从另一个列更改列中的df [英] Change column in df from column from another

问题描述

我有数据：

                 date                      id 
0     2016-06-17 06:25:05    [e-mail]    
1     2016-06-17 06:25:07    [e-mail]       
2     2016-06-17 06:25:10    [e-mail]         
3     2016-06-17 06:25:11    [e-mail]

其他数据

Other data

Email,UTC shift
[e-mail],5
[e-mail],3
[e-mail],3
[e-mail],2

我需要将 UTC shift 添加到第一个文件 date 到 hours 。
欲望输出：

I need to add UTC shift to first file date to hours. Desire output:

                     date                      id 
0     2016-06-17 11:25:05    [e-mail]    
1     2016-06-17 11:25:07    [e-mail]       
2     2016-06-17 09:25:10    [e-mail]         
3     2016-06-17 09:25:11    [e-mail]

我转换 date 到datetime，但我不知道如何将 UTC转换转换为小时。

I convert date to datetime, but I don't know, how convert UTC shift to hours.

推荐答案

您需要先转换 to_datetime 列日期如果 dtype 不是 datetime ， id 和电子邮件合并 rel =nofollow> code>。然后转换 to_timedelta 列 UTC移位，添加到日期，最后 drop 不必要的列： p>



You need first convert to_datetime column date if dtype is not datetime, merge by columns id and Email. Then convert to_timedelta column UTC shift, add to date and last drop unnecessary columns:

import pandas as pd


df1 = pd.DataFrame({'date': {0: '2016-06-17 06:25:05', 1: '2016-06-17 06:25:07', 2: '2016-06-17 06:25:10', 3: '2016-06-17 06:25:11'}, 
                      'id': {0: '[e-mail]', 1: '[e-mail]', 2: '[e-mail]', 3: '[e-mail]'}})

df2 = pd.DataFrame({'Email': {0: '[e-mail]', 1: '[e-mail]', 2: '[e-mail]', 3: '[e-mail]'}, 
                    'UTC shift': {0: 5, 1: 3, 2: 3, 3: 2}})

print (df1)
                  date                    id
0  2016-06-17 06:25:05  [e-mail]
1  2016-06-17 06:25:07  [e-mail]
2  2016-06-17 06:25:10  [e-mail]
3  2016-06-17 06:25:11  [e-mail]

print (df2)
                          Email  UTC shift
0          [e-mail]          5
1             [e-mail]          3
2          [e-mail]          3
3  [e-mail]          2

df1['date'] = pd.to_datetime(df1.date)

df = pd.merge(df1, df2, left_on='id', right_on='Email')
df['date'] += pd.to_timedelta(df['UTC shift'], unit='H')
df.drop(['Email','UTC shift'], axis=1, inplace=True)
print (df)
                 date                    id
0 2016-06-17 11:25:05  [e-mail]
1 2016-06-17 11:25:07  [e-mail]
2 2016-06-17 09:25:10  [e-mail]
3 2016-06-17 09:25:11  [e-mail]

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