numpy.ma.mask_rows() function | Python

In this numpy.ma.mask_rows() function, mask rows of a 2D array that contain masked values. This function is a shortcut to mask_rowcols with axis equal to 0. 

Syntax : numpy.ma.mask_rows(arr, axis = None) 
Parameters : 
arr : [array_like, MaskedArray] The array to mask. The result is a MaskedArray. 
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_rows() 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_rows(arr)

print (gfg)

Output : 

[[0 0 0 0]
 [0 0 0 0]
 [-- -- -- --]
 [0 0 0 0]]

Code #2 : 

Python3

# Python program explaining
# numpy.ma.mask_rows() function

# importing numpy as geek
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma

arr = geek.zeros((5, 5), dtype = int)
arr[3, 3] = 1

arr = ma.masked_equal(arr, 1)

gfg = ma.mask_rows(arr)

print (gfg)

Output : 

[[0 0 0 0 0]
 [0 0 0 0 0]
 [0 0 0 0 0]
 [-- -- -- -- --]
 [0 0 0 0 0]]