changed labels

get_forecast.py

@@ -48,12 +48,14 @@ def get_forecast(serie: str, periods, percent_change: int):
     aux_0 = pd.concat([last_obs, values_0])
     
     # arrange dataframe
-    df_future = future_values.rename(columns = {'ds': 'Date', 'yhat': f'{serie} with price policy change'}).copy()
+    df_future = future_values.rename(columns = {'ds': 'Date', 'yhat': f'{serie} changing prices'}).copy()
     df_future['Date'] = df_future['Date'].apply(lambda x: x.date())
-    df_future[f'{serie} without policy change'] = values_0.rename(columns = {'ds': 'Date', 'yhat': serie})[serie]
-    df_future['Diff'] = df_future[f'{serie} with price policy change'] - df_future[f'{serie} without policy change']
-    df_future[f'{serie} with price policy change'] = df_future[f'{serie} with price policy change'].apply(lambda x: round(x, 4))
-    df_future[f'{serie} without policy change'] = df_future[f'{serie} without policy change'].apply(lambda x: round(x, 4))
+    df_future[f'{serie} holding prices'] = values_0.rename(columns = {'ds': 'Date', 'yhat': serie})[serie]
+    df_future['Diff'] = df_future[f'{serie} changing prices'] - df_future[f'{serie} holding prices']
+    
+    # round values to 4 decimals
+    df_future[f'{serie} changing prices'] = df_future[f'{serie} changing prices'].apply(lambda x: round(x, 4))
+    df_future[f'{serie} holding prices'] = df_future[f'{serie} holding prices'].apply(lambda x: round(x, 4))
     df_future['Diff'] = df_future['Diff'].apply(lambda x: round(x, 4))
 
     # plot