Drop columns whose name contains a specific string from pandas DataFrame

Question

I have a pandas dataframe with the following column names   Result1  Test1  Result2  Test2  Result3  Test3  etc     I want to drop all the columns whose name contains the word  Test   The numbers of such columns is not static but depends on a previous function   How can I do that

User · Answer

Solution when dropping a list of column names containing regex  I prefer this approach because I m frequently editing the drop list  Uses a negative filter regex for the drop list   drop column names     A   B     C     drop columns regex                 join drop column names        print  Dropping columns        join  c for c in df columns if re search drop columns regex c     df   df filter regex drop columns regex axis 1

User · Answer

the shortest way to do is is     resdf   df filter like  Test  axis 1

User · Answer

import pandas as pd  import numpy as np  array np random random  2 4    df pd DataFrame array  columns   Test1    toto    test2    riri     print df        Test1      toto     test2      riri 0  0 923249  0 572528  0 845464  0 144891 1  0 020438  0 332540  0 144455  0 741412  cols    c for c in df columns if c lower    4      test    df df cols   print df        toto      riri 0  0 572528  0 144891 1  0 332540  0 741412

User · Answer

This can be done neatly in one line with   df   df drop df filter regex  Test   columns  axis 1

User · Answer

Cheaper  Faster  and Idiomatic  str contains  In recent versions of pandas  you can use string methods on the index and columns  Here  str startswith seems like a good fit   To remove all columns starting with a given substring   df columns str startswith  Test     array   True  False  False  False    df loc    df columns str startswith  Test       toto test2 riri 0    x     x    x 1    x     x    x     For case-insensitive matching  you can use regex-based matching with str contains with an SOL anchor   df columns str contains   test   case False    array   True  False   True  False    df loc    df columns str contains   test   case False       toto riri 0    x    x 1    x    x   if mixed-types is a possibility  specify na False as well

User · Answer

Don t drop  Catch the opposite of what you want    df   df filter regex       badword        columns

User · Answer

You can filter out the columns you DO want using  filter   import pandas as pd import numpy as np  data2      test2   1   result1   2     test   5   result34   10   c   20    df   pd DataFrame data2   df      c   result1     result34    test    test2 0   NaN     2 0     NaN     NaN     1 0 1   20 0    NaN     10 0    5 0     NaN   Now filter  df filter like  result  axis 1    Get       result1  result34 0   2 0     NaN 1   NaN     10 0

User · Answer

This method does everything in place  Many of the other answers create copies and are not as efficient   df drop df columns df columns str contains  Test     axis 1  inplace True

User · Answer

Use the DataFrame select method   In  38   df   DataFrame   Test1   randn 10    Test2   randn 10    awesome   randn 10     In  39   df select lambda x  not re search  Test d    x   axis 1  Out 39      awesome 0    1 215 1    1 247 2    0 142 3    0 169 4    0 137 5   -0 971 6    0 736 7    0 214 8    0 111 9   -0 214

User · Answer

Question states  I want to drop all the columns whose name contains the word  quot Test quot    test columns    col for col in df if  Test  in col  df drop columns test columns  inplace True

User · Answer

Here is one way to do this  df   df df columns drop list df filter regex  Test

[python] Drop columns whose name contains a specific string from pandas DataFrame

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