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# numpy.ma.sum

ma.sum(self, axis=None, dtype=None, out=None, keepdims=<no value>)

  Return the sum of the array elements over the given axis.

  Masked elements are set to 0 internally.

  Refer to `numpy.sum` for full documentation.

  See also

  `numpy.ndarray.sum`

    corresponding function for ndarrays

  `numpy.sum`

    equivalent function

  Examples

      >>> import numpy as np
      >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
      >>> x
      masked_array(
        data=[[1, --, 3],
              [--, 5, --],
              [7, --, 9]],
        mask=[[False,  True, False],
              [ True, False,  True],
              [False,  True, False]],
        fill_value=999999)
      >>> x.sum()
      25
      >>> x.sum(axis=1)
      masked_array(data=[4, 5, 16],
                   mask=[False, False, False],
             fill_value=999999)
      >>> x.sum(axis=0)
      masked_array(data=[8, 5, 12],
                   mask=[False, False, False],
             fill_value=999999)
      >>> print(type(x.sum(axis=0, dtype=np.int64)[0]))
      <class 'numpy.int64'>