Update app.py

app.py

@@ -108,5 +108,6 @@ def run():
             flat_predictions = [item for sublist in predictions for item in sublist]
             flat_predictions = np.argmax(flat_predictions, axis=1).flatten()#p = [i for i in classifier(tweet_list)]
             df = pd.DataFrame(list(zip(tweet_list, flat_predictions)),columns =['Latest'+str(number_of_tweets)+'Tweets'+' on '+search_words, 'Sexista'])
+            df['Sexista']= np.where(df['Sexista']== 0, 'No Sexista', 'Sexista')
             st.write(df)
 run()