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# numpy.ma.compress_rowcols

`numpy.ma.``compress_rowcols`(x, axis=None)

  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: | x : array_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. axis : int, optional Axis along which to perform the operation. Default is None.
  Returns: | compressed_array : ndarray The compressed array.

  Examples

      >>> 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]])