在 pandas 数据框中将两个时间列加在一起? [英] Adding two time columns together in pandas dataframe?

问题描述

我有以下数据:

 time_begin  DRTN_IN_SCND
 16:22:16           439
 16:29:37            53
 16:30:33            85

我想创建一个新列，其中添加time_begin和DRTN_IN_SCND(以秒为单位的持续时间)以创建新时间.

I would like to make a new column that adds time_begin and DRTN_IN_SCND (the duration in seconds) to create a new time.

我尝试过:

df['new_time'] = df['time_begin'].apply(lambda x: (dt.datetime.combine(dt.datetime(1,1,1), x,) + dt.timedelta(seconds=df.DRTN_IN_SCND)).time())

如果dt.timedelta(seconds = 3)有效，但是当我更改为dt.timedelta(seconds = df.DRTN_IN_SCND)时不起作用.我收到以下错误.

This works if dt.timedelta(seconds=3) but does not work when I change to dt.timedelta(seconds=df.DRTN_IN_SCND). I get the following error.

TypeError: unsupported type for timedelta seconds component: Series

有人知道如何解决此问题或以其他方式完成我要尝试的工作吗?谢谢！

Does anyone know how to fix this or of another way to accomplish what I'm trying to do? Thanks!

推荐答案

如果要对列进行正确的计算，则必须将DRTN_IN_SCND和time_begin转换为时间增量，pandas具有 to_timedelta 十分方便:

You'll have to convert the DRTN_IN_SCND and time_begin to time deltas if you want to do properly calculations on the columns, pandas has to_timedelta which is pretty handy:

df['DRTN_IN_SCND'] = pd.to_timedelta(df['DRTN_IN_SCND'], unit='s')
df['time_begin'] = pd.to_timedelta(df['time_begin'])
df['new_time'] = df['time_begin'] + df['DRTN_IN_SCND']

这将为您提供新的列new_time:

   time_begin  DRTN_IN_SCND  new_time
0    16:22:16      00:07:19  16:29:35
1    16:29:37      00:00:53  16:30:30
2    16:30:33      00:01:25  16:31:58

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