numpy.ma.compress_cols() function in Python
Last Updated :
12 Nov, 2020
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Prerequisite: numpy
This numpy inbuilt function suppresses whole columns that contain masked values in a 2-D array.
Syntax: numpy.ma.compress_cols(arr)
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.
Return : Returns the compressed array.
Below is the Implementation of the above function.
Example 1:
# importing numpy as geek
import numpy as geek
# defining an array with mask
arr = geek.ma.array(geek.arange(6).reshape(2, 3),
mask=[[1, 0, 0], [0, 0, 0]])
# applying mask to array elements
gfg = geek.ma.compress_cols(arr)
print(gfg)
Output :
[[1 2] [4 5]]
Example 2:
# importing numpy as geek
import numpy as geek
# defining array
arr = geek.ma.array(geek.arange(9).reshape(3, 3), mask=[
[1, 0, 0], [1, 0, 0], [0, 0, 0]])
# applying mask to array elements
gfg = geek.ma.compress_cols(arr)
print(gfg)
Output :
[[1 2] [4 5] [7 8]]
