Update fixcsv.py

scripts/fixcsv.py

@@ -6,27 +6,10 @@
 def create_directory(path):
     Path(path).mkdir(parents=True, exist_ok=True)
 
-# Function to determine the latest finished gameweek (for logging only)
-def get_latest_finished_gameweek(season_path):
-    """
-    Determines the latest gameweek with at least one finished match.
-    This is kept for informational purposes but not used for filtering.
-    """
-    matches_path = os.path.join(season_path, 'matches', 'matches.csv')
-    matches_df = pd.read_csv(matches_path)
-    # Assuming there's a 'finished' column indicating match status
-    finished_matches = matches_df[matches_df['finished'] == True]
-    if not finished_matches.empty:
-        latest = finished_matches['gameweek'].max()
-    else:
-        latest = 0  # Default if no matches are finished
-    return latest
-
 # Update matches for all gameweeks
 def update_matches_by_gameweek(season_path):
     """
     Processes all gameweeks in matches_df and saves matches per gameweek.
-    No skipping based on latest_finished_gameweek.
     """
     matches_path = os.path.join(season_path, 'matches', 'matches.csv')
     matches_df = pd.read_csv(matches_path)
@@ -46,18 +29,17 @@ def update_matches_by_gameweek(season_path):
 def update_player_match_stats(season_path, matches_df):
     """
     Processes all gameweeks in player match stats, mapping match_id to gameweek.
-    No skipping based on latest_finished_gameweek.
     """
     stats_path = os.path.join(season_path, 'playermatchstats', 'playermatchstats.csv')
     stats_df = pd.read_csv(stats_path)
     gw_base_path = os.path.join(season_path, 'playermatchstats', 'gameweeks')
     create_directory(gw_base_path)
 
-    # Create a mapping from match_id to gameweek using matches_df
+    # Map match_id to gameweek using matches_df
     match_to_gw = matches_df.set_index('match_id')['gameweek'].to_dict()
     stats_df['gameweek'] = stats_df['match_id'].map(match_to_gw)
 
-    # Handle any unmapped gameweeks (e.g., missing matches)
+    # Warn about any stats that don’t map to a gameweek
     if stats_df['gameweek'].isna().any():
         print(f"Warning: {stats_df['gameweek'].isna().sum()} player stats have no matching gameweek.")
 
@@ -66,54 +48,25 @@ def update_player_match_stats(season_path, matches_df):
 
     for gw in stats_df['gameweek'].unique():
         if pd.isna(gw):
-            continue  # Skip if gameweek is NaN
+            continue  # Skip if gameweek is missing
         gw_path = os.path.join(gw_base_path, f'GW{gw}')
         create_directory(gw_path)
         gw_stats = stats_df[stats_df['gameweek'] == gw]
         gw_stats.to_csv(os.path.join(gw_path, 'playermatchstats.csv'), index=False)
         print(f"Updated GW{gw} with {len(gw_stats)} player match stats")
 
-# Update player stats for all gameweeks
-def update_player_stats(season_path):
-    """
-    Processes all gameweeks in player stats.
-    No skipping based on latest_finished_gameweek.
-    """
-    stats_path = os.path.join(season_path, 'playerstats', 'playerstats.csv')
-    stats_df = pd.read_csv(stats_path)
-    gw_base_path = os.path.join(season_path, 'playerstats', 'gameweeks')
-    create_directory(gw_base_path)
-
-    # Assuming stats_df has a 'gameweek' column
-    total_stats = len(stats_df)
-    print(f"Found {total_stats} player stats across all gameweeks")
-
-    for gw in stats_df['gameweek'].unique():
-        gw_path = os.path.join(gw_base_path, f'GW{gw}')
-        create_directory(gw_path)
-        gw_stats = stats_df[stats_df['gameweek'] == gw]
-        gw_stats.to_csv(os.path.join(gw_path, 'playerstats.csv'), index=False)
-        print(f"Updated GW{gw} with {len(gw_stats)} player stats")
-
 # Main execution function
 def main():
     season = "2024-2025"
     season_path = os.path.join('data', season)
 
-    # Calculate latest finished gameweek for logging (optional)
-    latest_finished_gameweek = get_latest_finished_gameweek(season_path)
-    print(f"Latest gameweek with at least one finished match: {latest_finished_gameweek}")
-
-    # Process all gameweeks for matches, player match stats, and player stats
-    print("\nUpdating matches by gameweek...")
+    # Process all gameweeks for matches and player match stats
+    print("Updating matches by gameweek...")
     matches_df = update_matches_by_gameweek(season_path)
 
     print("\nUpdating player match stats by gameweek...")
     update_player_match_stats(season_path, matches_df)
 
-    print("\nUpdating player stats by gameweek...")
-    update_player_stats(season_path)
-
     print("\nProcessing complete.")
 
 if __name__ == "__main__":