updating show preds

app.py

@@ -235,17 +235,18 @@ def display_predictions():
         # Convert the list of dictionaries to a DataFrame
         predictions_df = pd.DataFrame(all_predictions)
 
-        predictions_df['prediction_date'] = predictions_df.apply(lambda x: datetime.strptime(x['prediction_date'], '%Y-%m-%d'), axis=1)
+        if not predictions_df.empty:
+            predictions_df['prediction_date'] = predictions_df.apply(lambda x: datetime.strptime(x['prediction_date'], '%Y-%m-%d'), axis=1)
 
-        # Filter for today's predictions
-        today_str = datetime.now().strftime('%Y-%m-%d')
-        todays_predictions = predictions_df[predictions_df['prediction_date'] == today_str]
+            # Filter for today's predictions
+            today_str = datetime.now().strftime('%Y-%m-%d')
+            todays_predictions = predictions_df[predictions_df['prediction_date'] == today_str]
 
-        # Remove the 'prediction_id' column if it exists
-        if 'prediction_id' in todays_predictions.columns:
-            todays_predictions = todays_predictions.drop(columns=['prediction_id', 'prediction_date'])
+            # Remove the 'prediction_id' column if it exists
+            if 'prediction_id' in todays_predictions.columns:
+                todays_predictions = todays_predictions.drop(columns=['prediction_id', 'prediction_date'])
 
-        if not todays_predictions.empty:
+        
             st.dataframe(todays_predictions, hide_index=True)
         else:
             st.write("No predictions for today's matches yet.")