def mask_cols(a, axis=None):
return mask_rowcols(a, <NUM_LIT:1>)<EOL>
Mask columns of a 2D array that contain masked values.

This function is a shortcut to ``mask_rowcols`` with `axis` equal to 1.

See Also
--------
mask_rowcols : Mask rows and/or columns of a 2D array.
masked_where : Mask where a condition is met.

Examples
--------
>>> import numpy.ma as ma
>>> a = np.zeros((3, 3), dtype=np.int)
>>> a[1, 1] = 1
>>> a
array([[0, 0, 0],
       [0, 1, 0],
       [0, 0, 0]])
>>> a = ma.masked_equal(a, 1)
>>> a
masked_array(data =
 [[0 0 0]
 [0 -- 0]
 [0 0 0]],
      mask =
 [[False False False]
 [False  True False]
 [False False False]],
      fill_value=999999)
>>> ma.mask_cols(a)
masked_array(data =
 [[0 -- 0]
 [0 -- 0]
 [0 -- 0]],
      mask =
 [[False  True False]
 [False  True False]
 [False  True False]],
      fill_value=999999)