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:
Python3
# 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:
Python3
# 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]]