熊猫:用空白组代替重复的值

Question

我得到了带有列的dataframe和一组重复值。我想要的是在这样的专栏中只保留第一项。

我尝试过df = df.groupby(['author', 'key'])，但不知道如何正确地获取所有行。使用df.first()，将只打印第一行。

import pandas as pd

lst = [
['juli', 'JIRA-1', 'assignee'],
['juli', 'JIRA-1', 'assignee'],
['nick', 'JIRA-1', 'timespent'], 
['nick', 'JIRA-3', 'status'], 
['nick', 'JIRA-3', 'assignee'],
['tom', 'JIRA-1', 'comment'], 
['tom', 'JIRA-1', 'assignee'], 
['tom', 'JIRA-2', 'status']] 

df = pd.DataFrame(lst, columns =['author', 'key', 'field']) 
#df = df.sort_values(by=['author', 'key'])

>>> df
  author     key      field
0   juli  JIRA-1   assignee
1   juli  JIRA-1   assignee
2   nick  JIRA-1  timespent
3   nick  JIRA-3     status
4   nick  JIRA-3   assignee
5    tom  JIRA-1    comment
6    tom  JIRA-1   assignee
7    tom  JIRA-2     status

我得到的是：

>>> df.groupby(['author', 'key']).first()
                   field
author key
juli   JIRA-1   assignee
nick   JIRA-1  timespent
       JIRA-3     status
tom    JIRA-1    comment
       JIRA-2     status

我想要的：

juli   JIRA-1   assignee
                assignee
nick   JIRA-1  timespent
       JIRA-3     status
                assignee
tom    JIRA-1    comment
                assignee
       JIRA-2     status

Answer 1

看起来，您需要df.duplicated()来查找重复项，需要df.loc[]来分配空白：

df.loc[df.duplicated(['author','key']),['author','key']]=''
print(df)

  author     key      field
0   juli  JIRA-1   assignee
1                  assignee
2   nick  JIRA-1  timespent
3   nick  JIRA-3     status
4                  assignee
5    tom  JIRA-1    comment
6                  assignee
7    tom  JIRA-2     status