def process_benchmark_df(df_input):
    """Take in the featurized the benchmark dataframe and clean it up"""
    # select the relevant columns
    df_output = df_input[["formula", "avg_mx_dists", "avg_mm_dists", "iv", "iv_p1",
                          "v_m", "v_x", "est_hubbard_u", "est_charge_trans"]]
    # rename the column names to match those found in torrance_tabulated.xlsx
    df_output = df_output.rename(columns={"avg_mx_dists": "d_mo", "avg_mm_dists": "d_mm", "v_x": "v_o",
                                          "est_hubbard_u": "hubbard", "est_charge_trans": "charge_transfer"})
    # drop rows containing NA values, sort by the formula and reindex the dataframe
    return df_output.dropna().sort_values("formula").reset_index(drop=True)