Skip to content
Related Articles

Related Articles

Improve Article
Save Article
Like Article

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) 

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course

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]]



My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!