data_process.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d6e3c2de215d28d7",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Przetwarzanie danych"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5562e26a026ed454",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Importy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5737f9724f382706",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.382788Z",
     "start_time": "2024-07-07T13:12:43.922839Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, precision_score, classification_report, confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from ydata_profiling import ProfileReport"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8ed3ff11d9224c78",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.414837Z",
     "start_time": "2024-07-07T13:12:47.384196Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matches = pd.read_csv('bigger_matches.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ce796bd7555228e",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## EDA (Eksploracyjna analiza danych)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "e92e2936dd63786d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.422060Z",
     "start_time": "2024-07-07T13:12:47.415870Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3800, 27)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "c06a7f52cba7c6d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.429583Z",
     "start_time": "2024-07-07T13:12:47.422587Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date             object\n",
       "time             object\n",
       "comp             object\n",
       "round            object\n",
       "day              object\n",
       "venue            object\n",
       "result           object\n",
       "gf                int64\n",
       "ga                int64\n",
       "opponent         object\n",
       "xg              float64\n",
       "xga             float64\n",
       "poss            float64\n",
       "attendance      float64\n",
       "captain          object\n",
       "formation        object\n",
       "referee          object\n",
       "match report     object\n",
       "notes           float64\n",
       "sh              float64\n",
       "sot             float64\n",
       "dist            float64\n",
       "fk              float64\n",
       "pk                int64\n",
       "pkatt             int64\n",
       "season            int64\n",
       "team             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ae03b226b25bbbc",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Zamiana poszczególnych kolumn na odpowiednie typy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "7d479dfc037b71fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.461527Z",
     "start_time": "2024-07-07T13:12:47.430591Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>comp</th>\n",
       "      <th>round</th>\n",
       "      <th>day</th>\n",
       "      <th>venue</th>\n",
       "      <th>result</th>\n",
       "      <th>gf</th>\n",
       "      <th>ga</th>\n",
       "      <th>opponent</th>\n",
       "      <th>...</th>\n",
       "      <th>pk</th>\n",
       "      <th>pkatt</th>\n",
       "      <th>season</th>\n",
       "      <th>team</th>\n",
       "      <th>venue_code</th>\n",
       "      <th>opponent_code</th>\n",
       "      <th>referee_code</th>\n",
       "      <th>hour</th>\n",
       "      <th>day_code</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-08-11</td>\n",
       "      <td>20:00</td>\n",
       "      <td>Premier League</td>\n",
       "      <td>Matchweek 1</td>\n",
       "      <td>Fri</td>\n",
       "      <td>Away</td>\n",
       "      <td>W</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>Burnley</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-08-19</td>\n",
       "      <td>20:00</td>\n",
       "      <td>Premier League</td>\n",
       "      <td>Matchweek 2</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Home</td>\n",
       "      <td>W</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Newcastle Utd</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-08-27</td>\n",
       "      <td>14:00</td>\n",
       "      <td>Premier League</td>\n",
       "      <td>Matchweek 3</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Away</td>\n",
       "      <td>W</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Sheffield Utd</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-09-02</td>\n",
       "      <td>15:00</td>\n",
       "      <td>Premier League</td>\n",
       "      <td>Matchweek 4</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Home</td>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-09-16</td>\n",
       "      <td>15:00</td>\n",
       "      <td>Premier League</td>\n",
       "      <td>Matchweek 5</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Away</td>\n",
       "      <td>W</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>West Ham</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        date   time            comp        round  day venue result  gf  ga  \\\n",
       "1 2023-08-11  20:00  Premier League  Matchweek 1  Fri  Away      W   3   0   \n",
       "3 2023-08-19  20:00  Premier League  Matchweek 2  Sat  Home      W   1   0   \n",
       "4 2023-08-27  14:00  Premier League  Matchweek 3  Sun  Away      W   2   1   \n",
       "5 2023-09-02  15:00  Premier League  Matchweek 4  Sat  Home      W   5   1   \n",
       "6 2023-09-16  15:00  Premier League  Matchweek 5  Sat  Away      W   3   1   \n",
       "\n",
       "        opponent  ...  pk  pkatt  season             team venue_code  \\\n",
       "1        Burnley  ...   0      0    2023  Manchester City          0   \n",
       "3  Newcastle Utd  ...   0      0    2023  Manchester City          1   \n",
       "4  Sheffield Utd  ...   0      1    2023  Manchester City          0   \n",
       "5         Fulham  ...   1      1    2023  Manchester City          1   \n",
       "6       West Ham  ...   0      0    2023  Manchester City          0   \n",
       "\n",
       "  opponent_code referee_code hour  day_code  target  \n",
       "1             5            4   20         4       1  \n",
       "3            16           25   20         5       1  \n",
       "4            19            9   14         6       1  \n",
       "5             9           18   15         5       1  \n",
       "6            24            1   15         5       1  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches[\"date\"] = pd.to_datetime(matches[\"date\"])\n",
    "matches[\"venue_code\"] = matches[\"venue\"].astype(\"category\").cat.codes\n",
    "matches[\"opponent_code\"] = matches[\"opponent\"].astype(\"category\").cat.codes\n",
    "matches[\"referee_code\"] = matches[\"referee\"].astype(\"category\").cat.codes\n",
    "matches[\"hour\"] = matches[\"time\"].str.replace(\":.+\", \"\", regex=True).astype(\"int\")\n",
    "matches[\"day_code\"] = matches[\"date\"].dt.dayofweek\n",
    "matches[\"target\"] = (matches[\"result\"] == \"W\").astype(int)\n",
    "matches.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2692c1917cc61407",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Odrzucenie niepotrzebnych kolumn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "758a39c419506dd0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.467509Z",
     "start_time": "2024-07-07T13:12:47.462550Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matches.drop(columns=[\"venue\", \"time\", \"comp\", \"round\", \"day\", \"venue\",\"result\", \"captain\", \"referee\", \"match report\", \"notes\", \"opponent\", \"formation\", \"attendance\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2570c3394af73145",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.481426Z",
     "start_time": "2024-07-07T13:12:47.469057Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gf</th>\n",
       "      <th>ga</th>\n",
       "      <th>xg</th>\n",
       "      <th>xga</th>\n",
       "      <th>poss</th>\n",
       "      <th>sh</th>\n",
       "      <th>sot</th>\n",
       "      <th>dist</th>\n",
       "      <th>fk</th>\n",
       "      <th>pk</th>\n",
       "      <th>pkatt</th>\n",
       "      <th>season</th>\n",
       "      <th>team</th>\n",
       "      <th>venue_code</th>\n",
       "      <th>opponent_code</th>\n",
       "      <th>referee_code</th>\n",
       "      <th>hour</th>\n",
       "      <th>day_code</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-08-11</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>65.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-08-19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>59.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-08-27</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>79.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>17.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-09-02</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.4</td>\n",
       "      <td>68.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-09-16</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.9</td>\n",
       "      <td>68.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2023</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gf  ga   xg  xga  poss    sh   sot  dist   fk  pk  pkatt  \\\n",
       "1 2023-08-11   3   0  1.9  0.3  65.0  17.0   8.0  13.9  0.0   0      0   \n",
       "3 2023-08-19   1   0  1.0  0.3  59.0  14.0   4.0  17.9  0.0   0      0   \n",
       "4 2023-08-27   2   1  3.5  0.7  79.0  29.0   9.0  17.3  2.0   0      1   \n",
       "5 2023-09-02   5   1  2.2  1.4  68.0   6.0   4.0  14.8  0.0   1      1   \n",
       "6 2023-09-16   3   1  3.6  0.9  68.0  29.0  13.0  16.4  1.0   0      0   \n",
       "\n",
       "   season             team  venue_code  opponent_code  referee_code  hour  \\\n",
       "1    2023  Manchester City           0              5             4    20   \n",
       "3    2023  Manchester City           1             16            25    20   \n",
       "4    2023  Manchester City           0             19             9    14   \n",
       "5    2023  Manchester City           1              9            18    15   \n",
       "6    2023  Manchester City           0             24             1    15   \n",
       "\n",
       "   day_code  target  \n",
       "1         4       1  \n",
       "3         5       1  \n",
       "4         6       1  \n",
       "5         5       1  \n",
       "6         5       1  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df041839ad7f4940",
   "metadata": {
    "collapsed": false
   },
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "90f75a4f85ebd00b",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Mapa korelacji dla ramki matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "d9e6ca6e44b23a54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:47.973096Z",
     "start_time": "2024-07-07T13:12:47.482434Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(matches.drop(columns=\"team\").corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c09055185e8bb",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Wpływ współczynnika oczekiwanych goli na rezultat meczu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "919b38ea74094f89",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:12:48.516434Z",
     "start_time": "2024-07-07T13:12:47.974105Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='target', ylabel='count'>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"target\", hue=\"xg\", data=matches)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3a9266695fbcc41",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Utworzenie ProfileReportu, dla ułatwienia analizy danych"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f7fb95843b4edd5a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:11.898338Z",
     "start_time": "2024-07-07T13:12:48.517442Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# ProfileReport(matches, title=\"Profiling report for matches\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f084ec4482d35265",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date             datetime64[ns]\n",
       "gf                        int64\n",
       "ga                        int64\n",
       "xg                      float64\n",
       "xga                     float64\n",
       "poss                    float64\n",
       "sh                      float64\n",
       "sot                     float64\n",
       "dist                    float64\n",
       "fk                      float64\n",
       "pk                        int64\n",
       "pkatt                     int64\n",
       "season                    int64\n",
       "team                     object\n",
       "venue_code                 int8\n",
       "opponent_code              int8\n",
       "referee_code               int8\n",
       "hour                      int32\n",
       "day_code                  int32\n",
       "target                    int32\n",
       "dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b300c93dd47296e",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Tworzenie średniej kroczącej"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "1c60d593723f7bfa",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def rolling_averages(group, cols, new_cols):\n",
    "    group = group.sort_values(\"date\")\n",
    "    rolling_stats = group[cols].rolling(3, closed='left').mean()\n",
    "    group[new_cols] = rolling_stats\n",
    "    group = group.dropna(subset=new_cols)\n",
    "    return group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "240be6a2a6508aad",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cols = [\"gf\", \"ga\", \"sh\", \"sot\", \"dist\", \"fk\", \"pk\", \"pkatt\"]\n",
    "new_cols = [f\"{c}_rolling\" for c in cols]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80c278cd1fe1fcc5",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Utworzenie nowej ramki danych - matches_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "336160c81e00ad0c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.140142Z",
     "start_time": "2024-07-07T13:13:11.917223Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matches_rolling = matches.groupby(\"team\").apply(lambda x: rolling_averages(x, cols, new_cols), include_groups=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "41ffc6c375165562",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.146588Z",
     "start_time": "2024-07-07T13:13:12.141150Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "if 'team' not in matches_rolling.columns:\n",
    "    matches_rolling['team'] = matches_rolling.index.get_level_values(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "49c3ae357a610349",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.169670Z",
     "start_time": "2024-07-07T13:13:12.147597Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gf</th>\n",
       "      <th>ga</th>\n",
       "      <th>xg</th>\n",
       "      <th>xga</th>\n",
       "      <th>poss</th>\n",
       "      <th>sh</th>\n",
       "      <th>sot</th>\n",
       "      <th>dist</th>\n",
       "      <th>fk</th>\n",
       "      <th>...</th>\n",
       "      <th>target</th>\n",
       "      <th>gf_rolling</th>\n",
       "      <th>ga_rolling</th>\n",
       "      <th>sh_rolling</th>\n",
       "      <th>sot_rolling</th>\n",
       "      <th>dist_rolling</th>\n",
       "      <th>fk_rolling</th>\n",
       "      <th>pk_rolling</th>\n",
       "      <th>pkatt_rolling</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Arsenal</th>\n",
       "      <th>3</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>10.666667</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>17.2</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-09-15</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>48.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-09-22</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>58.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>19.3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.9</td>\n",
       "      <td>45.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>17.666667</td>\n",
       "      <td>5.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>12.333333</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>18.1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 date  gf  ga   xg  xga  poss    sh  sot  dist   fk  ...  \\\n",
       "team                                                                 ...   \n",
       "Arsenal 3  2019-09-01   2   2  2.4  2.0  55.0  26.0  8.0  18.1  2.0  ...   \n",
       "        4  2019-09-15   2   2  0.8  2.7  48.0   7.0  4.0  20.8  0.0  ...   \n",
       "        6  2019-09-22   3   2  2.4  1.5  58.0  20.0  5.0  16.9  2.0  ...   \n",
       "        8  2019-09-30   1   1  1.9  0.9  45.0  10.0  5.0  16.6  1.0  ...   \n",
       "        10 2019-10-06   1   0  1.2  0.6  53.0  12.0  2.0  15.3  0.0  ...   \n",
       "\n",
       "            target  gf_rolling  ga_rolling  sh_rolling  sot_rolling  \\\n",
       "team                                                                  \n",
       "Arsenal 3        0    1.333333    1.333333   10.666667     4.666667   \n",
       "        4        0    1.666667    2.000000   16.666667     6.666667   \n",
       "        6        1    1.666667    2.333333   14.000000     5.000000   \n",
       "        8        0    2.333333    2.000000   17.666667     5.666667   \n",
       "        10       1    2.000000    1.666667   12.333333     4.666667   \n",
       "\n",
       "            dist_rolling  fk_rolling  pk_rolling  pkatt_rolling     team  \n",
       "team                                                                      \n",
       "Arsenal 3           17.2    0.333333    0.000000       0.000000  Arsenal  \n",
       "        4           18.6    1.000000    0.000000       0.000000  Arsenal  \n",
       "        6           19.3    1.000000    0.000000       0.000000  Arsenal  \n",
       "        8           18.6    1.333333    0.333333       0.333333  Arsenal  \n",
       "        10          18.1    1.000000    0.333333       0.333333  Arsenal  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_rolling.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "61ba31db3378f089",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.199058Z",
     "start_time": "2024-07-07T13:13:12.170187Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>3</th>\n",
       "      <td>2019-09-01</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-09-15</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-09-22</td>\n",
       "      <td>3</td>\n",
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       "      <td>58.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.9</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>1</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>19.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.9</td>\n",
       "      <td>45.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
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       "      <td>17.666667</td>\n",
       "      <td>5.666667</td>\n",
       "      <td>18.600000</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>12.333333</td>\n",
       "      <td>4.666667</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2024-04-24</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.9</td>\n",
       "      <td>63.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.1</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2.000000</td>\n",
       "      <td>9.666667</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>20.533333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Wolverhampton Wanderers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2024-04-27</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>58.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>10.333333</td>\n",
       "      <td>3.333333</td>\n",
       "      <td>18.766667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Wolverhampton Wanderers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2024-05-04</td>\n",
       "      <td>1</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
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       "      <td>11.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>19.666667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Wolverhampton Wanderers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2024-05-11</td>\n",
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       "      <td>3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>62.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.6</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>10.000000</td>\n",
       "      <td>3.333333</td>\n",
       "      <td>15.966667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Wolverhampton Wanderers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2024-05-19</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>33.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.666667</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>14.133333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Wolverhampton Wanderers</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3719 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  gf  ga   xg  xga  poss    sh  sot  dist   fk  ...  target  \\\n",
       "3  2019-09-01   2   2  2.4  2.0  55.0  26.0  8.0  18.1  2.0  ...       0   \n",
       "4  2019-09-15   2   2  0.8  2.7  48.0   7.0  4.0  20.8  0.0  ...       0   \n",
       "6  2019-09-22   3   2  2.4  1.5  58.0  20.0  5.0  16.9  2.0  ...       1   \n",
       "8  2019-09-30   1   1  1.9  0.9  45.0  10.0  5.0  16.6  1.0  ...       0   \n",
       "10 2019-10-06   1   0  1.2  0.6  53.0  12.0  2.0  15.3  0.0  ...       1   \n",
       "..        ...  ..  ..  ...  ...   ...   ...  ...   ...  ...  ...     ...   \n",
       "40 2024-04-24   0   1  0.5  1.9  63.0  15.0  4.0  20.1  0.0  ...       0   \n",
       "41 2024-04-27   2   1  1.2  0.6  58.0  13.0  5.0  18.8  0.0  ...       1   \n",
       "42 2024-05-04   1   5  0.3  3.7  42.0   2.0  1.0   9.0  0.0  ...       0   \n",
       "43 2024-05-11   1   3  1.6  2.6  62.0  14.0  8.0  14.6  0.0  ...       0   \n",
       "44 2024-05-19   0   2  0.5  4.5  33.0   4.0  2.0  19.0  1.0  ...       0   \n",
       "\n",
       "    gf_rolling  ga_rolling  sh_rolling  sot_rolling  dist_rolling  fk_rolling  \\\n",
       "3     1.333333    1.333333   10.666667     4.666667     17.200000    0.333333   \n",
       "4     1.666667    2.000000   16.666667     6.666667     18.600000    1.000000   \n",
       "6     1.666667    2.333333   14.000000     5.000000     19.300000    1.000000   \n",
       "8     2.333333    2.000000   17.666667     5.666667     18.600000    1.333333   \n",
       "10    2.000000    1.666667   12.333333     4.666667     18.100000    1.000000   \n",
       "..         ...         ...         ...          ...           ...         ...   \n",
       "40    1.000000    2.000000    9.666667     4.000000     20.533333    0.333333   \n",
       "41    0.666667    1.666667   10.333333     3.333333     18.766667    0.000000   \n",
       "42    0.666667    1.333333   11.000000     4.000000     19.666667    0.000000   \n",
       "43    1.000000    2.333333   10.000000     3.333333     15.966667    0.000000   \n",
       "44    1.333333    3.000000    9.666667     4.666667     14.133333    0.000000   \n",
       "\n",
       "    pk_rolling  pkatt_rolling                     team  \n",
       "3     0.000000       0.000000                  Arsenal  \n",
       "4     0.000000       0.000000                  Arsenal  \n",
       "6     0.000000       0.000000                  Arsenal  \n",
       "8     0.333333       0.333333                  Arsenal  \n",
       "10    0.333333       0.333333                  Arsenal  \n",
       "..         ...            ...                      ...  \n",
       "40    0.333333       0.333333  Wolverhampton Wanderers  \n",
       "41    0.000000       0.000000  Wolverhampton Wanderers  \n",
       "42    0.000000       0.000000  Wolverhampton Wanderers  \n",
       "43    0.000000       0.000000  Wolverhampton Wanderers  \n",
       "44    0.000000       0.000000  Wolverhampton Wanderers  \n",
       "\n",
       "[3719 rows x 28 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_rolling.droplevel(\"team\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c49563d2b51abb73",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.203766Z",
     "start_time": "2024-07-07T13:13:12.199058Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matches_rolling.index = range(matches_rolling.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "6ae34af07109039e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:12.225231Z",
     "start_time": "2024-07-07T13:13:12.204774Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gf</th>\n",
       "      <th>ga</th>\n",
       "      <th>xg</th>\n",
       "      <th>xga</th>\n",
       "      <th>poss</th>\n",
       "      <th>sh</th>\n",
       "      <th>sot</th>\n",
       "      <th>dist</th>\n",
       "      <th>fk</th>\n",
       "      <th>...</th>\n",
       "      <th>target</th>\n",
       "      <th>gf_rolling</th>\n",
       "      <th>ga_rolling</th>\n",
       "      <th>sh_rolling</th>\n",
       "      <th>sot_rolling</th>\n",
       "      <th>dist_rolling</th>\n",
       "      <th>fk_rolling</th>\n",
       "      <th>pk_rolling</th>\n",
       "      <th>pkatt_rolling</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>10.666667</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>17.2</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-09-15</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>48.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-09-22</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>58.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>19.3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.9</td>\n",
       "      <td>45.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>17.666667</td>\n",
       "      <td>5.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>12.333333</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>18.1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gf  ga   xg  xga  poss    sh  sot  dist   fk  ...  target  \\\n",
       "0 2019-09-01   2   2  2.4  2.0  55.0  26.0  8.0  18.1  2.0  ...       0   \n",
       "1 2019-09-15   2   2  0.8  2.7  48.0   7.0  4.0  20.8  0.0  ...       0   \n",
       "2 2019-09-22   3   2  2.4  1.5  58.0  20.0  5.0  16.9  2.0  ...       1   \n",
       "3 2019-09-30   1   1  1.9  0.9  45.0  10.0  5.0  16.6  1.0  ...       0   \n",
       "4 2019-10-06   1   0  1.2  0.6  53.0  12.0  2.0  15.3  0.0  ...       1   \n",
       "\n",
       "   gf_rolling  ga_rolling  sh_rolling  sot_rolling  dist_rolling  fk_rolling  \\\n",
       "0    1.333333    1.333333   10.666667     4.666667          17.2    0.333333   \n",
       "1    1.666667    2.000000   16.666667     6.666667          18.6    1.000000   \n",
       "2    1.666667    2.333333   14.000000     5.000000          19.3    1.000000   \n",
       "3    2.333333    2.000000   17.666667     5.666667          18.6    1.333333   \n",
       "4    2.000000    1.666667   12.333333     4.666667          18.1    1.000000   \n",
       "\n",
       "   pk_rolling  pkatt_rolling     team  \n",
       "0    0.000000       0.000000  Arsenal  \n",
       "1    0.000000       0.000000  Arsenal  \n",
       "2    0.000000       0.000000  Arsenal  \n",
       "3    0.333333       0.333333  Arsenal  \n",
       "4    0.333333       0.333333  Arsenal  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_rolling.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f31ef3308827534",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Odrzucenie niepotrzebnych kolumn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "3a4a5319fdc800e7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:15.041881Z",
     "start_time": "2024-07-07T13:13:12.226237Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matches_rolling= matches_rolling.drop(columns=[\"gf\", \"ga\", \"xg\", \"xga\", \"poss\",  \"sh\", \"sot\", \"dist\", \"fk\", \"pk\", \"pkatt\"] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9ffab3e1e6a9e0e8",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.044905Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>season</th>\n",
       "      <th>venue_code</th>\n",
       "      <th>opponent_code</th>\n",
       "      <th>referee_code</th>\n",
       "      <th>hour</th>\n",
       "      <th>day_code</th>\n",
       "      <th>target</th>\n",
       "      <th>gf_rolling</th>\n",
       "      <th>ga_rolling</th>\n",
       "      <th>sh_rolling</th>\n",
       "      <th>sot_rolling</th>\n",
       "      <th>dist_rolling</th>\n",
       "      <th>fk_rolling</th>\n",
       "      <th>pk_rolling</th>\n",
       "      <th>pkatt_rolling</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1.333333</td>\n",
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       "      <td>17.2</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-09-15</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
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       "      <td>6.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-09-22</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>19.3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>2019</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>13</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>17.666667</td>\n",
       "      <td>5.666667</td>\n",
       "      <td>18.6</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>12.333333</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>18.1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>Arsenal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  season  venue_code  opponent_code  referee_code  hour  day_code  \\\n",
       "0 2019-09-01    2019           1             21            16    16         6   \n",
       "1 2019-09-15    2019           0             22             2    16         6   \n",
       "2 2019-09-22    2019           1              1            11    16         6   \n",
       "3 2019-09-30    2019           0             15            13    20         0   \n",
       "4 2019-10-06    2019           1              2            16    14         6   \n",
       "\n",
       "   target  gf_rolling  ga_rolling  sh_rolling  sot_rolling  dist_rolling  \\\n",
       "0       0    1.333333    1.333333   10.666667     4.666667          17.2   \n",
       "1       0    1.666667    2.000000   16.666667     6.666667          18.6   \n",
       "2       1    1.666667    2.333333   14.000000     5.000000          19.3   \n",
       "3       0    2.333333    2.000000   17.666667     5.666667          18.6   \n",
       "4       1    2.000000    1.666667   12.333333     4.666667          18.1   \n",
       "\n",
       "   fk_rolling  pk_rolling  pkatt_rolling     team  \n",
       "0    0.333333    0.000000       0.000000  Arsenal  \n",
       "1    1.000000    0.000000       0.000000  Arsenal  \n",
       "2    1.000000    0.000000       0.000000  Arsenal  \n",
       "3    1.333333    0.333333       0.333333  Arsenal  \n",
       "4    1.000000    0.333333       0.333333  Arsenal  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches_rolling.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91042d0546e1c05e",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Mapa korelacji dla ramki matches_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "c005fe02abe884a6",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(matches_rolling.drop(columns=\"team\").corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73f2493f6ac45cce",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Przygotowanie cech, na podstawie których będę przewidywał wynik meczu (target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "b7e900011a0cc9ff",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.048433Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X = matches[[\n",
    "    \"venue_code\",\n",
    "    \"opponent_code\",\n",
    "    \"referee_code\",\n",
    "    \"sh\",\n",
    "    \"sot\",\n",
    "    \"dist\",\n",
    "    \"fk\",\n",
    "    \"pk\",\n",
    "    \"pkatt\"\n",
    "]]\n",
    "Y = matches[\"target\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "1a8b57da5f1dcb1d",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.049431Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X_other = matches_rolling[[\n",
    "    \"venue_code\",\n",
    "    \"opponent_code\",\n",
    "    \"referee_code\",\n",
    "    \"ga_rolling\",\n",
    "    \"gf_rolling\",\n",
    "    \"sh_rolling\",\n",
    "    \"sot_rolling\",\n",
    "    \"dist_rolling\",\n",
    "    \"fk_rolling\",\n",
    "    \"pk_rolling\",\n",
    "    \"pkatt_rolling\"\n",
    "]]\n",
    "Y_other = matches_rolling[\"target\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1f5ab46ed25b50fd",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.050432Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Liczba NaN w każdej kolumnie:\n",
      " venue_code       0\n",
      "opponent_code    0\n",
      "referee_code     0\n",
      "sh               0\n",
      "sot              0\n",
      "dist             1\n",
      "fk               0\n",
      "pk               0\n",
      "pkatt            0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "nan_columns = X.isna().sum()\n",
    "print(\"Liczba NaN w każdej kolumnie:\\n\", nan_columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "925f8b6bcd539cf5",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Odrzucenie wierszu z wartością NaN w kolumnie dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6ef6c6cf68ed46b9",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.051431Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X_cleaned = X.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "9f716551979d40e2",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.052511Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(X_cleaned.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "3408b8ff4f5eba36",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.053525Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Liczba NaN w każdej kolumnie:\n",
      " venue_code       0\n",
      "opponent_code    0\n",
      "referee_code     0\n",
      "ga_rolling       0\n",
      "gf_rolling       0\n",
      "sh_rolling       0\n",
      "sot_rolling      0\n",
      "dist_rolling     0\n",
      "fk_rolling       0\n",
      "pk_rolling       0\n",
      "pkatt_rolling    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "nan_columns = X_other.isna().sum()\n",
    "print(\"Liczba NaN w każdej kolumnie:\\n\", nan_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "6498178c2c3c9921",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>venue_code</th>\n",
       "      <th>opponent_code</th>\n",
       "      <th>referee_code</th>\n",
       "      <th>sh</th>\n",
       "      <th>sot</th>\n",
       "      <th>fk</th>\n",
       "      <th>pk</th>\n",
       "      <th>pkatt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>29.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>29.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>13</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3800 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    venue_code  opponent_code  referee_code    sh   sot   fk  pk  pkatt\n",
       "1            0              5             4  17.0   8.0  0.0   0      0\n",
       "3            1             16            25  14.0   4.0  0.0   0      0\n",
       "4            0             19             9  29.0   9.0  2.0   0      1\n",
       "5            1              9            18   6.0   4.0  0.0   1      1\n",
       "6            0             24             1  29.0  13.0  1.0   0      0\n",
       "..         ...            ...           ...   ...   ...  ...  ..    ...\n",
       "38           0             22             2  12.0   3.0  1.0   0      0\n",
       "39           1             24            13  11.0   2.0  1.0   0      0\n",
       "40           0              6            11   2.0   0.0  0.0   0      0\n",
       "41           1              5            13   6.0   2.0  0.0   0      0\n",
       "42           0             14             4   5.0   4.0  0.0   0      0\n",
       "\n",
       "[3800 rows x 8 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_cleaned"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3df865ab587d6f28",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Kod dotyczący modeli i wyników przewidywań"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10b19bed1e640c62",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### SVC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "e71d41276403a060",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-07-07T13:13:15.065217Z",
     "start_time": "2024-07-07T13:13:15.064711Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def creating_svc_model(X,Y):\n",
    "    X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)\n",
    "    sc = StandardScaler()\n",
    "    X_train_sc = sc.fit_transform(X_train)\n",
    "    X_test_sc = sc.transform(X_test)\n",
    "    \n",
    "    clf = SVC(kernel='rbf')\n",
    "    clf.fit(X_train_sc, Y_train)\n",
    "    Y_pred = clf.predict(X_test_sc)\n",
    "    return Y_pred, Y_test, clf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dc03fd737c81757",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### RFC z wykorzystaniem GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "921ed4bb103f583e",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.066719Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "def creating_rf_model(X, Y):\n",
    "    X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)\n",
    "    sc = StandardScaler()\n",
    "    X_train_sc = sc.fit_transform(X_train)\n",
    "    X_test_sc = sc.transform(X_test)\n",
    "    param_grid = {\n",
    "    'n_estimators': [50, 100, 200],\n",
    "    'max_depth': [5, 10, 20],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'min_samples_leaf': [1, 2, 4],\n",
    "    'max_features': ['auto', 'sqrt', 'log2']\n",
    "    }   \n",
    "\n",
    "    rf_model = RandomForestClassifier(random_state=42)\n",
    "    grid_search = GridSearchCV(estimator=rf_model, param_grid=param_grid, cv=5, scoring='recall')\n",
    "    grid_result = grid_search.fit(X_train_sc, Y_train)\n",
    "    Y_pred = grid_result.best_estimator_.predict(X_test_sc)\n",
    "    \n",
    "    return Y_pred, Y_test, rf_model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62675101e2ffd4bd",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Wyświetlanie wyników klasyfikacji przy pomocy raportu dotyczącego klasyfikacji i macierzy pomyłek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "bf07af497e7004d7",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.067727Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def draw_plot_result_clf(Y_test, Y_pred):\n",
    "    print(\"Classification Report:\")\n",
    "    print(classification_report(Y_test, Y_pred))\n",
    "    conf_matrix = confusion_matrix(Y_test, Y_pred)\n",
    "\n",
    "    plt.figure(figsize=(5, 5))\n",
    "    sns.heatmap(conf_matrix, annot=True, fmt='d')\n",
    "    plt.xlabel('Przewidywany wynik')\n",
    "    plt.ylabel('Rzeczywisty wynik')\n",
    "    plt.title('Macierz pomyłek')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49d41fa244b909b1",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Wyświetlenie krzywej ROC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "82ce45799594fbb7",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.068739Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def auc_roc(y_test, y_pred):\n",
    "    fpr, tpr, thresholds = roc_curve(y_test, y_pred)\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    \n",
    "    plt.figure()\n",
    "    plt.plot(fpr, tpr, lw=2, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], lw=2, linestyle='--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.0])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title('Receiver Operating Characteristic')\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show()\n",
    "    return roc_auc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e7247a7d5754d6d",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Eksperymenty dla ramki matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "b8925698010b8a62",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.069738Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Y_test_svc, Y_pred_svc, clf = creating_svc_model(X_cleaned, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "e645b709a8290e01",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.070740Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.86      0.73      0.79       550\n",
      "           1       0.49      0.68      0.57       210\n",
      "\n",
      "    accuracy                           0.72       760\n",
      "   macro avg       0.67      0.71      0.68       760\n",
      "weighted avg       0.76      0.72      0.73       760\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_svc, Y_pred_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "81a52924e6526245",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.7053679653679654"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_svc, Y_pred_svc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b04dcbb13db660c1",
   "metadata": {
    "collapsed": false
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "e792725ea7474cce",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py:540: FitFailedWarning: \n",
      "405 fits failed out of a total of 1215.\n",
      "The score on these train-test partitions for these parameters will be set to nan.\n",
      "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n",
      "\n",
      "Below are more details about the failures:\n",
      "--------------------------------------------------------------------------------\n",
      "405 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py\", line 888, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 1466, in wrapper\n",
      "    estimator._validate_params()\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 666, in _validate_params\n",
      "    validate_parameter_constraints(\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\utils\\_param_validation.py\", line 95, in validate_parameter_constraints\n",
      "    raise InvalidParameterError(\n",
      "sklearn.utils._param_validation.InvalidParameterError: The 'max_features' parameter of RandomForestClassifier must be an int in the range [1, inf), a float in the range (0.0, 1.0], a str among {'sqrt', 'log2'} or None. Got 'auto' instead.\n",
      "\n",
      "  warnings.warn(some_fits_failed_message, FitFailedWarning)\n",
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_search.py:1052: UserWarning: One or more of the test scores are non-finite: [       nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.54201226 0.53946268 0.53605481\n",
      " 0.5454093  0.54200865 0.54029571 0.54371078 0.54200865 0.54370357\n",
      " 0.54285972 0.5369167  0.53690588 0.54117202 0.53776415 0.53945546\n",
      " 0.53947349 0.54115759 0.5411612  0.53692752 0.53776415 0.54115398\n",
      " 0.53692752 0.53776415 0.54115398 0.54031735 0.5369167  0.53860801\n",
      " 0.55134151 0.55727732 0.55473134 0.55049405 0.5555824  0.55388388\n",
      " 0.54540209 0.55303282 0.55133429 0.55135233 0.5555788  0.55388388\n",
      " 0.55134511 0.55643347 0.55218897 0.54880274 0.55557519 0.55303282\n",
      " 0.54794446 0.55642625 0.55472773 0.54794446 0.55642625 0.55472773\n",
      " 0.55049405 0.55642265 0.55557519        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.54457266 0.54372521 0.5437216  0.54456906 0.54287775 0.54117923\n",
      " 0.54117202 0.54200144 0.54201587 0.54541291 0.54202308 0.54202308\n",
      " 0.53439235 0.54201947 0.54032816 0.54797692 0.55135954 0.54879913\n",
      " 0.5411612  0.54285611 0.5411612  0.5411612  0.54285611 0.5411612\n",
      " 0.54625676 0.54710422 0.54455463 0.54373603 0.54967184 0.54372881\n",
      " 0.54626758 0.54288496 0.54882077 0.54798053 0.5462784  0.55051208\n",
      " 0.54458709 0.5445907  0.55053372 0.55136675 0.54966462 0.55560765\n",
      " 0.54456906 0.54626037 0.55050847 0.55135954 0.5479661  0.55050487\n",
      " 0.55135954 0.5479661  0.55050487 0.55050847 0.55559683 0.54965741\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.53525424 0.55136314 0.56154706\n",
      " 0.55052651 0.55643707 0.5522106  0.5454057  0.55134151 0.55388388\n",
      " 0.5657555  0.55388027 0.55134872 0.56408583 0.55474216 0.55729535\n",
      " 0.54966462 0.55390552 0.55134151 0.55897944 0.55135593 0.55898305\n",
      " 0.55897944 0.55135593 0.55898305 0.54286693 0.54456545 0.54456545\n",
      " 0.56325279 0.5666282  0.57512441 0.56239452 0.56747926 0.56239452\n",
      " 0.55558601 0.56407862 0.56153985 0.55475658 0.56662459 0.56153624\n",
      " 0.56917057 0.55984133 0.56833393 0.55390191 0.56323837 0.56153985\n",
      " 0.55814281 0.560696   0.56408943 0.55814281 0.560696   0.56408943\n",
      " 0.55729174 0.55729535 0.56408222]\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "Y_test_rf, Y_pred_rf, rf = creating_rf_model(X_cleaned, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "6a7131f6a5512a2",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.79      0.73      0.76       508\n",
      "           1       0.53      0.61      0.57       252\n",
      "\n",
      "    accuracy                           0.69       760\n",
      "   macro avg       0.66      0.67      0.66       760\n",
      "weighted avg       0.70      0.69      0.70       760\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_rf, Y_pred_rf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "1f307af988596d15",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.075355Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.6697131608548932"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_rf, Y_pred_rf)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "791e3be23514cdbe",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Eksperymenty dla matches_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "3cb3cd2dc66aa008",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.076427Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Y_test_other_svc, Y_pred_other_svc, clf_other = creating_svc_model(X_other, Y_other)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "a8fda56b8cae8aa1",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.077583Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py:540: FitFailedWarning: \n",
      "405 fits failed out of a total of 1215.\n",
      "The score on these train-test partitions for these parameters will be set to nan.\n",
      "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n",
      "\n",
      "Below are more details about the failures:\n",
      "--------------------------------------------------------------------------------\n",
      "405 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py\", line 888, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 1466, in wrapper\n",
      "    estimator._validate_params()\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 666, in _validate_params\n",
      "    validate_parameter_constraints(\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\utils\\_param_validation.py\", line 95, in validate_parameter_constraints\n",
      "    raise InvalidParameterError(\n",
      "sklearn.utils._param_validation.InvalidParameterError: The 'max_features' parameter of RandomForestClassifier must be an int in the range [1, inf), a float in the range (0.0, 1.0], a str among {'sqrt', 'log2'} or None. Got 'auto' instead.\n",
      "\n",
      "  warnings.warn(some_fits_failed_message, FitFailedWarning)\n",
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_search.py:1052: UserWarning: One or more of the test scores are non-finite: [       nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.20642381 0.2073125  0.21605378\n",
      " 0.21254118 0.20642381 0.21080211 0.21254118 0.21079828 0.21167548\n",
      " 0.21781583 0.20992492 0.2116908  0.21081361 0.21080211 0.21430706\n",
      " 0.21254501 0.2134222  0.21518808 0.21867387 0.21167548 0.21691948\n",
      " 0.21867387 0.21167548 0.21691948 0.21517276 0.21254501 0.21167165\n",
      " 0.20642381 0.2073125  0.21605378 0.21254118 0.20642381 0.21080211\n",
      " 0.21254118 0.21079828 0.21167548 0.21781583 0.20992492 0.2116908\n",
      " 0.21081361 0.21080211 0.21430706 0.21254501 0.2134222  0.21518808\n",
      " 0.21867387 0.21167548 0.21691948 0.21867387 0.21167548 0.21691948\n",
      " 0.21517276 0.21254501 0.21167165        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.29307056 0.28257489 0.28342144 0.30000383 0.30090018 0.2974029\n",
      " 0.30006895 0.29482494 0.29479047 0.30003064 0.30004597 0.29392477\n",
      " 0.29739523 0.30791389 0.30442427 0.3009155  0.29569065 0.29392477\n",
      " 0.28870758 0.29308971 0.29482111 0.28870758 0.29308971 0.29482111\n",
      " 0.28955796 0.27992416 0.29304758 0.29307056 0.28257489 0.28342144\n",
      " 0.30000383 0.30090018 0.2974029  0.30006895 0.29482494 0.29479047\n",
      " 0.30003064 0.30004597 0.29392477 0.29739523 0.30791389 0.30442427\n",
      " 0.3009155  0.29569065 0.29392477 0.28870758 0.29308971 0.29482111\n",
      " 0.28870758 0.29308971 0.29482111 0.28955796 0.27992416 0.29304758\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.31667433 0.32716617 0.33944304\n",
      " 0.33591512 0.33245231 0.33417988 0.32894737 0.33506091 0.32454225\n",
      " 0.34029725 0.33155979 0.3324255  0.34208611 0.34029725 0.3315483\n",
      " 0.32718915 0.31932889 0.32192599 0.32105646 0.3105493  0.30438596\n",
      " 0.32105646 0.3105493  0.30438596 0.31754386 0.31928292 0.30266605\n",
      " 0.31667433 0.32716617 0.33944304 0.33591512 0.33245231 0.33417988\n",
      " 0.32894737 0.33506091 0.32454225 0.34029725 0.33155979 0.3324255\n",
      " 0.34208611 0.34029725 0.3315483  0.32718915 0.31932889 0.32192599\n",
      " 0.32105646 0.3105493  0.30438596 0.32105646 0.3105493  0.30438596\n",
      " 0.31754386 0.31928292 0.30266605]\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "Y_test_other_rf, Y_pred_other_rf, rf_other = creating_rf_model(X_other, Y_other)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "70a7195692ebb1bf",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      0.63      0.75       653\n",
      "           1       0.19      0.60      0.29        91\n",
      "\n",
      "    accuracy                           0.63       744\n",
      "   macro avg       0.55      0.62      0.52       744\n",
      "weighted avg       0.83      0.63      0.69       744\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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kYNGiRTA2NoaTkxNycnLw6NEjnePS0tKgVCoBAEqlssCq0Oevn/cpKiZAIiIqFW3atMHZs2dx6tQp7da4cWP07dtX+7OJiQl2796tPSYpKQk3btyAr68vAMDX1xdnz55Fenq6ts/OnTthbW0NT09PveJhCZSISIoMcCF8hQoVUL9+fZ02S0tLVKpUSds+aNAgREREwM7ODtbW1hg1ahR8fX3RtGlTAEC7du3g6emJ0NBQfPXVV1CpVJg0aRLCw8MLnXW+ChMgEZEUldEnws+fPx9yuRwhISFQq9UICgrC0qVLtfuNjIwQGxuL4cOHw9fXF5aWlggLC8P06dP1fi+ZIAiCmMGXBbn3/jF0CCQRKc1GGjoEkgiPy3+KOp76UoJoYyk8/EUbqzRxBkhEJEW8FygTIBGRJPFxSFwFSkRE0sQZIBGRFLEEygRIRCRJLIGyBEpERNLEGSARkQQJQtm8DrA0MQESEUkRzwGyBEpERNLEGSARkRRxEQwTIBGRJLEEyhIoERFJE2eARERSVEafBlGamACJiKSIJVCWQImISJo4AyQikiKuAmUCJCKSJJZAWQIlIiJp4gyQiEiKWAJlAiQikiQmQJZAiYhImjgDJCKSID4OiQmQiEiaWAJlCZSIiKSJM0AiIinidYBMgEREksQSKEugREQkTZwBEhFJEUugTIBERJLEEihLoEREJE2cARIRSRFLoEyARESSxBIoS6BERCRNnAESEUkRZ4BMgEREksRzgCyBEhGRNHEGSEQkRSyBMgESEUkSS6AsgRIRkTRxBkhEJEUsgXIGSEQkSYJGvE0Py5Ytg5eXF6ytrWFtbQ1fX1/89ddf2v0BAQGQyWQ627Bhw3TGuHHjBoKDg2FhYQFHR0eMGzcOeXl5en8FnAESEVGpqVKlCmbNmoVatWpBEASsXr0anTt3xsmTJ1GvXj0AwODBgzF9+nTtMRYWFtqf8/PzERwcDKVSiYMHDyI1NRX9+/eHiYkJvvzyS71iYQIkIpIiA5VAO3XqpPN65syZWLZsGQ4dOqRNgBYWFlAqlYUev2PHDly4cAG7du2Ck5MTGjZsiC+++AITJkzA1KlTYWpqWuRYWAIlIpIijUa0Ta1WIzMzU2dTq9WvDSE/Px8//fQTsrOz4evrq21fv3497O3tUb9+fURFReHJkyfafYmJiWjQoAGcnJy0bUFBQcjMzMT58+f1+gqYAImI6I3ExMTAxsZGZ4uJiXlp/7Nnz8LKygoKhQLDhg3D1q1b4enpCQDo06cP1q1bh7179yIqKgpr165Fv379tMeqVCqd5AdA+1qlUukVN0ugRERSJAiiDRUVFYWIiAidNoVC8dL+derUwalTp5CRkYEtW7YgLCwMCQkJ8PT0xJAhQ7T9GjRoAGdnZ7Rp0wYpKSmoWbOmaDEDTIBERNIk4jlAhULxyoT3X6ampnB3dwcAeHt74+jRo1i4cCG+/fbbAn19fHwAAMnJyahZsyaUSiWOHDmi0yctLQ0AXnre8GVYAiUiIoPS/P/ziIU5deoUAMDZ2RkA4Ovri7NnzyI9PV3bZ+fOnbC2ttaWUYuKM0AiIiky0CrQqKgodOjQAdWqVcPjx4+xYcMGxMfHIy4uDikpKdiwYQM6duyISpUq4cyZMxg7diz8/Pzg5eUFAGjXrh08PT0RGhqKr776CiqVCpMmTUJ4eLhes1CACZCISJoMdC/Q9PR09O/fH6mpqbCxsYGXlxfi4uLQtm1b3Lx5E7t27cKCBQuQnZ2NqlWrIiQkBJMmTdIeb2RkhNjYWAwfPhy+vr6wtLREWFiYznWDRSUTBBHPhJYRuff+MXQIJBEpzUYaOgSSCI/Lf4o63tN1n4s2lnm/maKNVZo4AyQikiLeC5QJkIhIkt6+4p/euAqUiIgkiTNAIiIpYgmUCZCISJKYAFkCJSIiaeIMkIhIigx0HWBZwgRIRCRBgoarQFkCJSIiSeIMkIhIirgIhgmQiEiSeA6QJVAiIpImzgCJiKSIi2CYAImIJInnAFkCJSIiaeIMkIhIijgDZAIkIpIkPg6JJVAiIpImzgCJiKSIJVAmQKn4Ye0mLFi+Ev16dMbEMcMAAJt//RN/7IzHxaRkZD95ioPbN8O6glWhx+fk5ODDwWORlPwPtqz8Bh61a5Zm+FTG2Q3tiQrtmsHUrQoEdQ6enryIu3NWIOfqbW0fp+kjYdmsEYwd7aB58gxPT1zA3bkrkfPPLW0fC993YD86FIra1SE8fYaMrbtxd/5qIJ9/rEXHyyBYApWCsxeTsPnXP1Hb3U2n/dkzNVr4NMbg/r1fO8bXS1fA0d6upEKkcs7ivfp4tC4W13tG4ObAzyEzNkLVFTMhM1do+zw7n4zUifNxtcNQ3PxoEiCToeqKGYD83z9DCg83VPl+OrL3H8e1LqNwe8wsWLXxgUPkQEN9LHrLMQG+5Z48eYqJ0+Zg6oTRBWZ3ob264uPQnvCq5/HKMfYnHsXBIycQOfLjkgyVyrFbH0cjY+su5CTfgPrSVaROmAeTyo4wq1dL2yfj5+14euwccm+nQ30hBfcWrIGJiyNMKjsCACp09IM66SruL9mI3BupeHr0HO5+tQIV+74PuaW5oT7a20vQiLeVUwYtgd67dw8rVqxAYmIiVCoVAECpVKJZs2YYMGAAHBwcDBneW2HG10vg5/sefN9rhG9Xb9T7+HsPHmLq7IVYGBMNMzOzEoiQ3kbyCpYAgPyMx4Xul5krYNOtLXJupiJXde/fY0xNIKhzdPpp1DmQmylgVs8dT46cLdmgpYYlUMPNAI8ePYratWtj0aJFsLGxgZ+fH/z8/GBjY4NFixbBw8MDx44de+04arUamZmZOptarS6FT1D2/bkrHhcvp2DMsOKVkARBwKSZ89CzSzDq160tcnT01pLJ4PT5UDw5fh45V67r7LLtE4zaJ/+HOqe3wtK/MW4O+BzIzQMAZO0/DvNGdVEh2B+Qy2HsVAn24X0AAEYOLL+T+Aw2Axw1ahR69OiB5cuXQyaT6ewTBAHDhg3DqFGjkJiY+MpxYmJiMG3aNJ22SeM+QfT40aLHXJ6kpt3FrAXf4vsFX0KhMC3WGOu3/IbsJ0/wcWhPkaOjt5nTlBFQ1HLF9Q8jC+zL/G0vsv8+CWMHO9gN6obKC6NwvXckhJxcPPn7JNK/WgHl9JFwmfNv272lG2HxXn1es1YCBK4ChUwQDPObZW5ujpMnT8LDo/DzT5cuXUKjRo3w9OnTV46jVqsLzPjkj29DoVC85Ahp2L3vIEZHfQEjo/+b5OfnayCTySCXy3Bi728wMjICABw5cQYfjZpQYBXoJxOnI/7vw3jx3yf5+RoYGckR3LYVvpxc8A+c1KQ0G2noEMoUp+jhsGrTFDf6jkfurbRXdzYxRu2jm5D6+UI8/iNBZ5exox3yM7JgUsUJNf76FtdCRuPZ2SslGHnZ53H5T1HHy57ZX7SxLD9fI9pYpclgM0ClUokjR468NAEeOXIETk5Orx1HoVAUSHa5OfdEibE8a+rdEFvXLtNpmzRzHtxcq2JQvx7a5PcqUWOGYdSQ//s/Sfrd+xgaMQlzp0WhQb06osdM5ZtT9HBYtfXFjX4TX5/8AMj+/3/JTU0K7MtLfwAAsA72R+6ddDw7nyJytEQGTICRkZEYMmQIjh8/jjZt2miTXVpaGnbv3o3vv/8ec+fONVR45Z6lpQVq1aiu02ZubgZb6wra9nv3H+De/Ye4cesOAOBKyjVYWpjDWekIG+sKcFY66hxvYf7vSryqlZ2hdOQCJfo/TlNGwLpTAG4Nnw5N9lMY2VcEAGgeZ0NQ58CkqhIVOvoh+8AJ5D/IgInSHnZDekB4loOshKPacewGhSB7/3EIGg0qtGuOSkN64PaYWbxouySU49WbYjFYAgwPD4e9vT3mz5+PpUuXIj8/HwBgZGQEb29vrFq1Cj178txTSfp5259YtmK99nVY+DgAwIzPItAluK2hwqJyqGLf9wEAruu/0mlPnTAPGVt3QVDnwKJxPdiFdYaRtRXy7j/Ck6PncL33p8h/kKHtb+nXGJWG94LM1ATqS1dxa8QXyN73+sVwVAxcBWq4c4Avys3Nxb17/5Yt7e3tYWJSsCSi13j3/hEjLKLX4jlAKi2inwOc3le0sSyj17++UxlUJm6FZmJiAmdnZ0OHQUQkHSwrl40ESEREpYwlUN4KjYiIpIkzQCIiKeIqUCZAIiJJYgmUJVAiIpImzgCJiCSI9wLlDJCIiCSKM0AiIiniOUAmQCIiSWICZAmUiIhKz7Jly+Dl5QVra2tYW1vD19cXf/31l3b/s2fPEB4ejkqVKsHKygohISFIS9N9usiNGzcQHBwMCwsLODo6Yty4ccjLy9M7FiZAIiIpEjTibXqoUqUKZs2ahePHj+PYsWNo3bo1OnfujPPnzwMAxo4di99//x2bN29GQkIC7ty5g27dummPz8/PR3BwMHJycnDw4EGsXr0aq1atQnR0tN5fQZm4GbbYeDNsKi28GTaVFrFvhp0V8YFoY1nN++2Njrezs8OcOXPQvXt3ODg4YMOGDejevTuAfx+OXrduXSQmJqJp06b466+/8P777+POnTvax+gtX74cEyZMwN27d2Fqalrk9+UMkIiI3oharUZmZqbOplarX3tcfn4+fvrpJ2RnZ8PX1xfHjx9Hbm4uAgMDtX08PDxQrVo1JCYmAgASExPRoEEDnQemBwUFITMzUzuLLComQCIiCRI0gmhbTEwMbGxsdLaYmJiXvvfZs2dhZWUFhUKBYcOGYevWrfD09IRKpYKpqSlsbW11+js5OUGlUgEAVCqVTvJ7vv/5Pn1wFSgRkRSJuAo0KioKEREROm0KheKl/evUqYNTp04hIyMDW7ZsQVhYGBISEkSLp6iYAImI6I0oFIpXJrz/MjU1hbu7OwDA29sbR48excKFC9GrVy/k5OTg0aNHOrPAtLQ0KJVKAIBSqcSRI0d0xnu+SvR5n6JiCZSISIo0GvG2Nw5FA7VaDW9vb5iYmGD37t3afUlJSbhx4wZ8fX0BAL6+vjh79izS09O1fXbu3Alra2t4enrq9b6cARIRSZGBLoSPiopChw4dUK1aNTx+/BgbNmxAfHw84uLiYGNjg0GDBiEiIgJ2dnawtrbGqFGj4Ovri6ZNmwIA2rVrB09PT4SGhuKrr76CSqXCpEmTEB4ertcsFGACJCKiUpSeno7+/fsjNTUVNjY28PLyQlxcHNq2bQsAmD9/PuRyOUJCQqBWqxEUFISlS5dqjzcyMkJsbCyGDx8OX19fWFpaIiwsDNOnT9c7Fl4HSPQGeB0glRaxrwN8PKy9aGNVWL5dtLFKE2eAREQS9BbOffTGRTBERCRJnAESEUkRnwbBBEhEJElMgCyBEhGRNHEGSEQkQQJngPrPADMzM1+6Lzk5+Y2CISKiUqIRxNvKKb0TYHBwcKGPuUhKSkJAQIAYMREREZU4vROglZUVunbtqvP4+YsXLyIgIAAhISGiBkdERCVEI+JWTumdAH/55RdkZGSgb9++EAQB586dQ0BAAD788EMsXLiwJGIkIiKRifk8wPJK7wRobm6OP/74A0lJSejZsyfatGmD/v37Y968eSURHxERUYko0irQ/y58kcvl+Pnnn9G2bVuEhIRg8uTJ2j7W1tbiR0lEROIqxzM3sRQpAdra2kImkxVoFwQBy5cvx7fffgtBECCTyZCfny96kEREJLJyfO5OLEVKgHv37i3pOIiIiEpVkRKgv79/ScdBRESlqDwvXhFLkRLgmTNnUL9+fcjlcpw5c+aVfb28vEQJjIiIShBLoEVLgA0bNoRKpYKjoyMaNmwImUxW6LOkeA6QiIjKiyIlwKtXr8LBwUH7MxERlW8sgRYxAbq6uhb6MxERlVMsgRbvaRBXrlzB3r17kZ6eDo1G91uMjo4WJTAiIqKSpHcC/P777zF8+HDY29tDqVTqXB8ok8mYAImIygGBM0D9E+CMGTMwc+ZMTJgwoSTiISKi0sAEqP+9QB8+fIgePXqURCxERESlRu8E2KNHD+zYsaMkYiEiolIiaMTbyiu9S6Du7u6YPHkyDh06hAYNGsDExERn/yeffCJacEREVELKceISi0wo7Ir2V3Bzc3v5YDIZ/vnnnzcO6k3l3jN8DCQNKc1GGjoEkgiPy3+KOt69IPFucWkflyDaWKVJ7xkgL4QnIir/ynPpUix6nwPkkyGIiMo/ngMsRgJs3749atasiRkzZuDmzZslERMREVGJ0zsB3r59GyNHjsSWLVtQo0YNBAUFYdOmTcjJySmJ+IiIqARwBliMBGhvb4+xY8fi1KlTOHz4MGrXro0RI0bAxcUFn3zyCU6fPl0ScRIRkZgEmXhbOaV3AnzRu+++i6ioKIwcORJZWVlYsWIFvL290bJlS5w/f16sGImIiERXrASYm5uLLVu2oGPHjnB1dUVcXBy++eYbpKWlITk5Ga6urrxbDBFRGcYSaDEugxg1ahQ2btwIQRAQGhqKr776CvXr19fut7S0xNy5c+Hi4iJqoEREJB5BU35Ll2LROwFeuHABixcvRrdu3aBQKArtY29vz8sliIioTNM7Ae7evfv1gxobw99fvLsMEBGRuMpz6VIseidAV1dX+Pv7w9/fHwEBAahZs2ZJxEVERCVIKMerN8Wi9yKYmTNnwszMDLNnz0atWrVQtWpV9OvXD99//z2uXLlSEjESERGJTu8ZYL9+/dCvXz8AQGpqKhISEhAbG4sRI0ZAo9EgPz9f9CCJiEhcLIEWIwECwJMnT3DgwAHEx8dj7969OHnyJOrXr4+AgACRwyMiopLAVaDFKIE2a9YMlSpVwsSJE/Hs2TNMnDgRqampOHnyJObPn18SMRIR0VsiJiYG7733HipUqABHR0d06dIFSUlJOn0CAgIgk8l0tmHDhun0uXHjBoKDg2FhYQFHR0eMGzcOeXl5esWi9wzw0qVLsLS0hIeHBzw8PFC3bl1UrFhR32GIiMiA9HsSrHgSEhIQHh6O9957D3l5efjss8/Qrl07XLhwAZaWltp+gwcPxvTp07WvLSwstD/n5+cjODgYSqUSBw8eRGpqKvr37w8TExN8+eWXRY5F7wR4//59nD17FvHx8YiLi8Pnn38OU1NT+Pv7o1WrVhg8eLC+QxIRUSkzVAl0+/btOq9XrVoFR0dHHD9+HH5+ftp2CwsLKJXKQsfYsWMHLly4gF27dsHJyQkNGzbEF198gQkTJmDq1KkwNTUtUix6l0BlMhm8vLzwySefYMuWLfjrr7/Qtm1bbN68ucAUlYiI3n5qtRqZmZk6m1qtLtKxGRkZAAA7Ozud9vXr18Pe3h7169dHVFQUnjx5ot2XmJiIBg0awMnJSdsWFBSEzMxMve5DrfcM8MSJE4iPj0d8fDwOHDiAx48fo0GDBhg1ahQvficiKifEnAHGxMRg2rRpOm1TpkzB1KlTX3mcRqPBmDFj0Lx5c51bavbp0weurq5wcXHBmTNnMGHCBCQlJeGXX34BAKhUKp3kB0D7WqVSFTluvRNgkyZN0KhRI/j7+2Pw4MHw8/ODjY2NvsMQEZEBiXkOMCoqChERETptL7tV5ovCw8Nx7tw5HDhwQKd9yJAh2p8bNGgAZ2dntGnTBikpKaLefEXvBPjgwQNYW1uLFgAREZVvCoWiSAnvRSNHjkRsbCz27duHKlWqvLKvj48PACA5ORk1a9aEUqnEkSNHdPqkpaUBwEvPGxZG73OATH5EROWfoJGJtun1voKAkSNHYuvWrdizZw/c3Nxee8ypU6cAAM7OzgAAX19fnD17Funp6do+O3fuhLW1NTw9PYscS7EuhCciovLNUPcCDQ8Px4YNG/Drr7+iQoUK2nN2NjY2MDc3R0pKCjZs2ICOHTuiUqVKOHPmDMaOHQs/Pz94eXkBANq1awdPT0/tI/lUKhUmTZqE8PBwvWaib/REeCIiIn0sW7YMGRkZCAgIgLOzs3b7+eefAQCmpqbYtWsX2rVrBw8PD3z66acICQnB77//rh3DyMgIsbGxMDIygq+vL/r164f+/fvrXDdYFJwBEhFJkKHuBSq8ZvVN1apVkZCQ8NpxXF1d8eeff75RLHrPAPmgWyKi8k8jyETbyiu9E2D79u1Rs2ZNzJgxAzdv3iyJmIiIiEqc3gnw9u3bGDlyJLZs2YIaNWogKCgImzZtQk5OTknER0REJUAQZKJt5ZXeCdDe3h5jx47FqVOncPjwYdSuXRsjRoyAi4sLPvnkE5w+fbok4iQiIhEZ6jKIsuSNVoG+++67iIqKwsiRI5GVlYUVK1bA29sbLVu21Ot+bERERKWtWAkwNzcXW7ZsQceOHeHq6oq4uDh88803SEtLQ3JyMlxdXdGjRw+xYyUiIpEIgnhbeaX3ZRCjRo3Cxo0bIQiC9iLEF29iamlpiblz58LFxUXUQImISDzluXQpFr0T4IULF7B48WJ069btpVfc29vb83IJIiIq0/QugU6ZMgU9evQokPzy8vKwb98+AICxsTEfjUREVIbxOsBiJMBWrVrhwYMHBdozMjLQqlUrUYIiIqKSxcsgipEABUGATFbwA9+/fx+WlpaiBEVERFTSinwOsFu3bgAAmUyGAQMG6JRA8/PzcebMGTRr1kz8CImISHTlefWmWIqcAJ8/9V0QBFSoUAHm5ubafaampmjatCkGDx4sfoRERCS68nzuTixFToArV64EAFSvXh2RkZEsdxIRUbmm92UQ48eP13mcxfXr17F161Z4enqiXbt2ogZHREQlozwvXhGL3otgOnfujDVr1gAAHj16hCZNmuDrr79G586dsWzZMtEDJCIi8fFOMMVIgCdOnEDLli0BAFu2bIFSqcT169exZs0aLFq0SPQAiYiISoLeJdAnT56gQoUKAIAdO3agW7dukMvlaNq0Ka5fvy56gEREJD4ugilGAnR3d8e2bdvQtWtXxMXFYezYsQCA9PR0WFtbix5gcZi7tDR0CCQRtmZcDEal457I4/EcYDFKoNHR0YiMjET16tXh4+MDX19fAP/OBhs1aiR6gERERCVBJgj6n8JUqVRITU3FO++8A7n83xx65MgRWFtbw8PDQ/Qg9WVsWtnQIZBEcAZIpeVe5mVRxzvs0k20sXzu/CLaWKVJ7xIoACiVSiiVSp22Jk2aiBIQERGVvHK8eFM0RUqA3bp1w6pVq2Btba29JdrL/PJL+fyXABERSUuREqCNjY32BtjPb4lGRETlF1eBFvMcYFnHc4BUWngOkEqL2OcA/1Z2F22s5qotoo1VmvReBbpixQpcvXq1JGIhIiIqNXonwJiYGLi7u6NatWoIDQ3FDz/8gOTk5JKIjYiISohGxK280jsBXrlyBTdu3EBMTAwsLCwwd+5c1KlTB1WqVEG/fv1KIkYiIhKZAJloW3n1RucAnzx5gv3792Pjxo1Yv349BEFAXl6emPEVC88BUmnhOUAqLWKfA9yn7CHaWH6qzaKNVZr0vg5wx44diI+PR3x8PE6ePIm6devC398fW7ZsgZ+fX0nESEREItO8dcsf9ad3Amzfvj0cHBzw6aef4s8//4StrW0JhEVERCVJU45Ll2LR+xzgvHnz0Lx5c3z11VeoV68e+vTpg++++w6XL4s7PSciIipJb3QO8OzZs0hISMCePXsQGxsLR0dH3Lp1S8z4ioXnAKm08BwglRaxzwHuduol2lht0n4WbazSVKx7gQqCgJMnTyI+Ph579+7FgQMHoNFo4ODgIHZ8RERUAsrz5Qti0TsBdurUCX///TcyMzPxzjvvICAgAIMHD4afnx/PBxIRUbmhdwL08PDA0KFD0bJlS94XlIionCrP1++JRe8EOHz4cNSoUaMkYiEiolLCEmgxVoG6u7ujVatWWLduHZ49e1YSMREREZU4vRPgiRMn4OXlhYiICCiVSgwdOhRHjhwpidiIiKiE8F6gxUiADRs2xMKFC3Hnzh2sWLECqampaNGiBerXr4958+bh7t27JREnERGJiPcCLUYCfM7Y2BjdunXD5s2bMXv2bCQnJyMyMhJVq1ZF//79kZqaKmacRET0FoiJicF7772HChUqwNHREV26dEFSUpJOn2fPniE8PByVKlWClZUVQkJCkJaWptPnxo0bCA4OhoWFBRwdHTFu3Di970Vd7AR47NgxjBgxAs7Ozpg3bx4iIyORkpKCnTt34s6dO+jcuXNxhyYiohKmkYm36SMhIQHh4eE4dOgQdu7cidzcXLRr1w7Z2dnaPmPHjsXvv/+OzZs3IyEhAXfu3EG3bt20+/Pz8xEcHIycnBwcPHgQq1evxqpVqxAdHa1XLHrfCWbevHlYuXIlkpKS0LFjR3z88cfo2LEj5PL/y6W3bt1C9erVDfZkCN4JhkoL7wRDpUXsO8H8quwj2lidVRuKfezdu3fh6OiIhIQE+Pn5ISMjAw4ODtiwYQO6d//3qfWXLl1C3bp1kZiYiKZNm+Kvv/7C+++/jzt37sDJyQkAsHz5ckyYMAF3796Fqalpkd5b7xngsmXL0KdPH1y/fh3btm3D+++/r5P8AMDR0RE//vijvkMTEVE5pFarkZmZqbOp1eoiHZuRkQEAsLOzAwAcP34cubm5CAwM1Pbx8PBAtWrVkJiYCABITExEgwYNtMkPAIKCgpCZmYnz588XOe5iPRA3KioKzs7OL+1jamqKsLAwfYcmIqJSIoi4xcTEwMbGRmeLiYl5bQwajQZjxoxB8+bNUb9+fQCASqWCqalpgTuLOTk5QaVSafu8mPye73++r6j0ToA1atTAwIEDC2T3e/fu8QJ5IqJyQszLIKKiopCRkaGzRUVFvTaG8PBwnDt3Dj/99JPYH69I9E6A165dw99//42WLVvqZNr8/Hxcv35d1OCIiKjsUygUsLa21tkUCsUrjxk5ciRiY2Oxd+9eVKlSRduuVCqRk5ODR48e6fRPS0uDUqnU9vnvqtDnr5/3KQq9E6BMJsP27dtRpUoVeHt74+jRo/oOQUREBqaRyUTb9CEIAkaOHImtW7diz549cHNz09nv7e0NExMT7N69W9uWlJSEGzduwNfXFwDg6+uLs2fPIj09Xdtn586dsLa2hqenZ5Fj0TsBCoIAKysr/PLLL+jfvz/8/f2xbt06fYchIiIDEvMcoD7Cw8Oxbt06bNiwARUqVIBKpYJKpcLTp08BADY2Nhg0aBAiIiKwd+9eHD9+HAMHDoSvry+aNm0KAGjXrh08PT0RGhqK06dPIy4uDpMmTUJ4ePhrZ54v0vtm2LIXsn1MTAzq1auHwYMH48MPP9R3KCIikphly5YBAAICAnTaV65ciQEDBgAA5s+fD7lcjpCQEKjVagQFBWHp0qXavkZGRoiNjcXw4cPh6+sLS0tLhIWFYfr06XrFovd1gHK5HCqVCo6Ojtq2xMREdO3aFXfv3kV+fr5eAZQEXgdIpYXXAVJpEfs6wJ+d+4o2Vq/U9aKNVZr0ngFqNAVvferr64vTp0/j0qVLogRFREQlS987uLyN9D4HePXqVVy5cqVAe2ZmJlxdXUUJioiIqKTpnQAHDBiAgwcPFmg/fPiwtn5LRERlmwYy0bbySu8EePLkSTRv3rxAe9OmTXHq1CkxYiIiohJmqFWgZUmxrgN8/PhxgfaMjIwysQCGiIioKPROgH5+foiJidFJdvn5+YiJiUGLFi1EDY6IiEqGoR6HVJbovQp09uzZ8PPzQ506ddCyZUsAwP79+5GZmYk9e/aIHiAREYmv4Hp+6dF7Bujp6YkzZ86gZ8+eSE9Px+PHj9G/f39cunRJezdvIiKisk7vGSAAuLi44MsvvxQ7FiIiKiXlefGKWPSeAQL/ljz79euHZs2a4fbt2wCAtWvX4sCBA6IGR0REJYPnAIuRAP/3v/8hKCgI5ubmOHHihPa5gBkZGZwVEhFRuaF3ApwxYwaWL1+O77//HiYmJtr25s2b48SJE6IGR0REJUPMB+KWV3qfA0xKSoKfn1+BdhsbmwIPMCQiorKpPCcuseg9A1QqlUhOTi7QfuDAAdSoUUOUoIiIiEqa3glw8ODBGD16NA4fPgyZTIY7d+5g/fr1iIyMxPDhw0siRiIiEpkgE28rr/QugU6cOBEajQZt2rTBkydP4OfnB4VCgcjISIwaNaokYiQiIpGxBFqMB+I+l5OTg+TkZGRlZcHT0xNWVlZix1ZsfCAulRY+EJdKi9gPxF1atZ9oY424uU60sUqT3iXQNWvW4OLFizA1NYWnpyeaNGkCKysrPHv2DGvWrCmJGImISGRcBVrM5wE2adIE//vf/3TaMzIyMHDgQNECIyKiksPHIRXzTjDTpk1DaGgopk6dKnI4REREpaNY9wJ9fhu0rl274ty5c1i7dq3YcRERUQkqz7cwE0uxHogL/PsE+MOHDyM5ORnNmjXDtWvXxI6NiIhKCM8BFiMBvrhotFq1ajh48CCqV6+Otm3bihoYERFRSdI7AU6ZMkXnkgcLCwts3boVY8eOLfQWaUREVPZwBvgG1wEW5unTpzA3NxdruGLjdYBUWngdIJUWsa8DnFtNvOsAI29I5DrAwqjVasybNw9ubm5iDEdERFTiipwA1Wo1oqKi0LhxYzRr1gzbtm0DAKxcuRJubm6YP38+xo4dW1JxEhGRiPhAXD0ug4iOjsa3336LwMBAHDx4ED169MDAgQNx6NAhzJs3Dz169ICRkVFJxkpERCIpz+fuxFLkBLh582asWbMGH3zwAc6dOwcvLy/k5eXh9OnT2ksjiIiIyosiJ8Bbt27B29sbAFC/fn0oFAqMHTuWyY+IqBwqz7cwE0uRE2B+fj5MTU3/70Bj4zL1BAgiIio6DVNg0ROgIAgYMGAAFAoFAODZs2cYNmwYLC11l4H/8ssv4kZIRERUAoqcAMPCwnRe9+sn3jUkRERUurgIRo8EuHLlypKMg4iIShELoCJdCE9ERFTeFOtxSEREVL6xBMoESEQkSeX5Di5iYQmUiIgkiTNAIiIJ4nWATIBERJLE9McSKBERlaJ9+/ahU6dOcHFxgUwm0z5Z6LkBAwZAJpPpbO3bt9fp8+DBA/Tt2xfW1tawtbXFoEGDkJWVpXcsTIBERBJkqCfCZ2dn45133sGSJUte2qd9+/ZITU3Vbhs3btTZ37dvX5w/fx47d+5EbGws9u3bhyFDhugZCUugRESSZKhzgB06dECHDh1e2UehUECpVBa67+LFi9i+fTuOHj2Kxo0bAwAWL16Mjh07Yu7cuXBxcSlyLJwBEhHRG1Gr1cjMzNTZ1Gp1sceLj4+Ho6Mj6tSpg+HDh+P+/fvafYmJibC1tdUmPwAIDAyEXC7H4cOH9XofJkAiIgkSRNxiYmJgY2Ojs8XExBQrrvbt22PNmjXYvXs3Zs+ejYSEBHTo0AH5+fkAAJVKBUdHR51jjI2NYWdnB5VKpdd7sQRKRCRBYt4JJioqChERETptz58cpK/evXtrf27QoAG8vLxQs2ZNxMfHo02bNm8U539xBkhERG9EoVDA2tpaZytuAvyvGjVqwN7eHsnJyQAApVKJ9PR0nT55eXl48ODBS88bvgwTIBGRBGkgiLaVpFu3buH+/ftwdnYGAPj6+uLRo0c4fvy4ts+ePXug0Wjg4+Oj19gsgRIRSZChLoTPysrSzuYA4OrVqzh16hTs7OxgZ2eHadOmISQkBEqlEikpKRg/fjzc3d0RFBQEAKhbty7at2+PwYMHY/ny5cjNzcXIkSPRu3dvvVaAApwBEhFRKTp27BgaNWqERo0aAQAiIiLQqFEjREdHw8jICGfOnMEHH3yA2rVrY9CgQfD29sb+/ft1Sqrr16+Hh4cH2rRpg44dO6JFixb47rvv9I5FJgjCW3dHHGPTyoYOgSTC1szS0CGQRNzLvCzqeKOr9359pyJaeO0n0cYqTSyBEhFJkMC7gbIESkRE0sQZIBGRBPGJ8EyARESSxOcBsgRKREQSxRkgEZEEcf7HBEhEJEksgbIEKilDh/THieM78eDeJTy4dwkH9v2G9kGtdPo09fHGzrhNyHh4BQ/uXcLe3f+DmZmZgSKm8mp81Cjcy7yssyUe267d/+sfawvsnzt/mgEjJiniDFBCbt9Oxeefx+BK8lXIZDL0D+2BX/63Ao2bBOHChcto6uONP2LXYfZX32D02EnIy8uHl5cnNBquFyP9XbxwGSEfDNC+zsvL19m/ZuXPmDVzofb1k6dPSys0AleBAkyAkhL7x06d15OjZ2PokFD4NHkXFy5cxtdzp+KbJSvw1Zwl2j6XL6eUdpj0lsjLy0d6+r2X7n/y9Okr91PJ4oXwLIFKllwuR8+eH8DS0gKHDh+Hg0Ml+Pi8i/T0e9if8Ctu3zyFPbu2oHmz9wwdKpVTNWq64lzSfhw7vRvLf5iLylWcdfZ37/kBkq4exv5DsZg05VOYm7PUTqWr3M8A1Wo11Gq1TpsgCJDJZAaKqGyrX98DB/b9BjMzBbKystG9x8e4ePEKfJq8CwCInvwpxk+YjtNnziO0bw/siPsZ7zRqg+TkqwaOnMqT48dOY9TwiUi+chVOSgeMmzgSsds3oGXT95GVlY3/bY7FzZu3oUpNR736dRA9bRzca7lhQL+Rhg5dMlgCLeMJ8ObNm5gyZQpWrFjx0j4xMTGYNk335LlMbgWZkXVJh1cuJSWlwPu9drCxroCQkGCs+HEBWgeGQC7/txjw/Q/rsHrNJgDAqVPn0ap1cwwc0AufT5plyLCpnNm9c5/25wvnk3D82GmcOhePzl07YP3aLViz6mft/osXLiNNdRdbY9egultVXLt60xAhSw5LoGW8BPrgwQOsXr36lX2ioqKQkZGhs8nkFUopwvInNzcXKSnXcOLkWXw+aRbOnLmAUSM/RqoqDQBw4aLuHecvXUpG1ap8uga9mcyMx0hJuQa3Gq6F7j9+7DQAvHQ/UUkw6Azwt99+e+X+f/7557VjKBQKnedEAWD5Uw9yuRwKhSmuXbuJ27dTUad2TZ39tWrVQFzcXgNFR28LS0sLVHerik0/pRe6v36DugCANNXd0gxL0lgCNXAC7NKlC2QyGV71SEImM/HMnDER27fvxY2bt1GhghU+7N0F/v6+6BjcBwDw9bzlmBL9KU6fuYDTp8+jf2gPeNSpiV69hxg4cipvps2YgLi/9uDmzTtQKh0x4bNPkJ+vwS+bY1HdrSpCenTCrh0JePDgEerVq4MvZn2GgweO4ML5JEOHLhmat+9RsHozaAJ0dnbG0qVL0blz50L3nzp1Ct7e3qUc1dvLwcEeK1cshLOzIzIyHuPs2YvoGNwHu3bvBwAsWvwDzMwU+HrOVNjZ2eLMmQto3+FD/PPPdQNHTuWNS2UlvlsxDxXtKuL+vQc4fOg42rfpgfv3H0JhpoB/QDMMHREGCwsL3Lmdithf4/D1nKWGDpskxqBPhP/ggw/QsGFDTJ8+vdD9p0+fRqNGjfS+EJtPhKfSwifCU2kR+4nw/Vy7iTbWuuu/iDZWaTLoDHDcuHHIzs5+6X53d3fs3cvzT0REYuO9QA2cAFu2bPnK/ZaWlvD39y+laIiISErK9HWARERUMngdIBMgEZEk8TKIMn4hPBERUUnhDJCISIK4CIYzQCIikijOAImIJIiLYJgAiYgkiYtgWAIlIiKJ4gyQiEiCDHgXzDKDCZCISIK4CpQlUCIikijOAImIJIiLYJgAiYgkiZdBsARKREQSxRkgEZEEcREMEyARkSTxMgiWQImISKI4AyQikiCuAmUCJCKSJK4CZQmUiIgkigmQiEiCNBBE2/Sxb98+dOrUCS4uLpDJZNi2bZvOfkEQEB0dDWdnZ5ibmyMwMBBXrlzR6fPgwQP07dsX1tbWsLW1xaBBg5CVlaX3d8AESEQkQYIgiLbpIzs7G++88w6WLFlS6P6vvvoKixYtwvLly3H48GFYWloiKCgIz5490/bp27cvzp8/j507dyI2Nhb79u3DkCFD9P4OZMJbuBbW2LSyoUMgibA1szR0CCQR9zIvizpemyrtRBtr960dxTpOJpNh69at6NKlC4B/k7KLiws+/fRTREZGAgAyMjLg5OSEVatWoXfv3rh48SI8PT1x9OhRNG7cGACwfft2dOzYEbdu3YKLi0uR358zQCIiCRKzBKpWq5GZmamzqdVqvWO6evUqVCoVAgMDtW02Njbw8fFBYmIiACAxMRG2trba5AcAgYGBkMvlOHz4sF7vxwRIRCRBgoj/iYmJgY2Njc4WExOjd0wqlQoA4OTkpNPu5OSk3adSqeDo6Kiz39jYGHZ2dto+RcXLIIiI6I1ERUUhIiJCp02hUBgomqJjAiQikiCNiMs/FAqFKAlPqVQCANLS0uDs7KxtT0tLQ8OGDbV90tPTdY7Ly8vDgwcPtMcXFUugREQSJIi4icXNzQ1KpRK7d+/WtmVmZuLw4cPw9fUFAPj6+uLRo0c4fvy4ts+ePXug0Wjg4+Oj1/txBkhERKUmKysLycnJ2tdXr17FqVOnYGdnh2rVqmHMmDGYMWMGatWqBTc3N0yePBkuLi7alaJ169ZF+/btMXjwYCxfvhy5ubkYOXIkevfurdcKUIAJkIhIkgz1OKRjx46hVatW2tfPzx2GhYVh1apVGD9+PLKzszFkyBA8evQILVq0wPbt22FmZqY9Zv369Rg5ciTatGkDuVyOkJAQLFq0SO9YeB0g0RvgdYBUWsS+DtC3cqvXdyqixNt7RRurNPEcIBERSRJLoEREEvQWFv/0xgRIRCRBhjoHWJawBEpERJLEGSARkQTxgbhMgEREksRzgCyBEhGRRHEGSEQkQVwEwwRIRCRJLIGyBEpERBLFGSARkQSxBMoESEQkSbwMgiVQIiKSKM4AiYgkSMwnwpdXTIBERBLEEihLoEREJFGcARIRSRBLoEyARESSxBIoS6BERCRRnAESEUkQS6BMgEREksQSKEugREQkUZwBEhFJEEugTIBERJLEEihLoEREJFGcARIRSZAgaAwdgsExARIRSRCfB8gSKBERSRRngEREEiRwFSgTIBGRFLEEyhIoERFJFGeAREQSxBIoEyARkSTxTjAsgRIRkURxBkhEJEG8FRoTIBGRJPEcIEugREQkUZwBEhFJEK8DZAIkIpIklkBZAiUiIoliAiQikiCNIIi26WPq1KmQyWQ6m4eHh3b/s2fPEB4ejkqVKsHKygohISFIS0sT++MDYAIkIpIkQRBE2/RVr149pKamarcDBw5o940dOxa///47Nm/ejISEBNy5cwfdunUT86Nr8RwgERG9EbVaDbVardOmUCigUCgK7W9sbAylUlmgPSMjAz/++CM2bNiA1q1bAwBWrlyJunXr4tChQ2jatKmocXMGSEQkQRoIom0xMTGwsbHR2WJiYl763leuXIGLiwtq1KiBvn374saNGwCA48ePIzc3F4GBgdq+Hh4eqFatGhITE0X/DjgDJCKSIDFXgUZFRSEiIkKn7WWzPx8fH6xatQp16tRBamoqpk2bhpYtW+LcuXNQqVQwNTWFra2tzjFOTk5QqVSixfscEyAREb2RV5U7/6tDhw7an728vODj4wNXV1ds2rQJ5ubmJRVioVgCJSKSIEOtAv0vW1tb1K5dG8nJyVAqlcjJycGjR490+qSlpRV6zvBNMQESEUmQIOJ/3kRWVhZSUlLg7OwMb29vmJiYYPfu3dr9SUlJuHHjBnx9fd/0IxfAEigREZWayMhIdOrUCa6urrhz5w6mTJkCIyMjfPjhh7CxscGgQYMQEREBOzs7WFtbY9SoUfD19RV9BSjABEhEJEmGeiDurVu38OGHH+L+/ftwcHBAixYtcOjQITg4OAAA5s+fD7lcjpCQEKjVagQFBWHp0qUlEotMeAtvCGdsWtnQIZBE2JpZGjoEkoh7mZdFHc/MrJpoYz17dkO0sUoTzwESEZEksQRKRCRBfCI8EyARkSS9hWe/9MYSKBERSRJngEREEsQZIBMgEZEkMf2xBEpERBL1Vl4HSPpTq9WIiYlBVFRUkW9qS1Qc/F2jsoIJkAAAmZmZsLGxQUZGBqytrQ0dDr3F+LtGZQVLoEREJElMgEREJElMgEREJElMgATg3yc6T5kyhYsSqMTxd43KCi6CISIiSeIMkIiIJIkJkIiIJIkJkIiIJIkJkIiIJIkJkLBkyRJUr14dZmZm8PHxwZEjRwwdEr2F9u3bh06dOsHFxQUymQzbtm0zdEgkcUyAEvfzzz8jIiICU6ZMwYkTJ/DOO+8gKCgI6enphg6N3jLZ2dl45513sGTJEkOHQgSAl0FIno+PD9577z188803AACNRoOqVati1KhRmDhxooGjo7eVTCbD1q1b0aVLF0OHQhLGGaCE5eTk4Pjx4wgMDNS2yeVyBAYGIjEx0YCRERGVPCZACbt37x7y8/Ph5OSk0+7k5ASVSmWgqIiISgcTIBERSRIToITZ29vDyMgIaWlpOu1paWlQKpUGioqIqHQwAUqYqakpvL29sXv3bm2bRqPB7t274evra8DIiIhKnrGhAyDDioiIQFhYGBo3bowmTZpgwYIFyM7OxsCBAw0dGr1lsrKykJycrH199epVnDp1CnZ2dqhWrZoBIyOp4mUQhG+++QZz5syBSqVCw4YNsWjRIvj4+Bg6LHrLxMfHo1WrVgXaw8LCsGrVqtIPiCSPCZCIiCSJ5wCJiEiSmACJiEiSmACJiEiSmACJiEiSmACJiEiSmACJiEiSmACJiEiSmACJiEiSmADprTBgwIDXPlw1ICAAY8aMKZV43mbVq1fHggULtK9lMhm2bdtmsHiIiov3AqXXGjBgAFavXg0AMDExQbVq1dC/f3989tlnMDYuG79CCxcuBG9qVDqOHj0KS0tLQ4dB9MbKxl8vKvPat2+PlStXQq1W488//0R4eDhMTEwQFRVVoG9OTg5MTU1LNT4bG5tSfT8pc3BwMHQIRKJgCZSKRKFQQKlUwtXVFcOHD0dgYCB+++03AP9Xfpw5cyZcXFxQp04dxMfHQyaTFdgGDBigHfPXX3/Fu+++CzMzM9SoUQPTpk1DXl4eACAyMhLvv/++tu+CBQsgk8mwfft2bZu7uzt++OEHnRiey87ORv/+/WFlZQVnZ2d8/fXXOp9n+vTpqF+/foHP2bBhQ0yePBnnzp2DXC7H3bt3AQAPHjyAXC5H7969tX1nzJiBFi1aAADy8/MxaNAguLm5wdzcHHXq1MHChQt1xn4e49y5c+Hs7IxKlSohPDwcubm5RYqpMI0bN8bcuXO1r7t06QITExNkZWUBAG7dugWZTIbk5OQijf+6GIGCJdD/mjJlCpydnXHmzJmX9iEqC5gAqVjMzc2Rk5Ojfb17924kJSVh586diI2NRbNmzZCamqrd9uzZAzMzM/j5+QEA9u/fj/79+2P06NG4cOECvv32W6xatQozZ84EAPj7++PAgQPIz88HACQkJMDe3h7x8fEAgNu3byMlJQUBAQGFxjdu3DgkJCTg119/xY4dOxAfH48TJ05o93/00Ue4ePEijh49qm07efIkzpw5g4EDB6JevXqoVKkSEhIStPG++Pp5TM/fX6PRoEqVKti8eTMuXLiA6OhofPbZZ9i0aZNOXHv37kVKSgr27t2L1atXY9WqVdonIbwupsL4+/trvxNBELB//37Y2triwIED2hgrV64Md3f3Io//qhhfRRAEjBo1CmvWrMH+/fvh5eX12mOIDEogeo2wsDChc+fOgiAIgkajEXbu3CkoFAohMjJSu9/JyUlQq9WFHn/v3j2hRo0awogRI7Rtbdq0Eb788kudfmvXrhWcnZ0FQRCEhw8fCnK5XDh69Kig0WgEOzs7ISYmRvDx8REEQRDWrVsnVK5cudAYHz9+LJiamgqbNm3S7r9//75gbm4ujB49WtvWoUMHYfjw4drXo0aNEgICArSvu3XrJoSHhwuCIAhjxowRxo0bJ1SsWFG4ePGikJOTI1hYWAg7dux46fcWHh4uhISE6MTo6uoq5OXladt69Ogh9OrVq8gx/ddvv/0m2NjYCHl5ecKpU6cEpVIpjB49WpgwYYIgCILw8ccfC3369Cny+EWJ0dXVVZg/f772NQBh8+bNQp8+fYS6desKt27demm8RGUJZ4BUJLGxsbCysoKZmRk6dOiAXr16YerUqdr9DRo0KPS8X25uLkJCQuDq6qpTEjx9+jSmT58OKysr7TZ48GCkpqbiyZMnsLW1xTvvvIP4+HicPXsWpqamGDJkCE6ePImsrCwkJCTA39+/0FhTUlKQk5Oj80xDOzs71KlTR6ff4MGDsXHjRjx79gw5OTnYsGEDPvroI+3+F2dXCQkJaN26Nfz8/BAfH4+jR48iNzcXzZs31/ZfsmQJvL294eDgACsrK3z33Xe4ceOGznvWq1cPRkZG2tfOzs5IT08vckz/1bJlSzx+/BgnT57UficBAQE6cb84Sy7K+K+LsTBjx47F4cOHsW/fPlSuXPmVfYnKCi6CoSJp1aoVli1bBlNTU7i4uBRY/fmyVYHDhw/HzZs3ceTIEZ1jsrKyMG3aNHTr1q3AMWZmZgCg/UOuUCjg7+8POzs71K1bFwcOHEBCQgI+/fTTN/pMnTp1gkKhwNatW2Fqaorc3Fx0795du//5ZRNXrlzBhQsX0KJFC1y6dAnx8fF4+PAhGjduDAsLCwDATz/9hMjISHz99dfw9fVFhQoVMGfOHBw+fFjnPU1MTHRey2QyaDSaIsf0Xy/+QyExMRFt27aFn58fevXqhcuXL+PKlSs6/1Aoyvivi7Ewbdu2xcaNGxEXF4e+ffu+si9RWcEESEViaWkJd3d3vY6ZN28eNm3ahIMHD6JSpUo6+959910kJSW9ckx/f3+sWLECxsbGaN++PYB/k9LGjRtx+fLll57/q1mzJkxMTHD48GFUq1YNAPDw4UNcvnxZJxkYGxsjLCwMK1euhKmpKXr37g1zc3Pt/gYNGqBixYqYMWMGGjZsCCsrKwQEBGD27Nl4+PChzvv//fffaNasGUaMGKFtS0lJKfJ3VdSYCuPv74+9e/fiyJEjmDlzpvYfCjNnzoSzszNq1679RuMXxQcffIBOnTqhT58+MDIy0lksRFRWMQFSidi1axfGjx+PJUuWwN7eHiqVCsC/i2dsbGwQHR2N999/H9WqVUP37t0hl8tx+vRpnDt3DjNmzAAA+Pn54fHjx4iNjcWsWbMA/JsAu3fvXuAP+4usrKwwaNAgjBs3DpUqVYKjoyM+//xzyOUFK/4ff/wx6tatC+DfJPYimUwGPz8/rF+/HpGRkQAALy8vqNVq7N69GxEREdq+tWrVwpo1axAXFwc3NzesXbsWR48ehZubm97f3atiKkxAQAAWL14MBwcHeHh4aNu++eYb9OjR443HL6quXbti7dq1CA0NhbGx8StnrkRlAc8BUol4voJz2LBhcHZ21m6jR48GAAQFBSE2NhY7duzAe++9h6ZNm2L+/PlwdXXVjlGxYkU0aNBA5w+7n58fNBrNS8//PTdnzhy0bNkSnTp1QmBgIFq0aAFvb+8C/WrVqoVmzZrBw8ND55zhc/7+/sjPz9fO9uRyOfz8/CCTyXTO/w0dOhTdunVDr1694OPjg/v37+vMBvXxupj+q2XLlgW+k4CAAJ2432R8fXTv3h2rV69GaGgofvnlF1HHJhKbTBB4+wySLkEQUKtWLYwYMUJnRmdIJR1TWfzMRIbAEihJ1t27d/HTTz9BpVK99Dq70lbSMZXFz0xkKEyAJFmOjo6wt7fHd999h4oVKxo6HAAlH1NZ/MxEhsISKBERSRIXwRARkSQxARIRkSQxARIRkSQxARIRkSQxARIRkSQxARIRkSQxARIRkSQxARIRkST9P6p+u8HdsodfAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_other_svc, Y_pred_other_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "c3733e8d63cf6527",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.6191962708042341"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_other_svc, Y_pred_other_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "26a3907adbfdeef9",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.83      0.65      0.73       576\n",
      "           1       0.32      0.56      0.40       168\n",
      "\n",
      "    accuracy                           0.63       744\n",
      "   macro avg       0.58      0.60      0.57       744\n",
      "weighted avg       0.72      0.63      0.66       744\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_other_rf, Y_pred_other_rf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "9cddb621d232ddad",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.603546626984127"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_other_rf, Y_pred_other_rf)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14d10ab08744c643",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Eksperymenty dla matches_rolling bez kolumn _rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "8bbd3ce96782141f",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X_norolling = matches_rolling[[\n",
    "    \"venue_code\",\n",
    "    \"opponent_code\",\n",
    "    \"referee_code\",\n",
    "    \"day_code\"\n",
    "]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "211dc10f388e5fef",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.084064Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Y_test_norolling_svc, Y_pred_norolling_svc, clf_norolling = creating_svc_model(X_norolling, Y_other)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "6919dcc7bd6e8946",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.086581Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py:540: FitFailedWarning: \n",
      "405 fits failed out of a total of 1215.\n",
      "The score on these train-test partitions for these parameters will be set to nan.\n",
      "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n",
      "\n",
      "Below are more details about the failures:\n",
      "--------------------------------------------------------------------------------\n",
      "405 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_validation.py\", line 888, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 1466, in wrapper\n",
      "    estimator._validate_params()\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\base.py\", line 666, in _validate_params\n",
      "    validate_parameter_constraints(\n",
      "  File \"c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\utils\\_param_validation.py\", line 95, in validate_parameter_constraints\n",
      "    raise InvalidParameterError(\n",
      "sklearn.utils._param_validation.InvalidParameterError: The 'max_features' parameter of RandomForestClassifier must be an int in the range [1, inf), a float in the range (0.0, 1.0], a str among {'sqrt', 'log2'} or None. Got 'auto' instead.\n",
      "\n",
      "  warnings.warn(some_fits_failed_message, FitFailedWarning)\n",
      "c:\\Users\\oleks\\OneDrive\\Pulpit\\coding\\msid-project\\.venv\\Lib\\site-packages\\sklearn\\model_selection\\_search.py:1052: UserWarning: One or more of the test scores are non-finite: [       nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.13155246 0.14873835 0.14786888\n",
      " 0.13500444 0.15132455 0.1444354  0.13755735 0.14960411 0.14701421\n",
      " 0.1332766  0.14617434 0.14958931 0.13586651 0.14789848 0.14959671\n",
      " 0.13411277 0.14788738 0.14960041 0.13413127 0.15217922 0.14615214\n",
      " 0.13413127 0.15217922 0.14615214 0.14100562 0.14702161 0.14529377\n",
      " 0.13155246 0.14873835 0.14786888 0.13500444 0.15132455 0.1444354\n",
      " 0.13755735 0.14960411 0.14701421 0.1332766  0.14617434 0.14958931\n",
      " 0.13586651 0.14789848 0.14959671 0.13411277 0.14788738 0.14960041\n",
      " 0.13413127 0.15217922 0.14615214 0.13413127 0.15217922 0.14615214\n",
      " 0.14100562 0.14702161 0.14529377        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.32244709 0.32073775 0.32761211 0.31728948 0.31300133 0.30869469\n",
      " 0.30093607 0.30869839 0.29753219 0.3138412  0.32589167 0.30784742\n",
      " 0.29750259 0.30867619 0.30524641 0.29578585 0.30095457 0.29580435\n",
      " 0.29323664 0.30182773 0.29151621 0.29323664 0.30182773 0.29151621\n",
      " 0.28803463 0.29408391 0.29321814 0.32244709 0.32073775 0.32761211\n",
      " 0.31728948 0.31300133 0.30869469 0.30093607 0.30869839 0.29753219\n",
      " 0.3138412  0.32589167 0.30784742 0.29750259 0.30867619 0.30524641\n",
      " 0.29578585 0.30095457 0.29580435 0.29323664 0.30182773 0.29151621\n",
      " 0.29323664 0.30182773 0.29151621 0.28803463 0.29408391 0.29321814\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan 0.39810197 0.39553056 0.39294065\n",
      " 0.38434586 0.37400474 0.37573257 0.34392852 0.35425115 0.34565636\n",
      " 0.37144073 0.36628311 0.3611255  0.36540255 0.36370431 0.35856149\n",
      " 0.3473398  0.35078437 0.34392112 0.32156652 0.33532633 0.32673524\n",
      " 0.32156652 0.33532633 0.32673524 0.31726358 0.31983499 0.31725618\n",
      " 0.39810197 0.39553056 0.39294065 0.38434586 0.37400474 0.37573257\n",
      " 0.34392852 0.35425115 0.34565636 0.37144073 0.36628311 0.3611255\n",
      " 0.36540255 0.36370431 0.35856149 0.3473398  0.35078437 0.34392112\n",
      " 0.32156652 0.33532633 0.32673524 0.32156652 0.33532633 0.32673524\n",
      " 0.31726358 0.31983499 0.31725618]\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "Y_test_norolling_rf, Y_pred_norolling_rf, rf_norolling = creating_rf_model(X_norolling, Y_other)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "10459e59f8f1fa4b",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.087581Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.62      0.76       722\n",
      "           1       0.03      0.36      0.05        22\n",
      "\n",
      "    accuracy                           0.62       744\n",
      "   macro avg       0.50      0.49      0.41       744\n",
      "weighted avg       0.94      0.62      0.74       744\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_norolling_svc, Y_pred_norolling_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "6c67fa727752d513",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.088589Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.4934525308486528"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_norolling_svc, Y_pred_norolling_svc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "747e148f206175fc",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.089590Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.71      0.66      0.68       505\n",
      "           1       0.38      0.44      0.40       239\n",
      "\n",
      "    accuracy                           0.59       744\n",
      "   macro avg       0.54      0.55      0.54       744\n",
      "weighted avg       0.60      0.59      0.59       744\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_plot_result_clf(Y_test_norolling_rf, Y_pred_norolling_rf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "9b7d69e2f4e5130f",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2024-07-07T13:13:15.090589Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.5462860930444509"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_roc(Y_test_norolling_rf, Y_pred_norolling_rf)"
   ]
  }
 ],
 "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}