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Regex 在数据框中添加“id”_Regex_Pandas_Numpy - Fatal编程技术网

Regex 在数据框中添加“id”

Regex 在数据框中添加“id”,regex,pandas,numpy,Regex,Pandas,Numpy,我有一个数据框,文档ID是唯一的ID,它将包含WORD列中的多个单词。我需要为文档中的每个单词添加ID 我需要补充一点 DOCUMENT_ID WORD COUNT 0 262056708396949504 4 1 262056708396949504 DVD 1 2 262056708396949504 Girls 1 3 262056708396949504 Gone 1 4 262056708396

我有一个数据框,文档ID是唯一的ID,它将包含WORD列中的多个单词。我需要为文档中的每个单词添加ID

我需要补充一点

    DOCUMENT_ID         WORD    COUNT
0   262056708396949504          4
1   262056708396949504  DVD     1
2   262056708396949504  Girls   1
3   262056708396949504  Gone    1
4   262056708396949504  Gras    1
5   262056708396949504  Hurricane   1
6   262056708396949504  Katrina 1
7   262056708396949504  Mardi   1
8   262056708396949504  Wild    1
10  262056708396949504  donated 1
11  262056708396949504  generated   1
13  262056708396949504  revenues    1
15  262056708396949504  themed  1
17  262056708396949504  torwhore    1
18  262056708396949504  victims 1
20  262167541718319104      18
21  262167541718319104  CCUFoodMan  1
22  262167541718319104  CCUinvolved 1
23  262167541718319104  Congrats    1
24  262167541718319104  Having  1
25  262167541718319104  K   1
29  262167541718319104  blast   1
30  262167541718319104  blasty  1
31  262167541718319104  carebrighton    1
32  262167541718319104  hurricane   1
34  262167541718319104  started 1
37  262197573421502464      21
我的预期结果:

    DOCUMENT_ID         WORD     COUNT WORD_ID
0   262056708396949504          4       1 
1   262056708396949504  DVD     1       2
2   262056708396949504  Girls   1       3
3   262056708396949504  Gone    1
4   262056708396949504  Gras    1
.........
20  262167541718319104            18    1
21  262167541718319104  CCUFoodMan  1  2
22  262167541718319104  CCUinvolved 1  3
我也添加了空单元格,但可以忽略

答案

df['WORD\u ID']=df.groupby['DOCUMENT\u ID'].cumcount+1

解释

让我们构建一个数据框架。 作为pd进口熊猫

df

鉴于您的单词嵌套在唯一的文档ID中,我们需要一个分组操作。 df['WORD\u ID']=df.groupby['DOCUMENT\u ID'].cumcount+1

输出:

          DOCUMENT_ID   WORD  WORD_ID
0  262056708396949504    DVD        1
1  262056708396949504  Girls        2
2  262056708396949504   Gras        3
3  262056708396949504   Gone        4
4  262167541718319104    DVD        1
5  262167541718319104  Girls        2
6  262167541718319104   Gone        3
          DOCUMENT_ID   WORD
0  262056708396949504    DVD
1  262056708396949504  Girls
2  262056708396949504   Gras
3  262056708396949504   Gone
4  262167541718319104    DVD
5  262167541718319104  Girls
6  262167541718319104   Gone
          DOCUMENT_ID   WORD  WORD_ID
0  262056708396949504    DVD        1
1  262056708396949504  Girls        2
2  262056708396949504   Gras        3
3  262056708396949504   Gone        4
4  262167541718319104    DVD        1
5  262167541718319104  Girls        2
6  262167541718319104   Gone        3