numpy.ma.mask_rows() function | Python
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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