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MaskedArray.mean(axis=None, dtype=None, out=None)[source] -
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.meanfor the full documentation.Parameters: a : array_like
Array containing numbers whose mean is desired. If
ais 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
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numpy.ma.mean - Equivalent function.
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numpy.mean - Equivalent function on non-masked arrays.
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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 -
MaskedArray.mean()
2017-01-10 18:10:12
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