转换数据框以显示第一，第二和第三个更改

发布于 2025-01-30 11:14:45 字数 1440 浏览 4 评论 0原文

我有一个与此类似的数据框架：

import pandas as pd
records_A = pd.DataFrame({'id': [1001,1001,1001,1001,1002,1002,1002,1003,1003,1003,1004,1005,1006,1006,1006,1006,1006], 
'location': ['NJ','OH','OH','OH','HI','AK','HI','NC','NJ','NJ','PA','UT','AZ','AZ','AZ','AZ','AZ'],
                     'date': ['1/1','4/1','6/1','7/11','1/1','4/1','6/1','1/1','4/1','6/1','1/1','1/1','1/1','2/2','7/3','9/9','12/10']})

我很想将其转换为每个ID的一行，列显示了第一个，第二和第三位置，以及这些位置的开始日期（如果存在）。奖励积分如果代码可以容纳3个以上的位置（即，添加和命名尽可能多的列）。

预期输出将为：

ID	第一位置	1个位置开始日期	2nd位置	2ndlocation开始日期	3rdlocation	3rd位置开始日期
1001	NJ	1/1	OH	4/1	NAN	NAN NAN
1002	HI	1/1	AK	4/1 AK 4/1	HI	HI 6/1
6/1 1003	NC	1/ 1	NJ	4/1	Nan	Nan
1004	PA	1/1	Nan	Nan Nan	Nan	Nan
1005	UT	1/1	Nan	Nan Nan	Nan Nan	Nan
1006	AZ	1/1	Nan	Nan Nan Nan Nan Nan Nan	Nan	Nan

原文

I have a dataframe similar to this:

import pandas as pd
records_A = pd.DataFrame({'id': [1001,1001,1001,1001,1002,1002,1002,1003,1003,1003,1004,1005,1006,1006,1006,1006,1006], 
'location': ['NJ','OH','OH','OH','HI','AK','HI','NC','NJ','NJ','PA','UT','AZ','AZ','AZ','AZ','AZ'],
                     'date': ['1/1','4/1','6/1','7/11','1/1','4/1','6/1','1/1','4/1','6/1','1/1','1/1','1/1','2/2','7/3','9/9','12/10']})

I would love to transform it to see a single row for each id, with columns showing the first, second, and third locations, along with the start date of each of those locations, if they exist. Bonus points if the code could accommodate even more than 3 locations (ie., add and name as many columns as necessary).

Expected output would be: