Update app.py

app.py

@@ -39,17 +39,6 @@ city = "Guangzhou"
 df_weather = get_weather_data_weekly(city, today)
 df_weather.date = df_weather.date.apply(timestamp_2_time)
 df_weather_x = df_weather.drop(columns=["date"]).fillna(0)
-df_weather_nn=np.array(df_weather_x)
-scaler = StandardScaler()
-scaler.fit(df_weather_x)
-
-df_weather_use=scaler.transform(df_weather_x)
-
-df_weather_use_1= pd.DataFrame(df_weather_use)
-
-#preds_zzz = model.predict(df_weather_use_1).astype(int)
-
-st.write(36 * "-")
 
 ########################根据模型名称进行修改#####################
 mr = project.get_model_registry()
@@ -60,7 +49,7 @@ model = joblib.load(model_dir + "/AIR_Forecast_Model.pkl")
 st.write("-" * 36)
 
 
-preds = model.predict(df_weather_use_1).astype(int)
+preds = model.predict(df_weather_x).astype(int)
 pollution_level = get_aplevel(preds.T.reshape(-1, 1))
 
 next_week = [f"{(today + timedelta(days=d)).strftime('%Y-%m-%d')},{(today + timedelta(days=d)).strftime('%A')}" for d in range(8)]