# 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)

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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]]
```

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