html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/7377#issuecomment-1406463669,https://api.github.com/repos/pydata/xarray/issues/7377,1406463669,IC_kwDOAMm_X85T1O61,56583917,2023-01-27T12:45:10Z,2024-01-03T08:41:41Z,CONTRIBUTOR,"Hi all,
I just created a simple workaround, which might be useful for others:  
https://gist.github.com/maawoo/0b34d371c3cc1960a1589ccaded868c2

It uses the `_nan_quantile` method of xclim and works fine for my applications. Here is a quick comparison using the same example data as in my initial post:
<img width=""592"" alt=""Screenshot 2023-01-27 at 13 41 42"" src=""https://user-images.githubusercontent.com/56583917/215089741-0504c4d7-9b62-4540-b61d-a59bfedf9741.png"">

EDIT: I've updated the code to use numbagg instead of xclim.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,1497031605
https://github.com/pydata/xarray/issues/7377#issuecomment-1362998362,https://api.github.com/repos/pydata/xarray/issues/7377,1362998362,IC_kwDOAMm_X85RPbRa,56583917,2022-12-22T15:52:31Z,2022-12-22T15:52:31Z,CONTRIBUTOR,"Thanks @arongergely!
I have mentioned the numpy issue in my post above (FYI, for anyone looking for it). I was really surprised to see that it's over 2 years old and that this is now the first Xarray issue referencing it. If it's really a ""well known"" issue, I think it should have been somehow mentioned in the Xarray quantiles method.

I have seen the blog post and tried to use the workaround with apply_ufunc and Dask but ran into some problems. I'll revisit that when I have some time and will also check xclim. Seems to be very promising, thanks!

Happy holidays! 🎄 ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1497031605
https://github.com/pydata/xarray/issues/7378#issuecomment-1357341994,https://api.github.com/repos/pydata/xarray/issues/7378,1357341994,IC_kwDOAMm_X85Q52Uq,56583917,2022-12-19T09:21:05Z,2022-12-19T09:21:05Z,CONTRIBUTOR,"Hi @TomNicholas,
thanks for your response! I'd be happy to contribute and will see what I can do once I find some spare time 🙂 ","{""total_count"": 2, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 2, ""rocket"": 0, ""eyes"": 0}",,1497131525
https://github.com/pydata/xarray/issues/7377#issuecomment-1351814726,https://api.github.com/repos/pydata/xarray/issues/7377,1351814726,IC_kwDOAMm_X85Qkw5G,56583917,2022-12-14T17:23:10Z,2022-12-14T17:23:10Z,CONTRIBUTOR,"This issue has an extra layer of evilness because users will also run into this issue when they don't specify the `skipna` parameter and their data is a float dtype, like in my example dummy data: `da.quantile(0.95, dim='time')`

The documentation could be a little bit clearer. The fact that `skipna=True` is the default for float dtypes could easily be overlooked in my opinion:

>  If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes;","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1497031605