# numpy.ma.masked_array.compress

`masked_array.``compress`(condition, axis=None, out=None)

  Return a where condition is `True`.

  If condition is a `MaskedArray`, missing values are considered as `False`.

  Parameters: | condition : var Boolean 1-d array selecting which entries to return. If len(condition) is less than the size of a along the axis, then output is truncated to length of condition array. axis : {None, int}, optional Axis along which the operation must be performed. out : {None, ndarray}, optional Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary.
  Returns: | result : MaskedArray A `MaskedArray` object.

  Notes

  Please note the difference with `compressed` ! The output of `compress` has a mask, the output of `compressed` does not.

  Examples

      >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
      >>> print(x)
      [[1 -- 3]
       [-- 5 --]
       [7 -- 9]]
      >>> x.compress([1, 0, 1])
      masked_array(data = [1 3],
            mask = [False False],
            fill_value=999999)

      >>> x.compress([1, 0, 1], axis=1)
      masked_array(data =
       [[1 3]
       [-- --]
       [7 9]],
            mask =
       [[False False]
       [ True  True]
       [False False]],
            fill_value=999999)