首页 > 解决方案 > Python - 可能的循环函数来跟踪一个人的整个时间的运动并将其与其他人分组?

问题描述

我的问题是,我想全程跟踪 ID,查看他们接下来要去的地方,并将他们与其他人分组为他们的第一个位置点。我目前正在使用 excel 按日期和 ID 进行排序。按日期排序时,我知道每个人第一次访问某个地点时去了哪里。如果我随后删除了这些 ID 的第一个实例,我将离开它们的下一个位置。然后我删除这些实例等等。

这是一个示例数据集:

ID  Location    Date
76  School      4/12/2018
111 Post Office 4/15/2018
112 School      4/10/2018
324 School      2/10/2018
22  Library     4/12/2018
19  Library     4/13/2028
17  Post Office 5/11/2018
76  Library     4/25/2018
19  Library     4/27/2019
112 School      3/23/2018
76  Post Office 4/27/2018
113 Ice Cream   5/23/2018
19  School      7/23/2019
112 Library     3/23/2018
76  Ice Cream   6/4/2019
112 Fountain    6/10/2019

这是预期的输出:

ID  Location    Date       Group
76  School      4/12/2018  1
111 Post Office 4/15/2018  1
112 School      4/10/2018  2
324 School      2/10/2018  1
22  Library     4/12/2018  1
19  Library     4/13/2028  1 
17  Post Office 5/11/2018  1
76  Library     4/25/2018  2
19  Library     4/27/2019  2
112 School      3/23/2018  1
76  Post Office 4/27/2018  3
113 Ice Cream   5/23/2018  1
19  School      7/23/2019  1
112 Library     3/23/2018  1
76  Ice Cream   6/4/2019   4
112 Fountain    6/10/2019  3

输出应该有一个新列,其中按 ID 的第一个位置(按日期)对 ID 进行分组,然后第二组应该是这些人接下来旅行的地方,依此类推。

任何帮助,将不胜感激。我知道如何将文件加载到 python 等中,但在我的一生中,我在为上述创建函数时遇到了难以置信的麻烦。再次感谢您的帮助!

标签: pythonpandasnumpy

解决方案


假设我们有你提到的 CSV 数据集(去掉第一行):

76  School      4/12/2018
111 Post Office 4/15/2018
112 School      4/10/2018
324 School      2/10/2018
22  Library     4/12/2018
19  Library     4/13/2028
17  Post Office 5/11/2018
76  Library     4/25/2018
19  Library     4/27/2019
112 School      3/23/2018
76  Post Office 4/27/2018
113 Ice Cream   5/23/2018
19  School      7/23/2019
112 Library     3/23/2018
76  Ice Cream   6/4/2019
112 Fountain    6/10/2019

然后,我们可以使用自定义 sort() 以您想要的方式对数据进行排序:

import csv
import datetime

l = []

with open('stack.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        l.append(row)


l.sort(key = lambda x: (int(x[0]), datetime.datetime.strptime(x[2], '%m/%d/%Y')))
[print(i) for i in l]

这将为您提供以下输出(按 ID 和日期排序):

['17', 'PO', '05/11/2018']
['19', 'L', '04/27/2019']
['19', 'S', '07/23/2019']
['19', 'L', '04/13/2028']
['22', 'L', '04/12/2018']
['76', 'S', '04/12/2018']
['76', 'L', '04/25/2018']
['76', 'IC', '06/04/2019']
['76', 'PO', '04/27/2020']
['111', 'PO', '04/15/2018']
['112', 'S', '02/23/2018']
['112', 'L', '03/23/2018']
['112', 'S', '04/10/2018']
['112', 'F', '06/10/2019']
['113', 'IC', '05/23/2018']
['324', 'S', '02/10/2018']

可以使用 for 循环向此输出添加组:

f_id = l[0][0]
group = 1
for i in l:
    if f_id != i[0]:
        group = 1
        f_id = i[0]
    i.append(group)
    group+=1

这将为您提供输出:

['17', 'PO', '05/11/2018', 1]
['19', 'L', '04/27/2019', 1]
['19', 'S', '07/23/2019', 2]
['19', 'L', '04/13/2028', 3]
['22', 'L', '04/12/2018', 1]
['76', 'S', '04/12/2018', 1]
['76', 'L', '04/25/2018', 2]
['76', 'IC', '06/04/2019', 3]
['76', 'PO', '04/27/2020', 4]
['111', 'PO', '04/15/2018', 1]
['112', 'S', '02/23/2018', 1]
['112', 'L', '03/23/2018', 2]
['112', 'S', '04/10/2018', 3]
['112', 'F', '06/10/2019', 4]
['113', 'IC', '05/23/2018', 1]
['324', 'S', '02/10/2018', 1]

然后,您可以将此列表写回带有标题的 CSV 文件


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