\n",
    "* Till 2019, IPL matches were hosted by 40 venues."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3d3c26f",
   "metadata": {},
   "source": [
    "### The most successful IPL team\n",
    "\n",
    "In a game of sports, every team competes for victory. Hence, the team that has registered the most number of victories is the most successful.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "39bed5e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "team_wins_ser = ipl_matches_df['winner'].value_counts()\n",
    "\n",
    "team_wins_df = pd.DataFrame(columns=[\"team\", \"wins\"])\n",
    "for items in team_wins_ser.iteritems():\n",
    "    temp_df1 = pd.DataFrame({\n",
    "        'team':[items[0]],\n",
    "        'wins':[items[1]]\n",
    "    })\n",
    "    team_wins_df = team_wins_df.append(temp_df1, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a81ab84f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           team wins\n",
       "0                Mumbai Indians  109\n",
       "1           Chennai Super Kings  100\n",
       "2         Kolkata Knight Riders   92\n",
       "3   Royal Challengers Bangalore   84\n",
       "4               Kings XI Punjab   82\n",
       "5              Rajasthan Royals   75\n",
       "6              Delhi Daredevils   67\n",
       "7           Sunrisers Hyderabad   58\n",
       "8               Deccan Chargers   29\n",
       "9                 Gujarat Lions   13\n",
       "10                Pune Warriors   12\n",
       "11       Rising Pune Supergiant   10\n",
       "12               Delhi Capitals   10\n",
       "13         Kochi Tuskers Kerala    6\n",
       "14      Rising Pune Supergiants    5"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_wins_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a21b79cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dLnVHJLlknM8HFl/FxHXP5sm0FaKfCpyZ5Iwkv0tyCm2uwV/S3l3/gjFfog3NngP8Nsk/kpxEG5a7A7PTA+/htN/dZd09HNf9Pfwb2Ib2f092m4V2SdKsMsCTJEkSVfUWWgDwQ9r/j/gQWu+xI4DHVNWeY5z6UuCztP/gvz+wbfdZvav3fOARwNeB/9LmSVudttrlQ4BTl8Dt3KKq5gPf69s12cUr+uu6iNbD6TW0nkurAg+mPa95tF5+/xg4bdzn09X7C+ABfeXuR+v5dCJt+PJWVXXpVNu9mHvah/YevtRde5Pu+jfQhrfuCry475R/AK8AvkFbifbu3fkrAz+l3e+zJzNEuesNuANtVdvf0hbGeCCtZ+KXgAdW1UwOH14a5tDmAhzrc6eZvmBVnUBbEXgP4HfddTan/dZOBvajLQhxTt85VwKPpq3SfAGwAW3RkO/RgrRjZ7qdE/AW4OO0Xnar0oaQ3x34K/Bh4AFVddqYZ0vSciqTn/5DkiRJkiRJ0tJiDzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwJMkSZIkSZJGmAGeJEmSJEmSNMJWnO0GSNKoSBJgPeCK2W6LJEmSJOk2YzXg/KqqsQoY4EnSrdYDzp3tRkiSJEmSbnPuBpw31kEDPEm61RUA//73v5kzZ85st0WSJEmStJxbsGABd7/73WExI8EM8CRpwJw5cwzwJEmSJEkjw0UsJEmSJEmSpBFmDzxJGvCDP57JqndabbabIUmSJEmapGduvvFsN2GJsAeeJEmSJEmSNMIM8CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYAZ40A5LsnKSS7LwEr1FJ5i2p+icryV5dm7br27dBt++gWWuYJEmSJEnLGQM8jYS+4KeSnJdkhTHKPaCv3GlLu53Lir5AcffZboskSZIkSZqeFWe7AdKAG4H1gCcARw05/oquzG3xt3tf4OrZbsRinEdr5/zZbogkSZIkScsLe+Bp1PyWFv7sMnggycrAixge7C33quq0qvrXbLdjPFV1Q9fOC2a7LZIkSZIkLS8M8DRqrgEOBZ6aZK2BY08D1gK+MuzEJAd1w0Y3GHJs2Hxt23X79kryqCQ/T3JFkouTfD7JHbpyT0zymyRXJbkwyUfGGuLblX9mkt8nuTrJf5L8vyRrjFHukCRndGXnJ/lVkmePUe+058BLcnb3uWOST3TDla9L8uckO41xzt27dl6W5Mokv0iyzRhlh86Bl2TzJJ9Ncmp3n9ckOSXJ7klWmm47k8xNsneSv3ZtnJ/ktCRfSXL3KT4uSZIkSZJGggGeRtGBQK+3Xb9dgIuAH87w9R4BHEvr+fcF4F/A64ADkjwHOAz4d3fscuAdwFhzy+0EfBP4O/Ap4J/Aa4Gf9wLBPvsC9wN+3ZX9NrAJ8J0ku87QvQ2zEvBj4Em0e/sasBHwrSSP7y+Y5K7A74DnAycAnwYuA34CbDmJa74KeCZwCu05fhkI7Rl8czrtTBLgGOC9Xdu+CBwAnNpdc6NJtFOSJEmSpJFzW5xHTCOuqo5P8hdaYPcpgCTrA48H/reqbmyZzYx5IvCMqjqiu9ZKwInAC2lz8W1bVb/vju0JnAG8NclHqurGgbp2BB5bVcf2diQ5EHg58HZgn76yT66qf/afnOROtGHE+yT5clUtiTnv1gN+D2xfVdd31/0G8FPgbbTQrGdfYH3gPVX1wb52vpoWxE3UvsAbquqmvjoCfAnYJclWVfWbKbbz/rQQ9ntV9az+CpKsQgsCh+qOr9K3a7VJ3JMkSZIkSUuFPfA0qr4CPDDJ5t33nYEVaL3zZtq8XngHbR434Du0HmI/6IV33bEraD0A1wTuNqSun/SHd533ADcAL+vfORjedfuuBA4C5gJbTOVmJuitvVCsu+6xwDn91+zmHHwerdfjxwfO/xLwj4lerKrO6Q/vun0FfK77+tiptrPPNUOue133TMeyB63nZe9z7jhlJUmSJEmaFQZ4GlVfpYVevcUsdgaOr6q/LoFr/XHIvt4iDH8a59j6Q479anBHVZ0PnAlslOSWHl5J1unmd/tbNwdeJSluDcvWm+gNTNLlVXXWkP3nAqv3fd8EuD1wYlVd21+wqm6m9RSckCQrJ3lbkhOSLEhyc3evf+iKDLvXibbzb7ShuS9M8svuOluMN09hn31pYWnvMyyUlSRJkiRpVjmEViOpqi5KchTwgiTfBzYGPraELrdgyL4bJ3Bs2NDMi8a4xoXApsAc4Iokd6YND70H8BvasNDLgZuABwNPZ+GhnTNp/hj7b2ThUH9utx3vnibqO8BTab32Du3qvIEWxL2Z4fc6oXZ2Q6p3APYCnsWtAeglST4DfHCw91/fudcB1/W+z/DQbEmSJEmSZoQBnkbZgbQg68u04ZGHLKb8zd122O967pB9S8I6Y+y/S7ftBYKvoIV3C80tB5Bkd9p9z7ZegLa4expXki1o4d0xwI4D8+BtSQvwpqWqLgHe2C3+sSmwA7Ar8H5aULjvdK8hSZIkSdJscQitRtlRwH9oQ1W/W1XDesP1+2+3HTa09SEz2bBxPHpwR5L1aCuhntnNoQe3roz6/YnUMUv+DlwLPCzJ7fsPJLkd8KgJ1tO71yOH9ISb0Xut5m9V9Tngcd3up83kNSRJkiRJWtoM8DSyuhVenwY8E3j3BE45sdvu3L8zyU7AtjPauLE9LsljBvZ9gDbc9uC+fed02637CyZ5IfDkJde8iesWj/gWrQfebgOHXwncZ4JVjXWv96MtIjEtSe6VZLMhh3o9BBdZ3EKSJEmSpGWJQ2g10roVYH+/2ILN4cBZwM5J7k5bnOK+tOGUR7F0grEjgaOSfBv4Ny04fCRwMgvP4fdV4J3AZ5JsTwu5HkhbjfUw2lxuo2B34DHAB5Jsza3P9MnAj4HHT6COE7rPc5PcFTiONnz4abTntdM02/gg4HtJfg+cyq29Np9Bm1NwcAVdSZIkSZKWKfbA03Kjqq6hhU1HAA8HXkdbRXUbJh4CTtd3gOfT5mF7C2346BeAHbr29dp6Li3cO5YW2r2GtpDD44EfLKW2LlZVXUAbKnso0Juvbk3a8NTfTbCOm4Cn0OY03Ig2N91mwNuBd8xAM08EPkwL63ak9RbcjhYwPqqqjpyBa0iSJEmSNGtSVbPdBkkaCUnmAPO/Nu8kVr3TarPdHEmSJEnSJD1z841nuwmTsmDBAubOnQswd7y5/+2BJ0mSJEmSJI0wAzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwJMkSZIkSZJGmAGeJEmSJEmSNMIM8CRJkiRJkqQRtuJsN0CSRs1TH7IRc+bMme1mSJIkSZIE2ANPkiRJkiRJGmkGeJIkSZIkSdIIM8CTJEmSJEmSRpgBniRJkiRJkjTCDPAkSZIkSZKkEWaAJ0mSJEmSJI0wAzxJkiRJkiRphK042w2QpFGzzXsOYYVV7jDbzZAkSZKkhfxhv5fOdhM0S+yBJ0mSJEmSJI0wAzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwJMkSZIkSZJGmAGeJEmSJEmSNMIM8CRJkiRJkqQRZoB3G5fkoCSVZIPZbsvSkuTsJGfPdjuWR0l27n5PO892WyRJkiRJWl4Y4C2Hkmye5MtJTk9yVZJrkpyZ5KtJHjfb7VvWJFkzyYeT/CXJ1d3nnCTHJtkzyV1mu41LShfGnTbGsRcmuSHJJUm2WNptkyRJkiTptmLF2W6AZk6S2wEfA94K3Aj8DPg+cAOwIbAj8OIk76uqfWatobPvMRMtmORuwG+BuwN/Ar4CXAlsADwI2Av4DXDhDLdxpCV5PfBZ4Hzg8VX11+7Q94DjgAtmq22SJEmSJC1vDPCWLx+ghXd/AnaqqjP7Dya5A/BGYM2l37TRMfhcFuP9tPBuaOiZ5AHA5TPUtGVCknfTfmtnAI+tqnN6x6pqPjB/ttomSZIkSdLyyCG0y4kkGwPvAC4FnjgspKqqa6pqP2DPMep4fZK/Jbm2GyK6Z9erb1jZp3dDSP/blT81yduTrDBQ7pY50ZI8Jsmvu2G9lyY5OMmaA+U36MoflGTDJN/prnFVkp8medCQtmyf5MAkf09yZfc5Mcmrx2j7ZObAe2S3/cywg1V1SlX9e1j7x7h2JZk3sG9et//2ST6a5N/dMz0lyS5jNWyK72DHJL9KcsVk5wFM83FaeHcysHV/eDd4rWH3nWTt7l1d1A3tPi7JdmNc74FJjuraOr/79/0zZN7GJLdL8sokJyS5rBvmfHaSw5NsM5n7lCRJkiRp1BjgLT92BlYAvlBV4w7nrKrrhuzej9bb7DjgC92+vYBhvc4+BBwO3Af4LvB54Nqujm+OcdmnAkcB/wH+H3Am8FLgiDHKbwAcD6wNHAj8hDb09edD5px7J7AN8HvasM6vAWsBX+gCp+m4rNtuPM16JuLbwPO67QHAOsCXk+wxWHCK7+A53TmXdOWPmmjDulDwS8DbgF8D2y7udzbE6rThxg8Evg4cBjwMOCbJ/Qeu96DuOo8HfgR8jvb7/jVwryF170t7ZncGvgF8CvglbZjzDpNspyRJkiRJI8UhtMuPrbrtz6Z4/ubAA6vqAoAk+wCnA7smeX9VXd/tfxywBy1U2amqru72hxYKvTbJs6vquwP1Pw3Yrqp+05VfAfgpsF2SLavquIHy2wK7V9VHeju6Nr0HeDnw4b6yr6uqs/pPTrIiLaB6c5JPVdW/pvZY+Dbt2f4gyeeAecCfqurKKdY3ng2B+1fVFQBJPgicBOyd5NCq+me3f6rv4Em0+ep+Osl2rQx8C3hWd81nV9U1U7i/B3Xt27Wqbu7a/DNaMPhG4LV9ZT8LrAY8p6q+09uZZC+G9yB9JXAe7Td8dV/5AGuM1aAkqwCr9O1abXK3JEmSJEnSkmcPvOXHut323Cmev08vvAOoqktoveNWAzbpK/fGbvua/qCkqgrYHSjgBUPq/0YvvOvK3wQc3H0dtoLpWbTeZP2+PKz8YHjX7bsR2J/Wa2v7IfVP1GeAT9B6du0D/ApYkLYi7YeT3HUadQ/6YC+8A6iq/3TXXhF4YV+5qb6Dw6cQ3kHr8fYs4BzgGVMM7wCuAt7ZC+86B9MWXLnlnSa5J7A18Mf+8K7zUW7tFTno+q6uW1QzVnloQej8vs9U/34kSZIkSVpi7IGnnpOG7OuFGav37duSFsS8onVuWsQ1wKbTqL/n5IGgZ8zySVYD3g48A9gIuOPAeesNa+hEdG3YLcm+wJNp9/8wWo/FzYDXJHliVR0/1Wv0+dU4+x7ct2+q7+CEKbbrfOC/wP2AzyV5dRcWTtbpgz0Xq+rGJBey8DvtzXP428EKqurqJCezaCj7LVoPvlOTHAr8AvhdVV21mDbtSwtJe1bDEE+SJEmSNGIM8JYf/6GFNusDf5/C+cNWDu31ZupfFOHOtN/N0IUwOoMB2mTqH7N8F/YsVD7JyrRhrQ8F/gh8lbaQx420efRexsJDJKek65H4f92HJOvShnk+G/git4ZO03HRkH29eebm9u2b6juY7Jx1PVfQArNjaUNVV0jyyiEB6+KMtTrtjSz8G5jTbS8eo/yw+3gT8E/aXJDv6T7XJvkWsFv3/hbRzQd5y5yQYwSikiRJkiTNKofQLj96w1Mfs4SvswC4tKoyzmfYIgNLytNp4d2XquqhVfW6qnpPVe0FHL2kLtoNb30JLfx5YG5dTbcXai0SjieZO7hvwDpD9vUW7OgPv6b6DqbSa66dWHUxbTGIP9PmIPxyxliheAYs6LZrj3F8cBETquqGqtqvqu5HC7FfSOu9+FLaghmSJEmSJC2zDPCWHwcBNwGvTjJW8AHcMnH/VB0PrJnk3tOoYyZt1G2/P+TYo5fwta8DbhjYd3m3XX9I+Ycspr5h7e3t+1Pfvll5B10vth26tuwMfGUJhXgnd9tHDR5IsiqL6e1YVedX1SHAE2kLsTw2yR1mvJWSJEmSJC0lBnjLiao6gzbB/1rAj5Is0gMrye2TvA3YaxqX+nS3PbCv11n/NdZNct9p1D9Z53TbrQfasS3wqulWnmS3JMPmk4M2bPNOwGlVdSlAVS0A/gFsnWTjvnpWo823Np53d+V659wFeBttiOk3+srN2jvo7vMxtDkNXwocPNMhXlWdQ+tR+pAkOw0c/h/aEOJbJFklyQ5ZdPzrHWlz2t1AC7clSZIkSVomOQfe8uU9wO2BtwJ/T/Iz4FRagHEv4LHAml25Kamqo5PsA7wXOCPJ0bQQbU1gY1qPsfcAf5vGfUzGD4CzgXckuT/tfjcBngIcTpujbjpeAnwsySm0nm8X0RZceCStR901wOsGzvkEbQXc3yX5Ni0ofxJw4mKu9U/aIgzfBVYCnksbVvvuqvpnr9Bsv4OquizJY4EfAy8GkuRl3crCM2VX4JfAN7vncSZtqPSW3f5tuHW48h1o8/P9M8nxwL9owepTaKszf6Sqrp/BtkmSJEmStFQZ4C1HukUF3pbkG7RQaZvuczvgAlrg8pWq+sk0r/O+JL+k9UB7DC3QuhQ4i9a7b6nNOVZVVybZAdiPdq/bAX8BXkRb7GC6Ad7LgafSho4+gTb/2k20wOz/AZ+sqtMH2vSFJCsBb6Yt+nABbYjzB4DxgqTnAnsDL6DN/3Y68K6q+vJgwdl+B1X1374Q70XA7ZK8ZAbr/2OSRwMfpq3+W8CvaT0tez0Ze3PlXQW8k/YcHk0LPf8LnAa8s6oOnal2SZIkSZI0G1I15XntJc2AJPOAbavKJVAXI8kKtN54d6iqRRazmIH65wDzH7Tr/qywitPmSZIkSRotf9jvpbPdBM2wBQsWMHfuXIC53bRcQzkHnqSRk2TFJGsNObQ7cE/a8GhJkiRJkm4THEIraRTdCTgvyU9oi4KsBDwC2II2JHmv2WuaJEmSJElLlwGepFF0NfBl2tyD29AWZ7kA+AKwT1VdMIttkyRJkiRpqTLAk2ZZVW03220YNd2qsa+f7XZIkiRJkjQKnANPkiRJkiRJGmEGeJIkSZIkSdIIM8CTJEmSJEmSRpgBniRJkiRJkjTCUlWz3QZJGglJ5gDz58+fz5w5c2a7OZIkSZKk5dyCBQuYO3cuwNyqWjBWOXvgSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwJMkSZIkSZJGmAGeJEmSJEmSNMIM8CRJkiRJkqQRZoAnSZIkSZIkjbAVZ7sBkjRqjv7bAax6pzvMdjMkSZIk9XnK/V4/202QZo098CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYAZ4kSZIkSZI0wgzwtJAkeyWpJNv17dug23fQrDVsGZBkXpKagXoqybwZaNKMS7Jz176dJ3HO2UnOXnKtkiRJkiRp+WaAt4zpC9OOHuP4O7rj/0yy0dJu32RNJRCa4nUO6q6z5ZBjd09yWnd87yXZjiVhqsFhF6xV3+emJJcmOTbJc5ZEWyVJkiRJ0uStONsN0MxJsi+wO/AX4PFVdf4sN2nkJbkP8BPg7sBbqupT06jupcCqM9Kwpecm4APdv1cC7g08A9ghyR5V9eGB8t8DjgMuWGotlCRJkiTpNs4AbzmQ5HbA54HXAMcDT66qy2a3VaMvyUOAo4E1gZ2r6v+mU19V/WtGGrZ03VhVe/XvSLIV8EvgfUk+XVVX945V1Xxg/tJtoiRJkiRJt20OoV3GJVkJ+AYtvPsp8NjB8C7Jmkk+meSsJNcluSjJoUk2m+a1V0ny3W745T7dvpWT7JrkmCT/7rveYV1g1n/+QcBXuq9f6R/O2Vdm8ySfTXJqkvlJrklySpLdu3ufatsfDfwcmAs8ezC865/3L8mGSb6T5L9Jrkry0yQPGlLn0KGsSVZN8tHueVzb3curkmzXXWOvMdq4dpIDu+d3TZLj+ucm7MoUsG3v332fg6b2ZKCqfgOcBtwBWOg3Mt6Q5yRPT/L7rq0XJjkgyRpjXaf7rbwtyUndc70iya+SPG1I2d4Q6A2TvDXJX7rf1kHd8dsn2S3Jyd3v5MokZyY5JMkDpvosJEmSJEkaBfbAW4YlWRX4DvAk4DDgBVV1/UCZNWlDHjcG5gHfBDYAdgJ2TPK4qvrdFK49BziCFh69qao+0x26M/C/wK+Ao4D/AhsCTwOelGSbqvp9V/ZwYHXg6V1dfxpyqVcBT6X1CDuKNkR1O2BfYAvg2VNo+5Npz+1G4ElV9fNxim9A69X4V+BAYKOuvT9Pct+qunAx11oB+CGwPXAyLWy9M/Bx2vsYy+rAb4AFwNeBdYDnAcck2byqTu3KvR/YGbhn9++eP43XrglIt71xQoWTlwIHd+39KnA58BRaqLwyMPi7XIXW+3E74I/Al2lDeHcEjkiya1V9dsilPgNsCRxJe669538w8Fzgz7RQ+DrgHrTnfgxwykTuQ5IkSZKkUWSAt+yaC/wY2IoWLL26qm4aUu6jtPBu36p6V29n13PpaODgJJtW1c0TvXCSu3Tnbga8sKq+2Xf4v8A9quq8gXPuRwsSPwQ8DqCqDk+yOi0QO7yqDhpyuX2BN/TfW5IAXwJ2SbJV12Nsop4PvJ42DPRJVXXiYspvC+xeVR/pu/4+wHuAlwODc8QN2pkWIn0feGbvOSf5OC24GsuDaMOid+0752e0+34j8FqAqtqr65V3z8GhsFOVZBtgE+BSWk+8xZWfQwvWrgK2qKp/dPvfTQvw7gqcM3Da+2jh3V7A3lVV3TmrAT8DPp7ksCHzOD4QeEj/cOUkc4HnACcCWw78VlYAVhun7asAq/TtGrOsJEmSJEmzxSG0y64taeHd76rqFcPCuyQrAy+gBTEf6D9WVcfQeibdG3jURC+atrLtb2mh4FMGwjuq6rrB8K7b/xfakNVtJjP0tarOGby3Luz5XPf1sROtq/NmWk+vF00gvAM4C9hvYN+Xu+0WEzj/xd32vf0haVWdRus1NpargHcOBKsH03rETeS6E7Vikr26zweTfIsWuhUtOL12AnU8A5gDHNgL7wCq6gbg3YOF0+ZsfB1wBn3hXXfOFcDetF57zxpyrf2GzDVYtB6D1w35rdxUVZeP0/Y9aGFu73PuOGUlSZIkSZoV9sBbdv2VNszykUneV1V7DymzKW0es3n9CxH0mQc8AXgw8OsJXHNT2rDOFYAd+obCLiTJg4F3AFsD69ICs35rMcFVTLsQ8o20nnObAnfi1uGdAOtNpJ4+P6H1ANw/yfZVNdgzbNDJQ3on9kKe1SdwvQcBV1XVn4cc+y1t7sJhTq+qK/t3VNWNSS6c4HUnagVgz4F9NwHPq6rvTrCO3nyAvxpy7HcsOgx3E2AN4Hxgz9ahciFrd9tNh9R3wuCOqlqQ5GjgiUlOog2P/hVw/OCQ8iH2BT7R9301DPEkSZIkSSPGAG/Z9W+6udiA9ye53ZAhlHO67VjztP2n286d4DXvQwtefg38ZViBJI+iDYGENsT3dOBKWi+pZ9DCnlWGnTuG79DmwPsHcChwEXADLcR68yTrgjZ08yTgncC8LsQ7e5zyi6y42gVp0MKvxZlDe1fDjDd/3lgrvd44wetO1HVVdXuAJHcCdqANyT4oyRlVdfIE6uj9fi4aPFBVNyW5dGD3nbvt/brPWO44ZN9Yz2wn4F20Hqcf7PZdkeRA4F1jBNhU1XW0+fIAGBImSpIkSZI06wzwlmFVdUY3/9nPaT2ZUlX9vakWdNu7jFHFXQbKLc73aUNK9wJ+mOQpQ4KRd9NCta0H56ZLsiW39tZarCRb0MK7Y4AdB+Y225IW4E1aVe2e5CZa4NML8c6aSl0TsIBbe5QNGuu9zIqux9/3kzyPNoz2oCQP7R/iOoZe2LjO4IFuDro1gf5h1b3f23eraqfJNnPozqqraL+9dye5F23ewdfSfiN3YOyejpIkSZIkjTznwFvGVdWZtIUWzgHe1y2w0HMacC2wRbdi7aBtu+2fJnG999N6sW0PHDmk3o2Ay4aEd6sCDx1SZS+UG9arbKNue+SQOf4ePdE2D1NV7wb2oa3eOi/JhtOpbxwnA3dM8sAhxyY89+Bi3AS3hGXTVlXH0lYIfjCtR9vi9HrpDXsnj2TR/6Hgb7QQ72GTmQ9xoqrqrKo6kPb7vpK2ArIkSZIkScssA7zlQNd7bDvgbOA9ST7Y7b8eOIQ259we/eckeSzwJNpCApNZxZWq2gd4b3fNo5L0D3U8B1ijW3W2d60VgI8xvCfaZd32bkOO9ean23qg7fdj4H6moqreR+tNeA9aiLfR+GdMyde77T7d4g0AJNkUeNkMXWO8ZzhVe9F6u+05gWDwCFogt0uS+/R2duHcBwYLV9WNwP+jhacfGxbiJbl/kkV69A2TZO0kDx9yaA1ab9BrJlKPJEmSJEmjyiG0y4mqOjvJtrThtO/q5sTbgzbX27a0YO9RwPHABrQ5w64GXj5kkYaJXO8DSW6mzTd2VJInd8MYPwM8Hvh1t6LptbSgb33aohnbDVT1O1rA8pYkc4CLu/o/TFuw4ATguUnuChxHC9ueBhzZ3cO0VNX7u/vYm1uH054x3Xr7fAV4Ca3Nf0hyDG0OuOfTFtR4KjDp5z/gZ7Rn8e0kR9Ge+SlVdeRUK6yqk5N8j7YS7IsZZ8Xcqpqf5E3AQcDvk3yTNqz2KbR3O2zBkj1pPTLfBOyY5Be0d78+8ADaUOtHMmRevSHWB45P8hfa/Ibn0YbtPp22gMpHJ1CHJEmSJEkjyx54y5Gq+hctIDsT2D3JR6rqYuARwKdpQ1LfTluF9QjgEVU1kdVnx7reh2jzyG0D/CjJnarqh7Qw6Z+04OeFtKG8D+fWHnX9dVzWlT8deB1tVdB9u2M30UKgA7u27wps1t3DO6ba7iFt2Ic2f9rdaCHevWew7puAJwMfp80R9xZgK2A3bg3FJjoH4VgOoIVUd6Hdx77Ac6ZZJ8D7ab3w3pdk3LC/qg4Gnkl7jy/rPr8BHgssshJst3jEk2hz0/2H9ht4C+23dAHtt3DKBNt5Nq3H4KXd9d4G7EgL855QVftPsB5JkiRJkkZSFj8/vaQlIckHaIHbk6vqR7PdHkHXC3T+ocd9jFXvdIfZbo4kSZKkPk+53+tnuwnSjFuwYAFz584FmFtVY3bwsQeetIR1w38H921GGz56OfCLpd0mSZIkSZK07HAOPGnJ+39JNqDN5/df2nDgp9LmZ3tFVV09i22TJEmSJEkjzgBPWvK+DbyWtiDEXOBKWq+7j1fVMbPZMEmSJEmSNPoM8KQlrKq+Dnx9ttshSZIkSZKWTc6BJ0mSJEmSJI0wAzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYamq2W6DJI2EJHOA+fPnz2fOnDmz3RxJkiRJ0nJuwYIFzJ07F2BuVS0Yq5w98CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkbYirPdAEkaNTvu/zhWvIP/51GSJEmj4+e7/ma2myBpFtkDT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYAZ4kSZIkSZI0wgzwJEmSJEmSpBFmgCdJkiRJkiSNMAM8SZIkSZIkaYQZ4EmSJEmSJEkjzABPkiRJkiRJGmEGeDMsyQZJKslBS/g6lWTeEqx/XpIa2Lddd929ltR1tfxYWn8LkiRJkiQt70YuwOv7j/7+zw1JzkvyrSQPm+02LglJVkzy8iRHJflPkuuTzE/y+yQfSHLP2W6jpq4XiA75Xf87yTeSPGC22yhJkiRJkkbTirPdgHGcCXyt+/cdgc2B5wDPSPLYqvrlrLVshnXh3BHAg4ALgZ8A/6bd90OB3YG3J7l/VZ0xaw3VTPg4cGX37zsBDwaeT/tdP7qq/jBbDZMkSZIkSaNplAO8M6pqr/4dSXYH9gX2AbadjUbNtCSrAccAmwD7Ae+rqmsHymwMfIIW+GjZ9rGq+k//jiT/A3wUeBPwsllplSRJkiRJGlkjN4R2Mb7cbTcfPJBkzSSfTHJWkuuSXJTk0CSbDZQ7uBu+uMWwCyT5aHf8mX37dklyRJKzk1yb5LIkxyTZfgbu6e208O5rVfWOwfAOoKrOqKqnAX8d0t61kxzY3e81SY5Lst2Qcpsn+WySU7uhudckOSXJ7klWmu5NJFmne/5ndM//kiTfTXL/IWXP7j53TPKJbnj0dUn+nGSnMerfoHuflyW5MskvkmyTZK/ufQ27522S/KBry3VJTu+GI686UO6Wuf2SPLJ7t5f3zwGYZPskP0pyflfX+d2w2FdO99kBR3fbtQfadZ/u93hSkku7394/knw4ySJhbt8w3RWTvLfvb+EfSV4/7MJJ1kryxe73c3U3ZPuZSXbu6tp5oPyM/C0kuUeSL3fv/vok53bf7z7Ofa2SZO/uN3ZD+uZiTHKvJF9K8q/uni9IclAcei5JkiRJWg6Mcg+88dzY/yXJmsBxwMbAPOCbwAbATsCOSR5XVb/rin8BeCnwKuD3A/Ws1B37D/CDvkOfA04GfgpcDKwPPAP4aZJnVdUR07iXXbrt3osrWFXXD+xaHfgNsAD4OrAO8DzgmCSbV9WpfWVfBTwV+CVwFLAqsB2tR+MWwLOnegNJNqI99/WBHwOHd215NvCEJI+pquMHTlupK3tn4LCuPc8HvpXkiVX147761wd+C9y1a/vJtNDzx8DPx2jTa4HPA/+lvcuLu/t8N7B9ku2HPM9HAe/q6vwicI+urh27Oi6nDXW+gBa2PRh4EfClCTym8Ty+2540sP9ZwCu69syjBe5bAu8Etk2yTVXdMKS+Q4BHAD8CbgKeC3wuyQ1VdUCvUBcC/gLYDPh191m/O//Hg5V2pv23kOTe3bXWoT3XvwD3o/0tPCXJVmMMFT+MNsz8GOAy4J9dfY/o9t2xq+8M2t//i4AnJXlkVf1zjLasAqzSt2u1xbVfkiRJkqSlbVkL8F7TbX89sP+jtPBu36p6V29n2uqXRwMHJ9m0qm6uqt8mORV4fpK3VtVVffU8BbgL8JGq6g8JN6uqs/ovmOSuwIm0Ya9TCvC63kF3A86tqtOnUMWDaCHVrlV1c1fnz2iB0huB1/aV3Rd4Q1Xd1Hf9dGV36UKT30zlPoD/A9YFnlBVP+mr/wO0Z3QA8MCBc9ajBai3BGlJvkELht7GwgHSh2nh3f9U1cf66t8Z+MpgY9J6XX4G+BPw2Kq6rO9Ybxj2rrT56Po9DnhFVR04sH8XIMB2VfXngWutOXj9xXh7kt4ceHekPZfHAscCHxso+1XgE4NBY5L3Ae+nBXNfH3KNuwP3r6oFXflPAacCu9HeRc87aeHd56rqjX31H8gYwSgz87ewPy28e01VfbGvnlfTAvb9ac9k0HrAAwfe50q0wP52wMOq6uS+Y1vTgs9P0cLrYfYA9pxAmyVJkiRJmjWjPIR2425I415J9ksyjzb33UXA//QKJVkZeAFwKfCB/gqq6hhaz5x703pX9XyR1tPmeQPXfCVQDPSoGgwsun0XAN8F7j2NYXrrdttzp3j+VcA7e+Fd52BaD8WFhghX1Tn94V23r2g9qmB4YLJYSR5Ce7YH94d3Xf3/oAVGD8iQobTAW/vDqao6Fjinv+1dD6nn0Bb3+PTA+QcDpw2p9zW0cPpN/WFP56O0nmMvGHLeH4eEd/2uGdxRVZeOU36Y3WiB0Z604dOPp93zQVV1+UDd5w3pJQjw2W471jvboxfedfX8ndZTc5O0ORd7XgxcRwsD+687j/Z3s4jp/i10Q2R3oA0HP2Dg8AHA34DHDBtKC+w55H0+hdbb7qP94V3Xrl/TAsUnJ5kzRpP2Beb2fe42XvslSZIkSZoNo9wDbyMW7RlzEfDoLhjq2RS4AzCvqq4eUs884Am04Y69nntfBT5CC+wOhFuGaT4B+MXg8L0kG9J66uxAGzLYP+QOWs+gcyZ+azPm9Kq6sn9HVd2Y5ELa8NpbdEHnG2nDVDelLYiRviLrTbENW3bbdfvnJOuzad+2f0jv5cPCIFqY+ci+75vQnveJg2FWVVWS3/VdY7BNT0wyLOS6Ycg5ACcM2QfwLdpw1uOTHAL8DPhVVV00Rvnx3LW3iEXaXHyb0XoYfjXJXatqv17Brofky4GdgfvTAqb+0H2sdzY4FBduDYlXB67oAq0NgL9U1cVDyv+W9vewkBn4W3hIt/1FFyDfonufvwTuS+td+u+Bc4e9n9673nSM39+6tGd2H1ovwYVU1XW0EBOA9sglSZIkSRotoxzgHVNVT4S2UANtdc6PAIcneXhfcNXrWXPhGPX0Vvyc29tRVZcn+RbwsiSbVdVfaUHJCgz0CkpbAfaE7jo/p82xtQC4mTaH3LYsGmJMVK9t60/x/Plj7L+Rdi/9vkMbRvgP4FBaGHoDLdB5M1O/hzt32x27z1juOPB9vLb3h1S99zssZILh773XpneP056J1kVVHZrkBuAttN59rweq6xX6tqr60ySv06v3auDEJM+mhVXvS/L5vmHdn6aFrv8Gvk+be68XNu3JGO+sqoY9296Q8N7vYtLPdYb+Fib99zpem7j1Xb9oMdcd/P1JkiRJkrTMGOUA7xZdD6GPJZkLvIc2VPYt3eHeUMG7jHH6XQbK9XyBFgq+MslutADvMtpE+f3eCqwBvLiqFppvLMn+tNBiSqrqnCTnAXdPcu8pzoO3WGkr7j6VNixyx4F58LakBXhT1Xuuu1bVZ8ctOb361x7j+LD33jtnTlVdMYlr1ZgHqg4DDut6rj2KWxeYOCbJJoPDXyejquYn+QdtdeV7A39Ksg7wBuDPwCP7e5cmWZfpz9s2lec6E38LU/17ZbDH3kC5p1bVDydwfUmSJEmSljmjPAfeMB8Czgden2SDbt9pwLXAFt2QxEG9UOFP/Tu7VWlPAV4CPAnYEPhaVV07cP5G3fb7/TuT3A7Yakp3sbAvd9v3LK5gNwx2Knr3cOTgPHjAo6dYZ09vddlHjltq6v5O63W2+eD9d0NMtxxyTq9Nw45NS1UtqKqjq+rVwEG0xRgeMQNV93qS9f4mN6QNcf7pkKHh031ndHPknU2ba3JYiPeoIftm4m/hT912mwyMV+2+P3qg3OIs6d+fJEmSJEmzbpkK8KrqGtow2pWA93b7rgcOAdaizc11i27+sycBZ9Am8R/0xe683rDZLw0p05vPa+uB/e+kzUs2XR+jhVQvTfKhbtGGhSS5V5LDafOlTcXQe0hyPwae2WRV1Qm0EOUFSQYXBSHJ7ZJMp5fidbThv+sCbxo4/FLafGmDPk8bMvqZYYshJFm9W3xjQpI8Jsnthxxap9susrjFZCR5GnAv4L/cOk9g7509qgvIemXvRpszbyZ8nTbkdaHefEm2Y8j8d8zA30JV/Ys2/PZ+tNV9++3S7f9ZVQ3OfzeWI4B/AW9Lss3gwSQrdavRSpIkSZK0zFomhtAO+CItMHhpkg9V1Znd922B9yR5FC1Q2gDYCbgaePnASq09vcUs1gOOr6pThpTZnza89rAkh9JWu90SeChwJOPP+7ZYVXVFkifQgog9gJcn+TFt0YFVaZP+b0ULpN4+xcuc0H2em+SuwHHAPYCndfew03Tugbai68+BbyZ5C/AHWq/Ie9B6Rq0NDAvAJmoP2oqr+yXZntY7axPaCqRHA0+kzcMGQFWdmuT1wP8D/p7kKOBM2vxrG9J+KwcBr53g9T8O3KOb8+5s2lDbrYGH0xZ7GBYOj+XtSXrzN65KCyCf3NX5lt5CHVV1QZLvAs+mzZN3LG146VNoi2hsOIlrjuUjXf1vSPJA2iIvdwOeS5vf7qn0PVdm7m/hdd21DkjyVNqKtJvRfo8Xd8cnpKquS7IT8CPgF91z6oWg96D16LuU4YuWSJIkSZK0TFimeuABdENc96WFj3t2+y6mDWP8NG2Y39uBx9FCsUdU1a/HqGt+VwYGFq/oK/NH4PG0UOpZtF5Cl9NCtUVWtZziPZ0DbNHV/Sda76f/oc2xthqwH3CfwdVxJ1H/TbTg50Da89mVFpi8HXjHNJtPt5rsQ2hzE96Jdh+voa38+0tawDed+v9NCwK/TXvub6H1fns8rXclDMyZVlUHdOcc0W3fSgsq1wI+CfzvJJqwL/AT4IG0+3oFsDLt2T1+yLDk8exG+93uCbyN9t6/D2xbVf83UHZnWni4Bu2dbQl8gmk+z55ufsBtaMO470t7Rpt19f+iK7agr/yM/C1U1d+Bh9FC1IfTfusP775vMbDK9ETq+z1t1dpP0UK719KCxk2Bw2mLjkiSJEmStMzK8HnhbzuS/IX2H/137VvZVsuIJL+mBXRzfX8zJ8nXaCu7blZVf5vt9iwt3SIl87f+yMNZ8Q7LYgdlSZIkLa9+vutkBv5IWlYsWLCAuXPnQss1FlnQsWeZ64E3k5I8mdbj6KuGP6OtG/o7uO9FtN5fP/X9Tc0Yz3Vb4PnA329L4Z0kSZIkSaPqNtnFJMnrgLsDr6ItQPDR2W2RJuDUJH+kzZd2E2147nbAFUx9bkDBUUmuoQ3dvooWaD+R9ox3ncV2SZIkSZKkzm0ywKMtenE32uqv76yqs2e3OZqA/WmLKjwMuCNtsYNvAPtU1Wmz2bBl3MG0obLPp823eDltAYt9q+r4WWyXJEmSJEnq3CYDvKraYLbboMmpqncD757tdixvqup/mdyCHpIkSZIkaSm7Tc+BJ0mSJEmSJI06AzxJkiRJkiRphBngSZIkSZIkSSMsVTXbbZCkkZBkDjB//vz5zJkzZ7abI0mSJElazi1YsIC5c+cCzK2qBWOVsweeJEmSJEmSNMIM8CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCFtxthsgSaPm8m9/i5tXXXW2myFJkqTlyOoveOFsN0HSMsweeJIkSZIkSdIIM8CTJEmSJEmSRpgBniRJkiRJkjTCDPAkSZIkSZKkEWaAJ0mSJEmSJI0wAzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwNNyI8leSSrJdrPdFo0vyXbdu9prmvVUknkz0ypJkiRJkkaTAZ5GUpINunDm6DGOv6M7/s8kGy3t9s2kJG/r7uXAMY6vneTCJAuS3KNv/7zuvHUneJ0a+NyY5IIkhyfZZqbuR5IkSZIkzawVZ7sB0mQl2RfYHfgL8PiqOr879Fngm8C/ZqttU/S/wDOAlyc5rKp+OHD8/wHrAK+squne26W05wRwB+BBwNOBpyV5blV9Z5r1T9QJwH2BS5bS9SRJkiRJWmYZ4GmZkeR2wOeB1wDHA0+uqst6x6vqEpbBQKiqbk6yM/Bn4IAk9+vdV5IXAc8GflRVX56By11SVXv170jySuAAYD9gqQR4VXU1cNrSuJYkSZIkScs6h9BqmZBkJeAbtPDup8Bj+8O7rswic+D1DcU9KMmGSb6T5L9Jrkry0yQPGuN62yb5ZVfu0iSHJrl7b9jqQNnbJ9ktyclJ5ie5MsmZSQ5J8oCJ3F9V/RN4B7Au8Lmu3rsCnwEuB145oQc1NQcCVwEbJFmru/aYc8slOTvJ2QP7DurO2SDJ65P8Lcm1Sc5JsmcXvvaXHzoHXpLtkxyY5O/dc7wyyYlJXj3eDXTv5tDuXV3VvadHTfpJSJIkSZI0guyBp5GXZFVaz7AnAYcBL6iq6ydZzQa0Xnt/pQVWG9GGjv48yX2r6sK+6z0eOBK4ETgUuADYDvg18N8hdR8MPJfWg+4rwHXAPYDtgWOAUybYxv8HPBN4fpLDgJ2BNYCX9A0TXlIyQ/XsR3tWPwR+TBsavBewMvDuCZz/TmBj4Djge8DqwBOBLyTZpKp2G3LOGsBvaO/pi8D6wPNo7/YJVTVvqjcjSZIkSdIoMMDTqJtLC4K2ogVvr66qm6ZQz7bA7lX1kd6OJPsA7wFeDny427cCLQS6HbBdVR3fV/4rtFCNvn1zgecAJwJb9retq2u1iTawqirJLsCpwFeBVYDvVdXXJnWnk7cLsCpwdjcMeTo2Bx5YVRfALc/4dGDXJO+fQPD6uqo6q39HkhWBo4A3J/nUkHkAH0h7Xi+rqurO+TLwc9qQ5E2q6uZhF0uyCu0590z4fUmSJEmStLQ4hFajbktaePe7qnrFFMM7gLNovcP69eaU26Jv39bAPYEj+sO7znuBwesXrffadYNtq6qbquryyTSyqv5Nm+dvFVpPvtdO5vwJWKsbarxXkg93q/weANwMvH0G6t+nF97BLfMSHkELxjZZ3MmD4V2370Zgf2AFWq/GQTcB7+6Fd905v6CFfhsD4w2l3QOY3/c5d3FtlCRJkiRpaTPA06j7K3A+8Mgk75tGPScP6YXVC2tW79vXmxPvt4MVVNW5DKxwW1ULgKOBrZKclORdSR6dZOWpNDLJXYBXdV9XAXacSj3jWBPYs/u8HXgwcDitt+F3Z6D+k4bsG/ach0qyWpL3d/MJXtnNk1dAr23rDTntnC74HPSrbvvgcS65L62XZ+9zt8W1UZIkSZKkpc0htBp1/6abqw54f5LbDa6iOkHzB3dU1Y1JoPXs6pnTbS8eo54LgXsN7NsJeBfwAuCD3b4rkhwIvKtbcXWivkgL2d4B7A58MsmPq+q8SdQxnr9X1aYzVNcwizxn2lyCsPBzXkQXes4DHgr8kTYs9tLu/A2Al7HwcNeei8aosjev4dyxrllV19F6OvbaMF4TJUmSJEmaFfbA08irqjNoCyP8G9gzyfuX4OUWdNu1xzh+l8EdVXVVVb27qjYENgReAZwGvBn45EQvnORlwNNow3f3A95EC58OmHjzZ0wxdsA/ZiA2TU+nhXdfqqqHVtXrquo9XWB79DjnrTPG/t67GhYqSpIkSZK0zDDA0zKhqs6kLURxDvC+bnGEJeHkbrvIvGlJ7gbcfbyTq+qsqjqQ1tYraYHcYnV1f4rW4+w1XV1fp80f96QkL5/oDcyQ/9JWc11Ikg2YwFDYKdqo235/yLFHj3PePZMMey+9c/40nUZJkiRJkjTbDPC0zOgWONgOOBt4T5IPjnvC1PyaNs/d05M8fODYPgz0Skuy9pByAGvQhnteM8HrfpnWs+0NVXVh3/7X0EK9T3Yh39JyIrBBku16O7ohrp9Ygtc8p9tu3b8zybbcOi/gMCsAH0zf+NfunCcDZzBkPkNJkiRJkpYlzoGnZUpVnd2FMz8H3tXNibfHDNZ/U5LX0nqB/SLJN4H/0HrUrU/roffAvlPWB45P8hfaAg7n0eawezqwEvDRxV2zu97jge9U1aED7bkwya7AN2jz4z15enc4YZ/s2nRkkkOAq4HHAZcDF4xz3nT8gBbOviPJ/YFTaSvXPoW20Mazxzjvz7Rg97gkP6MtdPF84AbgVUMWL5EkSZIkaZliDzwtc6rqX7TA5kxg9yQfmeH6f0QLr04Enge8mraS6ta03l4L+oqfDexF6yX3WOBttJVjTwKeUFX7j3etJPcC9qMtxPC6MdpzCHAYbSjtLlO8rUmpqqNp934m8BLgOcBPaCHe9UvomlcCO9BWnN0CeCMtjHsR8NlxTv0v7d2cQ+ux+BzgOGCHqpq3JNoqSZIkSdLSlKqa7TZIy4Qkq9FWNj2lqh4x2+1ZliV5IvAj2iq9+852e3qSzAHmn/OlA5iz6qqz3RxJkiQtR1Z/wQtnuwmSRtCCBQuYO3cuwNyqWjBWOXvgSQOS3LEL6/r3rUDrKXcH2nBOTc/G3fbcWW2FJEmSJEnLAOfAkxZ1b+DXSY4B/gmsRlvRdDPgL8CnZ7Fty7RuwY/nATvT5tU7ZlYbJEmSJEnSMsAeeNKizgO+DTwEeD3wcmBl4GPA1lV11Sy2bVn3KNo8dafT5gi8aJbbI0mSJEnSyLMHnjSgqi6mhXaaYVX1v8D/znIzJEmSJElaptgDT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYc+BJ0oDVn/Nc5syZM9vNkCRJkiQJsAeeJEmSJEmSNNIM8CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCFtxthsgSaPmD9tuz51WWGG2myFJknSbscWJJ8x2EyRppNkDT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYAZ4kSZIkSZI0wgzwJEmSJEmSpBFmgCdJkiRJkiSNMAM8SZIkSZIkaYQZ4EmSJEmSJEkjzABPkiRJkiRJGmEGeFpmJdkgSSU5yLbcdiTZq3vW2812WyRJkiRJWhoM8LRE9AVa/Z8bkpyX5FtJHjbbbZysJPOS1Gy3Y7r6ArD+z9VJTk3ywSRzZruNkiRJkiTpVivOdgO03DsT+Fr37zsCmwPPAZ6R5LFV9ctp1H0ecF9g/vSaeJv1XeDU7t/rAk8C3gU8JcnDq+q6WWuZJEmSJEm6hQGelrQzqmqv/h1Jdgf2BfYBtp1qxVV1A3DatFp32/adqvpm70uS2wPHAQ8CXgh8ZbYaJkmSJEmSbuUQWs2GL3fbzQcPJNklyRFJzk5ybZLLkhyTZPshZYfOO5dk8ySf7YaEzk9yTZJTkuyeZKUh9dw7yVeSnNVd85IkJyX5eF+ZogsbB4aeHjSkvg2TfCfJf5NcleSnSR40pNz2SQ5M8vckV3afE5O8ethD6643L8na3XkXdfd23EzMB1dV1wJf774OezePSnJk906uTXJaNxx31b4yqyW5IslfxriHFZKcn+TiJCt3+9ZL8v7uPi5Kcl33/j+fZJ2Jtr97nj/q6r+u285L8srJPQlJkiRJkkaLPfA0m24csu9zwMnAT4GLgfWBZwA/TfKsqjpiAvW+Cngq8EvgKGBVYDtar78tgGf3CiZZDziBNrz3SOBQ4E7AvYFdgd26ou8Hdgbu2f27508D194AOB74K3AgsBHwdODnSe5bVRf2lX0nsDGt19v3gNWBJwJfSLJJVe3GolYHfgMsoIVt6wDPA45JsnlVnTrknMlIt13o3SR5NvBN4HraM7oIeCywJ/D4JNtX1XVVdUWSQ4BXJXlUVf12oP4dgbsCH6+q67t929Ce87G0Z3cD8BDgdcATkjy0qsYdJp1kR+AHwOXAEcAFwNrAg4EXAV+azEOQJEmSJGmUGOBpNrym2/56yLHNquqs/h1J7gqcCOxHC2cWZ1/gDVV1U18doYU4uyTZqqp+0x16Ni0Ue3NVfXrgumv1/l1Ve3W93O45OCR4wLbA7lX1kb569gHeA7wc+HBf2dcNudcVaaHjm5N8qqr+NVD/g4DPA7tW1c3dOT/r7u2NwGvHadu4ktwBeHH39dd9+1fr6r8JeGRV/bnbH9r8hi8E/gf4QHfKF2kh6iuBwQDvFd22P1D7GbBuVV050J6XAgd39/XBxTR/F1r4uF2vfX31rDnWSUlWAVbp27XaYq4jSZIkSdJS5xBaLWkbd8Ms90qyX5J5tLnvLqKFPgsZDLS6fRfQFly4d5J7Lu6CVXVOf3jX7Sta7z5oPccGXTOknksWd60hzqIFjf16Q4a3GKh/2L3eCOwPrAAsMmwYuAp4Zy+86xxM6zG3xZDy49mp7938P+AfwANoIelhfeWeQQs5D+wPx7pnunt37Z379p8InAQ8twv/AEiyLvBk4NdVdVpf+YsGw7vOV2k9DYe9r7EMe4+XjlN+D9oiKL3PuZO4liRJkiRJS4U98LSkbUQbZtnvIuDRVfWPwcJJNqSFKjvQhs+uMlBkPeCc8S7Yza32RuD5wKa0IbHpK7Je379/SOsV97kkjwOOpgVMi7Rtgk4eCNfg1lBo9YF2rga8nRaQbUQbxttvPRZ1+mDYVVU3JrlwsP4JeDZ9w4k7hwE7deFcz0O67bzBCqrq30nOBDZJslpVXdEd+kL3eQGtRx60kG9FhgxnTfIsWs/MhwJr0ALMnmHPYdC3gGcBx3dDeH8G/KqqLlrMefsCn+j7vhqGeJIkSZKkEWOApyXtmKp6IkCStYGXAR8BDk/y8P4wKsnGtPno5gA/p81ptgC4mTaH3bYsGugN8x3aHHj/4Nb52m6gGyrbX0dVnZXkkbSQ8UnAc7q2/B14b1V9e5L3u8hcbV3ABn2hVBcyzqMFVn+k9Ta7lNabbQPacxp2r2PNBXcjC4deE/GCqvpmN2x3E+BjtBBsb+C9feXmdNsLGe4/3flzgF6A9w3g47RhtL0Ab5eu/Qs90yS7dde+GPgxLUDr9aR7CxN451V1aJIbuvKvAV4PVNfj821V9acxzrsOuK6vLYu7lCRJkiRJS50BnpaaqroY+FiSubQ54T5AC1x63krrffXiqvp6/7lJ9qdbBXY8SbaghXfHADsOzIO3JS3AG2zXn4Fnp61QuzktyHsTcGiS8/vmy5tJT6eFd1+qqlcN3MPzaQHeUtEN2/1LkmcCpwDvTvK9qjqpK7Kg295ljCruMlCOqroyyTeAVyd5IHBn2sIgn6+qq3vluvDwvcD5wIO730jvWIB3TOI+DgMOSzIHeBQtjHwFbYGPTarq8onWJUmSJEnSKHEOPM2GD9ECm9cn2aBv/0bd9vv9hZPcDthqgnX36jhycB484NHjnVhVN1TVcVW1Jy3AC/CUviI3de2ZbE+38dr5/SHHxm3nklJV19KG9IaFF9v4Y7fdbvCcJOvT7uWffcNne77QbV/J8MUrANYC5gLH9Yd3nYcBd5jELQBQVQuq6uiqejVwEG2l3kdMth5JkiRJkkaFAZ6Wuqq6hjaMdiUWHqrZm9tu64FT3gncf4LVD60jyf1oc+sxsH+LJOsMqafXq6x/UYTLuu3dJtiW8YzVzm1pK7jOiqo6grYAxeOS9ILEI2hDX1/ePUfglh5y+9Le40FD6joJ+ANtZdtnA3+oqj8OFLuI9owfmmTVvrrXAD4z0XYneUyS2w851Hu3iyxuIUmSJEnSssIhtJotX6QFcy9N8qGqOpO2+urLacMgD6XNCbclbajpkcCOE6j3hO7z3CR3BY4D7gE8ratjp4HyL6L1BJwHnEEbBroZbbXUS4AD+8r+rDv/20mOAq4FTqmqIyd360Cb3+9s4B1J7g+cSptH7inA4Sy6uMTStBetZ+DewPZVtSDJq4BDaItEHEqbr+4xtF5yJ7Doyrs9X+DWOfAWWbyiqm5O8nlgN+DkJD+gzaX3JFrIef4E2/xx4B7dezwbKFo4+nDgt8CSGAYtSZIkSdJSYQ88zYpuuOa+tBB5z27fH4HH03ptPYu26MHltOGzJ06w3ptoIdiBtKGdu9ICubczfD61Q7qyd6WtmPom2sq1nwMeWlX9K5IeAHyU1jvv3V37nzOxO16knVfSVtr9LrAFbdXc9WiB4menUudMqaof0J73dkl26PZ9G9ge+CXt3byVFrTtA+zQvc9hDqEtIHI1bWGLYfagPc+iLT7xOOCbtN/CDRNs9r7AT4AH0haxeAWwMu2dP37IcGpJkiRJkpYZqarZboM0JUk2Bf4GfLGqXjPb7dGikjwcOB74SlXtMtvtWZxuAYz5P3vwQ7nTCjMx1aEkSZImYosTT5jtJkjSrFiwYAFz584FmFtVC8YqZw88Lcs27rbnjltKs+nt3Xb/WW2FJEmSJEnLMOfA0zInyX1ow2tfCNxMW2RBIyLJPWjv5n60IcZHV5X/k6okSZIkSVNkgKdl0WbAm4F/AG+qqj/Pcnu0sA1pc9JdSVsMw+HNkiRJkiRNgwGeljlVdThwh9luh4arqnlAZrsdkiRJkiQtL5wDT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYc+BJ0oDNf/Fz5syZM9vNkCRJkiQJsAeeJEmSJEmSNNIM8CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCFtxthsgSaPm0l98mOvvePvZboYkSbqNWGuH9812EyRJI84eeJIkSZIkSdIIM8CTJEmSJEmSRpgBniRJkiRJkjTCDPAkSZIkSZKkEWaAJ0mSJEmSJI0wAzxJkiRJkiRphBngSZIkSZIkSSPMAE+SJEmSJEkaYQZ4kiRJkiRJ0ggzwNNyK8l2SSrJXgP7z05y9iTq2aurZ7uZbeGyI8nO3TPYeSlec+hz7/bNW1rtkCRJkiRpthngaalKskEXwPR/rk5yfpJjk+ydZKPZbud0dAFh//1dl+TiJCck+VySrWe7jZIkSZIkadmx4mw3QLdZZwJf6/69CrAO8HDgvcC7knwUeHdV1Sy1r99ngW8C/5rEOTcBH+j+vSKwBvAA4DXA65P8AHhZVf13Jhu6nJnKc5ckSZIkabljgKfZckZV7TW4M8mjgf8D9qCFYO9dyu1aRFVdAlwyydNuHOP+7gl8GXgq8L0kO1TVzdNv5fJnis9dkiRJkqTljkNoNVKq6lfAE4DrgHckuftgmSRP74bb/jfJtUlOTfL2JCtM5lpJ7pjkE0nO64a5/jnJTkPKzdgceFV1Di28+yuwLbDQ9ZLskuSIbhjutUkuS3JMku2HtOuWOf6SPLIrd3mS6iuTrs7fJFnQDVc+Mckuw9qX5M5J9k9yYVf290meOd49JXlgkm8muSDJ9UnOSfKZJGv2lblnkpuTHDtGHbdPMj/JGX37Jvzck8zthl//NcmVXV2nJfnKsN+QJEmSJEnLEgM8jZyq+gdwKLAy8Iz+Y0k+BBwO3Af4LvB54FpgP9pwy4laCfgx8CTgMNpw3o2AbyV5/LRuYDGq6hrgY93X5w0c/hxwF+CnwCeBHwKPBH6a5OljVPko4Bfdv79Ie3YkCe2+vgysBXwD+BJwR+DLST7WX0mSVYF5tGG+ZwKfAv7e1bdIsNmd8zTgBFooOQ/4X+AU4I3A75Ks0d3zOcCvgO2SrD+kqqcDc7h1WPWEdfd5DK235mXdMzgAOBV4Ju29SpIkSZK0zHIIrUbVL4CXAlv0diR5HG1o7Y+Anarq6m5/aEHea5M8u6q+O4H61wN+D2xfVdd39XyDFpy9jRbuLUm9wG2Lgf2bVdVZ/TuS3BU4kRZSHjGkrscBr6iqAwf2vxJ4IS3Ae21V3djVtzLwHWC3JIdU1R+68u+gzdN3QFW9uu/6/0cLyBbS9bD7KnAxsFVV/avv2AtogeHewK7d7q8C23Rt2m+guhd320kHeMD9gUcA36uqZw20cRVaWDtUd3yVvl2rTeH6kiRJkiQtUfbA06g6v9uu1bfvjd32Nb3wDqBb6GJ3oIAXTOIab+2Fd109xwLnsGiotiQMuz8Gw7tu3wW03ob37ubQG/THIeEdtOd1FfDGXnjX1Xc98O7ua//zeilwPfC+gev/GBg29PWltF5ze/SHd905hwAnAc/v2/1t2tDoF/eXTbIWbdj0cVV1BlN3zeCOqrquqq4c55w9gPl9n3OncX1JkiRJkpYIe+BpVGXIvi1pgdQrWqe7RVwDbDrB+i8fFpbRApxHTrCO6Rh6A0k2pIVKOwDrs3DvMGg9B88Z2HfCkHpWpfWmOx/Yfcjz6vVK27QrvxpwL+CvVfWfIU37FfCYgX1b9rZJNh5yzu2BtZKsVVWXVNX8bvXdnZI8oKpO6co9v2vPV4fUMRF/ow3bfWE3393hXXtPqqqbFnPuvsAn+r6vhiGeJEmSJGnEGOBpVN21217ct+/OtN/snuOcd8cJ1j9/jP03snR6pi5yf10IdgKtV9vPgR8AC4Cbge1oi14MBnoAFw7ZtwYtJFyfiT2vud32ojHKDbvGnbvtG8apv3eN3mqyX6XNp/ciWq9JaD3ybqCbu2+yqurGJDsAewHPAj7eHbokyWeAD44V5FXVdbRegQCMEQxLkiRJkjSrDPA0qrbrtr/v27eANmJ2rUWLL3O267b99/dWWvD24qr6en/hJPvTArxhasi+Bd32D1X1sAm0p1d+nTGO32Wccx5QVadO4BrQ5i+8hNZbbg/aAhOPAI6oqksnWMciquoS4I1JdqX1KtyBNvfe+2nh4L5TrVuSJEmSpNnmHHgaOUnuAzyX1jPqe32HjgfWTHLvWWnYDElyB2C37ushfYd6q6V+f6D87YCtJnONqrqCNrT0vklWn0D5BcBZwMZJ1h1S5NFD9h3fbSc85LiqbgC+BdydFkhOZ/GKYfVXVf2tqj5HW9wD4GkzUbckSZIkSbPFAE8jJcnWtBVPVwH2rarz+g5/utse2K2AOnjuuknuuxSaOWXdIhQ/ADajDZM9rO9wb267rQdOeydtpdXJ+jSwKnBAkkWGFie5V5IN+nZ9FViZtnJsf7nHs+j8dwBfAa4APpjkfkPqXzXJlouedstcdy+mDaW9nPZMpqS7j82GHOr1GlxkcQtJkiRJkpYlDqHVbNk4yV7dv1emDd18BC2ougn4AANBUlUdnWQf4L3AGUmOpoVeawIb03qJvYfW82y2rdh3fyvQhsY+gNaTbgXgCGDnbgXdnv2BlwOHJTkUuJS2UMRDgSOBHSfZhi90578M2CrJT2mLWtyFNsz0EcALgbO78h+lzSH3qi6Q+yWtp9xzh12/qi5O8gLa6rInd+/jNNriFfek9bD7LfDEgfOOS3I6bRXblYADurnopupBwPeS/B44FfgPbe6/Z9B+Sx8f+1RJkiRJkkafAZ5my0bcurjCNbReWKcB+wAHV9WZw06qqvcl+SXwJlqvsNVpQddZtEUMvj7svFmwArfe3/W0+eLOooVq36iq3wyeUFV/7Hq7fYAWpN1EC8C2og0DnVSA14WDOyc5CngV8BTgTrSFKk4H3g78tK/8VUm2pc0X90xacPgX4Hm0RS4WuX5VHZnkIcD/AI+lDVu9iraS61cYe2js12jz0zFOmYk6EfgwbV7BHWm/if8APwb2q6pFVumVJEmSJGlZkoU7AEnSbVeSOcD8f35/D1a74+1nuzmSJOk2Yq0d3jfbTZAkzZIFCxYwd+5cgLnd/PRDOQeeJEmSJEmSNMIM8CRJkiRJkqQRZoAnSZIkSZIkjTADPEmSJEmSJGmEGeBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCEtVzXYbJGkkJJkDzJ8/fz5z5syZ7eZIkiRJkpZzCxYsYO7cuQBzq2rBWOXsgSdJkiRJkiSNMAM8SZIkSZIkaYQZ4EmSJEmSJEkjbMXpnJzkTsArgAcB6wMrDSlWVfWY6VxHkiRJkiRJuq2acoCXZHPgaODOQMYp6ioZkiRJkiRJ0hRNZwjtZ4A1gN2BewArVdXthnxWmJGWSpIkSZIkSbdB0xlC+xDgm1W130w1RpIkSZIkSdLCphPgXQpcPFMNkaRRcc6+D2C1VVzjR5KkmbDBXmfNdhMkSVrmTee/UA8Ddkjif+VKkiRJkiRJS8h0wrd3AdcBX0+y/gy1R5IkSZIkSVKfKQ+hraork7wGOBZ4bpLLgfnDi9ZGU72OJEmSJEmSdFs25R54SR4D/AZYHbgRuBrIkI9DbCVJkiRJkqQpms4iFh+hBXTPB75TVTfPTJMkSZIkSZIk9UwnwNsM+FpVfWumGiNJkiRJkiRpYdMZ3noxcM1MNUSSJEmSJEnSoqYT4H0deFKSO8xUYyRJkiRJkiQtbDoB3l7AqcAxSbZOcqeZaZIkSZIkSZKknukEeNcATwO2Bn4BzE9y05DPjTPSUi03kmyQpJIcNNttWV6M6jNNcnaSs2fp2nt1z2S72bi+JEmSJEkzZTqLWPwKqJlqiKYuyarAW4CdgPvQ3uslwFnAr4EvVdWZs9bA5VySDWjP+piqeuIYZbYEfgccXFU7L73WSZIkSZKkZd2UA7yq2m4G26EpSrIaLaR7IHAG8DXgcuDuwP2A3YEzu8+oOA+4LzB/thsiSZIkSZI06qbTA0+j4S208O7LwKuqaqFekUnuBawyC+0aU1XdAJw22+2QJEmSJElaFkxnDjyNhkd2288OhncAVXVWVS0UlnXzgs0bVtmwOcuSHNSds0GS1yf5W5Jrk5yTZM8ktxsov3NXfuckOyb5VZIrevWONV9bkrsm+VSS05Nck+SyJKck+XySOQNlV07ytiQnJbmqq/9XSZ425J567d8wyVuT/CXJdb3rJ7l9kt2SnJxkfpIrk5yZ5JAkDxj2nGZCkl8kuSHJXcc4/q2u3Q/p27dCkncmOaN7B2ck2YNx/paTrJPkk13Z65JckuS7Se4/pOzZ3Wf1JJ9O8u8kNybZuTu+eZLPJjm1e1bXdO9o9yQrjdOGNZIckOTC7pwTxnhX6yV5f5LjklzUtffs7jewzhh13717V5d17+4XSbYZqy2SJEmSJC1rptUDL8kKwHOBxwLrMbynV1XVY6ZzHY3rsm67MfCnJXyt/YDtgB8CPwaeQVuNeGXg3UPKPwd4fFf+88BqY1XczeP3G2CDru7vdfVuCOwMfBRY0JVdBTi6a8sfab0PVwJ2BI5IsmtVfXbIZT4DbAkc2bXpwm7/wbTf8Z+BrwDXAfcAtgeOAU4Zq93T9AVgG+DlwIf6DyRZC3g68Ieq+mPfoS8Cu9Dm3PsccHvgbcCjhl0gyUbAPGB92nM9HFgHeDbwhCSPqarjB05bBfgZ7X39ALieW5/Vq4CnAr8EjgJWpb2HfYEtunoHrQz8FLgD7VmvDjwfODzJS6rq631ltwF2A44FjgduAB4CvK5r70Or6pah1134+bvu/o4BTqINz/4J8PNhz0SSJEmSpGXNlAO8JHekBQJbAqEtaJG+ItW3X0vOt4EXAV9O8jDaO/ljVf13CVxrc+CBVXUBQJJ9gNOBXZO8v6quHyj/JODxVfXTCdT9GOBewCer6m39B9Lm+buub9f7aKHRXsDevZ6HXbmfAR9PclhVnT9wjQcCD6mqf/XVPZcWNJ4IbFlVN/UdW4FxQschNk6y1xjH7jZk33eBTwO7JNl3oAflS2jB15f62rMdLbw7Gdiqqq7q9n+IscPb/wPWBZ5QVT/pq+sDtHs+gPZc+q1LCzO3qqprBo7tC7xh4Dmla+cuSbaqqt8MnHNX4G+053tDd84naGHbZ5N8v6qu6Mr+DFi3qq7sryDJS2nh3xuBDw60Z33gPVX1wb7yr6YFpOPqwuD+/+FhMu9bkiRJkqSlYjpDaN9DG765J7AWLazbi/Yf68+j9RD6DiM2/9rypqqOAN5Be5fvpPVcuqwbLvnZJPeewcvt0wvvumtfAhxBCz02GVL+8AmGd/0GAyOq6opeOJg2XPd1tAU79u4PvboQaG9a8PWsIXXv1x/e9U6j/Xav6w+luvpuqqrLJ9H2jWh/D8M+rxhyX9fRQqmNaL39+r0CuBr4Rt++l3bbvXvhXVfPecCnBuvvht4+irby7U/6j1XVP2jh3QOGDaUF/mdIeEdVnTPkORWtNyC03rjDvLcX3nXnnAYcSOuN9/S+/RcNhnedr9J6YN5Sf5KVaf+35iLg4wPlvwT8Y4y29NuDtphK73PuBM6RJEmSJGmpms4Q2mcBx1XVBwBaJxyoqguBbyf5Ha2n0P/QesloCamq/ZLsDzyRFtg8DHgE8AbgFUmeV1Xfn4FLnTRkXy/wWH3IsRMmUfcvgf8AeyR5MG2Y66+BUwZ6pm0CrAGcD+zZ+931WbvbbjqR9lTVgiRHA09MchItdP4VcPyQHoWLc0xVPXHYgSRb0oZ6DvoibQjsK2m9z3pl7wccVFUL+so+qNv+akg9w/Zt2W3XHaNn4KZ921P79l/LGMOGu9DsjbQhsJsCd2LhnrfrDTntBuC4Mdr8BuDBtNWTe9d4FvAa4KG0d73CGPVvQhtC/LOqura/4qq6OclvgfsMu48++wKf6Pu+GoZ4kiRJkqQRM50A7x60kKXnZvp621XVuUmOBF6GAd4S1/U++3b36Q0N/RDwetrw2vWnEEgNmj9k343ddoUhxy4csm+oqpqf5JHA+2lzrD25O3RuN7z08933O3fb+3WfsdxxEu3ZCXgX8AJuHZ55RZIDgXdV1dUTvI1Jq6q/J/kF8Kwkd66qy2hhHrQecv3m0v7OLhlS1bB76z2rHbvPWAaf1UXDFkTpfIf2fv4BHErr/XYDLcB9M8N73F5aVTeP0+a5vR1JdgM+BlxMGw5+Lrf2ynzLQP298y4ao62L/f11vSBvGZ49JBCWJEmSJGnWTSfAu4oWJvTMpw2f7fcfWtCnpawLxN5IC27uCTwA+EPvMGO/+7kMD+qm1IxJFa46G3hZN/fcA2gLYLwJ+FyS/1bVIXQLWQDfraqdZqI93XDUdwPvTnIv2nDW19ICqTvQeoMtSV8AtgVe3IWGzwP+WlW/HSg3nzZUei1awNXvLkPq7T2rsRb1GMvQ55RkC1p4dwyw48A8eFvSntcwaya53ZAQr9fm+V0dKwLvpfWufHBV3XKP3Tx77xg4v/c7Hbo6LcOfiSRJkiRJy5zpzIF3DguHc6cCO3STwvf+g/sxwAVDztVS0PWiGtZ77L+0if8XkmQDhg+FXaq6uef+VFUfpfWKA3hat/0bLZh6WJKVlsC1z6qqA2mB2pV9112SvkvrVfdKWnh3J/oWr+hzcrd99JBjw/b1Vpd95HQb2Nmo2x45OA/eGNfvWYlbh/MOO+dP3XYtWoB8XH9413kYLUzt93facN+HJbl9/4FursShK/NKkiRJkrSsmU6AdyywfddrBtpk/PcAfpdkP9r8ZQ+mhRNaQpK8pusZNezYs2jzlF3OwnOcnQhs0K1q2iu7MgvPBbZUJbl/knsOOdTrRXUNQFXdCPw/Wq/Cjw0L8bq6xuqVNVh27SQPH3JoDdpwzUUWcphp3dDmg2m9DvcGrqetHjuot+993SrQACRZnyG936rqBFqI94Ikzxs8nuR2SbadRFPP6bZbD9RzP9piEOPZp/9dJdmUtqLufNpCKNCGwl4DPDTJqn1l1wA+M1hh99y+ReuBt9vA4Vey+PnvJEmSJElaJkxnCO0BwKW0RQMuqKoDu1UvX08L7qCFd3tNp4FarCcB+yc5A/gNbfjhnWjv4NG0Yc6v7+b66vkkbXjqkUkOofXSexwt6JutHpOPBT6e5DfAabTf1oa0HnDXAP1DQPekLXDwJmDHbg65i2m9Ch9AW+zhkYw9N1q/9YHjk/yFtkjHecCatJVRVwI+Ou07m5gv0kKo9YBDq+rSwQJVNS/JV4CXA6ck+R4tZHwebZGIpwyp9wXAz4FvJnkLbRj1tbSw/ZG0v9/bDzlvmBO6z3OT3LW75j1o7+hI2lyCw1xA69n5p25ezLldu24PvKqbv7G38MTnu+dwcpIfAHNov/FzaL/tQbvTevp+IMnWwB+B+9LmUPwx7XcuSZIkSdIybcoBXlWdDnxkYN+uSfamBS/nVNV/ptk+Ld47acHd44BtuHUewvNovbo+U1V/6D+hqo7uemS9B3gJcBlt8Yt3sXBPvaXpGGAD2j08ixZCngd8E/hoVf2tV7CqrkvyJOAVwEtpwdEqtEUL/grszxirqA5xNi1k3oEWIq5JG856EvDJqvrx9G5rYqrqH93KzY9k0cUr+r2KtoDEq2irwZ5L6zn5LYYEeFV1Vhesvw14Bq3X2020UO2XtEUpJtrGm5I8BfgwbcXjLYDTgbcDP2LsAO962u/zI7RFbebS3s8+Q1ZH3oP2e9yZ9j8GXEj7DezJkN9mVV2Q5FG0oPUJtN/PH7rr7YABniRJkiRpOZCxF5uUtLR0c7idR+sFufE4q8BqCUoyB5j/593vwWqrTGeGAUmS1LPBXmfNdhMkSRpZCxYsYO7cuQBzq2rBWOWmM4QWgCTr0npMbQrcsape0e1fG7gXcEpVLfF5xKRl3C7AnYGPGN5JkiRJkqR+0wrwkrwe+Dht+CJA0YY1QptY/nfAaxl/SKB0m5Vkd9o8dK+hzdm3/+y2SJIkSZIkjZopjxFL8lTawgKn0Cax/3/9x6vqL8CfafNuSRpuX9pcdn8Fnj5ed1lJkiRJknTbNJ0eeP8D/AvYvqquSrL5kDKn0FZClTREVWW22yBJkiRJkkbbdGZpfzBwZFVdNU6Z84C7TOMakiRJkiRJ0m3adAK82wE3LKbM2sB107iGJEmSJEmSdJs2nQDv78DWYx1MsiKwLW0YrSRJkiRJkqQpmM4ceF8HPpbkPVX1gf4DSVYAPgZsCHxkGteQpKXunnucwpw5c2a7GZIkSZIkAdML8D4DPBV4f5KX0A2VTfIt4GHABsCPgS9Ps42SJEmSJEnSbdaUh9BW1Q3AE4APA2sB9wcC7ATcmdbz7mlVVTPQTkmSJEmSJOk2KVPN15LcA7i8qhYkCbAJLbhbAPytqm5KshqwRlX9a8ZaLElLSJI5wPz58+c7hFaSJEmStMQtWLCAuXPnAsytqgVjlZvOIhZnAW8BqOa0qvptVZ1aVTd1ZV7flZMkSZIkSZI0BdMJ8DJDZSRJkiRJkiSNYToB3kTcDbhiCV9DkiRJkiRJWm5NahXaJO8b2LVdm/5uESvQwrvnA8dPrWmSJEmSJEmSJrWIRZKb+74Wix8iez7wzKr6/RTaJklLVW8Ri2O/81vuuOqdZrs5ksbxiCc9YLabIEmSJE3bRBexmFQPPGD7bhvgZ8BBwMFDyt0EXAacVlU3DzkuSZIkSZIkaQImFeBV1S96/07yfuDnVfXLGW+VJEmSJEmSJGDyPfBuUVXvn8mGSJIkSZIkSVrUkl6FVpIkSZIkSdI0GOBJkiRJkiRJI8wAT5IkSZIkSRphBniSJEmSJEnSCDPAkyRJkiRJkkaYAZ4kSZIkSZI0wgzwpOVAkkoyb7bbIUmSJEmSZp4BnmZckg26QKn/c3WS85Mcm2TvJBvNdjtHWZIVk7w8yVFJ/pPk+iTzk/w+yQeS3HO22yhJkiRJkpaOFWe7AVqunQl8rfv3KsA6wMOB9wLvSvJR4N1VVbPUvpHUhXNHAA8CLgR+AvwbuCPwUGB34O1J7l9VZ8xaQyVJkiRJ0lJhgKcl6Yyq2mtwZ5JHA/8H7AHcRAv0BCRZDTgG2ATYD3hfVV07UGZj4BPAnZZ+CyVJkiRJ0tLmEFotdVX1K+AJwHXAO5LcfbBMkqd3w23/m+TaJKcmeXuSFYbVmeRpSY5JcmlX/uwkX01y/4FyKyd5c5ITklyR5Mokf03yiSRr9JXbPsmBSf7elbkyyYlJXj3G9SvJvCRrd+ddlOSaJMcl2W4Sj+fttPDua1X1jsHwrnt+Z1TV04C/DmnHhK6fZPMkn+2e6/yu7ClJdk+y0pDyZ3ef1ZN8Osm/k9yYZOe+Mq9J8pfu+f87yUeT3H6s+fmSrJbk/d051yS5PMnRSbYeUnZeV88q3RDsM5LckGSv7vjcbv9fu3c1P8lpSb4y7PclSZIkSdKyxB54mhVV9Y8khwIvBZ4BfKZ3LMmHaL3zzgW+CywAtqH1SHsE8Jz+urqhuP8DXAYcDlwE3B14LPAH4NSu3O1pvdu2AU4HvkILEe8NvJbWK/C/XbXvBDYGjgO+B6wOPBH4QpJNqmq3Ibe1OvCbrr1fpw0Zfh5wTJLNq+rUCTyaXbrt3osrWFXXT+P6rwKeCvwSOApYFdgO2BfYAnj2kEuuAvwMWA34AXA9bYgvSfam9aS8APgicCPtPW06rO1J7txd+37Ar2jvZS7wdODnSZ5TVYcPOfUw2tDiY2jv+59J0n1/RHf/RwM3AxsAzwQOpg1BliRJkiRpmWSAp9n0C1qAt0VvR5LH0cK7HwE7VdXV3f4Anwdem+TZVfXdbv+TaeHdKcD2VXVpX10rAmv2XW9vWnj3VeDlVXVTX9m5tOG8Pa+rqrP6G9vVdxTw5iSfqqp/DdzPg7o27lpVN3fn/Az4EvBGWkg4pm7uu7sB51bV6eOVHcNkrr8v8IaBZ5Cu7C5Jtqqq3wzUvy7wZ2Crqrqm77z7AO8C/gU8tPcOkryPFoAO8xlaeLdLVX2lr653Ab8Hvpjk6CE9ENcDHlhVl/Wd8wBaePe9qnpWf+EkqwCL9CgcOL5K367VxiorSZIkSdJscQitZtP53Xatvn1v7Lav6YV3AN1CF7sDBbygr/wbuu2b+8O77pwbq6rXQ2wF4DXA/K7sTQNl51fVlX3fFwrvevUB+wMrANsPuZ+rgHf2wrPOwbTeaFsMKT9o3W577gTKDjPh61fVOUOeQQGf674+doxr/E9/eNd5Ae2ZfLz/HXTP8wODFSRZi9Yz8Nj+8K4750JaT8u1x2jDnv3h3YDBdlFV1/W/1yH2oP0mep+pPntJkiRJkpYYe+BpNmXIvi1pQdQrWoewRVzDwsMyH04bBvuLxVxrU2AO8NOq+u9iyvYWk3g7bXjvRrQVYPutN+S00wfDoqq6McmFtOGtS9qEr59kZVpY+nzas7kTC7+PYfd3La2n46AHddvfDjk2bN8WtMDv9r057Abcu9tuCvxw4NgJQ8r/rWvXC7v57g6nDcs9aTCkHGJf2oIgPathiCdJkiRJGjEGeJpNd+22F/ftuzPtd7nnOOf1h2mrA+cN9DobZvVue97iGtWFW/OAhwJ/pA25vZTWk20D4GUsPOyyZ/4YVd5IC6wW5z/ddv0JlB1mMtf/Dm0OvH8Ah9LmDbyB9pzezPD7u6jrpTdoTre9eMixC4fsu3O33ar7jGUwNB1aXxdS7gDsBTwL+Hh36JIknwE+OFaQV1XX0QJgAMYIjSVJkiRJmlUGeJpN23Xb3/ftW0AbzbnWosWHuhxYN8ntFhPiXd5tJxKOPZ0W3n2pql7VfyDJ82kB3oyrqnOSnAfcPcm9pzgP3mIl2YIW3h0D7DgwD96WtABvaBPH2L+g264NnDNw7C7jlP94Vb19Qo3uNWB4gEhVXQK8McmutJ57OwC7Au+nBZP7TuY6kiRJkiSNEufA06zoFj54Lq330/f6Dh0P/P/27jtOsqrO///rvSQBZ0bFHFYUdDFiBpUwIChmRQwY8av8dA0rawRFGUHFRXFlWWVdE5hFVlAXBUQZFDGgKIYFFRQQARGUGTICn98f55YUNdUz3T3dXTXTr+fjUY/bde65535u1ZmG+cwJmyS5z9ALV/Qj2mix7VdR79e0xNEjk9x2FXU3645fHXJu20nGNV0f7477rqpiN1JwOnrPd+yQkWnTeb4zuuNjhpwbVnYaLRn46Gnca6WqObOqPgTs3BU/babvI0mSJEnSXDKBpzmXZBva6K8NgAOrqn9a6390x08k2WTItXdOcr++ot6mC4ckud1A3XWT3An+vgHFR4BFXd11BuouSnLr7m1vFNk2A3W2B24xIm8WvJ+WbHxxkvd0u6TeQpJ7JTkGuP807zHR8z2AtqnDVH0BuAl4ff93lmRj4G2DlavqYuBI4DFJ3pQh81aTbJVko8ncvPs8hn0WvdF/K2xuIUmSJEnSmsQptJpNm/dtUrA+cEdgK+CBwI20HUr377+gqo5LcgDwduDsJMfREk6bAJvTRojtS9u4gKr6epL30zac+G2So2nrud0NeBwtIfbBrvl30DbJeBGwdZJv0EYA3hvYhZbQ+hnwNeBc4M1JHgj8Evgn4Cm0DRKetfofzXBVdUWSJwBfoSXTXprkBNrGChsBD6WtG3dD98zT8aPu9ZwkdwF+APwjbaTascBuU4z510neC7wV+EWSL3Xx7UrbXOKBtARfv1fRPtODgBcl+T5tDb97AA+nbWRxF+BqVm1L4Ogkp9G+q4tp3/8zaP3s4IkvlSRJkiRp/JnA02zajJs3o7iGtg7dWcABwBFVdc6wi6rqHUm+A/wLLQl3G9omEr+nbVTw2YH6b+oSQK+hJZ9uBVwEfBv4Zl+9a5Ps3NV7IW003Y3A+cB/0ZJ2VNWV3aYI7wO2o63V9yvgBbRNFGYtgdfd/7xunboX0qYZP4G28cO1wG+7uA6rqj9Ms/0bkzwFeC8tcfnIrt03At9gigm8rs23JbmAtu7cK2lJ1C8Ah9DW21s+UP8vSR5D+y6eS/ts/4GWfDuD1kcuneTtf9w9y2LgybT+cjFwAvC+qhq2c60kSZIkSWuMTLAmvCSttiQ70ZKoB1XVW0Ydz6okWQgs+9ZRp7LxRrdeZX1Jo7PVEx806hAkSZKk1bZ8+XIWLVoEsKiqlk9UzzXwJK22JHcYsq7gbbh599dj5jomSZIkSZLWFk6hlTQTXgC8Mcm3gQtp69ftQlv38PCq+v4og5MkSZIkaU1mAk/STDgV+AmwE229vhtpG40cAHx4hHFJkiRJkrTGM4EnabV1G0U8fdRxSJIkSZK0NnINPEmSJEmSJGmMmcCTJEmSJEmSxpgJPEmSJEmSJGmMuQaeJA14xM4PYOHChaMOQ5IkSZIkwBF4kiRJkiRJ0lgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hhbd9QBSNK4ecOzPsT6691q1GFoAh/6+r+OOgRJkiRJmlOOwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8aZYkWZqkRh3HXEtybpJzRx2HJEmSJElrCxN4mpeSPCTJfyX5vyTLk1yf5KIkJyTZK8kmo45xNiRZkqSSLJ7idYd31209O5FJkiRJkqSJrDvqAKS5lOQfgIOANwA3AN8BTgCuBu4IPAb4d2D/JPeuqktX43YvBjZavYjXSI8bdQCSJEmSJK1NTOBpvnk3LXn3Y+B5VXXOYIUkj6Ql+W61OjeqqvNX5/o11bDPVJIkSZIkTZ9TaDVvJLkP8CbgEuCJEyWaquo0YEfgor5rF3dTSJcMaXfT7tzhA+UrrIGXZFGStyQ5OcmF3dTdC5N8KslmQ9r++5TXJC9J8pMkVydZOtX2umv2696e1LVbM71e3URr4CXZqHues5Jcm+QvSY5N8phVPPdzkpye5JpumvN/JNlwyDXP6j6HS7r2/5DkuCTPmMnnkyRJkiRprjkCT/PJHsA6wEdWNTW2qgq4cRZiuB+wP3AScDRwFbAF8HzgyUkeVlXnDbnuTcAOwFeBb9Km/061vcO74/bAEcC53fvLZ+bRJpZkA+BbwNbA6cAHaVOWnws8Pslzq+rLQy59NfBE4CvAUmAX4LXAJsAL+tr/Z+DDtKTr0cBlwF2ARwHPAI6Z8YeSJEmSJGmOmMDTfPLo7njSCGM4E7hLVf2lvzDJDsCJwL7AnkOu2x7Yqqp+Md32qurwJJt2bR1eVUtX+2km78205N1ngRd1CVKSfBD4EfCxJN+sqisGrtsZeHhV/bqr/zbgZ8DuSd5UVRd29V4OXA9sWVV/7m9gZRuSdInFDfqKFkzv8SRJkiRJmj0m8DSf3Lk7Xjh4IsmOwHYDxSdW1SkzGUBVLZug/KQkvwJ2muDS/x6SvFud9ubaHsDfgL17yTuAqvp5N/X4FcDTgc8MXHdIL3nX1b8myedpU4Efzi2/y791r1uoqstWEtc+3DytWJIkSZKkseQaeJpPspJzO9ISOf2vbWYliLau2zHdem5/661FBzwIuOsEl/1ohtubM0kWAvcGzq6qC4ZUWdodHzLk3OlDynpt3Kav7EhgY+CXSd6f5ClJbjN44RAHAov6XnefxDWSJEmSJM0pR+BpPvkTbX24uwG/7j9RVfvSppuSZA/gk7MRQJJnA18ErgSOp61DdzVQtFFq95zg0j/NcHtzaWF3HPoMwMXdcdGQc8NGGPbW/1unr+wg2rp3rwReT9tp+IYkXwf2qqrfD7txVV0HXNd7n6wsxytJkiRJ0miYwNN8cipt/bcdgG9P8dqbuuOwPzPDEk8TWQJcS1vX7bf9J5I8byXX1QTl021vLi3vjnea4PydBupNWTct92O0tfQ2AbYFdgeeA9wnyYOqajY2JZEkSZIkadY5hVbzyRG0RNz/l+T2U7z2r93xbkPOPXQK7WwGnDkk2XbX7txUTbW9XhJrnSHnZkVVLQd+B2yeZNjnt313/NkM3e+yqjqmqp5LS9TeD9h8JtqWJEmSJGkUTOBp3ug2Q/gAcEfgG0kmSpjdZkjZr2nTVJ+W5Ha9wiR3opt6O0nn0RJZfx+NluRWwGFMb0TsVNvr7VY712u9HQGsBxyYvnmqSR4IvJQ2VfaY6Tae5AlJ1h0oWw/ofVfXTLdtSZIkSZJGzSm0mm/2piWSXgf8OsnJwM9p68bdkbaRwiNo0zl/3ruoqq5P8p/d9acn+QqwAHgqcDKTHz13aPf6aZKjaH8Gd6ZtsHEGsOUUn2eq7Z1Em4777iRb0BJny6rqsEne7+1J/jzBuXdU1fkTnDsIeDLwIuB+Sb4F3AF4Lu37eHFVXTHJGIb5InB1klNoSc31aJ/D/YEvriQuSZIkSZLGngk8zSvdOmh7Jfk0bcOD7YCtgPVpo9N+QdsE4dNVdenA5fsC19NGjL2StmHEAcDXgGdNMoQPAX8DXgvsCVwOHAu8lbaT6lRNqb2q+r8kL6Vt8vCvwAa0hNdkE3hPWsm5DwJDE2VVdW2SHYG30JJ2/0pLmn4HeE9VnTLJ+09kH2AX4FG0pOpVwNnAK4BPrGbbkiRJkiSNVNra75JmWpIfAA+tqg1GHYsmJ8lCYNnLd3oP6693q1GHowl86Ov/OuoQJEmSJGlGLF++nEWLFgEs6taQH8o18KRZkGQd4F7ABaOORZIkSZIkrdlM4EkzLMnewNdpa+p9ecThSJIkSZKkNZxr4Ekz7820HWs/CLxjtKFIkiRJkqQ1nQk8aYZV1e1GHYMkSZIkSVp7OIVWkiRJkiRJGmMm8CRJkiRJkqQxZgJPkiRJkiRJGmOpqlHHIEljIclCYNmyZctYuHDhqMORJEmSJK3lli9fzqJFiwAWVdXyieo5Ak+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaY+uOOgBJGjdXXPElko1GHca8tWDB7qMOQZIkSZLGiiPwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk/SrEmyJEklWTzqWCRJkiRJWlOZwNNaJcmmXcKo/3V9kj8k+VySB486xqlK8sLuOQ6d4Pzx3fmjJzj/8e78c2Y3UkmSJEmSNBvWHXUA0iw5B/hM9/Otga2B3YFdk+xYVaeOLLKp+3Z33GHwRJJ1gccABWyf5B+q6qaBaou749LZCnAl/hP4AnD+CO4tSZIkSdJawQSe1lZnV9WS/oIk7wLeBrybIcmwcVVVFyb5DfCAJHesqkv6Tj+SlqD8MrArsCXw097JJHcH7g38auC6OVFVlwKXzvV9JUmSJElamziFVvNJbwrqI+EW020PH1a5O7d0oGxpV75ukrcn+X2S65L8JsmrJmgnSf5fku8lWZ7k6iQ/TvL/phD7Sd1x+4Hyxd1x/4H3Pb1E5UldLIuSvCXJyUku7KYXX5jkU0k2GxL739ewS/KSJD/p4l868HlskGT/JGcn+VuSJYPXD2n7KUlOSrIsyTVJfpZkryTrDNT7+/eUZIskX05yaVe2aVfnYUmOSnJ+9338Kcn3k+y9is9VkiRJkqSx5wg8zSc1g219HtgK+AZwI/Ac4ENJ/lZVH+1VShLaVN7nA78BPgdcD+wMfDzJ/avqjZO430nAK2gJuS/1le8AnFVVZyT5dff+3wfO964HuB8t2XcScDRwFbBFF9+Tkzysqs4bcv83dW19FfgmcMPA+S/TRv8dD/wF+N3KHibJ64APdnU/18Xx1C72bZPsVlWD39fmwA+AXwFHALcDrk/yEOBU2vfwFeA84DbAA4A9gfeuLBZJkiRJksadCTzNJ//SHU+bgbbuATywqpYDJDkE+CXwBuCjffVeTkuOfRx4ZVXd0NVfHzgKeEOSz1fVT1Zxv14CbnGvIMl6tPXvPt0VnQw8Z2AdvMW0xOXJ3fszgbtU1V/6G0+yA3AisC8t6TVoe2CrqvrFBPHdFXjwYLvDJLk38H7gEuARVfWHrvytwAm0qcAv4OY1DHseCxxQVe8YaO8NwAbA06vqqwPnNllFLBt01/YsWFX8kiRJkiTNNafQam21eTd9c0mS9yc5hbb+3bXAW2eg/X16yTuAqvo18D3gn5L0J4FeQxtd9ppe8q6rf30XD7TNNVaqW7/u/4D7JblzV/xIYGNuTs6dTBt59lCAJPcA7gX8vKou69pZNizJVlUn0Ua27TRBCP+9kuQdwH6TSd51XkD7x4ODe8m7Lobrgd6U1z2GXHcx8K6VtHvNYEHvuVdiH2BZ3+uCVdSXJEmSJGnOOQJPa6vNgP26n/8G/Ik2VfO9q0hETdbpQ8p6yZ/bAFck2Qh4EHAhsHebTXsL63XHLSZ5z5OA+9NG1X2BFXeX7SXydgB+ws3TZ3u72ALQrUe3F20K8O255e+B6ye4949WEduqzvd7aHdcOniiqn6Q5BrgIUOuO6NL8g06ivY8xyQ5kjbF95SqmszOtwcCH+h7vwCTeJIkSZKkMWMCT2ur46tql9lqvKqWDSnujbDrbcJwWyDA3bg5mTjMxpO87beBV3NzAm8H4DdVdXEX0x+TnNOdfz8rrn9HkmcDXwSupK1Xdy5wNW2a7R7APSe4959WEduqzvdbuIprLqF9ZpO6R1V9P8mOtNF0u9ON3kvyE+BN3ejCoarqOuC63vshSVZJkiRJkkbOBJ7ms946cSv8OUiyaAba702x/UlVPWIG2juZlmjboW/9u8F14pYCz+52cl1Me8bv9J1fQptG/PCq+m3/hUmet5J7r3QDkCEbTqxM73O5E23DiUF37KszqRiq6mTg5CQb0kYWPhV4FXBskgdV1TlTiE+SJEmSpLHiGniazy7vjsNGez10SNmUVNUVtE0j7pfkNjPQ3mXAz4H7As8ANuLmabM9J9NGuD0T2BQ4fWC04GbAmUOSd3ftzs2Fn3bHxYMnkjwK2BD42XQarqprqmppVb0BeE/X1kTr+kmSJEmStEYwgad5q9uE4jfANkk275V3m1AcOEO3+Q9aou2jSVaYKpvkXkk2nUJ7vemgvZ1Ylw6c7yX0elN2B6ePnkfb4ONOfTHcCjiMuRuR+znadOPXd4nDXhzrAe/t3h4+2caSbJtk4ZBTvWdcYXMLSZIkSZLWJE6h1Xz3AeC/gO8n+RItqf1E4Mcz1P5HgK2BlwCPTXIibVOLO9E2r9gKeD5tLbrJOIm2YcMDgbOr6sL+k1V1fpJzu/O9+v0O7V4/TXIU7XfAzrS1+s4Atpz8o01PVZ2T5C3AwcDPu40nrgKeQvtMvsKKU4NX5g3AzklOAn5HmyL8MOBxwNnA0TMYviRJkiRJc84Enua1qvpIN/LrdcDLgYtoo7/excQ7sk6l/QL2SPJ1YE9akurWtI0afgu8EThxCk2eDNxI2yhj6UrqbEob5fbdgXMfou3K+9ounsuBY4G3AkdOIY7VUlUfSHI28HrghcD6tNGQbwD+Y4pr6h0GLKMlQ7ejJSPPp32HH+ymMkuSJEmStMbK1P6eLElrr24q7rILLvgYCxduNOpw5q0FC3YfdQiSJEmSNCeWL1/OokWLABZ1S30N5Rp4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hhbd9QBSNK4WbDg2SxYsHDUYUiSJEmSBDgCT5IkSZIkSRprJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMbbuqAOQpHHzuVfsxIbr++txul5yxKmjDkGSJEmS1iqOwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYyZwBtzSQ5PUkk2neb1lWTpzEYlrVqSpUlq1HFIkiRJkrSmM4E3R5Js2iXT+l9/S/LHJEcmecSoY5wLvaRO3+umJH9N8p0keyTJqGOcjjQvTPLtJJcluT7Jn5L8NMmHk2w/6hjngySLu361ZNSxSJIkSZI0U9YddQDz0DnAZ7qfNwYeDjwbeEaSnarqOwP19wHeC/xxmve7H3D1NK+dTQcDVwLrAPcGdgW2pX0erx1hXNP1CWAP4K/A/wIXArcH7gu8DFgInDyq4EbkxcBGow5CkiRJkqQ1nQm8uXd2VS3pL0iyN3AgcABwi5FaVXURcNF0b1ZVZ0332ln2/qq6uPcmyYOAHwKvTvKBqvr96EKbmiTb0pJ3PwO2r6rlA+dvA9x/zgMbsao6f9QxSJIkSZK0NnAK7Xj4eHd8+OCJidbAS/KsJCcnuSTJtUn+kOS4JM8YqLfCGnj9bSZ5VZIzuzbOS7JfkhX6RZKNkhzU3efaJL9MsudMTVmsql/QRqil9zmsbA21YZ9LNwW3uuPjkpyS5KpuSusRSTaZoK0HJ/lCkou6qa/nJTl0ovpDPLo7HjGYvOue7fKqOnXgnqvzbM9MclqSq5NcnOSwJLedoK17JflYkvOTXNc94+FJ7jmkbnVx3a2rc3E3xXlxd37dJPskOafrA2d37+/dXXv4qp4xyaIkb+n67oXd531hkk8l2WxITEu6thcneU6S05Nc0z3HfyTZsL8ucFL3dr/ccqr2poNtS5IkSZK0pnAE3ni5YTKVkvwz8GHayLyjgcuAuwCPAp4BHDPJ+70PWEyb8nlCd+0SYH3gbX33W6erswNwBvA54Ha0abBLJ3mvufRU4CnA14DDgO1o0zk3A7bpr5jkacCRwI3AV4E/0EbLvQZ4QpKtquqvq7jfX7rj5jP1ACuxG7Az8CXgRNqIzVcCj07y6Kq6plcxyVbA8bSp2l8DzgY2BV4APLGr/7uB9jcBvk97pi/S+kIvKfkJ4EW0aeAfAjYA9uLmBOZk3A/Yn5ZoOxq4CtgCeD7w5CQPq6rzhlz3auCJwFdofW4X2lTrTbrnoSvfFHgJLRm8tO/6y6cQoyRJkiRJY8UE3nh4RXc8ZZL1Xw5cD2xZVX/uPzGFUWPQRro9uJumS5IDgN8Cr03yzqq6vqu3By1591XgmVV1U1f/YOCnU7jfhNKm0G4PFPDj1WzuacDiqvpe1/Y6tGTX4iRbV9UPuvJNgE8DfwYe2z/lM8nutETl/qx6Tb7jgSuAf06ygJaY+klV/WE1n2OYJwM7VdW3+mL9BPBS4I20adgkWQ/4Am2U7SOq6oy++tvQkluH0JKd/R4IfBLYs6pu7LvmcbTk3Y+B7XqJwiTvYmp94EzgLlX1l/7CJDvQvqN9gT2HXLcz8PCq+nVX/220Kcu7J3lTVV1YVUvT9kB5CbB0cKr6MEk2oCUiexZM4VkkSZIkSZoTTqGde5t30wKXJHlf2vTWA4BLgDdNoZ2/da9bqKrLptDGAb3kXXftpbQRTguAf+qr98Lu+PZe8q6rfxZwxBTu1++N3WdwQJLPAj8CNgQOrapzp9lmz+d6ybsuzhv74nxkX70X0zaX2Gdwvbaq+jxwOvC8Vd2sS9Q9m7bRyItpCbzz06Y3fzHJjqvzMAO+2Z+86+xL6wsv6St7Cm002kH9ybsu3lNo3/OTkiwcaOt64M39ybtOrw8c0D/Kr1vH8JDJBl9VywaTd135ScCvgJ0muPSQXvKuq38N8Hn6plxP0z7Asr7XBavRliRJkiRJs8IReHNvM2C/gbJLgG2r6jeTbONI2s60v0zyBdpoqlOq6vIpxnL6kLJeAuM2fWVbAldV1c+H1D+Vm0cQTsUbumPRpmieRlsL8FPTaGvQZJ9r694xybDpr7cCbp/k9l1yc0JVdXySe9OmJG9HSyptAzwHeE6SA6vqrZN/hAl9d8i9L0xyDrBFkgVVdQU3P9sWGb4+4Z1pCfz7cssRj7+f4Fm37I6nDjk3rGxC3Zp6ewFb0Xbq7f89dP2KVwCT/06n6kDgA33vF2AST5IkSZI0Zkzgzb3jq2oXgCR3oI2a+jfgmCSPqqorJ9HGQbR1714JvJ6WDLshydeBvaawg+uyIWW9dfjW6StbSFsbbpg/TfJeg+7SvwvtDJvsc92uO756Fe1tDKw0gQdQVTfQpoGeCG3TB9r048OAfZIcVVXDElFTcckE5X+irSW3kDadt/dsL5igfs/GQ9oZZiFwE63fDbv3pCR5Nm1tvStpU4/PBa6mJXL3AFbYXKMz2e90SqrqOuC6vvim25QkSZIkSbPGBN4IdevXvT/JIto0yHfRRiat6roCPgZ8rFvHbVtgd9por/skedCQKZCrYzlwhwnO3WkG7zOot9beul1yrN+iGWi/tznDg6rqlzPQ3i10MX8syba0qbU7cPNIsuk+2x0nKO99D8sHjk+tqv+dStgTlC+njdjbhBWTmVPpA0uAa2nr2f22/0SSVU5XliRJkiRpPnINvPHwHuBC4FVJNp3KhVV1WVUdU1XPBb5N2+VzpndDPQPYOMmDh5x7zAzfq19v99e79Rcm+QduntK5On7YHaeyi+p0XDWkbLrPtu1gQZK70qZmn9NNn4WZf7beOnrDvu+p9IHNgDOHJO96z7C6eonraY/KkyRJkiRp3JjAGwPdgvz/BqwHvH1V9ZM8oZue2V+2HjdPm7xmxatWy2e74wFdgql3zy245cYJM623NtseA+WvB+41A+1/kjbd9N1JHjB4MslGSbZe8bIV6u2S5OmD30l37r7Abt3b/l2Gp/tsO3c7wvZ7F63v9G8o8hXgfOD1SbYbEtd63W60k9XrA29Pcqu+du4MvG4K7ZxH28jl76P2uvYOY2ZGBPc2yLj7DLQlSZIkSdJYcArt+Phv4C3Ai5O8p6rOWUndLwJXJzmFlhBZD9gZuD/wxcEdVWfAJ4EXAU8DfpLkeFqy8HnAN4Gn0k0JnYX7vhlYkuQhwDnAI4AHAicD269O41X15yS7A18CzkhyHHAWbfOKe3btnwrssoqmtgD+Hbg0yXe6OEMbCfkkYH3gsKr6Yd810322Y4GvJ/kSbV3C7Wmj7M4A3t/3bNcl2Q34BnBykm8BvWnC/0gbyXdZF/sqVdWJ3W7BLwB+keQrwAa0ads/ZPJ94NDu9dMkR9F+B+1M+7zOYPVHVp5FG836vCRX0zakKNrnP2wdPUmSJEmSxp4j8MZEVV1L2xFzXVbcpXbQPrRdWx8FvAZ4IW0k2Su6n2c6thtpiaiDaWuw7QU8lrZ5Rm/U1/KhF6/efS8GdgS+BTwe2BO4nLbD6rkzdI9jgYcCh9OSZ68Fnk9L4H2SSYyIpI1O25O2G/ADaJuLvI62y+oJwG5V9aqB+0732Y6iJU63oH0PmwEfAXbsRnL23+M0WkLsEFrS7pXAS7trjwFuEdMk7EH7PNahfU5PAj5IGwEIk+sDH+ri+AvtmZ9JS1g+hvb8q6Xrq7vSkoovok1PPxC47eq2LUmSJEnSqKTthyBNT5J3AW8DnlRV3xh1PGurJHvQEoovrarDRxvNLSV5OfBR4FVVddio41kdSRYCyw573iPZcH0HKE/XS444ddQhSJIkSdIaYfny5SxatAhgUVVNODDGEXialCR3GVJ2f+BfaCOnTp7rmDS3ktw5SQbK7kbbQflGYCq73UqSJEmSpElyiIkm67Buh9wf0XZQ3Yy27tl6wMuq6uoRxqa5sTfw5CTfBS6hTct9CrAAWFJVfxhlcJIkSZIkra1M4GmyvkRbu2xXYBFwJW3U3cFVdfwoA9OcOY62UcqTaWvKXQv8HPhwVX1ulIFJkiRJkrQ2M4GnSamqz9I2a9AIdOveHT7iGI6jJfEkSZIkSdIccg08SZIkSZIkaYyZwJMkSZIkSZLGmAk8SZIkSZIkaYylqkYdgySNhSQLgWXLli1j4cKFow5HkiRJkrSWW758OYsWLQJYVFXLJ6rnCDxJkiRJkiRpjJnAkyRJkiRJksaYCTxJkiRJkiRpjJnAkyRJkiRJksaYCTxJkiRJkiRpjJnAkyRJkiRJksaYCTxJkiRJkiRpjJnAkyRJkiRJksbYuqMOQJLGzdd+eg4b3XrBqMNYYz3z4ZuPOgRJkiRJWqs4Ak+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk9aDUkWJ6kkSwbKz01y7hTaWdK1s3hmI5xb3TMsXdPvIUmSJEnSODGBp7VOkk27JE//6+okFyb5VpL9k2w26jhnQpK7JTkwyelJLk9yfZKLkhybZI8k649BjId338Gmo45FkiRJkqQ10bqjDkCaRecAn+l+3gC4I/Ao4O3AW5McBLytqmpE8fX7T+ALwPmTvSDJ7sDHgQ2Bn9CedRlwZ2BH4JPAi4DHzXSwK3E/4Oo5vJ8kSZIkSWs9E3ham51dVUsGC5NsC3wK2Ae4kZbQG6mquhS4dLL1k+xCS9hdDjy9qr45cD7AM4CXz1yUq1ZVZ83l/SRJkiRJmg+cQqt5p6q+CzwBuA54c5J7DNZJ8vRuuu1fk1yb5JdJ3phknancK8nGST6Q5I9Jrkvy8yS7Dak36TXwuhg+RPvz+5zB5F33jFVVRwO79l23KMlbkpzcTSe+vjt+atiU4v6YkuyZ5FfdZ3F+N233VkOuucX6dN06gC/p3v6+b0pzf51nJvl8krO7qc7Lknw3ybNW9VkMPNv+Sf4vyZVdG2cl+eSw71eSJEmSpDWJI/A0L1XVb5J8EXgxbaTaob1zSd5DG513AfA/wHJgO+B9wFbAsyd5m/WAE4DbAV8GNgKeBxyZZJeqOmGa4e8A3Bs4taq+tbKKVXVd39v7AfsDJwFHA1cBWwDPB56c5GFVdd6QZt4ALAa+CPwv8CRgb+ChSZ64iinIHwT2ALYEDqGNGAQ4t6/OgcD1wCnARcAdgKcBRyX5l6o6lJXoRhseT/tuvgccB9wEbAo8EzgC+MPK2pAkSZIkaZyZwNN8djItgffIXkGSnWnJu28Au1XV1V15gA8Dr0zyrKr6n0m0f1fgNGCHqrq+a+dzwInA62nJvel4bHf89hSvOxO4S1X9pb8wyQ5dTPsCew65bifgEVX1q67+24Cv00YxvhD49EQ3rKoPJnkILYH3wao6d0i1J1XV7wZiujVwKnBAko/3vocJPJCWvDu6qnbtP5FkA1oidaju/AZ9RQtWch9JkiRJkkbCKbSazy7sjrfvK3tNd3xFf9KoG2W2N1DA7lO4x7/2knddO98CzqMvaTgNd+6OF0zloqpaNpi868pPAn5FS9QN8+le8q6rfwPw1u7tS4ZfMqW4fjek7ErgcGARk/+srhnSznVdWxPZh7bxR+81pc9UkiRJkqS54Ag8zWcZUrY1bWrpy9qguxVcQ5t2OhmXV9Xvh5RfADx6km3MqG6Nvb1oI9Zuzy1/B1y/4hUAfHewoKp+nOQa4CEzENMdacnRJwL3pO2q2++uq2jiTOAXwPO79e6OocV8elXduIprDwQ+0Pd+ASbxJEmSJEljxgSe5rO7dMc/95XdjvbnYr+VXLfxJNtfNkH5Daze6NeLu+PdpnJRkmfT1rG7krZm3LnA1bRRhXvQkmfDXLKS8inFMCSm29GmGf8jbf26E2nr5N1ISw4+nVtOcV1BVd2QZEdgCW3TjoO7U5cmORR490SJvG6NwL+vEzhB0laSJEmSpJEygaf5bHF3PK2vbDltxuztV6w+Nr7XHR8HvGMK1y0BrgUeXlW/7T+R5Hkrue6OKymfKEk5WS+jJe/2rap3D8S0Ny2Bt0pVdSnwmiSvpY2Q3BF4LfBO4G+0kXaSJEmSJK2RXANP81KS+wLPoY2+Orrv1A+BTZLcZySBTc5JwO+Ax3QbUEyo26ShZzPgzCHJu7t25yay7ZB2H0Gb6vqzScTbG/22zpBzvft+dTL3XZVqzqyqDwE7d8VPm2o7kiRJkiSNExN4mneSbEObQroBcGBV/bHv9H90x08k2WTItXdOcr85CHNC3XTQVwM3AUd200dXkOSpwFF9RecBmye5U1+dWwGHsfLRuC9K8oC+a9YF3tO9PWISIfc2zrj7kHPndcdtBmJ/PvCkSbRNknsluf+QU73nXGFzC0mSJEmS1iROodXabPMkS7qf16dN+dwKeCBtVNi7gP37L6iq45IcALwdODvJcbQk0ybA5rRRYfvSNk4YmS7OFwEfA76V5MfA94EraImrxbTRbSf2XXZo9/ppkqNof/53pm3mcQaw5QS3OxH4QZIv0JJxT6J9hscDn5lEuN8G3gh8JMmXaJuEnF9VnwM+DbwFOLQbTXge8GDajrhfpq1ptypbAkcnOQ34JW2NwLsBz6B9zwdPfKkkSZIkSePPBJ7WZptx82YU19A2RzgLOAA4oqrOGXZRVb0jyXeAf6GtM3cb4DLg97R15D47m0FPVlV9LsnJtLXeHg+8BNiIFutPgXdzywTbh2jrwb0W2JP2eRwLvBU4ciW3Ohj4GvA62mf6Z+C9wP5VVZOI8xtJ3tzd8y3AesDJwOeq6oIk2wMH0ZJ26wKnd89zDyaXwPtxF89i4Mm07+ti4ATgfVX1o0m0IUmSJEnS2Mok/v4taR7qRi/uB+xQVUtHG83cSLIQWPaZpaez0a0XjDqcNdYzH775qEOQJEmSpDXC8uXLWbRoEcCiqlo+UT3XwJMkSZIkSZLGmAk8SZIkSZIkaYyZwJMkSZIkSZLGmAk8SUNV1ZKqynxZ/06SJEmSpHFlAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaY+uOOgBJGjdPfehmLFy4cNRhSJIkSZIEOAJPkiRJkiRJGmsm8CRJkiRJkqQxZgJPkiRJkiRJGmMm8CRJkiRJkqQxZgJPkiRJkiRJGmMm8CRJkiRJkqQxZgJPkiRJkiRJGmMm8CRJkiRJkqQxtu6oA5CkcbPdvp9nnQ02HHUY0/KT97141CFIkiRJkmaYI/AkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvA065Kcm+TcKdRfkqSSLJ61oGZIksO7WDcddSxru+5zXjrqOCRJkiRJmmsm8NZSSTbtEh7HTXD+zd353yXZbK7jmwlJlnbPMNnX4lHHPE76ko9bDzl3jyRndef3H0V8kiRJkiSpWXfUAWjuJTkQ2Bv4FfD4qrpwxCEN+k/gC8D5q6h3OLB0oGwP4J7AIcDlA+fOXd3A5oMk9wW+CdwD2KuqDhlxSJIkSZIkzWsm8OaRJP8AfBh4BfBD4ElV9ZfRRrWiqroUuHQS9Q4fLOtG2d0T+GBVnTvDoa31kjwUOA7YBNijqj414pAkSZIkSZr3nEI7TyRZD/gcLXl3IrDTYPIuySZJ/j3J75Ncl+SSJF9Mcv8J2lw/yeuS/CjJFUmuTPJ/ST6Q5LZD6m/cnftj1/7Pk+w2pN6MroHXN5348AnOr7C2WpK7JDkkyW+TXJPkL0l+keTDSRZO4p47JlneTVHevK/8wUm+kOSiJNcnOS/JoUk2mSjmJFsk+XKSS/vX20vysCRHJTm/+zz/lOT7SfaexsdEkm2Bk4BFwLOGJe9mOP5nJvl8krOTXJ1kWZLvJnnWFGK+b5KDkpye5LIk1yb5TZL3Jrn1dD4HSZIkSZLGjSPw5oEkGwFHAU8EvgzsXlXXD9TZBPgBsDltWuoXgE2B3YAnJ9m5qr7fV/9WwPHAdsBvgU8C1wH3AV4JfAr4a98t1gNOAG7XxbAR8DzgyCS7VNUJM/rQq6H7vL5He/4TgKOB9YF706boHgQsX8n1uwGfAX4N7FJVF3XlTwOOBG4Evgr8Abg/8BrgCUm2qqq/DjS3Oe17+RVwBO3zuz7JQ4BTu7a+ApwH3AZ4ALAn8N4pPvOTaH3kBuCJVXXSkDozFn937sDu51OAi4A7AE8DjkryL1V16CRC3xV4GS3xuJT2jxJbA28Btk+yXVX9bTKfgSRJkiRJ48oE3tpvES0J9VjgE8D/V1U3Dql3EC3ZcmBVvbVX2I1aOw44IskWVXVTd2p/WvLu08BL+9tMsoiW5Ol3V+A0YIde8jDJ52ijAV/fxTguHgfcC/j3qnp9/4kkC2iJyqGS/DNtDb9TgKdV1bKufBPaZ/Vn4LFVdX7fNbvTRkfuD7x2oMnHAgdU1TsG7vMGYAPg6VX11YFztxgNNwnPA14FLKMl73485LlmNP7Ok6rqdwP3uTUtMXlAko9X1dWriP3TwAeGJKTfAbwTeA7w2YkuTrIB7XPsWbCK+0mSJEmSNOecQrv225qWRPl+Vb1sWPIuyfrA7sBlwLv6z1XV8bSRdvcBHtPVX4c2FXcZ8LrBNqtqWVVdOSSWf+1PtFTVt2gjxx45/cebVdcMFlTVFYPJop4k+9HWGPwa8IRe8q7zYmAhsE9/8qtr8/PA6bRE2qCLGfhOJhHjZSupP8zraCMkXzAsedeZ8fgHk3dd2ZW0zUkWMYl+UVV/nOD7+M/uuNMqmtiH1o97rwtWdU9JkiRJkuaaI/DWfv9Hm1r56CTvqKr9h9TZAtgQWDrBiKelwBOAh9BGlm1BS+acOGTK5EQur6rfDym/AHj0JNuYK9+hJZ726aaqHkt77l9UVU1wzSG06Z8fB14xJFG6de/YvyZen1sBt09y+24Tj54zJkhQHQXsBRyT5EjarrGnDCbXJumbwM7AfyXZoarOG1JnpuMnyR1puyE/kbbxyIYDVe66qsCTBHgpbWrzA2mJv/5/mFhVGwcCH+h7vwCTeJIkSZKkMWMCb+33B+DptDXC3pnkH6pqyUCd3qYMf5qgjYu746LueJvu+McpxLFsgvIbGLORoFW1LMmjaVMwnwo8qTt1QZIDq+rDQy7bFijgaxNMUb5dd3z1Km6/MbfcgXfod1JV30+yI20E2e60BBZJfgK8adgadivxDtoIurcAS7sk3rmzGX+S29GmVP8jbb3BE4HLaVOvH0LrsxsMu3bAf9DW4PsDbV2+i7h5ivN+q2qjqq7rq0/LB0qSJEmSNF5M4M0DVXV22o6uJwH7JUlV7ddXpbchw50maOJOA/Uu7453m8EwZ1Nv3b4V+nu3Xt8KugTWS7rpwg8CHg/8C/ChJH/tpo32eyZt6ueXkjy7qr4ycL732T2oqn45hdgnGvFHVZ0MnJxkQ2ArWrLxVcCxSR5UVedM+iZVeye5EXgrNyfx+kdMznT8L6Ml7/atqnf3n+h20X36qhruRvC9Gvg58Oj+0aNJ7kxL4EmSJEmStMYbq5FPmj1dMmd72ppz70hyQN/ps4BrgUd2O7AO2r47/qw7/pqW0HlkktvOTsQz6vLuOCzh+NCVXVhVN1bVz6rqINpIN2hTZQedByymTb/8UpJnDJz/YXec8enCVXVNVS2tqjcA76FNRV3V2m/D2nkbcABtOuvSJPfuOz3T8W/WHb865Ny2k2zj3kBoU7kHp35Ptg1JkiRJksaeCbx5pBtRtRg4F9g3ybu78uuBzwO3p03J/LskO9HWKDubNtWRqroB+AhtSu0h3Si1/msWdbuJjoWqWg78Btimf/22bkfZAwfrJ3lgknsOaao3EnGFjSO6+/SSeH8AjkzyzL7TnwSuAN6d5AFD7rlRkq0HyyeSZNskC4ecWmmMq9LtFruENjpuaZJeom1G46clPAG2GWjn+dw8ZXmybTwmyd9/lyW5O/DeKcQiSZIkSdJYcwrtPFNV5ybZnjad9q3dmnj70NY/256W2HsMbcTVpsBuwNXAS6vqpr6m3kHb2OBFtI0NvkFbS+zewC60xMzP5uShJucDwH8B30/yJVry+onAsF1XdwIOTvI92ujEy2jP9TRaYuw/h1wDQFWd301XXgp8McnzqurLVfXnJLsDXwLOSHJc1/ataCPetgdOpX12k/EGYOckJwG/o42gfBjwOFqy9ehJtjPsGd6Z5CZgf26eTnv2DMf/aVqfOzTJDrRk3INpn/2XgV0nEedFSf4HeBbw4yTfoiUwnwJ8m/adSZIkSZK0xjOBNw/1JZlOAvbuknhvSbIV8Hba+mPb0jae+ArwzsF1z6rq2iQ70zYQeCGwJ20DgvNpibJz5+ZpJqeqPpJkPeB1wMtpmx0cDrwLGNwl9Xha8nI7WiLp1rQNO74AHFRVZ67iXn/okqRLuTmJ9z9VdWyShwJvoiWqdgauok27/STwmSk80mG072erLs7QPvt3AR+sqium0NawZzigWxPv3dycxJux+Kvqgu4zOqhra13aRhqPB+7BJBJ4nT1ofe1ZwGtpn8EHgH9jxe9VkiRJkqQ1UqomXCNfkuaVblrysi1f+1+ss8GGow5nWn7yvhePOgRJkiRJ0iQtX76cRYsWASzqlgAbyjXwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaYybwJEmSJEmSpDFmAk+SJEmSJEkaY6mqUccgSWMhyUJg2bJly1i4cOGow5EkSZIkreWWL1/OokWLABZV1fKJ6jkCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpjJvAkSZIkSZKkMWYCT5IkSZIkSRpj6446AEkaN8ed+VE2uvWGow5jqKc84FWjDkGSJEmSNMccgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgSdJkiRJkiSNMRN4kiRJkiRJ0hgzgTciSQ5PUkk2neb1lWTpzEYlrVqSpUlq1HFIkiRJkjRfmMBbTUk27ZJp/a+/JfljkiOTPGLUMc6FXlKn73VTkr8m+U6SPZJk1DFOR5oXJvl2ksuSXJ/kT0l+muTDSbYfdYzzQZLFXb9aMupYJEmSJEmaa+uOOoC1yDnAZ7qfNwYeDjwbeEaSnarqOwP19wHeC/xxmve7H3D1NK+dTQcDVwLrAPcGdgW2pX0erx1hXNP1CWAP4K/A/wIXArcH7gu8DFgInDyq4EbkxcBGow5CkiRJkqT5wgTezDm7qpb0FyTZGzgQOAC4xUitqroIuGi6N6uqs6Z77Sx7f1Vd3HuT5EHAD4FXJ/lAVf1+dKFNTZJtacm7nwHbV9XygfO3Ae4/54GNWFWdP+oYJEmSJEmaT5xCO7s+3h0fPnhiojXwkjwryclJLklybZI/JDkuyTMG6q2wBl5/m0leleTMro3zkuyXZIXvO8lGSQ7q7nNtkl8m2XOmpixW1S9oI9TS+xxWtobasM+lm4Jb3fFxSU5JclU3pfWIJJtM0NaDk3whyUXd1Nfzkhw6Uf0hHt0djxhM3nXPdnlVnTpwz9V5tmcmOS3J1UkuTnJYkttO0Na9knwsyflJruue8fAk9xxSt7q47tbVubib4ry4O79ukn2SnNP1gbO79/furj18Vc+YZFGSt3R998Lu874wyaeSbDYkpiVd24uTPCfJ6Umu6Z7jP5Js2F8XOKl7u19uOVV7077775/k/5JcmWRZkrOSfDLJPYZ9hpIkSZIkrSkcgTc3bphMpST/DHyYNjLvaOAy4C7Ao4BnAMdM8n7vAxbTpnye0F27BFgfeFvf/dbp6uwAnAF8DrgdbRrs0kneay49FXgK8DXgMGA72nTOzYBt+ismeRpwJHAj8FXgD7TRcq8BnpBkq6r66yru95fuuPlMPcBK7AbsDHwJOJE2YvOVwKOTPLqqrulVTLIVcDxtqvbXgLOBTYEXAE/s6v9uoP1NgO/TnumLtL7QS0p+AngRbRr4h4ANgL24OYE5GfcD9qcl2o4GrgK2AJ4PPDnJw6rqvCHXvRp4IvAVWp/bhTbVepPueejKNwVeQksGL+27/vIkoX0eWwHfA44DbuqueSZwBO37lyRJkiRpjWQCb3a9ojueMsn6LweuB7asqj/3n5jCqDFoI90e3E3TJckBwG+B1yZ5Z1Vd39Xbg5a8+yrwzKq6qat/MPDTKdxvQmlTaLcHCvjxajb3NGBxVX2va3sdWrJrcZKtq+oHXfkmwKeBPwOP7Z/ymWR3WqJyf1a9Jt/xwBXAPydZQEtM/aSqZiMZ9GRgp6r6Vl+snwBeCryRNg2bJOsBX6CNnn1EVZ3RV38bWnLrEFqys98DgU8Ce1bVjX3XPI6WvPsxsF0vUZjkXUytD5wJ3KWq/tJfmGQH2ne0L7DnkOt2Bh5eVb/u6r+NNmV59yRvqqoLq2ppy9HxEmDpkKnqD6Il746uql0Hzm0ArDdR0N35DfqKFqz6USVJkiRJmltOoZ05m3fTApckeV/a9NYDgEuAN02hnb91r1uoqsum0MYBveRdd+2ltBFOC4B/6qv3wu749l7yrqt/Fm3U0nS8sfsMDkjyWeBHwIbAoVV17jTb7PlcL3nXxXljX5yP7Kv3YtrmEvsMrtdWVZ8HTgeet6qbdYm6Z9M2GnkxLYF3ftr05i8m2XF1HmbAN/uTd519aX3hJX1lT6GNLDuoP3nXxXsK7Xt+UpKFA21dD7y5P3nX6fWBA/pH+XXrGB4y2eCratlg8q4rPwn4FbDTBJce0kvedfWvAT5P35TrKbhmsKCqrquqK1dyzT7Asr7XBVO8pyRJkiRJs84ReDNnM2C/gbJLgG2r6jeTbONI2s60v0zyBdpoqlOq6vIpxnL6kLJeYuI2fWVbAldV1c+H1D+Vm0cQTsUbumPRpmieRlsL8FPTaGvQZJ9r694xybDpr7cCbp/k9l1yc0JVdXySe9OmJG9HSyptAzwHeE6SA6vqrZN/hAl9d8i9L0xyDrBFkgVVdQU3P9sWGb4+4Z1pifn7cssRj7+f4Fm37I6nDjk3rGxC3Zp6e9FGw92eW/5+uX7FK4DJf6crcybwC+D53Xp3x9A+z9OHJCwHHQh8oO/9AkziSZIkSZLGjAm8mXN8Ve0CkOQOtFFT/wYck+RRqxgF1HMQbd27VwKvpyXDbkjydWCvKezgumxIWW8dvnX6yhYy8dpgf5rkvQbdpX8X2hk22ee6XXd89Sra2xhYaQIPoKpuoE0DPRHapg+06ceHAfskOaqqhiWipuKSCcr/RFtLbiFtOm/v2V4wQf2ejYe0M8xC2npxw0Z4TroPJHk2bW29K2lTj88FrqYlcvcAVthcozPZ73RCVXVDNxpyCbArbQ1HgEuTHAq8e6JEXlVdB1zX9xyTuaUkSZIkSXPKKbSzoKr+XFXvB95DW9z/XZO8rqrqY1X1COAOtAX4v0xb++3Ybs23mbS8u88wd5rhe/XrrbU3LIG8aAba723O8KCqykpewzZVWKWquqGqPkZbSw/aOoI90322O05Q3vselg8cn7qKZzt5MOwJ2l9O+z0wbI3FqfSBJcC1tPXsnl1Vb6qq/br16q6dQjvTUlWXVtVrgLtx82YllwHvBN482/eXJEmSJGk2mcCbXe8BLgRelWTTqVxYVZdV1TFV9Vzg27RE4EzvhnoGsHGSBw8595gZvle/3u6vd+svTPIP3Dylc3X8sDtOZRfV6bhqSNl0n23bwYIkd6VNzT6nmz4LM/9svXX0hn3fU+kDmwFnVtVv+wv7nmF19UbQrTSJ3SXBz6yqD9E2yICWAJckSZIkaY1lAm8WdQvy/xttF8y3r6p+kicMjtzqdh3tTZtcYZH+1fTZ7nhAl2Dq3XMLbrlxwkzrrc22x0D564F7zUD7n6RNN313kgcMnkyyUZKtV7xshXq7JHn6sNF0Se4L7Na97d9leLrPtnO3I2y/d9H6Tv+GIl8Bzgden2S7IXGt1+1GO1m9PvD2JLfqa+fOwOum0M55tI1c/j5qr2vvMGZmqn5vg4y7D55Icq8k9x9yTS+Wmf5zI0mSJEnSnHINvNn338BbgBcneU9VnbOSul8Erk5yCi0hsh5tFNH9gS8O7qg6Az4JvIg2QuknSY6nJQufB3wTeCrdlNBZuO+bgSVJHgKcAzwCeCBwMrD96jReVX9OsjvwJeCMJMcBZ9E2r7hn1/6pwC6raGoL4N9pa6l9p4sztJGQTwLWBw6rqh/2XTPdZzsW+HqSL9HWJdyeNsruDOD9fc92XZLdgG8AJyf5FvDL7vQ/0kbyXdbFvkpVdWK3W/ALgF8k+QqwAW2Tjh8y+T5waPf6aZKjaL9bdqZ9Xmew+iMrz6KNZn1ekqtpG00ULUG4JXB0ktNon8XFtBGQz6CN3Dt4WIOSJEmSJK0pHIE3y6rqWtpOl+uy4i61g/ah7dr6KNoaXi+kjSR7RffzTMd2Iy0RdTBtDba9gMfSNs/ojfpaPvTi1bvvxcCOwLeAxwN7ApfTdlg9d4bucSzwUOBwWvLstcDzaQm8TzKJEZG00Wl70nYDfgBtc5HX0XZZPQHYrapeNXDf6T7bUbTE6Ra072Ez4CPAjt1Izv57nEZLWh1CS9q9Enhpd+0xwC1imoQ9aJ/HOrTP6UnAB7l57cbJ9IEPdXH8hfbMz6QlLB9De/7V0vXVXWlJxRfRpqcfCNyWNurxvbRk3ZNp/Xcx7Tt6TNcXJEmSJElaY6VqorXtNZ8leRfwNuBJVfWNUceztkqyBy2h+NKqOny00dxSkpcDHwVeVVWHjTqeuZBkIbDsiz94PxvdesNRhzPUUx4w1fysJEmSJGlcLV++nEWLFgEsqqoJB9A4Am+eS3KXIWX3B/6FNnJqcDdTrWWS3DlJBsruBuxLG9X2vyMJTJIkSZIkAa6BJzis2yH3R7QdVDejrXu2HvCyqrp6hLFpbuwNPDnJd4FLaNNynwIsAJZU1R9GGZwkSZIkSfOdCTx9ibZ22a7AIuBK2qi7g6vq+FEGpjlzHG2jlCfT1pS7Fvg58OGq+twoA5MkSZIkSSbw5r2q+ixtswaNQLfu3eEjjuE4WhJPkiRJkiSNIdfAkyRJkiRJksaYCTxJkiRJkiRpjJnAkyRJkiRJksaYCTxJkiRJkiRpjKWqRh2DJI2FJAuBZcuWLWPhwoWjDkeSJEmStJZbvnw5ixYtAlhUVcsnqucIPEmSJEmSJGmMmcCTJEmSJEmSxti6ow5AksbN8uUTjlqWJEmSJGnGTPbvn66BJ0mdJJsCvx91HJIkSZKkeefuVfXHiU46Ak+SbvaX7nh34IpRBqJ5bQFwAfZDjZ59UePAfqhxYV/UOLAfrr0WABeurIIJPEla0RUr2/1Hmk1Jej/aDzVS9kWNA/uhxoV9UePAfrhWW+X36SYWkiRJkiRJ0hgzgSdJkiRJkiSNMRN4knSz64B3dkdpVOyHGhf2RY0D+6HGhX1R48B+OI+5C60kSZIkSZI0xhyBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ2neS/LIJF9P8tckVyX5UZLnjzourV2S3C3JXklOSHJ+kuuTXJzkf5JsNcE1C5N8IMl5Sa7rjh9IsnCu49faK8mbk1T32nqCOvZFzZokz0zyzSSXJbkmye+TfD7JPQbq2Q81K9LsmuSkJBcluTrJr5N8JMm9h9S3L2rakryw61s/7vpPJdljJfWn3N+SPL/7O81V3d9xvp7kEbPyQJoz7kIraV5Lshg4Hrge+AKwDNgVuBfwtqp6z8iC01olyXuBtwDnACcDlwD3AZ4BBNi9qo7sq78xcArwEOCbwOnAlsAuwM+Abarqqjl7AK2VktwP+ClwA7Ax8Oiq+sFAHfuiZkWSAP8F/H+0343HA1cAdwW2B15QVad0de2HmjVJDgZeD1wEfAVYTutfjweuBB5TVb/s6toXtVqSnAvcE7gUuKr7+aVVdfiQulPub0neCrwbOB84Crg18DzgVsATqmrpjD+U5kZV+fLly9e8fAHrAmcD1wIP7StfAPwS+Btwn1HH6WvteNESw9sOKd+WlkC+DNigr/ydQAH/NlC/V/7OUT+TrzX7BawD/Aj4IfDprl9tPaSefdHXrLyAf+n60H8C6ww5v27fz/ZDX7PyAu4M3Aj8Hlg4cG6vrn99oq/MvuhrtV7ATsA9u5/37vrNHhPUnVJ/o/3j8N+AXwOL+sofQEsWnt3/u9XXmvVyBJ6keSvJ42n/2v/Jqvp/A+eeSxuRd2BVvXUU8Wn+SHI87V/5H1lVP+5GpVwALATuXH3/sprkVsCFwNXAPcr/kGuaun+h3w94GPAm4CUMjMCzL2q2JNmQ1rcuB/6pqm5YSV37oWZNt3TA94HPVtULB87dB/gNcGxVPcW+qJmWZG/gQIaMwJtOf0vyHmAf4CVV9amB9g4DXkkbhXfCrD2UZo1r4EmazxZ3x2H/AeuVbT83oWie+1t37P0F9j60KWTfq4FpEVV1LfAd4G7A5nMWodYqSR5IS969q6p+tZKq9kXNlp2B2wHHAOt064/tneSVSQb7k/1Qs+m3tJHwj02yYODck7rjt7ujfVFzaTr9bXF3HPb3m+O7o3+/WUOtO+oAJGmE7tMdfzt4oqr+muTSvjrSrEjyj7SpFBcDv+iKJ+ybA+X3WUkdaagk6wKHA2cC711FdfuiZktvMfUbgDOAf+o7d1OSf6+qN3bv7YeaNVV1WZK3Ae8DzkzyVdpajA+i/ff5v4FDu+r2Rc2l6fS3+wBXVtXFq6ivNZAJPEnz2aLuuGyC88uBu89RLJqHkqxHW3tsA+DNVXVjd2oyfbO/njQVb6UtgL1VVf1tFXXti5otd+yOb6Atyv4oWlL5obSEyRuSnFNVh2E/1CyrqvcnuRD4CPDPfadOBT7T97vSvqi5NJ3+toi2Udpk62sN4hRaSZJGIMk/AJ8AtgM+WlWfHnFImgeSbAnsC7y/qk4fdTya13p/D7keeEZVnVZVV1bVd4HdgJtoyT1p1iXZlzYy+UDgHrRdO7ehDXg5Kcmuo4tOkhoTeJLms96/Zk30r1ALmfhfvKRp6xYl/ijwQuAztAWF+02mb/bXkybrCOAcYMkk69sXNVt6febHVXVh/4luXcbfAZsluQ32Q82iJDsCBwD/WVXvqaoLquqqqvoe8BTgGuDfu+r2Rc2l6fS3ZVOsrzWICTxJ89mE60AkuS1we1y/RDOsG3n3ceD/AZ8H9qiqmwaqrWqNklWtiSJNZEtgC+DaJNV70XagBfh+V/aM7r19UbPl193x8gnO98o3xH6o2fXk7njS4Imq+jNtfdp/TNL//4X2Rc2F6fS33wK3TnLnSdbXGsQ18CTNZyfTtll/PPCFgXOP76sjzYguefcx4KXAF4EX9a171++3wIW0HfE27t95LMmtaNNuLwTOnv2otZb5+ATl29H+x/6rwJ+Bc7ty+6JmSy9Zcr/BE936oJsDV9H648XYDzV71u+Od5jgfK/8OvydqLk1nf52MvBo2t9lPjXQ3hP66mgN5Ag8SfPZt2hTdJ6f5CG9wiQLgLfTdsY7fCSRaa3TN/LupcCXgBdOkLyjqoqW6Ls18I6B0/sAtwU+1tWTJq2qXj7sRVuoHeDAruxnXX37omZFVZ0DnABsnuTlA6f3Bm4DHF1VN9gPNcu+1x1fn+QWUw+TvISWTP5JVV1hX9RcmmZ/+yTt7zBv6+/PSR4AvJi2jMa3ZzNuzZ74u0XSfJZkB+B42r+qfp62O9OuwL2Afavq3SMMT2uRJEuA/YArgUNo/3M16Jhe4iTJxsApwEOAbwI/oU1/fCLwM2Cb/n+JlVZHksNp02gfXVU/GDhnX9SsSLIZLXl8R+BY4CzaLrQ7AucBW1fVxV1d+6FmRZJ1gBOBxbQRn18F/krrXzvT/h9xp6o6patvX9Rq6f7RYpvu7YOAh9ESyb2RdMdU1TFd3Sn3tyRvA94FnA8cBWwM7E5bkuAJVbXCdHGtGUzgSZr3kjwKeCdtuPn6wK+AD1bVZ0camNYqfQmSlXlpVR3ed80iWtJvN+DOtGlkRwHvrCoXINaMWVkCrztvX9SsSHIPYH9gF2ATWt/6KrB/VV0yUNd+qFmRZAPgdcBzaeuErg/8iTbV8MCq+uVAffuipm0S/0/4zqpa0ld/yv0tyQuAvYAH0Hb7/j7wjqo6bfWfQKNiAk+SJEmSJEkaY66BJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJi3J4iSVZMmoY5Ekab4wgSdJkiRJkiSNsVTVqGOQJEmStIZIshHwj8ClVXXpqOORJGk+MIEnSZIkSZIkjTGn0EqSJEnzSJLbJbkxyTED5Y/s1rarJHcfOPfDJFckWXeiNfCSnNu9Nk7ygSR/THJdkp8n2W1IHIuS7J/k/5JcmWRZkrOSfDLJPWbj2SVJWlOZwJMkSZLmkar6C/BzYPsk/X8fWNz38w69H5IsAB4GfLeqblhF8+sBJwBPBL4MfAbYDDgyyeP72gxwPPB24C/AfwMfBX4JPLO7RpIkddYddQCSJEmS5txJwL8CDwFO78p2AH4B3Kn7+dNd+ba0vzecNIl27wqcBuxQVdcDJPkccCLwelpyD+CBwFbA0VW1a38DSTagJQIlSVLHEXiSJEnS/LO0O+4IkGRdYBvg2925Hfvq7jBwzar8ay95B1BV3wLOAx45pO41gwVVdV1VXTnJe0mSNC+YwJMkSZLmn+8AN3Fzcu4RwALaKLuTgHsmuVd3bgdgOTeP1FuZy6vq90PKLwBu0/f+TNpov+cn+U6S13dr8K0z5SeRJGkeMIEnSZIkzTNVdTnwU2DbbvTdDrSE3ne4earsDkkWAQ8FvlNVN06i6WUTlN9A3989urX0dgQ+BGwOHAz8CLg4yTtM5EmSdEsm8CRJkqT56STaqLuH0zaw+FlV/bWqfg1cSEvqbUf7O8Nk1r+bkqq6tKpeA9wNuD/wGuAy4J3Am2f6fpIkrclM4EmSJEnz09Lu+ATgsbT173pOoiXwprr+3ZRVc2ZVfQjYuSt+2mzdT5KkNZEJPEmSJGl++i5wI23k28bccpTdSbSRcS8ELgd+NpM3TnKvJPcfcupO3XGFzS0kSZrP1h11AJIkSZLmXlUtT/IT4FG0RN53+073knl3AL5SVTfN8O23BI5OchrwS+BiWsLwGV0sB8/w/SRJWqM5Ak+SJEmav3qJuh9X1RW9wqr6HXBe93bpLNz3x8B7acm6JwNvoK3DdwLwmKo6dhbuKUnSGitVNeoYJEmSJEmSJE3AEXiSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI0xE3iSJEmSJEnSGDOBJ0mSJEmSJI2x/x9yDPlyyw4+KgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Total Victories of IPL Teams\")\n",
    "sns.barplot(x='wins', y='team', data=team_wins_df, palette='Paired');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1941223",
   "metadata": {},
   "source": [
    "### Observations:\n",
    "\n",
    "* Mumbai Indians is the most successful team(as they have won the maximum number of IPL matches -109) followed by Chennai Super Kings and Kolkata Knight Riders.\n",
    "\n",
    "## Most Valuable Player\n",
    "Winning matters the most in a competitive league match. If a player makes the most significant contribution to his team’s victory, then he’s chosen as the player_of_match. The player who has won the player_of_match title on most occasions is the most valuable player."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "71b9a8a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "mvp_ser = ipl_matches_df['player_of_match'].value_counts()\n",
    "\n",
    "mvp_ten_df = pd.DataFrame(columns=[\"player\", \"wins\"])\n",
    "count = 0\n",
    "for items in mvp_ser.iteritems():\n",
    "    if count>9:\n",
    "        break\n",
    "    else:\n",
    "        temp_df2 = pd.DataFrame({\n",
    "            'player':[items[0]],\n",
    "            'wins':[items[1]]\n",
    "        })\n",
    "        mvp_ten_df = mvp_ten_df.append(temp_df2, ignore_index=True)\n",
    "        count += 1    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7666b867",
   "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>player</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DA Warner</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SR Watson</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SK Raina</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>G Gambhir</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           player wins\n",
       "0        CH Gayle   21\n",
       "1  AB de Villiers   20\n",
       "2       RG Sharma   17\n",
       "3        MS Dhoni   17\n",
       "4       DA Warner   17\n",
       "5       YK Pathan   16\n",
       "6       SR Watson   15\n",
       "7        SK Raina   14\n",
       "8       G Gambhir   13\n",
       "9      MEK Hussey   12"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mvp_ten_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "42ae48d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Top Ten IPL Players\")\n",
    "sns.barplot(x='wins', y='player', data=mvp_ten_df, palette='Paired');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ade2f737",
   "metadata": {},
   "source": [
    "### Observations:\n",
    "\n",
    "* Cris Gayle is the player who won the most player of the match awards and hence is the most valuable player.\n",
    "* Six Indian players have figured in the top ten IPL players list.\n",
    "\n",
    "## The team that won the most number of toss\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5a03d819",
   "metadata": {},
   "outputs": [],
   "source": [
    "toss_ser = ipl_matches_df['toss_winner'].value_counts()\n",
    "\n",
    "toss_df = pd.DataFrame(columns=[\"team\", \"wins\"])\n",
    "\n",
    "for items in toss_ser.iteritems():\n",
    "    temp_df3 = pd.DataFrame({\n",
    "        'team':[items[0]],\n",
    "        'wins':[items[1]]\n",
    "    })\n",
    "    toss_df = toss_df.append(temp_df3, ignore_index=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8cd851c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           team wins\n",
       "0                Mumbai Indians   98\n",
       "1         Kolkata Knight Riders   92\n",
       "2           Chennai Super Kings   89\n",
       "3   Royal Challengers Bangalore   81\n",
       "4               Kings XI Punjab   81\n",
       "5              Delhi Daredevils   80\n",
       "6              Rajasthan Royals   80\n",
       "7           Sunrisers Hyderabad   46\n",
       "8               Deccan Chargers   43\n",
       "9                 Pune Warriors   20\n",
       "10                Gujarat Lions   15\n",
       "11               Delhi Capitals   10\n",
       "12         Kochi Tuskers Kerala    8\n",
       "13      Rising Pune Supergiants    7\n",
       "14       Rising Pune Supergiant    6"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toss_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e9a8e8d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"How IPL Teams fared in toss?\")\n",
    "sns.barplot(x='wins', y='team', data=toss_df, palette='Paired');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10ff35c3",
   "metadata": {},
   "source": [
    "### Observations:\n",
    "\n",
    "* Mumbai Indians has won the most toss(till 2019) in IPL history.\n",
    "* All the top teams in IPL are successful in winning the toss as well.\n",
    "\n",
    "## Asking and Answering Questions\n",
    "\n",
    "Let’s try to find answers to the questions that will linger in an IPL fan’s mind. In Part I, we are dealing with some very basic questions. In Part II, we will delve deeper.\n",
    "\n",
    "**Q1: Does the presence of the most valuable players in a team ensures the IPL trophy?** \n",
    "\n",
    "We have figured out the top ten players of IPL using the ‘Player of the Match’ title as the yardstick. It is interesting to note that the top two players — Chris Gayle and AB de Villers have never won an IPL. **Of the top ten players, 6 players(RG Sharma, MS Dhoni, DA Warner, SR Watson, SK Raina, and G Gambhir) have won the IPL.** It exemplifies the importance of the presence of the most valuable player(s) in a team."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "25a17f4d",
   "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>player</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DA Warner</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SR Watson</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SK Raina</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>G Gambhir</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           player wins\n",
       "0        CH Gayle   21\n",
       "1  AB de Villiers   20\n",
       "2       RG Sharma   17\n",
       "3        MS Dhoni   17\n",
       "4       DA Warner   17\n",
       "5       YK Pathan   16\n",
       "6       SR Watson   15\n",
       "7        SK Raina   14\n",
       "8       G Gambhir   13\n",
       "9      MEK Hussey   12"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mvp_ten_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eee05ab8",
   "metadata": {},
   "source": [
    "**Q2: Which umpire has officiated the most number of IPL matches on-field?**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f57b21ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "umpire1_ser = ipl_matches_df['umpire1'].value_counts()\n",
    "umpire2_ser = ipl_matches_df['umpire2'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "da94fd36",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HDPK Dharmasena</th>\n",
       "      <td>73.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asad Rauf</th>\n",
       "      <td>51.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Ravi</th>\n",
       "      <td>49.0</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK Chaudhary</th>\n",
       "      <td>43.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aleem Dar</th>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K Srinivasan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KN Anantapadmanabhan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD Ranade</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nand Kishore</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Subroto Das</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>75 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      umpire1  umpire2\n",
       "HDPK Dharmasena          73.0     14.0\n",
       "Asad Rauf                51.0      NaN\n",
       "S Ravi                   49.0     57.0\n",
       "AK Chaudhary             43.0     15.0\n",
       "Aleem Dar                38.0      NaN\n",
       "...                       ...      ...\n",
       "K Srinivasan              NaN      3.0\n",
       "KN Anantapadmanabhan      NaN      3.0\n",
       "SD Ranade                 NaN      2.0\n",
       "Nand Kishore              NaN      1.0\n",
       "Subroto Das               NaN      1.0\n",
       "\n",
       "[75 rows x 2 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umpires_df = pd.concat([umpire1_ser, umpire2_ser], axis=1)\n",
    "umpires_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d3ab827b",
   "metadata": {},
   "outputs": [],
   "source": [
    "umpire_ser = umpires_df.sum(axis=1)\n",
    "\n",
    "umpire_df = pd.DataFrame(columns=[\"umpire\", \"matches\"])\n",
    "\n",
    "for items in umpire_ser.iteritems():\n",
    "    temp_df4 = pd.DataFrame({\n",
    "        'umpire':[items[0]],\n",
    "        'matches':[items[1]]\n",
    "    })\n",
    "    umpire_df= umpire_df.append(temp_df4, ignore_index=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a520c6d0",
   "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>umpire</th>\n",
       "      <th>matches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S Ravi</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             umpire  matches\n",
       "2            S Ravi    106.0\n",
       "0   HDPK Dharmasena     87.0\n",
       "11    C Shamshuddin     73.0\n",
       "3      AK Chaudhary     58.0\n",
       "57       SJA Taufel     55.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umpire_df.sort_values('matches', ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84319e8a",
   "metadata": {},
   "source": [
    "**S. Ravi(Sundaram Ravi) has officiated the most number of IPL matches on-field**, followed by former Sri Lankan international cricketer HDPK Dharmasena.\n",
    "\n",
    "**Q3: Which team is the most successful team in IPL?**\n",
    "\n",
    "Nothing succeeds like success. In a game of cricket, winning is everything. We have narrowed down on the list of teams that made the most number of wins in each season. The DataFrame win_per_season_df gives the required information. Mumbai Indians has secured the most wins in four seasons(2010, 2013, 2017, and 2019). Mumbai Indians won the IPL trophy in 2013, 2015, 2017, and 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "77151cac",
   "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>year</th>\n",
       "      <th>team</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year                   team wins\n",
       "0  2008       Rajasthan Royals   13\n",
       "0  2009       Delhi Daredevils   10\n",
       "0  2010         Mumbai Indians   11\n",
       "0  2011    Chennai Super Kings   11\n",
       "0  2012  Kolkata Knight Riders   12\n",
       "0  2013         Mumbai Indians   13\n",
       "0  2014        Kings XI Punjab   12\n",
       "0  2015    Chennai Super Kings   10\n",
       "0  2016    Sunrisers Hyderabad   11\n",
       "0  2017         Mumbai Indians   12\n",
       "0  2018    Chennai Super Kings   11\n",
       "0  2019         Mumbai Indians   11"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_per_season_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2441212",
   "metadata": {},
   "source": [
    "Mumbai Indians secured the most number of wins(109) in IPL, followed by Chennai Super Kings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9425ceb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           team wins\n",
       "0                Mumbai Indians  109\n",
       "1           Chennai Super Kings  100\n",
       "2         Kolkata Knight Riders   92\n",
       "3   Royal Challengers Bangalore   84\n",
       "4               Kings XI Punjab   82\n",
       "5              Rajasthan Royals   75\n",
       "6              Delhi Daredevils   67\n",
       "7           Sunrisers Hyderabad   58\n",
       "8               Deccan Chargers   29\n",
       "9                 Gujarat Lions   13\n",
       "10                Pune Warriors   12\n",
       "11       Rising Pune Supergiant   10\n",
       "12               Delhi Capitals   10\n",
       "13         Kochi Tuskers Kerala    6\n",
       "14      Rising Pune Supergiants    5"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_wins_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeb2d334",
   "metadata": {},
   "source": [
    "Of all the IPL matches played till 2019, Mumbai Indians has emerged victorious in the most number of games. They have secured most wins in four seasons and have won four IPL trophies so far. **Hence Mumbai Indians is the most successful team in IPL.**\n",
    "\n",
    "**Q4: Which city has hosted the maximum number of IPL matches?**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "bad9658c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai            101\n",
       "Kolkata            77\n",
       "Delhi              74\n",
       "Bangalore          66\n",
       "Hyderabad          64\n",
       "Chennai            57\n",
       "Jaipur             47\n",
       "Chandigarh         46\n",
       "Pune               38\n",
       "Durban             15\n",
       "Bengaluru          14\n",
       "Visakhapatnam      13\n",
       "Centurion          12\n",
       "Ahmedabad          12\n",
       "Rajkot             10\n",
       "Mohali             10\n",
       "Indore              9\n",
       "Dharamsala          9\n",
       "Johannesburg        8\n",
       "Cuttack             7\n",
       "Ranchi              7\n",
       "Port Elizabeth      7\n",
       "Cape Town           7\n",
       "Abu Dhabi           7\n",
       "Sharjah             6\n",
       "Raipur              6\n",
       "Kochi               5\n",
       "Kanpur              4\n",
       "Nagpur              3\n",
       "Kimberley           3\n",
       "East London         3\n",
       "Bloemfontein        2\n",
       "Name: city, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl_matches_df['city'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0d895708",
   "metadata": {},
   "outputs": [],
   "source": [
    "city_ser = ipl_matches_df['city'].value_counts()\n",
    "\n",
    "city_df = pd.DataFrame(columns=['city', 'matches'])\n",
    "for items in city_ser.iteritems():\n",
    "    temp_df6 = pd.DataFrame({\n",
    "        'city':[items[0]],\n",
    "        'matches':[items[1]]\n",
    "    })\n",
    "    city_df = city_df.append(temp_df6, ignore_index=True)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "30de72fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Cities that hosted IPL matches\")\n",
    "sns.barplot(x='matches', y='city', data=city_df);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6a7e435",
   "metadata": {},
   "source": [
    "The city of Mumbai has hosted the maximum number of IPL matches.\n",
    "\n",
    "**Q5: Does winning the toss has any advantage?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "93be8b84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of times the team winning toss have won: 393\n",
      "The probability of winning if won the toss: 0.52\n"
     ]
    }
   ],
   "source": [
    "win_count = 0\n",
    "for index, value in ipl_matches_df.iterrows():\n",
    "    if(value['toss_winner']==value['winner']):\n",
    "#         print(value['winner'])\n",
    "        win_count += 1\n",
    "\n",
    "print(f'The number of times the team winning toss have won: {win_count}')\n",
    "prob = win_count/len(ipl_matches_df)\n",
    "print('The probability of winning if won the toss: {:.2f}' .format(prob))    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c385e3f1",
   "metadata": {},
   "source": [
    "**The probability of winning when the team had won the toss is 52%.** So winning toss gives a slight edge over the opponent. However, it would be naive to term winning the toss as a greater advantage as there were 363 instances when the team losing the toss has won the game.\n",
    "\n",
    "**Q6: What are the major victories in IPL? Is it better to defend or chase in IPL?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "17dc11f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "756"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ipl_matches_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "49c6da65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "118      1\n",
       "130      1\n",
       "60       1\n",
       "87       1\n",
       "62       1\n",
       "      ... \n",
       "1       10\n",
       "10      11\n",
       "4       11\n",
       "14      13\n",
       "0      419\n",
       "Name: win_by_runs, Length: 89, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "defend_vict_ser = ipl_matches_df['win_by_runs'].value_counts()\n",
    "defend_vict_ser.sort_values(ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edcdf801",
   "metadata": {},
   "source": [
    "* Of the 756 IPL matches played from 2008 to 2019, **419 matches were won chasing the target. Hence, more victories were registered by teams chasing a total(batting second) than defending the total.**\n",
    "\n",
    "* **When defending a total, the biggest victory was by 146 runs.** Let’s find out that particular match."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "1ee36128",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id                               44\n",
      "season                         2017\n",
      "city                          Delhi\n",
      "date                     2017-05-06\n",
      "team1                Mumbai Indians\n",
      "team2              Delhi Daredevils\n",
      "toss_winner        Delhi Daredevils\n",
      "toss_decision                 field\n",
      "result                       normal\n",
      "dl_applied                        0\n",
      "winner               Mumbai Indians\n",
      "win_by_runs                     146\n",
      "win_by_wickets                    0\n",
      "player_of_match         LMP Simmons\n",
      "venue              Feroz Shah Kotla\n",
      "umpire1                 Nitin Menon\n",
      "umpire2                   CK Nandan\n",
      "Name: 43, dtype: object\n"
     ]
    }
   ],
   "source": [
    "score = 146\n",
    "for index, row in ipl_matches_df.iterrows():\n",
    "    if(row['win_by_runs'] == score):\n",
    "        print(row)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2e620a2",
   "metadata": {},
   "source": [
    "**The greatest victory in IPL on defending a total is for Mumbai Indians when they defeated Delhi Daredevils by 146 runs on 06 May 2017 at Feroz Shah Kotla stadium, Delhi.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b25ee437",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     350\n",
       "6      85\n",
       "7      80\n",
       "5      71\n",
       "8      54\n",
       "4      41\n",
       "9      37\n",
       "3      18\n",
       "10     11\n",
       "2       6\n",
       "1       3\n",
       "Name: win_by_wickets, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chasing_vict_ser = ipl_matches_df['win_by_wickets'].value_counts()\n",
    "chasing_vict_ser"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4ce41ad",
   "metadata": {},
   "source": [
    "* Of the 756 IPL matches played from 2008 to 2019, **350 matches were won defending the total.**\n",
    "\n",
    "* When chasing a target, **the biggest victory was by 10 wickets**(without losing any wickets). There were 11 such instances and we can find the details about those matches by the following code snippet:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "1ad39941",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id                                                      3\n",
      "season                                               2017\n",
      "city                                               Rajkot\n",
      "date                                           2017-04-07\n",
      "team1                                       Gujarat Lions\n",
      "team2                               Kolkata Knight Riders\n",
      "toss_winner                         Kolkata Knight Riders\n",
      "toss_decision                                       field\n",
      "result                                             normal\n",
      "dl_applied                                              0\n",
      "winner                              Kolkata Knight Riders\n",
      "win_by_runs                                             0\n",
      "win_by_wickets                                         10\n",
      "player_of_match                                   CA Lynn\n",
      "venue              Saurashtra Cricket Association Stadium\n",
      "umpire1                                       Nitin Menon\n",
      "umpire2                                         CK Nandan\n",
      "Name: 2, dtype: object\n",
      "id                                                                35\n",
      "season                                                          2017\n",
      "city                                                      Chandigarh\n",
      "date                                                      2017-04-30\n",
      "team1                                               Delhi Daredevils\n",
      "team2                                                Kings XI Punjab\n",
      "toss_winner                                          Kings XI Punjab\n",
      "toss_decision                                                  field\n",
      "result                                                        normal\n",
      "dl_applied                                                         0\n",
      "winner                                               Kings XI Punjab\n",
      "win_by_runs                                                        0\n",
      "win_by_wickets                                                    10\n",
      "player_of_match                                       Sandeep Sharma\n",
      "venue              Punjab Cricket Association IS Bindra Stadium, ...\n",
      "umpire1                                                     YC Barde\n",
      "umpire2                                                    CK Nandan\n",
      "Name: 34, dtype: object\n",
      "id                                         72\n",
      "season                                   2008\n",
      "city                                   Mumbai\n",
      "date                               2008-04-27\n",
      "team1                          Mumbai Indians\n",
      "team2                         Deccan Chargers\n",
      "toss_winner                   Deccan Chargers\n",
      "toss_decision                           field\n",
      "result                                 normal\n",
      "dl_applied                                  0\n",
      "winner                        Deccan Chargers\n",
      "win_by_runs                                 0\n",
      "win_by_wickets                             10\n",
      "player_of_match                  AC Gilchrist\n",
      "venue              Dr DY Patil Sports Academy\n",
      "umpire1                             Asad Rauf\n",
      "umpire2                            SL Shastri\n",
      "Name: 71, dtype: object\n",
      "id                              120\n",
      "season                         2009\n",
      "city                      Cape Town\n",
      "date                     2009-04-19\n",
      "team1               Kings XI Punjab\n",
      "team2              Delhi Daredevils\n",
      "toss_winner        Delhi Daredevils\n",
      "toss_decision                 field\n",
      "result                       normal\n",
      "dl_applied                        1\n",
      "winner             Delhi Daredevils\n",
      "win_by_runs                       0\n",
      "win_by_wickets                   10\n",
      "player_of_match          DL Vettori\n",
      "venue                      Newlands\n",
      "umpire1                   MR Benson\n",
      "umpire2                   SD Ranade\n",
      "Name: 119, dtype: object\n",
      "id                                         184\n",
      "season                                    2010\n",
      "city                                 Bangalore\n",
      "date                                2010-03-18\n",
      "team1                         Rajasthan Royals\n",
      "team2              Royal Challengers Bangalore\n",
      "toss_winner        Royal Challengers Bangalore\n",
      "toss_decision                            field\n",
      "result                                  normal\n",
      "dl_applied                                   0\n",
      "winner             Royal Challengers Bangalore\n",
      "win_by_runs                                  0\n",
      "win_by_wickets                              10\n",
      "player_of_match                      JH Kallis\n",
      "venue                    M Chinnaswamy Stadium\n",
      "umpire1                            K Hariharan\n",
      "umpire2                              DJ Harper\n",
      "Name: 183, dtype: object\n",
      "id                              299\n",
      "season                         2011\n",
      "city                         Mumbai\n",
      "date                     2011-05-20\n",
      "team1                Mumbai Indians\n",
      "team2              Rajasthan Royals\n",
      "toss_winner          Mumbai Indians\n",
      "toss_decision                   bat\n",
      "result                       normal\n",
      "dl_applied                        0\n",
      "winner             Rajasthan Royals\n",
      "win_by_runs                       0\n",
      "win_by_wickets                   10\n",
      "player_of_match           SR Watson\n",
      "venue              Wankhede Stadium\n",
      "umpire1                 RE Koertzen\n",
      "umpire2                  PR Reiffel\n",
      "Name: 298, dtype: object\n",
      "id                                    377\n",
      "season                               2012\n",
      "city                               Jaipur\n",
      "date                           2012-05-20\n",
      "team1                    Rajasthan Royals\n",
      "team2                      Mumbai Indians\n",
      "toss_winner              Rajasthan Royals\n",
      "toss_decision                         bat\n",
      "result                             normal\n",
      "dl_applied                              0\n",
      "winner                     Mumbai Indians\n",
      "win_by_runs                             0\n",
      "win_by_wickets                         10\n",
      "player_of_match                  DR Smith\n",
      "venue              Sawai Mansingh Stadium\n",
      "umpire1                   HDPK Dharmasena\n",
      "umpire2                     C Shamshuddin\n",
      "Name: 376, dtype: object\n",
      "id                                                        391\n",
      "season                                                   2013\n",
      "city                                               Chandigarh\n",
      "date                                               2013-04-10\n",
      "team1                                         Kings XI Punjab\n",
      "team2                                     Chennai Super Kings\n",
      "toss_winner                               Chennai Super Kings\n",
      "toss_decision                                           field\n",
      "result                                                 normal\n",
      "dl_applied                                                  0\n",
      "winner                                    Chennai Super Kings\n",
      "win_by_runs                                                 0\n",
      "win_by_wickets                                             10\n",
      "player_of_match                                    MEK Hussey\n",
      "venue              Punjab Cricket Association Stadium, Mohali\n",
      "umpire1                                             Aleem Dar\n",
      "umpire2                                         C Shamshuddin\n",
      "Name: 390, dtype: object\n",
      "id                                         543\n",
      "season                                    2015\n",
      "city                                     Delhi\n",
      "date                                2015-04-26\n",
      "team1                         Delhi Daredevils\n",
      "team2              Royal Challengers Bangalore\n",
      "toss_winner        Royal Challengers Bangalore\n",
      "toss_decision                            field\n",
      "result                                  normal\n",
      "dl_applied                                   0\n",
      "winner             Royal Challengers Bangalore\n",
      "win_by_runs                                  0\n",
      "win_by_wickets                              10\n",
      "player_of_match                       VR Aaron\n",
      "venue                         Feroz Shah Kotla\n",
      "umpire1                              M Erasmus\n",
      "umpire2                                 S Ravi\n",
      "Name: 542, dtype: object\n",
      "id                                                    591\n",
      "season                                               2016\n",
      "city                                               Rajkot\n",
      "date                                           2016-04-21\n",
      "team1                                       Gujarat Lions\n",
      "team2                                 Sunrisers Hyderabad\n",
      "toss_winner                           Sunrisers Hyderabad\n",
      "toss_decision                                       field\n",
      "result                                             normal\n",
      "dl_applied                                              0\n",
      "winner                                Sunrisers Hyderabad\n",
      "win_by_runs                                             0\n",
      "win_by_wickets                                         10\n",
      "player_of_match                                   B Kumar\n",
      "venue              Saurashtra Cricket Association Stadium\n",
      "umpire1                                        K Bharatan\n",
      "umpire2                                   HDPK Dharmasena\n",
      "Name: 590, dtype: object\n",
      "id                                        7941\n",
      "season                                    2018\n",
      "city                                    Indore\n",
      "date                                  14/05/18\n",
      "team1                          Kings XI Punjab\n",
      "team2              Royal Challengers Bangalore\n",
      "toss_winner        Royal Challengers Bangalore\n",
      "toss_decision                            field\n",
      "result                                  normal\n",
      "dl_applied                                   0\n",
      "winner             Royal Challengers Bangalore\n",
      "win_by_runs                                  0\n",
      "win_by_wickets                              10\n",
      "player_of_match                       UT Yadav\n",
      "venue                   Holkar Cricket Stadium\n",
      "umpire1                         Bruce Oxenford\n",
      "umpire2                  Virender Kumar Sharma\n",
      "Name: 683, dtype: object\n"
     ]
    }
   ],
   "source": [
    "for index, row in ipl_matches_df.iterrows():\n",
    "    if(row['win_by_wickets'] == 10):\n",
    "        print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bcb999e1",
   "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>victory_margin</th>\n",
       "      <th>instances</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   victory_margin instances\n",
       "1               6        85\n",
       "2               7        80\n",
       "3               5        71\n",
       "4               8        54\n",
       "5               4        41\n",
       "6               9        37\n",
       "7               3        18\n",
       "8              10        11\n",
       "9               2         6\n",
       "10              1         3"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chasing_vict_df = pd.DataFrame(columns=['victory_margin', 'instances'])\n",
    "\n",
    "for items in chasing_vict_ser.iteritems():    \n",
    "    temp_df7 = pd.DataFrame({\n",
    "        'victory_margin': [items[0]],\n",
    "        'instances': [items[1]]\n",
    "    })\n",
    "    chasing_vict_df = chasing_vict_df.append(temp_df7, ignore_index=True)\n",
    "    \n",
    "#to drop the first row as it represents victory margin of zero wickets(victory by defending a total)\n",
    "chasing_vict_df2 = chasing_vict_df.drop([0]) \n",
    "chasing_vict_df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "244843fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('The IPL victories in numbers when chasing a total')\n",
    "sns.barplot(x='victory_margin', y='instances', data=chasing_vict_df2);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f28d9b6",
   "metadata": {},
   "source": [
    "## Inferences and Conclusion\n",
    "\n",
    "Let’s summarize the important observations we made during Exploratory Data Analysis:\n",
    "\n",
    "* Mumbai Indians is the most successful team in IPL.\n",
    "* Mumbai Indians has won the most number of toss.\n",
    "* There were more matches won by chasing the total(419 matches) than defending(350 matches).\n",
    "* When defending a total, the biggest victory was by 146 runs(Mumbai Indians defeated Delhi Daredevils by 146 runs on 06 May 2017 at Feroz Shah Kotla stadium, Delhi).\n",
    "* When chasing a target, the biggest victory was by 10 wickets(without losing any wickets) and there were 11 such instances.\n",
    "* The Mumbai city has hosted the most number of IPL matches.\n",
    "* Chris Gayle has won the maximum number of player of the match title.\n",
    "* Winning toss gives a slight edge(52% probability of winning) against the opponents.\n",
    "* Five Indian players have figured in the top ten IPL players list.\n",
    "* S. Ravi(Sundaram Ravi) has officiated the most number of IPL matches on-field.\n",
    "* Eden Gardens has hosted the maximum number of IPL matches.\n",
    "* Till 2019, 40 venues have hosted 756 IPL matches."
   ]
  }
 ],
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