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This commit is contained in:
Giuseppe Musicco
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5c9991b1",
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"metadata": {},
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"source": [
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"Generate player votes database, containing votes for Serie A matchday and player.\n",
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"\n",
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"Votes data is manually downloaded from https://www.fantacalcio.it/voti-fantacalcio-serie-a\n",
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"\n",
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"Serie A calendar is loaded from another file, to add information not containing in votes files: home/away, team opponent."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "b63beb69",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "a3c39376",
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"metadata": {},
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"outputs": [],
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"source": [
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"cal = np.array(pd.read_excel('fantacalcio/seriea_calendar.xlsx', header = None))\n",
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"\n",
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"cal_df = pd.DataFrame(columns = ['matchday', 'team1', 'team2'])\n",
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"\n",
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"matchday = 0\n",
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"\n",
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"for i in range(cal.shape[0]):\n",
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" if(cal[i, 0][0].isnumeric()):\n",
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" matchday = matchday + 1\n",
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" continue\n",
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" \n",
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" teams = cal[i, 0].split('-')\n",
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" \n",
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" frame = pd.DataFrame([[matchday, teams[0], teams[1]]], columns = cal_df.columns)\n",
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"\n",
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" cal_df = pd.concat([cal_df, frame], ignore_index = True)\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "92d3c6fb",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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||||
"<style scoped>\n",
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||||
" .dataframe tbody tr th:only-of-type {\n",
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||||
" vertical-align: middle;\n",
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" }\n",
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"\n",
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||||
" .dataframe tbody tr th {\n",
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||||
" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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||||
" text-align: right;\n",
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||||
" }\n",
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"</style>\n",
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||||
"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>matchday</th>\n",
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" <th>team1</th>\n",
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" <th>team2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>Fiorentina</td>\n",
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" <td>Cremonese</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>1</td>\n",
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" <td>Verona</td>\n",
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" <td>Napoli</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>1</td>\n",
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" <td>Juventus</td>\n",
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" <td>Sassuolo</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>1</td>\n",
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" <td>Lazio</td>\n",
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" <td>Bologna</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>1</td>\n",
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" <td>Lecce</td>\n",
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" <td>Inter</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>375</th>\n",
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" <td>38</td>\n",
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" <td>Milan</td>\n",
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" <td>Lazio</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>376</th>\n",
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" <td>38</td>\n",
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" <td>Sassuolo</td>\n",
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" <td>Monza</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>377</th>\n",
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" <td>38</td>\n",
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" <td>Napoli</td>\n",
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" <td>Salernitana</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>378</th>\n",
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" <td>38</td>\n",
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" <td>Udinese</td>\n",
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" <td>Sampdoria</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>379</th>\n",
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" <td>38</td>\n",
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" <td>Roma</td>\n",
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" <td>Spezia</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>380 rows × 3 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" matchday team1 team2\n",
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"0 1 Fiorentina Cremonese\n",
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"1 1 Verona Napoli\n",
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"2 1 Juventus Sassuolo\n",
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"3 1 Lazio Bologna\n",
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"4 1 Lecce Inter\n",
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".. ... ... ...\n",
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"375 38 Milan Lazio\n",
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"376 38 Sassuolo Monza\n",
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"377 38 Napoli Salernitana\n",
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"378 38 Udinese Sampdoria\n",
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"379 38 Roma Spezia\n",
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"\n",
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"[380 rows x 3 columns]"
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]
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},
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"execution_count": 13,
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"metadata": {},
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||||
"output_type": "execute_result"
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}
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],
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"source": [
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"cal_df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "0d4a330d",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.DataFrame(columns = ['matchday', 'player', 'team', 'oppteam', 'home', 'vote', 'goals', 'assists', 'cards_malus', 'fantavote'])\n",
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"\n",
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"LAST_MATCH = 14\n",
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"\n",
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"for matchday in range(1, LAST_MATCH + 1):\n",
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" \n",
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" votes_file = 'fantacalcio/voti/Voti_Fantacalcio_Stagione_2022_23_Giornata_' + str(matchday) + '.xlsx'\n",
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"\n",
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"\n",
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"\n",
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"\n",
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" rx = np.array(pd.read_excel(votes_file, header = None))\n",
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"\n",
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" read = 0\n",
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" for i in range(rx.shape[0]):\n",
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" if(rx[i, 0] == \"Cod.\"):\n",
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" read = 1\n",
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" team = rx[i-1, 0];\n",
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" continue\n",
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"\n",
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" if(read):\n",
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" if(isinstance(rx[i, 0], int)):\n",
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" if((isinstance(rx[i, 3], float) or isinstance(rx[i, 3], int)) and rx[i, 1] != \"ALL\") :\n",
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" player = rx[i, 2];\n",
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" vote = float(rx[i, 3])\n",
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" goals = rx[i, 4] + rx[i, 8] - rx[i, 5]\n",
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" assists = rx[i, 12]\n",
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" cards_malus = rx[i, 10] * 0.5 + rx[i, 11]\n",
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" \n",
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" oppteam = ''\n",
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" home = 0\n",
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" for j in range(cal_df.shape[0]):\n",
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" if(cal_df['matchday'][j] == matchday):\n",
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" if(cal_df['team1'][j] == team):\n",
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" oppteam = cal_df['team2'][j] \n",
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" home = 1\n",
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" elif(cal_df['team2'][j] == team):\n",
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" oppteam = cal_df['team1'][j] \n",
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" home = 0\n",
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"\n",
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" goals_gen = goals * 3;\n",
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" if(goals < 0):\n",
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" goals_gen = goals\n",
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" \n",
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" fantavote = vote + goals_gen + assists - cards_malus \n",
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" \n",
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" frame = pd.DataFrame([[matchday, player, team, oppteam, home, vote, goals, assists, cards_malus, fantavote]], columns = df.columns)\n",
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"\n",
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" df = pd.concat([df, frame], axis = 0, ignore_index = True)\n",
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" else:\n",
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" read = 0\n",
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" continue\n",
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"\n",
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" df"
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]
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},
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{
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"cell_type": "code",
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||||
"execution_count": 15,
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||||
"id": "6ade957d",
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||||
"metadata": {},
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"outputs": [
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||||
{
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"data": {
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"text/html": [
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||||
"<div>\n",
|
||||
"<style scoped>\n",
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||||
" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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||||
" }\n",
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||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
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||||
" vertical-align: top;\n",
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||||
" }\n",
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||||
"\n",
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||||
" .dataframe thead th {\n",
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||||
" text-align: right;\n",
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||||
" }\n",
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||||
"</style>\n",
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||||
"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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||||
" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>matchday</th>\n",
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" <th>player</th>\n",
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" <th>team</th>\n",
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" <th>oppteam</th>\n",
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" <th>home</th>\n",
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" <th>vote</th>\n",
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" <th>goals</th>\n",
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" <th>assists</th>\n",
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" <th>cards_malus</th>\n",
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" <th>fantavote</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>Musso</td>\n",
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" <td>Atalanta</td>\n",
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" <td>Sampdoria</td>\n",
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" <td>0</td>\n",
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" <td>6.0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>0.5</td>\n",
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" <td>5.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>1</td>\n",
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" <td>Toloi</td>\n",
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" <td>Atalanta</td>\n",
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" <td>Sampdoria</td>\n",
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" <td>0</td>\n",
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" <td>7.0</td>\n",
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" <td>1</td>\n",
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||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
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" <td>10.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>1</td>\n",
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" <td>Djimsiti</td>\n",
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" <td>Atalanta</td>\n",
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" <td>Sampdoria</td>\n",
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" <td>0</td>\n",
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" <td>6.0</td>\n",
|
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" <td>0</td>\n",
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||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
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||||
" <td>6.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>1</td>\n",
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" <td>Hateboer</td>\n",
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" <td>Atalanta</td>\n",
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" <td>Sampdoria</td>\n",
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||||
" <td>0</td>\n",
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||||
" <td>6.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
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||||
" <td>0.5</td>\n",
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" <td>5.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>1</td>\n",
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||||
" <td>Okoli</td>\n",
|
||||
" <td>Atalanta</td>\n",
|
||||
" <td>Sampdoria</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>5.5</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>5.0</td>\n",
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||||
" </tr>\n",
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||||
" <tr>\n",
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||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
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||||
" <tr>\n",
|
||||
" <th>4010</th>\n",
|
||||
" <td>14</td>\n",
|
||||
" <td>Sulemana I.</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>6.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>6.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4011</th>\n",
|
||||
" <td>14</td>\n",
|
||||
" <td>Lasagna</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>6.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>6.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4012</th>\n",
|
||||
" <td>14</td>\n",
|
||||
" <td>Kallon</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>5.5</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>5.5</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4013</th>\n",
|
||||
" <td>14</td>\n",
|
||||
" <td>Djuric</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>6.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>5.5</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4014</th>\n",
|
||||
" <td>14</td>\n",
|
||||
" <td>Henry</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>6.5</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>6.5</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
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||||
"<p>4015 rows × 10 columns</p>\n",
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||||
"</div>"
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||||
],
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"text/plain": [
|
||||
" matchday player team oppteam home vote goals assists \\\n",
|
||||
"0 1 Musso Atalanta Sampdoria 0 6.0 0 0 \n",
|
||||
"1 1 Toloi Atalanta Sampdoria 0 7.0 1 0 \n",
|
||||
"2 1 Djimsiti Atalanta Sampdoria 0 6.0 0 0 \n",
|
||||
"3 1 Hateboer Atalanta Sampdoria 0 6.0 0 0 \n",
|
||||
"4 1 Okoli Atalanta Sampdoria 0 5.5 0 0 \n",
|
||||
"... ... ... ... ... ... ... ... ... \n",
|
||||
"4010 14 Sulemana I. Verona Juventus 1 6.0 0 0 \n",
|
||||
"4011 14 Lasagna Verona Juventus 1 6.0 0 0 \n",
|
||||
"4012 14 Kallon Verona Juventus 1 5.5 0 0 \n",
|
||||
"4013 14 Djuric Verona Juventus 1 6.0 0 0 \n",
|
||||
"4014 14 Henry Verona Juventus 1 6.5 0 0 \n",
|
||||
"\n",
|
||||
" cards_malus fantavote \n",
|
||||
"0 0.5 5.5 \n",
|
||||
"1 0.0 10.0 \n",
|
||||
"2 0.0 6.0 \n",
|
||||
"3 0.5 5.5 \n",
|
||||
"4 0.5 5.0 \n",
|
||||
"... ... ... \n",
|
||||
"4010 0.0 6.0 \n",
|
||||
"4011 0.0 6.0 \n",
|
||||
"4012 0.0 5.5 \n",
|
||||
"4013 0.5 5.5 \n",
|
||||
"4014 0.0 6.5 \n",
|
||||
"\n",
|
||||
"[4015 rows x 10 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "230213fe",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df.to_excel('mid_outputs/players_votes.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ef91ece3",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Elaborate data for past seasons.\n",
|
||||
"\n",
|
||||
"Do not repeat if data is already present."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "da35bdf9",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>matchday</th>\n",
|
||||
" <th>team1</th>\n",
|
||||
" <th>team2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Sassuolo</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Inter</td>\n",
|
||||
" <td>Genoa</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Empoli</td>\n",
|
||||
" <td>Lazio</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Torino</td>\n",
|
||||
" <td>Atalanta</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Bologna</td>\n",
|
||||
" <td>Salernitana</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>375</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Spezia</td>\n",
|
||||
" <td>Napoli</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>376</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Sassuolo</td>\n",
|
||||
" <td>Milan</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>377</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Inter</td>\n",
|
||||
" <td>Sampdoria</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>378</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Salernitana</td>\n",
|
||||
" <td>Udinese</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>379</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Venezia</td>\n",
|
||||
" <td>Cagliari</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>380 rows × 3 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" matchday team1 team2\n",
|
||||
"0 1 Verona Sassuolo\n",
|
||||
"1 1 Inter Genoa\n",
|
||||
"2 1 Empoli Lazio\n",
|
||||
"3 1 Torino Atalanta\n",
|
||||
"4 1 Bologna Salernitana\n",
|
||||
".. ... ... ...\n",
|
||||
"375 38 Spezia Napoli\n",
|
||||
"376 38 Sassuolo Milan\n",
|
||||
"377 38 Inter Sampdoria\n",
|
||||
"378 38 Salernitana Udinese\n",
|
||||
"379 38 Venezia Cagliari\n",
|
||||
"\n",
|
||||
"[380 rows x 3 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"cal_df = pd.read_excel('fantacalcio/season2122/seriea_calendar.xlsx')\n",
|
||||
"\n",
|
||||
"to_drop = list()\n",
|
||||
"\n",
|
||||
"for i in range(cal_df.shape[0]):\n",
|
||||
" if(not isinstance(cal_df['matchday'][i], int)):\n",
|
||||
" to_drop.append(i)\n",
|
||||
" \n",
|
||||
"cal_df = cal_df.drop(to_drop)\n",
|
||||
"\n",
|
||||
"cal_df = cal_df.reset_index(drop = True)\n",
|
||||
"\n",
|
||||
"cal_df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "0313a0f4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df = pd.DataFrame(columns = ['matchday', 'player', 'team', 'oppteam', 'home', 'vote', 'goals', 'assists', 'cards_malus', 'fantavote'])\n",
|
||||
"\n",
|
||||
"LAST_MATCH = 38\n",
|
||||
"\n",
|
||||
"for matchday in range(1, LAST_MATCH + 1):\n",
|
||||
" \n",
|
||||
" votes_file = 'fantacalcio/season2122/voti/Voti_Fantacalcio_Stagione_2021_22_Giornata_' + str(matchday) + '.xlsx'\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" rx = np.array(pd.read_excel(votes_file, header = None))\n",
|
||||
"\n",
|
||||
" read = 0\n",
|
||||
" for i in range(rx.shape[0]):\n",
|
||||
" if(rx[i, 0] == \"Cod.\"):\n",
|
||||
" read = 1\n",
|
||||
" team = rx[i-1, 0];\n",
|
||||
" continue\n",
|
||||
"\n",
|
||||
" if(read):\n",
|
||||
" if(isinstance(rx[i, 0], int)):\n",
|
||||
" if((isinstance(rx[i, 3], float) or isinstance(rx[i, 3], int)) and rx[i, 1] != \"ALL\") :\n",
|
||||
" player = rx[i, 2];\n",
|
||||
" vote = float(rx[i, 3])\n",
|
||||
" goals = rx[i, 4] + rx[i, 8] - rx[i, 5]\n",
|
||||
" assists = rx[i, 12]\n",
|
||||
" cards_malus = rx[i, 10] * 0.5 + rx[i, 11]\n",
|
||||
" \n",
|
||||
" oppteam = ''\n",
|
||||
" home = 0\n",
|
||||
" for j in range(cal_df.shape[0]):\n",
|
||||
" if(cal_df['matchday'][j] == matchday):\n",
|
||||
" if(cal_df['team1'][j] == team):\n",
|
||||
" oppteam = cal_df['team2'][j] \n",
|
||||
" home = 1\n",
|
||||
" elif(cal_df['team2'][j] == team):\n",
|
||||
" oppteam = cal_df['team1'][j] \n",
|
||||
" home = 0\n",
|
||||
"\n",
|
||||
" goals_gen = goals * 3;\n",
|
||||
" if(goals < 0):\n",
|
||||
" goals_gen = goals\n",
|
||||
" \n",
|
||||
" fantavote = vote + goals_gen + assists - cards_malus \n",
|
||||
" \n",
|
||||
" frame = pd.DataFrame([[matchday, player, team, oppteam, home, vote, goals, assists, cards_malus, fantavote]], columns = df.columns)\n",
|
||||
"\n",
|
||||
" df = pd.concat([df, frame], axis = 0, ignore_index = True)\n",
|
||||
" else:\n",
|
||||
" read = 0\n",
|
||||
" continue\n",
|
||||
"\n",
|
||||
" df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "82b1cfc8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df.to_excel('mid_outputs/season2122/players_votes.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "d1fca3ba",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>matchday</th>\n",
|
||||
" <th>team1</th>\n",
|
||||
" <th>team2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Fiorentina</td>\n",
|
||||
" <td>Torino</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" <td>Roma</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Parma</td>\n",
|
||||
" <td>Napoli</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Genoa</td>\n",
|
||||
" <td>Crotone</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Sassuolo</td>\n",
|
||||
" <td>Cagliari</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>375</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Sassuolo</td>\n",
|
||||
" <td>Lazio</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>376</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Atalanta</td>\n",
|
||||
" <td>Milan</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>377</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Torino</td>\n",
|
||||
" <td>Benevento</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>378</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Bologna</td>\n",
|
||||
" <td>Juventus</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>379</th>\n",
|
||||
" <td>38</td>\n",
|
||||
" <td>Napoli</td>\n",
|
||||
" <td>Verona</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>380 rows × 3 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" matchday team1 team2\n",
|
||||
"0 1 Fiorentina Torino\n",
|
||||
"1 1 Verona Roma\n",
|
||||
"2 1 Parma Napoli\n",
|
||||
"3 1 Genoa Crotone\n",
|
||||
"4 1 Sassuolo Cagliari\n",
|
||||
".. ... ... ...\n",
|
||||
"375 38 Sassuolo Lazio\n",
|
||||
"376 38 Atalanta Milan\n",
|
||||
"377 38 Torino Benevento\n",
|
||||
"378 38 Bologna Juventus\n",
|
||||
"379 38 Napoli Verona\n",
|
||||
"\n",
|
||||
"[380 rows x 3 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"cal_df = pd.read_excel('fantacalcio/season2021/seriea_calendar.xlsx')\n",
|
||||
"\n",
|
||||
"to_drop = list()\n",
|
||||
"\n",
|
||||
"for i in range(cal_df.shape[0]):\n",
|
||||
" if(not isinstance(cal_df['matchday'][i], int)):\n",
|
||||
" to_drop.append(i)\n",
|
||||
" \n",
|
||||
"cal_df = cal_df.drop(to_drop)\n",
|
||||
"\n",
|
||||
"cal_df = cal_df.reset_index(drop = True)\n",
|
||||
"\n",
|
||||
"cal_df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "6d5d4101",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df = pd.DataFrame(columns = ['matchday', 'player', 'team', 'oppteam', 'home', 'vote', 'goals', 'assists', 'cards_malus', 'fantavote'])\n",
|
||||
"\n",
|
||||
"LAST_MATCH = 38\n",
|
||||
"\n",
|
||||
"for matchday in range(1, LAST_MATCH + 1):\n",
|
||||
" \n",
|
||||
" votes_file = 'fantacalcio/season2021/voti/Voti_Fantacalcio_Stagione_2020_21_Giornata_' + str(matchday) + '.xlsx'\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" rx = np.array(pd.read_excel(votes_file, header = None))\n",
|
||||
"\n",
|
||||
" read = 0\n",
|
||||
" for i in range(rx.shape[0]):\n",
|
||||
" if(rx[i, 0] == \"Cod.\"):\n",
|
||||
" read = 1\n",
|
||||
" team = rx[i-1, 0];\n",
|
||||
" continue\n",
|
||||
"\n",
|
||||
" if(read):\n",
|
||||
" if(isinstance(rx[i, 0], int)):\n",
|
||||
" if((isinstance(rx[i, 3], float) or isinstance(rx[i, 3], int)) and rx[i, 1] != \"ALL\") :\n",
|
||||
" player = rx[i, 2];\n",
|
||||
" vote = float(rx[i, 3])\n",
|
||||
" goals = rx[i, 4] + rx[i, 8] - rx[i, 5]\n",
|
||||
" assists = rx[i, 12]\n",
|
||||
" cards_malus = rx[i, 10] * 0.5 + rx[i, 11]\n",
|
||||
" \n",
|
||||
" oppteam = ''\n",
|
||||
" home = 0\n",
|
||||
" for j in range(cal_df.shape[0]):\n",
|
||||
" if(cal_df['matchday'][j] == matchday):\n",
|
||||
" if(cal_df['team1'][j] == team):\n",
|
||||
" oppteam = cal_df['team2'][j] \n",
|
||||
" home = 1\n",
|
||||
" elif(cal_df['team2'][j] == team):\n",
|
||||
" oppteam = cal_df['team1'][j] \n",
|
||||
" home = 0\n",
|
||||
"\n",
|
||||
" goals_gen = goals * 3;\n",
|
||||
" if(goals < 0):\n",
|
||||
" goals_gen = goals\n",
|
||||
" \n",
|
||||
" fantavote = vote + goals_gen + assists - cards_malus \n",
|
||||
" \n",
|
||||
" frame = pd.DataFrame([[matchday, player, team, oppteam, home, vote, goals, assists, cards_malus, fantavote]], columns = df.columns)\n",
|
||||
"\n",
|
||||
" df = pd.concat([df, frame], axis = 0, ignore_index = True)\n",
|
||||
" else:\n",
|
||||
" read = 0\n",
|
||||
" continue\n",
|
||||
"\n",
|
||||
" df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "0a4bbffd",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df.to_excel('mid_outputs/season2021/players_votes.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "48a341c2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
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|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "fd8a6cb9",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Scraping for playing probability for the current Serie A matchday.\n",
|
||||
"\n",
|
||||
"Data from http://fantacalcio.it"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "4c7b7d26",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import requests\n",
|
||||
"from bs4 import BeautifulSoup\n",
|
||||
"import pandas as pd\n",
|
||||
"import numpy as np\n",
|
||||
"import re\n",
|
||||
"import sys, getopt\n",
|
||||
"import csv\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "91897dbb",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"res = requests.get('https://www.fantacalcio.it/probabili-formazioni-serie-a')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "7ba89027",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>player</th>\n",
|
||||
" <th>starter</th>\n",
|
||||
" <th>percentage</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>Vicario</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>Ebuehi</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>Ismajli</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>Walukiewicz</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>Parisi</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>444</th>\n",
|
||||
" <td>Basic</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>445</th>\n",
|
||||
" <td>Bertini</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>10.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>446</th>\n",
|
||||
" <td>Marcos Antonio</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>50.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>447</th>\n",
|
||||
" <td>Romero L.</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>50.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>448</th>\n",
|
||||
" <td>Cancellieri</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>449 rows × 3 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" player starter percentage\n",
|
||||
"0 Vicario 1 100.0\n",
|
||||
"1 Ebuehi 1 100.0\n",
|
||||
"2 Ismajli 1 100.0\n",
|
||||
"3 Walukiewicz 1 100.0\n",
|
||||
"4 Parisi 1 100.0\n",
|
||||
".. ... ... ...\n",
|
||||
"444 Basic 0 55.0\n",
|
||||
"445 Bertini 0 10.0\n",
|
||||
"446 Marcos Antonio 0 50.0\n",
|
||||
"447 Romero L. 0 50.0\n",
|
||||
"448 Cancellieri 0 55.0\n",
|
||||
"\n",
|
||||
"[449 rows x 3 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"soup = BeautifulSoup(res.text)\n",
|
||||
"\n",
|
||||
"groups = soup.findAll('ul', attrs = {'class' : 'player-list'})\n",
|
||||
"\n",
|
||||
"probables = pd.DataFrame(columns = ['player', 'starter', 'percentage'])\n",
|
||||
"\n",
|
||||
"for i in range (len(groups)):\n",
|
||||
" players = groups[i].findAll('a', attrs = {'class' : 'player-name'})\n",
|
||||
" bars = groups[i].findAll('div', attrs = {'class' : 'progress-bar'})\n",
|
||||
" \n",
|
||||
" starter_string = groups[i]['class'][1]\n",
|
||||
" if(starter_string == 'starters'):\n",
|
||||
" starter = 1\n",
|
||||
" else:\n",
|
||||
" starter = 0\n",
|
||||
" \n",
|
||||
" for j in range(len(players)):\n",
|
||||
" player = players[j].contents[0].replace('\\n \\n ', '')\n",
|
||||
" perc = float(bars[j]['aria-valuenow'])\n",
|
||||
" \n",
|
||||
" row_df = pd.DataFrame([[player, starter, perc]], columns = probables.columns)\n",
|
||||
" \n",
|
||||
" probables = pd.concat([probables, row_df], ignore_index = True)\n",
|
||||
" \n",
|
||||
"probables "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "29e5b389",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"probables = probables.set_index('player')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "d711726e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>player1</th>\n",
|
||||
" <th>player2</th>\n",
|
||||
" <th>percentage</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>Lozano</td>\n",
|
||||
" <td>Politano</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>Zambo Anguissa</td>\n",
|
||||
" <td>Ndombele'</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>Mario Rui</td>\n",
|
||||
" <td>Olivera</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>Elmas</td>\n",
|
||||
" <td>Raspadori</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>Beto</td>\n",
|
||||
" <td>Success</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5</th>\n",
|
||||
" <td>Lovric</td>\n",
|
||||
" <td>Samardzic</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>Ehizibue</td>\n",
|
||||
" <td>Nuytinck</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7</th>\n",
|
||||
" <td>Rincon</td>\n",
|
||||
" <td>Vieira</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>8</th>\n",
|
||||
" <td>Augello</td>\n",
|
||||
" <td>Murru</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9</th>\n",
|
||||
" <td>Djuricic</td>\n",
|
||||
" <td>Leris</td>\n",
|
||||
" <td>65.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10</th>\n",
|
||||
" <td>Caputo</td>\n",
|
||||
" <td>Montevago</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>11</th>\n",
|
||||
" <td>Di Francesco F.</td>\n",
|
||||
" <td>Banda</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>12</th>\n",
|
||||
" <td>Colombo</td>\n",
|
||||
" <td>Ceesay</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>13</th>\n",
|
||||
" <td>Gonzalez J.</td>\n",
|
||||
" <td>Bistrovic</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>14</th>\n",
|
||||
" <td>Lykogiannis</td>\n",
|
||||
" <td>Cambiaso</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>15</th>\n",
|
||||
" <td>Barrow</td>\n",
|
||||
" <td>Orsolini</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>16</th>\n",
|
||||
" <td>Ferguson</td>\n",
|
||||
" <td>Schouten</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17</th>\n",
|
||||
" <td>Traore' Hj.</td>\n",
|
||||
" <td>Berardi</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>18</th>\n",
|
||||
" <td>Rogerio</td>\n",
|
||||
" <td>Kyriakopoulos</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>19</th>\n",
|
||||
" <td>Djimsiti</td>\n",
|
||||
" <td>Scalvini</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>20</th>\n",
|
||||
" <td>Zapata D.</td>\n",
|
||||
" <td>Hojlund</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>21</th>\n",
|
||||
" <td>Pasalic</td>\n",
|
||||
" <td>Malinovskyi</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>22</th>\n",
|
||||
" <td>Bastoni</td>\n",
|
||||
" <td>Acerbi</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>23</th>\n",
|
||||
" <td>Brozovic</td>\n",
|
||||
" <td>Mkhitaryan</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>24</th>\n",
|
||||
" <td>Skriniar</td>\n",
|
||||
" <td>D'ambrosio</td>\n",
|
||||
" <td>65.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>25</th>\n",
|
||||
" <td>Lazovic</td>\n",
|
||||
" <td>Depaoli</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>26</th>\n",
|
||||
" <td>Verdi</td>\n",
|
||||
" <td>Hongla</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>27</th>\n",
|
||||
" <td>Dawidowicz</td>\n",
|
||||
" <td>Hien</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>28</th>\n",
|
||||
" <td>Verde</td>\n",
|
||||
" <td>Gyasi</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>29</th>\n",
|
||||
" <td>Bastoni S.</td>\n",
|
||||
" <td>Amian</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>30</th>\n",
|
||||
" <td>Carlos Augusto</td>\n",
|
||||
" <td>D'alessandro</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>31</th>\n",
|
||||
" <td>Birindelli</td>\n",
|
||||
" <td>Ciurria</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>32</th>\n",
|
||||
" <td>Petagna</td>\n",
|
||||
" <td>Gytkjaer</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>33</th>\n",
|
||||
" <td>Caldirola</td>\n",
|
||||
" <td>Carboni</td>\n",
|
||||
" <td>65.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>34</th>\n",
|
||||
" <td>Lovato</td>\n",
|
||||
" <td>Bronn</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>35</th>\n",
|
||||
" <td>Piatek</td>\n",
|
||||
" <td>Bonazzoli</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>36</th>\n",
|
||||
" <td>Candreva</td>\n",
|
||||
" <td>Bradaric</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>37</th>\n",
|
||||
" <td>Zalewski</td>\n",
|
||||
" <td>El Shaarawy</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>38</th>\n",
|
||||
" <td>Volpato</td>\n",
|
||||
" <td>Dybala</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>39</th>\n",
|
||||
" <td>Matic</td>\n",
|
||||
" <td>Camara Ma.</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>40</th>\n",
|
||||
" <td>Vojvoda</td>\n",
|
||||
" <td>Singo</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>41</th>\n",
|
||||
" <td>Sanabria</td>\n",
|
||||
" <td>Pellegri</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>42</th>\n",
|
||||
" <td>Miranchuk</td>\n",
|
||||
" <td>Radonjic</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>43</th>\n",
|
||||
" <td>Kjaer</td>\n",
|
||||
" <td>Gabbia</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>44</th>\n",
|
||||
" <td>De Ketelaere</td>\n",
|
||||
" <td>Diaz B.</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>45</th>\n",
|
||||
" <td>Bennacer</td>\n",
|
||||
" <td>Pobega</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>46</th>\n",
|
||||
" <td>Martinez Quarta</td>\n",
|
||||
" <td>Igor</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>47</th>\n",
|
||||
" <td>Bonaventura</td>\n",
|
||||
" <td>Mandragora</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>48</th>\n",
|
||||
" <td>Dodo'</td>\n",
|
||||
" <td>Venuti</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>49</th>\n",
|
||||
" <td>Ikone'</td>\n",
|
||||
" <td>Saponara</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>50</th>\n",
|
||||
" <td>Locatelli</td>\n",
|
||||
" <td>Paredes</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>51</th>\n",
|
||||
" <td>Milik</td>\n",
|
||||
" <td>Vlahovic</td>\n",
|
||||
" <td>65.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>52</th>\n",
|
||||
" <td>Miretti</td>\n",
|
||||
" <td>Di Maria</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>53</th>\n",
|
||||
" <td>Immobile</td>\n",
|
||||
" <td>Cancellieri</td>\n",
|
||||
" <td>60.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>54</th>\n",
|
||||
" <td>Vecino</td>\n",
|
||||
" <td>Luis Alberto</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" player1 player2 percentage\n",
|
||||
"0 Lozano Politano 60.0\n",
|
||||
"1 Zambo Anguissa Ndombele' 60.0\n",
|
||||
"2 Mario Rui Olivera 55.0\n",
|
||||
"3 Elmas Raspadori 55.0\n",
|
||||
"4 Beto Success 60.0\n",
|
||||
"5 Lovric Samardzic 55.0\n",
|
||||
"6 Ehizibue Nuytinck 60.0\n",
|
||||
"7 Rincon Vieira 60.0\n",
|
||||
"8 Augello Murru 55.0\n",
|
||||
"9 Djuricic Leris 65.0\n",
|
||||
"10 Caputo Montevago 60.0\n",
|
||||
"11 Di Francesco F. Banda 55.0\n",
|
||||
"12 Colombo Ceesay 55.0\n",
|
||||
"13 Gonzalez J. Bistrovic 60.0\n",
|
||||
"14 Lykogiannis Cambiaso 55.0\n",
|
||||
"15 Barrow Orsolini 55.0\n",
|
||||
"16 Ferguson Schouten 55.0\n",
|
||||
"17 Traore' Hj. Berardi 55.0\n",
|
||||
"18 Rogerio Kyriakopoulos 60.0\n",
|
||||
"19 Djimsiti Scalvini 60.0\n",
|
||||
"20 Zapata D. Hojlund 60.0\n",
|
||||
"21 Pasalic Malinovskyi 55.0\n",
|
||||
"22 Bastoni Acerbi 55.0\n",
|
||||
"23 Brozovic Mkhitaryan 55.0\n",
|
||||
"24 Skriniar D'ambrosio 65.0\n",
|
||||
"25 Lazovic Depaoli 55.0\n",
|
||||
"26 Verdi Hongla 60.0\n",
|
||||
"27 Dawidowicz Hien 60.0\n",
|
||||
"28 Verde Gyasi 55.0\n",
|
||||
"29 Bastoni S. Amian 55.0\n",
|
||||
"30 Carlos Augusto D'alessandro 60.0\n",
|
||||
"31 Birindelli Ciurria 60.0\n",
|
||||
"32 Petagna Gytkjaer 55.0\n",
|
||||
"33 Caldirola Carboni 65.0\n",
|
||||
"34 Lovato Bronn 55.0\n",
|
||||
"35 Piatek Bonazzoli 55.0\n",
|
||||
"36 Candreva Bradaric 55.0\n",
|
||||
"37 Zalewski El Shaarawy 60.0\n",
|
||||
"38 Volpato Dybala 55.0\n",
|
||||
"39 Matic Camara Ma. 55.0\n",
|
||||
"40 Vojvoda Singo 60.0\n",
|
||||
"41 Sanabria Pellegri 55.0\n",
|
||||
"42 Miranchuk Radonjic 55.0\n",
|
||||
"43 Kjaer Gabbia 55.0\n",
|
||||
"44 De Ketelaere Diaz B. 55.0\n",
|
||||
"45 Bennacer Pobega 60.0\n",
|
||||
"46 Martinez Quarta Igor 55.0\n",
|
||||
"47 Bonaventura Mandragora 55.0\n",
|
||||
"48 Dodo' Venuti 55.0\n",
|
||||
"49 Ikone' Saponara 55.0\n",
|
||||
"50 Locatelli Paredes 60.0\n",
|
||||
"51 Milik Vlahovic 65.0\n",
|
||||
"52 Miretti Di Maria 55.0\n",
|
||||
"53 Immobile Cancellieri 60.0\n",
|
||||
"54 Vecino Luis Alberto 55.0"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"groups = soup.findAll('ul', attrs = {'class' : 'ballot-list'})\n",
|
||||
"\n",
|
||||
"ballots = pd.DataFrame(columns = ['player1', 'player2', 'percentage'])\n",
|
||||
"for i in range (len(groups)):\n",
|
||||
" players = groups[i].findAll('a', attrs = {'class' : 'player-name'})\n",
|
||||
" percs = groups[i].findAll('strong', attrs = {'class' : 'percentage'})\n",
|
||||
" \n",
|
||||
" player1 = players[0].contents[0].replace('\\n \\n ', '')\n",
|
||||
" player2 = players[1].contents[0].replace('\\n \\n ', '')\n",
|
||||
" perc = float(percs[0].contents[0].replace('%', ''))\n",
|
||||
" \n",
|
||||
" row_df = pd.DataFrame([[player1, player2, perc]], columns = ballots.columns)\n",
|
||||
" \n",
|
||||
" ballots = pd.concat([ballots, row_df], ignore_index = True)\n",
|
||||
" \n",
|
||||
"ballots"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "0171c61d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>starter</th>\n",
|
||||
" <th>percentage</th>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>player</th>\n",
|
||||
" <th></th>\n",
|
||||
" <th></th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>Vicario</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Ebuehi</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Ismajli</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Walukiewicz</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Parisi</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Basic</th>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Bertini</th>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>10.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Marcos Antonio</th>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>50.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Romero L.</th>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>50.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>Cancellieri</th>\n",
|
||||
" <td>0.4</td>\n",
|
||||
" <td>55.0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>449 rows × 2 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" starter percentage\n",
|
||||
"player \n",
|
||||
"Vicario 1 100.0\n",
|
||||
"Ebuehi 1 100.0\n",
|
||||
"Ismajli 1 100.0\n",
|
||||
"Walukiewicz 1 100.0\n",
|
||||
"Parisi 1 100.0\n",
|
||||
"... ... ...\n",
|
||||
"Basic 0 55.0\n",
|
||||
"Bertini 0 10.0\n",
|
||||
"Marcos Antonio 0 50.0\n",
|
||||
"Romero L. 0 50.0\n",
|
||||
"Cancellieri 0.4 55.0\n",
|
||||
"\n",
|
||||
"[449 rows x 2 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for i in range(ballots.shape[0]):\n",
|
||||
" p1 = ballots['player1'][i]\n",
|
||||
" p2 = ballots['player2'][i]\n",
|
||||
" \n",
|
||||
" perc = float(ballots['percentage'][i])\n",
|
||||
" \n",
|
||||
" probables.at[p1, 'starter'] = perc/100\n",
|
||||
" probables.at[p2, 'starter'] = 1 - perc/100\n",
|
||||
" \n",
|
||||
"probables"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "8b5468aa",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"probables.to_excel('mid_outputs/match_probable_players.xlsx') "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cf992051",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,21 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2022 Giuseppe Musicco
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
+165
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|
||||
<font size = "+3"><b>fantabeto</b></size>
|
||||
|
||||
Fantacalcio Bayesian Estimated Team's Outcome
|
||||
|
||||
<i>Machine learning model for predicting Serie A players performance in a match, in terms of Fantacalcio (italian fantasy football) scores.</i>
|
||||
|
||||
The aim of this project is to predict Fantacalcio (Serie A fantasy football) player performances (vote and fantavote, respectively their match rating and that summed to the bonus/malus given by goals, assists and cards), using players and teams data from http://fantacalcio.it and http://fbref.com.
|
||||
|
||||
"outputs" folder contains predictions for the next Serie A matchdays, and an excel file for analysis. A list of players can be inserted to help selecting an optimal line-up.
|
||||
|
||||
|
||||
|
||||
Two neural network models are trained for predicting vote and fantavote for outfield players and goalkeepers, for which the clean sheet probability is also an output.
|
||||
The outputs of these models are not raw predictions, but probability distributions, in the form of SinhArcsinh, which is a skewed distribution, meaning that the probability density is asymmetric.
|
||||
For predicting clean sheet probability, a Bernoulli distribution is instead used (a sample of which would be clean sheet = 1, with a given probability p, or clean sheet = 0 with probability 1-p)
|
||||
|
||||
See the following code and plot to show an example of vote and fantavote probability distributions.
|
||||
In this case, the player would be an attacking one, whose fantavote distribution is very skewed to the right (it is very more probable to score a goal and receive a 10 = 7+3 fantavote, than having an awful performance with a 4 fantavote!).
|
||||
|
||||
|
||||
```python
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
def sinh_archsinh_pdf(x, mu, sigma, eps, delta):
|
||||
mul = 2 / np.sinh( np.arcsinh(2) * delta)
|
||||
z = (x - mu) / (sigma*mul)
|
||||
S = np.sinh( -eps + (1/delta) * np.arcsinh(z))
|
||||
return np.exp(-0.5 * S * S) * np.sqrt(1 + S * S) / ( sigma * mul * delta ) / np.sqrt(1 + z * z) / np.sqrt(2 * np.pi)
|
||||
|
||||
x = np.arange(start = 0, stop = 30, step = 0.001)
|
||||
pxv = sinh_archsinh_pdf(x, 6.06, 0.62, 0.33, 1.06)
|
||||
pxf = sinh_archsinh_pdf(x, 5.6657, 1.224146, 0.795868, 1.9983)
|
||||
plt.plot(x, pxv, label = 'vote', color = 'b')
|
||||
plt.plot(x, pxf, label = 'fantavote', color = 'g')
|
||||
plt.fill_between(x, pxv, color = 'lightblue')
|
||||
plt.fill_between(x, pxf, color = 'lightgreen')
|
||||
mv = np.average(x, weights = pxv)
|
||||
mf = np.average(x, weights = pxf)
|
||||
plt.vlines(x = mv, color = 'b', ymin = 0, ymax = 3, linestyle = 'dashed', label = 'mean vote = ' + '{:.2f}'.format(mv))
|
||||
plt.vlines(x = mf, color = 'g', ymin = 0, ymax = 3, linestyle = 'dashed', label = 'mean fantavote = ' + '{:.2f}'.format(mf))
|
||||
plt.legend()
|
||||
plt.xlim([0, 20])
|
||||
plt.ylim([0, 1])
|
||||
plt.ylabel('Probability Density')
|
||||
plt.xlabel('Vote')
|
||||
plt.title('Beto (A) estimated performance')
|
||||
plt.show()
|
||||
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
There is code also for computing the expected points outcome of a particular line-up, by sampling multiple times from the players' points distribution and considering bonus for Defense Modifier ("Modificatore") and Clean Sheet. This leads to estimating the team's points probability distribution.
|
||||
|
||||
|
||||
|
||||
Credits:
|
||||
|
||||
http://Fantacalcio.it - The game! And of course, a lot of data, including votes, players list and probable line-ups.
|
||||
|
||||
http://FBRef.com - Plenty of stats for football players and teams.
|
||||
|
||||
https://github.com/amiles2233/ff_prob - Inspiration, for using Tensorflow Probability and Bayesian Neural Networks for this task.
|
||||
|
||||
https://github.com/parth1902/Scrape-FBref-data - FBref data scraping code.
|
||||
|
||||
#fantacalcio #fantasy-football #serie-a
|
||||
|
||||
#machine-learning #ai #neural-networks
|
||||
|
||||
#python #tensorflow #tensorflow-probability
|
||||
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|
||||
player,alike
|
||||
Doig,Lazovic
|
||||
Origi,Rebic
|
||||
Fagioli,Henderson L.
|
||||
Di Maria,Chiesa
|
||||
Ranocchia F.,Henderson L.
|
||||
Piccoli,Lasagna
|
||||
Alvarez A.,Raspadori
|
||||
Ballo-Toure',Calabria
|
||||
Ferguson,Svanberg
|
||||
Bijol,Rodrigo Becao
|
||||
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|
||||
FROM,TO,TEAM
|
||||
stigard,Ostigard,Napoli
|
||||
Min-jae,Kim,Napoli
|
||||
Hjlund,Hojlund,Atalanta
|
||||
Gytkjr,Gytkjaer,Monza
|
||||
Carlos,Augusto,Monza
|
||||
Mhle,Maehle,Atalanta
|
||||
Kjr,Kjaer,Milan
|
||||
uricic,Djuricic,Sampdoria
|
||||
uric,Djuric,Hellas Verona
|
||||
Arthur,Cabral,Fiorentina
|
||||
Martinez,Alvarez,Sassuolo
|
||||
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Reference in New Issue
Block a user