Refactor player iteration logic in hedging_preset.py to improve clarity and accuracy in lineup filtering. Changed variable names for consistency and adjusted mask conditions to enhance player selection criteria.

global_func/hedging_preset.py

@@ -14,18 +14,18 @@ def hedging_preset(portfolio: pd.DataFrame, lineup_target: int, projections_file
 
     concat_portfolio = pd.DataFrame(columns=portfolio.columns)
 
-    for players in top_owned:
-        print(players)
+    for player in top_owned:
+        print(player)
         working_df = portfolio.copy()
 
         # Create mask for lineups that contain any of the removed players
         player_columns = [col for col in working_df.columns if col not in excluded_cols]
 
         remove_mask = working_df[player_columns].apply(
-            lambda row: not any(player in list(row) for player in players), axis=1
+            lambda row: player not in list(row), axis=1
         )
         lock_mask = working_df[player_columns].apply(
-            lambda row: all(player in list(row) for player in players), axis=1
+            lambda row: player in list(row), axis=1
         )
 
         removed_df = working_df[remove_mask]