multi_rank.py

def rank_dataframe(df, ascending_cols=None):
    if ascending_cols is None:
        ascending_cols = []

    numeric_cols = df.select_dtypes(include=["number"]).columns
    ranks = df[numeric_cols].apply(
        lambda x: x.rank(
            method="min", na_option="bottom", ascending=x.name in ascending_cols
        )
    )
		
    scaled_ranks = (ranks - 1) / (len(ranks.columns) - 1)
    scaled_df = df.iloc[scaled_ranks.sum(axis=1).sort_values().index]
    return scaled_df.reset_index(drop=True)