ipl_dataset-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt \n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ipl = pd.read_csv('C:/Users/Vinayak BB/Desktop/Datasets/ipl data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-04-08</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city        date                        team1  \\\n",
       "0   1    2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "1   2    2017       Pune  2017-04-06               Mumbai Indians   \n",
       "2   3    2017     Rajkot  2017-04-07                Gujarat Lions   \n",
       "3   4    2017     Indore  2017-04-08       Rising Pune Supergiant   \n",
       "4   5    2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3              Kings XI Punjab              Kings XI Punjab         field   \n",
       "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0          Sunrisers Hyderabad           35   \n",
       "1  normal           0       Rising Pune Supergiant            0   \n",
       "2  normal           0        Kolkata Knight Riders            0   \n",
       "3  normal           0              Kings XI Punjab            0   \n",
       "4  normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "   win_by_wickets player_of_match                                      venue  \\\n",
       "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "          umpire1        umpire2 umpire3  \n",
       "0     AY Dandekar       NJ Llong     NaN  \n",
       "1  A Nand Kishore         S Ravi     NaN  \n",
       "2     Nitin Menon      CK Nandan     NaN  \n",
       "3    AK Chaudhary  C Shamshuddin     NaN  \n",
       "4             NaN            NaN     NaN  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(756, 18)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[101, 77, 74, 66, 64]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(ipl['city'].value_counts())[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Mumbai', 'Kolkata', 'Delhi', 'Bangalore', 'Hyderabad']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(ipl['city'].value_counts()[0:5].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.scatter(list(ipl['city'].value_counts()[0:5].keys()),list(ipl['city'].value_counts()[0:5]),color=\"g\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 98\n",
       "Kolkata Knight Riders          92\n",
       "Chennai Super Kings            89\n",
       "Kings XI Punjab                81\n",
       "Royal Challengers Bangalore    81\n",
       "Delhi Daredevils               80\n",
       "Rajasthan Royals               80\n",
       "Sunrisers Hyderabad            46\n",
       "Deccan Chargers                43\n",
       "Pune Warriors                  20\n",
       "Gujarat Lions                  15\n",
       "Delhi Capitals                 10\n",
       "Kochi Tuskers Kerala            8\n",
       "Rising Pune Supergiants         7\n",
       "Rising Pune Supergiant          6\n",
       "Name: toss_winner, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['toss_winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "win_batfirst=ipl[ipl['win_by_runs'] != 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>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>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>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-11</td>\n",
       "      <td>Delhi Daredevils</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>Delhi Daredevils</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>SV Samson</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>Kolkata Knight Riders</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>Kolkata Knight Riders</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>RV Uthappa</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2017</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>CJ Anderson</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>YC Barde</td>\n",
       "      <td>Nitin Menon</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>741</th>\n",
       "      <td>11337</td>\n",
       "      <td>2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>28/04/19</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>Feroz Shah Kotla Ground</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>11338</td>\n",
       "      <td>2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>28/04/19</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>Kolkata Knight Riders</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Anil Dandekar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>11339</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>29/04/19</td>\n",
       "      <td>Sunrisers Hyderabad</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>Sunrisers Hyderabad</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>11341</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>01/05/19</td>\n",
       "      <td>Chennai Super Kings</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>Chennai Super Kings</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Anil Dandekar</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</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>337 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  season       city        date                        team1  \\\n",
       "0        1    2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "4        5    2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "8        9    2017       Pune  2017-04-11             Delhi Daredevils   \n",
       "13      14    2017    Kolkata  2017-04-15        Kolkata Knight Riders   \n",
       "14      15    2017      Delhi  2017-04-15             Delhi Daredevils   \n",
       "..     ...     ...        ...         ...                          ...   \n",
       "741  11337    2019      Delhi    28/04/19               Delhi Capitals   \n",
       "742  11338    2019    Kolkata    28/04/19        Kolkata Knight Riders   \n",
       "743  11339    2019  Hyderabad    29/04/19          Sunrisers Hyderabad   \n",
       "745  11341    2019    Chennai    01/05/19          Chennai Super Kings   \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",
       "4               Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "8         Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "13           Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "14               Kings XI Punjab             Delhi Daredevils           bat   \n",
       "..                           ...                          ...           ...   \n",
       "741  Royal Challengers Bangalore               Delhi Capitals           bat   \n",
       "742               Mumbai Indians               Mumbai Indians         field   \n",
       "743              Kings XI Punjab              Kings XI Punjab         field   \n",
       "745               Delhi Capitals               Delhi Capitals         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",
       "4    normal           0  Royal Challengers Bangalore           15   \n",
       "8    normal           0             Delhi Daredevils           97   \n",
       "13   normal           0        Kolkata Knight Riders           17   \n",
       "14   normal           0             Delhi Daredevils           51   \n",
       "..      ...         ...                          ...          ...   \n",
       "741  normal           0               Delhi Capitals           16   \n",
       "742  normal           0        Kolkata Knight Riders           34   \n",
       "743  normal           0          Sunrisers Hyderabad           45   \n",
       "745  normal           0          Chennai Super Kings           80   \n",
       "755  normal           0               Mumbai Indians            1   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "0                 0    Yuvraj Singh   \n",
       "4                 0       KM Jadhav   \n",
       "8                 0       SV Samson   \n",
       "13                0      RV Uthappa   \n",
       "14                0     CJ Anderson   \n",
       "..              ...             ...   \n",
       "741               0        S Dhawan   \n",
       "742               0      AD Russell   \n",
       "743               0       DA Warner   \n",
       "745               0        MS Dhoni   \n",
       "755               0       JJ Bumrah   \n",
       "\n",
       "                                         venue         umpire1  \\\n",
       "0    Rajiv Gandhi International Stadium, Uppal     AY Dandekar   \n",
       "4                        M Chinnaswamy Stadium             NaN   \n",
       "8      Maharashtra Cricket Association Stadium     AY Dandekar   \n",
       "13                                Eden Gardens     AY Dandekar   \n",
       "14                            Feroz Shah Kotla        YC Barde   \n",
       "..                                         ...             ...   \n",
       "741                    Feroz Shah Kotla Ground  Bruce Oxenford   \n",
       "742                               Eden Gardens       Ian Gould   \n",
       "743         Rajiv Gandhi Intl. Cricket Stadium          S Ravi   \n",
       "745                  M. A. Chidambaram Stadium   Anil Dandekar   \n",
       "755         Rajiv Gandhi Intl. Cricket Stadium     Nitin Menon   \n",
       "\n",
       "                   umpire2        umpire3  \n",
       "0                 NJ Llong            NaN  \n",
       "4                      NaN            NaN  \n",
       "8                   S Ravi            NaN  \n",
       "13                NJ Llong            NaN  \n",
       "14             Nitin Menon            NaN  \n",
       "..                     ...            ...  \n",
       "741  KN Ananthapadmanabhan  C Shamshuddin  \n",
       "742            Nitin Menon  Anil Dandekar  \n",
       "743               O Nandan  Nanda Kishore  \n",
       "745            Nitin Menon      Ian Gould  \n",
       "755              Ian Gould    Nigel Llong  \n",
       "\n",
       "[337 rows x 18 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batfirst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>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>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>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2017-04-11</td>\n",
       "      <td>Delhi Daredevils</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>Delhi Daredevils</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>SV Samson</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>Kolkata Knight Riders</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>Kolkata Knight Riders</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>RV Uthappa</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2017</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>CJ Anderson</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>YC Barde</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id  season       city        date                        team1  \\\n",
       "0    1    2017  Hyderabad  2017-04-05          Sunrisers Hyderabad   \n",
       "4    5    2017  Bangalore  2017-04-08  Royal Challengers Bangalore   \n",
       "8    9    2017       Pune  2017-04-11             Delhi Daredevils   \n",
       "13  14    2017    Kolkata  2017-04-15        Kolkata Knight Riders   \n",
       "14  15    2017      Delhi  2017-04-15             Delhi Daredevils   \n",
       "\n",
       "                          team2                  toss_winner toss_decision  \\\n",
       "0   Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "4              Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "8        Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "13          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "14              Kings XI Punjab             Delhi Daredevils           bat   \n",
       "\n",
       "    result  dl_applied                       winner  win_by_runs  \\\n",
       "0   normal           0          Sunrisers Hyderabad           35   \n",
       "4   normal           0  Royal Challengers Bangalore           15   \n",
       "8   normal           0             Delhi Daredevils           97   \n",
       "13  normal           0        Kolkata Knight Riders           17   \n",
       "14  normal           0             Delhi Daredevils           51   \n",
       "\n",
       "    win_by_wickets player_of_match                                      venue  \\\n",
       "0                0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "4                0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "8                0       SV Samson    Maharashtra Cricket Association Stadium   \n",
       "13               0      RV Uthappa                               Eden Gardens   \n",
       "14               0     CJ Anderson                           Feroz Shah Kotla   \n",
       "\n",
       "        umpire1      umpire2 umpire3  \n",
       "0   AY Dandekar     NJ Llong     NaN  \n",
       "4           NaN          NaN     NaN  \n",
       "8   AY Dandekar       S Ravi     NaN  \n",
       "13  AY Dandekar     NJ Llong     NaN  \n",
       "14     YC Barde  Nitin Menon     NaN  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batfirst.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.hist(win_batfirst['win_by_runs'])\n",
    "plt.title(\"Distribution of runs\")\n",
    "plt.xlabel(\"Runs\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 57\n",
       "Chennai Super Kings            52\n",
       "Kings XI Punjab                38\n",
       "Kolkata Knight Riders          36\n",
       "Royal Challengers Bangalore    35\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batfirst[\"winner\"].value_counts()[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.hist(win_batfirst['winner'].value_counts()[0:5])\n",
    "plt.title(\"Distribution of winners\")\n",
    "plt.xlabel(\"winner\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.pie((win_batfirst[\"winner\"].value_counts()[0:9]),labels=list(win_batfirst[\"winner\"].value_counts()[0:9].keys()),autopct= '%0.1f%%')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "win_batsecond=ipl[ipl['win_by_wickets'] != 0 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>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>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-04-09</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>9</td>\n",
       "      <td>Rashid Khan</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>A Deshmukh</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2017-04-09</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>4</td>\n",
       "      <td>N Rana</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city        date                   team1  \\\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",
       "5   6    2017  Hyderabad  2017-04-09           Gujarat Lions   \n",
       "6   7    2017     Mumbai  2017-04-09   Kolkata Knight Riders   \n",
       "\n",
       "                    team2             toss_winner toss_decision  result  \\\n",
       "1  Rising Pune Supergiant  Rising Pune Supergiant         field  normal   \n",
       "2   Kolkata Knight Riders   Kolkata Knight Riders         field  normal   \n",
       "3         Kings XI Punjab         Kings XI Punjab         field  normal   \n",
       "5     Sunrisers Hyderabad     Sunrisers Hyderabad         field  normal   \n",
       "6          Mumbai Indians          Mumbai Indians         field  normal   \n",
       "\n",
       "   dl_applied                  winner  win_by_runs  win_by_wickets  \\\n",
       "1           0  Rising Pune Supergiant            0               7   \n",
       "2           0   Kolkata Knight Riders            0              10   \n",
       "3           0         Kings XI Punjab            0               6   \n",
       "5           0     Sunrisers Hyderabad            0               9   \n",
       "6           0          Mumbai Indians            0               4   \n",
       "\n",
       "  player_of_match                                      venue         umpire1  \\\n",
       "1       SPD Smith    Maharashtra Cricket Association Stadium  A Nand Kishore   \n",
       "2         CA Lynn     Saurashtra Cricket Association Stadium     Nitin Menon   \n",
       "3      GJ Maxwell                     Holkar Cricket Stadium    AK Chaudhary   \n",
       "5     Rashid Khan  Rajiv Gandhi International Stadium, Uppal      A Deshmukh   \n",
       "6          N Rana                           Wankhede Stadium     Nitin Menon   \n",
       "\n",
       "         umpire2 umpire3  \n",
       "1         S Ravi     NaN  \n",
       "2      CK Nandan     NaN  \n",
       "3  C Shamshuddin     NaN  \n",
       "5       NJ Llong     NaN  \n",
       "6      CK Nandan     NaN  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batsecond.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PNz19/OVK0mD66ckdBt5SVS8ELgJ+PcmLgM3AzqpaB+zsliXpuLJoyFXVgaq6q5t/DNgNnAlsAGa6zWaAjWOqUZKGNtB7ckkm6X3R9B3Amqo6AL0gBFaPvDpJWqK+Qy7JqcCfAG+qqu8NsN+mJLuS7JqdnR2mRkkaWl8hl+QkegF3Y1Xd2jUfTLK2W78WOLTQvlW1taqmqmpqYmJiFDVLUt/6uboa4APA7qp635xV24Hpbn4a2Db68iRpaVb2sc3FwDXAl5Lc07W9A9gC3JzkWmAfcOVYKpSkJVg05Krq80COsnr9aMuRpNHyiQdJTetnuKoRmNx8W9/b7t1y+RgrkZ5a7MlJapohJ6lphpykphlykppmyElqmiEnqWmGnKSmGXKSmmbISWqaISepaYacpKYZcpKaZshJapohJ6lphpykphlykppmyElqmiEnqWmGnKSmGXKSmrboF9kk+SBwBXCoqs7v2lYBHwMmgb3Aq6rqu+MrU9KJrt8vcxr1Fzn105O7AbhsXttmYGdVrQN2dsuSdNxZNOSq6nPAd+Y1bwBmuvkZYONoy5Kk0Rj2Pbk1VXUAoJuuPtqGSTYl2ZVk1+zs7JCnk6ThjP3CQ1VtraqpqpqamJgY9+kk6f8zbMgdTLIWoJseGl1JkjQ6w4bcdmC6m58Gto2mHEkarUVDLslNwBeA85LsT3ItsAW4NMke4NJuWZKOO4veJ1dVrznKqvUjrkWSRs4nHiQ1zZCT1DRDTlLTDDlJTTPkJDXNkJPUNENOUtMWvU+uNcv1mVaSloc9OUlNM+QkNc2Qk9Q0Q05S0ww5SU0z5CQ1zZCT1DRDTlLTjvubgb15V9JS2JOT1DRDTlLTDDlJTTPkJDVtSSGX5LIkX03ytSSbR1WUJI3K0CGXZAXwfuAVwIuA1yR50agKk6RRWEpP7iXA16rqgar6IfBRYMNoypKk0VhKyJ0JfHPO8v6uTZKOG6mq4XZMrgR+tape3y1fA7ykqq6bt90mYFO3eB7w1eHLPSbOAB5a7iLGqPXXB+2/Rl/f33duVU0stGIpTzzsB86es3wW8OD8japqK7B1Cec5ppLsqqqp5a5jXFp/fdD+a/T1DWYpw9W/BNYleW6SpwFXAdtHU5YkjcbQPbmqOpzkXwP/G1gBfLCq7h9ZZZI0Akt6QL+q/gz4sxHVcrw4YYbWQ2r99UH7r9HXN4ChLzxI0onAx7okNc2QA5KcneTPk+xOcn+SNy53TeOQZEWSu5N8crlrGYckz05yS5KvdH+Xv7DcNY1Skjd3/z7vS3JTkpOXu6alSvLBJIeS3DenbVWSHUn2dNPTl3IOQ67nMPCWqnohcBHw640+ovZGYPdyFzFGvw98qqpeAFxAQ681yZnAG4Cpqjqf3sW+q5a3qpG4AbhsXttmYGdVrQN2dstDM+SAqjpQVXd184/R++Vo6umNJGcBlwPXL3ct45DkNOClwAcAquqHVfXIshY1eiuBpydZCZzCAvelnmiq6nPAd+Y1bwBmuvkZYONSzmHIzZNkEngxcMcylzJqvwe8FfjRMtcxLs8DZoEPdUPy65M8Y7mLGpWq+hbwXmAfcAB4tKo+vbxVjc2aqjoAvQ4IsHopBzPk5khyKvAnwJuq6nvLXc+oJLkCOFRVdy53LWO0Evg54A+r6sXA4yxxmHM86d6X2gA8F3gO8IwkVy9vVScGQ66T5CR6AXdjVd263PWM2MXAK5PspfdpMS9P8pHlLWnk9gP7q+pID/wWeqHXikuAr1fVbFU9AdwK/OIy1zQuB5OsBeimh5ZyMEMOSBJ67+Xsrqr3LXc9o1ZVb6+qs6pqkt6b1Z+tqqZ6AVX1beCbSc7rmtYDX17GkkZtH3BRklO6f6/raejCyjzbgelufhrYtpSDHfdfSXiMXAxcA3wpyT1d2zu6Jzp04rgOuLF7lvoB4HXLXM/IVNUdSW4B7qJ3N8DdNPDkQ5KbgJcBZyTZD7wL2ALcnORaeuF+5ZLO4RMPklrmcFVS0ww5SU0z5CQ1zZCT1DRDTlLTDDlJTTPkJDXNkJPUtP8LNvpEum7iVqEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.hist(win_batsecond['win_by_wickets'],bins=25)\n",
    "plt.title(\"Distribution of runs\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Kolkata Knight Riders          56\n",
       "Mumbai Indians                 50\n",
       "Chennai Super Kings            48\n",
       "Royal Challengers Bangalore    48\n",
       "Rajasthan Royals               46\n",
       "Delhi Daredevils               42\n",
       "Kings XI Punjab                42\n",
       "Sunrisers Hyderabad            27\n",
       "Gujarat Lions                  12\n",
       "Deccan Chargers                11\n",
       "Pune Warriors                   6\n",
       "Delhi Capitals                  6\n",
       "Rising Pune Supergiant          5\n",
       "Kochi Tuskers Kerala            4\n",
       "Rising Pune Supergiants         3\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_batsecond['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bA2eEW476jqm0dyKFGrF1jPvZrn6crip07wt8mzxhmkl6ZKi3GKVvOOlYn9Lz0Sgff/jTh4HOp28ILAu3PPWZQ06nqR9vE1DJvMDzdGQOcdVJWnQ68FXyhGmmroGhXmKUvuGkYn1Kz/uAvwEIxD38eaD3qJWBRWEWq96S5XBUZUd70qGK+3bv/+1L19Y14ZA3GvgkecI0U8XQUO8wSt9w0rA+pec1wMvB1wSifv1NYMDFiwLzwiRWvSbH4YgKtwz1gad8Ny2ZHeibWoNDXgy8lzxhmvmONdQrzH9Iw0nB+pSe/bFC80r8nxZw3fZz4IzrZ/pn17lg9ZwCh8SEW4ZwM81/+szX/JcMq4Whr6PYItRgCDdG6RsaPOtTejYBPgNKVWACjqvn6fC7v/PPrDvJ6j/uU7zS3uZAm7njvL+raGheVbgvecK0O2pxfIOhUhilb2jQrE/p6QDeBzpVpP35y3Xk777wz6hVoRoQfmgUbhnCRZbGrr7Y89SgOpjq5eQJ02ry6MBgqDJG6RsaOmnABZXpMGy9jnr0Q7PjB1BoFIBAuOWoa7zq3DXG/VxrDxF14dMQg+XYl1AHcxkMZWKUvqHBsj6l5yXAn6rSt992Hfnk277ZonrKKbwTEHFkOxzZFWl615cFtHgmhz4v5x679vsfCkl5KZe+r+Ry5ZR8jhZqiX6FPmXI67n0m5RL75dz+csvxzP//t+PhfR9JZfbPi84du3dlR7+vcBdnacqE1WyLvP8zXOIxGa1NklJugOv1+F8BkNIjNI3NEjWp/TsglVEp8px5l33MfzZN/zzHQE9pbPSHalged07+kfw3S2xJ1w7t4uLNffHserX8XRv4uCp2SWVdZQTpt8ex8qx8ay4L47vtvpYsNtHVqEyb7efVb+Ox6/K6gN+CrzK2yu93D84smYerhiq+MZ5f7d1vXbsUisTlM31yROmjQvDvAbDMYzSNzQ41qf0jAU+B5KqO1b7TIb9Z5J/qcuntbe1rOdUtNLeiI4umsScuMY6r4sLl8O6dkY7J7tzShpORIT4SKuNNwBev7VScwh4/IqqUuCFCCc8M8/DA0MiiailnEEv+y+b/03g9AG1MnjFeD55wrS68CMwGEJilL6hIfIaUGOOUS2yOP3ll/1rIr2aX1NjhmL3m7tZ/9v1bH5087FrWYuy2PzHzay5cw0F2wtK7Zv5fSab/7iZzY9uZtcruwh4LOW6/6P9bP7TZna/tvtY2yNzj5D5Q2aF5cpwOkufuBK8tcLLhV1D5/rxB5T+k3Jp8UwO53Z2cXo7FwlRwtU9Izjt1Tw6JTlIjBIW7/VzeUrt5LSZ4+8z8xnfDcNrZfCKEwl8bHL0G8KFUfqGBsX6lJ7XUgtlcpPyGDjpRf+W2EKtkKm7KjQ+qzHJ45NPuBbVLooOv+1AbPfY0J0A7xEvh348RJe0LnT7ezc0oGQtzMKf7yd/Sz7d/mZdK9xVSMAT4OicozQd07TCcmU4ndW2cvx9lhuXA25ODa2wnQ5hxdh4dj+cwKK9ftYc9APwh2FRrBgbz3PnR/PnX9z8dVQUbyzzcN3H+fxtVs0ZX/Zo00W3eieEW+EXkQxMTp4wzaRANtQ5RukbGgx2PP6LtTV+vJu+k17y722Up4dqY/y4HnE4404scBPdJpqo1uU7kGtACXgCqF9Rj+Jq7AIB9VnmcfUq4hQyv82k6blNEVfF9cnBalbam7zCw9TNPt6/KgaRsudNihZGdXTx3ZYTp1y+z1oEdG/q4J2VXj66NpY1B/1sPuSvjmgA5GvUhnPdz/RWHPXp++5S4JFwC2E49ahPfwQGQ3k8B9RqzfJoLz1fnug/2jRb99fmPJUhonEEzS5oxqbxm9jw4AYcMQ4S+iTgjHHSaFAjtj62lYhmEThiHRRsK6DRgMqF3mc4nSVd7ivId1t8/GOuh69uiCE2IrTCz8gLHPPqL/AqP233kdLsxK+eP//i5q+jo/AGwG9L4xDI91ZVMgu/yv5z3M8k5hMdV72RaoUnkidM6xZuIQynFqbYhqFBsD6l57nAHXUxV6SfLi++4t/58D3OXfubSE0UYKkW/jw/Octz6P5Md5yxTnZO3MnReUdJOjOJ5hc1p/lFzQHY89YeWlzVgsMzD5O7Jpfo9tG0uKxFueMfqmB53Rs/zWdGup/MfKXd8zk8PiqKp+a4cfvh3Hctd4gz2jmZdEkMe3MC/OqrQr65OZZ9ucrtX+TjD0BA4breEVzS/fgxwBcbvAxu46RNgrUQGNrOSeorufRt6aBfq6qX/lUl73rPY0f20qxnlQepXaKwLFeVyjNhMFQHUa3yIt9gqBPWp/SMA1ZTwax7NYVf2Pd/dzkLdraQzjU1pifDw45/7aDb30/c4G17ahutb2hNTKeSmYSzFmWRszqHdne3AyxHvYKtBbS5rc2xNgU7Cjj882Fa39ya9OfS6fzHzux6eRctrmpBVKuyjw+6uz1zPt27/6waeLx6gyqBP/ruXvyB/+zTwy1LBbg6/emLPwu3EIZTA2PeNzQEnqCOFT6AU2n9zzf9jbrt0Y11PXcwEU0jKNhaQMAdQFXJW5dXwg/g4GcHaXFlC9Snx/PrOTjm5V8W2U5H7QTFh5Ep/tGzG4jCB3ghecK00j05DYYaxCh9Q71mfUrPIcDvwjW/A5r97R1/q77bAqurO9auV3ax7W/bcO93s+GhDRyeeZjspdlseGgDBVsLSH8hnfRn0wHLYz/9eet1bJdYGg1uxJa/bGHLn7agAaXxqOMRX9lLs4npFENE4wiccU5iusaw+U9WWGBMh/KL6OXLyVVpb1Wg0+wJvntqs4hOTdOBKmaWNBgqizHvG+ot61N6RgBLqcGY/KqikPf8lY6NC1Mc4UzsUitEBnTr0h27wpGhrsbJ1EbLznC/lOrDVTvB/rWHB0hNf/riTeEWxHByY3b6hvrM76gHCh9AIO7hzwO9R68MLAq3LDWNT06OSntudW0b4362SwNU+GAl7XmpOgOISG7Q64tEZLOIdCivvYiMEpGplZhnlIicWUnZTphDRP4mIt+LSKkOJyJymYhMqMy4xe49KCIhj01EZIaIbBSRlSKyWET6B937RkSSQvRJE5EGH2ZplL6hXrI+pWcjoMw/+LpGIGrsN4EBFy8KzAu3LDVJABLDLUN1CagcutDztDOb+Ib8LOcmT5h2bXUHEZGzsaMCVHVn9cUqwSigUko/GBF5FBgGXKFaevprVf1KVZ+u6jzAg0BZvhI3q2o/4GXgmaB5L1LVo9WYFwARqZfRcUbpG+orDwMVTytXRwi4bvs5cMYNM/2zwy1LjSESmSdSofz79RFVPHd5f79nm7bpGG5ZaoDnkydMq3JOAREZjlXN72JV3Wpfe1hE1tg/D5bTf7CILBeRziJyqYgstN//JCItRSQZGAs8JCIrRGR4qHZljD8euAi4VFUL7GvpIvK4iCwTkdUikmJfv0NEXrJfdxGRBfau/K/BVg0gXkQ+EZENIvK+WDwAtAF+EZFfyvnY5gNtg2RMF5Fm9utHbYvAT0CPoDZdROQ7EVkqIrODZH5bRJ635/yHiIy0P6cV9ucT9vLKRukb6h3rU3o2xVL69RIBx1XzdPivvvPPDLcsNcXRClbaq48847t+8YxA/77hlqOGaAc8VsW+UcCXWDvoDQAiMhC4EzgdOAO4R0ROC9XZNtlPAi5X1W3AHOAMVT0N+BD4g6qm221eUNX+qjo7VLtS5BuGtWC4UFVzi93LVNUBwCuEzlT4b+DfqjoY2Fvs3mlYu/peQGdgmKr+x243WlVHlyJPERcAXxS/aH92N9jjXwUMDrr9GvBbVR1oy/ty0L3uwDmqOt6+N05V+wPDgRqpc1EdjNI31EcmAGFfEZfHect15IOf+2eEW46a4JDTWfxLuEHwnX/QzJf9lw8Ltxw1zO+SJ0xrXYV+XmAecHfQtbOAz1U1z1a0n2Epn+L0xFJklwYdCbQDvheR1cDvgd6lzFvRdluwCiyeF+JeUZ6CpVi1CYozFPjYfv2/YvcWqepuVQ0AK0rpH4r3RWQ38H+ETu89HOuzy1fVbOArABGJxzre+FhEVgCvAsG/r49VtSh/9FzgedvykKQa/jLe5Sp9EfHbpok1IvJ1KAeH6mCbQ64p5d4jtslmje1wcZt9/Zj5pYJzHHP2CDYZ1VeCPvOVtsmryudnVZg7WUTW1NV8xVmf0rM10GBqjp+5QUc9+kHD3/FnOJ21WmGwNtgWaD1vrPehEeGWoxaIwlKelSUAXAcMFpE/2tcqWoRhH1CItast4kXgJVVNBe4DokvpW9F2B7BM+y+ISPHdd9HZvp/KZ4oN9guoTP+bsfJ//A+YWEqbUOFtDuCobeko+gnO+njsqMz2SfgVEAMsKDoGCCcV2ekX2A/VBzhMHX0hi8hY4FxgiD33CCr+H7heUgnHjqLPvB/w/4CnalGsalELzip/wvoDaTD0S9eRT77tmy3WTqNBkuF0FoZbhsqQrTFrLvQ8NQDKqfDTcLkvecK0Cm9silDVfOAS4GYRuRuYBVwhIrEiEgdcCYTyRzkKXAw8KSKj7GuJwB779e1BbXM40RJXWrtQ8m3CMpW/F+wxXwEWAFfbr2+oYJ/icoaSx4v1nXOGiBRP1zwLuFJEYuyz+EvtPtnAdhG5FsD2IegXanwR6aKqq1X1H8ASoEEo/WCOOTyISH/bsWKViHwuIo1t54ZlRY1FpJuILLVfP2Y7YawRkddEyv1j/SNwv/0Bo6pZqjo56P5vQzh+DBGRebbDxDwR6RFq4CD5movIp7Zci0VkmH09TUTeEiusY5ttminq82fb+vCjiHwgdghHLTp2NAKO2GPFi8jPQc99uX09WUTWi8jrIrJWRH4QO+GKWI45q0Rkvog8U7SLt/vMtscKaU0QkWgR+a891/Ki1bltLflYRL4GfhCROPvzWmy3u7ycZwrJ+pSenYB7qtI33HTdx/DnXvfPdwTCb76rCgddzmqWtqk7vOrcPcb9XEs3kaXtKE8GYqmiX4uqHsY6p/4T0B54G1gELATeUNXlpfQ7gKXYJorI6UAalgl7NpAZ1PRrLGW4QizHwdLalSbfYiw/g69EpKL5IR4EHhaRRVim9Ir4oLwGfCvlOPLZDoXPUcyXQFWXAVOwjgw+5cTF0s3A3SKyElgLlPad96Ct81Zined/WwG5a5Vyk/OISK6qxouIE8tJ401V/U5EVmE5MswUkb8CjVT1QfsDfkhVV4jIk8A+VX1RRJrY/xkRkXeBj1T1axF5G5iqqp8EzZkA7FTVxsXlse+nA8/Z494PDFDVX4lIIyBfVX0icg7wa1W92l65PqKql4jIHcAgVf2NiPwPeFlV54gVz/q9qvYUkTSsc6fRWCvFjUAroB/wBtb5kgtYBryqqs+KyM/AWFXdbP/BPKWqY+zna4blHOO3FeXTqjpXrLOhwuLnPCLix8o1H431H3yMqi4Va1cdq6rZYh1vLAC6AR2xzssG2Z/7R8BXqvqereTvVdV5IvI0cImq9hErfjWgqoUi0g34QFUHieWdO9VuMx7oo6p32ouYH7CcVG4A/gb0VdXD9u95nT1fEtYXzGmqWimP8PUpPd+mnJ1CfSejEQt/d5+zv89VevxxfeSKnNyZT2QervdZ7FTJvsTz94NrtVPXcMtSB2QDHdOfvvhouAUJN/b3VYGqqojcANyoqlXaXJzqVGSnHyOWs8IhoAnwo4gkYjklFJ1lTsYyv4OlFO+0FwnXc9zpYrRYYR2rgTGU7uwBlhm/vFSBoRw/ErFWnGuAF8qZA+Ac4CX7+b4CGgXtvKepqltVM4GDWCVdzwK+VNUCVc3BWvHWhmNHkXk/BWvF/o6ICNbn8qS94PoJy+pSFB6zXVVXBH8mtgJOUNWiuPJgB5gI4HX79/Exludrcc4C3gWwvYF3YCl9gB+LFnFYC6QJ9rPPwFqslJoUJBT2Lv+WyvSpjzTP5vSXJ/rXRnkqt+AJN5kVrLQXTlTxP+D9zaZTROGDZeVrMP4ttcxAYIX93Xc/MD7M8jRYKnymj7WbjKT8/4SfAhdinSstVdVDIhKNFdJwje3s8TqlO3sUnZnkiZRZ3SyU48cTwC+2D8ClZc1h4wCGBjljtLWVefD4wXOUdiRRa44dqjofy1LQHMuk1BwYaP9ODgQ9Y2XkBXjI7t8PGIT1uy1OWf2DlZoAVwc9ewdVXV9G31DcD9R/zVMBkvIZ8MpL/q2xhdpgwuCOOB31PpLnNf/Fc78OnDko3HLUMeOSJ0w76QoiVRZVna2q/VS1r6qOUNUt4ZapoVLhP3RVzQIewDr3yAeO2Oc5ALcCM+12hcD3WPGW/7XvFymmTHtXHNJbvxhPYZ0tNQIQkUYicm85fYIdSu6owBw/AL8peiPlO5bMAS61z7rjsRxfatWxw14UOLEsLYnAQVX12ufrZSYjUdUjQI6InGFfCnaAScQ6eglg/f5CKdxZWAsNRKQ71u49VMW577F8LMRuGzIOuDTWp/SM5cQwowZPvJu+k17y72uUp4fCLUtFyHY46nXq2vn+njOf8t18Mnrql0drLIupwVAjVGp1bzuArMRSHrcDz9jmlv7AX4Oavo9lnv/B7ncUa3e/GisJwuIKTPcK8Auw2DbXz8RabJTFP4GnRGQuFds1PgAMsh3d1mEljigV2wHlK6zP4DMspV20m6tJx44Y20lmBZYjye328cD7trxL7Pk2VOAZ7wZeE5H5WDvyInlfBm4XkQVYJvtQ5uiXAad9BDAFuENDp818Auu4YJX9u3qiAnIFczMQ0n+jIRPtJeXlif6jTbN1f7hlKY9ch6PeOsXt1SaLbvI+Giq2/FThoXALYDh5qJUqe2J5tCeq6p9rfPAwIyLxqpprO5bMwnKSW1Zev3BRJK/9egLQWlXDVqo2FOtTeq4ETpaMaiXwOdj18D1O9jeR9uGWpTSiA4FNi3fs7l5+y7olXyM3Dna/0jaPmPhwyxJmRqU/fXGDzwdhCD81fo4nIp8Dt2GlTTwZec3egS8DPq3PCt/mYttqsAYrw9Tfwi1QMOtTeg7lJFb4AK4A7V94ze/qeMDKhV4f8VrHVfUKv8rB8zzPJBiFD1gVJw2GalMrO32DoaKsT+n5JnBXuOWoCwKQ+ditzsxN7cKflasEqnmr03dVudBLTaNK/vWeP6cv0p6hokpORTxASxO+Z6gu9d5j13Dysj6lZwKnkJOSA5o98a6/dd9tgdXhlqUEInEeS7GEHVX0Md8dq4zCP4FI4IpwC2Fo+Bilbwgn1wP1ZndZFwgkPjol0Pn0DYF6dyyUVU8q7X3iHzHrXf95Z5Tf8pTjunALYGj4GKVvCCd3hluAcCAQ9/Dngd6jVwYWhVuWYA45nTnlt6pd1gSSZ//eN7beZwYME+ckT5jWJNxCGBo2RukbwoJdTW9ouOUIFwJRY78JDLhkYWBe+a3rhkynM6xZBA9rwoorPH81O/zSicAqmGMwVBmj9A3h4hIaeNXE6iLgunV64IwbZvpDVT2rc8JZac+jru2j3c8l+3DV6yRB9QBj4jdUC6P0DeHisnALUB8QcFw1T4f/6jt/2GOwDzqdYXHkC6gcvtDzlCOL+KRwzN/AGJM8YVrTcAthaLgYpW+oc9an9IwBzg63HPWJ85bryIc+D6/iz3A567wssCqeX3nH79qqbctMKW04hgurHr3BUCVc5TcxGGqcc7EKDhmCGLpBR8Z94J/5txudYXFkC0elved81y6aHhhwVnXHyfzmXxRsXYwzNpE2d78MwNFZ75K/ZSGI4IxNoulFD+JKKLlJzl78BbkrfwCBiObJNLvoQcQVyZEZ/6Vg21IiW3Si2SVWUbfcNdMJFObQaFBYq7peh5XW3GCoNGanbwgHl4ZbgPpK33Qd+eTbvtliFUKqUw45nXXqY/Gjf8CMl/xXVlvhA8SnnkOLax8/4Vqj06+mzV0v0ebOF4npMpiseR+U6OfLySR76de0uv0Fa7EQCJC3fhYBdx7uPetpc9dLqAbwZKQT8LrJW/MTCaddXBMiV4fRyROmNQ+3EIaGiVH6hjplfUpPwXLiq3Me3bePs7Zs5rLt245d+y4nm0u3b6P3xg2sKSwote/kw4e5dPs2Ltu+jUf27sEdsHTycxkHuWL7dibs23us7VdZWbx75HCV5ey6j+HPve6f7whonZrbsxyOOrP8bQ+0nH+Pd3yNWTSi2/fBGZNwwjVHVOyx1+otpFS/0YAf9XnQgB/1uXHGNwEE9ftQVdTnQRxOshd9RsLAyxBn2A2kToyJ31BFjNI31DVDgFbhmPjKxERea3dizZtukVH8p21bBsWUftpwwOvlvaNH+LhjMl916owf+CYnmxy/n+UFBXzRqRN+hU3uQgoDAT7PzuKGpOoVDWx3iGEvvuJf5vKFrGpYK+Q4HFF1Mo/GrL3Q83R/kFq3LByZ9Q67X76DvHUzSBp+S4n7roRmNBpyJXteuZPdL92KRMUS02kAjqhYYnucyb63H8CV2BKJisOzbxOx3epNROGYcAtgaJgYpW+oa8Jm2h8UG0ui88T/8l2iougUWb6u86tSqIpPlcJAgBauCBwCXlVUFbcGcCG8dfgwtyQ1JqIG9FnzbIa8PNG/NsqjdRI/X+CQWvez8Kljz9nuZ1sUElUnPh2NR9xGu/vfJq7XKHKWTi1x31+YS/7mhbQd+ybtxr2Det3krv0FgMTTr6HNnS/SZMyvyJr9HknDbyFn5fdkfPE0R+d9WBfil0W9WX0YGhZG6RvqmvPCLUBlaRkRwZ1NmnD21i2M3LqFeIeTYXFxxDmcnBefwFU70mkbEUGC08mawgLOTkgof9AKkpTPgEkv+bfFFmqtp8h113KlPVVyrvI8nn+QxnV+Hh3XaxT5m+aWuF6YvgJXYkucsYmI00Vs96G496w/oY3ngFUc0dW4LXlrptP8igl4M3bgPbynTmQvhQ7JE6a1CacAhoaJUfqGOmN9Ss9IoF+45agsWX4/03Nz+bFzF2Z06UqBBvgqy9LBdzdtyufJnfi/Fi35T2YGv2nWnE+OHuWhvXuYdCizRuaPc5M66SX/vsQ8rZkBS8EPjWprbFX8D3nv37hKu3SrrTmKE6yU87csJKJJuxJtXI2a49m7kYC3EFWlcMdKIpqeeAR0dPZ7JJ51MwR8UORfKQ7UV2cnL6VhdvuGSmOUvqEu6YtVLaxBMT8/j7YRETRxuYgQ4dz4BFYUc/pbV2gls0uOjOTL7CxeaNOWzW436Z6ayXcT7SVl4kR/VtMs3VcjA4ZAoVEAaiVq4L/+C+Z+EThrUG2MDZDx1T/Z/+4jeA/vYffE28lZ+QNHZ05m75v3s/et31C4fRmNz7kXAF/OIQ58/BcAotr0ILbHMPa9/SD73hoHqiT0u+DYuPmb5hPZqhuuhKY4ouOJapPC3jfHgUBki8619TgVxSh9Q6UJuxuq4ZSi1r70a5PWrghWFhRQEAgQLcKC/Dx6R0ef0ObFzAweb9UKnyoBta45EAoDNadDI/10eXGSf9fD9zh37W8i7cvvUUlEHNkOx9GkQCCpJoddFOgx86++22o190Dzy/5Q4lpCv9AnSa6EprQMCu9LGn4zScNvDtk2tvtQYrsfLxHReMzdNObuakpbY5yytSsMVcfs9A11SViV/iN793Djjh2kezyM3rqFT48e5aecHEZv3cKKwkJ+vXs39+zaBcBBn5f7dluv+8XEcF5CAtfsSOfy9O0EgOsSk46N+1NODn2iY2jhiqCR00m/mBgu374dgJRii4Pq4grQ/oXX/BEdD+jWGh3Y5kgNl9fdr42X3OD5c43E4htKMDB5wjRTq8BQKURVwy2D4RRhfUrPFTTAM/36SAAyH7vVmbmpnaTU5Lhv7TuwbnChu1dNjFWgkZsHuV9plUdMzXk2GoozOP3pi5eEWwhDw8Hs9A11wvqUntFA73DLcbLggGZPvOtv3XdbYHVNjpvhdJaeoagS+FUyzvP8M9Yo/FrHnOsbKoVR+oa6oj/Gh6RGEUh8dEqg8xnrA8tqaswMp7PaLumqFNzs/ePBXdqibU3IZCgTo/QNlcIofUNdMTjcApyMCMQ99EWg9+iVgUU1Md7BalbaU0XTfLetWBDobaw6dYNx5jNUCqP0DXVFg/TcbwgIRI39JjDg0gWBktlnKkmG01ktJ58vAsNmTfZfYBRR3dE5ecK0WsuvYDj5MErfUFfUiHOYITQCrlt+CQy9cYZ/dnXGOVSN8rrrAx3mPOQdF5aywKc4NR++aThpMUrfUFeYL6ZaRsBx5Xwdfs+3/plVHeOow1ElrX9E41de5vnbkKrOa6gWJVMNGgylYJS+odZZn9IzAmgRbjlOFc5doSMf+tw/oyp9s52OSmdM9Khzxxj3s+29uBpctsWTBKP0DRXGKH1DXdCWUouZG2qDoRt01J8+qPyOP18qV2kvoBy9xPNk4AiNmlR2LkONYZS+ocIYpW+oC0zoVhjom64jn3zbN1tUK5wLuFAcsRVtq4r3Pu/D6Zu0faeqSWioIYzSN1QYo/QNdYH5UgoTXfcx/PnX/QscAa1QKJ5PKl5p79/+qxb8GBjUv8rCGWoK8/dlqDBG6RvqAvOlFEbaHuLMF1/xL3P5tNzEOwFIrMiY0/39Z/zLd83w6ktnqAHM35ehwhilb6gLzJdSmGmezZBXJvrXRnk0r8yGIpF5ImW22RFoseAu7+9NaF79wfx9GSqMUfqGusB8KdUDEvMZMOkl/7a4Ai2zkt7RMirt5Wr0uvM9/+gHYhwz6w9JyROmxYVbCEPDwCh9Q11glH49Ic5N6isT/fsS8zSztDaHnM7cUNd96th7jvvZpoVEVcrD31AnmL8xQ4UwSt9QFzQLtwCG40R7SZk40Z/VNEv3hbqf4XTmF7+mSu41nrSc/TRpWfsSGqqAUfqGCmGUvqEuMDvDekakny4vTvL7Wh/SncXvZTidhcHvVQn83nffuhXatUfdSWioJEnhFsDQMDBK31AXRIdbAENJXAHaP/+6P7LjAd0afP2gy+kNfv+O/9w5n/hHmhS79RtTttpQIYzSN9QFRunXU5xKq3+85U/qvls3FF3LcDqPJfNZGug26y++O0eERzpDJYgItwCGhoFZHRrqAqP06zEOaPrEu37X3693rF7V2ZGaaVfaO6hJS67zPHZmmMWrUQq2LeXwz69BIEB8v/NIPOPaE+5nLfyUvHUzrDcBP95Du2n32/dBA2R89ncC7lySht9KbHerevDBT5+gyXn340poWsdPUgLzXW6oEOY/iqFWmTh2urjOemYdqmqlgw0ERAMB0YCe8C8BlUBARf0q6kc0oI6i1wE/on4c9muH+hH12a8DIuoTR8Af9K9fHAGfiPodDvWJBPwOh/odEvDZ/9rv1ee0XztF/U4J+J0ODViv1e8QDbis1wGXqN/l0MBJ+/cikPjolEDnF65g2ZHODkehRmwZ4362ux/nSfPMGvBz+MdXaHH933AlNGXf5IeI6Xo6kc06HGuTePrVJJ5+NQD5WxaSvfhLnDEJZC/5irg+Y4jrOYKDH/+F2O5Dyd+ykMiWXeqDwodK7vRFxA+sxtIB24FbVfWoiLQB/qOq15TRd56qVnsxKCKjgC+BbVgbgw9V9fHqjlvGfC2BN7EqfkYA6ap6UW3NVwF5qvw5isgdwA+qureyfU+aP2hDvUV8rtjUcAtRY1h57H1BP35QP+AT1aLXfmuBo37RgP1v0YJHA/Y1Lbn48Wvwv9bixq+hFz1Fr31iXxNRH45AwCHqE4f6RQI+sRc54lCfI3jxYy2I/MGLHocE/M77vvM3nnGWe9s1Ub9JEIlOSHBIQTg/7pokb9eGiKhGLeKbNGp9BKCw25lx/vVzSBh2c8hkREdWT09s0n2YJyEgBW4lhsJ8ifN4CxyBQON4r/9wxsLPGydf/fgRRyD8KQsCqFayS4Gq9gcQkcnAOODvthIpVeED1ITCD2K2ql4iInHAChGZqqpLa3D8YP4K/Kiq/wYQkb61NA/2+C7V0tNfV/NzvANYAxilbzDUKiIOINL+KboIgAZ991f2G7i+EPAd3NozsC/qYPctm5KPrt7cad92aerJcuV54sTjjXMlFMRKvDvGEe2JcUb6o6ICzhjxumIDPlcMPlcMfle0+JzRTr8z0hlwREYEHBGRAYcrSsURreKIBYkFYpC6T+7z71kf4D6wgUNvjGv56HVvsiiqA+kH13NddnQ8gKryybyJrN25EJczAk9uBo8OfSQ6cKCw0atrZrPvcDq+5d8l/Gr4Q+xb8EPLrIJCbjrka5kUVy9Or6Kq0Xc+0BdARJKBqaraR0R6A//F+r/uAK5W1c0ikquq8fZOPQ3IBPoAS4FbVFVF5CLgefveMqCzql5SmgCqmiciS4EuInIpkKuqz9oyrQGK+n4LzAHOBPYAl6tqgYh0ASYCzYF84B7V434qNq2BH4LmXGWPPwp4pEg+EXkJWKKqb4tIOjAFGG13u0lVt4hIc2ASUGQmelBV54pIGtAGSAYyReR3wP+ApsBi4AJgoKpmBn2O8VgWj8ZYFog/qeqX9u+ixPMCFwODgPdFpAAYCvwFuAxrI/KDqj5S2mdtlL7BYADA79mwxJv3TbfO7e5ptmuPeOg52/th/9scu3e2dl62f3rBJZ5Z0RExqyM2xSg/x0T5NkVGxvsLpXGzLPG1OaRZ7Q5pQZvDBJof1UDjXKLjCkmK8NNcOLGIjyIBvzMyz++MLvC5ogt8rphCnyvW7XXFenyuWK83Itbvc8X5va5Y9bmi1e+KEZ8z2uF3Rjn9zsgIazHhigw4nNEqjhhwxAKxiJRp4u7Wuh8xEbFkZAdvjo6vPdbtWkRG1m7+csM7fLfsPaav+pi46EbMWP0ZQ1MuZGCX0bz8zQTaN+/G5wsm0av96XyzZDL57hzG9L2Wzq161+jvo5JUuJJiMCLiBM7GMnsXZyzwb1V9X0QiAWeINqcBvbF2nHOBYSKyBHgVGKGq20XkgwrI0RQ4A3gC6FVG027Ajap6j4h8BFwNvAe8Boy1FyWnAy8DY4r1nQhMEZHfAD8B/62geTxbVYeIyG3Av7AWIP8GXlDVOSLSAfge6Gm3HwicZS9GXgKmq+pTInIBcG+I8QuBK1U1W0SaAQtE5KvSnldV37Of4RFVXSIiTYArgRR7wZVU1sMYpW8wGPDm/zLL714+DHDGuZKSz/KmeD/ZcLTt7cmfzSvo7GnyTJdH9YPcq2JdG7N2dc3Y3uRGxy9HHnfO97XmcIu9Ec7sRa2ij87vFB2YHRUZtd/lauOD9kW7+Ri35rQ4Skabw3q0zSHy2xxSf6ujbkeTHHd0XGFWYkw+zRzQpLrPEBCn1++MzvO5ovN9rpgCnyumaCHh8UbE+k6XvNj1R7Z1Cvg8EU0OrV2cuW9ZhzhxOaILMvYFHJERSzd+32lA8jC3Q/2eHQfXt3Y5IyOycjNxOlzi9bnx+b2ICNOWTAaExLimNE5owaCuY3jt+z/zu0ufr+4jVAdPJdvHiMgKrB3pUuDHEG3mA4+KSDvgM1XdHKLNIlXdDRA0Xi6wTVW3220+ILSyAxguIsuxFi1Pq+paEbm2lLYA21V1hf16KZBs75TPBD4OMiCVsHyo6vci0hlrt30hsFxE+pQxVxEfBP37gv36HKBX0HyNRCTBfv2VqhYdi52FpZBR1e9E5EiI8QV4UkRGYH0ObYGiJFglnjdE/2yshcMbIjINmFrWwxilb6hVxk0aE5g4drqHE8zhhvqCasDnyZkyT/37RgDEuZL2OMTRNknjaKQxC3bs6D+8RcHWxa/1uK3nZ/HXr/hi4DV91mvTRo/v7rn079tudUS63XKed+nem9w/5z+Rs7FDlPg6AeSIZC+Pjto+NyYma1l0lGNHc1ezHS2kD9aOsQQRPi1snsXB1of1SNtD5LU9pN5WR1SaZhOVUEBClJemojSXMsKMHeqPcPjykiJ8eUmh7rdV5ZX8TKJF6LVq4sitO9L5Z+s2dFuY1hHg/QO7ON+7ne77prFz91Z6REXRdc4fdFR0Qt74PbsiVi57m6tadjj80dafEq9s0+PA0T3zcLlifG2i5YA7Z39qs4wVy/2uGE60SkS4Ao6IKHU4o1QcMWpZJeLKs0pUgXIrKBajQFX7i0gilpIYB/wnuIGq/k9EFmKZk78XkV+p6vQy5vVj6ZTKHN3MDmH293Hi7zn4/KT4fDF226NFPgploaqHsczt/xORqcAI4EAZ88GJp3VFrx3A0CDlDlC0zg32EanIZ3Ez1rHEQFX12kcKRTKEet4ThVP1icgQLIvNDcBvKGnlOIZR+oa64DDQKtxCGE5EAwVH3dlvb0MLjsXht4vttgNrp8FZvpSEbyKXc/Bgl8Fud9zaq/tOSblApjmfkT8u2NK++zB/h3iHp8C396tNjXKnHjijiyjtkmXfrpucP2+/xLkgenj+4T4jCgpji8b2gndDZOTmBTHRBxfGRPs2RUYkHnU4klUkyeuS6L1N6bC3qXRY2i20vI6A+ppls7/VYT3c9hA5bQ+pp9URaJatkYl5xEd7aOJQWkgpnuwuEX7TrBmP79/Ppdu3cWViIt2iovjwqLX5Kvo2/yk3h2FxcRz2+3Eg0hhf3FttWwPwmz27WjVRH7c5spMfP7iP2Xl5/LBjYdffN29O37WvV7jyYAmrhDPG7YuI8XhdsV7riCPO77N9Jbyu2GO+EgFnpNN/zFfCGaViHXE4Ar6cis5tEwegqlkiMgV4wVaCx44J7F3xNlX9j/26LxCs9CcQOsV2FjBYRJJVNR24HkiwLQFgnYNnYSmxUKWc07HP8EVkANDJvt4O6Fq8sW0W3y4i16rqx2Jp3r6qujK4nYiMARaoar69K+8C7AT2Y+3ao4BDQAYwx/ZLaItlpfh/9nPMt4f7AUu5PmOP3T9oRx7MHOA6EekJ7MI6ty9OInDQVvijgY4h2hQnB0iw544HYlX1GxFZAGwpq6NR+oa64BBG6dcrAv7M7Z7s94DAgODrbeO6HfM2bhNo0jtSXas84uubldWq99Ill+0YMHAqjzv+OHwDPdc/q38MFMTE9vb2a9IG1YBjf8GybVuc7r/n33LGk75bIiPxus9zLFl6k/Pn3IGOTR2ixNcp1ePplurxdLsnK/vYnLtdzj0Lo6P3zI+JLlgdFRV9wOVs67dMyifK7BDXwSTaHEySNqs6h34uUQ00zuVgyyNktjmkuW0PaWGbw2jzLI3459o9KYuy85IQcXzfucuxPjckWd/D3+Xk8Pu9e2nkdBLrcHDQ56WFy8Vhn48H9u4h2++nXUQEDzZvwTfZ2WzyePhfx448vv8A5yU0Ci1QKZRnlagCBZbVunKIyNnAQ8AsYBgwO+j29cAtIuLFUox/rciYqrpNRK4HvhORTGCRfX2kPefbWNaFTCCUw9mnwG32ImExsKkC094MvCIif8Ja9H0IHFP6IuLCOmt/SUSKLAlvqOpi+/5HwCqsHfZyrPP5P2NZAQpti4cDuNEe8gFgooiswtKjs0RkXAi5Hsc6FuiPtWDYh6Wwg3kf+Nr2hVgBFHdADMXbwCTbke9C4EsRicayLDxUVkfRSkd6GAyVY+LY6TOxzGiGeoDfs2mZN29qZ0Lka7+640MbXI7IlKL3G517F82OWH8sBW9EREHGoMFfZLhcvl4K+jE3zvmKq3qrOI6fybv9h1xbc9Y49+S1lcDxnVmy7Nt1s2UFiGnF4d4iHLMCFCfbIVnLoqLT58VEZy2LjnLsjHA1LxDpVNrxQEXI25iHP9/Prom7OOM/vY60PEJGm8Oa1S5TC1sfJvDtigMd1h3Ob/Zuh44H38s43PblQ5nRS7v34N0jh4kWB32io7h7127mdevGY/v3kenz80yb1vxq1y4+6JhcVbFqijN7blg/v/xmFiKSi6UsJgMXFXm6i8jDwF12szdU9V/29duwFLQCq1T1Vlt5Z2N5krcC/qCqn9he59+oai971z0R2KyqL9hjvY0VIfCJiMzguENaMyyv+eRQkQOAl+ORBZ2xFgf3YlkSS3ju2/McxnI2XAZ8heWAh/0cI1T1BAVc/HMBvrOf7wIsRR8JLATuV1W/3f554HxgPJZZ/VIsM/w84LdYFo03sBYv1wGfFWtzn9ahIjZK31DrTBw7/TNsZxZDePHmz5rldy85kxBWPpdE5F7V8aEY26MbAEX1v1G/pAdEi0ysOBzevEGDv1wfFVUwCCCHhCPP8OiarXQdZoc0HsNxqHCta1P2Ecn29heIL7oehafwXMfStTc7f84b6NjUPtL2BSgLD3jXR0Vunx8TnbEoOtq/2T4ewDqXLpddr+wid10u/hw/rsYuWlzRwvo6BpqMaYKqsu/dfeSszsER4cCX5dML/5yy7eC3GRGx2erbuysvMS/fG/VeSuf149bt6C1KZKEGXL9t1qzSO/1aIKXnhvUbK9rY3r3nAKOCQtcGYu0gz8DaMS4EbsFyEvwMGGaHmjVR1cO2Uo3DsgikYDmwdbWV/nysXXIk1s75HlXNt+d5m/KV/otYpvjgyIGWWBaCq7F28neq6goR+ZkTPfefUtUx9jzNsML6/CLyNZaz4FzbJF5YPI6++Odin6/fCPwRuMo2wb9sy/aOiChwvap+ZPdvYvsNICLvYllOfo1lsj9sj7W1WJuPVPXriv7uqosx7xvqgsPhFuBURzXg9+R+PFd9e0q1uLSK6bRZRE4LviaIpPo77F7p2nFMKQcCEXGLFl7V/7QB38yJjz9yVgI5jf/KhOHr6L3uOf1/FErMsZCrQNPo3p6h0eAL5LrSc+c4d+QmiU/7uImMnhoYOnBqwEpn20n27rzZOT394jKsAJEQ0c/t6d7P7ek+luPHAztdrj2LYqL2zI+JKVgTGRljHw+0Ld6//a/b48nwsONfO+j295KOAyJCm9vaAJD5bSbufW5JbyVd/Nc3Zd2kXfjiA7S6qy037cke7BjQlMZnNSbRqwXfZnFwxWE9WuSA2PKIStMcohMKiI/y0kyUZmU5INYQhyrZ3ou1y7wb+J197Szgc1XNAxCRz4DhWLviT1Q1E445wxXxhVoJq9aJlfHumDwVcawrgxKRA7aTXHOsmParbU//8jz3P1ZVe2nHXOB5EXnfHnN3iHlP+FzsBchvsI4GFhcFpAAH7fZ+LItDEaNF5A9ALFZEylpVPS1oobNYRK4u3gYwSt9wUlHZLyRDDaKBwix39uTNaF6ZRyzt4npkhbp+mq/T4JXOHRkIzY9fdbiWL7vkrJ49Z85s1nznSIBerO31OrcGPtKbZn/NlX0QOe605HLE+7o2OsvXtRGS7dni2pi9x3HY3UespCVs1zYd/ua7pcPffLcQhafwPMeSJTc5f84b6NjcoTwrQAefr22HHF/ba3KOO01nORxHl0ZHFR0PuHa5XM0LRTpRgXS1uetzOTLrCJ0etaZ1xjpJfjgZAH+en4xpGXT4bQf2vLUHf74/5ugFzTru6R7bcUkp4zn96m2Wzb5WR/Rw20xygx0QG+WTEOSAWNXvYz+VX1gHsEzNP4nIH1X1SUr3NBdKzzflLtausgR76h/zmg8VOYCVrjcLyyFuGJayLM9z/9h/ClV92g5puwgrFv6cEAl8SvtcJqvq/wsxfmHRosI+U38ZGKSqu8RK1HNCJEBF2tQ2Rukb6gKj9MNEwH94hyf7XR/4B5XXtkV0h4RQ1104ozsHWi7c5jxQwjt9/fqRI5MLls9u137NmSI4HajjBt4ffhFfHf6n/mn2drqcVTz7njaK7Ood3KwrAfU4d+XNd23LicQTOK1oN+wmMvrrwJmDvg5YWUo7y94dNzt/Tr/YuSC2JUf6iJQMWypOYiCQNCa/oP+YfCui6q4vC/h6k4/ISDwJTodvUEHhks2REYlZ9vFA7vpcdv5nJ65GLryZXhqPbowr3oUv28fOF3fiz/fT8qqW5G3Mo8WlLdj2920knZ5Ek7ObsPPfO+k0ofR1id8pEQca0/ZAY2m7siwHxBwOtDrCoTaHNadtprqLHBAT84iL8dDYGaClhM68l9Fzw/pKJ+exvdgvAWaLyAEsZ763ReRpLEV3JXArlnn/cxF5QVUPBZuwa4B0rF30IoLS/5YSObDNluUKrIVArr04KNdz3x6zi6quBlaLyFCsI4kSTnMhPpefsRzlXlDVg2Ilw0lQ1R3FuhYp70zbAnEN8EkV2tQqRukb6gKj9MOA37N1hTfvyw5ULPFNINoZVyIcqoih3u6p2xwHCgihcNPTTxteUJCwqFv3+X2KzPKNyGnyN/5v+Fr6rH1OJzjcEtOzxKAOifR3jB/q7xiP5Pt2uzZlbXUcLOwmSpvgZtu0TccnfLd2fMJ36zErwM2un/MHyOYOkeJLrsCzcUf/CH4zJJIbPsmPbOzQyP/uP3jM6rHD5do1MYPcyc1drbNyAjGdH+mYE9MzvhlA1sIskoYlkXh6Ituf2k5kq0j8BX4ikiJwxluuDwFvlZLhnYCKOA43ouXhRrRc17H0DXOjPD3c8iiZdgbEwtaHCCTm656SH24F57XO5i/AUvgPYp3pL7Jvv6GqywFE5O/ATLEK9SzHyv1eEzwLfCQit3JiOGCoyIFGtsx5tlL+UUTyKMdzP4gH7ZA4P7AOK8VtSEJ8Ln8CfhDLZ8WLlddgR7E+R0XkdaxCRulYkQfFxy23TW1jHPkMtc7EsdMvB74ItxynEt6CubP9hQvPoILV1xpHttp8XtvbS4mQt/gqcsmsg46sUo8IkpL2remT+lNrEU4oOxdAAh9yy9xpXJ5KOSlCUQ049hUsd23J9kqBf2BpMfdFBFkB4lpypHdZVoDLPsjn2y2W31bLOOHxUVEU6euUZg5u+7yAHI/SMdGBV/HniXi6DkrYvcfhdEaOaapr/7y1S6c/dmLfu/toe1dbdr26i0B+gBZXtiBxcIV8CWuLL1bfvto4yhoqhFH6hlpn4tjpvbEqQhlqGVUNeHM/mR3w7apwohiAvo1Hzu6ZdMbwstockbwdn0YuaI+U7pQWG3t0+2kDprocDm1f/F42jQ79gz+vT6fTsAoV3HH7M11bstc69+a3kwBdymsehafwAsfiNTe6pucNkE3JkeI/IclJ+tEAl/wvnzX3x5foOyPdx9UfFdCukdAmQXj23Gh6t3CSVajc9FkBB3IDPHF2tHfaQTm8PzYiK+6CZvu3REQkZVvHA+F23f/P6ttX/678ZhZiyuqesmV1wSh9Qx0wcez0CKz4WXOcVIuounPcWZM3oLmDK9v3/LZ3zkmKbHFWee2mRM5dmOMoPL2sNhGR+RmDB3+Z6XT6Qlqd15C65nkmuNwSnRLqfigcmYWrXZuysyTHe5rY2eTKo4vs2XGz8+f0i5wL41pypPeOrEBMaUo/2604BOIjhW82e/ndd242//bEdkcKlOs/yeez62N56LtCjhQqDw+N1Nado3ctjI7euyAm2r02KjI2w+ls5xdpXdFnqwEeXH376n+X38zCPguPt19PBjap6t9rTbrQMozCrmwndlld4AatpbK6IvIqsE6DyuoWhSrW0nxlltWt5tgzsMMcq9TfKH1DXTBx7PT1WI4zhlog4D+yy5P9jhv8pZ7Ll8W1yY/sdIizQ3ntdjsOrfkuckW5RUqcTm/uoEFfboi0Y/lLyIsE/sdtc77l0n4VjbMHwBfIcW3LWeHcmddU/FpWNbYTiMZdcPqR7zb/9NE7Xbc/EJtR3ApQnOR/5bDk3jiaxR43ajz0XSFXpLjYdCiAX+Gm1Agu/zCfX24vuQY54nAcXhIdlT43JiZnRXRkxG6Xq4VbJBkrM1xNc8nq21dPq2jjYkp/LJbj2/1Sh2V1g5W+/f5DrFwAvaiFsrpiVa2brKqfFrteXI4aK6uLFQpZG2V137bfFxAi/395mJ2Xoa4wSr+W8Hu3r/Lmft4Gy3RZaaKdcRkVUfgA7QJN+0Sqa41HfGUqfr8/In7Roqv69T9t2pz4+KMlLAgO1HELk0dcwpcZ/9A/zdlJcsVM/i5Hgq974nBf90Qky7M5YmPWPjniSZXQOc3J/OZfFGxdjDM2MSb3mr/0zXB9T3f3yx27yJ4dtzh/2hGxdUbLcZ9n9GiXILgccHWvSC7o6sIXgMs/yCfLDX8bE0Xv5g725gZ4foGHga0dtIp3IEBhKXu5xoFAk3PzC5qcm3/8+9gtFK6OjNo8Pyb60OKYqMDWiIjG9vFAyKiJSlCRNLUlEFNWt8GX1a2A/CUwSt9QV6wjTFn53pvxDGt2LCAhJolHr7O+35Ztnck3Sydz4MhOHrlqIh2b9yjRz+vz8K+vHsTn9+JXP6d1GsHFg+8A4IsFr7Fu1yLaNe3KbWMmALBo04/kubMZnXp1nT2br2DBHF/hvCFUo4ph29hu2yA4Br9sBvu65M2NKD/5m6ojYvmyS8/q1euXmU2b7Q7pY5DE0eZP8UjzVfRb/YL+IdIj0SV/EaWNnxjZzTOkeTf86nbuyp3n2p4bbYf+HVs8xKeeQ8KASzjwwR/Z/+4j+Auy2T3xdnLOurnjikDzjt7DZxJouzOQ2D5h946VC5t9uMYb8c1mX8S1vVz0au7khj4RXPB+Pm0ThLM7OdmfC2MHRXDFhwX8e6GHv44KFUEXmiglepDb3XOQ2w1H7WcA3R7h2jE/Jnrfguho97qoyNhMp7N9QKSitSo8WOfilcGU1T15yupWGqP0DXXFunBNfEb38xnZ+3Le+eUfx661aZLMPec9zgezXii1n8sZwQOXPkdURAx+v4/nv/odvToMoVVSB7YfWMsfr32Dt39+kj2HttE8sS0LNn7PuIuerotHsh32Pp8d8KVXymEvFG1juxdWpn2Kv+3g+a5NOwKiFakGxrp1o0d26rR0Vtt2686SUpwA+7Iy9U1u9b+nt8/8nov7V8rk75Qof3LCmf7kBCTPt8u1KWub42Bhd4HW0e374Ms6gKtRM9rc/XKJroU7V5G9aK9j7xl/6BBxhmUbbiu703fMf8kbmbsrqsDrb+EQov93dQznv5fP1zfGEhshzLu7Qm4F5SIgnb2+jp29uR1vzs49dv2Qw5G5JCZ657yY6JwVUVERu12ulh4hmaAUyTYbV9++2k/lMGV1T5KyulWhtlNDGgxFhE3pd23Tl9joEx2sWzXuSMuksq3hIkJUhPV35g/48Ad8CIKIA1/Ah6ri9blxOlz8vHIKo1KvxOms/XW0qifXnf3GkppQ+ABNo1o3Lb/VcQRx9Pa3L56YpEy2bx84Ysvm0xerUur5o4OA8zb+O/IlfuVprzvmVGb8IjTO1d57WtOR7vPatPD0SVociHEuVKVMhyr3ng3sfes3HPjoL3gydrBZ2yUvOe3P3V7c2a1Dh/daRDYefPnGX89M2HJ1r6jM2IiqJJ2rPE0DgWbn5+UPeDzz8Mgv9+w7c+mOXV0W79jteXPfgXW/Opo1u1+he1aCP7AmUnVR+aOFRlWzsIrIPCIiJ4RGBifHwSpU07eCw24AOttn0mDF21eGdGCALUNwWd2QqGo2sL3IQiAW/Yq3E5ExIhJrvw4uq7sDu6yuvQg6u1jX64P+LV5Wt2js/qWINwcrux8ich61UFa3KpidvqGu2IBlvmpQC81AwM8/Pvs1GVl7GNH7cpJbWkd3/TsN5+lP76NH29OIiYxjx8GNXDjwttqXx5+1x5M9OQ98Q8pvXT4OnO4IR1SZ8fmhGOjrPHi1c+chisXkl8X+/d1PL3THr+7T5+d2IqHP4AEac7T50zzcfLkOWPkfHonxSFT3ysqHiDPQNm6wp20cvnT3ocAn3mgVDoqeqEQiW3al7a/fwhEZQ8HWxWR8/jfa3vs6jqg4WlybBuBYXpjbI3Ppdr6/8t888cmzOU3yt7sfH0bG1Z0LO4nUXQrVaNWYIYXuXkMK3VjZaAHLqavKqOpyEVkJ3EDNlNUtEJH7KVZWtxLUeFldm4qU1d2MlXgomCipQFldLB+I4jwOfCBWmeGZ1E5Z3Uo78hnvfUOdMXHs9C1Qfrx1bXAoZz+Tvn302Jl+Ef/66mGuHHpfyDP9YPLdubz+w2NcO+y3tGly4ubj/ZnPMqL35ezK2MT63Utp27QzFwy4pcafwe/dsdqb+1kr0Aqfv5dHy5jk1aNaXZ9alb4/Rayame7MqLS1IS7uyLb+p02LdDi0XXltAzj873DnnB+58LSqxsP79+/lyB8foNlbn+A4WLDKtTk7W3J9AyWEuXT3K3fR+vYXcMYeP104/PPrxHY7A+/hPaAB4nqN4uBnT9DpxrT8CxyL1t7kml7QX7YkR4i/Qs6QNcxo0rJmhGHeUhGReFXNFSlZVrchYZvaB6ldaKgK/aMAv6r6xEr7+0pFjiFqmwa16zI0eJaFW4CqEhsVT7fW/Vm368SsmbsyLf+mFontWLjpR+4+9zH2Ht7OwaxQBbyqjq9w0Vxv7qfda1LhA7SPS6lyDvUzvT16oVTKHwAgL69x58WLrorw+53legM6CDjv4M2RL3FPYTvdObdqkh4n0CKmr2dYy7PcY1p7fMnxs715hzYXbXzcezeCKo6Y42sL7+E9+HMPE90hFfW5wa4crD4PBUTFfh4YPvhaz19GdHO/2+E89z+2T/adN/OgJi3RKnwuVUApuTOtD9xj79TXYpmvXw2vOGGjA1ZlvpVYPhP3hFkewCh9Q90yI9wCVIacgqPkuy3nKo/PzcY9S0v4AUxd/F8uHnQH/oAfq8IoiDjw+NwlxqsKqqqe3C9m+ArmDCN0sZVq0Sq6Y5XN07FENW+mCVXKHe7xxLZcuODaNh5PdIUWgo050uIfPDRsvD65MkLdoTzJQ3L0iQkc/s3t+HftIOO68yn45nPyv/qY/G8/TfT1SByeI+u67Xn3fs+eN+7NO/zjJH+zy/5wQuTg0VnvkjTcstrE9RxJ3uqf2P/uIzQaclWJuTZp+05/8d0xcoj75UG93P8NjPeMXbw40H2WV507KypvJVlLWlbIyoihEBG/iKwQkbUislJEHrZzyZfVJ9mOlUdE7rDD0EK1+0bsFMuq+oKq9lfVXsB9wAsistWed5YdVldpROSvInKO/frBojP6cvrMEJFyi02FQlWTq7rLt/tvVtXTVLWfqg4uOk4IN8a8b6gzJo6dnoIVr1+n/Penv7F530pyC7NoFNOYiwbdTlxUIz6e+yK5BVnERMXRtmlXfnPxPzial8n/Zj7H/Rc9xZ5DW3n3l38SUD+qyoAuI084t1+5fQ57Dm3jokHWtc/mT2L97iW0bdKZO87+Y7XlVvXme7LfWaWBrDOqPVgpXJf8+wwRR5WtB4cld/tnkQuTkSqVVUUk4D1twNRFcXFZwyrax4/DN5lfzf2Z8wYUj3H3H9xP1tN/JnD4EIgQe8nVxF590wn98z6cTOHP3wCgfj/+ndtp/tl08PoKjzw81ktufkTSqDuj4roPFYCDnz5Bk/Pux5VQKX/HE+ghO7ff7Px55wXORfHNyeojUiMLuNdIy7qvoo2LJeVpgeXJPldV/1JGn2SOJ+y5A8vc/ZvS2ofo/yFWqt9HVTVgOwj2VNUKJxMqZdx0KmB6l2pmrzsZMUrfUKdMHDt9L1CXKUobJOrP3ufOnpwF3lpLaJQQ0XTHRe1+VaGwu7L4IGrOojxxV8OxULV3719mNmm6Z1Rleh2myYGn+MvWvdLuWA5z/6EMAocyiejek0B+HofH3kTSX5/HlRzalcQ9byZ5n7xPk+dfI/+z/0FkNNFjzufIg/e4W419cUHhnOn9vBnpSUln3RSyf1WIwZ1/kWPh2htd0wv6ydZOEeKvUlIl4FbSst6raONgpW+/74zlLNcMy+r7NDAKy6I0UVVfDaH0LwNisXxzPlfVP9hjpVNMCduZ8n4Cuqpdc76YPF9gJZSKxkoE9FqRnFhHAqOBI1jpeTNE5G2sEMM2WNX5NgKZqjpaRF4BBmP5aXxStJApUvpYxyBvAoOwjkXeaoh+BjWBMe8b6ppfwi1Afcfv3bXWnf2mszYVPkD72O414ngwzJtSTQ92kbVrx4zasztlpioVrlPbhMMtn+F3Zz6sT6+IUM9WAGfT5kR0tyIsHLFxuDp0wp+ZUeoYhdO/I3rMBdYbpws8heD1IDHRUZ5+iSOz0n9MjLn9jiUa7VykVqx0tSkgKvbTwIjB13jSRnRzv9v+fPfT29/xnTszQxOXqVKZc6GZ1ZFDVbdh6YAWwN1AlqoOxlKe94hIqHC5/lie/anA9SJS1oKlN7AilMK3uUtVB2Ip4gfszHxg1VZYpqoDsJ7xBEuEHUa4FxitqkUpch9V1UFYoYUjRaR4iGF/oK2q9lHVVKwUw6ckRukb6priCT4MQfgKl87z5n7cBbRFbc/VJrZr9QvBAx0CzfpGqHNtdcfZtm3wyK1bhiyqrBPcQBb3f4NbOozWH2eieizDjX//XrxbNhLRM3TiNS0swL14HtEjrNDs6LMvxL14Pkf+bxxxt99HwZcfEXP+JaJdmw9yj2w1xD2yZYa/TcwMFSqVo6A8NmqHTo/57hw52P3KgN7ut3yPeO9btMTyBdhVRrdtpGWVdb+iFB3LnMfxULmFWPniQ4Vy/qyqWapaiJV7ozqWogdsJ7cFWDv+ovkCWDnvwUqzW24hKOA6EVmGtaPvTcl0vtuw8ge8aKfEza6G3A0aE6dvqGuM0g+Bqqo3b+qsgHdzjSTcqQiJkc0rmuq1XAb6umQviKhSCvgT2LevxxmFhfGreveZ3kGEpIr2c+GP+BWTRl7BJ/ue1sdW7ylsPPToXx4h4f5HcMSVrKoH4J4/i4je/XE0ssLzHPEJNH7qRQACOdnkf/A2iX99juxn/0ogN5vYa29tRWq/VvRRdRwsXOHanJ0veb4BUjKLW5XJJzruE//IIZ/4rf8GKbJz283On3Zd4Fwc3+xEX4DvqzuXbd73AwexlP9vVfX7Ym2Si3ULlYWvNNYC/UTEoUVersfHHYWVznaoqubbZvjSPscyz6Bti8QjwGBVPWIfA5wwln29H3A+VgbC64C7yhr3ZMXs9A11yrhJY7ZjZd0y2Kh6CzzZ/11Qlwo/whGV5RRXlSryhaKXv90QUamJnSdHjrTtu3zZxYdUZU9l+zYjs/XTvt8Ojf2/K3JizxpxqGgXH4rC6d8TffYFIe/lvfMacbfcTeHP3+Hq3pNGv08j903bcV1EAi1j+nvOanmme3TrQl/HuFnqkPKLEVSBDdqh8599d40c7H5lYG/3W77fe+9dvDTQbdYebVpdR7iiSnEvqeXY9T3w66LMfCLSXaySt1VGVbcCS4DH7Zh9RKSbiFyOFcp3xFb4KVgFd4pwANfYr2/CymxXnOCsdI2w0t9miUhLrNz6xZ+3GeCwq+z9GTvr36mIUfqGcGDO9W00kLPffXTSdg0cHVqX87aO6bK56Iu4JnAgzl7+ttvLb1kx8vKadFm08Eqn3++slPlAVXn22QwGdncnfHTL9EYj9eeZqOYVbxfIzcGzainRZ44qMYZv9w78hzKI7DcI3IXgcIAIeEIct0c6knwpSSPc57bp4R7SbH0gMWK2BqXLq0nyiY772D9q8NWex88Y5n6xKuf5MUUhe1gOdj9gZY0DeAPLXL/MDtF7lZqxBP8KaAVsEZHVwOtY5/HfAS47q90TWCb+IvKA3iKyFKtaXqhsgK8B34rIL6q6EsusvxZ4C6viX3HaAjPs44u3gf9X/UdrmBjvfUOdM3Hs9Juw0k+e0gS8u9d7cj9OAq3zaIZhLa6c2S6ue41aFrz48iZHzfRSCbN8eTidnuxBg7/YGhnpPq0i7VevLuShB/fSqVMkDntLc/ntHQ//b+ewo3nxbTrHXmYVcSv47ivci+eS9Od/lBjj6ON/IP7ucbjadSRw5DBH//wQgbxc4u/8NdEjzilfCH8g35met8y1I6eReLWiOesrw4/pT198Xi2MWy8oHmVgqFmM0jfUORPHTk/Eqm5V48lmGgq+wuXzfQW/9MMKf6pzLu/w2+XRztgKKdLK8EPEypk7nZk1upgQ8XsGDJy6JDY2+8zyW5fOQoYue5nfNfZJRJlFXGoSyfFud23K2unIdPeSSpQvLoffpj99ccgkOScDRunXLsa8b6hzxk0ak0UNOCI1VDy502b6Cn45gzApfEH8UY6YyhexqQDDvCk9UTw1OaaqM3LpksuGHjnculohaqczf8Cb3NJ2hE4PafKvDTQhopN3YLOR7nPbNPb2SlqoUY7F1Qz9U6yiNBUiKAvfGhH5uCJZ7KqKiHwuIlcEvd9oF8Epev+piJRMZViM0hR+cEY+Q9UxSt8QLj4KtwB1jaqv0J319ryAd+NIKld3vEZpGtVmc3WdtEojjqgWTTW+yuVeS0dkzZpzRu7d02OmKgGPJ8C4+/dw7z27ufuuXUx+u2QJAVXlpZcyue3Wndzzq91s3uTGhS/y+qP/GRk/bnjEkVsuKiicc9y95OifHsSfebDmRQdwiMvfPu5096jWg90jWh70t46ZoUJVHB/npj998b5KtC+wU+L2ATyErgZXU8wDzgSwY+5zgWBflaF2m3IREWfx96r6mKr+VFFhio9hsDBKnxKr4a+LckiX0X6QiPynCvMkiVV2suj9KBGZWgWRy5snWUQK7GdaJyLvSLF62TUwR5VzWtt8BXVSlKReoIHcg+6jk7Zq4HC1TNQ1Qbu4Hgdqc/zh3l6t0bLDrKrK1q1DRm7bOnihyyXuZ59rzWuvt+PV19qxeHEB69ad+N9p0aIC9uz2Mvmd9jz0cDP+/W8rWdwv03O57KKYyE9ejYqJfeeJPJd6t7vnzcTVrSfOZrWeHgFiXK29fZuMcp/bpp2nX5PlgVjXPKXCSXmmlN+kVGYDXYt/74jIS3a2PUQkXUQeF5FlIrLa9qxHROJE5C0RWSwiy20P/OLMxVb69r9TgeZi0QlrAbJfRF4RkSVi5eIvciQsmvsxEZkDXBvi/dsico3d9mxbjtW2XFGljPGA/R24SqyUwKc8RulbBK+GD2PFcZaKqi5R1QeqME8ScH95jWqIrXYZx1SgHVZcar1h3KQxOcDX4ZajLgj49m50Z73uA0/vcMsC0Dqmc40uAIvTTBO6xBJVa7nO9+5NGbp+3ZgN0dGOLACfT/H5lOKxCPPm5nHueQmICL16RZObG+DQIR9Ol+BxK16v0jS6IO41381t5d3nj8Zdd2t+bckcEhEJtIo5zTO85Znu0a3yfR3iZqlDyiom5Ac+ruJULqxQttUVaJ5pZ8N7BSv+HeBRYLqdsW808EwIa9FSoI+IRGIp/flYqXJ72u+LvOrLyp5XqKpnqeqHpbxHRKKxPPCvt7PruYBflzLGBOA0Ve1L7Vo5GgxG6ZdkPlZ4ByIyRETm2SvKeSLSw75+bKVcRpveIrLI3m2vEpFuWLmtu9jXnrHnixeRT0Rkg4i8XxRGZa9WF9vWh9eCrs8QkX/YY28SkeFlPYydAnNR0DOVWCHb1z4v6iMi54rIZ/brkKvyoLZOewW+xh7zoUp81u9Uom2DxOdetdCT82E70DbhlqWI+IjG1c63Xx5nenvU6sLi8OF2/ZYuvSDjV3fv9l1z9Q4GDoyhZ88Tc7tkZvpp3vx41Fnz5k4yM/2MGRPP4iX5/L8J+7jt9sZ889XhyHsuL0j6V/T4I831wMLalLtUIp2NfT2TRrjPbdPNM6jZ2kCjiNlqxaIH82P60xdX1koTI1aY2hJgJ1b++fL4zP53KZBsvz4PmGCPNQMr+U2H4E6q6sYKmxuAFXe/EOv79Ez7p8i0X1b2vOKWjFCWjR7AdlUtCuecDIwopc8q4H0RuQXwhXrYUw2j9IOwz4DOxjI9A2wARqjqacBjwJMhupXWZixWEYn+WLmld2OtOrfaVoXf2+1OAx7E+o/fGSiqNvaSXY6xD1YRiUuC5nSp6hC7X6kVsuxnigZOB74rY4U8HegpVsIOgDs5npu6NnNaf4eVDeykxJP33Uxf/k9DsHKJ1wtiXY32OcTRtrbnSQ407+9SZ61WVCzIb9713nt/m/Hue522btjgZvv2E/0HQ50wiEB8vIMnn2zNy6+0o1u3SBYsyGf4iDjefW5t28ZpV59+/pI/rHeqt0ZT7VaGQNOo3p6hLYa7z27t8HVJmKMuKdqdv1WF4YqsmP1V9beq6sFSfsHf/cUz4RUdNQRn3BPg6qCxOqhqqN/vPCwFnKCqR7Di74uU/lw5nj3vbHv3Pa3Y/MUdLEM5XJbnDxPc52JgIjAQWGpbPE5pjNK3KFoNHwKaAD/a1xOBj8VKVvEC1qq0OKW1mQ/8UUT+D+ioqgWlzL1IVXfbaSpXcHxlPVpEFoqV0GJMsblDrcSL0yXomXaq6ipKWSHbGbneBW4Ry59hKPCt3abWclqPmzTGx0kYr6/qc7uzJs8NeNaF1WEvFG1ju6XX1VwDfZ2O1PYcbnd86/Xrrm/WpUvs/sWLT7TON2/mIiPj+OYuI8NP06Yn+na9++4Rbro5ienTc+nePYpHft+cle/P7vkmt7Q6U2fNoPS/29rH5YjzdW10lvvsNqnuM5ov4fhmpLrsAHrZVr5ErI1OeXwP/DbI4lhauOdc4D5gpf1+FdauvwOWFaDc7HkVYAOQLCJFGSVvJUTxIRFxAO1V9RfgD1jHq6d8KKBR+hYF9o68IxDJ8TP9J4Bf7N32pYTODR2yjar+D6sMZQHwvYiMKWXuErms7R35y8A19u759WJzh1qJF6foTL8rcIaIXEbZCui/wC3AjcDHquqrwKocezXfD8vkNw4rs1dleLuS7es1GsjLcGe9ukkDhypcH74uaRfb3VtXc/X2tx8iKjVSya84eXl5FBZajnuFhZK4eHFsy/j4+BN2nkPPjOPHH3JQVdatKyQuzkHTpsf/XHbv9nLokJ9+/WJwF1o+ASLg8SgR+KLG8e9Rz/GbQ830YHhM/kFoYuSM9KcvrkwFvtLHUt2FFT2zCmvRvbwC3Z4AIoBV9gbniVLazcOyWM635/JhWfOWqGqggtnzypO/EMsa+bG9KQpgpRQujhN4z26zHHhBVY9Wdr6TjVPe1BGMqmaJyAPAl2LVZ04EivJ/31FKt5BtxCpmsU1V/2O/7ou1+k0oMUJJihRrpojEY+Wh/qQSj3IMVd0nIhOw0k6Oxl4hq+oWglbIqrpXRPYCfwLOtbuHWpXPCB5frJzWHlX9VES2UkklPm7SmFUTx06fgVXHu0ET8O3f7Mn5IAY0NdyylEbjqJbN6mouBw5Xir/N1vWuPe1qeuzc3Fy++OILAoEAqkrv3r0lIX5EyptvvL25Rcv8bpde2ojTT49h0cJ8brt1F1HRwu9/f6Jn/ltvHeauu5oAMHpMPH95bD+ff5bF7Xc0PtamFfvb/Ztft5uloxa/wa9b+MVV6/4QIVCstLiV71hKzLuq/gFr91v8enLQ6yXYf5e2pfK+CsxXVLwn+NqoYu/vKKVvcjnv7wh6/TPW0WhZ8nupWIW+Uwqj9IuhqsvFKvd4A/BPYLKIPEzJ6nBFB4altbkey1zuBfYDf1XVwyIy114pf4u1cw4lw1EReR3L0zYdWFzNx/oCSMOqk120QnbZ4wavkN8HmqvqOluOlSJStCrfRuk5rf9rm9Kgajmtn6GBK32fe+0iX/73PanYoi4sOMWV75LIWknKUxpDfF0HrnfuyUJIrMlxW7ZsyX33ldBB0r37nd26dl04U3XTCBGRB35X+hrnscdaHnvduLGT/7xYuqvDCGYMHsoc9yT97YwFDDsDyxpXV/y8f3T/LXU4n+EkxqThrQIicjVwmareHm5ZahIReQlYrqoV8fCtMSaOnS5YpsbQhc/rOd68H2f6PauHU8+Py9rEdl05vOXV/ep63u8iVszc7TxUZxUEAdq0XT+vc+clg0SIrOmx99F615Ok7TsszYbU9NilcPX+0f0/K7+ZwVA+9fpLqj5in43/nSqa2+orYlW06gu8V9dzj5s0RoFn63re6qLq97iz35vt96weSQP4W2of16PWHetCcZY3pQdKnfkSAOzd0/PM9etGrlWt+Yp3rdnX/kXuG3KvvrTYqb4aKSdcBpuwLHUGQ41Q77+o6huq+pWqpqhqhdJJNhRUdaCqjrBjbcPB/zjuG1Hv0UD+IXfWq+vVf7DMPAn1iRbRHcMSOhhPdKvGtZKat2wOHepw2orlFx5Ulcqkra0wI/ll8Bvc0nyIzp+J5VxWG/xz/+j+gVoa23AKYpS+oV4wbtIYL/DvcMtREQK+g1vdWa/loYV1biqvBhrjjO9afrPaYYS3Zx3kty1Jbm6zbosXXaGBgGNrbYwfiTf6dzw78hkeONBYD1XX96Y4e7BCaQ2GGsMofUN94lUqEecfDvzu9Us8Oe81h0CH8lvXH5IiW2wTkcblt6wdmmujbjEauTQcc7vd8W0WLrimqdcbubL81lWjDXs7vsS9g3+lLy9yqK+mwhSf2z+6f41WLDQYjCOfoV4xcez0fwK/L7dhGPDm/zzL7145DCv+t0HRJ2n4nN6Nzwxr+NI2x4Fl0yPXDCh+vbCwkK+++oqDBw8iIlx22WW0b9/+2P25c+eyerWVlC4QCJCZmcnvf/97AoEAU6ZMobCwkDFjxpCSkgLAhx9+yMUXX0xCwomBFCJ+98BBXy+LickZSi3iJrLgZR5ctIQhZ2AXgqkC+4HO+0f3r1ByIBHxY0X7RGBl3JsM/MtO+lUvEJHbsMIExf55S1WfFZEZwCN2iKChljEhe4b6xr+A3xI6EVJYUPV7PTlTFqh//4jyW9dP2sR2CbcIdA60HDBL1230SaBH8PXvvvuOrl27ct111+H3+/F6T/T5GzZsGMOGWbmONm7cyIIFC4iJiWHhwoX069ePPn368P7775OSksLGjRtp1apVCYUPoOqMWrL48tNT+/44MynpQK1FE0ThiXmIf47cQ9sdT2paxlFpUpVqlE9XVOHbFCUYQ0RaYPnIJFJOmu66QkQuxEobfp6dEyQaK09Idcd12vVFqjOGy04idEpgzPuGesW4SWP2As+HW44iNFBwxJ312hr1728wDnuhaBTZtNbz7VeE/r5OmcHv3W43O3bs4LTTrDwrTqeT6OjS13tr1qyhTx8rstPhcODz+fD7/YgIgUCAhQsXHlsghEYcq1edN3L/vq4ztZbK/xbRlj0dJ3LPoLt00kKH+itj8t9DNaKD7AQ59wK/EQuniDxjF/BaJSLHEhyIyB/sQlkrReRp+1pXEfnJvrZMRLqISLyI/CzHS+5ebrdNFpH1IvK6XZTrBxGJCSHW/8Paze+1ZSxU1deD7l8rxYqI2WPPtudcJiJn2tdHicgvIvI/YLWIOETkZXv+qSLyjRwvwTtQRGaKyFIR+V5EWtvXZ4jIkyIyE/idiFwrVtGwlSIyq6qffUPA7PQN9ZGnsJIItQ6nEAF/xnZP9vsOCJSWZzwkUxatZN2+g8RHRfL7C6wNZb7bw7sLlnMkL5/GcbHcOnQAsZEnFqLz+v28/Mt8fP4AAVX6tmvN+X2sXDpTV65n4/4M2iQ14sbT+wOwNH03+R4vw7t3KlOeKEfsIae4ym5UR/T1dxiy1LV1n4r1uz1y5AixsbF8+eWXHDhwgNatW3PBBRcQGVkyvN7r9bJlyxYuuugiAFJTU/nss89YuXIl55xzDosXL6Zv375ERJRf4G/z5qEj8wsaze3Uadng2ojlD+Zsfjz9LGblv6QPzlzG4KFYpWfL4sn9o/tXKxpAVbfZCbNaAJcDWao6WKzjhrki8gOQAlwBnK6q+SLSxO7+PvC0qn5u78gdgAe4UlWz7SycC0SkqBZAN+BGVb1HRD4CrqZk6G8frFohpeFS1SEichGWdeIcrPS956pqoVhVSj/AKl4GMAToo6rbbQWfjFVGvAWwHnhLRCKAF4HLVTVDRK7HCre+yx4jSVVHAtipes9X1T1i1R85aTE7fUO9Y9ykMbnAH8Mpg9+zcakn+90mEKh02tVBndpxz4gT87ZM37CVbi2aMuGi0XRr0ZTp60smWHM5HIwdeQbjzx/Bw+cNZ8P+DHYcOkKBx8uOQ0cYf/4IAqrsO5qN1+dncfpuzuxavnhtYrvWiud6VXDgiOjub1NU8IlAIMC+ffsYNGgQ9913HxEREcyZMydk340bN9KhQwdiYqyNZHR0NDfddBP33nsvrVu3ZtOmTfTq1YuvvvqKjz76iF27yg6h37O797D160esUa1959Eo3LHj+cfIp3loT6IeKUv5bcSqtVETFKXDPQ+4TawCXAuBpliK+hzgv6qaD2BnDE3Aqpr5uX2t0L4vwJMisgr4CSsTZ1FKw+2qusJ+XVYRsLIIVUQsAnjdVsgfc2Kxr0Wqut1+fRZWvZCAqu4HfrGv98BabPxoP/ufgOCU0MEleOcCb4vIPTRAn53KYJS+ob4ymbJ3BrWGN3/GLG/etH5QtdSxXZo3LbGLX7v3AIOSre+bQcntWLu3ZFl0ESEqwjK++QNKIBA4dt0XUFQVr9+P0+Hgl43bOKtbMk5H+X/C7eK6h69SXAhO93U7DVvRNmrUiEaNGtGunfXZ9OrVi/3794fst3bt2mOm/eLMnDmT4cOHs3r1atq0acPll1/O9OnFM2eX5FBmxwErV1ywT1UqW6e+SrRnV6eX+dXAO/S1BQ717w3R5MH9o/tXO5GRXe/Dj7VbFuC3QWVxO6nqD/b14kccpRXluhloDgy0fQcOcNzvpkTRsBD912KVty2NUEXEHrLn6Ye1ww+2kASXzy1NZgHWBj13qqqeF2oMVR2LtShoD6wQkaZlyNqgMUrfUC+xs/Q9WJdzqgZ87uwPZ/ndy0ZQw0dfOYVuGsVY35GNYqLJLQydAykQUJ7/YTZpX/1It5bN6Ni0MdERLvq2a8ULP86hSVws0REudh0+Sp+2rSo0d9OoNkk19Rw1QSSuRm0CjZcDxMfHk5iYSGamddS/fft2mjUrmS+/sLCQ9PR0evToUeLeoUOHyM3NJTk5Ga/Xi1jVX/H5KuablZPTvMeSxZd7ayuWPxTn8v0Zr3Nr4mm6ZCZWjXuAqftH9/+uumOLSHOsmhov2WWzvwd+bZu7EZHuIhIH/ADcJSKx9vUmqpoN7BaRK+xrUfb9ROCgqnpFZDRWRdLK8BTwTxFpFTTuA+X0SQT22REIt1L6DnwOcLV9tt+S43U8NgLNRWSoPWeEiIQqj46IdFHVhar6GJCJpfxPSsyZvqHeMm7SmDkTx07/GLi2tufSQGGWO/vtLWh+WD30HQ7h4fOGU+Dx8vbcJezLyqF1YgKjU7owOsXywP9o8Sou6NOdhdt2snF/Jm2SEjinV7eQ4wkOb6QjuqSmDDPDfT27TXHM8yG4LrzwQj777DP8fj+NGzfm8ssvZ8kSK3pr0CDrCHfDhg106dIl5Fn/9OnTGTPGqlydmprKhx9+yMKFCxk1alSF5SksTGi3cME1RwcN/mJVRISnb/WfsHyiccc9wlMjd9Fh+9P654NHpclD1RguxjZhF4Xsvctxh9g3sEzmy8RaEWUAV6jqdyLSH1giIh7gG6xjtVuBV0Xkr4AX6+/vfeBrEVkCrMCqaV9hVPUbWyH/ZMugWKV1y+Jl4FMRuRbLZJ9XSrtPgbOBNVhpixdi+TB47PP+/4hIIpa++xeW1aE4z9h+AwL8jFUR9aTExOkb6jUTx05PxnLMqbUQvoD/0A5P9nsB8NeYs9vhvHzenL34mCPfP76dwa9HnUGjmGiyCwp5ZcYC/u/CUWWO8cPaTUQ6nYxKOR5ut+dIFnO37ODy03rxxqzFjBszlPfmL+P8Pj1onlAyy26L6A5rR7e+MeTuJtx8Ejl/3lFH/pnhliMYcfgKBw38ekV0TO4ZdTz1384es/XPdTznSYOIxKtqrm2WXwQMs8/3DcUw5n1DvWbcpDHp1GIIn9+zZbkne3KjmlT4oejVpiVL0q2orSXpu+ndpmWJNrmFbgo81nGu1+dn84FMWjQ6sRz6d2s2cX6f7gTsM36wzvy9/tChyu3jUjJD3qgHDPf2bFJ+q7pFA67oxYuvGJKV1bwuw7a2YHmVG6rOVNvSMRt4wij80jHmfUND4G9YYUA1aqb2FsyZ7S9cNJQa/jt4b/5ytmYcIs/t4Ymvf+a83t0Yk9KFd+cvY9H2XSTFxnDbUCsxXVZBIR8vXsWvRgwhu9DNh4tWoqoEVOnXvg29ghYHa/bsp32TRBJt34COTZN49vtZtE5MoE1So5CytIpJrmpGuFqnpSalRGvE8kLxVioksvYRx6qVF4zo3n3ujBYtt40UKdVRrKa4/+wxW2urYM8pgaqOCrcMDQVj3jc0CCaOnT4ImE8NKGjVgN+T+8lc9e1usBn2Ksp1yb8/IOIoaVaoJ2xx7F8yI3JtVTLW1Qnt2q+em5y8YogI5Qf/V43/nT1m6821NLbBUAJj3jc0CMZNGrMEeKK646i6s91Zry8/FRR+vKvx7tIU/vhvnqb/i5dx9pu3H7t2pCCbmz58mOGv3chNHz7M0cKcEv0KfW4ueedeznvrTs5+4zaem33cF+vJGa9w7lt38ODU45bqT9d8z5tLPi5Vxq6BVoOc6iiZtKCesHtX6rAN64evUqXkh1F9DmKFpRkMdYZR+oaGxN+xPHOrRMB/eKf76KQMNK/e7ixrknZx3XeUdu/a1At499pnTrj28oL3GZY8gNn3fsCw5AG8vKB4UjWIckYy5YZ/8cNd/+W7O99ixvaFLNuzlmx3Lkv2rOXHu97Gr37WZ2ylwOvm4zXfcttpV5YpZz9fx3p9/pqZmTxw5crz96hysIaHvvPsMVtrekyDoUyM0jc0GMZNGuPHCicqLXSnVPyebSs92W/Hgz/8lWfqiLax3UotRHJG+/4kxZzoB/DDljlc0+cCAK7pcwHfby6ZGU9EiIuMBcAX8OEL+BARHDjw+r2oKoU+NxEOF68u+oA7B15NhLPsE5l+/uQhotRJcpyqkpPdImXJ4ss9gYBje/mtK8RLZ4/Z+k0NjWUwVBij9A0NinGTxmwGHqlMH2/BvNnevC96AfXOW7w2SYpsUamz/My8I7SMtxLjtIxvxqG8IyHb+QN+zv/vXfR/8XKGJw/itDa9iI+K5aIeI7ng7btpn9iahKg4Vu7bwPndyq9T5MQR2TXQqlJx3+GgsLBRu4ULrk70+SJWV3OotdTT8tGGkx+j9A0NjnGTxkzCSiRSJqoa8OR8MtNfuGA41JojVr3EJZE5TnGFzthTTZwOJ9/f+RaL7v+EFfs2sCFjGwC/Pv0mvr/zLR4b8xuenf0m44ffxQcrp/LrL/7Cv+dNLnPM073d+6Hk1oa8NYnPF91k4YJruhYWxlX1mKkAuNF46xvChVH6hobK3VjpMkOi6s5xZ72+NODbWWt10+szrWM7b7KrrFWYZnGNOZBrfaQHcjNpGte4zPaJ0QkMbd+fGdtO1H9rDlj1dDo3bs8na77jlSseZ2PGdrYfLr0ATjQRSa00aVll5A0XgYArZvGiKwZlZzerSiz/b84es7W6lgKDocoYpW9okIybNGY/cANWgY4TCPiP7HYffXU/mju47iWrH7SP61HpXfO5XYfxyRor9fsna77jvK5nlWhzKP8oWbZXf4HXzewdS+na9MQ07M/OfpPxZ92NN+AjoFbRIIc4KPCFrjdQxHBvz85oyd9n/cThXLniwhEHD3SaWYlOb589Zmt5qWePISItReR/IrLNrgc/X0TK9oq0+n1TU+VhReQOEWlTyr23i+rWB11rIyKf1MTchtrBKH1Dg2XcpDE/U+x83+/dvsqT/d9o8NWKabuh0CyqXUJZ98d99ThXvPtrth3eyeCJV/PhyqmMO+NmZqcvYfhrNzI7fQn3n2GFj+/PyeS2j60j6IO5h7j+gwc59607uOSdexmRPIhzuh7PpPvdptn0a5VCq4RmJEYnMKBNb85583ZEoFeLrmXKnKix7RI1dlF1n70u2bjxrJHp6f3mqFJedZ/VwP0VHdfOT/8FMEtVO6vqQKxFbrsyOwKqepGqHq3EXGWVkr0DCKn0S5l7r6peU35LQ7gwyXkMDZ6JY6e/DdzuK1g4x1c4dzBQb7PQ1RGB65L/kCsiodP01WP2y9H1U6OW9gy3HJWlefPtS3qkzEkRIT7E7SPAGWeP2bqpouOJyNnAY6oa8nhKRO4ABqnqb+z3U4FnVXWGiKTb9zJF5AusinHRwL9V9TW7fS5WeuvzgfHAGOBSIAaYB9yHlQXzbWAPli/CUFU9VqZZRN4GpqrqJ0HXku1rfUQkGngFqyyuD3hYVX+xZb8MiAW6AJ+r6h/sxcebdnsF3lLVFyr6mRkqhknDazgZuM+T9w0Bz4bby2968tMkqvUWEekebjmqQitN6hmlESvd4u0XblkqQ0ZGp0Fud+z6vv1+aCZC86BbHuCqyih8m95ATfg43KWqh0UkBlgsIp+q6iEgDlhjl5JFRNap6l/t1+8Cl6jqJyLyG+ARVV1ShbnHAahqqoikAD8E/b/sD5wGuIGNIvIi0AJoq6p9bDmSqvjMhjIw5n1Dg2fcpDHugGfD/wHp4ZalPtA+tke9TnZTHqf7unrKb1X/yM5u2XPpkssKAgFHetDle84es3VGdccWkYkislJEFley6wMishJYgLXjLzr28mOVpC1itIgsFJHVWLv+mqjMeBZWiV9UdQOwAyhS+j+rapaqFgLrgI7ANqCziLwoIhcA2TUgg6EYRukbTgrGT5l6ALgYyAq3LOGmdWyXBm3B6+ZvPcipjq3hlqMqFBQkdli08OoEny9iLfD42WO2vlPFodYCA4reqOo4rJrxRVYEHyd+f5coPS0io4BzsMzy/YDlQe0KVdVvt4vGql1/jaqmAq+HGq8KlFWoKNir0w+4VPUI0A+YgWUleKMGZDAUwyh9w0nD+ClT12GdQ3rDLUs4SYho3D7cMlQHQSTV32FfuOWoKl5vdNNFC6+ec/aYrWnVGGY6EC0ivw66Fhv0Oh3oLyIOEWkPDAkxRiJwRFXzbfP6GaXMVaTgM0UkHgh2xMsBynQKLYNZwM0Atlm/A7CxtMYi0gxwqOqnwJ8JWvQYag6j9A0nFeOnTP0ZuIUQoXynAjHO+AMOcTZopQ9wmq/TYJSMcMtRRb7w+yPGVWcAtTysrwBGish2EVkETAb+z24yF9iOFRXwLCXP/xX4DnCJyCqsYlULSpnrKNbufjVWxEDwEcLbwCQRWWH7BRTnVRHZbf/ML3bvZcBpHxlMAe5Q1bLiNtsCM0RkhT3v/yujraGKGO99w0nJc9dfciPWeWJZ4UgnHV0TTlswsNl5pe3oGhS/RKyZudV5oKElV5oBXJCWllZ2UoJawvaAPwi0UtVT2uJlCI3Z6RtOSsZPmfoBVoxxIMyi1Clt47qHRdnUBkO93fui5IdbjkqwFLgsXArfZi3whlH4htIwSt9w0jJ+ytT3gLs4hRR/k6jWzcItQ00RTWTjlppYlVCxcLASuDAtLS0nnEKoaoqq/l/5LQ2nKkbpG05qxk+ZOhm4F+uM86TGIc7CCIk8qTIRDvf2TEbr/aJtJjAyLS2tofogGE4hjNI3nPSMnzL1TWAsJ7nibxndcZOIRIZbjpokSeM6JGhMfU7N+znWGf4pHypqaBgYpW84JRg/ZeprwD1Qbo70Bku7uB6Hwy1DbTDcl1LVkLHa5g3g2rS0NFMm19BgMErfcMpg7/gv5iTN9NUypmNs+a0aHm0CTXpHqqu+laP9e1pa2j1paWmnZGiooeFilL7hlGL8lKk/YKUHLb24ewMl1tmoS7hlqC2G+LoWlN+qTlDggbS0tD+FWxCDoSoYpW845Rg/Zepq4HRqpqBJvaBRRLPtItI03HLUFj38bQY5VLaHWQwvcHNaWtqLYZbDYKgyRukbTknGT5m6DxgBfBVuWWqC9nHd94RbhtpEEEcff4fdYRQhF7gkLS3tgzDKYDBUG6P0Dacs46dMzQOuBP4TblmqS5vYrid1ZALAAF+nQSiZYZh6E3BmWlraD2GY22CoUYzSN5zSjJ8yNTB+ytTfYWXvywuzOFUmMaJ5m3DLUNu4cMZ0CrRYW8fTfgQMSktLq2+OhAZDlTC59w0Gm+euv6Q78CFwWrhlqQyRjuijV3R4IFFEyiplelJQgCfz/ajZcQihir/UJB7gEXN+bzjZMDt9g8Fm/JSpm7DKj/473LJUhjaxXTafCgofIIbIZs21UW2n5t0GDDcK33AyYpS+wRDE+ClTPeOnTH0QuATCcn5cadrF9mhIRWmqzXBvz3a1mJp3MtA/LS2tPmcBNBiqjFH6BkMIxk+ZOg3oB/wSblnKo1l028Rwy1CXNNH4TvFE1/Ru/whwfVpa2h3hLppjMNQmRukbDKUwfsrUvcA5wCNQP0u8CuKLdMR0D7ccdc0wb4+aPNP/Geiblpb2UQ2OaTDUS4zSNxjKwPbufw7oDXwbbnmK0yy67SYROSnT75ZF+0Cz1Ah1rqnmMLuAG9LS0s5JS0urVA4AEXlURNaKyCoRWSEip1dTluCxvxGRpJoar4x5kkVkTbFraSLySCXGGCUiU2tLnrrsf6pglL7BUAHGT5maPn7K1IuAG4H94ZaniPaxKQ3C76A2GOTrklvFroXA34CUtLS0KZXtLCJDsXw+BqhqXyxrULXTOouFQ1UvUtWj1RzLVV15aoP6KtephFH6BkMlGD9l6odAd+B56kHFvlaxnSLCLUO46OVvN8ShsrOS3b4AeqWlpf05LS2tqkc2rYFMVXUDqGqmqu4FEJF0EWlmvx4kIjPs12ki8paIzBCRbSLygH09WUTWi8jLWGmh2xeNISJxIjJNRFaKyBoRud7uM1BEZorIUhH5XkRa29dniMiTIjIT+J2IXGv3WykisyrzgCLSRUSWBb3vJiJL7dcXiMgGEZkDXBXUJs5+xsUislxELrev3yEiH4vI18APIhIvIj+LyDIRWV3UzsYlIpNtC8onRVYsEXnMHneNiLxWFK1ifxYrRWQ+MK4yz3iqYpS+wVBJxk+ZmjN+ytTxWI5+P4dTljhXUnI45w8ngjh6+dulV7D5euC8tLS0K9PS0qqbw/8HLOW8SUReFpGRFeyXApwPDAH+IiJFC7YewDuqepqq7ghqfwGwV1X7qWof4Du7z4vANao6EHgL+HtQnyRVHamqzwGPAeeraj/gslJk6mIfT6wQkRXAWABV3QpkiUh/u92dwNsiEg28DlwKDAdaBY31KDBdVQcDo4FnRCTOvjcUuF1Vx2BZWq5U1QF2u+eCQk57AK/ZFpRs4H77+kuqOtj+HGKwLC0A/wUeUNWhpTyfoRhG6RsMVWT8lKnrxk+Zeg6WeXduXc8f50rc6xBH67qetz4x0NdlEMqRMppkAQ9jOer9WBNzqmouMBC4F8gApojIHRXoOk1V3aqaCRwEWtrXd6jqghDtVwPniMg/RGS4qmZhKcU+wI+2kv4T0C6oT/BxxVwsRX0P4CxFpq2q2r/oB5gUdO8N4E4RcQLXA//DWrhsV9XNamV2ey+o/XnABFuuGUA00MG+96OqHrZfC/CkiKwCfgLaBn0Wu1S16G/pPayKmACjRWShiKwGxgC9RSQRa5Ez027zbinPaAjCnK8YDNVk/JSpPwM/P3f9JecBj2Ml+Kl12sZ2SwdO+vS7ZRGBM7ZjoNniHc7M4rvtQqxd8ONpaWkHa3peVfVjKbYZtiK6HXgb68inaDMVXaybO+i1n+PfvyHTP6vqJhEZCFwEPCUiPwCfA2vL2NnmBfUfazsYXgysEJH+qnqoYk8IwKfAX4DpwFJVPSQi7bHKC4dCgKtVdeMJFy0Zgp/xZqA5MFBVvSKSzvHPqvjYalsXXgYGqeouEUmz20sZshhKwez0T1JExG+b7NbaZ14Pi0iZv+9g71f7HO6lUtqF9C62zyJX2z/rRORvIhJVIw9Ucq5KeRkX6/tXETnHfj1DRAbVhEzjp0z9YfyUqUOxvqQX18SYZdEurnvYfQrqA8O8Kb3QYwo1B/gn0CktLW1cbSh8EekhIt2CLvUHiszy6VhWAICrqzlPGyBfVd8DngUGABuB5mI5EyIiESLSu5T+XVR1oao+hpVoqn1l5lfVQuB74BUsMzrABqCTiHSx398Y1OV74LdB5+2lpbNOBA7aCn800DHoXoeiZ7PHnsPxBUGmiMQD19jyHcU6giiyBtxcmec7VTE7/ZOXAttch4i0wDLNJWKt3KuFql5Uxu3Rqlr0x/ma/XN7Rca1vyxEVWsr2xoA9pdgrTF+ytRvgW+fu/6SS7A+7xpZVBQnKbJl89oYt6ERS1Tz1oGkb/Y5j84HXkpLSztay1PGAy/aC18fsAXL1A+WpedNEfkjsLCa86RinYsHAC/wa1X1iMg1wH9s87YL+BcQqhDRM/biRLB8T1ZWQYb3sZz1fgBrISAi9wLTRCQTSyn3sds+Ycuyyv5bTuf42XvxMb8WkSXACqyFRBHrgdtF5FVgM/CKquaLyOtYxx3pnLigvhN4S0TysRYdhnIwBXdOUkQkV1Xjg953xvpjaYZl4XkaGAVEARNV9VURSQamqmof+4zyMiAW6AJ8rqp/sMdKxzK1nRAuVvy6iDTCCmXqhFXA5EugMRAB/ElVv7Tn/BYr891Q4ArgOvsnyp73L/Z4jwK32WNmYJkcn7V3HROxTIb5wD3APqwvuc6qGrC9gDcCnbEckaaq6idieVc/AiwH3sRS0Aq8paovVP6TL8lz118yFMtB6jpKmnyrhFMi8q7u+FC0fd56KrMWq1bCe+2eHl4QbmFONmxrWqKq/jncshhqBrPTP0VQ1W22eb8FcDmQpaqDbfP7XPu8sPgKsD9WxTk3sFFEXlTVCscjq2q2iGwHugFLsTx2s8UKaVogIl/ZTXsAd6rq/SJynt1+CNYO5SsRGYF1JniDLY8LK7xpqd3/NWCsqm62zw9fVtUxIrISGIm1oLgU+N42KYYStz/Q1vYOJtTxRVUZP2XqfGD+c9df8hCW1WMsVthflWkV02lTGebTkx0f1kLxxXZPD68R5zxDSUTkc6wF/5hwy2KoOYzSP7Uo0nbnAX1tMyFYZv9uwKZi7X+2PYYRkXVYZ2+VTUIiQf8+aSvwACd67AZ7L59n/yy338fbsiVg7frzbXm+sv+NB84EPg5S5kV+BFOwvI5/wVowvFyGnNuAziLyIjAN25xZk4yfMvUw8ALwwnPXXzIGS/lfgWX5qBTt43pk16x0DYKFWB7dU9o9PTwj3MKc7KjqleGWwVDzGKV/imCb9/1YoUIC/FZVvy/WJrlYt9K8jSs6ZwKQjLWYKMtjN9izV4CnVPXVYmM9SGhPXQdwtMh/oRhfYXk9N8FyrppemqyqekRE+mHFUY/DMsXfVfYTVp3xU6ZOB6Y/d/0lLbEcvq7AOm6p0AKgRXT7/9/enYZoVcVxHP/+MsuNVKwMHTTK9jLRsoXGqChajJIWCaNeFNECUViRlWUIMVFCm4ZF2aLUaEWRvWgXbaEoc4Mg0zZ7YVmaWKgt/16c8+RlchbHZ3ycub8PXJ47z3PPvecOw/yfc+4559+79aO6hJWkZ8Bz6hrqv651Zcw6Owf9EpC0H2n+7WMREZLeBK6T9F4OwIcCP1b5mn1ILetXc0BtacRu0ZvAVElzImKTpMGkQUwLSXOOG0h/t+cDMyuPECRdEhHz8gCi4RGxNJf/lPTMd36eZtVcffcFtkbEy5JWkaZfdbiJjfPXkn5PM6aNH9uPNPBpHGlhlubW1I8e3foc0sxnXcE3wHxSoN/ZwXBmVuCg33X1VFokozvpGejzpKVjIS26cSCwOAfJn0ktzWp4P59zD9Kc4qn5/ZZG7P4nIt6SdATwce6u3wRcHhGLJTXmst8BiwrFJgCPS7qLdL8vsm2kciMwj9SKbslgYFZhWuOkttxsNU1snL+B1H09e9r4sT1JjznGkaYA/jdSv/9eA1dJGrar69eB1pN6Yd4G3qlrqF9V4/qYdVkevW/WCUwbP/ZIYAwwZnj/U3sf0e/E5pZV7Qy2Ah+TgvzbwGd1DfUdOk3TzBIHfbNOaM3tiwYBJxS2oyj0BuxGfiH1ulS2JcCXdQ31W2tZKbOyctA36yLW3L6oLzCMNNuh6TagAy+9mTSr4wfge9LAzaXA0rqG+qqOFTGzneOgb1YC+QvBAKBfM1tf0vTIv0gDJytb05//IM0A+QlYC6yta6jfkfXczayGHPTNzMxKwgl3zMzMSsJB38zMrCQc9M3MzErCQd/MzKwkHPTNrCokbSrsnytppaQhkq6VdEUHXvcRSZMLP98paXref6aQWKpY5pm8fPMSSYslnbQT1/+olc8PlLSivec3qyYvw2tmVSXpDOBR4KyI+J6U96Ej3QUskTSHlJTpalIK5tbcGhEv5XTOM4Hh7bl4RJzcnnJmteCWvplVjaR64EngvIhYld+bIumWvL9A0v2SPpX0VT4eSb0kzZW0TFKjpE8kHSepW26Vr5C0XNLNTa8ZERuBO4HHgOnA3RGxYQeqvZC0qBGSvs3Jl8jXX1C4h6dz/VdLurFwz5vyax9J7+aeg+WSLihcY09Jz+b7e0lSc8mUzDqUg76ZVcvewGvAhRGx3YRK2Z4RMRq4Cbgnv3c9sD4ihpOSNI3K748ABkfE0RFxDDBreyeMiBeA/sA+EfH8Dtb7fGB5G447nJR6eTRwj6SmaZA3A+MiYiRwGjAtJ58COAx4It/fRtL9mu1yDvpmVi1/Ah8BV7Vy3Cv59XNStkeAU0jZEYmIFcCy/P5q4CBJj0o6mxQw/0dSHXAAMCindW6LB3ImymvaUGeANyJiS0SsI61IOLBpNYD7JC0D3iFlbqwc80NEfJj3Z5Pu12yXc9A3s2r5B7gUOF7SHS0ctyW//s22cUXa3oERsR44FlgA3EBKC709DwNTgLls6z1oza0RMSIizsxfNCAtO1z5v9ijmXo3rXvFBFLSo1ERMYK0THHlHE2XPvVSqFYTDvpmVjUR8QcwFpggqS2t54oPSF8YkHQkcEze3xfYIyJeBiYDI5sWlHQOsD/wHOnRwLh8jvb4lm2PFi7awbJ9gZ8i4k9JpwFDC58NKcwQuIx0v2a7nEfvm1lVRcSvuSt+oaR1bSw2A3g2d41/Qere/43URT5LUqWBMqlYSFIP4CHg4kiJRH6XdBtpUN/p7aj+vcBTuafikzaWqbTa5wCvS/qMlEK4OK7hS+BKSTOBlcDj7aib2U5zwh0zqzlJ3YDuEbFZ0sHAu8ChEbG1xlVrkaQBwOKIGNrqwWa7Abf0zWx30At4P4+IF3BdJwj4g0hjDR6scVXM2swtfTMzs5LwQD4zM7OScNA3MzMrCQd9MzOzknDQNzMzKwkHfTMzs5Jw0DczMysJB30zM7OScNA3MzMrCQd9MzOzknDQNzMzKwkHfTMzs5Jw0DczMysJB30zM7OScNA3MzMrCQd9MzOzknDQNzMzKwkHfTMzs5Jw0DczMyuJfwFKGaldyL0RKAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.pie((win_batsecond['winner'].value_counts()),labels=win_batsecond['winner'].value_counts().keys(),autopct='%0.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-68-e25bd2303085>:2: MatplotlibDeprecationWarning: Using a string of single character colors as a color sequence is deprecated since 3.2 and will be removed two minor releases later. Use an explicit list instead.\n",
      "  plt.bar((win_batsecond['winner'].value_counts()[0:3].keys()),win_batsecond['winner'].value_counts()[0:3],color=\"rgby\")\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.bar((win_batsecond['winner'].value_counts()[0:3].keys()),win_batsecond['winner'].value_counts()[0:3],color=\"rgby\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013    76\n",
       "2012    74\n",
       "2011    73\n",
       "2019    60\n",
       "2018    60\n",
       "2016    60\n",
       "2014    60\n",
       "2010    60\n",
       "2017    59\n",
       "2015    59\n",
       "2008    58\n",
       "2009    57\n",
       "Name: season, dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['season'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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",
       "Mohali             10\n",
       "Rajkot             10\n",
       "Dharamsala          9\n",
       "Indore              9\n",
       "Johannesburg        8\n",
       "Port Elizabeth      7\n",
       "Abu Dhabi           7\n",
       "Cape Town           7\n",
       "Cuttack             7\n",
       "Ranchi              7\n",
       "Raipur              6\n",
       "Sharjah             6\n",
       "Kochi               5\n",
       "Kanpur              4\n",
       "Kimberley           3\n",
       "Nagpur              3\n",
       "East London         3\n",
       "Bloemfontein        2\n",
       "Name: city, dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['city'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "393"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.sum(ipl['toss_winner']==ipl['winner'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(756, 18)"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5198412698412699"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "393/756"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}