enhanced admin panel

app.py

@@ -349,13 +349,23 @@ ADMIN_PASSPHRASE = "admin123"
 
 
 def fetch_latest_predictions(match_id):
-    dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", name="predictions")
-    # Convert to pandas DataFrame
+    # Load the dataset. Adjust "split" to "train" or appropriate if "predictions" is a configuration.
+    dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "predictions", split='train')
+
+    # Convert the dataset to a pandas DataFrame
     df = pd.DataFrame(dataset)
-    # Remove duplicate rows
-    df_unique = df.drop_duplicates(subset=['user_name'])
-    predictions = df_unique['train'].filter(lambda example: example['match_id'] == match_id)
-    return predictions
+
+    # Ensure the DataFrame is not empty and contains the required columns
+    if not df.empty and {'user_name', 'match_id'}.issubset(df.columns):
+        # Filter rows by 'match_id'
+        filtered_df = df[df['match_id'] == match_id]
+
+        # Drop duplicate rows based on 'user_name'
+        unique_df = filtered_df.drop_duplicates(subset=['user_name'])
+
+        return unique_df
+    else:
+        return pd.DataFrame()
 
 
 def save_match_outcomes(outcomes):
@@ -369,7 +379,7 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
 
     outcomes = load_data(OUTCOMES_JSON)  # Load existing match outcomes
     # Load existing match outcomes and user data from the test split
-    dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", name="leaders")
+    dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
     users = pd.DataFrame(dataset)
 
     # Directly update or add the match outcome