numpy.ma.compress_rowcols() function in Python
Last Updated :
12 Nov, 2020
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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:
# 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:
# 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]]