计算DataFrame Pandas中“时间”行之间的差异 [英] Calculate difference between 'times' rows in DataFrame Pandas

问题描述

我的DataFrame的格式为：

My DataFrame is in the Form:

       TimeWeek   TimeSat  TimeHoli
0      6:40:00   8:00:00   8:00:00
1      6:45:00   8:05:00   8:05:00
2      6:50:00   8:09:00   8:10:00
3      6:55:00   8:11:00   8:14:00
4      6:58:00   8:13:00   8:17:00
5      7:40:00   8:15:00   8:21:00

我需要在TimeWeek，TimeSat中找到每一行之间的时差和TimeHoli，输出必须为

I need to find the time difference between each row in TimeWeek , TimeSat and TimeHoli, the output must be

TimeWeekDiff   TimeSatDiff  TimeHoliDiff
00:05:00          00:05:00       00:05:00
00:05:00          00:04:00       00:05:00
00:05:00          00:02:00       00:04:00  
00:03:00          00:02:00       00:03:00
00:02:00          00:02:00       00:04:00 

我尝试使用（d ['TimeWeek']-df ['TimeWeek']。shift（）。fillna（0）抛出错误：

TypeError: unsupported operand type(s) for -: 'str' and 'str'

可能是因为该列中包含：。我该如何解决呢？

Probably because of the presence of ':' in the column. How do I resolve this?

推荐答案

看起来好像抛出了错误，因为数据是字符串形式而不是字符串形式时间戳记。首先将它们转换为时间戳：

It looks like the error is thrown because the data is in the form of a string instead of a timestamp. First convert them to timestamps:

df2 = df.apply(lambda x: [pd.Timestamp(ts) for ts in x])

默认情况下，它们将包含今天的日期，但这与您的时间差不重要（希望您不必担心跨日期的23:55和00:05之间的差异）。

They will contain today's date by default, but this shouldn't matter once you difference the time (hopefully you don't have to worry about differencing 23:55 and 00:05 across dates).

一旦转换，只需更改DataFrame：

Once converted, simply difference the DataFrame:

>>> df2 - df2.shift()
   TimeWeek  TimeSat  TimeHoli
0       NaT      NaT       NaT
1  00:05:00 00:05:00  00:05:00
2  00:05:00 00:04:00  00:05:00
3  00:05:00 00:02:00  00:04:00
4  00:03:00 00:02:00  00:03:00
5  00:42:00 00:02:00  00:04:00

根据您的需要，您可以只接受第1行以上（忽略NaT）：

Depending on your needs, you can just take rows 1+ (ignoring the NaTs):

(df2 - df2.shift()).iloc[1:, :]

，也可以用零填充NaT：

or you can fill the NaTs with zeros:

(df2 - df2.shift()).fillna(0)

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