def _create_component_masks(
        untransformed_stat_covs: pd.DataFrame,
        cols_num: Sequence[str],
        cols_cat: Sequence[str],
    ):
        """
        Returns a boolean array indicating which components of the UNTRANSFORMED
        `stat_covs` are numerical and a boolean array indicating which components
        of the UNTRANSFORMED `stat_covs` are categorical.

        It's important to recognize that these masks only apply to the UNTRANSFORMED
        static covariates since some transformations can generate multiple new components
        from a single component (e.g. one-hot encoding).
        """
        mask_num = untransformed_stat_covs.columns.isin(cols_num)
        mask_cat = untransformed_stat_covs.columns.isin(cols_cat)
        return mask_num, mask_cat

        Returns a boolean array indicating which components of the UNTRANSFORMED
        `stat_covs` are numerical and a boolean array indicating which components
        of the UNTRANSFORMED `stat_covs` are categorical.

        It's important to recognize that these masks only apply to the UNTRANSFORMED
        static covariates since some transformations can generate multiple new components
        from a single component (e.g. one-hot encoding).
        
darts/dataprocessing/transformers/static_covariates_transformer.py