Pandas get all columns without one

Question

In pandas, if I have a dataframe called df, I can get one column with

df.column_one

and, I can get some specific columns with

df[['column_one', 'column_two']]

how I can get all columns without one specific?

Example: if I have a dataframe with n columns col_1, col_2, ... col_n, How I can get all columns without col_n?

There is a little known method that does this: `df[df.columns.difference('col_n')]`. — IanS, May 25 '16 at 15:09

MaxU - stop genocide of UA · Accepted Answer · 2016-05-25T15:23:44.227

10

try this:

df.drop(['col_n'], axis=1)

or

df.loc[:, df.columns != 'col_n']

or

df.loc[:, df.columns - ['col_n']]

or as @IanS posted in the comment:

df[df.columns.difference('col_n')]

or using filter() function in junction with negative look ahead RegEx:

df.filter(regex=r'^((?!col_n).*)$')

edited May 25 '16 at 15:23

answered May 25 '16 at 14:57

1

There is also a little known method that does this: `df[df.columns.difference('col_n')]`. – IanS May 25 '16 at 15:20
1

@IanS, thanks! I've added it to the answer – MaxU - stop genocide of UA May 25 '16 at 15:24

score 0 · Answer 2 · answered May 25 '16 at 14:57

0

You can use df.drop:

df.drop('column_one',axis=1)

answered May 25 '16 at 14:57

Jan van der Vegt

2 Answers2