如何从填充有datetime.time值的系列中提取小时，分钟和秒 [英] How to extract hour, minute and second from Series filled with datetime.time values

问题描述

数据:

0    09:30:38
1    13:40:27
2    18:05:24
3    04:58:08
4    09:00:09

基本上，我想将其分为三列[小时，分钟，秒]

Essentially what I'd like to do is split this into three columns [hour, minute, second]

我尝试了以下代码，但似乎都无法正常工作:

I've tried the following code but none seem to be working:

train_sample.time.hour
AttributeError: 'Series' object has no attribute 'hour'

train_sample.time.dt.hour
AttributeError: Can only use .dt accessor with datetimelike values 

pd.DatetimeIndex(train_sample.time).hour
TypeError: <class 'datetime.time'> is not convertible to datetime

这似乎很简单，但我无法弄清楚.任何帮助将非常感激.

This seems so simple but I can't figure it out. Any help would be much appreciated.

推荐答案

使用列表理解和time s的提取属性:

Use list comprehension with extract attributes of times:

import datetime as datetime

df = pd.DataFrame({'time': [datetime.time(9, 30, 38), 
                            datetime.time(13, 40, 27), 
                            datetime.time(18, 5, 24),
                            datetime.time(4, 58, 8), 
                            datetime.time(9, 0, 9)]})

print (df)
       time
0  09:30:38
1  13:40:27
2  18:05:24
3  04:58:08
4  09:00:09

df[['h','m','s']] = pd.DataFrame([(x.hour, x.minute, x.second) for x in df['time']])

或转换为string s，拆分并转换为int:

Or convert to strings, split and convert to int:

df[['h','m','s']] = df['time'].astype(str).str.split(':', expand=True).astype(int)

print (df)
       time   h   m   s
0  09:30:38   9  30  38
1  13:40:27  13  40  27
2  18:05:24  18   5  24
3  04:58:08   4  58   8
4  09:00:09   9   0   9

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