Question

我有一个数据集要根据'user_id'和'contest_id'进行分组，其中，我必须按日期和时间升序对每个比赛中进入比赛的每个用户进行排序订单。

我首先尝试根据contest_id和user handle对数据进行分组，然后在将datetime列转换为`to_datetime'

当我尝试保存代码时，出现错误 '''

      Excel doesn't support timezones in datetimes. Set the tzinfo in the 

       datetime/time object to None or use the 'remove_timezone' Workbook() 

       option

'''


       dftotal.groupby(["contestID", "userHandle"])

       dftotal["registerDateTime"]=pd.to_datetime(dftotal.registerDateTime)

       dftotal["RegistrationDateTime"] = dftotal["registerDateTime"]

       dftotal["submitDateTime"] = pd.to_datetime(dftotal.submitDateTime)

       dftotal["SubmissionDateTime"] = dftotal["submitDateTime"]

       dftotal = dftotal.sort_values(by=['RegistrationDateTime'])

数据是

        contest_id user_id  registration    submission          score 
        1234       abc     2012-01-09       2012-01-09           90
                          21:51:00+00:00   22:51:00+00:00 


        4489      pabc     2013-01-09     2013-01-09             39
                         21:51:00+00:00   22:55:00+00:00 

        1234     tiop      2012-01-09      2012-01-09            100
                        23:51:00+00:00   23:55:00+00:00 

        4489    pabceu    2013-01-09      2013-01-09              39
                        23:20:00+00:00   23:55:00+00:00

预期为

        contest_id user_id   registration     submission             score 
        1234       abc      2012-01-09       2012-01-09              90
                         21:51:00+00:00   22:51:00+00:00 

        1234      tiop    2012-01-09       2012-01-09               100
                        23:51:00+00:00    23:55:00+00:00 

        4489      pabc    2013-01-09      2013-01-09                 39
                        21:51:00+00:00   22:55:00+00:00 

        4489     pabceu   2013-01-09     2013-01-09                  39
                        23:20:00+00:00  23:55:00+00:00

Answer 1

我终于可以复制并修复了。

复制步骤

import pandas as pd
import io

t = '''contest_id  user_id  registration    submission          score 
        1234       abc     2012-01-09 21:51:00+00:00       2012-01-09 22:51:00+00:00           90
        4489      pabc     2013-01-09 21:51:00+00:00     2013-01-09 22:55:00+00:00             39
        1234     tiop      2012-01-09 23:51:00+00:00      2012-01-09 23:55:00+00:00            100
        4489    pabceu    2013-01-09 23:20:00+00:00      2013-01-09 23:55:00+00:00              39'''

dftotal=pd.read_csv(io.StringIO(t), sep=r'\s\s+', engine='python')

print(dftotal.to_string())

dftotal['registration'] = pd.to_datetime(dftotal.registration, utc=True)
dftotal['submission'] = pd.to_datetime(dftotal.submission, utc=True)

print(dftotal.to_string())
dftotal.to_excel('contest_new.xlsx')

哪个显示：

   contest_id user_id               registration                 submission  score
0        1234     abc  2012-01-09 21:51:00+00:00  2012-01-09 22:51:00+00:00     90
1        4489    pabc  2013-01-09 21:51:00+00:00  2013-01-09 22:55:00+00:00     39
2        1234    tiop  2012-01-09 23:51:00+00:00  2012-01-09 23:55:00+00:00    100
3        4489  pabceu  2013-01-09 23:20:00+00:00  2013-01-09 23:55:00+00:00     39
   contest_id user_id              registration                submission  score
0        1234     abc 2012-01-09 21:51:00+00:00 2012-01-09 22:51:00+00:00     90
2        1234    tiop 2012-01-09 23:51:00+00:00 2012-01-09 23:55:00+00:00    100
1        4489    pabc 2013-01-09 21:51:00+00:00 2013-01-09 22:55:00+00:00     39
3        4489  pabceu 2013-01-09 23:20:00+00:00 2013-01-09 23:55:00+00:00     39

并加注：

TypeError：Excel在日期时间中不支持时区。将datetime / time对象中的tzinfo设置为None或使用'remove_timezone'Workbook（）选项

可能的解决方法：

使用openpyxl：

xlsxwriter后端引发此错误。如果已安装openpyxl，则足以要求该引擎：
```
...
dftotal.to_excel('contest_new.xlsx', engine='openpyxl')
```
它会自动删除tz信息并正确写入excel文件

明确删除ts信息：

可以使用tz_localize(None)明确删除时区信息：

...
dftotal['registration'] = pd.to_datetime(dftotal.registration).dt.tz_localize(None)
dftotal['submission'] = pd.to_datetime(dftotal.submission).dt.tz_localize(None)
dftotal = dftotal.sort_values(by=['registration'])
print(dftotal.to_string())

dftotal.to_excel('contest_new.xlsx')

数据框显示为：

   contest_id user_id        registration          submission  score
0        1234     abc 2012-01-09 21:51:00 2012-01-09 22:51:00     90
2        1234    tiop 2012-01-09 23:51:00 2012-01-09 23:55:00    100
1        4489    pabc 2013-01-09 21:51:00 2013-01-09 22:55:00     39
3        4489  pabceu 2013-01-09 23:20:00 2013-01-09 23:55:00     39

，并由默认的xlsxwriter引擎正确写入。

如何在熊猫中的每个组中按日期时间升序应用排序

1 个答案:

复制步骤

可能的解决方法：