Update app.py

app.py

@@ -140,7 +140,7 @@ def tweets_localidad(buscar_localidad):
         geolocator = Nominatim(user_agent="nombre_del_usuario")
         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")
+        tweets = api.search_tweets(q="",lang="es",geocode=f"{location.latitude},{location.longitude},{radius}", count = 30, tweet_mode="extended")
         
         tweet_list = [i.full_text for i in tweets]
         text= pd.DataFrame(tweet_list)
@@ -158,8 +158,9 @@ def tweets_localidad(buscar_localidad):
         df = pd.DataFrame(result)
         df['Prediccion'] = np.where( df['Prediccion'] == 'LABEL_1', 'Sexista', 'No Sexista')
         df['Probabilidad'] = df['Probabilidad'].apply(lambda x: '{:.2f}%'.format(x))
-        df=df[df["Prediccion"] == 'Sexista']
-        tabla = st.table(df.reset_index(drop=True).head(50).style.applymap(color_survived, subset=['Prediccion']))
+        df.sort_values(by='Probabilidad', ascending=False, inplace=True)
+        #df=df[df["Prediccion"] == 'Sexista']
+        tabla = st.table(df.reset_index(drop=True).head(30).style.applymap(color_survived, subset=['Prediccion']))
                     
         df_sexista = df[df['Prediccion']=="Sexista"]
         df_no_sexista = df[df['Prediccion']=="No Sexista"]
@@ -177,6 +178,8 @@ def tweets_localidad(buscar_localidad):
         centre_circle = plt.Circle((0,0),0.70,fc='white')
         fig = plt.gcf()
         fig.gca().add_artist(centre_circle)
+        fig1.set_size_inches(6, 6)
+        
 
         # Equal aspect ratio ensures that pie is drawn as a circle
         ax1.axis('equal')