【发布时间】:2018-10-16 22:39:43
【问题描述】:
我希望将自定义工作日偏移列添加到日期列:
>> import pandas as pd
>> from pandas.tseries.offsets import CustomBusinessDay
>> df = pd.DataFrame({'ship_date_et': ['2018-10-01' for x in range(10)], 'offset': [x for x in range(10)]})
>> df['offset'] = pd.to_timedelta(df['offset'], unit='D')
>> df['ship_date_et'] = pd.to_datetime(df['ship_date_et'])
>> df.dtypes
offset timedelta64[ns]
ship_date_et datetime64[ns]
>> df
offset ship_date_et
0 0 days 2018-10-01
1 1 days 2018-10-01
2 2 days 2018-10-01
3 3 days 2018-10-01
4 4 days 2018-10-01
5 5 days 2018-10-01
6 6 days 2018-10-01
7 7 days 2018-10-01
8 8 days 2018-10-01
9 9 days 2018-10-01
>> holidays = ['2018-10-10'] # '2018-10-10' just a made-up holiday
>> cdays = CustomBusinessDay(holidays=holidays, weekmask='Mon Tue Wed Thu Fri')
>> df['ship_date_et'] + df['offset'].apply(cdays)
0 2018-10-02
1 2018-10-03
2 2018-10-04
3 2018-10-05
4 2018-10-06
5 2018-10-07
6 2018-10-08
7 2018-10-09
8 2018-10-10
9 2018-10-11
dtype: datetime64[ns]
这是疯狂的错误。未计算周末(2018-10-06 和 2018-10-07)(Pandas 文档称CDay 包含周末)。这与我只定义了 2 weekmask 天(周一和周二)无关。
我真的很困惑和沮丧,因为这适用于正常的BDay:
>> df['ship_date_et'] + df['offset'].dt.days.apply(BDay) # Doing dt.days to get integer for BDay since we defined df['offset'] as a `timedelta`
0 2018-10-01
1 2018-10-02
2 2018-10-03
3 2018-10-04
4 2018-10-05
5 2018-10-08
6 2018-10-09
7 2018-10-10
8 2018-10-11
9 2018-10-12
我想要的结果:
>> df['ship_date_et'] + df['offset'].apply(cdays)
0 2018-10-01
1 2018-10-02
2 2018-10-03
3 2018-10-04
4 2018-10-05
5 2018-10-08
6 2018-10-09
7 2018-10-11
8 2018-10-12
9 2018-10-15
我已阅读文档(包括 numpy busday 和 Pandas)并搜索了互联网,例如 here 和 here),但找不到发生这种情况的原因。最令人担忧的部分是我的cdays 定义,index=0 是0 days,但结果返回我的ship_date_et days + 1。
当然,使用apply 也有一个问题:
PerformanceWarning: Adding/subtracting array of DateOffsets to Series not vectorized "Series not vectorized"
熊猫给予。
如果有任何反馈或意见,我将不胜感激。谢谢!
【问题讨论】: