Pandas regex filtering

In [36]:

    

import pandas as pd
import re


    

In [37]:

    

cols = ['PAY_0',
 'PAY_2',
 'PAY_3',
 'PAY_4',
 'PAY_5',
 'PAY_6',
 'BILL_AMT1',
 'BILL_AMT2',
 'BILL_AMT3',
 'BILL_AMT4',
 'BILL_AMT5',
 'BILL_AMT6',
 'PAY_AMT1',
 'PAY_AMT2',
 'PAY_AMT3',
 'PAY_AMT4',
 'PAY_AMT5',
 'PAY_AMT6']


    

In [38]:

    

# Dummy dataframe for testing regex
df = pd.DataFrame({col: [1,2,3] for col in cols})


    

In [39]:

    

regex_string = "^PAY_[0-9]+$"


    

In [40]:

    

df.filter(regex=regex_string)


    

    
Out[40]:







  

    

      

      
PAY_0
      
PAY_2
      
PAY_3
      
PAY_4
      
PAY_5
      
PAY_6
    
  
  

    

      
0
      
1
      
1
      
1
      
1
      
1
      
1
    
    

      
1
      
2
      
2
      
2
      
2
      
2
      
2
    
    

      
2
      
3
      
3
      
3
      
3
      
3
      
3
    
  

In [43]:

    

regex = re.compile(regex_string)
# This gives you back an iterable
columns_of_interest = filter(regex.match, df.columns)
type(columns_of_interest)


    

    
Out[43]:





filter

In [42]:

    

columns_of_interest_list = list(columns_of_interest)
columns_of_interest_list


    

    
Out[42]:





['PAY_0', 'PAY_2', 'PAY_3', 'PAY_4', 'PAY_5', 'PAY_6']