numpy.ma.compress_rowcols#

ma.compress_rowcols(x, axis=None)[source]#

Suppress the rows and/or columns of a 2-D array that contain masked values.

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.

Parameters:
xarray_like, MaskedArray

The array to operate on. If not a MaskedArray instance (or if no array elements are masked), x is interpreted as a MaskedArray with mask set to nomask. Must be a 2D array.

axisint, optional

Axis along which to perform the operation. Default is None.

Returns:
compressed_arrayndarray

The compressed array.

Examples

>>> import numpy as np
>>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
...                                                   [1, 0, 0],
...                                                   [0, 0, 0]])
>>> x
masked_array(
  data=[[--, 1, 2],
        [--, 4, 5],
        [6, 7, 8]],
  mask=[[ True, False, False],
        [ True, False, False],
        [False, False, False]],
  fill_value=999999)

>>> np.ma.compress_rowcols(x)
array([[7, 8]])
>>> np.ma.compress_rowcols(x, 0)
array([[6, 7, 8]])
>>> np.ma.compress_rowcols(x, 1)
array([[1, 2],
       [4, 5],
       [7, 8]])
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