generate_future_features

df_forecast['value'] = 0
df_forecast= (df_forecast
              .assign(hour = df_forecast.index.hour)
              .assign(day = df_forecast.index.day)
              .assign(month = df_forecast.index.month)
              .assign(day_of_week = df_forecast.index.dayofweek)
              .assign(week_of_year = df_forecast.index.week)
              )

df_forecast = onehot_encode_pd(df_forecast, ['month','day','day_of_week','week_of_year'])
df_forecast = generate_cyclical_features(df_forecast, 'hour', 24, 0)
df_forecast = add_holiday_col(df_forecast, us_holidays)
df_forecast[list(set(X_train.columns)-set(df_forecast.columns))] = 0