added 0 price change scenario

get_forecast.py

@@ -35,11 +35,6 @@ def get_forecast(serie: str, periods, percent_change: int):
     forecast = model.predict(future)
 
     future_values = forecast[['ds', 'yhat']]
-    
-    # arrange dataframe
-    df_future = future_values.rename(columns = {'ds': 'Date', 'yhat': serie}).copy()
-    df_future['Date'] = df_future['Date'].apply(lambda x: x.date())
-    df_future[serie] = df_future[serie].apply(lambda x: round(x, 4))
 
     # aux to plot
     last_obs = history.iloc[-1:][['ds', 'y']].rename(columns = {'y': 'yhat'})
@@ -51,6 +46,15 @@ def get_forecast(serie: str, periods, percent_change: int):
     forecast_0 = model.predict(future_0)
     values_0 = forecast_0[['ds', 'yhat']]
     aux_0 = pd.concat([last_obs, values_0])
+    
+    # arrange dataframe
+    df_future = future_values.rename(columns = {'ds': 'Date', 'yhat': serie}).copy()
+    df_future['Date'] = df_future['Date'].apply(lambda x: x.date())
+    df_future[f'No change {serie}'] = values_0.rename(columns = {'ds': 'Date', 'yhat': serie})[serie]
+    df_future['Diff'] = df_future[serie] - df_future[f'No change {serie}']
+    df_future[serie] = df_future[serie].apply(lambda x: round(x, 4))
+    df_future[f'No change {serie}'] = df_future[f'No change {serie}'].apply(lambda x: round(x, 4))
+    df_future['Diff'] = df_future['Diff'].apply(lambda x: round(x, 4))
 
     # plot
     fig = plt.figure()