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/3810#issuecomment-592738965,https://api.github.com/repos/pydata/xarray/issues/3810,592738965,MDEyOklzc3VlQ29tbWVudDU5MjczODk2NQ==,5635139,2020-02-28T21:33:35Z,2020-02-28T21:33:35Z,MEMBER,"Yeah, unfortunately I'm fairly confident about this; have a go with moderately large arrays for `sum` and you'll quickly see the performance cliff ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592721162,https://api.github.com/repos/pydata/xarray/issues/3810,592721162,MDEyOklzc3VlQ29tbWVudDU5MjcyMTE2Mg==,5635139,2020-02-28T20:47:33Z,2020-02-28T20:47:33Z,MEMBER,"Great -- that's cool and a good implementation of `apply_ufunc`. As above, we wouldn't want to replace `rank` with that given the reshaping (we'd need a function that computes over multiple dimensions)

We could use something similar for groupbys though?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592708353,https://api.github.com/repos/pydata/xarray/issues/3810,592708353,MDEyOklzc3VlQ29tbWVudDU5MjcwODM1Mw==,5635139,2020-02-28T20:13:51Z,2020-02-28T20:13:51Z,MEMBER,Could you try running that?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592665711,https://api.github.com/repos/pydata/xarray/issues/3810,592665711,MDEyOklzc3VlQ29tbWVudDU5MjY2NTcxMQ==,5635139,2020-02-28T18:34:44Z,2020-02-28T18:34:44Z,MEMBER,"Yes, we can always reshape as a way of running numerical operations over multiple dimensions. But reshaping can be an expensive operation, so doing it as part of a numerical operation can cause surprises. (if you're interested, try running a sum over multiple dimensions and comparing to a reshape + a sum over the single reshaped dimension). 

Instead, users can do this themselves, giving them context and control.

Reshaping is OK to do in `groupby` though (I think), so adding `rank` to groupby would be one way of accomplishing this.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592645335,https://api.github.com/repos/pydata/xarray/issues/3810,592645335,MDEyOklzc3VlQ29tbWVudDU5MjY0NTMzNQ==,5635139,2020-02-28T17:43:05Z,2020-02-28T17:43:05Z,MEMBER,"This would be great. The underlying numerical library we use, bottleneck, [doesn't support multiple dimensions](https://kwgoodman.github.io/bottleneck-doc/reference.html#bottleneck.rankdata). If there were another option, or someone wanted to write one in numbagg, that would be a welcome addition.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480