{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analiza zależności ilości kibiców w baseball mlb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Unnamed: 0</th>\n",
       "      <th>attendance</th>\n",
       "      <th>away_team</th>\n",
       "      <th>away_team_errors</th>\n",
       "      <th>away_team_hits</th>\n",
       "      <th>away_team_runs</th>\n",
       "      <th>date</th>\n",
       "      <th>field_type</th>\n",
       "      <th>game_type</th>\n",
       "      <th>home_team</th>\n",
       "      <th>...</th>\n",
       "      <th>temperature</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>sky</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>game_hours_dec</th>\n",
       "      <th>season</th>\n",
       "      <th>home_team_win</th>\n",
       "      <th>home_team_loss</th>\n",
       "      <th>home_team_outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>40030.0</td>\n",
       "      <td>New York Mets</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-04-03</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Night Game</td>\n",
       "      <td>Kansas City Royals</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>from Right to Left</td>\n",
       "      <td>Sunny</td>\n",
       "      <td>7</td>\n",
       "      <td>3.216667</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>21621.0</td>\n",
       "      <td>Philadelphia Phillies</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Night Game</td>\n",
       "      <td>Cincinnati Reds</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>from Right to Left</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>5</td>\n",
       "      <td>2.383333</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>12622.0</td>\n",
       "      <td>Minnesota Twins</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Night Game</td>\n",
       "      <td>Baltimore Orioles</td>\n",
       "      <td>...</td>\n",
       "      <td>48.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>out to Leftfield</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>6</td>\n",
       "      <td>3.183333</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>18531.0</td>\n",
       "      <td>Washington Nationals</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Night Game</td>\n",
       "      <td>Atlanta Braves</td>\n",
       "      <td>...</td>\n",
       "      <td>65.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>from Right to Left</td>\n",
       "      <td>Cloudy</td>\n",
       "      <td>4</td>\n",
       "      <td>2.883333</td>\n",
       "      <td>regular season</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Loss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>18572.0</td>\n",
       "      <td>Colorado Rockies</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Day Game</td>\n",
       "      <td>Arizona Diamondbacks</td>\n",
       "      <td>...</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>in unknown direction</td>\n",
       "      <td>In Dome</td>\n",
       "      <td>7</td>\n",
       "      <td>2.650000</td>\n",
       "      <td>regular season</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Loss</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2458</th>\n",
       "      <td>2458</td>\n",
       "      <td>31042.0</td>\n",
       "      <td>Toronto Blue Jays</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2016-04-03</td>\n",
       "      <td>on turf</td>\n",
       "      <td>Day Game</td>\n",
       "      <td>Tampa Bay Rays</td>\n",
       "      <td>...</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>in unknown direction</td>\n",
       "      <td>In Dome</td>\n",
       "      <td>8</td>\n",
       "      <td>2.850000</td>\n",
       "      <td>regular season</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Loss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2459</th>\n",
       "      <td>2459</td>\n",
       "      <td>39500.0</td>\n",
       "      <td>St. Louis Cardinals</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-04-03</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Day Game</td>\n",
       "      <td>Pittsburgh Pirates</td>\n",
       "      <td>...</td>\n",
       "      <td>39.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>out to Leftfield</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>5</td>\n",
       "      <td>3.033333</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2460</th>\n",
       "      <td>2460</td>\n",
       "      <td>20098.0</td>\n",
       "      <td>San Francisco Giants</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Day Game</td>\n",
       "      <td>Milwaukee Brewers</td>\n",
       "      <td>...</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>in unknown direction</td>\n",
       "      <td>In Dome</td>\n",
       "      <td>7</td>\n",
       "      <td>3.316667</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2461</th>\n",
       "      <td>2461</td>\n",
       "      <td>17883.0</td>\n",
       "      <td>Detroit Tigers</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Day Game</td>\n",
       "      <td>Miami Marlins</td>\n",
       "      <td>...</td>\n",
       "      <td>71.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>in unknown direction</td>\n",
       "      <td>In Dome</td>\n",
       "      <td>10</td>\n",
       "      <td>3.366667</td>\n",
       "      <td>regular season</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Loss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2462</th>\n",
       "      <td>2462</td>\n",
       "      <td>10298.0</td>\n",
       "      <td>Boston Red Sox</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-04-06</td>\n",
       "      <td>on grass</td>\n",
       "      <td>Night Game</td>\n",
       "      <td>Cleveland Indians</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>out to Leftfield</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>13</td>\n",
       "      <td>3.483333</td>\n",
       "      <td>regular season</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2463 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  attendance              away_team  away_team_errors  \\\n",
       "0              0     40030.0          New York Mets                 1   \n",
       "1              1     21621.0  Philadelphia Phillies                 0   \n",
       "2              2     12622.0        Minnesota Twins                 0   \n",
       "3              3     18531.0   Washington Nationals                 0   \n",
       "4              4     18572.0       Colorado Rockies                 1   \n",
       "...          ...         ...                    ...               ...   \n",
       "2458        2458     31042.0      Toronto Blue Jays                 2   \n",
       "2459        2459     39500.0    St. Louis Cardinals                 0   \n",
       "2460        2460     20098.0   San Francisco Giants                 0   \n",
       "2461        2461     17883.0         Detroit Tigers                 0   \n",
       "2462        2462     10298.0         Boston Red Sox                 1   \n",
       "\n",
       "      away_team_hits  away_team_runs        date field_type   game_type  \\\n",
       "0                  7               3  2016-04-03   on grass  Night Game   \n",
       "1                  5               2  2016-04-06   on grass  Night Game   \n",
       "2                  5               2  2016-04-06   on grass  Night Game   \n",
       "3                  8               3  2016-04-06   on grass  Night Game   \n",
       "4                  8               4  2016-04-06   on grass    Day Game   \n",
       "...              ...             ...         ...        ...         ...   \n",
       "2458               7               5  2016-04-03    on turf    Day Game   \n",
       "2459               5               1  2016-04-03   on grass    Day Game   \n",
       "2460               6               3  2016-04-06   on grass    Day Game   \n",
       "2461              13               7  2016-04-06   on grass    Day Game   \n",
       "2462              10               6  2016-04-06   on grass  Night Game   \n",
       "\n",
       "                 home_team  ...  temperature  wind_speed  \\\n",
       "0       Kansas City Royals  ...         74.0        14.0   \n",
       "1          Cincinnati Reds  ...         55.0        24.0   \n",
       "2        Baltimore Orioles  ...         48.0         7.0   \n",
       "3           Atlanta Braves  ...         65.0        10.0   \n",
       "4     Arizona Diamondbacks  ...         77.0         0.0   \n",
       "...                    ...  ...          ...         ...   \n",
       "2458        Tampa Bay Rays  ...         72.0         0.0   \n",
       "2459    Pittsburgh Pirates  ...         39.0        14.0   \n",
       "2460     Milwaukee Brewers  ...         66.0         0.0   \n",
       "2461         Miami Marlins  ...         71.0         0.0   \n",
       "2462     Cleveland Indians  ...         60.0         7.0   \n",
       "\n",
       "             wind_direction       sky total_runs game_hours_dec  \\\n",
       "0        from Right to Left     Sunny          7       3.216667   \n",
       "1        from Right to Left  Overcast          5       2.383333   \n",
       "2          out to Leftfield   Unknown          6       3.183333   \n",
       "3        from Right to Left    Cloudy          4       2.883333   \n",
       "4      in unknown direction   In Dome          7       2.650000   \n",
       "...                     ...       ...        ...            ...   \n",
       "2458   in unknown direction   In Dome          8       2.850000   \n",
       "2459       out to Leftfield   Unknown          5       3.033333   \n",
       "2460   in unknown direction   In Dome          7       3.316667   \n",
       "2461   in unknown direction   In Dome         10       3.366667   \n",
       "2462       out to Leftfield   Unknown         13       3.483333   \n",
       "\n",
       "              season  home_team_win home_team_loss home_team_outcome  \n",
       "0     regular season              1              0               Win  \n",
       "1     regular season              1              0               Win  \n",
       "2     regular season              1              0               Win  \n",
       "3     regular season              0              1              Loss  \n",
       "4     regular season              0              1              Loss  \n",
       "...              ...            ...            ...               ...  \n",
       "2458  regular season              0              1              Loss  \n",
       "2459  regular season              1              0               Win  \n",
       "2460  regular season              1              0               Win  \n",
       "2461  regular season              0              1              Loss  \n",
       "2462  regular season              1              0               Win  \n",
       "\n",
       "[2463 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv(\"baseball_reference_2016_clean.csv\")\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pogoda\n",
    "\n",
    "![image](sky.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Sunny', 'Overcast', 'Unknown', 'Cloudy', 'In Dome', 'Drizzle',\n",
       "       'Rain', 'Night'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['sky'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sunny = data[data['sky'] == 'Sunny']\n",
    "overcast = data[data['sky'] == 'Overcast']\n",
    "cloudy = data[data['sky'] == 'Cloudy']\n",
    "in_dome = data[data['sky'] == 'In Dome']\n",
    "drizzle = data[data['sky'] == 'Drizzle']\n",
    "rain = data[data['sky'] == 'Rain']\n",
    "night = data[data['sky'] == 'Night']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Średnia ilość kibiców w zależności od pogody"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "  \n",
    "left = [1, 2, 3, 4, 5, 6, 7]\n",
    "\n",
    "height = [sunny['attendance'].mean(), overcast['attendance'].mean(), cloudy['attendance'].mean(), \n",
    "in_dome['attendance'].mean(), drizzle['attendance'].mean(), rain['attendance'].mean(), night['attendance'].mean()]\n",
    "\n",
    "tick_label = ['sunny', 'overcast', 'cloudy', 'in dome', 'drizzle', 'rain', 'night']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'green', 'red'])\n",
    "  \n",
    "plt.xlabel('Weather')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Weather')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mediana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "  \n",
    "left = [1, 2, 3, 4, 5, 6, 7]\n",
    "\n",
    "height = [sunny['attendance'].median(), overcast['attendance'].median(), cloudy['attendance'].median(), \n",
    "in_dome['attendance'].median(), drizzle['attendance'].median(), rain['attendance'].median(), night['attendance'].median()]\n",
    "\n",
    "tick_label = ['sunny', 'overcast', 'cloudy', 'in dome', 'drizzle', 'rain', 'night']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'green', 'red'])\n",
    "  \n",
    "plt.xlabel('Weather')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Weather')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "W nocy prawdopodobnie najwięcej, gdyż większa grupa odbiorców ma dostęp do meczy online z całego świata.  \n",
    "Pod kopułą może być najmniej widzów, gdyż takie stadiony mają mniejsze trybuny."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dzień tygodnia\n",
    "\n",
    "![image2](week.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Sunday', 'Wednesday', 'Tuesday', 'Monday', 'Thursday', 'Saturday',\n",
       "       'Friday'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['day_of_week'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "monday = data[data['day_of_week'] == 'Monday']\n",
    "tuesday = data[data['day_of_week'] == 'Tuesday']\n",
    "wednesday = data[data['day_of_week'] == 'Wednesday']\n",
    "thursday = data[data['day_of_week'] == 'Thursday']\n",
    "friday = data[data['day_of_week'] == 'Friday']\n",
    "saturday = data[data['day_of_week'] == 'Saturday']\n",
    "sunday = data[data['day_of_week'] == 'Sunday']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Średnia ilość kibiców w danym dniu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "  \n",
    "left = [1, 2, 3, 4, 5, 6, 7]\n",
    "\n",
    "height = [monday['attendance'].mean(), tuesday['attendance'].mean(), wednesday['attendance'].mean(), \n",
    "thursday['attendance'].mean(), friday['attendance'].mean(), saturday['attendance'].mean(), sunday['attendance'].mean()]\n",
    "\n",
    "tick_label = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'green', 'red'])\n",
    "  \n",
    "plt.xlabel('Day')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Day')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mediana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IiJAUG5v0xoqI0aQnEVNfX1/17ZmZdRWVXBO5FvgfwHHAvUBvoKIn+UrqTiog10dEY/fX87mbivx3aY4vBvoUFu+dY63FezcTNzOzGqmkiOwTET8EXomIscCnSRe5W5XvlLoaeCwiflWYNBFovMNqGHBrIT4036V1BLAqd3tNBgbkpwfvTLo2MzlPWy3piLytoYV1mZlZDVRyYf2N/HelpINI1zHeXcFyHwFOA+ZKmpVj3wN+CkyQdDrwT+ALedok0tOBG0gX8ocDRMRySRcBM/J8P268yA6cBVwDbEu6oO6L6mZmNVRJERmdWwA/JLUWtgd+tKGFIuIBoKXvbRzbNJDvyjq7hXWNAcY0E58JHLShXMzMrDoquTvrd3nwXuC91U3HzMw6kxaLiKRvtbZgk+scZmbWBbXWEtkh/90P+BCpKwvgRGB6NZMyM7POocUiEhEXAki6Dzg0Il7K4xcAt9ckOzMz69AqucW3J/B6Yfx13v6WuZmZdWGV3J01Dpgu6Y95fDD+eVwzM6Oyu7MukfQX4KgcGh4Rj1Y3LTMz6wwq+nlcYBbpibxbAkjaIyKerVZSZmbWOVTyAMavkn7P43ngTdIXCAN4f3VTMzOzjq6SlsjXgf0i4sVqJ2NmZp1LJXdnLQRWVTsRMzPrfCppiTwF3CPpdmBtY9DfWDczs0qKyLP5tVV+mZmZAZXd4tv4zfXtImJN9VMyM7POYoPXRCQdKWkB8HgeP0TS5VXPzMzMOrxKLqz/mvTTuC8CRMRs4GNVzMnMzDqJSooIEbGwSejNKuRiZmadTCUX1hdK+jAQkrqTvjfyWHXTMjOzzqCSlsiZpJ+t7QUsBvqTftvczMy6uEpaIvtFxCnFgKSPAA9WJyUzM+ssKmmJXFZh7B0kjZG0VNK8QuwCSYslzcqvEwrTzpfUIOkJSccV4gNzrEHSeYX4XpKm5fhNkvwdFjOzGmvtN9aPBD4M1DX5vfUdgW4VrPsa4Dek3yMpujQi/k+TbR0ADAEOBN4D/D9J++bJvwU+BSwCZkiaGBELgJ/ldY2XdCVwOnBFBXmZmdkm0lpLZCtge1Kh2aHwWg2ctKEVR8R9wPIK8xgEjI+ItRHxNNAAHJZfDRHxVES8DowHBkkScAxwc15+LOnHsszMrIZa+431e4F7Jb0aET8vTpP0eeDJkts8R9JQYCbw7YhYQbpo/3BhnkU5BukBkMX44cCuwMqIWNfM/OuRNAIYAbDHHnuUTNvMzJqq5JrIkGZi55fc3hXA3qQ7vJYAvyy5no0SEaMjoj4i6uvq6mqxSTOzLqG1ayLHAycAvSSNKkzaAXijzMYi4vnC+q8Cbsuji4E+hVl75xgtxF8EekjaMrdGivObmVmNtNYS+RfwCPBa/tv4eprUFbXRJO1eGP0s0Hjn1kRgiKStJe0F9AOmAzOAfvlOrK1IraKJERHA3bx9bWYYcGuZnMzMrLzWronMBmZLuh44CPgS8HlSEbllQyuWdCNwNLCbpEWkn9g9WlJ/0s/rPgN8JW9rvqQJwAJgHXB2RLyZ13MOMJl0R9iYiJifN3EuMF7SxcCjwNUbs+NmZtZ2rXVn7QucnF8vADcBiohPVLLiiDi5mXCLb/QRcQlwSTPxScCkZuJPke7eMjOzdtLaN9YfB+4HPhMRDQCSvlmTrMzMrFNo7ZrI50h3UN0t6SpJxwKqTVpmZtYZtFhEIuJPETEE2J90EfsbwLslXSFpQI3yMzOzDmyD3xOJiFci4oaIOJF0K+2jpIvaZmbWxVX0o1SNImJF/uLesdVKyMzMOo+NKiJmZmZFLiJmZlaai4iZmZXmImJmZqW5iJiZWWkuImZmVpqLiJmZleYiYmZmpbmImJlZaS4iZmZWmouImZmV5iJiZmaluYiYmVlpLiJmZlaai4iZmZVWtSIiaYykpZLmFWK7SJoi6cn8d+ccl6RRkhokzZF0aGGZYXn+JyUNK8Q/KGluXmaUJP90r5lZjVWzJXINMLBJ7DxgakT0A6bmcYDjgX75NQK4AlLRAUYChwOHASMbC0+e54zCck23ZWZmVVa1IhIR9wHLm4QHAWPz8FhgcCE+LpKHgR6SdgeOA6ZExPKIWAFMAQbmaTtGxMMREcC4wrrMzKxGan1NpGdELMnDzwE983AvYGFhvkU51lp8UTNxMzOroXa7sJ5bEFGLbUkaIWmmpJnLli2rxSbNzLqEWheR53NXFPnv0hxfDPQpzNc7x1qL924m3qyIGB0R9RFRX1dX1+adMDOzpNZFZCLQeIfVMODWQnxovkvrCGBV7vaaDAyQtHO+oD4AmJynrZZ0RL4ra2hhXWZmViNbVmvFkm4EjgZ2k7SIdJfVT4EJkk4H/gl8Ic8+CTgBaADWAMMBImK5pIuAGXm+H0dE48X6s0h3gG0L3JFfZmZWQ1UrIhFxcguTjm1m3gDObmE9Y4AxzcRnAge1JUczM2sbf2PdzMxKcxExM7PSXETMzKw0FxEzMyvNRcTMzEpzETEzs9JcRMzMrDQXETMzK81FxMzMSnMRMTOz0lxEzMysNBcRMzMrzUXEzMxKcxExM7PSXETMzKw0FxEzMyvNRcTMzEpzETEzs9JcRMzMrDQXETMzK81FxMzMSmuXIiLpGUlzJc2SNDPHdpE0RdKT+e/OOS5JoyQ1SJoj6dDCeobl+Z+UNKw99sXMrCtrz5bIJyKif0TU5/HzgKkR0Q+YmscBjgf65dcI4ApIRQcYCRwOHAaMbCw8ZmZWGx2pO2sQMDYPjwUGF+LjInkY6CFpd+A4YEpELI+IFcAUYGCNczYz69Laq4gEcKekRySNyLGeEbEkDz8H9MzDvYCFhWUX5VhL8fVIGiFppqSZy5Yt21T7YGbW5W3ZTts9KiIWS3o3MEXS48WJERGSYlNtLCJGA6MB6uvrN9l6zcy6unZpiUTE4vx3KfBH0jWN53M3Ffnv0jz7YqBPYfHeOdZS3MzMaqTmRUTSuyTt0DgMDADmAROBxjushgG35uGJwNB8l9YRwKrc7TUZGCBp53xBfUCOmZlZjbRHd1ZP4I+SGrd/Q0T8RdIMYIKk04F/Al/I808CTgAagDXAcICIWC7pImBGnu/HEbG8drthZmY1LyIR8RRwSDPxF4Fjm4kHcHYL6xoDjNnUOZqZWWU60i2+ZmbWybiImJlZaS4iZmZWmouImZmV5iJiZmaluYiYmVlpLiJmZlaai4iZmZXmImJmZqW5iJiZWWkuImZmVpqLiJmZleYiYmZmpbmImJlZaS4iZmZWmouImZmV5iJiZmaluYiYmVlpLiJmZlaai4iZmZXW6YuIpIGSnpDUIOm89s7HzKwr6dRFRFI34LfA8cABwMmSDmjfrMzMuo5OXUSAw4CGiHgqIl4HxgOD2jknM7MuY8v2TqCNegELC+OLgMObziRpBDAij74s6Yka5Naa3YAX2roSaRNkUrk256wLaprwJjnGNT7IXfK8AJ8bG9BRzos9mwt29iJSkYgYDYxu7zwaSZoZEfXtncfG6Gw5d7Z8wTnXSmfLuaPn29m7sxYDfQrjvXPMzMxqoLMXkRlAP0l7SdoKGAJMbOeczMy6jE7dnRUR6ySdA0wGugFjImJ+O6dViQ7TtbYROlvOnS1fcM610tly7tD5KiLaOwczM+ukOnt3lpmZtSMXETMzK81FpAORdIGk72yidfWQdNamWFcr23hG0m7V3EaT7R0t6bYqrr+vpHkVzPffx7baORW2ucnOjVa28TVJj0m6vkm8XtKoFpap6TnQEklflvSeTbCeDrE/ranFubAxXEQ2Xz2AqhaRLqwHm+jYSupIN7ecBXwqIk5pDEjaMiJmRsTX2jGvSnwZ2Kgi0sGOfaflIlKh/Cn1cUnXSPq7pOslfVLSg5KelHSYpF0k/UnSHEkPS3p/XvYCSWMk3SPpKUlfK6z3+3l9DwD7FeJnSJohabakWyRtJ2kHSU9L6p7n2bE43sRPgb0lzcrrua2w7t9I+nIe/qCkeyU9ImmypN1z/GuSFuR9GZ9ju0q6U9J8Sb8DVFjnn/I65ucnBCDp3yT9Og9/V9KNki7Nr7ty/Jh8LAdIekjS3yT9l6Tt8/SB+bj/DfhcYXutHdNTJU3P+/6fkrrl1zWS5kmaK+mbhf2fLWk2cHaTf+/7cz5/k/ThHB8HXNt4bIFbgD0l3ZzzvF5K3w0ufqrNn+bvKeR+raQHgWslHVjId46kflU+N9Yj6UrgvcAdklY1ye+/W1ttOQcKuV9aYU7vknR73s95kr4o6Ud53+dJGq3kJKAeuD4fw2034thXdX9a2IfWcqv1+0TbRYRfFbyAvsA64GBS8X0EGEM66QYBfwIuA0bm+Y8BZuXhC4C/AluTHmHwItAd+CAwF9gO2BFoAL6Tl9m1sO2Lga/m4d8Dg/PwCOCXreQ7Lw8fDdxWmPYb0ie37jmvuhz/Iuk2aYB/AVvn4R757yjgR3n400AAu+XxXfLfbYF5wK7A9sA/8naOID264WDgfmB6jo8EzgXuA96V13Eu8CNgG9Jjbfrl4zyhcT9aOabvA/4MdM/zXQ4Mzcd6SuEYNO7THOBjefgXhWO2HbBNHu4HzMzDHwfuzPu4E7AEWEX6ousWwEPAUXneZwrHpx64p5D7I8C2efwy4JQ8vFU+hlU7N1o5x5/Jx7JpfkcXjnvpcyBP+ytwcIX5/E/gqsL4To3byOPXAifm4XuA+qb7UsGxr+r+tLAPreVW0/eJTfFyS2TjPB0RcyPiLWA+MDXSv9Jc0pv2UaQTm4i4C9hV0o552dsjYm1EvAAsBXoCHwX+GBFrImI17/yi5EH5k/Bc4BTgwBz/HTA8Dw8nnSxl7QccBEzJn6p/QHozhPTmer2kU0nFE+BjwHV5/24HVhTW9TWlT/MPk54i0C8iXgbuAj4DvEz6D/hPYC3pzbY+H4NXSU9hfjDnMYz0nJ79Scf8yXycr2uSf3PH9FjSf7oZeV3Hkj5hPwW8V9JlkgYCqyX1IBWT+/L6ri2suztwVT7+/5XzIyLuJf1bdwNOJhW/6RGxKJ8Xs/L0DZkYEa/m4YeA70k6F9gzx9v73CjmV1T6HJC0P+nNd26FOcwFPiXpZ5I+GhGrgE9Impb3/Rje3vey+1bt/WluH1rTEd8nWuU+wY2ztjD8VmH8LdKxfKPCZd9kw8f+GtInidlKXU9HA0TEg0pdLUcD3SJigxeCSUWg+IFhm/xXwPyIOLKZZT5N+g92IvB9SQe3tPKcyyeBIyNiTW6eN27jd8D3gMdJn8C+TPq0NQf4BLAP8DSplXByk/X238B+NXdMBYyNiPObyfMQ4DjgTOALwLdaWfc3geeBQ0jH7rXCtD+QCt1wUkvn883kAe887tvwTq80DkTEDZKmkY75JElfaSUv2LTnRkte2fAsb9uIc6DiN7OI+LukQ4ETgIslTSV1OdZHxEJJF7D+cW1U0bGv9v60sA+t5dae7xOluCWyad1P+jTQeBK+kD85tOQ+YHDuw92B9IbdaAdgSe7HPKXJcuOAG2j9BH4prwPSp/8DJG2dP30fm+NPAHWSjsw5d1fqn98C6BMRd5O6lnYitSLuA76U5z0e2DmvZydgRf7Ptj+p6wqAiJhG+hT3JVKX33fyeu4nvZk/Svqk9xFJ++R1v0vSvqT/pH0l7Z1X944i04KpwEmS3p3XtYukPXMf9BYRcQupxXVoRKwEVko6Ki9bPM47AUty6+I0Usuj0TVAXeHYtuQZUqsIUrdGsyS9F3gqIkYBtwLvp7rnRlu09Ry4sdINKd1ttSYiriN1NR6aJ72gdM3spMLsxfMdKjz21d6fFvah0tyKOXbEcwFwS2RTuwAYI2kOsIb0abVFEfE3STcBs0lN1xmFyT8EpgHL8t/if5DrSf2fLZ7AEfGi0kX/ecAdpOsJ80if+h/N87yudFFylKSdSOfDr4G/A9flmIBREbFS0oXAjZLmk1oTz+bN/QU4U9JjpML0cJN0JgD9gSnAt4GHIuIVSa8B90fEsvwp6kZJW+dlfpA/xY0Abpe0hlR4dqAVEbFA0g+AO3MxfIP06fVV4Pc5BtDYUhlO+jcL0rWORpcDt0gamvev2HJ4XNJSUtffL0gtluZcCFwt6SJSn31LvgCcJukN4DngJxGxvFrnRhu16RyIiBVU7mDgF5LeIv07/jswmHQeP8c7j8k1wJWSXgWOpPJjX+39aW4ftq0wN6C67xObgh970gnlN/5BEXFae+dSCaU7ey6NiKntncumIGk7Ul/3oRX0cddURz03NsNzoMPvT63OBbdEOhlJl5F+DviE9s5lQ3LX2XRgdkf+z7YxJH0SuJr0BtLRCkiHOzc2t3Ogs+xPLc8Ft0TMzKw0X1g3M7PSXETMzKw0FxEzMyvNF9bNakDSm6Q7urqTvmw2jnRx/q12TcysjVxEzGrj1YjoD5C/CHkD6TlII9szKbO2cneWWY1FxFLSQ/HOUdLiE4MlDW5cTukJwYPaKW2zZvkWX7MakPRyRGzfJLaS9BDMl4C3IuI1pcfA3xgR9ZI+DnwzIgbnpwfMIj0EcB1mHYS7s8zaX3fgN/mBk28C+0J6YrCkyyXVkZ6xdIsLiHU0LiJm7SA/dPFN0rOQRtLyE4PHAacCQ3j70d5mHYaLiFmN5ZbFlcBvIiJyV9WiiHhL0jDWf2LwdOC5iFhQ+2zNWuciYlYb2yr9SFbjLb7XAr/K01p7YvDz+Umyf6pptmYV8oV1sw6sIz8x2Ax8i69Zh5WfGPwYcJkLiHVUbomYmVlpbomYmVlpLiJmZlaai4iZmZXmImJmZqW5iJiZWWn/H05cusdBfF7XAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "  \n",
    "left = [1, 2, 3, 4, 5, 6, 7]\n",
    "\n",
    "height = [monday['attendance'].median(), tuesday['attendance'].median(), wednesday['attendance'].median(), \n",
    "thursday['attendance'].median(), friday['attendance'].median(), saturday['attendance'].median(), sunday['attendance'].median()]\n",
    "\n",
    "tick_label = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'green', 'red'])\n",
    "  \n",
    "plt.xlabel('Day')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Day')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Najwięcej kibiców jest w weekendy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Zwycięstwo / porażka gospodarzy\n",
    "![image3](win.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Win', 'Loss'], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['home_team_outcome'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "win = data[data['home_team_outcome'] == 'Win']\n",
    "loss = data[data['home_team_outcome'] == 'Loss']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Średnia ilość kibiców przy wygraniu/przegraniu gospodarzy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "left = [1, 2]\n",
    "\n",
    "height = [win['attendance'].mean(), loss['attendance'].mean()]\n",
    "\n",
    "tick_label = ['win', 'loss']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'red'])\n",
    "  \n",
    "plt.xlabel('Win')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Win')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mediana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "left = [1, 2]\n",
    "\n",
    "height = [win['attendance'].median(), loss['attendance'].median()]\n",
    "\n",
    "tick_label = ['win', 'loss']\n",
    "\n",
    "plt.bar(left, height, tick_label = tick_label,\n",
    "        width = 0.8, color = ['blue', 'red'])\n",
    "  \n",
    "plt.xlabel('Win')\n",
    "plt.ylabel('Attendance')\n",
    "plt.title('Attendance - Win')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nie ma to wpływu, raczej nie jest tak, że widać przegraną przed końcem i przez to kibice wychodzą. A nawet jeśli to działa to w miarę równomiernie w obie strony."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.0 64-bit",
   "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": "3.9.0"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "3dafdb3de6203a1118d6c063d9a807622a512a5be3d463a10b75ce9c56521739"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}