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# numpy.ma.mask_rows

`numpy.ma.``mask_rows`(a, axis=None)

  Mask rows of a 2D array that contain masked values.

  This function is a shortcut to `mask_rowcols` with axis equal to 0.

  See also

  `mask_rowcols`
    Mask rows and/or columns of a 2D array.
  `masked_where`
    Mask where a condition is met.

  Examples

      >>> import numpy.ma as ma
      >>> a = np.zeros((3, 3), dtype=np.int)
      >>> a[1, 1] = 1
      >>> a
      array([[0, 0, 0],
             [0, 1, 0],
             [0, 0, 0]])
      >>> a = ma.masked_equal(a, 1)
      >>> a
      masked_array(data =
       [[0 0 0]
       [0 -- 0]
       [0 0 0]],
            mask =
       [[False False False]
       [False  True False]
       [False False False]],
            fill_value=999999)
      >>> ma.mask_rows(a)
      masked_array(data =
       [[0 0 0]
       [-- -- --]
       [0 0 0]],
            mask =
       [[False False False]
       [ True  True  True]
       [False False False]],
            fill_value=999999)