如何将 datetime.time() 对象转换为 datetime.datetime 对象 pandas [英] how to convert a datetime.time() object to datetime.datetime object pandas

问题描述

import pandas as pd
import datetime
df = pd.DataFrame([{'st':datetime.datetime.strptime('21:00:00','%H:%M:%S').time(),'et':datetime.datetime.strptime('22:00:00','%H:%M:%S').time()}, {'st':datetime.datetime.strptime('1:00:00','%H:%M:%S').time(),'et':datetime.datetime.strptime('3:00:00','%H:%M:%S').time()}])


Out[183]: df
         et        st
0  22:00:00  21:00:00
1  03:00:00  01:00:00

我希望能够将上述数据框转换为具有 datetime.datetime 对象的新字段和另外两个额外的列，例如这里有任何虚拟日期并使用它们各自的时间行:

I would like to be able to convert the above dataframe with new fields having datetime.datetime objects with two other extra columns such as here having any dummy date in it and using the time from their respective rows:

      et        st      sdate_time                edate_time
0  22:00:00  21:00:00   2018-01-01 21:00:00      2018-01-01 22:00:00  
1  03:00:00  01:00:00   2018-01-01 1:00:00       2018-01-01 3:00:00

我尝试过的方法是使用 apply 方法

The approach I have tried is using apply method

df['et'].apply(lambda et: pd.datetime.combine(datetime.datetime.strptime('2018-01-01', '%Y-%m-%d').date(),et))

但事实证明数据帧可能非常庞大，我想在没有 apply 方法的情况下对上述操作进行矢量化.

but turns out that the dataframe could be really huge and I would like to vectorize the above operation without the apply method .

推荐答案

试试这个

date = str(datetime.datetime.strptime('2018-01-01', '%Y-%m-%d').date())

df['edate_time'] = pd.to_datetime(date + " " + df.et.astype(str))

       et          st            edate_time
0   22:00:00    21:00:00    2018-01-01 22:00:00
1   03:00:00    01:00:00    2018-01-01 03:00:00

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