Handling the model alias field

app/backend/data_engine.py

@@ -125,6 +125,10 @@ class DataEngine:
             df_model_extended = df_model
 
         df = pd.merge(df_result, df_dataset, on=["dataset_name"], how="inner")
+
+        # set dataset default value to 0
+        df = df.pivot(index=["model_name", "embd_dim", "embd_dtype", "group_name"], columns="dataset_name",
+                 values=["ndcg_at_10"]).fillna(0).stack(level=1).reset_index()
         # df = pd.merge(df, df_model, on=["model_name"], how="inner")
 
         # dataset_num_map = {}
@@ -140,13 +144,13 @@ class DataEngine:
         }).reset_index()
 
         pivot = grouped_model.pivot(index=["model_name", "embd_dim", "embd_dtype"], columns="group_name",
-                                    values=["ndcg_at_10"]).round(2)
+                                    values=["ndcg_at_10"]).round(2).fillna(0)
 
         # Rename columns
         pivot.columns = list(
             map(lambda x: f"{x[1].capitalize()} Average" if x[1] != 'text' else f"Average", pivot.columns))
 
-        pivot_dataset = df_result.pivot(index=["model_name", "embd_dim", "embd_dtype"], columns="dataset_name", values="ndcg_at_10")
+        pivot_dataset = df_result.pivot(index=["model_name", "embd_dim", "embd_dtype"], columns="dataset_name", values="ndcg_at_10").fillna(0)
 
         df = pd.merge(df_model_extended, pivot, on=["model_name", "embd_dim", "embd_dtype"])
         df = pd.merge(df, pivot_dataset, on=["model_name", "embd_dim", "embd_dtype"])