SARIMAX_example.py

SARIMAX_example.py

    model = SARIMAX(data1, exog=data2, order=(1, 1, 2), seasonal_order=(1, 1, 1, 52))
    model_fit = model.fit(disp=False)
    print(f"Global: {model_fit.summary()}")
    
    
    for site in sites:
        # make prediction
        newdfinner = df_site.loc[df_site.site == site, :].fillna(0).reset_index(drop=True)
        exog2 = newdfinner.loc[
            newdfinner["start_week_dt"] >= last_sunday, ["exog1", "exog2"]
        ].astype("float64")
        yhat = model_fit.predict(
            newdfinner[newdfinner["start_week_dt"] == last_sunday].index[0],
            newdfinner.iloc[len(newdfinner) - 1, :].name,
            exog=exog2,
        )