How to remove multiple columns that end with same text in Pandas?

Question

I\'m trying to remove a group of columns from a dataset. All of the variables to remove end with the text \"prefix\".

I did manage to \"collect\' them into a group

Answer 1

for the sake of completeness:

In [306]: df
Out[306]:
   prefixcol1  col2prefix  col3prefix  colN
0           1           1           1     1
1           2           2           2     2
2           3           3           3     3

In [307]: df.loc[:, ~df.columns.str.contains('prefix$')]
Out[307]:
   prefixcol1  colN
0           1     1
1           2     2
2           3     3

or another variant:

In [388]: df.select(lambda x: re.search(r'prefix$', str(x)) is None, axis=1)
Out[388]:
   prefixcol1  colN
0           1     1
1           2     2
2           3     3

Answer 2

using filter and regex

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

Demo

df = pd.DataFrame(np.random.rand(2, 6),
                  columns=['oneprefix', 'one',
                           'twoprefix', 'two',
                           'threeprefix', 'three'])

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

where:

df

---

Timing

All are about the same

Answer 3

df2 = df.loc[:, ~df.columns.str.endswith('prefix')]

Answer 4

I think you need:

not_prefix_cols= [col for col in df.columns if not 'prefix' in col]
df2[not_prefix_cols]

But better is use:

prefix_cols= [col for col in df.columns if not col.endswith('prefix')]
print (df[prefix_cols])

Sample:

import pandas as pd

df = pd.DataFrame({'prefixone' : pd.Series([1, 2, 3, 4]),
                   'twoprefix' : pd.Series([20, 30, 40, 50]),
                   'two1prefix' : pd.Series([20, 30, 40, 50])})

print (df)
   prefixone  two1prefix  twoprefix
0          1          20         20
1          2          30         30
2          3          40         40
3          4          50         50

prefix_cols= [col for col in df.columns if not col.endswith('prefix')]
print (df[prefix_cols])
   prefixone
0          1
1          2
2          3
3          4

Answer 5

df2 = df.drop([col for col in df.columns if 'prefix' in col],axis=1)