Pandas dataframeは2つの列を結合してdatetime列を取得します

Question

uptimeのデータフレームがナノ秒である場合、date_is列をuptimeと組み合わせてdatetimeオブジェクト型の新しい列を作成する方法。

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 

Answer 1

使用+ to_timedeltato_datetime：

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 

が可能ですまた、列が戻って割り当てる変換：

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