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import pandas as pd
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import sqlite3
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import streamlit as st
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from pathlib import Path
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@st.cache_data
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def load_data():
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"""Charge les données depuis le fichier CSV"""
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try:
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data_path = Path(__file__).parent.parent.parent / "data/transformed/Rugby_Stats.csv"
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df = pd.read_csv(data_path)
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return df
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except Exception as e:
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st.error(f"Impossible de charger les données : {e}")
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return pd.DataFrame()
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@st.cache_data
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def load_from_database():
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"""Charge les données depuis la base SQLite"""
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try:
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db_path = Path(__file__).parent.parent.parent / "data/transformed/Rugby_Stats.db"
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conn = sqlite3.connect(db_path)
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query = '''
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SELECT j.prenom, j.nom, m.nom_match, s.numero, a.nom_action,
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n.id_niveau, s.nb_actions
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FROM Statistiques s
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JOIN Joueuse j ON s.id_joueuse = j.id_joueuse
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JOIN Match m ON s.id_match = m.id_match
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JOIN Action a ON s.id_action = a.id_action
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JOIN Niveau n ON s.id_niveau = n.id_niveau
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'''
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df = pd.read_sql_query(query, conn)
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conn.close()
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return df
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except Exception as e:
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st.error(f"Impossible de charger depuis la base : {e}")
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return pd.DataFrame()
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def get_database_stats():
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"""Retourne les statistiques générales de la base"""
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try:
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db_path = Path(__file__).parent.parent.parent / "data/transformed/Rugby_Stats.db"
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conn = sqlite3.connect(db_path)
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nb_joueuses = pd.read_sql_query("SELECT COUNT(*) as count FROM Joueuse", conn).iloc[0]['count']
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nb_matchs = pd.read_sql_query("SELECT COUNT(*) as count FROM Match", conn).iloc[0]['count']
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nb_stats = pd.read_sql_query("SELECT COUNT(*) as count FROM Statistiques", conn).iloc[0]['count']
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conn.close()
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return {
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'nb_joueuses': nb_joueuses,
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'nb_matchs': nb_matchs,
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'nb_stats': nb_stats
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}
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except Exception as e:
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return {'nb_joueuses': 0, 'nb_matchs': 0, 'nb_stats': 0}
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def get_player_stats(df, player_name=None):
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"""Retourne les statistiques d'une joueuse spécifique"""
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if player_name:
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return df[df['Nom'].str.contains(player_name, case=False, na=False)]
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return df
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def get_match_stats(df, match_name=None):
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"""Retourne les statistiques d'un match spécifique"""
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if match_name:
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return df[df['Match'] == match_name]
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return df |
