def kpi_transform()

in causalml/inference/tree/utils.py [0:0]

• 30 lines of code
• 4 McCabe index (conditional complexity)

def kpi_transform(dfx, kpi_combo, kpi_combo_new):
    '''
    Feature transformation from continuous feature to binned features for a list of features

    Args
    ----

    dfx : DataFrame
        DataFrame containing the features.

    kpi_combo : list of string
        List of feature names to be transformed

    kpi_combo_new : list of string
        List of new feature names to be assigned to the transformed features.

    Returns
    -------
    dfx : DataFrame
        Updated DataFrame containing the new features.
    '''
    for j in range(len(kpi_combo)):
        if type(dfx[kpi_combo[j]].values[0]) == str:
            dfx[kpi_combo_new[j]] = dfx[kpi_combo[j]].values
            dfx[kpi_combo_new[j]] = cat_group(dfx=dfx, kpix=kpi_combo_new[j])
        else:
            if len(kpi_combo) > 1:
                dfx[kpi_combo_new[j]] = cat_continuous(
                    dfx[kpi_combo[j]].values, granularity='Low'
                )
            else:
                dfx[kpi_combo_new[j]] = cat_continuous(
                    dfx[kpi_combo[j]].values, granularity='High'
                )
    return dfx