[英]Pandas dataframe combine two columns to get datetime column
給定下面的數據幀,其中uptime
是十億分之一秒,如何將date_is
列與uptime
結合起來以形成類型為datetime對象的新列。
date_is uptime
0 14/05/2016 10:54:33 11537640270059
1 14/05/2016 10:54:33 11537650128140
2 14/05/2016 10:54:33 11537659894659
3 14/05/2016 10:54:33 11537679549779
4 14/05/2016 10:54:33 11537699204899
使用to_datetime
+ to_timedelta
:
df['new'] = pd.to_datetime(df['date_is']) + pd.to_timedelta(df['uptime'])
print (df)
date_is uptime new
0 14/05/2016 10:54:33 11537640270059 2016-05-14 14:06:50.640270059
1 14/05/2016 10:54:33 11537650128140 2016-05-14 14:06:50.650128140
2 14/05/2016 10:54:33 11537659894659 2016-05-14 14:06:50.659894659
3 14/05/2016 10:54:33 11537679549779 2016-05-14 14:06:50.679549779
4 14/05/2016 10:54:33 11537699204899 2016-05-14 14:06:50.699204899
也可以將轉換后的列分配回去:
df['date_is'] = pd.to_datetime(df['date_is'])
df['uptime'] = pd.to_timedelta(df['uptime'])
df['new'] = df['date_is'] + df['uptime']
print (df)
date_is uptime new
0 2016-05-14 10:54:33 03:12:17.640270 2016-05-14 14:06:50.640270059
1 2016-05-14 10:54:33 03:12:17.650128 2016-05-14 14:06:50.650128140
2 2016-05-14 10:54:33 03:12:17.659894 2016-05-14 14:06:50.659894659
3 2016-05-14 10:54:33 03:12:17.679549 2016-05-14 14:06:50.679549779
4 2016-05-14 10:54:33 03:12:17.699204 2016-05-14 14:06:50.699204899
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.