def get_preds(x):
train = x.iloc[first_day_idx - history:first_day_idx]
train.index = pd.to_datetime(calendar[calendar['d'].isin(
train.index)].date)
train = pd.DataFrame({'date': train.index, 'sales': train.values})
model = ExponentialSmoothing(np.asarray(train['sales']))
model._index = pd.to_datetime(train.index.values).astype(
np.int64) // 10**9
fit1 = model.fit(smoothing_level=.1, smoothing_slope=.1)
return fit1.forecast(28)
