您应该使用
CustomBusinessHour和
pd.date_range代替
pd.bdate_range。
第二行的小时数应为145，因为结束时间为
09:31:39.967。
us_bh = CustomBusinessHour(calendar=USFederalHolidayCalendar())df['count'] = df.apply(lambda x: len(pd.date_range(start=x.start, end=x.end, freq= us_bh)),axis=1)df['diff'] = df.apply(lambda x: pd.date_range(start=x.start, end=x.end, freq= us_bh),axis=1)print(df) start end count diff0 2018-10-29 18:48:46.697 2018-10-31 17:56:38.830 16 DatetimeIndex(['2018-10-30 09:00:00', '2018-10...1 2018-10-29 19:01:10.887 2018-11-27 09:31:39.967 145 DatetimeIndex(['2018-10-30 09:00:00', '2018-10...2 2018-10-22 17:42:24.467 2018-11-28 18:33:35.243 200 DatetimeIndex(['2018-10-23 09:00:00', '2018-10...
而
diff列创业小时的意志
'2018-10-29 09:00:00'，当你使用
pd.bdate_range。
us_bh = CustomBusinessHour(calendar=USFederalHolidayCalendar())df['count'] = df.apply(lambda x: len(pd.bdate_range(start=x.start, end=x.end, freq= us_bh)),axis=1)df['diff'] = df.apply(lambda x: pd.bdate_range(start=x.start, end=x.end, freq= us_bh),axis=1)print(df) start end count diff0 2018-10-29 18:48:46.697 2018-10-31 17:56:38.830 16 DatetimeIndex(['2018-10-29 09:00:00', '2018-10...1 2018-10-29 19:01:10.887 2018-11-27 09:31:39.967 152 DatetimeIndex(['2018-10-29 09:00:00', '2018-10...2 2018-10-22 17:42:24.467 2018-11-28 18:33:35.243 200 DatetimeIndex(['2018-10-22 09:00:00', '2018-10...
