Update app.py

app.py

@@ -144,22 +144,23 @@ def tweets_localidad(buscar_localidad):
         location = geolocator.geocode(buscar_localidad)
         radius = "10km"
         tweets = api.search_tweets(q="",lang="es",geocode=f"{location.latitude},{location.longitude},{radius}", count = 50, tweet_mode="extended")
+        
+        tweet_list = [i.full_text for i in tweets]
+        text= pd.DataFrame(tweet_list)
+        text[0] = text[0].apply(preprocess)
+        text_list = text[0].tolist()
+        result = []
+        for text in text_list:
+            if (text.startswith('RT')):
+                continue
+            else:
+                prediction = pipeline_nlp(text)
+                for predic in prediction:
+                    etiqueta = {'Tweets': text,'Prediccion': predic['label'], 'Probabilidad': predic['score']}
+                    result.append(etiqueta) 
     except AttributeError:
         st.text("No existe ninguna localidad con ese nombre") 
-        
-    tweet_list = [i.full_text for i in tweets]
-    text= pd.DataFrame(tweet_list)
-    text[0] = text[0].apply(preprocess_tweet)
-    text_list = text[0].tolist()
-    result = []
-    for text in text_list:
-        if (text.startswith('RT')):
-            continue
-        else:
-            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']))