如何在熊猫中的每个组中按日期时间升序应用排序

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'contest_id'到大对每个比赛中进入比赛的每个用户进行排序。

我尝试过先根据contest_id和user handle对数据进行分组，然后在将datetime列转换为“ to_datetime”后，尝试使用sort_values对日期进行升序排序

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 

        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

我终于可以复制和修复了。

重现步骤

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')

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

并提出：

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

可能的修复：

1. 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

2. 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。