In thisnumpy.ma.mask_cols() function, mask columns of a 2D array that contain masked values. This function is a shortcut to mask_rowcols with axis equal to 1.
Syntax : numpy.ma.mask_cols(arr, axis = None)
Parameters :
arr : [array_like, MaskedArray] The array to mask.
axis : [int, optional] Axis along which to perform the operation. Default is None.Return : [MaskedArray] A modified version of the input array.
Code #1 :
# Python program explaining # numpy.ma.mask_cols() function   # importing numpy as geek  # and numpy.ma module as ma import numpy as geek import numpy.ma as ma   arr = geek.zeros((3, 3), dtype = int) arr[1, 1] = 1   arr = ma.masked_equal(arr, 1)   gfg = ma.mask_cols(arr)   print (gfg) |
Output :
[[0 -- 0] [0 -- 0] [0 -- 0]]
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Code #2 :
# Python program explaining # numpy.ma.mask_cols() function   # importing numpy as geek  # and numpy.ma module as ma import numpy as geek import numpy.ma as ma   arr = geek.zeros((4, 4), dtype = int) arr[2, 2] = 1   arr = ma.masked_equal(arr, 1)   gfg = ma.mask_cols(arr)   print (gfg) |
Output :
[[0 0 -- 0] [0 0 -- 0] [0 0 -- 0] [0 0 -- 0]]
