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2 rows where author_association = "CONTRIBUTOR", issue = 1076265104 and user = 16700639 sorted by updated_at descending

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  • bzah · 2 ✖

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  • Weighted quantile · 2 ✖

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  • CONTRIBUTOR · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1033607850 https://github.com/pydata/xarray/pull/6059#issuecomment-1033607850 https://api.github.com/repos/pydata/xarray/issues/6059 IC_kwDOAMm_X849m5qq bzah 16700639 2022-02-09T10:30:40Z 2022-02-09T10:40:08Z CONTRIBUTOR

@mathause This PR goes beyond what is currently implemented in numpy. For now, all weighted quantiles PR on numpy are more or less based on "linear" method (method 7) and none have been merged. I plan to work on integrating weights with the other interpolation methods but don't have the time right now. I'll probably pick some ideas from here.

As for the numerics here, everything looks good to me. The only limitations I can see are: - This only handles sampling weights, which is fine I guess. - Some interpolation methods are missing, they can be added later. - ~A nan_weighted_quantile could also be interesting to add~

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  Weighted quantile 1076265104
1021975396 https://github.com/pydata/xarray/pull/6059#issuecomment-1021975396 https://api.github.com/repos/pydata/xarray/issues/6059 IC_kwDOAMm_X8486htk bzah 16700639 2022-01-26T08:32:56Z 2022-02-07T16:57:56Z CONTRIBUTOR

FYI, weighted quantiles topic will be discussed in numpy's triage meeting of today (17:00 UTC). I'm not a maintainer but I'm sure you are welcomed to join in if you are interested. Meeting information: https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg

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  Weighted quantile 1076265104

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