def _process_imp(imp_df, imp_name):
    """
    Preprocessing on the input feature importance dataframe

    :param imp_df: feature importance pandas dataframe
    :param imp_name: column name of the importance value
    :return:
        dataframe with relative_imp and feat_rank
    """

    imp_df = imp_df.sort_values(
        by=imp_name,
        ascending=False).reset_index(
        drop=True)
    imp_df['relative_imp'] = imp_df[imp_name] * 1.0 / imp_df[imp_name].max()
    imp_df['relative_imp'] = imp_df['relative_imp'].apply(
        lambda x: round(x, 3))
    imp_df['feat_rank'] = imp_df.index.values + 1
    return imp_df