Python 熊猫：替换字符串中的值

我有数据帧，我尝试从其他df替换它

我使用：

df['term_code'] = df.search_term.map(rep_term.set_index('search_term')['code_action'])

但我有一个错误：

File "C:/Users/����� �����������/Desktop/projects/find_time_before_buy/graph (2).py", line 36, in <module>
df['term_code'] = df.search_term.map(rep_term.set_index('search_term')['code_action'])
 File "C:\Python27\lib\site-packages\pandas\core\series.py", line 2101, in map
indexer = arg.index.get_indexer(values)
 File "C:\Python27\lib\site-packages\pandas\indexes\base.py", line 2082, in get_indexer
   raise InvalidIndexError('Reindexing only valid with uniquely'
pandas.indexes.base.InvalidIndexError: Reindexing only valid with uniquely valued Index objects

而且

rep_term

看起来像

search_term code_action
авито   6
вк  9
яндекс  12
мтс 7
связной 8
ситилинк    8

---

DataFrame

rep\u term

列

search\u term

中存在重复项问题

我模拟它：

import pandas as pd

df = pd.DataFrame({'search_term':[1,2,3]})

print (df)
   search_term
0            1
1            2
2            3

对于

search\u term

中的值

1

，在

code\u action

中有

2

值：

rep_term = pd.DataFrame({'search_term':[1,2,1], 'code_action':['ss','dd','gg']})
print (rep_term)
  code_action  search_term
0          ss            1
1          dd            2
2          gg            1


df['term_code'] = df.search_term.map(rep_term.set_index('search_term')['code_action'])
print (df)
#InvalidIndexError: Reindexing only valid with uniquely valued Index objects

因此，首先通过以下方式确定重复VAUE的行：

然后，您可以通过将最后一个或第一个值保留为

---

我应该重命名列吗？当这个列的名称是另一个时，它也返回了这个错误。给我一点时间，我补充一下你们能做些什么来回答这个问题。

rep_term = pd.DataFrame({'search_term':[1,2,1], 'code_action':['ss','dd','gg']})
print (rep_term)
  code_action  search_term
0          ss            1
1          dd            2
2          gg            1


df['term_code'] = df.search_term.map(rep_term.set_index('search_term')['code_action'])
print (df)
#InvalidIndexError: Reindexing only valid with uniquely valued Index objects

print (rep_term[rep_term.duplicated(subset=['search_term'], keep=False)])
  code_action  search_term
0          ss            1
2          gg            1

rep_term1 = rep_term.drop_duplicates(subset=['search_term'], keep='first')
print (rep_term1)
  code_action  search_term
0          ss            1
1          dd            2

rep_term2 = rep_term.drop_duplicates(subset=['search_term'], keep='last')
print (rep_term2)
  code_action  search_term
1          dd            2
2          gg            1