Update app.py

app.py

@@ -104,14 +104,12 @@ def analizar_tweets(search_words, number_of_tweets ):
   text_list = text[0].tolist()
   result = []
   for text in text_list:
-  prediction = pipeline_nlp(text)
-  for predic in prediction:
-    etiqueta = {'Tweets': text,'Prediccion': predic['label'], 'Probabilidad': predic['score']}
-    result.append(etiqueta)
-
+      prediction = pipeline_nlp(text)
+      for predic in prediction:
+          etiqueta = {'Tweets': text,'Prediccion': predic['label'], 'Probabilidad': predic['score']}
+          result.append(etiqueta)
   df = pd.DataFrame(result)
   df['Prediccion'] = np.where( df['Prediccion'] == 'LABEL_1', 'Sexista', 'No Sexista')
-  
   tabla = st.table(df.reset_index(drop=True).head(30).style.applymap(color_survived, subset=['Prediccion']))
     
   return tabla