Comment out the column drop logic in reassess_edge function to retain additional data for debugging purposes, enhancing flexibility in data handling.

global_func/reassess_edge.py

@@ -118,6 +118,6 @@ def reassess_edge(refactored_frame: pd.DataFrame, original_frame: pd.DataFrame,
         refactored_df.loc[lineups, 'Weighted Own'] = calculate_weighted_ownership_single_row(refactored_df.loc[lineups, own_columns])
         refactored_df.loc[lineups, 'Geomean'] = np.power((refactored_df.loc[lineups, own_columns] * 100).product(), 1 / len(own_columns))
     
-    refactored_df = refactored_df.drop(columns=['salary_diff', 'median_diff', 'own_diff', 'player_0_own', 'Edge'] + own_columns)
+    # refactored_df = refactored_df.drop(columns=['salary_diff', 'median_diff', 'own_diff', 'player_0_own', 'Edge'] + own_columns)
 
     return refactored_df