pandas 在多列中搜索子字符串 [英] pandas search for substring over multiple columns

问题描述

我有一个这样的df

       c_name  f_name 
0      abc     abc12  
1      xyz     abc1  
2      mnq     mnq2

目标是在两列中找到一个子字符串，并知道它属于哪一列.优先选择c_name，因为如果子字符串在两列中，那么c_name都具有优先权例如:如果在上述数据框中搜索abc，我应该以某种方式获取abc >，第1行abc1表示f_name.

The goal is to find a substring across the two columns an know which column it belongs to. Preference should be to c_name, as in if the substring is in both the columns then c_name gets precedence For eg: if I search for abc in the above dataframe I should somehow get row 0 abc for c_name and row 1 abc1 for f_name.

为了解决这个问题，我从 df[df['c_name'].str.contains('abc', case=False)] 这将给我c_name的结果.现在的问题是如何排除在f_name上执行相同操作的结果所在的行.任何帮助是极大的赞赏！

To solve this I started with df[df['c_name'].str.contains('abc', case=False)] which will give me the results for c_name. The question now is to how to exclude the rows where I already have the results from performing the same operation on f_name. Any help is greatly appreciated!

推荐答案

import pandas as pd
row  =[['abcx','abcy'],
       ['efg','abcz'],
       ['higj','UK']]
df= pd.DataFrame(row)
df.columns = ['c_name', 'f_name']

print df[df['c_name'].str.contains('abc', case=False)]

delta_df =df[~df['c_name'].str.contains('abc', case=False)]
print delta_df[delta_df['f_name'].str.contains('abc', case=False)]

输出

  c_name f_name
0   abcx   abcy
  c_name f_name
1    efg   abcz

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