Pandas DataFrame 分組求和、分組乘積

import numpy as np
import pandas as pd
pd.set_option('display.max_columns', 10)

# 刪除空數據
def DropNan(data_qd):
    for i in range(len(data_qd)):
        if np.isnan(data_qd['test_uniq_cnt'][i]) or \
                np.isnan(data_qd['fail_uniq_cnt'][i]):
            data_qd = data_qd.drop(i)
    return data_qd


def GetGroupSum(df, lst_merge):
    pop_group = df.groupby(lst_merge).sum().reset_index().\
        rename(columns = {'test_uniq_cnt':'sum_test_cnt','fail_uniq_cnt':'sum_fail_cnt'})
    pop_group['Percentofpass'] = pop_group.\
        apply(lambda x: -99999 if x.sum_test_cnt == 0 or np.isnan(x.sum_test_cnt) or np.isnan(x.sum_fail_cnt) \
        else 1 - float(x.sum_fail_cnt)/x.sum_test_cnt, axis = 1)

    return pop_group


def GetGroupProd(df, lst_group):
    fpy_group = df.groupby(lst_group).\
        apply(lambda x: '無生產' if x['Percentofpass'].max(axis = 0) < 0 \
        else 'NA' if x['Percentofpass'].min(axis = 0) < 0 \
        else x['Percentofpass'].cumprod(axis = 0).iloc[-1]).reset_index()
    fpy_group.columns = lst_group + ['fpy']
    return fpy_group