import numpy as np
import pandas as pd
from sktime.forecasting.base import ForecastingHorizon
from sktime.forecasting.naive import NaiveForecaster

data = pd.Series(
    index=pd.date_range(
        "2021-06-01 00:00", periods=12, freq="1h", closed="left"
    ),
    data=[1, 2, 3, 1, 2, 3, np.nan, 2, 3, 1, 2, 3]
)
train_data = data[:7]
test_data = data[7:]

print(train_data)
# 2021-06-01 00:00:00    1.0
# 2021-06-01 01:00:00    2.0
# 2021-06-01 02:00:00    3.0
# 2021-06-01 03:00:00    1.0
# 2021-06-01 04:00:00    2.0
# 2021-06-01 05:00:00    3.0
# 2021-06-01 06:00:00    NaN
# Freq: H, dtype: float64

fh = ForecastingHorizon(test_data.index, is_relative=False)
model = NaiveForecaster(strategy="last", sp=3)
model.fit(train_data)
forecast_data = model.predict(fh)

print(forecast_data)
# 2021-06-01 07:00:00    2.0
# 2021-06-01 08:00:00    3.0
# 2021-06-01 09:00:00    NaN  # Let's make this a 1
# 2021-06-01 10:00:00    2.0
# 2021-06-01 11:00:00    3.0
# dtype: float64