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# numpy.ma.masked_array.product

`masked_array.``product`(axis=None, dtype=None, out=None)

  Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation.

  Parameters : | axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If `dtype` has the value `None` and the type of a is an integer type of precision less than the default platform integer, then the default platform integer precision is used. Otherwise, the dtype is the same as that of a. out : {None, array}, 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 : | product_along_axis : {array, scalar}, see dtype parameter above. Returns an array whose shape is the same as a with the specified axis removed. Returns a 0d array when a is 1d or axis=None. Returns a reference to the specified output array if specified.

  See also

  `prod`
    equivalent function

  Notes

  Arithmetic is modular when using integer types, and no error is raised on overflow.

  Examples

      >>> np.prod([1.,2.])
      2.0
      >>> np.prod([1.,2.], dtype=np.int32)
      2
      >>> np.prod([[1.,2.],[3.,4.]])
      24.0
      >>> np.prod([[1.,2.],[3.,4.]], axis=1)
      array([  2.,  12.])

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