Update app.py

app.py

@@ -21,13 +21,19 @@ predictions_df['Sentiment'] = predictions_df['Sentiment'].map({0: 'Negative', 1:
 def article_selection(sentiment):
     if sentiment == "Positive":
         predictions = negative_preds
-        predictions_df_url0 = predictions['Url'].iloc[0]
-        predictions_df_head0 = predictions['Headlines_string'].iloc[0]
-        predictions_df_url1 = predictions['Url'].iloc[1]
-        predictions_df_head1 = predictions['Headlines_string'].iloc[1]
-        predictions_df_url2 = predictions['Url'].iloc[2]
-        predictions_df_head2 = predictions['Headlines_string'].iloc[2]
-        return [[predictions_df_head0, predictions_df_url0], [predictions_df_head1, predictions_df_url1], [predictions_df_head2, predictions_df_url2]]
+        top3 = predictions[0:3]
+        top3_result = top3[['Headline_string','Url']]
+        top3_result.rename(columns = {'Headline_str':'Headlines', 'Url':'URL'})
+       # predictions_df_url0 = predictions['Url'].iloc[0]
+       # predictions_df_head0 = predictions['Headline_string'].iloc[0]
+       # predictions_df_url1 = predictions['Url'].iloc[1]
+       # predictions_df_head1 = predictions['Headline_string'].iloc[1]
+       # predictions_df_url2 = predictions['Url'].iloc[2]
+       # predictions_df_head2 = predictions['Headline_string'].iloc[2]
+       # predictions_df = [[predictions_df_head0, predictions_df_url0], [predictions_df_head1, predictions_df_url1], [predictions_df_head2, predictions_df_url2]]
+       # negative_df = pd.DataFrame(negative_df, columns=['Headline','URL'])
+        return top3_result
+    
     elif sentiment == "Negative":
         predictions = negative_preds
         predictions_df_url0 = predictions['Url'].iloc[0]