debug

src/populate.py

@@ -222,20 +222,21 @@ def create_intervention_averaged_df(df: pd.DataFrame) -> pd.DataFrame:
 #     return detailed_df
 
 def get_leaderboard_df_mib_causalgraph(results_path: str, requests_path: str, cols: list, benchmark_cols: list) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
-    """Creates three dataframes from all the MIB causal graph experiment results"""
     print(f"results_path is {results_path}, requests_path is {requests_path}")
     raw_data = get_raw_eval_results_mib_causalgraph(results_path, requests_path)
-    print(f"raw_data is {raw_data}")
     
     # Convert each result to dict format for detailed df
     all_data_json = [v.to_dict() for v in raw_data]
     detailed_df = pd.DataFrame.from_records(all_data_json)
+    print("Columns in detailed_df:", detailed_df.columns.tolist())  # Print actual columns
     
     # Create aggregated df
     aggregated_df = aggregate_methods(detailed_df)
+    print("Columns in aggregated_df:", aggregated_df.columns.tolist())
     
     # Create intervention-averaged df
     intervention_averaged_df = create_intervention_averaged_df(aggregated_df)
+    print("Columns in intervention_averaged_df:", intervention_averaged_df.columns.tolist())
     
     return detailed_df, aggregated_df, intervention_averaged_df