Pandas：替换字符串中的值

Question

我有数据框，我尝试从其他 df 替换它

我用：

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

但我得到一个错误：

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

我应该改变什么？ search_term 在哪里

729948                               None  
729949                               None  
729950                               None  
729951  пансионат джемете отдых 2016 цены  
729952                               None  
729953                               None  
729954                               купить телефон  
729955                               None  
729956                               вк  
729957                               None  
729958                               яндекс  

而rep_term 看起来像

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

Answer 1

DataFramerep_term 列 search_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_term 中的1 值，您在code_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

所以首先通过duplicated 识别重复值的行：

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

然后您可以通过 drop_duplicates 保留最后一个或第一个值来删除重复性

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