[Numpy-discussion] Weighted percentile / quantile

[Joseph Fox-Rabinovitz]

Alex,

At the moment, there does not appear to be anything in numpy. However,
I am working (slowly) on upgrading the C code for partitioning with
arbitrary arrays of real weights. That will get `partition`, `median`,
`percentile` to work with weights, as well as enabling weights for the
automated bin estimators of `histogram`. `mean` already has an
implementation of weights via `average`.

You may be interested in my original post to the mailing list here:
https://mail.scipy.org/pipermail/numpy-discussion/2016-February/075000.html.
Josef P. mentioned in one of his responses that statsmodels has a
weighted quantile computation available as of PR 2707:
https://github.com/statsmodels/statsmodels/pull/2707. That should
effectively serve your purpose.

    -Joe


On Tue, Mar 1, 2016 at 6:03 PM, Alex Rogozhnikov
<alex.rogozhnikov at yandex.ru> wrote:
> Hi,
> I know the topic was already raised a long ago:
> https://mail.scipy.org/pipermail/numpy-discussion/2010-July/051851.html
>
> There are also several questions on SO:
> http://stackoverflow.com/questions/20601872/numpy-or-scipy-to-calculate-weighted-median
> http://stackoverflow.com/questions/13546146/percentile-calculation-with-weighted-data
> http://stackoverflow.com/questions/26102867/python-weighted-median-algorithm-with-pandas
>
> The only working solution with numpy:
> http://stackoverflow.com/questions/21844024/weighted-percentile-using-numpy
> uses sorting.
>
> Are there better options at the moment (numpy/scipy/pandas)?
>
> Cheers,
> Alex.
>
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