Python aggregate_single_columns_means Exemples

Exemple #1

def prepare_data(gened_column, heinz_column):
    gened_column='rpm' 
    heinz_column='n'
    vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)
    vehdata['pmr'] = 1000.0 * vehdata['rated_power'] / vehdata['kerb_mass']

    return vehdata.pmr, vehdata.gened, vehdata.heinz

Exemple #2

def prepare_data(gened_column, heinz_column):
    gened_column='rpm' 
    heinz_column='n'
    vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)
    vehdata['pmr'] = 1000.0 * vehdata['rated_power'] / vehdata['kerb_mass']

    return vehdata.pmr, vehdata.gened, vehdata.heinz

Exemple #3

Fichier : pmr_n_scatter.py Projet : JRCSTU/wltp

def data_meanN_pmr(gened_column, heinz_column):
    gened_column='rpm'
    heinz_column='n'
    vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)

    return vehdata

Exemple #4

Fichier : pmr_n_scatter.py Projet : wbyjason/wltp

def data_meanN_pmr(gened_column, heinz_column):
    gened_column = 'rpm'
    heinz_column = 'n'
    vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)

    return vehdata