Update app.py

app.py

@@ -278,7 +278,10 @@ with news_analysis:
     events['Date'] = pd.to_datetime(events['Date'])
     events = events[(events['Date'] >= start_date) & (events['Date'] <= end_date)]
     print(events.shape, events.columns)
-    
+
+    cols = ['Raw_Headline', 'Bold_KW', 'Feature', 'Raw_News', 'Sources', 'Urls']
+    for col in cols:
+        events[col] = events[col].apply(convert_str_to_list)
     # Add a new column for positive values of column A
     events['Positive_Impacts'] = events[events['Events_Impact'] >= 4.7]['Events_Impact']
 
@@ -362,9 +365,7 @@ with news_analysis:
     # pos_news = plot_sub_pos[['Date', 'Raw_Headline', 'Bold_KW', 'Feature', 'Raw_News', 'Sources', 'Urls']]
     # neg_news = plot_sub_neg[['Date', 'Raw_Headline', 'Bold_KW', 'Feature', 'Raw_News', 'Sources', 'Urls']]
     
-    cols = ['Raw_Headline', 'Bold_KW', 'Feature', 'Raw_News', 'Sources', 'Urls']
-    for col in cols:
-        news[col] = news[col].apply(convert_str_to_list)
+    
         # pos_news[col] = pos_news[col].apply(convert_str_to_list)
         # neg_news[col] = neg_news[col].apply(convert_str_to_list)
     # Extract only the date part