numpy.ma.masked_all() function | Python

numpy.ma.mask_cols() function | Python

Last Updated : 22 Apr, 2020

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 :

Python3

# 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]]

Code #2 :

Python3

# 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]]

numpy.ma.masked_all() function | Python

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