Search code examples
pythonnumpystatsmodelsstandard-deviationweighted

Weighted standard deviation in NumPy

numpy.average() has a weights option, but numpy.std() does not. Does anyone have suggestions for a workaround?

Solution

  • How about the following short "manual calculation"?

    def weighted_avg_and_std(values, weights):
    """
    Return the weighted average and standard deviation.

    They weights are in effect first normalized so that they 
    sum to 1 (and so they must not all be 0).

    values, weights -- NumPy ndarrays with the same shape.
    """
    average = numpy.average(values, weights=weights)
    # Fast and numerically precise:
    variance = numpy.average((values-average)**2, weights=weights)
    return (average, math.sqrt(variance))