FEATURES["past_covariates_final"] = []
for col in FEATURES["past_covariates"]:
    new_features = data_preprocess[col].to_frame().copy()
    # Lag Features
    new_features[col+"_L7D"] = new_features[col].shift(7)
    new_features[col+"_L14D"] = new_features[col].shift(14)
    new_features[col+"_L21D"] = new_features[col].shift(21)

    # Rolling Features
    # Shift to move the new features into the prediction space (2019-01-01 to 2019-01-07)
    new_features[col+"_RMean14D"] = new_features[col].shift(7).rolling('14D').mean()

    # Differencing Features
    # Shift to move the new features into the prediction space (2019-01-01 to 2019-01-07)
    new_features[col+"_Diff7D"] = (new_features[col].shift(7) - new_features[col].shift(7).shift(7))

    FEATURES["past_covariates_final"].extend([col+"_L7D", col+"_L14D", col+"_L21D", col+"_RMean14D", col+"_Diff7D"])
    new_features = new_features.drop(columns=col)
    data_preprocess = pd.concat([data_preprocess, new_features], axis=1)

assert len(data_preprocess.loc[:, FEATURES["past_covariates_final"]].columns) == len(FEATURES["past_covariates"])*5