How to select all columns, except one column in pandas?

When the columns are not a MultiIndex, df.columns is just an array of column names so you can do:

df.loc[:, df.columns != 'b']          a         c         d0  0.561196  0.013768  0.7728271  0.882641  0.615396  0.0753812  0.368824  0.651378  0.3972033  0.788730  0.568099  0.869127

Don't use ix. It's deprecated. The most readable and idiomatic way of doing this is df.drop():

>>> df          a         b         c         d0  0.175127  0.191051  0.382122  0.8692421  0.414376  0.300502  0.554819  0.4975242  0.142878  0.406830  0.314240  0.0931323  0.337368  0.851783  0.933441  0.949598>>> df.drop('b', axis=1)          a         c         d0  0.175127  0.382122  0.8692421  0.414376  0.554819  0.4975242  0.142878  0.314240  0.0931323  0.337368  0.933441  0.949598

Note that by default, .drop() does not operate inplace; despite the ominous name, df is unharmed by this process. If you want to permanently remove b from df, do df.drop('b', inplace=True).

df.drop() also accepts a list of labels, e.g. df.drop(['a', 'b'], axis=1) will drop column a and b.

df[df.columns.difference(['b'])]Out:           a         c         d0  0.427809  0.459807  0.3338691  0.678031  0.668346  0.6459512  0.996573  0.673730  0.3149113  0.786942  0.719665  0.330833