Numpy MaskedArray.compressed() function - Python

numpy.ma.compress_rowcols() function in Python

Last Updated : 12 Nov, 2020

numpy.ma.compress_rowcols() function suppresses rows and columns that contain masked values in a 2-D array.
The suppression behavior is selected with the axis parameter:

If axis is None, both rows and columns are suppressed.
If axis is 0, only rows are suppressed.
If axis is 1 or -1, only columns are suppressed.

Syntax : numpy.ma.compress_rowcols(arr, axis = None)

Parameters :
arr : [array_like, MaskedArray] This parameter holds the array to operate on.The array must be a 2D array. If no array elements are masked, arr is interpreted as a MaskedArray with mask set to nomask.
axis : [int, optional] Axis along which to perform the operation. Default is None.

Return : Return the compressed array.

Code #1:

Python3

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

# importing numpy as geek
import numpy as geek

arr = geek.ma.array(geek.arange(6).reshape(2, 3),
                    mask=[[1, 0, 0], [0, 0, 0]])

gfg = geek.ma.compress_rowcols(arr)

print(gfg)

Output:

[[4 5]]

Code #2:

Python3

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

# importing numpy as geek
import numpy as geek

arr = geek.ma.array(geek.arange(6).reshape(2, 3),
                    mask=[[1, 0, 0], [0, 0, 0]])

gfg = geek.ma.compress_rowcols(arr, 1)

print(gfg)

Output:

[[1 2]
 [4 5]]

Numpy MaskedArray.compressed() function - Python

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