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]]
