numpy.ma.mask_rows() function | Python (original) (raw)

Last Updated : 13 Mar, 2021

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

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

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]]

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