["python","numpy","statsmodels","standard-deviation","weighted"]
Weighted standard deviation in NumPy

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