Update app.py

app.py

@@ -156,7 +156,7 @@ 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 =['Últimos '+ str(number_of_tweets)+' Tweets'+' de '+search_words, 'Sexista'])
-                df['Sexista']= np.where(df['Sexista']== 0, 'No Sexista', 'Sexista')
+                df['Sexi']= np.where(df['Sexi']== 0, 'No Sexistas', 'Sexistas')
                 
                 
                 st.table(df.reset_index(drop=True).head(20).style.applymap(color_survived, subset=['Sexista']))