#### Previous topic

numpy.ma.cumprod

#### Next topic

numpy.ma.median

# numpy.ma.mean

`numpy.ma.``mean`(self, axis=None, dtype=None, out=None) = <numpy.ma.core._frommethod instance at 0x424506ac>

  Returns the average of the array elements.

  Masked entries are ignored. The average is taken over the flattened array by default, otherwise over the specified axis. Refer to `numpy.mean` for the full documentation.

  Parameters: | a : array_like Array containing numbers whose mean is desired. If a is not an array, a conversion is attempted. axis : int, optional Axis along which the means are computed. The default is to compute the mean of the flattened array. dtype : dtype, optional Type to use in computing the mean. For integer inputs, the default is float64; for floating point, inputs it is the same as the input dtype. out : 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: | mean : ndarray, see dtype parameter above If out=None, returns a new array containing the mean values, otherwise a reference to the output array is returned.

  See also

  `numpy.ma.mean`
    Equivalent function.
  `numpy.mean`
    Equivalent function on non-masked arrays.
  `numpy.ma.average`
    Weighted average.

  Examples

      >>> a = np.ma.array([1,2,3], mask=[False, False, True])
      >>> a
      masked_array(data = [1 2 --],
                   mask = [False False  True],
             fill_value = 999999)
      >>> a.mean()
      1.5