Update app.py

app.py

@@ -15,6 +15,8 @@ grouped_predictions = predictions_df.groupby(predictions_df.Sentiment)
 #neutral_preds = grouped_predictions.get_group(1)
 negative_preds = grouped_predictions.get_group(0)
 
+predictions_df['Sentiment'] = predictions_df['Sentiment'].map({0: 'Negative', 1: 'Neutral', 2: 'Positive'})
+
 
 def article_selection(sentiment):
     if sentiment == "Positive":
@@ -37,9 +39,6 @@ def article_selection(sentiment):
         return predictions_df_url0, predictions_df_url1, predictions_df_url2
 
 def manual_label():
-    # Encoding sentiment data
-    predictions_df['Sentiment'] = predictions_df['Sentiment'].map({0: 'Negative', 1: 'Neutral', 2: 'Positive'})
-
     # Selecting random row from batch data
     random_sample = predictions_df.sample()
     random_headline = random_sample['Headline_string'].iloc[0]